WorldWideScience

Sample records for genome-wide computational prediction

  1. Genome-wide computational prediction and analysis of core promoter elements across plant monocots and dicots.

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    Sunita Kumari

    Full Text Available Transcription initiation, essential to gene expression regulation, involves recruitment of basal transcription factors to the core promoter elements (CPEs. The distribution of currently known CPEs across plant genomes is largely unknown. This is the first large scale genome-wide report on the computational prediction of CPEs across eight plant genomes to help better understand the transcription initiation complex assembly. The distribution of thirteen known CPEs across four monocots (Brachypodium distachyon, Oryza sativa ssp. japonica, Sorghum bicolor, Zea mays and four dicots (Arabidopsis thaliana, Populus trichocarpa, Vitis vinifera, Glycine max reveals the structural organization of the core promoter in relation to the TATA-box as well as with respect to other CPEs. The distribution of known CPE motifs with respect to transcription start site (TSS exhibited positional conservation within monocots and dicots with slight differences across all eight genomes. Further, a more refined subset of annotated genes based on orthologs of the model monocot (O. sativa ssp. japonica and dicot (A. thaliana genomes supported the positional distribution of these thirteen known CPEs. DNA free energy profiles provided evidence that the structural properties of promoter regions are distinctly different from that of the non-regulatory genome sequence. It also showed that monocot core promoters have lower DNA free energy than dicot core promoters. The comparison of monocot and dicot promoter sequences highlights both the similarities and differences in the core promoter architecture irrespective of the species-specific nucleotide bias. This study will be useful for future work related to genome annotation projects and can inspire research efforts aimed to better understand regulatory mechanisms of transcription.

  2. Genome-wide computational prediction and analysis of core promoter elements across plant monocots and dicots

    Science.gov (United States)

    Transcription initiation, essential to gene expression regulation, involves recruitment of basal transcription factors to the core promoter elements (CPEs). The distribution of currently known CPEs across plant genomes is largely unknown. This is the first large scale genome-wide report on the compu...

  3. Computational tools for genome-wide miRNA prediction and study

    KAUST Repository

    Malas, T.B.

    2012-11-02

    MicroRNAs (miRNAs) are single-stranded non-coding RNA susually of 22 nucleotidesin length that play an important post-transcriptional regulation role in many organisms. MicroRNAs bind a seed sequence to the 3-untranslated region (UTR) region of the target messenger RNA (mRNA), inducing degradation or inhibition of translation and resulting in a reduction in the protein level. This regulatory mechanism is central to many biological processes and perturbation could lead to diseases such as cancer. Given the biological importance, of miRNAs, there is a great need to identify and study their targets and functions. However, miRNAs are very difficult to clone in the lab and this has hindered the identification of novel miRNAs. Next-generation sequencing coupled with new computational tools has recently evolved to help researchers efficiently identify large numbers of novel miRNAs. In this review, we describe recent miRNA prediction tools and discuss their priorities, advantages and disadvantages. Malas and Ravasi.

  4. Genome-wide computational function prediction of Arabidopsis thaliana proteins by integration of multiple data sources

    NARCIS (Netherlands)

    Kourmpetis, Y.I.A.; Dijk, van A.D.J.; Ham, van R.C.H.J.; Braak, ter C.J.F.

    2011-01-01

    Although Arabidopsis thaliana is the best studied plant species, the biological role of one third of its proteins is still unknown. We developed a probabilistic protein function prediction method that integrates information from sequences, protein-protein interactions and gene expression. The method

  5. Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes

    Science.gov (United States)

    Oh, Jung Hun; Kerns, Sarah; Ostrer, Harry; Powell, Simon N.; Rosenstein, Barry; Deasy, Joseph O.

    2017-02-01

    The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing complication risk, and furthermore could be used to identify key biological sources of variability. We developed a novel learning algorithm, called pre-conditioned random forest regression (PRFR), to construct polygenic risk models using hundreds of SNPs, thereby capturing genomic features that confer small differential risk. Predictive models were trained and validated on a cohort of 368 prostate cancer patients for two post-radiotherapy clinical endpoints: late rectal bleeding and erectile dysfunction. The proposed method results in better predictive performance compared with existing computational methods. Gene ontology enrichment analysis and protein-protein interaction network analysis are used to identify key biological processes and proteins that were plausible based on other published studies. In conclusion, we confirm that novel machine learning methods can produce large predictive models (hundreds of SNPs), yielding clinically useful risk stratification models, as well as identifying important underlying biological processes in the radiation damage and tissue repair process. The methods are generally applicable to GWAS data and are not specific to radiotherapy endpoints.

  6. Genome-Wide Prediction of C. elegans Genetic Interactions

    OpenAIRE

    Zhong, Weiwei; Sternberg, Paul W.

    2006-01-01

    To obtain a global view of functional interactions among genes in a metazoan genome, we computationally integrated interactome data, gene expression data, phenotype data, and functional annotation data from three model organisms—Saccharomyces cerevisiae, Caenorhabditis elegans, and Drosophila melanogaster—and predicted genome-wide genetic interactions in C. elegans. The resulting genetic interaction network (consisting of 18,183 interactions) provides a framework for system-level understandin...

  7. Effect of reference genome selection on the performance of computational methods for genome-wide protein-protein interaction prediction.

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    Vijaykumar Yogesh Muley

    Full Text Available BACKGROUND: Recent progress in computational methods for predicting physical and functional protein-protein interactions has provided new insights into the complexity of biological processes. Most of these methods assume that functionally interacting proteins are likely to have a shared evolutionary history. This history can be traced out for the protein pairs of a query genome by correlating different evolutionary aspects of their homologs in multiple genomes known as the reference genomes. These methods include phylogenetic profiling, gene neighborhood and co-occurrence of the orthologous protein coding genes in the same cluster or operon. These are collectively known as genomic context methods. On the other hand a method called mirrortree is based on the similarity of phylogenetic trees between two interacting proteins. Comprehensive performance analyses of these methods have been frequently reported in literature. However, very few studies provide insight into the effect of reference genome selection on detection of meaningful protein interactions. METHODS: We analyzed the performance of four methods and their variants to understand the effect of reference genome selection on prediction efficacy. We used six sets of reference genomes, sampled in accordance with phylogenetic diversity and relationship between organisms from 565 bacteria. We used Escherichia coli as a model organism and the gold standard datasets of interacting proteins reported in DIP, EcoCyc and KEGG databases to compare the performance of the prediction methods. CONCLUSIONS: Higher performance for predicting protein-protein interactions was achievable even with 100-150 bacterial genomes out of 565 genomes. Inclusion of archaeal genomes in the reference genome set improves performance. We find that in order to obtain a good performance, it is better to sample few genomes of related genera of prokaryotes from the large number of available genomes. Moreover, such a sampling

  8. Genome-wide prediction of C. elegans genetic interactions.

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    Zhong, Weiwei; Sternberg, Paul W

    2006-03-10

    To obtain a global view of functional interactions among genes in a metazoan genome, we computationally integrated interactome data, gene expression data, phenotype data, and functional annotation data from three model organisms-Saccharomyces cerevisiae, Caenorhabditis elegans, and Drosophila melanogaster-and predicted genome-wide genetic interactions in C. elegans. The resulting genetic interaction network (consisting of 18,183 interactions) provides a framework for system-level understanding of gene functions. We experimentally tested the predicted interactions for two human disease-related genes and identified 14 new modifiers.

  9. Reducing dimensionality for prediction of genome-wide breeding values

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    Woolliams John A

    2009-03-01

    Full Text Available Abstract Partial least square regression (PLSR and principal component regression (PCR are methods designed for situations where the number of predictors is larger than the number of records. The aim was to compare the accuracy of genome-wide breeding values (EBV produced using PLSR and PCR with a Bayesian method, 'BayesB'. Marker densities of 1, 2, 4 and 8 Ne markers/Morgan were evaluated when the effective population size (Ne was 100. The correlation between true breeding value and estimated breeding value increased with density from 0.611 to 0.681 and 0.604 to 0.658 using PLSR and PCR respectively, with an overall advantage to PLSR of 0.016 (s.e = 0.008. Both methods gave a lower accuracy compared to the 'BayesB', for which accuracy increased from 0.690 to 0.860. PLSR and PCR appeared less responsive to increased marker density with the advantage of 'BayesB' increasing by 17% from a marker density of 1 to 8Ne/M. PCR and PLSR showed greater bias than 'BayesB' in predicting breeding values at all densities. Although, the PLSR and PCR were computationally faster and simpler, these advantages do not outweigh the reduction in accuracy, and there is a benefit in obtaining relevant prior information from the distribution of gene effects.

  10. Psoriasis prediction from genome-wide SNP profiles

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    Fang Xiangzhong

    2011-01-01

    Full Text Available Abstract Background With the availability of large-scale genome-wide association study (GWAS data, choosing an optimal set of SNPs for disease susceptibility prediction is a challenging task. This study aimed to use single nucleotide polymorphisms (SNPs to predict psoriasis from searching GWAS data. Methods Totally we had 2,798 samples and 451,724 SNPs. Process for searching a set of SNPs to predict susceptibility for psoriasis consisted of two steps. The first one was to search top 1,000 SNPs with high accuracy for prediction of psoriasis from GWAS dataset. The second one was to search for an optimal SNP subset for predicting psoriasis. The sequential information bottleneck (sIB method was compared with classical linear discriminant analysis(LDA for classification performance. Results The best test harmonic mean of sensitivity and specificity for predicting psoriasis by sIB was 0.674(95% CI: 0.650-0.698, while only 0.520(95% CI: 0.472-0.524 was reported for predicting disease by LDA. Our results indicate that the new classifier sIB performs better than LDA in the study. Conclusions The fact that a small set of SNPs can predict disease status with average accuracy of 68% makes it possible to use SNP data for psoriasis prediction.

  11. Probabilistic protein function prediction from heterogeneous genome-wide data.

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    Naoki Nariai

    Full Text Available Dramatic improvements in high throughput sequencing technologies have led to a staggering growth in the number of predicted genes. However, a large fraction of these newly discovered genes do not have a functional assignment. Fortunately, a variety of novel high-throughput genome-wide functional screening technologies provide important clues that shed light on gene function. The integration of heterogeneous data to predict protein function has been shown to improve the accuracy of automated gene annotation systems. In this paper, we propose and evaluate a probabilistic approach for protein function prediction that integrates protein-protein interaction (PPI data, gene expression data, protein motif information, mutant phenotype data, and protein localization data. First, functional linkage graphs are constructed from PPI data and gene expression data, in which an edge between nodes (proteins represents evidence for functional similarity. The assumption here is that graph neighbors are more likely to share protein function, compared to proteins that are not neighbors. The functional linkage graph model is then used in concert with protein domain, mutant phenotype and protein localization data to produce a functional prediction. Our method is applied to the functional prediction of Saccharomyces cerevisiae genes, using Gene Ontology (GO terms as the basis of our annotation. In a cross validation study we show that the integrated model increases recall by 18%, compared to using PPI data alone at the 50% precision. We also show that the integrated predictor is significantly better than each individual predictor. However, the observed improvement vs. PPI depends on both the new source of data and the functional category to be predicted. Surprisingly, in some contexts integration hurts overall prediction accuracy. Lastly, we provide a comprehensive assignment of putative GO terms to 463 proteins that currently have no assigned function.

  12. RNA 3D modules in genome-wide predictions of RNA 2D structure

    DEFF Research Database (Denmark)

    Theis, Corinna; Zirbel, Craig L; Zu Siederdissen, Christian Höner

    2015-01-01

    Recent experimental and computational progress has revealed a large potential for RNA structure in the genome. This has been driven by computational strategies that exploit multiple genomes of related organisms to identify common sequences and secondary structures. However, these computational...... approaches have two main challenges: they are computationally expensive and they have a relatively high false discovery rate (FDR). Simultaneously, RNA 3D structure analysis has revealed modules composed of non-canonical base pairs which occur in non-homologous positions, apparently by independent evolution....... These modules can, for example, occur inside structural elements which in RNA 2D predictions appear as internal loops. Hence one question is if the use of such RNA 3D information can improve the prediction accuracy of RNA secondary structure at a genome-wide level. Here, we use RNAz in combination with 3D...

  13. Predicting genome-wide redundancy using machine learning

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    Shasha Dennis E

    2010-11-01

    Full Text Available Abstract Background Gene duplication can lead to genetic redundancy, which masks the function of mutated genes in genetic analyses. Methods to increase sensitivity in identifying genetic redundancy can improve the efficiency of reverse genetics and lend insights into the evolutionary outcomes of gene duplication. Machine learning techniques are well suited to classifying gene family members into redundant and non-redundant gene pairs in model species where sufficient genetic and genomic data is available, such as Arabidopsis thaliana, the test case used here. Results Machine learning techniques that combine multiple attributes led to a dramatic improvement in predicting genetic redundancy over single trait classifiers alone, such as BLAST E-values or expression correlation. In withholding analysis, one of the methods used here, Support Vector Machines, was two-fold more precise than single attribute classifiers, reaching a level where the majority of redundant calls were correctly labeled. Using this higher confidence in identifying redundancy, machine learning predicts that about half of all genes in Arabidopsis showed the signature of predicted redundancy with at least one but typically less than three other family members. Interestingly, a large proportion of predicted redundant gene pairs were relatively old duplications (e.g., Ks > 1, suggesting that redundancy is stable over long evolutionary periods. Conclusions Machine learning predicts that most genes will have a functionally redundant paralog but will exhibit redundancy with relatively few genes within a family. The predictions and gene pair attributes for Arabidopsis provide a new resource for research in genetics and genome evolution. These techniques can now be applied to other organisms.

  14. Genome-Wide Prediction of DNA Methylation Using DNA Composition and Sequence Complexity in Human

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    Wu, Chengchao; Yao, Shixin; Li, Xinghao; Chen, Chujia; Hu, Xuehai

    2017-01-01

    DNA methylation plays a significant role in transcriptional regulation by repressing activity. Change of the DNA methylation level is an important factor affecting the expression of target genes and downstream phenotypes. Because current experimental technologies can only assay a small proportion of CpG sites in the human genome, it is urgent to develop reliable computational models for predicting genome-wide DNA methylation. Here, we proposed a novel algorithm that accurately extracted sequence complexity features (seven features) and developed a support-vector-machine-based prediction model with integration of the reported DNA composition features (trinucleotide frequency and GC content, 65 features) by utilizing the methylation profiles of embryonic stem cells in human. The prediction results from 22 human chromosomes with size-varied windows showed that the 600-bp window achieved the best average accuracy of 94.7%. Moreover, comparisons with two existing methods further showed the superiority of our model, and cross-species predictions on mouse data also demonstrated that our model has certain generalization ability. Finally, a statistical test of the experimental data and the predicted data on functional regions annotated by ChromHMM found that six out of 10 regions were consistent, which implies reliable prediction of unassayed CpG sites. Accordingly, we believe that our novel model will be useful and reliable in predicting DNA methylation. PMID:28212312

  15. Genome-wide identification of the regulatory targets of a transcription factor using biochemical characterization and computational genomic analysis

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    Jolly Emmitt R

    2005-11-01

    Full Text Available Abstract Background A major challenge in computational genomics is the development of methodologies that allow accurate genome-wide prediction of the regulatory targets of a transcription factor. We present a method for target identification that combines experimental characterization of binding requirements with computational genomic analysis. Results Our method identified potential target genes of the transcription factor Ndt80, a key transcriptional regulator involved in yeast sporulation, using the combined information of binding affinity, positional distribution, and conservation of the binding sites across multiple species. We have also developed a mathematical approach to compute the false positive rate and the total number of targets in the genome based on the multiple selection criteria. Conclusion We have shown that combining biochemical characterization and computational genomic analysis leads to accurate identification of the genome-wide targets of a transcription factor. The method can be extended to other transcription factors and can complement other genomic approaches to transcriptional regulation.

  16. Genome-wide protein localization prediction strategies for gram negative bacteria

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    Romine Margaret F

    2011-06-01

    Full Text Available Abstract Background Genome-wide prediction of protein subcellular localization is an important type of evidence used for inferring protein function. While a variety of computational tools have been developed for this purpose, errors in the gene models and use of protein sorting signals that are not recognized by the more commonly accepted tools can diminish the accuracy of their output. Results As part of an effort to manually curate the annotations of 19 strains of Shewanella, numerous insights were gained regarding the use of computational tools and proteomics data to predict protein localization. Identification of the suite of secretion systems present in each strain at the start of the process made it possible to tailor-fit the subsequent localization prediction strategies to each strain for improved accuracy. Comparisons of the computational predictions among orthologous proteins revealed inconsistencies in the computational outputs, which could often be resolved by adjusting the gene models or ortholog group memberships. While proteomic data was useful for verifying start site predictions and post-translational proteolytic cleavage, care was needed to distinguish cellular versus sample processing-mediated cleavage events. Searches for lipoprotein signal peptides revealed that neither TatP nor LipoP are designed for identification of lipoprotein substrates of the twin arginine translocation system and that the +2 rule for lipoprotein sorting does not apply to this Genus. Analysis of the relationships between domain occurrence and protein localization prediction enabled identification of numerous location-informative domains which could then be used to refine or increase confidence in location predictions. This collective knowledge was used to develop a general strategy for predicting protein localization that could be adapted to other organisms. Conclusion Improved localization prediction accuracy is not simply a matter of developing better

  17. Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis

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    Chen Jiun-Ching

    2007-05-01

    Full Text Available Abstract Background Genome-wide identification of specific oligonucleotides (oligos is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network (ANN is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos. Results We present a novel and efficient algorithm, named the integration of ANN and BLAST (IAB algorithm, to identify specific oligos. We establish the unique marker database for human and rat gene index databases using the hash table algorithm. We then create the input vectors, via the unique marker database, to train and test the ANN. The trained ANN predicted the specific oligos with high efficiency, and these oligos were subsequently verified by BLAST. To improve the prediction performance, the ANN over-fitting issue was avoided by early stopping with the best observed error and a k-fold validation was also applied. The performance of the IAB algorithm was about 5.2, 7.1, and 6.7 times faster than the BLAST search without ANN for experimental results of 70-mer, 50-mer, and 25-mer specific oligos, respectively. In addition, the results of polymerase chain reactions showed that the primers predicted by the IAB algorithm could specifically amplify the corresponding genes. The IAB algorithm has been integrated into a previously published comprehensive web server to support microarray analysis and genome-wide iterative enrichment analysis, through which users can identify a group of desired genes and then discover the specific oligos of these genes. Conclusion The IAB algorithm has been developed to construct SpecificDB, a web server that provides a specific and valid oligo database of the probe, siRNA, and primer design for the human genome. We also demonstrate the ability of the IAB algorithm to predict specific oligos through

  18. Genome-wide prediction and validation of sigma70 promoters in Lactobacillus plantarum WCFS1.

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    Tilman J Todt

    Full Text Available BACKGROUND: In prokaryotes, sigma factors are essential for directing the transcription machinery towards promoters. Various sigma factors have been described that recognize, and bind to specific DNA sequence motifs in promoter sequences. The canonical sigma factor σ(70 is commonly involved in transcription of the cell's housekeeping genes, which is mediated by the conserved σ(70 promoter sequence motifs. In this study the σ(70-promoter sequences in Lactobacillus plantarum WCFS1 were predicted using a genome-wide analysis. The accuracy of the transcriptionally-active part of this promoter prediction was subsequently evaluated by correlating locations of predicted promoters with transcription start sites inferred from the 5'-ends of transcripts detected by high-resolution tiling array transcriptome datasets. RESULTS: To identify σ(70-related promoter sequences, we performed a genome-wide sequence motif scan of the L. plantarum WCFS1 genome focussing on the regions upstream of protein-encoding genes. We obtained several highly conserved motifs including those resembling the conserved σ(70-promoter consensus. Position weight matrices-based models of the recovered σ(70-promoter sequence motif were employed to identify 3874 motifs with significant similarity (p-value<10(-4 to the model-motif in the L. plantarum genome. Genome-wide transcript information deduced from whole genome tiling-array transcriptome datasets, was used to infer transcription start sites (TSSs from the 5'-end of transcripts. By this procedure, 1167 putative TSSs were identified that were used to corroborate the transcriptionally active fraction of these predicted promoters. In total, 568 predicted promoters were found in proximity (≤ 40 nucleotides of the putative TSSs, showing a highly significant co-occurrence of predicted promoter and TSS (p-value<10(-263. CONCLUSIONS: High-resolution tiling arrays provide a suitable source to infer TSSs at a genome-wide level, and

  19. Risk Prediction Using Genome-Wide Association Studies on Type 2 Diabetes

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    Sungkyoung Choi

    2016-12-01

    Full Text Available The success of genome-wide association studies (GWASs has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the “large p and small n” problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR, least absolute shrinkage and selection operator (LASSO, and Elastic-Net (EN. We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes.

  20. Risk Prediction Using Genome-Wide Association Studies on Type 2 Diabetes

    Science.gov (United States)

    Choi, Sungkyoung; Bae, Sunghwan

    2016-01-01

    The success of genome-wide association studies (GWASs) has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the “large p and small n” problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN). We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC) for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes.

  1. Genomic selection and complex trait prediction using a fast EM algorithm applied to genome-wide markers.

    Science.gov (United States)

    Shepherd, Ross K; Meuwissen, Theo H E; Woolliams, John A

    2010-10-22

    The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding programs. Genome-wide association studies relate individual single nucleotide polymorphisms (SNP) from dense SNP panels to individual measurements of complex traits, with the underlying assumption being that any association is caused by linkage disequilibrium (LD) between SNP and quantitative trait loci (QTL) affecting the trait. Often SNP are in genomic regions of no trait variation. Whole genome Bayesian models are an effective way of incorporating this and other important prior information into modelling. However a full Bayesian analysis is often not feasible due to the large computational time involved. This article proposes an expectation-maximization (EM) algorithm called emBayesB which allows only a proportion of SNP to be in LD with QTL and incorporates prior information about the distribution of SNP effects. The posterior probability of being in LD with at least one QTL is calculated for each SNP along with estimates of the hyperparameters for the mixture prior. A simulated example of genomic selection from an international workshop is used to demonstrate the features of the EM algorithm. The accuracy of prediction is comparable to a full Bayesian analysis but the EM algorithm is considerably faster. The EM algorithm was accurate in locating QTL which explained more than 1% of the total genetic variation. A computational algorithm for very large SNP panels is described. emBayesB is a fast and accurate EM algorithm for implementing genomic selection and predicting complex traits by mapping QTL in genome-wide dense SNP marker data. Its accuracy is similar to Bayesian methods but it takes only a fraction of the time.

  2. [A novel method of the genome-wide prediction for the target genes and its application].

    Science.gov (United States)

    Zhang, Jing-Jing; Feng, Jing; Zhu, Ying-Guo; Li, Yang-Sheng

    2006-10-01

    Based on the protein databases of several model species, this study developed a new method of the Genome-wide prediction for the target genes, using Hidden Markov model by Perl programming. The advantages of this method are high throughput, high quality and easy prediction, especially in the case of multi-domains proteins families. By this method, we predicted the PPR and TPR proteins families in whole genome of several model species. There were 536 PPR proteins and 199 TPR proteins in Oryza sativa ssp. japonica, 519 PPR proteins and 177 TPR proteins in Oryza sativa L. ssp. indica, 735 PPR proteins and 292 TPR proteins in Arabidopsis thaliana, 6 PPR proteins and 32 TPR proteins in Cyanidioschyzon merolae. Synechococcus and Thermophilic archaebacterium did not have PPR proteins. By contrast, 10 TPR proteins were found in Synechococcus and 4 TPR proteins were found in Thermophilic archaebacterium. Moreover, of these results, some further bioinformatics analyses were conducted.

  3. Sequence-based prediction of single nucleosome positioning and genome-wide nucleosome occupancy.

    Science.gov (United States)

    van der Heijden, Thijn; van Vugt, Joke J F A; Logie, Colin; van Noort, John

    2012-09-18

    Nucleosome positioning dictates eukaryotic DNA compaction and access. To predict nucleosome positions in a statistical mechanics model, we exploited the knowledge that nucleosomes favor DNA sequences with specific periodically occurring dinucleotides. Our model is the first to capture both dyad position within a few base pairs, and free binding energy within 2 k(B)T, for all the known nucleosome positioning sequences. By applying Percus's equation to the derived energy landscape, we isolate sequence effects on genome-wide nucleosome occupancy from other factors that may influence nucleosome positioning. For both in vitro and in vivo systems, three parameters suffice to predict nucleosome occupancy with correlation coefficients of respectively 0.74 and 0.66. As predicted, we find the largest deviations in vivo around transcription start sites. This relatively simple algorithm can be used to guide future studies on the influence of DNA sequence on chromatin organization.

  4. Genome-wide de Novo Prediction of Proximal and Distal Tissue-Specific Enhancers

    Energy Technology Data Exchange (ETDEWEB)

    Loots, G G; Ovcharenko, I V

    2005-11-03

    Determining how transcriptional regulatory networks are encoded in the human genome is essential for understanding how cellular processes are directed. Here, we present a novel approach for systematically predicting tissue specific regulatory elements (REs) that blends genome-wide expression profiling, vertebrate genome comparisons, and pattern analysis of transcription factor binding sites. This analysis yields 4,670 candidate REs in the human genome with distinct tissue specificities, the majority of which reside far away from transcription start sites. We identify key transcription factors (TFs) for 34 distinct tissues and demonstrate that tissue-specific gene expression relies on multiple regulatory pathways employing similar, but different cohorts of interacting TFs. The methods and results we describe provide a global view of tissue specific gene regulation in humans, and propose a strategy for deciphering the transcriptional regulatory code in eukaryotes.

  5. Computational modelling of genome-wide [corrected] transcription assembly networks using a fluidics analogy.

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    Yousry Y Azmy

    Full Text Available Understanding how a myriad of transcription regulators work to modulate mRNA output at thousands of genes remains a fundamental challenge in molecular biology. Here we develop a computational tool to aid in assessing the plausibility of gene regulatory models derived from genome-wide expression profiling of cells mutant for transcription regulators. mRNA output is modelled as fluid flow in a pipe lattice, with assembly of the transcription machinery represented by the effect of valves. Transcriptional regulators are represented as external pressure heads that determine flow rate. Modelling mutations in regulatory proteins is achieved by adjusting valves' on/off settings. The topology of the lattice is designed by the experimentalist to resemble the expected interconnection between the modelled agents and their influence on mRNA expression. Users can compare multiple lattice configurations so as to find the one that minimizes the error with experimental data. This computational model provides a means to test the plausibility of transcription regulation models derived from large genomic data sets.

  6. Computer vision and machine learning for robust phenotyping in genome-wide studies

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    Zhang, Jiaoping; Naik, Hsiang Sing; Assefa, Teshale; Sarkar, Soumik; Reddy, R. V. Chowda; Singh, Arti; Ganapathysubramanian, Baskar; Singh, Asheesh K.

    2017-01-01

    Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems. PMID:28272456

  7. Computer vision and machine learning for robust phenotyping in genome-wide studies.

    Science.gov (United States)

    Zhang, Jiaoping; Naik, Hsiang Sing; Assefa, Teshale; Sarkar, Soumik; Reddy, R V Chowda; Singh, Arti; Ganapathysubramanian, Baskar; Singh, Asheesh K

    2017-03-08

    Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems.

  8. Genome Wide Association Study to predict severe asthma exacerbations in children using random forests classifiers

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    Litonjua Augusto A

    2011-06-01

    Full Text Available Abstract Background Personalized health-care promises tailored health-care solutions to individual patients based on their genetic background and/or environmental exposure history. To date, disease prediction has been based on a few environmental factors and/or single nucleotide polymorphisms (SNPs, while complex diseases are usually affected by many genetic and environmental factors with each factor contributing a small portion to the outcome. We hypothesized that the use of random forests classifiers to select SNPs would result in an improved predictive model of asthma exacerbations. We tested this hypothesis in a population of childhood asthmatics. Methods In this study, using emergency room visits or hospitalizations as the definition of a severe asthma exacerbation, we first identified a list of top Genome Wide Association Study (GWAS SNPs ranked by Random Forests (RF importance score for the CAMP (Childhood Asthma Management Program population of 127 exacerbation cases and 290 non-exacerbation controls. We predict severe asthma exacerbations using the top 10 to 320 SNPs together with age, sex, pre-bronchodilator FEV1 percentage predicted, and treatment group. Results Testing in an independent set of the CAMP population shows that severe asthma exacerbations can be predicted with an Area Under the Curve (AUC = 0.66 with 160-320 SNPs in comparison to an AUC score of 0.57 with 10 SNPs. Using the clinical traits alone yielded AUC score of 0.54, suggesting the phenotype is affected by genetic as well as environmental factors. Conclusions Our study shows that a random forests algorithm can effectively extract and use the information contained in a small number of samples. Random forests, and other machine learning tools, can be used with GWAS studies to integrate large numbers of predictors simultaneously.

  9. Genome-wide Transcription Factor Gene Prediction and their Expressional Tissue-Specificities in Maize

    Institute of Scientific and Technical Information of China (English)

    Yi Jiang; Biao Zeng; Hainan Zhao; Mei Zhang; Shaojun Xie; Jinsheng Lai

    2012-01-01

    Transcription factors (TFs) are important regulators of gene expression.To better understand TFencoding genes in maize (Zea mays L.),a genome-wide TF prediction was performed using the updated B73 reference genome.A total of 2 298 TF genes were identified,which can be classified into 56 families.The largest family,known as the MYB superfamily,comprises 322 MYB and MYB-related TF genes.The expression patterns of 2014 (87.64%) TF genes were examined using RNA-seq data,which resulted in the identification of a subset of TFs that are specifically expressed in particular tissues (including root,shoot,leaf,ear,tassel and kernel).Similarly,98 kernel-specific TF genes were further analyzed,and it was observed that 29 of the kernel-specific genes were preferentially expressed in the early kernel developmental stage,while 69 of the genes were expressed in the late kernel developmental stage.Identification of these TFs,particularly the tissue-specific ones,provides important information for the understanding of development and transcriptional regulation of maize.

  10. Prediction of disease and phenotype associations from genome-wide association studies.

    Directory of Open Access Journals (Sweden)

    Stephanie N Lewis

    Full Text Available BACKGROUND: Genome wide association studies (GWAS have proven useful as a method for identifying genetic variations associated with diseases. In this study, we analyzed GWAS data for 61 diseases and phenotypes to elucidate common associations based on single nucleotide polymorphisms (SNP. The study was an expansion on a previous study on identifying disease associations via data from a single GWAS on seven diseases. METHODOLOGY/PRINCIPAL FINDINGS: Adjustments to the originally reported study included expansion of the SNP dataset using Linkage Disequilibrium (LD and refinement of the four levels of analysis to encompass SNP, SNP block, gene, and pathway level comparisons. A pair-wise comparison between diseases and phenotypes was performed at each level and the Jaccard similarity index was used to measure the degree of association between two diseases/phenotypes. Disease relatedness networks (DRNs were used to visualize our results. We saw predominant relatedness between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis for the first three levels of analysis. Expected relatedness was also seen between lipid- and blood-related traits. CONCLUSIONS/SIGNIFICANCE: The predominant associations between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis can be validated by clinical studies. The diseases have been proposed to share a systemic inflammation phenotype that can result in progression of additional diseases in patients with one of these three diseases. We also noticed unexpected relationships between metabolic and neurological diseases at the pathway comparison level. The less significant relationships found between diseases require a more detailed literature review to determine validity of the predictions. The results from this study serve as a first step towards a better understanding of seemingly unrelated diseases and phenotypes with similar symptoms or modes of treatment.

  11. Enhancing genomic prediction with genome-wide association studies in multiparental maize populations

    Science.gov (United States)

    Genome-wide association mapping using dense marker sets has identified some nucleotide variants affecting complex traits which have been validated with fine-mapping and functional analysis. Many sequence variants associated with complex traits in maize have small effects and low repeatability, howev...

  12. Meta-analysis of genome-wide association from genomic prediction models

    Science.gov (United States)

    A limitation of many genome-wide association studies (GWA) in animal breeding is that there are many loci with small effect sizes; thus, larger sample sizes (N) are required to guarantee suitable power of detection. To increase sample size, results from different GWA can be combined in a meta-analys...

  13. A combined approach for genome wide protein function annotation/prediction

    DEFF Research Database (Denmark)

    Benso, Alfredo; Di Carlo, Stefano; Ur Rehman, Hafeez

    2013-01-01

    proteins in functional genomics and biology in general motivates the use of computational techniques well orchestrated to accurately predict their functions. METHODS: We propose a computational flow for the functional annotation of a protein able to assign the most probable functions to a protein...

  14. Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.

    Science.gov (United States)

    Haque, M Muksitul; Holder, Lawrence B; Skinner, Michael K

    2015-01-01

    Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs). Different environmental toxicants have been shown to promote exposure (i.e., toxicant) specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm) epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT) and methoxychlor (MXC) exposure lineage F3 generation. Analysis of this positive validation data set showed a 100% prediction accuracy for all the DDT-MXC sperm epimutations. Observations further elucidate the genomic features associated with transgenerational germline epimutations and identify a genome-wide set

  15. Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering

    OpenAIRE

    Guo, Xuan; Meng, Yu; Yu, Ning; Pan, Yi

    2014-01-01

    Backgroud Taking the advan tage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions...

  16. A genome-wide MeSH-based literature mining system predicts implicit gene-to-gene relationships and networks.

    Science.gov (United States)

    Xiang, Zuoshuang; Qin, Tingting; Qin, Zhaohui S; He, Yongqun

    2013-10-16

    The large amount of literature in the post-genomics era enables the study of gene interactions and networks using all available articles published for a specific organism. MeSH is a controlled vocabulary of medical and scientific terms that is used by biomedical scientists to manually index articles in the PubMed literature database. We hypothesized that genome-wide gene-MeSH term associations from the PubMed literature database could be used to predict implicit gene-to-gene relationships and networks. While the gene-MeSH associations have been used to detect gene-gene interactions in some studies, different methods have not been well compared, and such a strategy has not been evaluated for a genome-wide literature analysis. Genome-wide literature mining of gene-to-gene interactions allows ranking of the best gene interactions and investigation of comprehensive biological networks at a genome level. The genome-wide GenoMesh literature mining algorithm was developed by sequentially generating a gene-article matrix, a normalized gene-MeSH term matrix, and a gene-gene matrix. The gene-gene matrix relies on the calculation of pairwise gene dissimilarities based on gene-MeSH relationships. An optimized dissimilarity score was identified from six well-studied functions based on a receiver operating characteristic (ROC) analysis. Based on the studies with well-studied Escherichia coli and less-studied Brucella spp., GenoMesh was found to accurately identify gene functions using weighted MeSH terms, predict gene-gene interactions not reported in the literature, and cluster all the genes studied from an organism using the MeSH-based gene-gene matrix. A web-based GenoMesh literature mining program is also available at: http://genomesh.hegroup.org. GenoMesh also predicts gene interactions and networks among genes associated with specific MeSH terms or user-selected gene lists. The GenoMesh algorithm and web program provide the first genome-wide, MeSH-based literature mining

  17. A foundation for provitamin A biofortification of maize: genome-wide association and genomic prediction models of carotenoid levels.

    Science.gov (United States)

    Owens, Brenda F; Lipka, Alexander E; Magallanes-Lundback, Maria; Tiede, Tyler; Diepenbrock, Christine H; Kandianis, Catherine B; Kim, Eunha; Cepela, Jason; Mateos-Hernandez, Maria; Buell, C Robin; Buckler, Edward S; DellaPenna, Dean; Gore, Michael A; Rocheford, Torbert

    2014-12-01

    Efforts are underway for development of crops with improved levels of provitamin A carotenoids to help combat dietary vitamin A deficiency. As a global staple crop with considerable variation in kernel carotenoid composition, maize (Zea mays L.) could have a widespread impact. We performed a genome-wide association study (GWAS) of quantified seed carotenoids across a panel of maize inbreds ranging from light yellow to dark orange in grain color to identify some of the key genes controlling maize grain carotenoid composition. Significant associations at the genome-wide level were detected within the coding regions of zep1 and lut1, carotenoid biosynthetic genes not previously shown to impact grain carotenoid composition in association studies, as well as within previously associated lcyE and crtRB1 genes. We leveraged existing biochemical and genomic information to identify 58 a priori candidate genes relevant to the biosynthesis and retention of carotenoids in maize to test in a pathway-level analysis. This revealed dxs2 and lut5, genes not previously associated with kernel carotenoids. In genomic prediction models, use of markers that targeted a small set of quantitative trait loci associated with carotenoid levels in prior linkage studies were as effective as genome-wide markers for predicting carotenoid traits. Based on GWAS, pathway-level analysis, and genomic prediction studies, we outline a flexible strategy involving use of a small number of genes that can be selected for rapid conversion of elite white grain germplasm, with minimal amounts of carotenoids, to orange grain versions containing high levels of provitamin A.

  18. A novel genome-wide full- length kinesin prediction analysis reveals additional mammalian kinesins

    Institute of Scientific and Technical Information of China (English)

    XUE Yu; LIU Dan; FU Chuanhai; DOU Zhen; ZHOU Qing; YAO Xuebiao

    2006-01-01

    Kinesin superfamily of microtubule- based motor orchestrates a variety of cellular processes. Recent availability of mammalian genomes has enabled analyses of kinesins on the whole genome. Here we present a novel full-length kinesin prediction program (FKPP) for mammalian kinesin gene discovery based on a comparative genomics approach. Contrary to previous predictions of 94 kinesins, we identify a total of 134 potentially kinesin genes from mammalian genomes, including 45 from mouse, 45 from rat and 44 from human. In addition, FKPP synthesizes 25 potentially full-length mammalian kinesins based on the partial sequences in the database. Surprisingly, FKPP reveals that full-length human CENP-E contains 2701 aa rather than 2663 aa in the database. Experimentation using sequence specific antibody and cDNA sequencing of human CENP-E validates the accuracy of FKPP. Given the remarkable computing efficiency and accuracy of FKPP, we reclassify the mammalian kinesin superfamily. Since current databases contain many incomplete sequences, FKPP may provide a novel approach for molecular delineation of kinesins and other protein families.

  19. Genome-wide DNA methylation analysis predicts an epigenetic switch for GATA factor expression in endometriosis.

    Directory of Open Access Journals (Sweden)

    Matthew T Dyson

    2014-03-01

    Full Text Available Endometriosis is a gynecological disease defined by the extrauterine growth of endometrial-like cells that cause chronic pain and infertility. The disease is limited to primates that exhibit spontaneous decidualization, and diseased cells are characterized by significant defects in the steroid-dependent genetic pathways that typify this process. Altered DNA methylation may underlie these defects, but few regions with differential methylation have been implicated in the disease. We mapped genome-wide differences in DNA methylation between healthy human endometrial and endometriotic stromal cells and correlated this with gene expression using an interaction analysis strategy. We identified 42,248 differentially methylated CpGs in endometriosis compared to healthy cells. These extensive differences were not unidirectional, but were focused intragenically and at sites distal to classic CpG islands where methylation status was typically negatively correlated with gene expression. Significant differences in methylation were mapped to 403 genes, which included a disproportionally large number of transcription factors. Furthermore, many of these genes are implicated in the pathology of endometriosis and decidualization. Our results tremendously improve the scope and resolution of differential methylation affecting the HOX gene clusters, nuclear receptor genes, and intriguingly the GATA family of transcription factors. Functional analysis of the GATA family revealed that GATA2 regulates key genes necessary for the hormone-driven differentiation of healthy stromal cells, but is hypermethylated and repressed in endometriotic cells. GATA6, which is hypomethylated and abundant in endometriotic cells, potently blocked hormone sensitivity, repressed GATA2, and induced markers of endometriosis when expressed in healthy endometrial cells. The unique epigenetic fingerprint in endometriosis suggests DNA methylation is an integral component of the disease, and

  20. Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.

    Directory of Open Access Journals (Sweden)

    M Muksitul Haque

    Full Text Available Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs. Different environmental toxicants have been shown to promote exposure (i.e., toxicant specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT and methoxychlor (MXC exposure lineage F3 generation. Analysis of this positive validation

  1. Genome-wide Studies of Mycolic Acid Bacteria: Computational Identification and Analysis of a Minimal Genome

    KAUST Repository

    Kamanu, Frederick Kinyua

    2012-12-01

    The mycolic acid bacteria are a distinct suprageneric group of asporogenous Grampositive, high GC-content bacteria, distinguished by the presence of mycolic acids in their cell envelope. They exhibit great diversity in their cell and morphology; although primarily non-pathogens, this group contains three major pathogens Mycobacterium leprae, Mycobacterium tuberculosis complex, and Corynebacterium diphtheria. Although the mycolic acid bacteria are a clearly defined group of bacteria, the taxonomic relationships between its constituent genera and species are less well defined. Two approaches were tested for their suitability in describing the taxonomy of the group. First, a Multilocus Sequence Typing (MLST) experiment was assessed and found to be superior to monophyletic (16S small ribosomal subunit) in delineating a total of 52 mycolic acid bacterial species. Phylogenetic inference was performed using the neighbor-joining method. To further refine phylogenetic analysis and to take advantage of the widespread availability of bacterial genome data, a computational framework that simulates DNA-DNA hybridisation was developed and validated using multiscale bootstrap resampling. The tool classifies microbial genomes based on whole genome DNA, and was deployed as a web-application using PHP and Javascript. It is accessible online at http://cbrc.kaust.edu.sa/dna_hybridization/ A third study was a computational and statistical methods in the identification and analysis of a putative minimal mycolic acid bacterial genome so as to better understand (1) the genomic requirements to encode a mycolic acid bacterial cell and (2) the role and type of genes and genetic elements that lead to the massive increase in genome size in environmental mycolic acid bacteria. Using a reciprocal comparison approach, a total of 690 orthologous gene clusters forming a putative minimal genome were identified across 24 mycolic acid bacterial species. In order to identify new potential drug

  2. Genome-wide prediction of transcriptional regulatory elements of human promoters using gene expression and promoter analysis data

    Directory of Open Access Journals (Sweden)

    Kim Seon-Young

    2006-07-01

    Full Text Available Abstract Background A complete understanding of the regulatory mechanisms of gene expression is the next important issue of genomics. Many bioinformaticians have developed methods and algorithms for predicting transcriptional regulatory mechanisms from sequence, gene expression, and binding data. However, most of these studies involved the use of yeast which has much simpler regulatory networks than human and has many genome wide binding data and gene expression data under diverse conditions. Studies of genome wide transcriptional networks of human genomes currently lag behind those of yeast. Results We report herein a new method that combines gene expression data analysis with promoter analysis to infer transcriptional regulatory elements of human genes. The Z scores from the application of gene set analysis with gene sets of transcription factor binding sites (TFBSs were successfully used to represent the activity of TFBSs in a given microarray data set. A significant correlation between the Z scores of gene sets of TFBSs and individual genes across multiple conditions permitted successful identification of many known human transcriptional regulatory elements of genes as well as the prediction of numerous putative TFBSs of many genes which will constitute a good starting point for further experiments. Using Z scores of gene sets of TFBSs produced better predictions than the use of mRNA levels of a transcription factor itself, suggesting that the Z scores of gene sets of TFBSs better represent diverse mechanisms for changing the activity of transcription factors in the cell. In addition, cis-regulatory modules, combinations of co-acting TFBSs, were readily identified by our analysis. Conclusion By a strategic combination of gene set level analysis of gene expression data sets and promoter analysis, we were able to identify and predict many transcriptional regulatory elements of human genes. We conclude that this approach will aid in decoding

  3. Genome-wide association and genomic prediction of resistance to maize lethal necrosis disease in tropical maize germplasm.

    Science.gov (United States)

    Gowda, Manje; Das, Biswanath; Makumbi, Dan; Babu, Raman; Semagn, Kassa; Mahuku, George; Olsen, Michael S; Bright, Jumbo M; Beyene, Yoseph; Prasanna, Boddupalli M

    2015-10-01

    Genome-wide association analysis in tropical and subtropical maize germplasm revealed that MLND resistance is influenced by multiple genomic regions with small to medium effects. The maize lethal necrosis disease (MLND) caused by synergistic interaction of Maize chlorotic mottle virus and Sugarcane mosaic virus, and has emerged as a serious threat to maize production in eastern Africa since 2011. Our objective was to gain insights into the genetic architecture underlying the resistance to MLND by genome-wide association study (GWAS) and genomic selection. We used two association mapping (AM) panels comprising a total of 615 diverse tropical/subtropical maize inbred lines. All the lines were evaluated against MLND under artificial inoculation. Both the panels were genotyped using genotyping-by-sequencing. Phenotypic variation for MLND resistance was significant and heritability was moderately high in both the panels. Few promising lines with high resistance to MLND were identified to be used as potential donors. GWAS revealed 24 SNPs that were significantly associated (P < 3 × 10(-5)) with MLND resistance. These SNPs are located within or adjacent to 20 putative candidate genes that are associated with plant disease resistance. Ridge regression best linear unbiased prediction with five-fold cross-validation revealed higher prediction accuracy for IMAS-AM panel (0.56) over DTMA-AM (0.36) panel. The prediction accuracy for both within and across panels is promising; inclusion of MLND resistance associated SNPs into the prediction model further improved the accuracy. Overall, the study revealed that resistance to MLND is controlled by multiple loci with small to medium effects and the SNPs identified by GWAS can be used as potential candidates in MLND resistance breeding program.

  4. MicroTrout: A comprehensive, genome-wide miRNA target prediction framework for rainbow trout, Oncorhynchus mykiss.

    Science.gov (United States)

    Mennigen, Jan A; Zhang, Dapeng

    2016-12-01

    Rainbow trout represent an important teleost research model and aquaculture species. As such, rainbow trout are employed in diverse areas of biological research, including basic biological disciplines such as comparative physiology, toxicology, and, since rainbow trout have undergone both teleost- and salmonid-specific rounds of genome duplication, molecular evolution. In recent years, microRNAs (miRNAs, small non-protein coding RNAs) have emerged as important posttranscriptional regulators of gene expression in animals. Given the increasingly recognized importance of miRNAs as an additional layer in the regulation of gene expression and hence biological function, recent efforts using RNA- and genome sequencing approaches have resulted in the creation of several resources for the construction of a comprehensive repertoire of rainbow trout miRNAs and isomiRs (variant miRNA sequences that all appear to derive from the same gene but vary in sequence due to post-transcriptional processing). Importantly, through the recent publication of the rainbow trout genome (Berthelot et al., 2014), mRNA 3'UTR information has become available, allowing for the first time the genome-wide prediction of miRNA-target RNA relationships in this species. We here report the creation of the microtrout database, a comprehensive resource for rainbow trout miRNA and annotated 3'UTRs. The comprehensive database was used to implement an algorithm to predict genome-wide rainbow trout-specific miRNA-mRNA target relationships, generating an improved predictive framework over previously published approaches. This work will serve as a useful framework and sequence resource to experimentally address the role of miRNAs in several research areas using the rainbow trout model, examples of which are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

    OpenAIRE

    Teng Shaolei; Yang Jack Y; Wang Liangjiang

    2013-01-01

    Abstract Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study,...

  6. Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data.

    Science.gov (United States)

    Teng, Shaolei; Yang, Jack Y; Wang, Liangjiang

    2013-01-01

    Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs) and Support Vector Machines (SVMs) were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression.

  7. Genome-wide prediction, display and refinement of binding sites with information theory-based models

    Directory of Open Access Journals (Sweden)

    Leeder J Steven

    2003-09-01

    Full Text Available Abstract Background We present Delila-genome, a software system for identification, visualization and analysis of protein binding sites in complete genome sequences. Binding sites are predicted by scanning genomic sequences with information theory-based (or user-defined weight matrices. Matrices are refined by adding experimentally-defined binding sites to published binding sites. Delila-Genome was used to examine the accuracy of individual information contents of binding sites detected with refined matrices as a measure of the strengths of the corresponding protein-nucleic acid interactions. The software can then be used to predict novel sites by rescanning the genome with the refined matrices. Results Parameters for genome scans are entered using a Java-based GUI interface and backend scripts in Perl. Multi-processor CPU load-sharing minimized the average response time for scans of different chromosomes. Scans of human genome assemblies required 4–6 hours for transcription factor binding sites and 10–19 hours for splice sites, respectively, on 24- and 3-node Mosix and Beowulf clusters. Individual binding sites are displayed either as high-resolution sequence walkers or in low-resolution custom tracks in the UCSC genome browser. For large datasets, we applied a data reduction strategy that limited displays of binding sites exceeding a threshold information content to specific chromosomal regions within or adjacent to genes. An HTML document is produced listing binding sites ranked by binding site strength or chromosomal location hyperlinked to the UCSC custom track, other annotation databases and binding site sequences. Post-genome scan tools parse binding site annotations of selected chromosome intervals and compare the results of genome scans using different weight matrices. Comparisons of multiple genome scans can display binding sites that are unique to each scan and identify sites with significantly altered binding strengths

  8. Influence of Feature Encoding and Choice of Classifier on Disease Risk Prediction in Genome-Wide Association Studies.

    Directory of Open Access Journals (Sweden)

    Florian Mittag

    Full Text Available Various attempts have been made to predict the individual disease risk based on genotype data from genome-wide association studies (GWAS. However, most studies only investigated one or two classification algorithms and feature encoding schemes. In this study, we applied seven different classification algorithms on GWAS case-control data sets for seven different diseases to create models for disease risk prediction. Further, we used three different encoding schemes for the genotypes of single nucleotide polymorphisms (SNPs and investigated their influence on the predictive performance of these models. Our study suggests that an additive encoding of the SNP data should be the preferred encoding scheme, as it proved to yield the best predictive performances for all algorithms and data sets. Furthermore, our results showed that the differences between most state-of-the-art classification algorithms are not statistically significant. Consequently, we recommend to prefer algorithms with simple models like the linear support vector machine (SVM as they allow for better subsequent interpretation without significant loss of accuracy.

  9. Traumatic Brain Injury Induces Genome-Wide Transcriptomic, Methylomic, and Network Perturbations in Brain and Blood Predicting Neurological Disorders

    Directory of Open Access Journals (Sweden)

    Qingying Meng

    2017-02-01

    Full Text Available The complexity of the traumatic brain injury (TBI pathology, particularly concussive injury, is a serious obstacle for diagnosis, treatment, and long-term prognosis. Here we utilize modern systems biology in a rodent model of concussive injury to gain a thorough view of the impact of TBI on fundamental aspects of gene regulation, which have the potential to drive or alter the course of the TBI pathology. TBI perturbed epigenomic programming, transcriptional activities (expression level and alternative splicing, and the organization of genes in networks centered around genes such as Anax2, Ogn, and Fmod. Transcriptomic signatures in the hippocampus are involved in neuronal signaling, metabolism, inflammation, and blood function, and they overlap with those in leukocytes from peripheral blood. The homology between genomic signatures from blood and brain elicited by TBI provides proof of concept information for development of biomarkers of TBI based on composite genomic patterns. By intersecting with human genome-wide association studies, many TBI signature genes and network regulators identified in our rodent model were causally associated with brain disorders with relevant link to TBI. The overall results show that concussive brain injury reprograms genes which could lead to predisposition to neurological and psychiatric disorders, and that genomic information from peripheral leukocytes has the potential to predict TBI pathogenesis in the brain.

  10. Traumatic Brain Injury Induces Genome-Wide Transcriptomic, Methylomic, and Network Perturbations in Brain and Blood Predicting Neurological Disorders.

    Science.gov (United States)

    Meng, Qingying; Zhuang, Yumei; Ying, Zhe; Agrawal, Rahul; Yang, Xia; Gomez-Pinilla, Fernando

    2017-02-01

    The complexity of the traumatic brain injury (TBI) pathology, particularly concussive injury, is a serious obstacle for diagnosis, treatment, and long-term prognosis. Here we utilize modern systems biology in a rodent model of concussive injury to gain a thorough view of the impact of TBI on fundamental aspects of gene regulation, which have the potential to drive or alter the course of the TBI pathology. TBI perturbed epigenomic programming, transcriptional activities (expression level and alternative splicing), and the organization of genes in networks centered around genes such as Anax2, Ogn, and Fmod. Transcriptomic signatures in the hippocampus are involved in neuronal signaling, metabolism, inflammation, and blood function, and they overlap with those in leukocytes from peripheral blood. The homology between genomic signatures from blood and brain elicited by TBI provides proof of concept information for development of biomarkers of TBI based on composite genomic patterns. By intersecting with human genome-wide association studies, many TBI signature genes and network regulators identified in our rodent model were causally associated with brain disorders with relevant link to TBI. The overall results show that concussive brain injury reprograms genes which could lead to predisposition to neurological and psychiatric disorders, and that genomic information from peripheral leukocytes has the potential to predict TBI pathogenesis in the brain.

  11. Genome-wide study of percent emphysema on computed tomography in the general population. The Multi-Ethnic Study of Atherosclerosis Lung/SNP Health Association Resource Study

    NARCIS (Netherlands)

    Manichaikul, Ani; Hoffman, Eric A.; Smolonska, Joanna; Gao, Wei; Cho, Michael H.; Baumhauer, Heather; Budoff, Matthew; Austin, John H. M.; Washko, George R.; Carr, J. Jeffrey; Kaufman, Joel D.; Pottinger, Tess; Powell, Charles A.; Wijmenga, Cisca; Zanen, Pieter; Groen, Harry J.M.; Postma, Dirkje S.; Wanner, Adam; Rouhani, Farshid N.; Brantly, Mark L.; Powell, Rhea; Smith, Benjamin M.; Rabinowitz, Dan; Raffel, Leslie J.; Stukovsky, Karen D. Hinckley; Crapo, James D.; Beaty, Terri H.; Hokanson, John E.; Silverman, Edwin K.; Dupuis, Josee; O'Connor, George T.; Boezen, Hendrika; Rich, Stephen S.; Barr, R. Graham

    2014-01-01

    Rationale: Pulmonary emphysema overlaps partially with spirometrically defined chronic obstructive pulmonary disease and is heritable, with moderately high familial clustering. Objectives: To complete a genome-wide association study (GWAS) for the percentage of emphysema-like lung on computed tomogr

  12. Genome-wide association studies and prediction of 17 traits related to phenology, biomass and cell wall composition in the energy grass Miscanthus sinensis.

    Science.gov (United States)

    Slavov, Gancho T; Nipper, Rick; Robson, Paul; Farrar, Kerrie; Allison, Gordon G; Bosch, Maurice; Clifton-Brown, John C; Donnison, Iain S; Jensen, Elaine

    2014-03-01

    • Increasing demands for food and energy require a step change in the effectiveness, speed and flexibility of crop breeding. Therefore, the aim of this study was to assess the potential of genome-wide association studies (GWASs) and genomic selection (i.e. phenotype prediction from a genome-wide set of markers) to guide fundamental plant science and to accelerate breeding in the energy grass Miscanthus. • We generated over 100,000 single-nucleotide variants (SNVs) by sequencing restriction site-associated DNA (RAD) tags in 138 Micanthus sinensis genotypes, and related SNVs to phenotypic data for 17 traits measured in a field trial. • Confounding by population structure and relatedness was severe in naïve GWAS analyses, but mixed-linear models robustly controlled for these effects and allowed us to detect multiple associations that reached genome-wide significance. Genome-wide prediction accuracies tended to be moderate to high (average of 0.57), but varied dramatically across traits. As expected, predictive abilities increased linearly with the size of the mapping population, but reached a plateau when the number of markers used for prediction exceeded 10,000-20,000, and tended to decline, but remain significant, when cross-validations were performed across subpopulations. • Our results suggest that the immediate implementation of genomic selection in Miscanthus breeding programs may be feasible.

  13. Genome-wide association analysis and genomic prediction of Mycobacterium avium subspecies paratuberculosis infection in US Jersey cattle.

    Directory of Open Access Journals (Sweden)

    Yalda Zare

    Full Text Available Paratuberculosis (Johne's disease, an enteric disorder in ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP, causes economic losses in excess of $200 million annually to the US dairy industry. To identify genomic regions underlying susceptibility to MAP infection in Jersey cattle, a case-control genome-wide association study (GWAS was performed. Blood and fecal samples were collected from ∼ 5,000 mature cows in 30 commercial Jersey herds from across the US. Discovery data consisted of 450 cases and 439 controls genotyped with the Illumina BovineSNP50 BeadChip. Cases were animals with positive ELISA and fecal culture (FC results. Controls were animals negative to both ELISA and FC tests that matched cases on birth date and herd. Validation data consisted of 180 animals including 90 cases (positive to FC and 90 controls (negative to ELISA and FC, selected from discovery herds and genotyped by Illumina BovineLD BeadChip (∼ 7K SNPs. Two analytical approaches were used: single-marker GWAS using the GRAMMAR-GC method and Bayesian variable selection (Bayes C using GenSel software. GRAMMAR-GC identified one SNP on BTA7 at 68 megabases (Mb surpassing a significance threshold of 5 × 10(-5. ARS-BFGL-NGS-11887 on BTA23 (27.7 Mb accounted for the highest percentage of genetic variance (3.3% in the Bayes C analysis. SNPs identified in common by GRAMMAR-GC and Bayes C in both discovery and combined data were mapped to BTA23 (27, 29 and 44 Mb, 3 (100, 101, 106 and 107 Mb and 17 (57 Mb. Correspondence between results of GRAMMAR-GC and Bayes C was high (70-80% of most significant SNPs in common. These SNPs could potentially be associated with causal variants underlying susceptibility to MAP infection in Jersey cattle. Predictive performance of the model developed by Bayes C for prediction of infection status of animals in validation set was low (55% probability of correct ranking of paired case and control samples.

  14. Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

    DEFF Research Database (Denmark)

    Su, Guosheng; Christensen, Ole Fredslund; Ostersen, Tage;

    2012-01-01

    Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total...... genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP) markers. In addition...... of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects...

  15. From human monocytes to genome-wide binding sites--a protocol for small amounts of blood: monocyte isolation/ChIP-protocol/library amplification/genome wide computational data analysis.

    Directory of Open Access Journals (Sweden)

    Sebastian Weiterer

    Full Text Available Chromatin immunoprecipitation in combination with a genome-wide analysis via high-throughput sequencing is the state of the art method to gain genome-wide representation of histone modification or transcription factor binding profiles. However, chromatin immunoprecipitation analysis in the context of human experimental samples is limited, especially in the case of blood cells. The typically extremely low yields of precipitated DNA are usually not compatible with library amplification for next generation sequencing. We developed a highly reproducible protocol to present a guideline from the first step of isolating monocytes from a blood sample to analyse the distribution of histone modifications in a genome-wide manner.The protocol describes the whole work flow from isolating monocytes from human blood samples followed by a high-sensitivity and small-scale chromatin immunoprecipitation assay with guidance for generating libraries compatible with next generation sequencing from small amounts of immunoprecipitated DNA.

  16. VIGoR: Variational Bayesian Inference for Genome-Wide Regression

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    Akio Onogi

    2016-04-01

    Full Text Available Genome-wide regression using a number of genome-wide markers as predictors is now widely used for genome-wide association mapping and genomic prediction. We developed novel software for genome-wide regression which we named VIGoR (variational Bayesian inference for genome-wide regression. Variational Bayesian inference is computationally much faster than widely used Markov chain Monte Carlo algorithms. VIGoR implements seven regression methods, and is provided as a command line program package for Linux/Mac, and as a cross-platform R package. In addition to model fitting, cross-validation and hyperparameter tuning using cross-validation can be automatically performed by modifying a single argument. VIGoR is available at https://github.com/Onogi/VIGoR. The R package is also available at https://cran.r-project.org/web/packages/VIGoR/index.html.

  17. Genome-Wide Prediction of SH2 Domain Targets Using Structural Information and the FoldX Algorithm

    DEFF Research Database (Denmark)

    Sanchez, Ignacio E.; Beltrao, Pedro; Stricher, Francois;

    2008-01-01

    validated the predictions using literature-derived SH2 interactions and a probabilistic score obtained from a naive Bayes integration of information on coexpression, conservation of the interaction in other species, shared interaction partners, and functions. We show how our predictions lead to a new......Current experiments likely cover only a fraction of all protein-protein interactions. Here, we developed a method to predict SH2-mediated protein-protein interactions using the structure of SH2-phosphopeptide complexes and the FoldX algorithm. We show that our approach performs similarly...... to experimentally derived consensus sequences and substitution matrices at predicting known in vitro and in vivo targets of SH2 domains. We use our method to provide a set of high-confidence interactions for human SH2 domains with known structure filtered on secondary structure and phosphorylation state. We...

  18. Detecting correlation between allele frequencies and environmental variables as a signature of selection. A fast computational approach for genome-wide studies

    DEFF Research Database (Denmark)

    Guillot, Gilles; Vitalis, Renaud; Rouzic, Arnaud le;

    2014-01-01

    Genomic regions (or loci) displaying outstanding correlation with some environmental variables are likely to be under selection and this is the rationale of recent methods of identifying selected loci and retrieving functional information about them. To be efficient, such methods need to be able...... to disentangle the potential effect of environmental variables from the confounding effect of population history. For the routine analysis of genome-wide datasets, one also needs fast inference and model selection algorithms. We propose a method based on an explicit spatial model which is an instance of spatial...... generalized linear mixed model (SGLMM). For inference, we make use of the INLA–SPDE theoretical and computational framework developed by Rue et al. (2009) and Lindgren et al. (2011). The method we propose allows one to quantify the correlation between genotypes and environmental variables. It works...

  19. Open source tool for prediction of genome wide protein-protein interaction network based on ortholog information

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    Pedamallu Chandra Sekhar

    2010-08-01

    Full Text Available Abstract Background Protein-protein interactions are crucially important for cellular processes. Knowledge of these interactions improves the understanding of cell cycle, metabolism, signaling, transport, and secretion. Information about interactions can hint at molecular causes of diseases, and can provide clues for new therapeutic approaches. Several (usually expensive and time consuming experimental methods can probe protein - protein interactions. Data sets, derived from such experiments make the development of prediction methods feasible, and make the creation of protein-protein interaction network predicting tools possible. Methods Here we report the development of a simple open source program module (OpenPPI_predictor that can generate a putative protein-protein interaction network for target genomes. This tool uses the orthologous interactome network data from a related, experimentally studied organism. Results Results from our predictions can be visualized using the Cytoscape visualization software, and can be piped to downstream processing algorithms. We have employed our program to predict protein-protein interaction network for the human parasite roundworm Brugia malayi, using interactome data from the free living nematode Caenorhabditis elegans. Availability The OpenPPI_predictor source code is available from http://tools.neb.com/~posfai/.

  20. Genomic prediction and genome-wide association analysis of female longevity in a composite beef cattle breed

    Science.gov (United States)

    Longevity is a highly important trait to the efficiency of beef cattle production. The objective of this study was to evaluate the genomic prediction of longevity and identify genomic regions associated with this trait. The data used in this study consisted of 547 Composite Gene Combination (CGC) c...

  1. Genome wide prediction of HNF4alpha functional binding sites by the use of local and global sequence context.

    Science.gov (United States)

    Kel, Alexander E; Niehof, Monika; Matys, Volker; Zemlin, Rüdiger; Borlak, Jürgen

    2008-01-01

    We report an application of machine learning algorithms that enables prediction of the functional context of transcription factor binding sites in the human genome. We demonstrate that our method allowed de novo identification of hepatic nuclear factor (HNF)4alpha binding sites and significantly improved an overall recognition of faithful HNF4alpha targets. When applied to published findings, an unprecedented high number of false positives were identified. The technique can be applied to any transcription factor.

  2. Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach.

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    Simon Boitard

    2016-03-01

    Full Text Available Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey, PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.

  3. BiForce Toolbox: powerful high-throughput computational analysis of gene-gene interactions in genome-wide association studies.

    Science.gov (United States)

    Gyenesei, Attila; Moody, Jonathan; Laiho, Asta; Semple, Colin A M; Haley, Chris S; Wei, Wen-Hua

    2012-07-01

    Genome-wide association studies (GWAS) have discovered many loci associated with common disease and quantitative traits. However, most GWAS have not studied the gene-gene interactions (epistasis) that could be important in complex trait genetics. A major challenge in analysing epistasis in GWAS is the enormous computational demands of analysing billions of SNP combinations. Several methods have been developed recently to address this, some using computers equipped with particular graphical processing units, most restricted to binary disease traits and all poorly suited to general usage on the most widely used operating systems. We have developed the BiForce Toolbox to address the demand for high-throughput analysis of pairwise epistasis in GWAS of quantitative and disease traits across all commonly used computer systems. BiForce Toolbox is a stand-alone Java program that integrates bitwise computing with multithreaded parallelization and thus allows rapid full pairwise genome scans via a graphical user interface or the command line. Furthermore, BiForce Toolbox incorporates additional tests of interactions involving SNPs with significant marginal effects, potentially increasing the power of detection of epistasis. BiForce Toolbox is easy to use and has been applied in multiple studies of epistasis in large GWAS data sets, identifying interesting interaction signals and pathways.

  4. A Genetic Predictive Model for Canine Hip Dysplasia: Integration of Genome Wide Association Study (GWAS) and Candidate Gene Approaches

    Science.gov (United States)

    Bartolomé, Nerea; Segarra, Sergi; Artieda, Marta; Francino, Olga; Sánchez, Elisenda; Szczypiorska, Magdalena; Casellas, Joaquim; Tejedor, Diego; Cerdeira, Joaquín; Martínez, Antonio; Velasco, Alfonso; Sánchez, Armand

    2015-01-01

    Canine hip dysplasia is one of the most prevalent developmental orthopedic diseases in dogs worldwide. Unfortunately, the success of eradication programs against this disease based on radiographic diagnosis is low. Adding the use of diagnostic genetic tools to the current phenotype-based approach might be beneficial. The aim of this study was to develop a genetic prognostic test for early diagnosis of hip dysplasia in Labrador Retrievers. To develop our DNA test, 775 Labrador Retrievers were recruited. For each dog, a blood sample and a ventrodorsal hip radiograph were taken. Dogs were divided into two groups according to their FCI hip score: control (A/B) and case (D/E). C dogs were not included in the sample. Genetic characterization combining a GWAS and a candidate gene strategy using SNPs allowed a case-control population association study. A mathematical model which included 7 SNPs was developed using logistic regression. The model showed a good accuracy (Area under the ROC curve = 0.85) and was validated in an independent population of 114 dogs. This prognostic genetic test represents a useful tool for choosing the most appropriate therapeutic approach once genetic predisposition to hip dysplasia is known. Therefore, it allows a more individualized management of the disease. It is also applicable during genetic selection processes, since breeders can benefit from the information given by this test as soon as a blood sample can be collected, and act accordingly. In the authors’ opinion, a shift towards genomic screening might importantly contribute to reducing canine hip dysplasia in the future. In conclusion, based on genetic and radiographic information from Labrador Retrievers with hip dysplasia, we developed an accurate predictive genetic test for early diagnosis of hip dysplasia in Labrador Retrievers. However, further research is warranted in order to evaluate the validity of this genetic test in other dog breeds. PMID:25874693

  5. A genetic predictive model for canine hip dysplasia: integration of Genome Wide Association Study (GWAS and candidate gene approaches.

    Directory of Open Access Journals (Sweden)

    Nerea Bartolomé

    Full Text Available Canine hip dysplasia is one of the most prevalent developmental orthopedic diseases in dogs worldwide. Unfortunately, the success of eradication programs against this disease based on radiographic diagnosis is low. Adding the use of diagnostic genetic tools to the current phenotype-based approach might be beneficial. The aim of this study was to develop a genetic prognostic test for early diagnosis of hip dysplasia in Labrador Retrievers. To develop our DNA test, 775 Labrador Retrievers were recruited. For each dog, a blood sample and a ventrodorsal hip radiograph were taken. Dogs were divided into two groups according to their FCI hip score: control (A/B and case (D/E. C dogs were not included in the sample. Genetic characterization combining a GWAS and a candidate gene strategy using SNPs allowed a case-control population association study. A mathematical model which included 7 SNPs was developed using logistic regression. The model showed a good accuracy (Area under the ROC curve = 0.85 and was validated in an independent population of 114 dogs. This prognostic genetic test represents a useful tool for choosing the most appropriate therapeutic approach once genetic predisposition to hip dysplasia is known. Therefore, it allows a more individualized management of the disease. It is also applicable during genetic selection processes, since breeders can benefit from the information given by this test as soon as a blood sample can be collected, and act accordingly. In the authors' opinion, a shift towards genomic screening might importantly contribute to reducing canine hip dysplasia in the future. In conclusion, based on genetic and radiographic information from Labrador Retrievers with hip dysplasia, we developed an accurate predictive genetic test for early diagnosis of hip dysplasia in Labrador Retrievers. However, further research is warranted in order to evaluate the validity of this genetic test in other dog breeds.

  6. A genetic predictive model for canine hip dysplasia: integration of Genome Wide Association Study (GWAS) and candidate gene approaches.

    Science.gov (United States)

    Bartolomé, Nerea; Segarra, Sergi; Artieda, Marta; Francino, Olga; Sánchez, Elisenda; Szczypiorska, Magdalena; Casellas, Joaquim; Tejedor, Diego; Cerdeira, Joaquín; Martínez, Antonio; Velasco, Alfonso; Sánchez, Armand

    2015-01-01

    Canine hip dysplasia is one of the most prevalent developmental orthopedic diseases in dogs worldwide. Unfortunately, the success of eradication programs against this disease based on radiographic diagnosis is low. Adding the use of diagnostic genetic tools to the current phenotype-based approach might be beneficial. The aim of this study was to develop a genetic prognostic test for early diagnosis of hip dysplasia in Labrador Retrievers. To develop our DNA test, 775 Labrador Retrievers were recruited. For each dog, a blood sample and a ventrodorsal hip radiograph were taken. Dogs were divided into two groups according to their FCI hip score: control (A/B) and case (D/E). C dogs were not included in the sample. Genetic characterization combining a GWAS and a candidate gene strategy using SNPs allowed a case-control population association study. A mathematical model which included 7 SNPs was developed using logistic regression. The model showed a good accuracy (Area under the ROC curve = 0.85) and was validated in an independent population of 114 dogs. This prognostic genetic test represents a useful tool for choosing the most appropriate therapeutic approach once genetic predisposition to hip dysplasia is known. Therefore, it allows a more individualized management of the disease. It is also applicable during genetic selection processes, since breeders can benefit from the information given by this test as soon as a blood sample can be collected, and act accordingly. In the authors' opinion, a shift towards genomic screening might importantly contribute to reducing canine hip dysplasia in the future. In conclusion, based on genetic and radiographic information from Labrador Retrievers with hip dysplasia, we developed an accurate predictive genetic test for early diagnosis of hip dysplasia in Labrador Retrievers. However, further research is warranted in order to evaluate the validity of this genetic test in other dog breeds.

  7. SNPs and other features as they predispose to complex disease: genome-wide predictive analysis of a quantitative phenotype for hypertension.

    Directory of Open Access Journals (Sweden)

    Joong-Ho Won

    Full Text Available Though recently they have fallen into some disrepute, genome-wide association studies (GWAS have been formulated and applied to understanding essential hypertension. The principal goal here is to use data gathered in a GWAS to gauge the extent to which SNPs and their interactions with other features can be combined to predict mean arterial blood pressure (MAP in 3138 pre-menopausal and naturally post-menopausal white women. More precisely, we quantify the extent to which data as described permit prediction of MAP beyond what is possible from traditional risk factors such as blood cholesterol levels and glucose levels. Of course, these traditional risk factors are genetic, though typically not explicitly so. In all, there were 44 such risk factors/clinical variables measured and 377,790 single nucleotide polymorphisms (SNPs genotyped. Data for women we studied are from first visit measurements taken as part of the Atherosclerotic Risk in Communities (ARIC study. We begin by assessing non-SNP features in their abilities to predict MAP, employing a novel regression technique with two stages, first the discovery of main effects and next discovery of their interactions. The long list of SNPs genotyped is reduced to a manageable list for combining with non-SNP features in prediction. We adapted Efron's local false discovery rate to produce this reduced list. Selected non-SNP and SNP features and their interactions are used to predict MAP using adaptive linear regression. We quantify quality of prediction by an estimated coefficient of determination (R(2. We compare the accuracy of prediction with and without information from SNPs.

  8. Improvement in prediction of coronary heart disease risk over conventional risk factors using SNPs identified in genome-wide association studies.

    Directory of Open Access Journals (Sweden)

    Jennifer L Bolton

    Full Text Available OBJECTIVE: We examined whether a panel of SNPs, systematically selected from genome-wide association studies (GWAS, could improve risk prediction of coronary heart disease (CHD, over-and-above conventional risk factors. These SNPs have already demonstrated reproducible associations with CHD; here we examined their use in long-term risk prediction. STUDY DESIGN AND SETTING: SNPs identified from meta-analyses of GWAS of CHD were tested in 840 men and women aged 55-75 from the Edinburgh Artery Study, a prospective, population-based study with 15 years of follow-up. Cox proportional hazards models were used to evaluate the addition of SNPs to conventional risk factors in prediction of CHD risk. CHD was classified as myocardial infarction (MI, coronary intervention (angioplasty, or coronary artery bypass surgery, angina and/or unspecified ischaemic heart disease as a cause of death; additional analyses were limited to MI or coronary intervention. Model performance was assessed by changes in discrimination and net reclassification improvement (NRI. RESULTS: There were significant improvements with addition of 27 SNPs to conventional risk factors for prediction of CHD (NRI of 54%, P<0.001; C-index 0.671 to 0.740, P = 0.001, as well as MI or coronary intervention, (NRI of 44%, P<0.001; C-index 0.717 to 0.750, P = 0.256. ROC curves showed that addition of SNPs better improved discrimination when the sensitivity of conventional risk factors was low for prediction of MI or coronary intervention. CONCLUSION: There was significant improvement in risk prediction of CHD over 15 years when SNPs identified from GWAS were added to conventional risk factors. This effect may be particularly useful for identifying individuals with a low prognostic index who are in fact at increased risk of disease than indicated by conventional risk factors alone.

  9. The Molecular Revolution in Cutaneous Biology: The Era of Genome-Wide Association Studies and Statistical, Big Data, and Computational Topics.

    Science.gov (United States)

    Anbunathan, Hima; Bowcock, Anne M

    2017-05-01

    The investigation of biological systems involving all organs of the body including the skin is in era of big data. This requires heavy-duty computational tools, and novel statistical methods. Microarrays have allowed the interrogation of thousands of common genetic markers in thousands of individuals from the same population (termed genome wide association studies or GWAS) to reveal common variation associated with disease or phenotype. These markers are usually single nucleotide polymorphisms (SNPs) that are relatively common in the population. In the case of dermatological diseases such as alopecia areata, vitiligo, psoriasis and atopic dermatitis, common variants have been identified that are associated with disease, and these provide insights into biological pathways and reveal possible novel drug targets. Other skin phenotypes such as acne, color and skin cancers are also being investigated with GWAS. Analyses of such large GWAS datasets require a consideration of a number of statistical issues including the testing of multiple markers, population substructure, and ultimately a requirement for replication. There are also issues regarding the missing heritability of disease that cannot be entirely explained with current GWAS approaches. Next generation sequencing technologies such as exome and genome sequencing of similar patient cohorts will reveal additional variants contributing to disease susceptibility. However, the data generated with these approaches will be orders of magnitude greater than that those generated with arrays, with concomitant challenges in the identification of disease causing variants. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  10. Inbreeding in genome-wide selection

    NARCIS (Netherlands)

    Daetwyler, H.D.; Villanueva, B.; Bijma, P.; Woolliams, J.A.

    2007-01-01

    Traditional selection methods, such as sib and best linear unbiased prediction (BLUP) selection, which increased genetic gain by increasing accuracy of evaluation have also led to an increased rate of inbreeding per generation (¿FG). This is not necessarily the case with genome-wide selection, which

  11. Genome-wide association and genomic prediction of breeding values for fatty acid composition in subcutaneous adipose and longissimus lumborum muscle of beef cattle.

    Science.gov (United States)

    Chen, Liuhong; Ekine-Dzivenu, Chinyere; Vinsky, Michael; Basarab, John; Aalhus, Jennifer; Dugan, Mike E R; Fitzsimmons, Carolyn; Stothard, Paul; Li, Changxi

    2015-11-21

    Identification of genetic variants that are associated with fatty acid composition in beef will enhance our understanding of host genetic influence on the trait and also allow for more effective improvement of beef fatty acid profiles through genomic selection and marker-assisted diet management. In this study, 81 and 83 fatty acid traits were measured in subcutaneous adipose (SQ) and longissimus lumborum muscle (LL), respectively, from 1366 purebred and crossbred beef steers and heifers that were genotyped on the Illumina BovineSNP50 Beadchip. The objective was to conduct genome-wide association studies (GWAS) for the fatty acid traits and to evaluate the accuracy of genomic prediction for fatty acid composition using genomic best linear unbiased prediction (GBLUP) and Bayesian methods. In total, 302 and 360 significant SNPs spanning all autosomal chromosomes were identified to be associated with fatty acid composition in SQ and LL tissues, respectively. Proportions of total genetic variance explained by individual significant SNPs ranged from 0.03 to 11.06% in SQ, and from 0.005 to 24.28% in the LL muscle. Markers with relatively large effects were located near fatty acid synthase (FASN), stearoyl-CoA desaturase (SCD), and thyroid hormone responsive (THRSP) genes. For the majority of the fatty acid traits studied, the accuracy of genomic prediction was relatively low ( = 0.50) were achieved for 10:0, 12:0, 14:0, 15:0, 16:0, 9c-14:1, 12c-16:1, 13c-18:1, and health index (HI) in LL, and for 12:0, 14:0, 15:0, 10 t,12c-18:2, and 11 t,13c + 11c,13 t-18:2 in SQ. The Bayesian method performed similarly as GBLUP for most of the traits but substantially better for traits that were affected by SNPs of large effects as identified by GWAS. Fatty acid composition in beef is influenced by a few host genes with major effects and many genes of smaller effects. With the current training population size and marker density, genomic prediction has the potential to predict

  12. RGS2 expression predicts amyloid-β sensitivity, MCI and Alzheimer's disease: genome-wide transcriptomic profiling and bioinformatics data mining

    Science.gov (United States)

    Hadar, A; Milanesi, E; Squassina, A; Niola, P; Chillotti, C; Pasmanik-Chor, M; Yaron, O; Martásek, P; Rehavi, M; Weissglas-Volkov, D; Shomron, N; Gozes, I; Gurwitz, D

    2016-01-01

    Alzheimer's disease (AD) is the most frequent cause of dementia. Misfolded protein pathological hallmarks of AD are brain deposits of amyloid-β (Aβ) plaques and phosphorylated tau neurofibrillary tangles. However, doubts about the role of Aβ in AD pathology have been raised as Aβ is a common component of extracellular brain deposits found, also by in vivo imaging, in non-demented aged individuals. It has been suggested that some individuals are more prone to Aβ neurotoxicity and hence more likely to develop AD when aging brains start accumulating Aβ plaques. Here, we applied genome-wide transcriptomic profiling of lymphoblastoid cells lines (LCLs) from healthy individuals and AD patients for identifying genes that predict sensitivity to Aβ. Real-time PCR validation identified 3.78-fold lower expression of RGS2 (regulator of G-protein signaling 2; P=0.0085) in LCLs from healthy individuals exhibiting high vs low Aβ sensitivity. Furthermore, RGS2 showed 3.3-fold lower expression (P=0.0008) in AD LCLs compared with controls. Notably, RGS2 expression in AD LCLs correlated with the patients' cognitive function. Lower RGS2 expression levels were also discovered in published expression data sets from postmortem AD brain tissues as well as in mild cognitive impairment and AD blood samples compared with controls. In conclusion, Aβ sensitivity phenotyping followed by transcriptomic profiling and published patient data mining identified reduced peripheral and brain expression levels of RGS2, a key regulator of G-protein-coupled receptor signaling and neuronal plasticity. RGS2 is suggested as a novel AD biomarker (alongside other genes) toward early AD detection and future disease modifying therapeutics. PMID:27701409

  13. Genome wide selection in Citrus breeding.

    Science.gov (United States)

    Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A

    2016-10-17

    Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seq(TM) (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.

  14. Integration of Genome-Wide Computation DRE Search, AhR ChIP-chip and Gene Expression Analyses of TCDD-Elicited Responses in the Mouse Liver

    Directory of Open Access Journals (Sweden)

    Matthews Jason

    2011-07-01

    Full Text Available Abstract Background The aryl hydrocarbon receptor (AhR is a ligand-activated transcription factor (TF that mediates responses to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD. Integration of TCDD-induced genome-wide AhR enrichment, differential gene expression and computational dioxin response element (DRE analyses further elucidate the hepatic AhR regulatory network. Results Global ChIP-chip and gene expression analyses were performed on hepatic tissue from immature ovariectomized mice orally gavaged with 30 μg/kg TCDD. ChIP-chip analysis identified 14,446 and 974 AhR enriched regions (1% false discovery rate at 2 and 24 hrs, respectively. Enrichment density was greatest in the proximal promoter, and more specifically, within ± 1.5 kb of a transcriptional start site (TSS. AhR enrichment also occurred distal to a TSS (e.g. intergenic DNA and 3' UTR, extending the potential gene expression regulatory roles of the AhR. Although TF binding site analyses identified over-represented DRE sequences within enriched regions, approximately 50% of all AhR enriched regions lacked a DRE core (5'-GCGTG-3'. Microarray analysis identified 1,896 number of TCDD-responsive genes (|fold change| ≥ 1.5, P1(t > 0.999. Integrating this gene expression data with our ChIP-chip and DRE analyses only identified 625 differentially expressed genes that involved an AhR interaction at a DRE. Functional annotation analysis of differentially regulated genes associated with AhR enrichment identified overrepresented processes related to fatty acid and lipid metabolism and transport, and xenobiotic metabolism, which are consistent with TCDD-elicited steatosis in the mouse liver. Conclusions Details of the AhR regulatory network have been expanded to include AhR-DNA interactions within intragenic and intergenic genomic regions. Moreover, the AhR can interact with DNA independent of a DRE core suggesting there are alternative mechanisms of AhR-mediated gene regulation.

  15. Post genome-wide association studies of novel genes associated with type 2 diabetes show gene-gene interaction and high predictive value.

    Directory of Open Access Journals (Sweden)

    Stéphane Cauchi

    Full Text Available BACKGROUND: Recently, several Genome Wide Association (GWA studies in populations of European descent have identified and validated novel single nucleotide polymorphisms (SNPs, highly associated with type 2 diabetes (T2D. Our aims were to validate these markers in other European and non-European populations, then to assess their combined effect in a large French study comparing T2D and normal glucose tolerant (NGT individuals. METHODOLOGY/PRINCIPAL FINDINGS: In the same French population analyzed in our previous GWA study (3,295 T2D and 3,595 NGT, strong associations with T2D were found for CDKAL1 (OR(rs7756992 = 1.30[1.19-1.42], P = 2.3x10(-9, CDKN2A/2B (OR(rs10811661 = 0.74[0.66-0.82], P = 3.5x10(-8 and more modestly for IGFBP2 (OR(rs1470579 = 1.17[1.07-1.27], P = 0.0003 SNPs. These results were replicated in both Israeli Ashkenazi (577 T2D and 552 NGT and Austrian (504 T2D and 753 NGT populations (except for CDKAL1 but not in the Moroccan population (521 T2D and 423 NGT. In the overall group of French subjects (4,232 T2D and 4,595 NGT, IGFBP2 and CXCR4 synergistically interacted with (LOC38776, SLC30A8, HHEX and (NGN3, CDKN2A/2B, respectively, encoding for proteins presumably regulating pancreatic endocrine cell development and function. The T2D risk increased strongly when risk alleles, including the previously discovered T2D-associated TCF7L2 rs7903146 SNP, were combined (8.68-fold for the 14% of French individuals carrying 18 to 30 risk alleles with an allelic OR of 1.24. With an area under the ROC curve of 0.86, only 15 novel loci were necessary to discriminate French individuals susceptible to develop T2D. CONCLUSIONS/SIGNIFICANCE: In addition to TCF7L2, SLC30A8 and HHEX, initially identified by the French GWA scan, CDKAL1, IGFBP2 and CDKN2A/2B strongly associate with T2D in French individuals, and mostly in populations of Central European descent but not in Moroccan subjects. Genes expressed in the pancreas interact together and their

  16. Epigenetic Patterns in Blood Associated With Lipid Traits Predict Incident Coronary Heart Disease Events and Are Enriched for Results From Genome-Wide Association Studies

    Science.gov (United States)

    Hedman, Åsa K.; Mendelson, Michael M.; Marioni, Riccardo E.; Gustafsson, Stefan; Joehanes, Roby; Irvin, Marguerite R.; Zhi, Degui; Sandling, Johanna K.; Yao, Chen; Liu, Chunyu; Liang, Liming; Huan, Tianxiao; McRae, Allan F.; Demissie, Serkalem; Shah, Sonia; Starr, John M.; Cupples, L. Adrienne; Deloukas, Panos; Spector, Timothy D.; Sundström, Johan; Krauss, Ronald M.; Arnett, Donna K.; Deary, Ian J.; Lind, Lars; Levy, Daniel

    2017-01-01

    Background— Genome-wide association studies have identified loci influencing circulating lipid concentrations in humans; further information on novel contributing genes, pathways, and biology may be gained through studies of epigenetic modifications. Methods and Results— To identify epigenetic changes associated with lipid concentrations, we assayed genome-wide DNA methylation at cytosine–guanine dinucleotides (CpGs) in whole blood from 2306 individuals from 2 population-based cohorts, with replication of findings in 2025 additional individuals. We identified 193 CpGs associated with lipid levels in the discovery stage (P<1.08E-07) and replicated 33 (at Bonferroni-corrected P<0.05), including 25 novel CpGs not previously associated with lipids. Genes at lipid-associated CpGs were enriched in lipid and amino acid metabolism processes. A differentially methylated locus associated with triglycerides and high-density lipoprotein cholesterol (HDL-C; cg27243685; P=8.1E-26 and 9.3E-19) was associated with cis-expression of a reverse cholesterol transporter (ABCG1; P=7.2E-28) and incident cardiovascular disease events (hazard ratio per SD increment, 1.38; 95% confidence interval, 1.15–1.66; P=0.0007). We found significant cis-methylation quantitative trait loci at 64% of the 193 CpGs with an enrichment of signals from genome-wide association studies of lipid levels (PTC=0.004, PHDL-C=0.008 and Ptriglycerides=0.00003) and coronary heart disease (P=0.0007). For example, genome-wide significant variants associated with low-density lipoprotein cholesterol and coronary heart disease at APOB were cis-methylation quantitative trait loci for a low-density lipoprotein cholesterol–related differentially methylated locus. Conclusions— We report novel associations of DNA methylation with lipid levels, describe epigenetic mechanisms related to previous genome-wide association studies discoveries, and provide evidence implicating epigenetic regulation of reverse cholesterol

  17. Profiling genome-wide DNA methylation.

    Science.gov (United States)

    Yong, Wai-Shin; Hsu, Fei-Man; Chen, Pao-Yang

    2016-01-01

    DNA methylation is an epigenetic modification that plays an important role in regulating gene expression and therefore a broad range of biological processes and diseases. DNA methylation is tissue-specific, dynamic, sequence-context-dependent and trans-generationally heritable, and these complex patterns of methylation highlight the significance of profiling DNA methylation to answer biological questions. In this review, we surveyed major methylation assays, along with comparisons and biological examples, to provide an overview of DNA methylation profiling techniques. The advances in microarray and sequencing technologies make genome-wide profiling possible at a single-nucleotide or even a single-cell resolution. These profiling approaches vary in many aspects, such as DNA input, resolution, genomic region coverage, and bioinformatics analysis, and selecting a feasible method requires knowledge of these methods. We first introduce the biological background of DNA methylation and its pattern in plants, animals and fungi. We present an overview of major experimental approaches to profiling genome-wide DNA methylation and hydroxymethylation and then extend to the single-cell methylome. To evaluate these methods, we outline their strengths and weaknesses and perform comparisons across the different platforms. Due to the increasing need to compute high-throughput epigenomic data, we interrogate the computational pipeline for bisulfite sequencing data and also discuss the concept of identifying differentially methylated regions (DMRs). This review summarizes the experimental and computational concepts for profiling genome-wide DNA methylation, followed by biological examples. Overall, this review provides researchers useful guidance for the selection of a profiling method suited to specific research questions.

  18. Genome-wide identification of enhancer elements.

    Science.gov (United States)

    Tulin, Sarah; Barsi, Julius C; Bocconcelli, Carlo; Smith, Joel

    2016-01-01

    We present a prospective genome-wide regulatory element database for the sea urchin embryo and the modified chromosome capture-related methodology used to create it. The method we developed is termed GRIP-seq for genome-wide regulatory element immunoprecipitation and combines features of chromosome conformation capture, chromatin immunoprecipitation, and paired-end next-generation sequencing with molecular steps that enrich for active cis-regulatory elements associated with basal transcriptional machinery. The first GRIP-seq database, available to the community, comes from S. purpuratus 24 hpf embryos and takes advantage of the extremely well-characterized cis-regulatory elements in this system for validation. In addition, using the GRIP-seq database, we identify and experimentally validate a novel, intronic cis-regulatory element at the onecut locus. We find GRIP-seq signal sensitively identifies active cis-regulatory elements with a high signal-to-noise ratio for both distal and intronic elements. This promising GRIP-seq protocol has the potential to address a rate-limiting step in resolving comprehensive, predictive network models in all systems.

  19. Handling Permutation in Sequence Comparison: Genome-Wide Enhancer Prediction in Vertebrates by a Novel Non-Linear Alignment Scoring Principle.

    Directory of Open Access Journals (Sweden)

    Dirk Dolle

    Full Text Available Enhancers have been described to evolve by permutation without changing function. This has posed the problem of how to predict enhancer elements that are hidden from alignment-based approaches due to the loss of co-linearity. Alignment-free algorithms have been proposed as one possible solution. However, this approach is hampered by several problems inherent to its underlying working principle. Here we present a new approach, which combines the power of alignment and alignment-free techniques into one algorithm. It allows the prediction of enhancers based on the query and target sequence only, no matter whether the regulatory logic is co-linear or reshuffled. To test our novel approach, we employ it for the prediction of enhancers across the evolutionary distance of ~450Myr between human and medaka. We demonstrate its efficacy by subsequent in vivo validation resulting in 82% (9/11 of the predicted medaka regions showing reporter activity. These include five candidates with partially co-linear and four with reshuffled motif patterns. Orthology in flanking genes and conservation of the detected co-linear motifs indicates that those candidates are likely functionally equivalent enhancers. In sum, our results demonstrate that the proposed principle successfully predicts mutated as well as permuted enhancer regions at an encouragingly high rate.

  20. Power analysis for genome-wide association studies

    Directory of Open Access Journals (Sweden)

    Klein Robert J

    2007-08-01

    Full Text Available Abstract Background Genome-wide association studies are a promising new tool for deciphering the genetics of complex diseases. To choose the proper sample size and genotyping platform for such studies, power calculations that take into account genetic model, tag SNP selection, and the population of interest are required. Results The power of genome-wide association studies can be computed using a set of tag SNPs and a large number of genotyped SNPs in a representative population, such as available through the HapMap project. As expected, power increases with increasing sample size and effect size. Power also depends on the tag SNPs selected. In some cases, more power is obtained by genotyping more individuals at fewer SNPs than fewer individuals at more SNPs. Conclusion Genome-wide association studies should be designed thoughtfully, with the choice of genotyping platform and sample size being determined from careful power calculations.

  1. Genome-wide association study identifies five new schizophrenia loci.

    LENUS (Irish Health Repository)

    Ripke, Stephan

    2011-10-01

    We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded genome-wide significant associations with schizophrenia for seven loci, five of which are new (1p21.3, 2q32.3, 8p23.2, 8q21.3 and 10q24.32-q24.33) and two of which have been previously implicated (6p21.32-p22.1 and 18q21.2). The strongest new finding (P = 1.6 × 10(-11)) was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of neuronal development. Four other schizophrenia loci achieving genome-wide significance contain predicted targets of MIR137, suggesting MIR137-mediated dysregulation as a previously unknown etiologic mechanism in schizophrenia. In a joint analysis with a bipolar disorder sample (16,374 affected individuals and 14,044 controls), three loci reached genome-wide significance: CACNA1C (rs4765905, P = 7.0 × 10(-9)), ANK3 (rs10994359, P = 2.5 × 10(-8)) and the ITIH3-ITIH4 region (rs2239547, P = 7.8 × 10(-9)).

  2. Genome-wide association studies in pediatric endocrinology.

    Science.gov (United States)

    Dauber, Andrew; Hirschhorn, Joel N

    2011-01-01

    Genome-wide association (GWA) studies are a powerful tool for understanding the genetic underpinnings of human disease. In this article, we briefly review the role and findings of GWA studies in type 1 diabetes, stature, pubertal timing, obesity, and vitamin D deficiency. We then discuss the present and future implications of these findings with regards to disease prediction, uncovering basic biology, and the development of novel therapeutic agents.

  3. Statistical Approaches in Genome-Wide Association Studies

    OpenAIRE

    Yazdani, Akram

    2014-01-01

    Genome-wide association studies, GWAS, typically contain hundreds of thousands single nucleotide polymorphisms, SNPs, genotyped for few numbers of samples. The aim of these studies is to identify regions harboring SNPs or to predict the outcomes of interest. Since the number of predictors in the GWAS far exceeds the number of samples, it is impossible to analyze the data with classical statistical methods. In the current GWAS, the widely applied methods are based on single marker analysis th...

  4. Genome-wide inference of regulatory networks in Streptomyces coelicolor

    Directory of Open Access Journals (Sweden)

    Takano Eriko

    2010-10-01

    Full Text Available Abstract Background The onset of antibiotics production in Streptomyces species is co-ordinated with differentiation events. An understanding of the genetic circuits that regulate these coupled biological phenomena is essential to discover and engineer the pharmacologically important natural products made by these species. The availability of genomic tools and access to a large warehouse of transcriptome data for the model organism, Streptomyces coelicolor, provides incentive to decipher the intricacies of the regulatory cascades and develop biologically meaningful hypotheses. Results In this study, more than 500 samples of genome-wide temporal transcriptome data, comprising wild-type and more than 25 regulatory gene mutants of Streptomyces coelicolor probed across multiple stress and medium conditions, were investigated. Information based on transcript and functional similarity was used to update a previously-predicted whole-genome operon map and further applied to predict transcriptional networks constituting modules enriched in diverse functions such as secondary metabolism, and sigma factor. The predicted network displays a scale-free architecture with a small-world property observed in many biological networks. The networks were further investigated to identify functionally-relevant modules that exhibit functional coherence and a consensus motif in the promoter elements indicative of DNA-binding elements. Conclusions Despite the enormous experimental as well as computational challenges, a systems approach for integrating diverse genome-scale datasets to elucidate complex regulatory networks is beginning to emerge. We present an integrated analysis of transcriptome data and genomic features to refine a whole-genome operon map and to construct regulatory networks at the cistron level in Streptomyces coelicolor. The functionally-relevant modules identified in this study pose as potential targets for further studies and verification.

  5. Genome-Wide Detection and Analysis of Multifunctional Genes

    Science.gov (United States)

    Pritykin, Yuri; Ghersi, Dario; Singh, Mona

    2015-01-01

    Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms—H. sapiens, D. melanogaster, and S. cerevisiae—and show that, as compared to other annotated genes, genes involved in multiple biological processes possess distinct physicochemical properties, are more broadly expressed, tend to be more central in protein interaction networks, tend to be more evolutionarily conserved, and are more likely to be essential. We also find that multifunctional genes are significantly more likely to be involved in human disorders. These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes. Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality. PMID:26436655

  6. Chapter 10: Mining genome-wide genetic markers.

    Directory of Open Access Journals (Sweden)

    Xiang Zhang

    Full Text Available Genome-wide association study (GWAS aims to discover genetic factors underlying phenotypic traits. The large number of genetic factors poses both computational and statistical challenges. Various computational approaches have been developed for large scale GWAS. In this chapter, we will discuss several widely used computational approaches in GWAS. The following topics will be covered: (1 An introduction to the background of GWAS. (2 The existing computational approaches that are widely used in GWAS. This will cover single-locus, epistasis detection, and machine learning methods that have been recently developed in biology, statistic, and computer science communities. This part will be the main focus of this chapter. (3 The limitations of current approaches and future directions.

  7. Genome-wide Analysis of Gene Regulation

    DEFF Research Database (Denmark)

    Chen, Yun

    cells are capable of regulating their gene expression, so that each cell can only express a particular set of genes yielding limited numbers of proteins with specialized functions. Therefore a rigid control of differential gene expression is necessary for cellular diversity. On the other hand, aberrant...... gene regulation will disrupt the cell’s fundamental processes, which in turn can cause disease. Hence, understanding gene regulation is essential for deciphering the code of life. Along with the development of high throughput sequencing (HTS) technology and the subsequent large-scale data analysis......, genome-wide assays have increased our understanding of gene regulation significantly. This thesis describes the integration and analysis of HTS data across different important aspects of gene regulation. Gene expression can be regulated at different stages when the genetic information is passed from gene...

  8. Genome-Wide Approaches to Drosophila Heart Development

    Directory of Open Access Journals (Sweden)

    Manfred Frasch

    2016-05-01

    Full Text Available The development of the dorsal vessel in Drosophila is one of the first systems in which key mechanisms regulating cardiogenesis have been defined in great detail at the genetic and molecular level. Due to evolutionary conservation, these findings have also provided major inputs into studies of cardiogenesis in vertebrates. Many of the major components that control Drosophila cardiogenesis were discovered based on candidate gene approaches and their functions were defined by employing the outstanding genetic tools and molecular techniques available in this system. More recently, approaches have been taken that aim to interrogate the entire genome in order to identify novel components and describe genomic features that are pertinent to the regulation of heart development. Apart from classical forward genetic screens, the availability of the thoroughly annotated Drosophila genome sequence made new genome-wide approaches possible, which include the generation of massive numbers of RNA interference (RNAi reagents that were used in forward genetic screens, as well as studies of the transcriptomes and proteomes of the developing heart under normal and experimentally manipulated conditions. Moreover, genome-wide chromatin immunoprecipitation experiments have been performed with the aim to define the full set of genomic binding sites of the major cardiogenic transcription factors, their relevant target genes, and a more complete picture of the regulatory network that drives cardiogenesis. This review will give an overview on these genome-wide approaches to Drosophila heart development and on computational analyses of the obtained information that ultimately aim to provide a description of this process at the systems level.

  9. A genome-wide association study of aging.

    Science.gov (United States)

    Walter, Stefan; Atzmon, Gil; Demerath, Ellen W; Garcia, Melissa E; Kaplan, Robert C; Kumari, Meena; Lunetta, Kathryn L; Milaneschi, Yuri; Tanaka, Toshiko; Tranah, Gregory J; Völker, Uwe; Yu, Lei; Arnold, Alice; Benjamin, Emelia J; Biffar, Reiner; Buchman, Aron S; Boerwinkle, Eric; Couper, David; De Jager, Philip L; Evans, Denis A; Harris, Tamara B; Hoffmann, Wolfgang; Hofman, Albert; Karasik, David; Kiel, Douglas P; Kocher, Thomas; Kuningas, Maris; Launer, Lenore J; Lohman, Kurt K; Lutsey, Pamela L; Mackenbach, Johan; Marciante, Kristin; Psaty, Bruce M; Reiman, Eric M; Rotter, Jerome I; Seshadri, Sudha; Shardell, Michelle D; Smith, Albert V; van Duijn, Cornelia; Walston, Jeremy; Zillikens, M Carola; Bandinelli, Stefania; Baumeister, Sebastian E; Bennett, David A; Ferrucci, Luigi; Gudnason, Vilmundur; Kivimaki, Mika; Liu, Yongmei; Murabito, Joanne M; Newman, Anne B; Tiemeier, Henning; Franceschini, Nora

    2011-11-01

    Human longevity and healthy aging show moderate heritability (20%-50%). We conducted a meta-analysis of genome-wide association studies from 9 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium for 2 outcomes: (1) all-cause mortality, and (2) survival free of major disease or death. No single nucleotide polymorphism (SNP) was a genome-wide significant predictor of either outcome (p < 5 × 10(-8)). We found 14 independent SNPs that predicted risk of death, and 8 SNPs that predicted event-free survival (p < 10(-5)). These SNPs are in or near genes that are highly expressed in the brain (HECW2, HIP1, BIN2, GRIA1), genes involved in neural development and function (KCNQ4, LMO4, GRIA1, NETO1) and autophagy (ATG4C), and genes that are associated with risk of various diseases including cancer and Alzheimer's disease. In addition to considerable overlap between the traits, pathway and network analysis corroborated these findings. These findings indicate that variation in genes involved in neurological processes may be an important factor in regulating aging free of major disease and achieving longevity.

  10. Genome-wide association between DNA methylation and alternative splicing in an invertebrate

    Directory of Open Access Journals (Sweden)

    Flores Kevin

    2012-09-01

    Full Text Available Abstract Background Gene bodies are the most evolutionarily conserved targets of DNA methylation in eukaryotes. However, the regulatory functions of gene body DNA methylation remain largely unknown. DNA methylation in insects appears to be primarily confined to exons. Two recent studies in Apis mellifera (honeybee and Nasonia vitripennis (jewel wasp analyzed transcription and DNA methylation data for one gene in each species to demonstrate that exon-specific DNA methylation may be associated with alternative splicing events. In this study we investigated the relationship between DNA methylation, alternative splicing, and cross-species gene conservation on a genome-wide scale using genome-wide transcription and DNA methylation data. Results We generated RNA deep sequencing data (RNA-seq to measure genome-wide mRNA expression at the exon- and gene-level. We produced a de novo transcriptome from this RNA-seq data and computationally predicted splice variants for the honeybee genome. We found that exons that are included in transcription are higher methylated than exons that are skipped during transcription. We detected enrichment for alternative splicing among methylated genes compared to unmethylated genes using fisher’s exact test. We performed a statistical analysis to reveal that the presence of DNA methylation or alternative splicing are both factors associated with a longer gene length and a greater number of exons in genes. In concordance with this observation, a conservation analysis using BLAST revealed that each of these factors is also associated with higher cross-species gene conservation. Conclusions This study constitutes the first genome-wide analysis exhibiting a positive relationship between exon-level DNA methylation and mRNA expression in the honeybee. Our finding that methylated genes are enriched for alternative splicing suggests that, in invertebrates, exon-level DNA methylation may play a role in the construction of splice

  11. Genome-wide analysis correlates Ayurveda Prakriti.

    Science.gov (United States)

    Govindaraj, Periyasamy; Nizamuddin, Sheikh; Sharath, Anugula; Jyothi, Vuskamalla; Rotti, Harish; Raval, Ritu; Nayak, Jayakrishna; Bhat, Balakrishna K; Prasanna, B V; Shintre, Pooja; Sule, Mayura; Joshi, Kalpana S; Dedge, Amrish P; Bharadwaj, Ramachandra; Gangadharan, G G; Nair, Sreekumaran; Gopinath, Puthiya M; Patwardhan, Bhushan; Kondaiah, Paturu; Satyamoorthy, Kapaettu; Valiathan, Marthanda Varma Sankaran; Thangaraj, Kumarasamy

    2015-10-29

    The practice of Ayurveda, the traditional medicine of India, is based on the concept of three major constitutional types (Vata, Pitta and Kapha) defined as "Prakriti". To the best of our knowledge, no study has convincingly correlated genomic variations with the classification of Prakriti. In the present study, we performed genome-wide SNP (single nucleotide polymorphism) analysis (Affymetrix, 6.0) of 262 well-classified male individuals (after screening 3416 subjects) belonging to three Prakritis. We found 52 SNPs (p ≤ 1 × 10(-5)) were significantly different between Prakritis, without any confounding effect of stratification, after 10(6) permutations. Principal component analysis (PCA) of these SNPs classified 262 individuals into their respective groups (Vata, Pitta and Kapha) irrespective of their ancestry, which represent its power in categorization. We further validated our finding with 297 Indian population samples with known ancestry. Subsequently, we found that PGM1 correlates with phenotype of Pitta as described in the ancient text of Caraka Samhita, suggesting that the phenotypic classification of India's traditional medicine has a genetic basis; and its Prakriti-based practice in vogue for many centuries resonates with personalized medicine.

  12. Layers of epistasis: genome-wide regulatory networks and network approaches to genome-wide association studies

    Science.gov (United States)

    Cowper-Sal·lari, Richard; Cole, Michael D.; Karagas, Margaret R.; Lupien, Mathieu; Moore, Jason H.

    2010-01-01

    The conceptual foundation of the genome-wide association study (GWAS) has advanced unchecked since its conception. A revision might seem premature as the potential of GWAS has not been fully realized. Multiple technical and practical limitations need to be overcome before GWAS can be fairly criticized. But with the completion of hundreds of studies and a deeper understanding of the genetic architecture of disease, warnings are being raised. The results compiled to date indicate that risk-associated variants lie predominantly in non-coding regions of the genome. Additionally, alternative methodologies are uncovering large and heterogeneous sets of rare variants underlying disease. The fear is that, even in its fulfilment, the current GWAS paradigm might be incapable of dissecting all kinds of phenotypes. In the following text we review several initiatives that aim to overcome these limitations. The overarching theme of these studies is the inclusion of biological knowledge to both the analysis and interpretation of genotyping data. GWAS is uninformed of biology by design and although there is some virtue in its simplicity it is also its most conspicuous deficiency. We propose a framework in which to integrate these novel approaches, both empirical and theoretical, in the form of a genome-wide regulatory network (GWRN). By processing experimental data into networks, emerging data types based on chromatin-immunoprecipitation are made computationally tractable. This will give GWAS re-analysis efforts the most current and relevant substrates, and root them firmly on our knowledge of human disease. PMID:21197657

  13. Genome-wide association studies in pharmacogenomics of antidepressants.

    Science.gov (United States)

    Lin, Eugene; Lane, Hsien-Yuan

    2015-01-01

    Major depressive disorder (MDD) is one of the most common psychiatric disorders worldwide. Doctors must prescribe antidepressants based on educated guesses due to the fact that it is unmanageable to predict the effectiveness of any particular antidepressant in an individual patient. With the recent advent of scientific research, the genome-wide association study (GWAS) is extensively employed to analyze hundreds of thousands of single nucleotide polymorphisms by high-throughput genotyping technologies. In addition to the candidate-gene approach, the GWAS approach has recently been utilized to investigate the determinants of antidepressant response to therapy. In this study, we reviewed GWAS studies, their limitations and future directions with respect to the pharmacogenomics of antidepressants in MDD.

  14. Genome-wide measurement of RNA folding energies.

    Science.gov (United States)

    Wan, Yue; Qu, Kun; Ouyang, Zhengqing; Kertesz, Michael; Li, Jun; Tibshirani, Robert; Makino, Debora L; Nutter, Robert C; Segal, Eran; Chang, Howard Y

    2012-10-26

    RNA structural transitions are important in the function and regulation of RNAs. Here, we reveal a layer of transcriptome organization in the form of RNA folding energies. By probing yeast RNA structures at different temperatures, we obtained relative melting temperatures (Tm) for RNA structures in over 4000 transcripts. Specific signatures of RNA Tm demarcated the polarity of mRNA open reading frames and highlighted numerous candidate regulatory RNA motifs in 3' untranslated regions. RNA Tm distinguished noncoding versus coding RNAs and identified mRNAs with distinct cellular functions. We identified thousands of putative RNA thermometers, and their presence is predictive of the pattern of RNA decay in vivo during heat shock. The exosome complex recognizes unpaired bases during heat shock to degrade these RNAs, coupling intrinsic structural stabilities to gene regulation. Thus, genome-wide structural dynamics of RNA can parse functional elements of the transcriptome and reveal diverse biological insights.

  15. Genome-wide detection of predicted non-coding RNAs in Rhizobium etli expressed during free-living and host-associated growth using a high-resolution tiling array

    Directory of Open Access Journals (Sweden)

    Thijs Inge M

    2010-01-01

    Full Text Available Abstract Background Non-coding RNAs (ncRNAs play a crucial role in the intricate regulation of bacterial gene expression, allowing bacteria to quickly adapt to changing environments. In the past few years, a growing number of regulatory RNA elements have been predicted by computational methods, mostly in well-studied γ-proteobacteria but lately in several α-proteobacteria as well. Here, we have compared an extensive compilation of these non-coding RNA predictions to intergenic expression data of a whole-genome high-resolution tiling array in the soil-dwelling α-proteobacterium Rhizobium etli. Results Expression of 89 candidate ncRNAs was detected, both on the chromosome and on the six megaplasmids encompassing the R. etli genome. Of these, 11 correspond to functionally well characterized ncRNAs, 12 were previously identified in other α-proteobacteria but are as yet uncharacterized and 66 were computationally predicted earlier but had not been experimentally identified and were therefore classified as novel ncRNAs. The latter comprise 17 putative sRNAs and 49 putative cis-regulatory ncRNAs. A selection of these candidate ncRNAs was validated by RT-qPCR, Northern blotting and 5' RACE, confirming the existence of 4 ncRNAs. Interestingly, individual transcript levels of numerous ncRNAs varied during free-living growth and during interaction with the eukaryotic host plant, pointing to possible ncRNA-dependent regulation of these specialized processes. Conclusions Our data support the practical value of previous ncRNA prediction algorithms and significantly expand the list of candidate ncRNAs encoded in the intergenic regions of R. etli and, by extension, of α-proteobacteria. Moreover, we show high-resolution tiling arrays to be suitable tools for studying intergenic ncRNA transcription profiles across the genome. The differential expression levels of some of these ncRNAs may indicate a role in adaptation to changing environmental conditions.

  16. Genome-wide association and genomic selection in animal breeding.

    Science.gov (United States)

    Hayes, Ben; Goddard, Mike

    2010-11-01

    Results from genome-wide association studies in livestock, and humans, has lead to the conclusion that the effect of individual quantitative trait loci (QTL) on complex traits, such as yield, are likely to be small; therefore, a large number of QTL are necessary to explain genetic variation in these traits. Given this genetic architecture, gains from marker-assisted selection (MAS) programs using only a small number of DNA markers to trace a limited number of QTL is likely to be small. This has lead to the development of alternative technology for using the available dense single nucleotide polymorphism (SNP) information, called genomic selection. Genomic selection uses a genome-wide panel of dense markers so that all QTL are likely to be in linkage disequilibrium with at least one SNP. The genomic breeding values are predicted to be the sum of the effect of these SNPs across the entire genome. In dairy cattle breeding, the accuracy of genomic estimated breeding values (GEBV) that can be achieved and the fact that these are available early in life have lead to rapid adoption of the technology. Here, we discuss the design of experiments necessary to achieve accurate prediction of GEBV in future generations in terms of the number of markers necessary and the size of the reference population where marker effects are estimated. We also present a simple method for implementing genomic selection using a genomic relationship matrix. Future challenges discussed include using whole genome sequence data to improve the accuracy of genomic selection and management of inbreeding through genomic relationships.

  17. A genome-wide methylation study on obesity

    Science.gov (United States)

    Xu, Xiaojing; Su, Shaoyong; Barnes, Vernon A.; De Miguel, Carmen; Pollock, Jennifer; Ownby, Dennis; Shi, Huidong; Zhu, Haidong; Snieder, Harold; Wang, Xiaoling

    2013-01-01

    Besides differential methylation, DNA methylation variation has recently been proposed and demonstrated to be a potential contributing factor to cancer risk. Here we aim to examine whether differential variability in methylation is also an important feature of obesity, a typical non-malignant common complex disease. We analyzed genome-wide methylation profiles of over 470,000 CpGs in peripheral blood samples from 48 obese and 48 lean African-American youth aged 14–20 y old. A substantial number of differentially variable CpG sites (DVCs), using statistics based on variances, as well as a substantial number of differentially methylated CpG sites (DMCs), using statistics based on means, were identified. Similar to the findings in cancers, DVCs generally exhibited an outlier structure and were more variable in cases than in controls. By randomly splitting the current sample into a discovery and validation set, we observed that both the DVCs and DMCs identified from the first set could independently predict obesity status in the second set. Furthermore, both the genes harboring DMCs and the genes harboring DVCs showed significant enrichment of genes identified by genome-wide association studies on obesity and related diseases, such as hypertension, dyslipidemia, type 2 diabetes and certain types of cancers, supporting their roles in the etiology and pathogenesis of obesity. We generalized the recent finding on methylation variability in cancer research to obesity and demonstrated that differential variability is also an important feature of obesity-related methylation changes. Future studies on the epigenetics of obesity will benefit from both statistics based on means and statistics based on variances. PMID:23644594

  18. Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function

    NARCIS (Netherlands)

    D.B. Hancock (Dana); M. Eijgelsheim (Mark); J.B. Wilk (Jemma); S.A. Gharib (Sina); L.R. Loehr (Laura); K. Marciante (Kristin); N. Franceschini (Nora); Y.M.T.A. van Durme; T.H. Chen; R.G. Barr (Graham); M.B. Schabath (Matthew); D.J. Couper (David); G.G. Brusselle (Guy); B.M. Psaty (Bruce); P. Tikka-Kleemola (Päivi); J.I. Rotter (Jerome); A.G. Uitterlinden (André); A. Hofman (Albert); N.M. Punjabi (Naresh); F. Rivadeneira Ramirez (Fernando); A.C. Morrison (Alanna); P.L. Enright (Paul); K.E. North (Kari); S.R. Heckbert (Susan); T. Lumley (Thomas); B.H.Ch. Stricker (Bruno); G.T. O'Connor (George); S.J. London (Stephanie)

    2010-01-01

    textabstractSpirometric measures of lung function are heritable traits that reflect respiratory health and predict morbidity and mortality. We meta-analyzed genome-wide association studies for two clinically important lung-function measures: forced expiratory volume in the first second (FEV1) and it

  19. Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function

    NARCIS (Netherlands)

    D.B. Hancock (Dana); M. Eijgelsheim (Mark); J.B. Wilk (Jemma); S.A. Gharib (Sina); L.R. Loehr (Laura); K. Marciante (Kristin); N. Franceschini (Nora); Y.M.T.A. van Durme; T.H. Chen; R.G. Barr (Graham); M.B. Schabath (Matthew); D.J. Couper (David); G.G. Brusselle (Guy); B.M. Psaty (Bruce); P. Tikka-Kleemola (Päivi); J.I. Rotter (Jerome); A.G. Uitterlinden (André); A. Hofman (Albert); N.M. Punjabi (Naresh); F. Rivadeneira Ramirez (Fernando); A.C. Morrison (Alanna); P.L. Enright (Paul); K.E. North (Kari); S.R. Heckbert (Susan); T. Lumley (Thomas); B.H.Ch. Stricker (Bruno); G.T. O'Connor (George); S.J. London (Stephanie)

    2010-01-01

    textabstractSpirometric measures of lung function are heritable traits that reflect respiratory health and predict morbidity and mortality. We meta-analyzed genome-wide association studies for two clinically important lung-function measures: forced expiratory volume in the first second (FEV1) and

  20. Comparative analysis of methods for genome-wide nucleosome cartography.

    Science.gov (United States)

    Quintales, Luis; Vázquez, Enrique; Antequera, Francisco

    2015-07-01

    Nucleosomes contribute to compacting the genome into the nucleus and regulate the physical access of regulatory proteins to DNA either directly or through the epigenetic modifications of the histone tails. Precise mapping of nucleosome positioning across the genome is, therefore, essential to understanding the genome regulation. In recent years, several experimental protocols have been developed for this purpose that include the enzymatic digestion, chemical cleavage or immunoprecipitation of chromatin followed by next-generation sequencing of the resulting DNA fragments. Here, we compare the performance and resolution of these methods from the initial biochemical steps through the alignment of the millions of short-sequence reads to a reference genome to the final computational analysis to generate genome-wide maps of nucleosome occupancy. Because of the lack of a unified protocol to process data sets obtained through the different approaches, we have developed a new computational tool (NUCwave), which facilitates their analysis, comparison and assessment and will enable researchers to choose the most suitable method for any particular purpose. NUCwave is freely available at http://nucleosome.usal.es/nucwave along with a step-by-step protocol for its use. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  1. Genome-wide association study of clinical dimensions of schizophrenia

    DEFF Research Database (Denmark)

    Fanous, Ayman H; Zhou, Baiyu; Aggen, Steven H;

    2012-01-01

    Multiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia....

  2. Cancer genetic association studies in the genome-wide age

    OpenAIRE

    Savage, Sharon A

    2008-01-01

    Genome-wide association studies of hundreds of thousands of SNPs have led to a deluge of studies of genetic variation in cancer and other common diseases. Large case–control and cohort studies have identified novel SNPs as markers of cancer risk. Genome-wide association study SNP data have also advanced understanding of population-specific genetic variation. While studies of risk profiles, combinations of SNPs that may increase cancer risk, are not yet clinically applicable, future, large-sca...

  3. Genome-wide polymorphisms show unexpected targets of natural selection

    OpenAIRE

    Pespeni, Melissa H.; Garfield, David A.; Manier, Mollie K; Palumbi, Stephen R.

    2011-01-01

    Natural selection can act on all the expressed genes of an individual, leaving signatures of genetic differentiation or diversity at many loci across the genome. New power to assay these genome-wide effects of selection comes from associating multi-locus patterns of polymorphism with gene expression and function. Here, we performed one of the first genome-wide surveys in a marine species, comparing purple sea urchins, Strongylocentrotus purpuratus, from two distant locations along the species...

  4. Genome-wide association study of multiplex schizophrenia pedigrees

    DEFF Research Database (Denmark)

    Levinson, Douglas F; Shi, Jianxin; Wang, Kai

    2012-01-01

    The authors used a genome-wide association study (GWAS) of multiply affected families to investigate the association of schizophrenia to common single-nucleotide polymorphisms (SNPs) and rare copy number variants (CNVs).......The authors used a genome-wide association study (GWAS) of multiply affected families to investigate the association of schizophrenia to common single-nucleotide polymorphisms (SNPs) and rare copy number variants (CNVs)....

  5. PEPIS: A Pipeline for Estimating Epistatic Effects in Quantitative Trait Locus Mapping and Genome-Wide Association Studies.

    Directory of Open Access Journals (Sweden)

    Wenchao Zhang

    2016-05-01

    Full Text Available The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the 'missing heritability,' which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS, for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.

  6. PEPIS: A Pipeline for Estimating Epistatic Effects in Quantitative Trait Locus Mapping and Genome-Wide Association Studies.

    Science.gov (United States)

    Zhang, Wenchao; Dai, Xinbin; Wang, Qishan; Xu, Shizhong; Zhao, Patrick X

    2016-05-01

    The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the 'missing heritability,' which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS), for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.

  7. A method for detecting epistasis in genome-wide studies using case-control multi-locus association analysis

    OpenAIRE

    Galan Jose; Quintas Antonio; Royo Jose; Sáez María; Bermudo Fernando; González-Pérez Antonio; Gayán Javier; Morón Francisco; Ramirez-Lorca Reposo; Real Luis; Ruiz Agustín

    2008-01-01

    Abstract Background The difficulty in elucidating the genetic basis of complex diseases roots in the many factors that can affect the development of a disease. Some of these genetic effects may interact in complex ways, proving undetectable by current single-locus methodology. Results We have developed an analysis tool called Hypothesis Free Clinical Cloning (HFCC) to search for genome-wide epistasis in a case-control design. HFCC combines a relatively fast computing algorithm for genome-wide...

  8. The Challenges of Genome-Wide Interaction Studies: Lessons to Learn from the Analysis of HDL Blood Levels

    OpenAIRE

    van Leeuwen, Elisabeth M.; Smouter, Françoise A. S.; Tony Kam-Thong; Nazanin Karbalai; Smith, Albert V.; Harris, Tamara B.; Launer, Lenore J.; Sitlani, Colleen M.; Guo Li; Brody, Jennifer A; Bis, Joshua C.; White, Charles C.; Alok Jaiswal; Oostra, Ben A.; Albert Hofman

    2014-01-01

    Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNPxSNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform l...

  9. Reconstructing Roma history from genome-wide data.

    Directory of Open Access Journals (Sweden)

    Priya Moorjani

    Full Text Available The Roma people, living throughout Europe and West Asia, are a diverse population linked by the Romani language and culture. Previous linguistic and genetic studies have suggested that the Roma migrated into Europe from South Asia about 1,000-1,500 years ago. Genetic inferences about Roma history have mostly focused on the Y chromosome and mitochondrial DNA. To explore what additional information can be learned from genome-wide data, we analyzed data from six Roma groups that we genotyped at hundreds of thousands of single nucleotide polymorphisms (SNPs. We estimate that the Roma harbor about 80% West Eurasian ancestry-derived from a combination of European and South Asian sources-and that the date of admixture of South Asian and European ancestry was about 850 years before present. We provide evidence for Eastern Europe being a major source of European ancestry, and North-west India being a major source of the South Asian ancestry in the Roma. By computing allele sharing as a measure of linkage disequilibrium, we estimate that the migration of Roma out of the Indian subcontinent was accompanied by a severe founder event, which appears to have been followed by a major demographic expansion after the arrival in Europe.

  10. Reconstructing Roma History from Genome-Wide Data

    Science.gov (United States)

    Moorjani, Priya; Patterson, Nick; Loh, Po-Ru; Lipson, Mark; Kisfali, Péter; Melegh, Bela I.; Bonin, Michael; Kádaši, Ľudevít; Rieß, Olaf; Berger, Bonnie; Reich, David; Melegh, Béla

    2013-01-01

    The Roma people, living throughout Europe and West Asia, are a diverse population linked by the Romani language and culture. Previous linguistic and genetic studies have suggested that the Roma migrated into Europe from South Asia about 1,000–1,500 years ago. Genetic inferences about Roma history have mostly focused on the Y chromosome and mitochondrial DNA. To explore what additional information can be learned from genome-wide data, we analyzed data from six Roma groups that we genotyped at hundreds of thousands of single nucleotide polymorphisms (SNPs). We estimate that the Roma harbor about 80% West Eurasian ancestry–derived from a combination of European and South Asian sources–and that the date of admixture of South Asian and European ancestry was about 850 years before present. We provide evidence for Eastern Europe being a major source of European ancestry, and North-west India being a major source of the South Asian ancestry in the Roma. By computing allele sharing as a measure of linkage disequilibrium, we estimate that the migration of Roma out of the Indian subcontinent was accompanied by a severe founder event, which appears to have been followed by a major demographic expansion after the arrival in Europe. PMID:23516520

  11. Genome-wide analyses of small noncoding RNAs in streptococci

    Directory of Open Access Journals (Sweden)

    Nadja ePatenge

    2015-05-01

    Full Text Available Streptococci represent a diverse group of Gram-positive bacteria, which colonize a wide range of hosts among animals and humans. Streptococcal species occur as commensal as well as pathogenic organisms. Many of the pathogenic species can cause severe, invasive infections in their hosts leading to a high morbidity and mortality. The consequence is a tremendous suffering on the part of men and livestock besides the significant financial burden in the agricultural and healthcare sectors. An environmentally stimulated and tightly controlled expression of virulence factor genes is of fundamental importance for streptococcal pathogenicity. Bacterial small noncoding RNAs (sRNAs modulate the expression of genes involved in stress response, sugar metabolism, surface composition, and other properties that are related to bacterial virulence. Even though the regulatory character is shared by this class of RNAs, variation on the molecular level results in a high diversity of functional mechanisms. The knowledge about the role of sRNAs in streptococci is still limited, but in recent years, genome-wide screens for sRNAs have been conducted in an increasing number of species. Bioinformatics prediction approaches have been employed as well as expression analyses by classical array techniques or next generation sequencing. This review will give an overview of whole genome screens for sRNAs in streptococci with a focus on describing the different methods and comparing their outcome considering sRNA conservation among species, functional similarities, and relevance for streptococcal infection.

  12. Improved statistics for genome-wide interaction analysis.

    Science.gov (United States)

    Ueki, Masao; Cordell, Heather J

    2012-01-01

    Recently, Wu and colleagues [1] proposed two novel statistics for genome-wide interaction analysis using case/control or case-only data. In computer simulations, their proposed case/control statistic outperformed competing approaches, including the fast-epistasis option in PLINK and logistic regression analysis under the correct model; however, reasons for its superior performance were not fully explored. Here we investigate the theoretical properties and performance of Wu et al.'s proposed statistics and explain why, in some circumstances, they outperform competing approaches. Unfortunately, we find minor errors in the formulae for their statistics, resulting in tests that have higher than nominal type 1 error. We also find minor errors in PLINK's fast-epistasis and case-only statistics, although theory and simulations suggest that these errors have only negligible effect on type 1 error. We propose adjusted versions of all four statistics that, both theoretically and in computer simulations, maintain correct type 1 error rates under the null hypothesis. We also investigate statistics based on correlation coefficients that maintain similar control of type 1 error. Although designed to test specifically for interaction, we show that some of these previously-proposed statistics can, in fact, be sensitive to main effects at one or both loci, particularly in the presence of linkage disequilibrium. We propose two new "joint effects" statistics that, provided the disease is rare, are sensitive only to genuine interaction effects. In computer simulations we find, in most situations considered, that highest power is achieved by analysis under the correct genetic model. Such an analysis is unachievable in practice, as we do not know this model. However, generally high power over a wide range of scenarios is exhibited by our joint effects and adjusted Wu statistics. We recommend use of these alternative or adjusted statistics and urge caution when using Wu et al

  13. Quantitative models of the mechanisms that control genome-wide patterns of transcription factor binding during early Drosophila development.

    Directory of Open Access Journals (Sweden)

    Tommy Kaplan

    2011-02-01

    Full Text Available Transcription factors that drive complex patterns of gene expression during animal development bind to thousands of genomic regions, with quantitative differences in binding across bound regions mediating their activity. While we now have tools to characterize the DNA affinities of these proteins and to precisely measure their genome-wide distribution in vivo, our understanding of the forces that determine where, when, and to what extent they bind remains primitive. Here we use a thermodynamic model of transcription factor binding to evaluate the contribution of different biophysical forces to the binding of five regulators of early embryonic anterior-posterior patterning in Drosophila melanogaster. Predictions based on DNA sequence and in vitro protein-DNA affinities alone achieve a correlation of ∼0.4 with experimental measurements of in vivo binding. Incorporating cooperativity and competition among the five factors, and accounting for spatial patterning by modeling binding in every nucleus independently, had little effect on prediction accuracy. A major source of error was the prediction of binding events that do not occur in vivo, which we hypothesized reflected reduced accessibility of chromatin. To test this, we incorporated experimental measurements of genome-wide DNA accessibility into our model, effectively restricting predicted binding to regions of open chromatin. This dramatically improved our predictions to a correlation of 0.6-0.9 for various factors across known target genes. Finally, we used our model to quantify the roles of DNA sequence, accessibility, and binding competition and cooperativity. Our results show that, in regions of open chromatin, binding can be predicted almost exclusively by the sequence specificity of individual factors, with a minimal role for protein interactions. We suggest that a combination of experimentally determined chromatin accessibility data and simple computational models of transcription

  14. A novel statistic for genome-wide interaction analysis.

    Science.gov (United States)

    Wu, Xuesen; Dong, Hua; Luo, Li; Zhu, Yun; Peng, Gang; Reveille, John D; Xiong, Momiao

    2010-09-23

    Although great progress in genome-wide association studies (GWAS) has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked). The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDRanalysis is a valuable tool for finding remaining missing heritability unexplained by the current GWAS, and the developed novel statistic is able to search significant interaction between SNPs across the genome. Real data analysis showed that the results of genome-wide interaction analysis can be replicated in two independent studies.

  15. A Genome-Wide Scan for Breast Cancer Risk Haplotypes among African American Women

    Science.gov (United States)

    Song, Chi; Chen, Gary K.; Millikan, Robert C.; Ambrosone, Christine B.; John, Esther M.; Bernstein, Leslie; Zheng, Wei; Hu, Jennifer J.; Ziegler, Regina G.; Nyante, Sarah; Bandera, Elisa V.; Ingles, Sue A.; Press, Michael F.; Deming, Sandra L.; Rodriguez-Gil, Jorge L.; Chanock, Stephen J.; Wan, Peggy; Sheng, Xin; Pooler, Loreall C.; Van Den Berg, David J.; Le Marchand, Loic; Kolonel, Laurence N.; Henderson, Brian E.; Haiman, Chris A.; Stram, Daniel O.

    2013-01-01

    Genome-wide association studies (GWAS) simultaneously investigating hundreds of thousands of single nucleotide polymorphisms (SNP) have become a powerful tool in the investigation of new disease susceptibility loci. Haplotypes are sometimes thought to be superior to SNPs and are promising in genetic association analyses. The application of genome-wide haplotype analysis, however, is hindered by the complexity of haplotypes themselves and sophistication in computation. We systematically analyzed the haplotype effects for breast cancer risk among 5,761 African American women (3,016 cases and 2,745 controls) using a sliding window approach on the genome-wide scale. Three regions on chromosomes 1, 4 and 18 exhibited moderate haplotype effects. Furthermore, among 21 breast cancer susceptibility loci previously established in European populations, 10p15 and 14q24 are likely to harbor novel haplotype effects. We also proposed a heuristic of determining the significance level and the effective number of independent tests by the permutation analysis on chromosome 22 data. It suggests that the effective number was approximately half of the total (7,794 out of 15,645), thus the half number could serve as a quick reference to evaluating genome-wide significance if a similar sliding window approach of haplotype analysis is adopted in similar populations using similar genotype density. PMID:23468962

  16. A novel statistic for genome-wide interaction analysis.

    Directory of Open Access Journals (Sweden)

    Xuesen Wu

    2010-09-01

    Full Text Available Although great progress in genome-wide association studies (GWAS has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked. The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR<0.001 and 0.001genome-wide interaction analysis is a valuable tool for finding remaining missing heritability unexplained by the current GWAS, and the developed novel statistic is able to search significant interaction between SNPs across the genome. Real data analysis showed that the results of genome-wide interaction analysis can be replicated in two independent studies.

  17. Genome-wide prediction of interferon family members of tree shrew and their molecular characteristics analysis%树鼩干扰素家族的基本构成及分子特征分析

    Institute of Scientific and Technical Information of China (English)

    李明利; 田巍威; 高跃东; 郭彦; 黄京飞; 张华堂

    2012-01-01

    Interferons (IFNs) represent proteins with antiviral activities that are secreted from cells in response to a variety of stimuli. In addition to antiviral, antibacterial and anti-parasitic host-defense functions they are now also recognized as crucial regulators of cell proliferation, differentiation, survival and death as well as activators of specialized cell functions particularly in the immune system and play important roles in infectious and inflammatory diseases, autoimmunity and cancer. Tree shrews (Tupaia belangeri) were found to be susceptible to several human viruses and therefore are widely regarded as good models for analyzing mechanism of human diseases. In this report, we have forecasted the interferon family members of tree shrew from its genome mainly using the methods like Blast (whole genome shotgun sequence) and gene prediction. Our data show that tree shrew interferon system includes: type I IFN: a (five subtypes), β, ω,κ, ε,δ; type II IFN: y; type III IFN: λ1, λ2/3. Furthermore, the predicted structures of a and X have similar character with those of other mammals. However, there are some differences in cysteine position and N-glycosylation numbers between human and Tree shrew IFNs. These results provide fundamental basis for further molecular cloning and function analysis of tree shrew IFNs in future.%干扰素(IFN)是在“危险信号”刺激下,由细胞分泌的具有抗病毒、抗肿瘤、抑制细胞增殖和免疫调节等多重作用的糖蛋白家族,在机体免疫系统中具有重要地位.树鼩作为多种人类疾病研究模型的前景已受到广泛关注,但对其IFN家族的研究尚属空白.该研究在现有的树鼩全基因组数据基础上,应用大片段核酸序列比对、基因预测等方法,对树鼩IFN家族的基本构成和分子特征进行预测和分析.结果显示,树鼩具有Ⅰ型IFN:α(5个亚型)、β、ω、κ、ε、δ;Ⅱ型IFN-γ; Ⅲ型IFN:IFN-λ1、λ2/3,所编码的氨基酸序列

  18. Genome-Wide Architecture of Disease Resistance Genes in Lettuce.

    Science.gov (United States)

    Christopoulou, Marilena; Wo, Sebastian Reyes-Chin; Kozik, Alex; McHale, Leah K; Truco, Maria-Jose; Wroblewski, Tadeusz; Michelmore, Richard W

    2015-10-08

    Genome-wide motif searches identified 1134 genes in the lettuce reference genome of cv. Salinas that are potentially involved in pathogen recognition, of which 385 were predicted to encode nucleotide binding-leucine rich repeat receptor (NLR) proteins. Using a maximum-likelihood approach, we grouped the NLRs into 25 multigene families and 17 singletons. Forty-one percent of these NLR-encoding genes belong to three families, the largest being RGC16 with 62 genes in cv. Salinas. The majority of NLR-encoding genes are located in five major resistance clusters (MRCs) on chromosomes 1, 2, 3, 4, and 8 and cosegregate with multiple disease resistance phenotypes. Most MRCs contain primarily members of a single NLR gene family but a few are more complex. MRC2 spans 73 Mb and contains 61 NLRs of six different gene families that cosegregate with nine disease resistance phenotypes. MRC3, which is 25 Mb, contains 22 RGC21 genes and colocates with Dm13. A library of 33 transgenic RNA interference tester stocks was generated for functional analysis of NLR-encoding genes that cosegregated with disease resistance phenotypes in each of the MRCs. Members of four NLR-encoding families, RGC1, RGC2, RGC21, and RGC12 were shown to be required for 16 disease resistance phenotypes in lettuce. The general composition of MRCs is conserved across different genotypes; however, the specific repertoire of NLR-encoding genes varied particularly of the rapidly evolving Type I genes. These tester stocks are valuable resources for future analyses of additional resistance phenotypes. Copyright © 2015 Christopoulou et al.

  19. BlueSNP: R package for highly scalable genome-wide association studies using Hadoop clusters.

    Science.gov (United States)

    Huang, Hailiang; Tata, Sandeep; Prill, Robert J

    2013-01-01

    Computational workloads for genome-wide association studies (GWAS) are growing in scale and complexity outpacing the capabilities of single-threaded software designed for personal computers. The BlueSNP R package implements GWAS statistical tests in the R programming language and executes the calculations across computer clusters configured with Apache Hadoop, a de facto standard framework for distributed data processing using the MapReduce formalism. BlueSNP makes computationally intensive analyses, such as estimating empirical p-values via data permutation, and searching for expression quantitative trait loci over thousands of genes, feasible for large genotype-phenotype datasets. http://github.com/ibm-bioinformatics/bluesnp

  20. Genome-wide gene expression analysis of anguillid herpesvirus 1

    NARCIS (Netherlands)

    Beurden, van S.J.; Peeters, B.P.H.; Rottier, P.J.M.; Davison, A.A.; Engelsma, M.Y.

    2013-01-01

    Background Whereas temporal gene expression in mammalian herpesviruses has been studied extensively, little is known about gene expression in fish herpesviruses. Here we report a genome-wide transcription analysis of a fish herpesvirus, anguillid herpesvirus 1, in cell culture, studied during the

  1. Genome-Wide Scan Reveals Mutation Associated with Melanoma

    Science.gov (United States)

    ... Q R S T U V W X Y Z We want to hear from you You are here: News & Events 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 Spotlight on Research 2012 July 2012 (historical) Genome-Wide Scan Reveals Mutation Associated with Melanoma A team of ...

  2. A genome-wide scan for preeclampsia in the Netherlands

    NARCIS (Netherlands)

    Lachmeijer, AMA; Arngrimsson, R; Bastiaans, EJ; Frigge, ML; Pals, G; Sigurdardottir, S; Stefansson, H; Palsson, B; Nicolae, D; Kong, A; Aarnoudse, JG; Gulcher, [No Value; Dekker, GA; ten Kate, LP; Stefansson, K

    2001-01-01

    Preeclampsia, hallmarked by de novo hypertension and proteinuria in pregnancy, has a familial tendency. Recently, a large Icelandic genome-wide scan provided evidence for a maternal susceptibility locus for preeclampsia on chromosome 2p13 which was confirmed by a genome scan from Australia and New

  3. Genome-wide RNA Tomography in the Zebrafish Embryo

    NARCIS (Netherlands)

    Junker, Jan Philipp; Noël, Emily S; Guryev, Victor; Peterson, Kevin A; Shah, Gopi; Huisken, Jan; McMahon, Andrew P; Berezikov, Eugene; Bakkers, Jeroen; van Oudenaarden, Alexander

    2014-01-01

    Advancing our understanding of embryonic development is heavily dependent on identification of novel pathways or regulators. Although genome-wide techniques such as RNA sequencing are ideally suited for discovering novel candidate genes, they are unable to yield spatially resolved information in

  4. Genome-wide RNA Tomography in the zebrafish embryo

    NARCIS (Netherlands)

    Junker, Jan Philipp; Noël, Emily S; Guryev, Victor; Peterson, Kevin A; Shah, Gopi; Huisken, Jan; McMahon, Andrew P; Berezikov, Eugene; Bakkers, Jeroen; van Oudenaarden, Alexander

    2014-01-01

    Advancing our understanding of embryonic development is heavily dependent on identification of novel pathways or regulators. Although genome-wide techniques such as RNA sequencing are ideally suited for discovering novel candidate genes, they are unable to yield spatially resolved information in

  5. Genome-wide association study identifies five new schizophrenia loci

    NARCIS (Netherlands)

    Ripke, Stephan; Sanders, Alan R.; Kendler, Kenneth S.; Levinson, Douglas F.; Sklar, Pamela; Holmans, Peter A.; Lin, Dan-Yu; Duan, Jubao; Ophoff, Roel A.; Andreassen, Ole A.; Scolnick, Edward; Cichon, Sven; Clair, David St.; Corvin, Aiden; Gurling, Hugh; Werge, Thomas; Rujescu, Dan; Blackwood, Douglas H. R.; Pato, Carlos N.; Malhotra, Anil K.; Purcell, Shaun; Dudbridge, Frank; Neale, Benjamin M.; Rossin, Lizzy; Visscher, Peter M.; Posthuma, Danielle; Ruderfer, Douglas M.; Fanous, Ayman; Stefansson, Hreinn; Steinberg, Stacy; Mowry, Bryan J.; Golimbet, Vera; De Hert, Marc; Jonsson, Erik G.; Bitter, Istvan; Pietilainen, Olli P. H.; Collier, David A.; Tosato, Sarah; Agartz, Ingrid; Albus, Margot; Alexander, Madeline; Amdur, Richard L.; Amin, Farooq; Bass, Nicholas; Bergen, Sarah E.; Black, Donald W.; Borglum, Anders D.; Brown, Matthew A.; Bruggeman, Richard; Buccola, Nancy G.; Byerley, William F.; Cahn, Wiepke; Cantor, Rita M.; Carr, Vaughan J.; Catts, Stanley V.; Choudhury, Khalid; Cloninger, C. Robert; Cormican, Paul; Craddock, Nicholas; Danoy, Patrick A.; Datta, Susmita; De Haan, Lieuwe; Demontis, Ditte; Dikeos, Dimitris; Djurovic, Srdjan; Donnelly, Peter; Donohoe, Gary; Duong, Linh; Dwyer, Sarah; Fink-Jensen, Anders; Freedman, Robert; Freimer, Nelson B.; Friedl, Marion; Georgieva, Lyudmila; Giegling, Ina; Gill, Michael; Glenthoj, Birte; Godard, Stephanie; Hamshere, Marian; Hansen, Mark; Hansen, Thomas; Hartmann, Annette M.; Henskens, Frans A.; Hougaard, David M.; Hultman, Christina M.; Ingason, Andres; Jablensky, Assen V.; Jakobsen, Klaus D.; Jay, Maurice; Juergens, Gesche; Kahn, Renes; Keller, Matthew C.; Kenis, Gunter; Kenny, Elaine; Kim, Yunjung; Kirov, George K.; Konnerth, Heike; Konte, Bettina; Krabbendam, Lydia; Krasucki, Robert; Lasseter, Virginia K.; Laurent, Claudine; Lawrence, Jacob; Lencz, Todd; Lerer, F. Bernard; Liang, Kung-Yee; Lichtenstein, Paul; Lieberman, Jeffrey A.; Linszen, Don H.; Lonnqvist, Jouko; Loughland, Carmel M.; Maclean, Alan W.; Maher, Brion S.; Maier, Wolfgang; Mallet, Jacques; Malloy, Pat; Mattheisen, Manuel; Mattingsdal, Morten; McGhee, Kevin A.; McGrath, John J.; McIntosh, Andrew; McLean, Duncan E.; McQuillin, Andrew; Melle, Ingrid; Michie, Patricia T.; Milanova, Vihra; Morris, Derek W.; Mors, Ole; Mortensen, Preben B.; Moskvina, Valentina; Muglia, Pierandrea; Myin-Germeys, Inez; Nertney, Deborah A.; Nestadt, Gerald; Nielsen, Jimmi; Nikolov, Ivan; Nordentoft, Merete; Norton, Nadine; Noethen, Markus M.; O'Dushlaine, Colm T.; Olincy, Ann; Olsen, Line; O'Neill, F. Anthony; Orntoft, Torben F.; Owen, Michael J.; Pantelis, Christos; Papadimitriou, George; Pato, Michele T.; Peltonen, Leena; Petursson, Hannes; Pickard, Ben; Pimm, Jonathan; Pulver, Ann E.; Puri, Vinay; Quested, Digby; Quinn, Emma M.; Rasmussen, Henrik B.; Rethelyi, Janos M.; Ribble, Robert; Rietschel, Marcella; Riley, Brien P.; Ruggeri, Mirella; Schall, Ulrich; Schulze, Thomas G.; Schwab, Sibylle G.; Scott, Rodney J.; Shi, Jianxin; Sigurdsson, Engilbert; Silverman, Jeremy M.; Spencer, Chris C. A.; Stefansson, Kari; Strange, Amy; Strengman, Eric; Stroup, T. Scott; Suvisaari, Jaana; Terenius, Lars; Thirumalai, Srinivasa; Thygesen, Johan H.; Timm, Sally; Toncheva, Draga; van den Oord, Edwin; van Os, Jim; van Winkel, Ruud; Veldink, Jan; Walsh, Dermot; Wang, August G.; Wiersma, Durk; Wildenauer, Dieter B.; Williams, Hywel J.; Williams, Nigel M.; Wormley, Brandon; Zammit, Stan; Sullivan, Patrick F.; O'Donovan, Michael C.; Daly, Mark J.; Gejman, Pablo V.

    2011-01-01

    We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded

  6. A genome-wide association study of anorexia nervosa

    NARCIS (Netherlands)

    Boraska, V; Franklin, C S; Floyd, J A B; Thornton, L M; Huckins, L M; Southam, L; Rayner, N W; Tachmazidou, I; Klump, K L; Treasure, J; Lewis, C M; Schmidt, U; Tozzi, F; Kiezebrink, K; Hebebrand, J; Gorwood, P; Adan, R A H; Kas, M J H; Favaro, A; Santonastaso, P; Fernández-Aranda, F; Gratacos, M; Rybakowski, F; Dmitrzak-Weglarz, M; Kaprio, J; Keski-Rahkonen, A; Raevuori, A; Van Furth, E F; Slof-Op 't Landt, M C T; Hudson, J I; Reichborn-Kjennerud, T; Knudsen, G P S; Monteleone, P; Kaplan, A S; Karwautz, A; Hakonarson, H; Berrettini, W H; Guo, Y; Li, D; Schork, N J; Komaki, G; Ando, T; Inoko, H; Esko, T; Fischer, K; Männik, K; Metspalu, A; Baker, J H; Cone, R D; Dackor, J; DeSocio, J E; Hilliard, C E; O'Toole, J K; Pantel, J; Szatkiewicz, J P; Taico, C; Zerwas, S; Trace, S E; Davis, O S P; Helder, S; Bühren, K; Burghardt, R; de Zwaan, M; Egberts, K; Ehrlich, S; Herpertz-Dahlmann, B; Herzog, W; Imgart, H; Scherag, A; Scherag, S; Zipfel, S; Boni, C; Ramoz, N; Versini, A; Brandys, M K; Danner, U N; de Kovel, C; Hendriks, J; Koeleman, B P C; Ophoff, R A; Strengman, E; van Elburg, Annemarie; Bruson, A; Clementi, M; Degortes, D; Forzan, M; Tenconi, E; Docampo, E; Escaramís, G; Jiménez-Murcia, S; Lissowska, J; Rajewski, A; Szeszenia-Dabrowska, N; Slopien, A; Hauser, J; Karhunen, L; Meulenbelt, I; Slagboom, P E; Tortorella, A; Maj, M; Dedoussis, G; Dikeos, D; Gonidakis, F; Tziouvas, K; Tsitsika, A; Papezova, H; Slachtova, L; Martaskova, D; Kennedy, J L; Levitan, R D; Yilmaz, Z; Huemer, J; Koubek, D; Merl, E; Wagner, G; Lichtenstein, P; Breen, G; Cohen-Woods, S; Farmer, A; McGuffin, P; Cichon, S; Giegling, I; Herms, S; Rujescu, D; Schreiber, S; Wichmann, H-E; Dina, C; Sladek, R; Gambaro, G; Soranzo, N; Julia, A; Marsal, S; Rabionet, R; Gaborieau, V; Dick, D M; Palotie, A; Ripatti, S; Widén, E; Andreassen, O A; Espeseth, T; Lundervold, A; Reinvang, I; Steen, V M; Le Hellard, S; Mattingsdal, M; Ntalla, I; Bencko, V; Foretova, L; Janout, V; Navratilova, M; Gallinger, S; Pinto, D; Scherer, S W; Aschauer, H; Carlberg, L; Schosser, A; Alfredsson, L; Ding, B; Klareskog, L; Padyukov, L; Courtet, P; Guillaume, S; Jaussent, I; Finan, C; Kalsi, G; Roberts, M; Logan, D W; Peltonen, L; Ritchie, G R S; Barrett, J C; Estivill, X; Hinney, A; Sullivan, P F; Collier, D A; Zeggini, E; Bulik, C M

    2014-01-01

    Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome-wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2907 cases with AN from 14 countri

  7. Genome-Wide Association Analysis in Primary Sclerosing Cholangitis

    NARCIS (Netherlands)

    T.H. Karlsen; A. Franke; E. Melum; A.. Kaser; J.R. Hov; T. Balschun; B.A. Lie; A. Bergquist; C. Schramm; T.J. Weismüller; D. Gotthardt; C. Rust; E.E.R. Philipp; T. Fritz; L. Henckaerts; R. Weersma; P. Stokkers; C.Y. Ponsioen; C. Wijmenga; M. Sterneck; M. Nothnagel; J. Hampe; A. Teufel; H. Runz; P. Rosenstiel; A. Stiehl; S. Vermeire; U. Beuers; M. Manns; E. Schrumpf; K.M. Boberg; S. Schreiber

    2010-01-01

    BACKGROUND & AIMS: We aimed to characterize the genetic susceptibility to primary sclerosing cholangitis (PSC) by means of a genome-wide association analysis of single nucleotide polymorphism (SNP) markers. METHODS: A total of 443,816 SNPs on the Affymetrix SNP Array 5.0 (Affymetrix, Santa Clara, CA

  8. Genome-wide association study of Tourette's syndrome

    NARCIS (Netherlands)

    Scharf, J. M.; Yu, D.; Mathews, C. A.; Neale, B. M.; Stewart, S. E.; Fagerness, J. A.; Evans, P.; Gamazon, E.; Edlund, C. K.; Service, S. K.; Tikhomirov, A.; Osiecki, L.; Illmann, C.; Pluzhnikov, A.; Konkashbaev, A.; Davis, L. K.; Han, B.; Crane, J.; Moorjani, P.; Crenshaw, A. T.; Parkin, M. A.; Reus, V. I.; Lowe, T. L.; Rangel-Lugo, M.; Chouinard, S.; Dion, Y.; Girard, S.; Cath, D. C.; Smit, J. H.; King, R. A.; Fernandez, T. V.; Leckman, J. F.; Kidd, K. K.; Kidd, J. R.; Pakstis, A. J.; State, M. W.; Herrera, L. D.; Romero, R.; Fournier, E.; Sandor, P.; Barr, C. L.; Phan, N.; Gross-Tsur, V.; Benarroch, F.; Pollak, Y.; Budman, C. L.; Bruun, R. D.; Erenberg, G.; Naarden, A. L.; Lee, P. C.; Weiss, N.; Kremeyer, B.; Berrio, G. B.; Campbell, D. D.; Cardona Silgado, J. C.; Ochoa, W. C.; Mesa Restrepo, S. C.; Muller, H.; Valencia Duarte, A. V.; Lyon, G. J.; Leppert, M.; Morgan, J.; Weiss, R.; Grados, M. A.; Anderson, K.; Davarya, S.; Singer, H.; Walkup, J.; Jankovic, J.; Tischfield, J. A.; Heiman, G. A.; Gilbert, D. L.; Hoekstra, P. J.; Robertson, M. M.; Kurlan, R.; Liu, C.; Gibbs, J. R.; Singleton, A.; Hardy, J.; Strengman, E.; Ophoff, R. A.; Wagner, M.; Moessner, R.; Mirel, D. B.; Posthuma, D.; Sabatti, C.; Eskin, E.; Conti, D. V.; Knowles, J. A.; Ruiz-Linares, A.; Rouleau, G. A.; Purcell, S.; Heutink, P.; Oostra, B. A.; McMahon, W. M.; Freimer, N. B.; Cox, N. J.; Pauls, D. L.

    2013-01-01

    Tourette's syndrome (TS) is a developmental disorder that has one of the highest familial recurrence rates among neuropsychiatric diseases with complex inheritance. However, the identification of definitive TS susceptibility genes remains elusive. Here, we report the first genome-wide association

  9. Genome-wide association study identifies five new schizophrenia loci

    NARCIS (Netherlands)

    Ripke, Stephan; Sanders, Alan R.; Kendler, Kenneth S.; Levinson, Douglas F.; Sklar, Pamela; Holmans, Peter A.; Lin, Dan-Yu; Duan, Jubao; Ophoff, Roel A.; Andreassen, Ole A.; Scolnick, Edward; Cichon, Sven; Clair, David St.; Corvin, Aiden; Gurling, Hugh; Werge, Thomas; Rujescu, Dan; Blackwood, Douglas H. R.; Pato, Carlos N.; Malhotra, Anil K.; Purcell, Shaun; Dudbridge, Frank; Neale, Benjamin M.; Rossin, Lizzy; Visscher, Peter M.; Posthuma, Danielle; Ruderfer, Douglas M.; Fanous, Ayman; Stefansson, Hreinn; Steinberg, Stacy; Mowry, Bryan J.; Golimbet, Vera; De Hert, Marc; Jonsson, Erik G.; Bitter, Istvan; Pietilainen, Olli P. H.; Collier, David A.; Tosato, Sarah; Agartz, Ingrid; Albus, Margot; Alexander, Madeline; Amdur, Richard L.; Amin, Farooq; Bass, Nicholas; Bergen, Sarah E.; Black, Donald W.; Borglum, Anders D.; Brown, Matthew A.; Bruggeman, Richard; Buccola, Nancy G.; Byerley, William F.; Cahn, Wiepke; Cantor, Rita M.; Carr, Vaughan J.; Catts, Stanley V.; Choudhury, Khalid; Cloninger, C. Robert; Cormican, Paul; Craddock, Nicholas; Danoy, Patrick A.; Datta, Susmita; De Haan, Lieuwe; Demontis, Ditte; Dikeos, Dimitris; Djurovic, Srdjan; Donnelly, Peter; Donohoe, Gary; Duong, Linh; Dwyer, Sarah; Fink-Jensen, Anders; Freedman, Robert; Freimer, Nelson B.; Friedl, Marion; Georgieva, Lyudmila; Giegling, Ina; Gill, Michael; Glenthoj, Birte; Godard, Stephanie; Hamshere, Marian; Hansen, Mark; Hansen, Thomas; Hartmann, Annette M.; Henskens, Frans A.; Hougaard, David M.; Hultman, Christina M.; Ingason, Andres; Jablensky, Assen V.; Jakobsen, Klaus D.; Jay, Maurice; Juergens, Gesche; Kahn, Renes; Keller, Matthew C.; Kenis, Gunter; Kenny, Elaine; Kim, Yunjung; Kirov, George K.; Konnerth, Heike; Konte, Bettina; Krabbendam, Lydia; Krasucki, Robert; Lasseter, Virginia K.; Laurent, Claudine; Lawrence, Jacob; Lencz, Todd; Lerer, F. Bernard; Liang, Kung-Yee; Lichtenstein, Paul; Lieberman, Jeffrey A.; Linszen, Don H.; Lonnqvist, Jouko; Loughland, Carmel M.; Maclean, Alan W.; Maher, Brion S.; Maier, Wolfgang; Mallet, Jacques; Malloy, Pat; Mattheisen, Manuel; Mattingsdal, Morten; McGhee, Kevin A.; McGrath, John J.; McIntosh, Andrew; McLean, Duncan E.; McQuillin, Andrew; Melle, Ingrid; Michie, Patricia T.; Milanova, Vihra; Morris, Derek W.; Mors, Ole; Mortensen, Preben B.; Moskvina, Valentina; Muglia, Pierandrea; Myin-Germeys, Inez; Nertney, Deborah A.; Nestadt, Gerald; Nielsen, Jimmi; Nikolov, Ivan; Nordentoft, Merete; Norton, Nadine; Noethen, Markus M.; O'Dushlaine, Colm T.; Olincy, Ann; Olsen, Line; O'Neill, F. Anthony; Orntoft, Torben F.; Owen, Michael J.; Pantelis, Christos; Papadimitriou, George; Pato, Michele T.; Peltonen, Leena; Petursson, Hannes; Pickard, Ben; Pimm, Jonathan; Pulver, Ann E.; Puri, Vinay; Quested, Digby; Quinn, Emma M.; Rasmussen, Henrik B.; Rethelyi, Janos M.; Ribble, Robert; Rietschel, Marcella; Riley, Brien P.; Ruggeri, Mirella; Schall, Ulrich; Schulze, Thomas G.; Schwab, Sibylle G.; Scott, Rodney J.; Shi, Jianxin; Sigurdsson, Engilbert; Silverman, Jeremy M.; Spencer, Chris C. A.; Stefansson, Kari; Strange, Amy; Strengman, Eric; Stroup, T. Scott; Suvisaari, Jaana; Terenius, Lars; Thirumalai, Srinivasa; Thygesen, Johan H.; Timm, Sally; Toncheva, Draga; van den Oord, Edwin; van Os, Jim; van Winkel, Ruud; Veldink, Jan; Walsh, Dermot; Wang, August G.; Wiersma, Durk; Wildenauer, Dieter B.; Williams, Hywel J.; Williams, Nigel M.; Wormley, Brandon; Zammit, Stan; Sullivan, Patrick F.; O'Donovan, Michael C.; Daly, Mark J.; Gejman, Pablo V.

    2011-01-01

    We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded

  10. Genome-wide association study identifies five new schizophrenia loci

    DEFF Research Database (Denmark)

    Ripke, Stephan; Sanders, Alan R; Kendler, Kenneth S

    2011-01-01

    We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yiel...

  11. Genome-wide significant risk associations for mucinous ovarian carcinoma

    DEFF Research Database (Denmark)

    Kelemen, Linda E; Lawrenson, Kate; Tyrer, Jonathan;

    2015-01-01

    Genome-wide association studies have identified several risk associations for ovarian carcinomas but not for mucinous ovarian carcinomas (MOCs). Our analysis of 1,644 MOC cases and 21,693 controls with imputation identified 3 new risk associations: rs752590 at 2q13 (P = 3.3 × 10(-8)), rs711830 at...

  12. Potential assessment of genome-wide association study and genomic selection in Japanese pear Pyrus pyrifolia

    OpenAIRE

    Iwata, Hiroyoshi; Hayashi, Takeshi; Terakami, Shingo; Takada, Norio; Sawamura, Yutaka; Yamamoto, Toshiya

    2013-01-01

    Although the potential of marker-assisted selection (MAS) in fruit tree breeding has been reported, bi-parental QTL mapping before MAS has hindered the introduction of MAS to fruit tree breeding programs. Genome-wide association studies (GWAS) are an alternative to bi-parental QTL mapping in long-lived perennials. Selection based on genomic predictions of breeding values (genomic selection: GS) is another alternative for MAS. This study examined the potential of GWAS and GS in pear breeding w...

  13. Supervised Learning-Based tagSNP Selection for Genome-Wide Disease Classifications

    OpenAIRE

    Yang Mary Qu; Chen Zhongxue; Yang Jack; Liu Qingzhong; Sung Andrew H; Huang Xudong

    2008-01-01

    Abstract Background Comprehensive evaluation of common genetic variations through association of single nucleotide polymorphisms (SNPs) with complex human diseases on the genome-wide scale is an active area in human genome research. One of the fundamental questions in a SNP-disease association study is to find an optimal subset of SNPs with predicting power for disease status. To find that subset while reducing study burden in terms of time and costs, one can potentially reconcile information...

  14. Candidate essential genes in Burkholderia cenocepacia J2315 identified by genome-wide TraDIS

    Directory of Open Access Journals (Sweden)

    Yee-Chin Wong

    2016-08-01

    Full Text Available Burkholderia cenocepacia infection often leads to fatal cepacia syndrome in cystic fibrosis patients. However, antibiotic therapy rarely results in complete eradication of the pathogen due to its intrinsic resistance to many clinically available antibiotics. Recent attention has turned to the identification of essential genes as the proteins encoded by these genes may serve as potential targets for development of novel antimicrobials. In this study, we utilized TraDIS (Transposon Directed Insertion-site Sequencing as a genome-wide screening tool to facilitate the identification of B. cenocepacia genes essential for its growth and viability. A transposon mutant pool consisting of approximately 500,000 mutants was successfully constructed, with more than 400,000 unique transposon insertion sites identified by computational analysis of TraDIS datasets. The saturated library allowed for the identification of 383 genes that were predicted to be essential in B. cenocepacia. We extended the application of TraDIS to identify conditionally essential genes required for in vitro growth and revealed an additional repertoire of 439 genes to be crucial for B. cenocepacia growth under nutrient-depleted conditions. The library of B. cenocepacia mutants can subsequently be subjected to various biologically related conditions to facilitate the discovery of genes involved in niche adaptation as well as pathogenicity and virulence.

  15. Candidate Essential Genes in Burkholderia cenocepacia J2315 Identified by Genome-Wide TraDIS

    KAUST Repository

    Wong, Yee-Chin

    2016-08-22

    Burkholderia cenocepacia infection often leads to fatal cepacia syndrome in cystic fibrosis patients. However, antibiotic therapy rarely results in complete eradication of the pathogen due to its intrinsic resistance to many clinically available antibiotics. Recent attention has turned to the identification of essential genes as the proteins encoded by these genes may serve as potential targets for development of novel antimicrobials. In this study, we utilized TraDIS (Transposon Directed Insertion-site Sequencing) as a genome-wide screening tool to facilitate the identification of B. cenocepacia genes essential for its growth and viability. A transposon mutant pool consisting of approximately 500,000 mutants was successfully constructed, with more than 400,000 unique transposon insertion sites identified by computational analysis of TraDIS datasets. The saturated library allowed for the identification of 383 genes that were predicted to be essential in B. cenocepacia. We extended the application of TraDIS to identify conditionally essential genes required for in vitro growth and revealed an additional repertoire of 439 genes to be crucial for B. cenocepacia growth under nutrient-depleted conditions. The library of B. cenocepacia mutants can subsequently be subjected to various biologically related conditions to facilitate the discovery of genes involved in niche adaptation as well as pathogenicity and virulence.

  16. Escherichia coli genome-wide promoter analysis: Identification of additional AtoC binding target elements

    Directory of Open Access Journals (Sweden)

    Kolisis Fragiskos N

    2011-05-01

    Full Text Available Abstract Background Studies on bacterial signal transduction systems have revealed complex networks of functional interactions, where the response regulators play a pivotal role. The AtoSC system of E. coli activates the expression of atoDAEB operon genes, and the subsequent catabolism of short-chain fatty acids, upon acetoacetate induction. Transcriptome and phenotypic analyses suggested that atoSC is also involved in several other cellular activities, although we have recently reported a palindromic repeat within the atoDAEB promoter as the single, cis-regulatory binding site of the AtoC response regulator. In this work, we used a computational approach to explore the presence of yet unidentified AtoC binding sites within other parts of the E. coli genome. Results Through the implementation of a computational de novo motif detection workflow, a set of candidate motifs was generated, representing putative AtoC binding targets within the E. coli genome. In order to assess the biological relevance of the motifs and to select for experimental validation of those sequences related robustly with distinct cellular functions, we implemented a novel approach that applies Gene Ontology Term Analysis to the motif hits and selected those that were qualified through this procedure. The computational results were validated using Chromatin Immunoprecipitation assays to assess the in vivo binding of AtoC to the predicted sites. This process verified twenty-two additional AtoC binding sites, located not only within intergenic regions, but also within gene-encoding sequences. Conclusions This study, by tracing a number of putative AtoC binding sites, has indicated an AtoC-related cross-regulatory function. This highlights the significance of computational genome-wide approaches in elucidating complex patterns of bacterial cell regulation.

  17. Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes.

    Science.gov (United States)

    Wang, Yue; Goh, Wilson; Wong, Limsoon; Montana, Giovanni

    2013-01-01

    Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly

  18. Identification of Transcribed Enhancers by Genome-Wide Chromatin Immunoprecipitation Sequencing.

    Science.gov (United States)

    Blinka, Steven; Reimer, Michael H; Pulakanti, Kirthi; Pinello, Luca; Yuan, Guo-Cheng; Rao, Sridhar

    2017-01-01

    Recent work has shown that RNA polymerase II-mediated transcription at distal cis-regulatory elements serves as a mark of highly active enhancers. Production of noncoding RNAs at enhancers, termed eRNAs, correlates with higher expression of genes that the enhancer interacts with; hence, eRNAs provide a new tool to model gene activity in normal and disease tissues. Moreover, this unique class of noncoding RNA has diverse roles in transcriptional regulation. Transcribed enhancers can be identified by a common signature of epigenetic marks by overlaying a series of genome-wide chromatin immunoprecipitation and RNA sequencing datasets. A computational approach to filter non-enhancer elements and other classes of noncoding RNAs is essential to not cloud downstream analysis. Here we present a protocol that combines wet and dry bench methods to accurately identify transcribed enhancers genome-wide as well as an experimental procedure to validate these datasets.

  19. cuGWAM: Genome-wide association multifactor dimensionality reduction using CUDA-enabled high-performance graphics processing unit.

    Science.gov (United States)

    Kwon, Min-Seok; Kim, Kyunga; Lee, Sungyoung; Park, Taesung

    2012-01-01

    Multifactor dimensionality reduction (MDR) method has been widely applied to detect gene-gene interactions that are well recognized as playing an important role in understanding complex traits. However, because of an exhaustive analysis of MDR, the current MDR software has some limitations to be extended to the genome-wide association studies (GWAS) with a large number of genetic markers up to approximately 1 million. To overcome this computational problem, we developed CUDA (Compute Unified Device Architecture) based genome-wide association MDR (cuGWAM) software using efficient hardware accelerators, cuGWAM has better performance than CPU-based MDR methods and other GPU-based methods.

  20. Genome-wide analytical approaches for reverse metabolic engineering of industrially relevant phenotypes in yeast

    Science.gov (United States)

    Oud, Bart; Maris, Antonius J A; Daran, Jean-Marc; Pronk, Jack T

    2012-01-01

    Successful reverse engineering of mutants that have been obtained by nontargeted strain improvement has long presented a major challenge in yeast biotechnology. This paper reviews the use of genome-wide approaches for analysis of Saccharomyces cerevisiae strains originating from evolutionary engineering or random mutagenesis. On the basis of an evaluation of the strengths and weaknesses of different methods, we conclude that for the initial identification of relevant genetic changes, whole genome sequencing is superior to other analytical techniques, such as transcriptome, metabolome, proteome, or array-based genome analysis. Key advantages of this technique over gene expression analysis include the independency of genome sequences on experimental context and the possibility to directly and precisely reproduce the identified changes in naive strains. The predictive value of genome-wide analysis of strains with industrially relevant characteristics can be further improved by classical genetics or simultaneous analysis of strains derived from parallel, independent strain improvement lineages. PMID:22152095

  1. Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function.

    Science.gov (United States)

    Hancock, Dana B; Eijgelsheim, Mark; Wilk, Jemma B; Gharib, Sina A; Loehr, Laura R; Marciante, Kristin D; Franceschini, Nora; van Durme, Yannick M T A; Chen, Ting-Hsu; Barr, R Graham; Schabath, Matthew B; Couper, David J; Brusselle, Guy G; Psaty, Bruce M; van Duijn, Cornelia M; Rotter, Jerome I; Uitterlinden, André G; Hofman, Albert; Punjabi, Naresh M; Rivadeneira, Fernando; Morrison, Alanna C; Enright, Paul L; North, Kari E; Heckbert, Susan R; Lumley, Thomas; Stricker, Bruno H C; O'Connor, George T; London, Stephanie J

    2010-01-01

    Spirometric measures of lung function are heritable traits that reflect respiratory health and predict morbidity and mortality. We meta-analyzed genome-wide association studies for two clinically important lung-function measures: forced expiratory volume in the first second (FEV(1)) and its ratio to forced vital capacity (FEV(1)/FVC), an indicator of airflow obstruction. This meta-analysis included 20,890 participants of European ancestry from four CHARGE Consortium studies: Atherosclerosis Risk in Communities, Cardiovascular Health Study, Framingham Heart Study and Rotterdam Study. We identified eight loci associated with FEV(1)/FVC (HHIP, GPR126, ADAM19, AGER-PPT2, FAM13A, PTCH1, PID1 and HTR4) and one locus associated with FEV(1) (INTS12-GSTCD-NPNT) at or near genome-wide significance (P < 5 x 10(-8)) in the CHARGE Consortium dataset. Our findings may offer insights into pulmonary function and pathogenesis of chronic lung disease.

  2. Genome-wide analytical approaches for reverse metabolic engineering of industrially relevant phenotypes in yeast.

    Science.gov (United States)

    Oud, Bart; van Maris, Antonius J A; Daran, Jean-Marc; Pronk, Jack T

    2012-03-01

    Successful reverse engineering of mutants that have been obtained by nontargeted strain improvement has long presented a major challenge in yeast biotechnology. This paper reviews the use of genome-wide approaches for analysis of Saccharomyces cerevisiae strains originating from evolutionary engineering or random mutagenesis. On the basis of an evaluation of the strengths and weaknesses of different methods, we conclude that for the initial identification of relevant genetic changes, whole genome sequencing is superior to other analytical techniques, such as transcriptome, metabolome, proteome, or array-based genome analysis. Key advantages of this technique over gene expression analysis include the independency of genome sequences on experimental context and the possibility to directly and precisely reproduce the identified changes in naive strains. The predictive value of genome-wide analysis of strains with industrially relevant characteristics can be further improved by classical genetics or simultaneous analysis of strains derived from parallel, independent strain improvement lineages.

  3. Translating Lung Function Genome-Wide Association Study (GWAS) Findings: New Insights for Lung Biology.

    Science.gov (United States)

    Kheirallah, A K; Miller, S; Hall, I P; Sayers, I

    2016-01-01

    Chronic respiratory diseases are a major cause of worldwide mortality and morbidity. Although hereditary severe deficiency of α1 antitrypsin (A1AD) has been established to cause emphysema, A1AD accounts for only ∼ 1% of Chronic Obstructive Pulmonary Disease (COPD) cases. Genome-wide association studies (GWAS) have been successful at detecting multiple loci harboring variants predicting the variation in lung function measures and risk of COPD. However, GWAS are incapable of distinguishing causal from noncausal variants. Several approaches can be used for functional translation of genetic findings. These approaches have the scope to identify underlying alleles and pathways that are important in lung function and COPD. Computational methods aim at effective functional variant prediction by combining experimentally generated regulatory information with associated region of the human genome. Classically, GWAS association follow-up concentrated on manipulation of a single gene. However association data has identified genetic variants in >50 loci predicting disease risk or lung function. Therefore there is a clear precedent for experiments that interrogate multiple candidate genes in parallel, which is now possible with genome editing technology. Gene expression profiling can be used for effective discovery of biological pathways underpinning gene function. This information may be used for informed decisions about cellular assays post genetic manipulation. Investigating respiratory phenotypes in human lung tissue and specific gene knockout mice is a valuable in vivo approach that can complement in vitro work. Herein, we review state-of-the-art in silico, in vivo, and in vitro approaches that may be used to accelerate functional translation of genetic findings. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Genome-wide analysis of alternative splicing in Chlamydomonas reinhardtii

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    Thomas Julie

    2010-02-01

    Full Text Available Abstract Background Genome-wide computational analysis of alternative splicing (AS in several flowering plants has revealed that pre-mRNAs from about 30% of genes undergo AS. Chlamydomonas, a simple unicellular green alga, is part of the lineage that includes land plants. However, it diverged from land plants about one billion years ago. Hence, it serves as a good model system to study alternative splicing in early photosynthetic eukaryotes, to obtain insights into the evolution of this process in plants, and to compare splicing in simple unicellular photosynthetic and non-photosynthetic eukaryotes. We performed a global analysis of alternative splicing in Chlamydomonas reinhardtii using its recently completed genome sequence and all available ESTs and cDNAs. Results Our analysis of AS using BLAT and a modified version of the Sircah tool revealed AS of 498 transcriptional units with 611 events, representing about 3% of the total number of genes. As in land plants, intron retention is the most prevalent form of AS. Retained introns and skipped exons tend to be shorter than their counterparts in constitutively spliced genes. The splice site signals in all types of AS events are weaker than those in constitutively spliced genes. Furthermore, in alternatively spliced genes, the prevalent splice form has a stronger splice site signal than the non-prevalent form. Analysis of constitutively spliced introns revealed an over-abundance of motifs with simple repetitive elements in comparison to introns involved in intron retention. In almost all cases, AS results in a truncated ORF, leading to a coding sequence that is around 50% shorter than the prevalent splice form. Using RT-PCR we verified AS of two genes and show that they produce more isoforms than indicated by EST data. All cDNA/EST alignments and splice graphs are provided in a website at http://combi.cs.colostate.edu/as/chlamy. Conclusions The extent of AS in Chlamydomonas that we observed is much

  5. Genome-wide association study of colorectal cancer in Hispanics

    Science.gov (United States)

    Schmit, Stephanie L.; Schumacher, Fredrick R.; Edlund, Christopher K.; Conti, David V.; Ihenacho, Ugonna; Wan, Peggy; Van Den Berg, David; Casey, Graham; Fortini, Barbara K.; Lenz, Heinz-Josef; Tusié-Luna, Teresa; Aguilar-Salinas, Carlos A.; Moreno-Macías, Hortensia; Huerta-Chagoya, Alicia; Ordóñez-Sánchez, María Luisa; Rodríguez-Guillén, Rosario; Cruz-Bautista, Ivette; Rodríguez-Torres, Maribel; Muñóz-Hernández, Linda Liliana; Arellano-Campos, Olimpia; Gómez, Donají; Alvirde, Ulices; González-Villalpando, Clicerio; González-Villalpando, María Elena; Le Marchand, Loic; Haiman, Christopher A.; Figueiredo, Jane C.

    2016-01-01

    Genome-wide association studies (GWAS) have identified 58 susceptibility alleles across 37 regions associated with the risk of colorectal cancer (CRC) with P < 5×10−8. Most studies have been conducted in non-Hispanic whites and East Asians; however, the generalizability of these findings and the potential for ethnic-specific risk variation in Hispanic and Latino (HL) individuals have been largely understudied. We describe the first GWAS of common genetic variation contributing to CRC risk in HL (1611 CRC cases and 4330 controls). We also examine known susceptibility alleles and implement imputation-based fine-mapping to identify potential ethnicity-specific association signals in known risk regions. We discovered 17 variants across 4 independent regions that merit further investigation due to suggestive CRC associations (P < 1×10−6) at 1p34.3 (rs7528276; Odds Ratio (OR) = 1.86 [95% confidence interval (CI): 1.47–2.36); P = 2.5×10−7], 2q23.3 (rs1367374; OR = 1.37 (95% CI: 1.21–1.55); P = 4.0×10−7), 14q24.2 (rs143046984; OR = 1.65 (95% CI: 1.36–2.01); P = 4.1×10−7) and 16q12.2 [rs142319636; OR = 1.69 (95% CI: 1.37–2.08); P=7.8×10−7]. Among the 57 previously published CRC susceptibility alleles with minor allele frequency ≥1%, 76.5% of SNPs had a consistent direction of effect and 19 (33.3%) were nominally statistically significant (P < 0.05). Further, rs185423955 and rs60892987 were identified as novel secondary susceptibility variants at 3q26.2 (P = 5.3×10–5) and 11q12.2 (P = 6.8×10−5), respectively. Our findings demonstrate the importance of fine mapping in HL. These results are informative for variant prioritization in functional studies and future risk prediction modeling in minority populations. PMID:27207650

  6. Genome-wide association studies and resting heart rate

    DEFF Research Database (Denmark)

    Oskari Kilpeläinen, Tuomas

    2016-01-01

    Genome-wide association studies (GWASs) have revolutionized the search for genetic variants regulating resting heart rate. In the last 10 years, GWASs have led to the identification of at least 21 novel heart rate loci. These discoveries have provided valuable insights into the mechanisms...... and pathways that regulate heart rate and link heart rate to cardiovascular morbidity and mortality. GWASs capture majority of genetic variation in a population sample by utilizing high-throughput genotyping chips measuring genotypes for up to several millions of SNPs across the genome in thousands...... of individuals. This allows the identification of the strongest heart rate associated signals at genome-wide level. While GWASs provide robust statistical evidence of the association of a given genetic locus with heart rate, they are only the starting point for detailed follow-up studies to locate the causal...

  7. Genome-wide patterns of selection in 230 ancient Eurasians

    Science.gov (United States)

    Mathieson, Iain; Lazaridis, Iosif; Rohland, Nadin; Mallick, Swapan; Patterson, Nick; Roodenberg, Songül Alpaslan; Harney, Eadaoin; Stewardson, Kristin; Fernandes, Daniel; Novak, Mario; Sirak, Kendra; Gamba, Cristina; Jones, Eppie R.; Llamas, Bastien; Dryomov, Stanislav; Pickrel, Joseph; Arsuaga, Juan Luís; de Castro, José María Bermúdez; Carbonell, Eudald; Gerritsen, Fokke; Khokhlov, Aleksandr; Kuznetsov, Pavel; Lozano, Marina; Meller, Harald; Mochalov, Oleg; Moiseyev, Vayacheslav; Rojo Guerra, Manuel A.; Roodenberg, Jacob; Vergès, Josep Maria; Krause, Johannes; Cooper, Alan; Alt, Kurt W.; Brown, Dorcas; Anthony, David; Lalueza-Fox, Carles; Haak, Wolfgang; Pinhasi, Ron; Reich, David

    2016-01-01

    Ancient DNA makes it possible to directly witness natural selection by analyzing samples from populations before, during and after adaptation events. Here we report the first scan for selection using ancient DNA, capitalizing on the largest genome-wide dataset yet assembled: 230 West Eurasians dating to between 6500 and 1000 BCE, including 163 with newly reported data. The new samples include the first genome-wide data from the Anatolian Neolithic culture whose genetic material we extracted from the DNA-rich petrous bone and who we show were members of the population that was the source of Europe’s first farmers. We also report a complete transect of the steppe region in Samara between 5500 and 1200 BCE that allows us to recognize admixture from at least two external sources into steppe populations during this period. We detect selection at loci associated with diet, pigmentation and immunity, and two independent episodes of selection on height. PMID:26595274

  8. Genome wide copy number analysis of single cells

    Science.gov (United States)

    Baslan, Timour; Kendall, Jude; Rodgers, Linda; Cox, Hilary; Riggs, Mike; Stepansky, Asya; Troge, Jennifer; Ravi, Kandasamy; Esposito, Diane; Lakshmi, B.; Wigler, Michael; Navin, Nicholas; Hicks, James

    2016-01-01

    Summary Copy number variation (CNV) is increasingly recognized as an important contributor to phenotypic variation in health and disease. Most methods for determining CNV rely on admixtures of cells, where information regarding genetic heterogeneity is lost. Here, we present a protocol that allows for the genome wide copy number analysis of single nuclei isolated from mixed populations of cells. Single nucleus sequencing (SNS), combines flow sorting of single nuclei based on DNA content, whole genome amplification (WGA), followed by next generation sequencing to quantize genomic intervals in a genome wide manner. Multiplexing of single cells is discussed. Additionally, we outline informatic approaches that correct for biases inherent in the WGA procedure and allow for accurate determination of copy number profiles. All together, the protocol takes ~3 days from flow cytometry to sequence-ready DNA libraries. PMID:22555242

  9. Genome-wide patterns of nucleotide polymorphism in domesticated rice

    DEFF Research Database (Denmark)

    Caicedo, Ana L; Williamson, Scott H; Hernandez, Ryan D

    2007-01-01

    Domesticated Asian rice (Oryza sativa) is one of the oldest domesticated crop species in the world, having fed more people than any other plant in human history. We report the patterns of DNA sequence variation in rice and its wild ancestor, O. rufipogon, across 111 randomly chosen gene fragments......, and use these to infer the evolutionary dynamics that led to the origins of rice. There is a genome-wide excess of high-frequency derived single nucleotide polymorphisms (SNPs) in O. sativa varieties, a pattern that has not been reported for other crop species. We developed several alternative models...... explanations for patterns of variation in domesticated rice varieties. If selective sweeps are indeed the explanation for the observed nucleotide data of domesticated rice, it suggests that strong selection can leave its imprint on genome-wide polymorphism patterns, contrary to expectations that selection...

  10. Genome-Wide Association Study of Polymorphisms Predisposing to Bronchiolitis

    Science.gov (United States)

    Pasanen, Anu; Karjalainen, Minna K.; Bont, Louis; Piippo-Savolainen, Eija; Ruotsalainen, Marja; Goksör, Emma; Kumawat, Kuldeep; Hodemaekers, Hennie; Nuolivirta, Kirsi; Jartti, Tuomas; Wennergren, Göran; Hallman, Mikko; Rämet, Mika; Korppi, Matti

    2017-01-01

    Bronchiolitis is a major cause of hospitalization among infants. Severe bronchiolitis is associated with later asthma, suggesting a common genetic predisposition. Genetic background of bronchiolitis is not well characterized. To identify polymorphisms associated with bronchiolitis, we conducted a genome-wide association study (GWAS) in which 5,300,000 single nucleotide polymorphisms (SNPs) were tested for association in a Finnish–Swedish population of 217 children hospitalized for bronchiolitis and 778 controls. The most promising SNPs (n = 77) were genotyped in a Dutch replication population of 416 cases and 432 controls. Finally, we used a set of 202 Finnish bronchiolitis cases to further investigate candidate SNPs. We did not detect genome-wide significant associations, but several suggestive association signals (p bronchiolitis. These preliminary findings require further validation in a larger sample size. PMID:28139761

  11. Genome-wide association study of relative telomere length.

    Science.gov (United States)

    Prescott, Jennifer; Kraft, Peter; Chasman, Daniel I; Savage, Sharon A; Mirabello, Lisa; Berndt, Sonja I; Weissfeld, Joel L; Han, Jiali; Hayes, Richard B; Chanock, Stephen J; Hunter, David J; De Vivo, Immaculata

    2011-05-10

    Telomere function is essential to maintaining the physical integrity of linear chromosomes and healthy human aging. The probability of forming proper telomere structures depends on the length of the telomeric DNA tract. We attempted to identify common genetic variants associated with log relative telomere length using genome-wide genotyping data on 3,554 individuals from the Nurses' Health Study and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial that took part in the National Cancer Institute Cancer Genetic Markers of Susceptibility initiative for breast and prostate cancer. After genotyping 64 independent SNPs selected for replication in additional Nurses' Health Study and Women's Genome Health Study participants, we did not identify genome-wide significant loci; however, we replicated the inverse association of log relative telomere length with the minor allele variant [C] of rs16847897 at the TERC locus (per allele β = -0.03, P = 0.003) identified by a previous genome-wide association study. We did not find evidence for an association with variants at the OBFC1 locus or other loci reported to be associated with telomere length. With this sample size we had >80% power to detect β estimates as small as ±0.10 for SNPs with minor allele frequencies of ≥0.15 at genome-wide significance. However, power is greatly reduced for β estimates smaller than ±0.10, such as those for variants at the TERC locus. In general, common genetic variants associated with telomere length homeostasis have been difficult to detect. Potential biological and technical issues are discussed.

  12. Genome-wide association study of relative telomere length.

    Directory of Open Access Journals (Sweden)

    Jennifer Prescott

    Full Text Available Telomere function is essential to maintaining the physical integrity of linear chromosomes and healthy human aging. The probability of forming proper telomere structures depends on the length of the telomeric DNA tract. We attempted to identify common genetic variants associated with log relative telomere length using genome-wide genotyping data on 3,554 individuals from the Nurses' Health Study and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial that took part in the National Cancer Institute Cancer Genetic Markers of Susceptibility initiative for breast and prostate cancer. After genotyping 64 independent SNPs selected for replication in additional Nurses' Health Study and Women's Genome Health Study participants, we did not identify genome-wide significant loci; however, we replicated the inverse association of log relative telomere length with the minor allele variant [C] of rs16847897 at the TERC locus (per allele β = -0.03, P = 0.003 identified by a previous genome-wide association study. We did not find evidence for an association with variants at the OBFC1 locus or other loci reported to be associated with telomere length. With this sample size we had >80% power to detect β estimates as small as ±0.10 for SNPs with minor allele frequencies of ≥0.15 at genome-wide significance. However, power is greatly reduced for β estimates smaller than ±0.10, such as those for variants at the TERC locus. In general, common genetic variants associated with telomere length homeostasis have been difficult to detect. Potential biological and technical issues are discussed.

  13. Integrative genome-wide approaches in embryonic stem cell research.

    Science.gov (United States)

    Zhang, Xinyue; Huang, Jing

    2010-10-01

    Embryonic stem (ES) cells are derived from blastocysts. They can differentiate into the three embryonic germ layers and essentially any type of somatic cells. They therefore hold great potential in tissue regeneration therapy. The ethical issues associated with the use of human embryonic stem cells are resolved by the technical break-through of generating induced pluripotent stem (iPS) cells from various types of somatic cells. However, how ES and iPS cells self-renew and maintain their pluripotency is still largely unknown in spite of the great progress that has been made in the last two decades. Integrative genome-wide approaches, such as the gene expression microarray, chromatin immunoprecipitation based microarray (ChIP-chip) and chromatin immunoprecipitation followed by massive parallel sequencing (ChIP-seq) offer unprecedented opportunities to elucidate the mechanism of the pluripotency, reprogramming and DNA damage response of ES and iPS cells. This frontier article summarizes the fundamental biological questions about ES and iPS cells and reviews the recent advances in ES and iPS cell research using genome-wide technologies. To this end, we offer our perspectives on the future of genome-wide studies on stem cells.

  14. Genome-wide patterns of promoter sharing and co-expression in bovine skeletal muscle

    Directory of Open Access Journals (Sweden)

    Dalrymple Brian P

    2011-01-01

    Full Text Available Abstract Background Gene regulation by transcription factors (TF is species, tissue and time specific. To better understand how the genetic code controls gene expression in bovine muscle we associated gene expression data from developing Longissimus thoracis et lumborum skeletal muscle with bovine promoter sequence information. Results We created a highly conserved genome-wide promoter landscape comprising 87,408 interactions relating 333 TFs with their 9,242 predicted target genes (TGs. We discovered that the complete set of predicted TGs share an average of 2.75 predicted TF binding sites (TFBSs and that the average co-expression between a TF and its predicted TGs is higher than the average co-expression between the same TF and all genes. Conversely, pairs of TFs sharing predicted TGs showed a co-expression correlation higher that pairs of TFs not sharing TGs. Finally, we exploited the co-occurrence of predicted TFBS in the context of muscle-derived functionally-coherent modules including cell cycle, mitochondria, immune system, fat metabolism, muscle/glycolysis, and ribosome. Our findings enabled us to reverse engineer a regulatory network of core processes, and correctly identified the involvement of E2F1, GATA2 and NFKB1 in the regulation of cell cycle, fat, and muscle/glycolysis, respectively. Conclusion The pivotal implication of our research is two-fold: (1 there exists a robust genome-wide expression signal between TFs and their predicted TGs in cattle muscle consistent with the extent of promoter sharing; and (2 this signal can be exploited to recover the cellular mechanisms underpinning transcription regulation of muscle structure and development in bovine. Our study represents the first genome-wide report linking tissue specific co-expression to co-regulation in a non-model vertebrate.

  15. Integrating experimental and analytic approaches to improve data quality in genome-wide RNAi screens.

    Science.gov (United States)

    Zhang, Xiaohua Douglas; Espeseth, Amy S; Johnson, Eric N; Chin, Jayne; Gates, Adam; Mitnaul, Lyndon J; Marine, Shane D; Tian, Jenny; Stec, Eric M; Kunapuli, Priya; Holder, Dan J; Heyse, Joseph F; Strulovici, Berta; Ferrer, Marc

    2008-06-01

    RNA interference (RNAi) not only plays an important role in drug discovery but can also be developed directly into drugs. RNAi high-throughput screening (HTS) biotechnology allows us to conduct genome-wide RNAi research. A central challenge in genome-wide RNAi research is to integrate both experimental and computational approaches to obtain high quality RNAi HTS assays. Based on our daily practice in RNAi HTS experiments, we propose the implementation of 3 experimental and analytic processes to improve the quality of data from RNAi HTS biotechnology: (1) select effective biological controls; (2) adopt appropriate plate designs to display and/or adjust for systematic errors of measurement; and (3) use effective analytic metrics to assess data quality. The applications in 5 real RNAi HTS experiments demonstrate the effectiveness of integrating these processes to improve data quality. Due to the effectiveness in improving data quality in RNAi HTS experiments, the methods and guidelines contained in the 3 experimental and analytic processes are likely to have broad utility in genome-wide RNAi research.

  16. Genome-wide analysis of interactions between ATP-dependent chromatin remodeling and histone modifications

    Directory of Open Access Journals (Sweden)

    Wang Jiang

    2009-07-01

    Full Text Available Abstract Background ATP-dependent chromatin remodeling and the covalent modification of histones play central roles in determining chromatin structure and function. Although several specific interactions between these two activities have been elaborated, the global landscape remains to be elucidated. Results In this paper, we have developed a computational method to generate the first genome-wide landscape of interactions between ATP-dependent chromatin remodeling and the covalent modification of histones in Saccharomyces cerevisiae. Our method succeeds in identifying known interactions and uncovers many previously unknown interactions between these two activities. Analysis of the genome-wide picture revealed that transcription-related modifications tend to interact with more chromatin remodelers. Our results also demonstrate that most chromatin remodeling-modification interactions act via interactions of remodelers with both histone-modifying enzymes and histone residues. We also found that the co-occurrence of both modification and remodeling has significantly different influences on multiple gene features (e.g. nucleosome occupancy compared with the presence of either one. Conclusion We gave the first genome-wide picture of ATP-dependent chromatin remodeling-histone modification interactions. We also revealed how these two activities work together to regulate chromatin structure and function. Our results suggest that distinct strategies for regulating chromatin activity are selectively employed by genes with different properties.

  17. Genome-wide association study for wool production traits in a Chinese Merino sheep population.

    Directory of Open Access Journals (Sweden)

    Zhipeng Wang

    Full Text Available Genome-wide association studies (GWAS provide a powerful approach for identifying quantitative trait loci without prior knowledge of location or function. To identify loci associated with wool production traits, we performed a genome-wide association study on a total of 765 Chinese Merino sheep (JunKen type genotyped with 50 K single nucleotide polymorphisms (SNPs. In the present study, five wool production traits were examined: fiber diameter, fiber diameter coefficient of variation, fineness dispersion, staple length and crimp. We detected 28 genome-wide significant SNPs for fiber diameter, fiber diameter coefficient of variation, fineness dispersion, and crimp trait in the Chinese Merino sheep. About 43% of the significant SNP markers were located within known or predicted genes, including YWHAZ, KRTCAP3, TSPEAR, PIK3R4, KIF16B, PTPN3, GPRC5A, DDX47, TCF9, TPTE2, EPHA5 and NBEA genes. Our results not only confirm the results of previous reports, but also provide a suite of novel SNP markers and candidate genes associated with wool traits. Our findings will be useful for exploring the genetic control of wool traits in sheep.

  18. Genome-wide association study for wool production traits in a Chinese Merino sheep population.

    Science.gov (United States)

    Wang, Zhipeng; Zhang, Hui; Yang, Hua; Wang, Shouzhi; Rong, Enguang; Pei, Wenyu; Li, Hui; Wang, Ning

    2014-01-01

    Genome-wide association studies (GWAS) provide a powerful approach for identifying quantitative trait loci without prior knowledge of location or function. To identify loci associated with wool production traits, we performed a genome-wide association study on a total of 765 Chinese Merino sheep (JunKen type) genotyped with 50 K single nucleotide polymorphisms (SNPs). In the present study, five wool production traits were examined: fiber diameter, fiber diameter coefficient of variation, fineness dispersion, staple length and crimp. We detected 28 genome-wide significant SNPs for fiber diameter, fiber diameter coefficient of variation, fineness dispersion, and crimp trait in the Chinese Merino sheep. About 43% of the significant SNP markers were located within known or predicted genes, including YWHAZ, KRTCAP3, TSPEAR, PIK3R4, KIF16B, PTPN3, GPRC5A, DDX47, TCF9, TPTE2, EPHA5 and NBEA genes. Our results not only confirm the results of previous reports, but also provide a suite of novel SNP markers and candidate genes associated with wool traits. Our findings will be useful for exploring the genetic control of wool traits in sheep.

  19. Cooperative genome-wide analysis shows increased homozygosity in early onset Parkinson's disease.

    Directory of Open Access Journals (Sweden)

    Javier Simón-Sánchez

    Full Text Available Parkinson's disease (PD occurs in both familial and sporadic forms, and both monogenic and complex genetic factors have been identified. Early onset PD (EOPD is particularly associated with autosomal recessive (AR mutations, and three genes, PARK2, PARK7 and PINK1, have been found to carry mutations leading to AR disease. Since mutations in these genes account for less than 10% of EOPD patients, we hypothesized that further recessive genetic factors are involved in this disorder, which may appear in extended runs of homozygosity.We carried out genome wide SNP genotyping to look for extended runs of homozygosity (ROHs in 1,445 EOPD cases and 6,987 controls. Logistic regression analyses showed an increased level of genomic homozygosity in EOPD cases compared to controls. These differences are larger for ROH of 9 Mb and above, where there is a more than three-fold increase in the proportion of cases carrying a ROH. These differences are not explained by occult recessive mutations at existing loci. Controlling for genome wide homozygosity in logistic regression analyses increased the differences between cases and controls, indicating that in EOPD cases ROHs do not simply relate to genome wide measures of inbreeding. Homozygosity at a locus on chromosome19p13.3 was identified as being more common in EOPD cases as compared to controls. Sequencing analysis of genes and predicted transcripts within this locus failed to identify a novel mutation causing EOPD in our cohort.There is an increased rate of genome wide homozygosity in EOPD, as measured by an increase in ROHs. These ROHs are a signature of inbreeding and do not necessarily harbour disease-causing genetic variants. Although there might be other regions of interest apart from chromosome 19p13.3, we lack the power to detect them with this analysis.

  20. Simultaneous analysis of all SNPs in genome-wide and re-sequencing association studies.

    Directory of Open Access Journals (Sweden)

    Clive J Hoggart

    2008-07-01

    Full Text Available Testing one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants, which is a plausible scenario for many complex diseases. We show that simultaneous analysis of the entire set of SNPs from a genome-wide study to identify the subset that best predicts disease outcome is now feasible, thanks to developments in stochastic search methods. We used a Bayesian-inspired penalised maximum likelihood approach in which every SNP can be considered for additive, dominant, and recessive contributions to disease risk. Posterior mode estimates were obtained for regression coefficients that were each assigned a prior with a sharp mode at zero. A non-zero coefficient estimate was interpreted as corresponding to a significant SNP. We investigated two prior distributions and show that the normal-exponential-gamma prior leads to improved SNP selection in comparison with single-SNP tests. We also derived an explicit approximation for type-I error that avoids the need to use permutation procedures. As well as genome-wide analyses, our method is well-suited to fine mapping with very dense SNP sets obtained from re-sequencing and/or imputation. It can accommodate quantitative as well as case-control phenotypes, covariate adjustment, and can be extended to search for interactions. Here, we demonstrate the power and empirical type-I error of our approach using simulated case-control data sets of up to 500 K SNPs, a real genome-wide data set of 300 K SNPs, and a sequence-based dataset, each of which can be analysed in a few hours on a desktop workstation.

  1. Computer loss experience and predictions

    Science.gov (United States)

    Parker, Donn B.

    1996-03-01

    The types of losses organizations must anticipate have become more difficult to predict because of the eclectic nature of computers and the data communications and the decrease in news media reporting of computer-related losses as they become commonplace. Total business crime is conjectured to be decreasing in frequency and increasing in loss per case as a result of increasing computer use. Computer crimes are probably increasing, however, as their share of the decreasing business crime rate grows. Ultimately all business crime will involve computers in some way, and we could see a decline of both together. The important information security measures in high-loss business crime generally concern controls over authorized people engaged in unauthorized activities. Such controls include authentication of users, analysis of detailed audit records, unannounced audits, segregation of development and production systems and duties, shielding the viewing of screens, and security awareness and motivation controls in high-value transaction areas. Computer crimes that involve highly publicized intriguing computer misuse methods, such as privacy violations, radio frequency emanations eavesdropping, and computer viruses, have been reported in waves that periodically have saturated the news media during the past 20 years. We must be able to anticipate such highly publicized crimes and reduce the impact and embarrassment they cause. On the basis of our most recent experience, I propose nine new types of computer crime to be aware of: computer larceny (theft and burglary of small computers), automated hacking (use of computer programs to intrude), electronic data interchange fraud (business transaction fraud), Trojan bomb extortion and sabotage (code security inserted into others' systems that can be triggered to cause damage), LANarchy (unknown equipment in use), desktop forgery (computerized forgery and counterfeiting of documents), information anarchy (indiscriminate use of

  2. Epigenomic model of cardiac enhancers with application to genome wide association studies.

    Science.gov (United States)

    Sahu, Avinash Das; Aniba, Radhouane; Chang, Yen-Pei Christy; Hannenhalli, Sridhar

    2013-01-01

    Mammalian gene regulation is often mediated by distal enhancer elements, in particular, for tissue specific and developmental genes. Computational identification of enhancers is difficult because they do not exhibit clear location preference relative to their target gene and also because they lack clearly distinguishing genomic features. This represents a major challenge in deciphering transcriptional regulation. Recent ChIP-seq based genome-wide investigation of epigenomic modifications have revealed that enhancers are often enriched for certain epigenomic marks. Here we utilize the epigenomic data in human heart tissue along with validated human heart enhancers to develop a Support Vector Machine (SVM) model of cardiac enhancers. Cross-validation classification accuracy of our model was 84% and 92% on positive and negative sets respectively with ROC AUC = 0.92. More importantly, while P300 binding has been used as gold standard for enhancers, our model can distinguish P300-bound validated enhancers from other P300-bound regions that failed to exhibit enhancer activity in transgenic mouse. While GWAS studies reveal polymorphic regions associated with certain phenotypes, they do not immediately provide causality. Next, we hypothesized that genomic regions containing a GWAS SNP associated with a cardiac phenotype might contain another SNP in a cardiac enhancer, which presumably mediates the phenotype. Starting with a comprehensive set of SNPs associated with cardiac phenotypes in GWAS studies, we scored other SNPs in LD with the GWAS SNP according to its probability of being an enhancer and choose one with best score in the LD as enhancer. We found that our predicted enhancers are enriched for known cardiac transcriptional regulator motifs and are likely to regulate the nearby gene. Importantly, these tendencies are more favorable for the predicted enhancers compared with an approach that uses P300 binding as a marker of enhancer activity.

  3. Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits

    NARCIS (Netherlands)

    Speliotes, E.K.; Yerges-Armstrong, L.M.; Wu, J.; Hernaez, R.; Kim, L.J.; Palmer, C.D.; Gudnason, V.; Eiriksdottir, G.; Garcia, M.E.; Launer, L.J.; Nalls, M.A.; Clark, J.M.; Mitchell, B.D.; Shuldiner, A.R.; Butler, J.L.; Tomas, M.; Hoffmann, U.; Hwang, S.J.; Massaro, J.M.; O'Donnell, C.J.; Sahani, D.V.; Salomaa, V.; Schadt, E.E.; Schwartz, S.M.; Siscovick, D.S.; Voight, B.F.; Carr, J.J.; Feitosa, M.F.; Harris, T.B.; Fox, C.S.; Smith, A.V.; Kao, W.H.; Hirschhorn, J.N.; Borecki, I.B.; Heijer, M. den

    2011-01-01

    Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic

  4. Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits

    DEFF Research Database (Denmark)

    Speliotes, Elizabeth K; Yerges-Armstrong, Laura M; Wu, Jun

    2011-01-01

    Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic...

  5. Genome-Wide Association Analysis Identifies Variants Associated with Nonalcoholic Fatty Liver Disease That Have Distinct Effects on Metabolic Traits

    NARCIS (Netherlands)

    Speliotes, Elizabeth K.; Yerges-Armstrong, Laura M.; Wu, Jun; Hernaez, Ruben; Kim, Lauren J.; Palmer, Cameron D.; Gudnason, Vilmundur; Eiriksdottir, Gudny; Garcia, Melissa E.; Launer, Lenore J.; Nalls, Michael A.; Clark, Jeanne M.; Mitchell, Braxton D.; Shuldiner, Alan R.; Butler, Johannah L.; Tomas, Marta; Hoffmann, Udo; Hwang, Shih-Jen; Massaro, Joseph M.; O'Donnell, Christopher J.; Sahani, Dushyant V.; Salomaa, Veikko; Schadt, Eric E.; Schwartz, Stephen M.; Siscovick, David S.; Voight, Benjamin F.; Carr, J. Jeffrey; Feitosa, Mary F.; Harris, Tamara B.; Fox, Caroline S.; Smith, Albert V.; Kao, W. H. Linda; Hirschhorn, Joel N.; Borecki, Ingrid B.

    2011-01-01

    Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic st

  6. Genome-wide analysis of regions similar to promoters of histone genes

    KAUST Repository

    Chowdhary, Rajesh

    2010-05-28

    Background: The purpose of this study is to: i) develop a computational model of promoters of human histone-encoding genes (shortly histone genes), an important class of genes that participate in various critical cellular processes, ii) use the model so developed to identify regions across the human genome that have similar structure as promoters of histone genes; such regions could represent potential genomic regulatory regions, e.g. promoters, of genes that may be coregulated with histone genes, and iii/ identify in this way genes that have high likelihood of being coregulated with the histone genes.Results: We successfully developed a histone promoter model using a comprehensive collection of histone genes. Based on leave-one-out cross-validation test, the model produced good prediction accuracy (94.1% sensitivity, 92.6% specificity, and 92.8% positive predictive value). We used this model to predict across the genome a number of genes that shared similar promoter structures with the histone gene promoters. We thus hypothesize that these predicted genes could be coregulated with histone genes. This hypothesis matches well with the available gene expression, gene ontology, and pathways data. Jointly with promoters of the above-mentioned genes, we found a large number of intergenic regions with similar structure as histone promoters.Conclusions: This study represents one of the most comprehensive computational analyses conducted thus far on a genome-wide scale of promoters of human histone genes. Our analysis suggests a number of other human genes that share a high similarity of promoter structure with the histone genes and thus are highly likely to be coregulated, and consequently coexpressed, with the histone genes. We also found that there are a large number of intergenic regions across the genome with their structures similar to promoters of histone genes. These regions may be promoters of yet unidentified genes, or may represent remote control regions that

  7. Wrapper-based selection of genetic features in genome-wide association studies through fast matrix operations.

    Science.gov (United States)

    Pahikkala, Tapio; Okser, Sebastian; Airola, Antti; Salakoski, Tapio; Aittokallio, Tero

    2012-05-02

    Through the wealth of information contained within them, genome-wide association studies (GWAS) have the potential to provide researchers with a systematic means of associating genetic variants with a wide variety of disease phenotypes. Due to the limitations of approaches that have analyzed single variants one at a time, it has been proposed that the genetic basis of these disorders could be determined through detailed analysis of the genetic variants themselves and in conjunction with one another. The construction of models that account for these subsets of variants requires methodologies that generate predictions based on the total risk of a particular group of polymorphisms. However, due to the excessive number of variants, constructing these types of models has so far been computationally infeasible. We have implemented an algorithm, known as greedy RLS, that we use to perform the first known wrapper-based feature selection on the genome-wide level. The running time of greedy RLS grows linearly in the number of training examples, the number of features in the original data set, and the number of selected features. This speed is achieved through computational short-cuts based on matrix calculus. Since the memory consumption in present-day computers can form an even tighter bottleneck than running time, we also developed a space efficient variation of greedy RLS which trades running time for memory. These approaches are then compared to traditional wrapper-based feature selection implementations based on support vector machines (SVM) to reveal the relative speed-up and to assess the feasibility of the new algorithm. As a proof of concept, we apply greedy RLS to the Hypertension - UK National Blood Service WTCCC dataset and select the most predictive variants using 3-fold external cross-validation in less than 26 minutes on a high-end desktop. On this dataset, we also show that greedy RLS has a better classification performance on independent test data than a

  8. Genome-wide Association Study of Obsessive-Compulsive Disorder

    Science.gov (United States)

    Stewart, S Evelyn; Yu, Dongmei; Scharf, Jeremiah M; Neale, Benjamin M; Fagerness, Jesen A; Mathews, Carol A; Arnold, Paul D; Evans, Patrick D; Gamazon, Eric R; Osiecki, Lisa; McGrath, Lauren; Haddad, Stephen; Crane, Jacquelyn; Hezel, Dianne; Illman, Cornelia; Mayerfeld, Catherine; Konkashbaev, Anuar; Liu, Chunyu; Pluzhnikov, Anna; Tikhomirov, Anna; Edlund, Christopher K; Rauch, Scott L; Moessner, Rainald; Falkai, Peter; Maier, Wolfgang; Ruhrmann, Stephan; Grabe, Hans-Jörgen; Lennertz, Leonard; Wagner, Michael; Bellodi, Laura; Cavallini, Maria Cristina; Richter, Margaret A; Cook, Edwin H; Kennedy, James L; Rosenberg, David; Stein, Dan J; Hemmings, Sian MJ; Lochner, Christine; Azzam, Amin; Chavira, Denise A; Fournier, Eduardo; Garrido, Helena; Sheppard, Brooke; Umaña, Paul; Murphy, Dennis L; Wendland, Jens R; Veenstra-VanderWeele, Jeremy; Denys, Damiaan; Blom, Rianne; Deforce, Dieter; Van Nieuwerburgh, Filip; Westenberg, Herman GM; Walitza, Susanne; Egberts, Karin; Renner, Tobias; Miguel, Euripedes Constantino; Cappi, Carolina; Hounie, Ana G; Conceição do Rosário, Maria; Sampaio, Aline S; Vallada, Homero; Nicolini, Humberto; Lanzagorta, Nuria; Camarena, Beatriz; Delorme, Richard; Leboyer, Marion; Pato, Carlos N; Pato, Michele T; Voyiaziakis, Emanuel; Heutink, Peter; Cath, Danielle C; Posthuma, Danielle; Smit, Jan H; Samuels, Jack; Bienvenu, O Joseph; Cullen, Bernadette; Fyer, Abby J; Grados, Marco A; Greenberg, Benjamin D; McCracken, James T; Riddle, Mark A; Wang, Ying; Coric, Vladimir; Leckman, James F; Bloch, Michael; Pittenger, Christopher; Eapen, Valsamma; Black, Donald W; Ophoff, Roel A; Strengman, Eric; Cusi, Daniele; Turiel, Maurizio; Frau, Francesca; Macciardi, Fabio; Gibbs, J Raphael; Cookson, Mark R; Singleton, Andrew; Hardy, John; Crenshaw, Andrew T; Parkin, Melissa A; Mirel, Daniel B; Conti, David V; Purcell, Shaun; Nestadt, Gerald; Hanna, Gregory L; Jenike, Michael A; Knowles, James A; Cox, Nancy; Pauls, David L

    2014-01-01

    Obsessive-compulsive disorder (OCD) is a common, debilitating neuropsychiatric illness with complex genetic etiology. The International OCD Foundation Genetics Collaborative (IOCDF-GC) is a multi-national collaboration established to discover the genetic variation predisposing to OCD. A set of individuals affected with DSM-IV OCD, a subset of their parents, and unselected controls, were genotyped with several different Illumina SNP microarrays. After extensive data cleaning, 1,465 cases, 5,557 ancestry-matched controls and 400 complete trios remained, with a common set of 469,410 autosomal and 9,657 X-chromosome SNPs. Ancestry-stratified case-control association analyses were conducted for three genetically-defined subpopulations and combined in two meta-analyses, with and without the trio-based analysis. In the case-control analysis, the lowest two p-values were located within DLGAP1 (p=2.49×10-6 and p=3.44×10-6), a member of the neuronal postsynaptic density complex. In the trio analysis, rs6131295, near BTBD3, exceeded the genome-wide significance threshold with a p-value=3.84 × 10-8. However, when trios were meta-analyzed with the combined case-control samples, the p-value for this variant was 3.62×10-5, losing genome-wide significance. Although no SNPs were identified to be associated with OCD at a genome-wide significant level in the combined trio-case-control sample, a significant enrichment of methylation-QTLs (p<0.001) and frontal lobe eQTLs (p=0.001) was observed within the top-ranked SNPs (p<0.01) from the trio-case-control analysis, suggesting these top signals may have a broad role in gene expression in the brain, and possibly in the etiology of OCD. PMID:22889921

  9. Genome-wide landscapes of human local adaptation in Asia.

    Directory of Open Access Journals (Sweden)

    Wei Qian

    Full Text Available Genetic studies of human local adaptation have been facilitated greatly by recent advances in high-throughput genotyping and sequencing technologies. However, few studies have investigated local adaptation in Asian populations on a genome-wide scale and with a high geographic resolution. In this study, taking advantage of the dense population coverage in Southeast Asia, which is the part of the world least studied in term of natural selection, we depicted genome-wide landscapes of local adaptations in 63 Asian populations representing the majority of linguistic and ethnic groups in Asia. Using genome-wide data analysis, we discovered many genes showing signs of local adaptation or natural selection. Notable examples, such as FOXQ1, MAST2, and CDH4, were found to play a role in hair follicle development and human cancer, signal transduction, and tumor repression, respectively. These showed strong indications of natural selection in Philippine Negritos, a group of aboriginal hunter-gatherers living in the Philippines. MTTP, which has associations with metabolic syndrome, body mass index, and insulin regulation, showed a strong signature of selection in Southeast Asians, including Indonesians. Functional annotation analysis revealed that genes and genetic variants underlying natural selections were generally enriched in the functional category of alternative splicing. Specifically, many genes showing significant difference with respect to allele frequency between northern and southern Asian populations were found to be associated with human height and growth and various immune pathways. In summary, this study contributes to the overall understanding of human local adaptation in Asia and has identified both known and novel signatures of natural selection in the human genome.

  10. Genome-wide association studies and contribution to cardiovascular physiology.

    Science.gov (United States)

    Munroe, Patricia B; Tinker, Andrew

    2015-09-01

    The study of family pedigrees with rare monogenic cardiovascular disorders has revealed new molecular players in physiological processes. Genome-wide association studies of complex traits with a heritable component may afford a similar and potentially intellectually richer opportunity. In this review we focus on the interpretation of genetic associations and the issue of causality in relation to known and potentially new physiology. We mainly discuss cardiometabolic traits as it reflects our personal interests, but the issues pertain broadly in many other disciplines. We also describe some of the resources that are now available that may expedite follow up of genetic association signals into observations on causal mechanisms and pathophysiology.

  11. [Genome-wide association study for adolescent idiopathic scoliosis].

    Science.gov (United States)

    Ogura, Yoji; Kou, Ikuyo; Scoliosis, Japan; Matsumoto, Morio; Watanabe, Kota; Ikegawa, Shiro

    2016-04-01

    Adolescent idiopathic scoliosis(AIS)is a polygenic disease. Genome-wide association studies(GWASs)have been performed for a lot of polygenic diseases. For AIS, we conducted GWAS and identified the first AIS locus near LBX1. After the discovery, we have extended our study by increasing the numbers of subjects and SNPs. In total, our Japanese GWAS has identified four susceptibility genes. GWASs for AIS have also been performed in the USA and China, which identified one and three susceptibility genes, respectively. Here we review GWASs in Japan and abroad and functional analysis to clarify the pathomechanism of AIS.

  12. Genome-wide approaches to understanding human ageing

    Directory of Open Access Journals (Sweden)

    Kaeberlein Matt

    2006-06-01

    Full Text Available Abstract The use of genomic technologies in biogerontology has the potential to greatly enhance our understanding of human ageing. High-throughput screens for alleles correlated with survival in long-lived people have uncovered novel genes involved in age-associated disease. Genome-wide longevity studies in simple eukaryotes are identifying evolutionarily conserved pathways that determine longevity. It is hoped that validation of these 'public' aspects of ageing in mice, along with analyses of variation in candidate human ageing genes, will provide targets for future interventions to slow the ageing process and retard the onset of age-associated pathologies.

  13. Genome-wide approaches to understanding behaviour in Drosophila melanogaster.

    Science.gov (United States)

    Neville, Megan; Goodwin, Stephen F

    2012-09-01

    Understanding how an organism exhibits specific behaviours remains a major and important biological question. Studying behaviour in a simple model organism like the fruit fly Drosophila melanogaster has the advantages of advanced molecular genetics approaches along with well-defined anatomy and physiology. With advancements in functional genomic technologies, researchers are now attempting to uncover genes and pathways involved in complex behaviours on a genome-wide scale. A systems-level network approach, which will include genomic approaches, to study behaviour will be key to understanding the regulation and modulation of behaviours and the importance of context in regulating them.

  14. Arabidopsis transcription factors: genome-wide comparative analysis among eukaryotes.

    Science.gov (United States)

    Riechmann, J L; Heard, J; Martin, G; Reuber, L; Jiang, C; Keddie, J; Adam, L; Pineda, O; Ratcliffe, O J; Samaha, R R; Creelman, R; Pilgrim, M; Broun, P; Zhang, J Z; Ghandehari, D; Sherman, B K; Yu, G

    2000-12-15

    The completion of the Arabidopsis thaliana genome sequence allows a comparative analysis of transcriptional regulators across the three eukaryotic kingdoms. Arabidopsis dedicates over 5% of its genome to code for more than 1500 transcription factors, about 45% of which are from families specific to plants. Arabidopsis transcription factors that belong to families common to all eukaryotes do not share significant similarity with those of the other kingdoms beyond the conserved DNA binding domains, many of which have been arranged in combinations specific to each lineage. The genome-wide comparison reveals the evolutionary generation of diversity in the regulation of transcription.

  15. Genome-wide discovery and verification of novel structured RNAs in Plasmodium falciparum

    DEFF Research Database (Denmark)

    Mourier, Tobias; Carret, Celine; Kyes, Sue;

    2008-01-01

    We undertook a genome-wide search for novel noncoding RNAs (ncRNA) in the malaria parasite Plasmodium falciparum. We used the RNAz program to predict structures in the noncoding regions of the P. falciparum 3D7 genome that were conserved with at least one of seven other Plasmodium spp. genome seq...

  16. Genome-wide search for miRNA-target interactions in Arabidopsis thaliana with an integrated approach

    Directory of Open Access Journals (Sweden)

    Ding Jiandong

    2012-06-01

    Full Text Available Abstract Background MiRNA are about 22nt long small noncoding RNAs that post transcriptionally regulate gene expression in animals, plants and protozoa. Confident identification of MiRNA-Target Interactions (MTI is vital to understand their function. Currently, several integrated computational programs and databases are available for animal miRNAs, the mechanisms of which are significantly different from plant miRNAs. Methods Here we present an integrated MTI prediction and analysis toolkit (imiRTP for Arabidopsis thaliana. It features two important functions: (i combination of several effective plant miRNA target prediction methods provides a sufficiently large MTI candidate set, and (ii different filters allow for an efficient selection of potential targets. The modularity of imiRTP enables the prediction of high quality targets on genome-wide scale. Moreover, predicted MTIs can be presented in various ways, which allows for browsing through the putative target sites as well as conducting simple and advanced analyses. Results Results show that imiRTP could always find high quality candidates compared with single method by choosing appropriate filter and parameter. And we also reveal that a portion of plant miRNA could bind target genes out of coding region. Based on our results, imiRTP could facilitate the further study of Arabidopsis miRNAs in real use. All materials of imiRTP are freely available under a GNU license at (http://admis.fudan.edu.cn/projects/imiRTP.htm.

  17. A genome-wide association study of female sexual dysfunction.

    Directory of Open Access Journals (Sweden)

    Andrea Burri

    Full Text Available BACKGROUND: Female sexual dysfunction (FSD is an important but controversial problem with serious negative impact on women's quality of life. Data from twin studies have shown a genetic contribution to the development and maintenance of FSD. METHODOLOGY/PRINCIPAL FINDINGS: We performed a genome-wide association study (GWAS on 2.5 million single-nucleotide polymorphisms (SNPs in 1,104 female twins (25-81 years of age in a population-based register and phenotypic data on lifelong sexual functioning. Although none reached conventional genome-wide level of significance (10 × -8, we found strongly suggestive associations with the phenotypic dimension of arousal (rs13202860, P = 1.2 × 10(-7; rs1876525, P = 1.2 × 10(-7; and rs13209281 P = 8.3 × 10(-7 on chromosome 6, around 500 kb upstream of the locus HTR1E (5-hydroxytryptamine receptor 1E locus, related to the serotonin brain pathways. We could not replicate previously reported candidate SNPs associated with FSD in the DRD4, 5HT2A and IL-1B loci. CONCLUSIONS/SIGNIFICANCE: We report the first GWAS of FSD symptoms in humans. This has pointed to several "risk alleles" and the implication of the serotonin and GABA pathways. Ultimately, understanding key mechanisms via this research may lead to new FSD treatments and inform clinical practice and developments in psychiatric nosology.

  18. A Pooled Genome-Wide Association Study of Asperger Syndrome.

    Directory of Open Access Journals (Sweden)

    Varun Warrier

    Full Text Available Asperger Syndrome (AS is a neurodevelopmental condition characterized by impairments in social interaction and communication, alongside the presence of unusually repetitive, restricted interests and stereotyped behaviour. Individuals with AS have no delay in cognitive and language development. It is a subset of Autism Spectrum Conditions (ASC, which are highly heritable and has a population prevalence of approximately 1%. Few studies have investigated the genetic basis of AS. To address this gap in the literature, we performed a genome-wide pooled DNA association study to identify candidate loci in 612 individuals (294 cases and 318 controls of Caucasian ancestry, using the Affymetrix GeneChip Human Mapping version 6.0 array. We identified 11 SNPs that had a p-value below 1x10-5. These SNPs were independently genotyped in the same sample. Three of the SNPs (rs1268055, rs7785891 and rs2782448 were nominally significant, though none remained significant after Bonferroni correction. Two of our top three SNPs (rs7785891 and rs2782448 lie in loci previously implicated in ASC. However, investigation of the three SNPs in the ASC genome-wide association dataset from the Psychiatric Genomics Consortium indicated that these three SNPs were not significantly associated with ASC. The effect sizes of the variants were modest, indicating that our study was not sufficiently powered to identify causal variants with precision.

  19. Genome-wide association studies of obesity and metabolic syndrome.

    Science.gov (United States)

    Fall, Tove; Ingelsson, Erik

    2014-01-25

    Until just a few years ago, the genetic determinants of obesity and metabolic syndrome were largely unknown, with the exception of a few forms of monogenic extreme obesity. Since genome-wide association studies (GWAS) became available, large advances have been made. The first single nucleotide polymorphism robustly associated with increased body mass index (BMI) was in 2007 mapped to a gene with for the time unknown function. This gene, now known as fat mass and obesity associated (FTO) has been repeatedly replicated in several ethnicities and is affecting obesity by regulating appetite. Since the first report from a GWAS of obesity, an increasing number of markers have been shown to be associated with BMI, other measures of obesity or fat distribution and metabolic syndrome. This systematic review of obesity GWAS will summarize genome-wide significant findings for obesity and metabolic syndrome and briefly give a few suggestions of what is to be expected in the next few years. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  20. Genome-wide mapping of DNA strand breaks.

    Directory of Open Access Journals (Sweden)

    Frédéric Leduc

    Full Text Available Determination of cellular DNA damage has so far been limited to global assessment of genome integrity whereas nucleotide-level mapping has been restricted to specific loci by the use of specific primers. Therefore, only limited DNA sequences can be studied and novel regions of genomic instability can hardly be discovered. Using a well-characterized yeast model, we describe a straightforward strategy to map genome-wide DNA strand breaks without compromising nucleotide-level resolution. This technique, termed "damaged DNA immunoprecipitation" (dDIP, uses immunoprecipitation and the terminal deoxynucleotidyl transferase-mediated dUTP-biotin end-labeling (TUNEL to capture DNA at break sites. When used in combination with microarray or next-generation sequencing technologies, dDIP will allow researchers to map genome-wide DNA strand breaks as well as other types of DNA damage and to establish a clear profiling of altered genes and/or intergenic sequences in various experimental conditions. This mapping technique could find several applications for instance in the study of aging, genotoxic drug screening, cancer, meiosis, radiation and oxidative DNA damage.

  1. A Pooled Genome-Wide Association Study of Asperger Syndrome.

    Science.gov (United States)

    Warrier, Varun; Chakrabarti, Bhismadev; Murphy, Laura; Chan, Allen; Craig, Ian; Mallya, Uma; Lakatošová, Silvia; Rehnstrom, Karola; Peltonen, Leena; Wheelwright, Sally; Allison, Carrie; Fisher, Simon E; Baron-Cohen, Simon

    2015-01-01

    Asperger Syndrome (AS) is a neurodevelopmental condition characterized by impairments in social interaction and communication, alongside the presence of unusually repetitive, restricted interests and stereotyped behaviour. Individuals with AS have no delay in cognitive and language development. It is a subset of Autism Spectrum Conditions (ASC), which are highly heritable and has a population prevalence of approximately 1%. Few studies have investigated the genetic basis of AS. To address this gap in the literature, we performed a genome-wide pooled DNA association study to identify candidate loci in 612 individuals (294 cases and 318 controls) of Caucasian ancestry, using the Affymetrix GeneChip Human Mapping version 6.0 array. We identified 11 SNPs that had a p-value below 1x10-5. These SNPs were independently genotyped in the same sample. Three of the SNPs (rs1268055, rs7785891 and rs2782448) were nominally significant, though none remained significant after Bonferroni correction. Two of our top three SNPs (rs7785891 and rs2782448) lie in loci previously implicated in ASC. However, investigation of the three SNPs in the ASC genome-wide association dataset from the Psychiatric Genomics Consortium indicated that these three SNPs were not significantly associated with ASC. The effect sizes of the variants were modest, indicating that our study was not sufficiently powered to identify causal variants with precision.

  2. Genome-wide patterns of Arabidopsis gene expression in nature.

    Directory of Open Access Journals (Sweden)

    Christina L Richards

    Full Text Available Organisms in the wild are subject to multiple, fluctuating environmental factors, and it is in complex natural environments that genetic regulatory networks actually function and evolve. We assessed genome-wide gene expression patterns in the wild in two natural accessions of the model plant Arabidopsis thaliana and examined the nature of transcriptional variation throughout its life cycle and gene expression correlations with natural environmental fluctuations. We grew plants in a natural field environment and measured genome-wide time-series gene expression from the plant shoot every three days, spanning the seedling to reproductive stages. We find that 15,352 genes were expressed in the A. thaliana shoot in the field, and accession and flowering status (vegetative versus flowering were strong components of transcriptional variation in this plant. We identified between ∼110 and 190 time-varying gene expression clusters in the field, many of which were significantly overrepresented by genes regulated by abiotic and biotic environmental stresses. The two main principal components of vegetative shoot gene expression (PC(veg correlate to temperature and precipitation occurrence in the field. The largest PC(veg axes included thermoregulatory genes while the second major PC(veg was associated with precipitation and contained drought-responsive genes. By exposing A. thaliana to natural environments in an open field, we provide a framework for further understanding the genetic networks that are deployed in natural environments, and we connect plant molecular genetics in the laboratory to plant organismal ecology in the wild.

  3. Planning and executing a genome wide association study (GWAS).

    Science.gov (United States)

    Sale, Michèle M; Mychaleckyj, Josyf C; Chen, Wei-Min

    2009-01-01

    In recent years, genome-wide association approaches have proven a powerful and successful strategy to identify genetic contributors to complex traits, including a number of endocrine disorders. Their success has meant that genome wide association studies (GWAS) are fast becoming the default study design for discovery of new genetic variants that influence a clinical trait or phenotype. This chapter focuses on a number of key elements that require consideration for the successful conduct of a GWAS. Although many of the considerations are common to any genetic study, the greater cost, extreme multiple testing, and greater openness to data sharing require specific awareness and planning by investigators. In the section on designing a GWAS, we reflect on ethical considerations, study design, selection of phenotype/s, power considerations, sample tracking and storage issues, and genotyping product selection. During execution, important considerations include DNA quantity and preparation, genotyping methods, quality control checks of genotype data, in silico genotyping (imputation), tests of association, and replication of association signals. Although the field of human genetics is rapidly evolving, recent experiences can help guide an investigator in making practical and methodological choices that will eventually determine the overall quality of GWAS results. Given the investment to recruit patient populations or cohorts that are powered for a GWAS, and the still substantial costs associated with genotyping, it is helpful to be aware of these aspects to maximize the likelihood of success, especially where there is an opportunity for implementing them prospectively.

  4. Genome-wide patterns of nucleotide polymorphism in domesticated rice.

    Directory of Open Access Journals (Sweden)

    Ana L Caicedo

    2007-09-01

    Full Text Available Domesticated Asian rice (Oryza sativa is one of the oldest domesticated crop species in the world, having fed more people than any other plant in human history. We report the patterns of DNA sequence variation in rice and its wild ancestor, O. rufipogon, across 111 randomly chosen gene fragments, and use these to infer the evolutionary dynamics that led to the origins of rice. There is a genome-wide excess of high-frequency derived single nucleotide polymorphisms (SNPs in O. sativa varieties, a pattern that has not been reported for other crop species. We developed several alternative models to explain contemporary patterns of polymorphisms in rice, including a (i selectively neutral population bottleneck model, (ii bottleneck plus migration model, (iii multiple selective sweeps model, and (iv bottleneck plus selective sweeps model. We find that a simple bottleneck model, which has been the dominant demographic model for domesticated species, cannot explain the derived nucleotide polymorphism site frequency spectrum in rice. Instead, a bottleneck model that incorporates selective sweeps, or a more complex demographic model that includes subdivision and gene flow, are more plausible explanations for patterns of variation in domesticated rice varieties. If selective sweeps are indeed the explanation for the observed nucleotide data of domesticated rice, it suggests that strong selection can leave its imprint on genome-wide polymorphism patterns, contrary to expectations that selection results only in a local signature of variation.

  5. Genome-wide mapping of DNA methylation in chicken.

    Directory of Open Access Journals (Sweden)

    Qinghe Li

    Full Text Available Cytosine DNA methylation is an important epigenetic modification termed as the fifth base that functions in diverse processes. Till now, the genome-wide DNA methylation maps of many organisms has been reported, such as human, Arabidopsis, rice and silkworm, but the methylation pattern of bird remains rarely studied. Here we show the genome-wide DNA methylation map of bird, using the chicken as a model organism and an immunocapturing approach followed by high-throughput sequencing. In both of the red jungle fowl and the avian broiler, DNA methylation was described separately for the liver and muscle tissue. Generally, chicken displays analogous methylation pattern with that of animals and plants. DNA methylation is enriched in the gene body regions and the repetitive sequences, and depleted in the transcription start site (TSS and the transcription termination site (TTS. Most of the CpG islands in the chicken genome are kept in unmethylated state. Promoter methylation is negatively correlated with the gene expression level, indicating its suppressive role in regulating gene transcription. This work contributes to our understanding of epigenetics in birds.

  6. Genome-Wide Scan for Methylation Profiles in Keloids

    Directory of Open Access Journals (Sweden)

    Lamont R. Jones

    2015-01-01

    Full Text Available Keloids are benign fibroproliferative tumors of the skin which commonly occur after injury mainly in darker skinned patients. Medical treatment is fraught with high recurrence rates mainly because of an incomplete understanding of the biological mechanisms that lead to keloids. The purpose of this project was to examine keloid pathogenesis from the epigenome perspective of DNA methylation. Genome-wide profiling used the Infinium HumanMethylation450 BeadChip to interrogate DNA from 6 fresh keloid and 6 normal skin samples from 12 anonymous donors. A 3-tiered approach was used to call out genes most differentially methylated between keloid and normal. When compared to normal, of the 685 differentially methylated CpGs at Tier 3, 510 were hypomethylated and 175 were hypermethylated with 190 CpGs in promoter and 495 in nonpromoter regions. The 190 promoter region CpGs corresponded to 152 genes: 96 (63% were hypomethylated and 56 (37% hypermethylated. This exploratory genome-wide scan of the keloid methylome highlights a predominance of hypomethylated genomic landscapes, favoring nonpromoter regions. DNA methylation, as an additional mechanism for gene regulation in keloid pathogenesis, holds potential for novel treatments that reverse deleterious epigenetic changes. As an alternative mechanism for regulating genes, epigenetics may explain why gene mutations alone do not provide definitive mechanisms for keloid formation.

  7. Time-Predictable Computer Architecture

    Directory of Open Access Journals (Sweden)

    Schoeberl Martin

    2009-01-01

    Full Text Available Today's general-purpose processors are optimized for maximum throughput. Real-time systems need a processor with both a reasonable and a known worst-case execution time (WCET. Features such as pipelines with instruction dependencies, caches, branch prediction, and out-of-order execution complicate WCET analysis and lead to very conservative estimates. In this paper, we evaluate the issues of current architectures with respect to WCET analysis. Then, we propose solutions for a time-predictable computer architecture. The proposed architecture is evaluated with implementation of some features in a Java processor. The resulting processor is a good target for WCET analysis and still performs well in the average case.

  8. FHSA-SED: Two-Locus Model Detection for Genome-Wide Association Study with Harmony Search Algorithm.

    Directory of Open Access Journals (Sweden)

    Shouheng Tuo

    Full Text Available Two-locus model is a typical significant disease model to be identified in genome-wide association study (GWAS. Due to intensive computational burden and diversity of disease models, existing methods have drawbacks on low detection power, high computation cost, and preference for some types of disease models.In this study, two scoring functions (Bayesian network based K2-score and Gini-score are used for characterizing two SNP locus as a candidate model, the two criteria are adopted simultaneously for improving identification power and tackling the preference problem to disease models. Harmony search algorithm (HSA is improved for quickly finding the most likely candidate models among all two-locus models, in which a local search algorithm with two-dimensional tabu table is presented to avoid repeatedly evaluating some disease models that have strong marginal effect. Finally G-test statistic is used to further test the candidate models.We investigate our method named FHSA-SED on 82 simulated datasets and a real AMD dataset, and compare it with two typical methods (MACOED and CSE which have been developed recently based on swarm intelligent search algorithm. The results of simulation experiments indicate that our method outperforms the two compared algorithms in terms of detection power, computation time, evaluation times, sensitivity (TPR, specificity (SPC, positive predictive value (PPV and accuracy (ACC. Our method has identified two SNPs (rs3775652 and rs10511467 that may be also associated with disease in AMD dataset.

  9. A genome-wide association study of optic disc parameters.

    Directory of Open Access Journals (Sweden)

    Wishal D Ramdas

    2010-06-01

    Full Text Available The optic nerve head is involved in many ophthalmic disorders, including common diseases such as myopia and open-angle glaucoma. Two of the most important parameters are the size of the optic disc area and the vertical cup-disc ratio (VCDR. Both are highly heritable but genetically largely undetermined. We performed a meta-analysis of genome-wide association (GWA data to identify genetic variants associated with optic disc area and VCDR. The gene discovery included 7,360 unrelated individuals from the population-based Rotterdam Study I and Rotterdam Study II cohorts. These cohorts revealed two genome-wide significant loci for optic disc area, rs1192415 on chromosome 1p22 (p = 6.72x10(-19 within 117 kb of the CDC7 gene and rs1900004 on chromosome 10q21.3-q22.1 (p = 2.67x10(-33 within 10 kb of the ATOH7 gene. They revealed two genome-wide significant loci for VCDR, rs1063192 on chromosome 9p21 (p = 6.15x10(-11 in the CDKN2B gene and rs10483727 on chromosome 14q22.3-q23 (p = 2.93x10(-10 within 40 kbp of the SIX1 gene. Findings were replicated in two independent Dutch cohorts (Rotterdam Study III and Erasmus Rucphen Family study; N = 3,612, and the TwinsUK cohort (N = 843. Meta-analysis with the replication cohorts confirmed the four loci and revealed a third locus at 16q12.1 associated with optic disc area, and four other loci at 11q13, 13q13, 17q23 (borderline significant, and 22q12.1 for VCDR. ATOH7 was also associated with VCDR independent of optic disc area. Three of the loci were marginally associated with open-angle glaucoma. The protein pathways in which the loci of optic disc area are involved overlap with those identified for VCDR, suggesting a common genetic origin.

  10. Genome-wide Pleiotropy Between Parkinson Disease and Autoimmune Diseases.

    Science.gov (United States)

    Witoelar, Aree; Jansen, Iris E; Wang, Yunpeng; Desikan, Rahul S; Gibbs, J Raphael; Blauwendraat, Cornelis; Thompson, Wesley K; Hernandez, Dena G; Djurovic, Srdjan; Schork, Andrew J; Bettella, Francesco; Ellinghaus, David; Franke, Andre; Lie, Benedicte A; McEvoy, Linda K; Karlsen, Tom H; Lesage, Suzanne; Morris, Huw R; Brice, Alexis; Wood, Nicholas W; Heutink, Peter; Hardy, John; Singleton, Andrew B; Dale, Anders M; Gasser, Thomas; Andreassen, Ole A; Sharma, Manu

    2017-07-01

    Recent genome-wide association studies (GWAS) and pathway analyses supported long-standing observations of an association between immune-mediated diseases and Parkinson disease (PD). The post-GWAS era provides an opportunity for cross-phenotype analyses between different complex phenotypes. To test the hypothesis that there are common genetic risk variants conveying risk of both PD and autoimmune diseases (ie, pleiotropy) and to identify new shared genetic variants and their pathways by applying a novel statistical framework in a genome-wide approach. Using the conjunction false discovery rate method, this study analyzed GWAS data from a selection of archetypal autoimmune diseases among 138 511 individuals of European ancestry and systemically investigated pleiotropy between PD and type 1 diabetes, Crohn disease, ulcerative colitis, rheumatoid arthritis, celiac disease, psoriasis, and multiple sclerosis. NeuroX data (6927 PD cases and 6108 controls) were used for replication. The study investigated the biological correlation between the top loci through protein-protein interaction and changes in the gene expression and methylation levels. The dates of the analysis were June 10, 2015, to March 4, 2017. The primary outcome was a list of novel loci and their pathways involved in PD and autoimmune diseases. Genome-wide conjunctional analysis identified 17 novel loci at false discovery rate less than 0.05 with overlap between PD and autoimmune diseases, including known PD loci adjacent to GAK, HLA-DRB5, LRRK2, and MAPT for rheumatoid arthritis, ulcerative colitis and Crohn disease. Replication confirmed the involvement of HLA, LRRK2, MAPT, TRIM10, and SETD1A in PD. Among the novel genes discovered, WNT3, KANSL1, CRHR1, BOLA2, and GUCY1A3 are within a protein-protein interaction network with known PD genes. A subset of novel loci was significantly associated with changes in methylation or expression levels of adjacent genes. The study findings provide novel mechanistic

  11. Genome-wide association study of antisocial personality disorder

    Science.gov (United States)

    Rautiainen, M-R; Paunio, T; Repo-Tiihonen, E; Virkkunen, M; Ollila, H M; Sulkava, S; Jolanki, O; Palotie, A; Tiihonen, J

    2016-01-01

    The pathophysiology of antisocial personality disorder (ASPD) remains unclear. Although the most consistent biological finding is reduced grey matter volume in the frontal cortex, about 50% of the total liability to developing ASPD has been attributed to genetic factors. The contributing genes remain largely unknown. Therefore, we sought to study the genetic background of ASPD. We conducted a genome-wide association study (GWAS) and a replication analysis of Finnish criminal offenders fulfilling DSM-IV criteria for ASPD (N=370, N=5850 for controls, GWAS; N=173, N=3766 for controls and replication sample). The GWAS resulted in suggestive associations of two clusters of single-nucleotide polymorphisms at 6p21.2 and at 6p21.32 at the human leukocyte antigen (HLA) region. Imputation of HLA alleles revealed an independent association with DRB1*01:01 (odds ratio (OR)=2.19 (1.53–3.14), P=1.9 × 10-5). Two polymorphisms at 6p21.2 LINC00951–LRFN2 gene region were replicated in a separate data set, and rs4714329 reached genome-wide significance (OR=1.59 (1.37–1.85), P=1.6 × 10−9) in the meta-analysis. The risk allele also associated with antisocial features in the general population conditioned for severe problems in childhood family (β=0.68, P=0.012). Functional analysis in brain tissue in open access GTEx and Braineac databases revealed eQTL associations of rs4714329 with LINC00951 and LRFN2 in cerebellum. In humans, LINC00951 and LRFN2 are both expressed in the brain, especially in the frontal cortex, which is intriguing considering the role of the frontal cortex in behavior and the neuroanatomical findings of reduced gray matter volume in ASPD. To our knowledge, this is the first study showing genome-wide significant and replicable findings on genetic variants associated with any personality disorder. PMID:27598967

  12. High-resolution genome-wide mapping of histone modifications.

    Science.gov (United States)

    Roh, Tae-young; Ngau, Wing Chi; Cui, Kairong; Landsman, David; Zhao, Keji

    2004-08-01

    The expression patterns of eukaryotic genomes are controlled by their chromatin structure, consisting of nucleosome subunits in which DNA of approximately 146 bp is wrapped around a core of 8 histone molecules. Post-translational histone modifications play an essential role in modifying chromatin structure. Here we apply a combination of SAGE and chromatin immunoprecipitation (ChIP) protocols to determine the distribution of hyperacetylated histones H3 and H4 in the Saccharomyces cerevisiae genome. We call this approach genome-wide mapping technique (GMAT). Using GMAT, we find that the highest acetylation levels are detected in the 5' end of a gene's coding region, but not in the promoter. Furthermore, we show that the histone acetyltransferase, GCN5p, regulates H3 acetylation in the promoter and 5' end of the coding regions. These findings indicate that GMAT should find valuable applications in mapping target sites of chromatin-modifying enzymes.

  13. Genome-wide association studies in pediatric chronic kidney disease.

    Science.gov (United States)

    Gupta, Jayanta; Kanetsky, Peter A; Wuttke, Matthias; Köttgen, Anna; Schaefer, Franz; Wong, Craig S

    2016-08-01

    The genome-wide association study (GWAS) has become an established scientific method that provides an unbiased screen for genetic loci potentially associated with phenotypes of clinical interest, such as chronic kidney disease (CKD). Thus, GWAS provides opportunities to gain new perspectives regarding the genetic architecture of CKD progression by identifying new candidate genes and targets for intervention. As such, it has become an important arm of translational science providing a complementary line of investigation to identify novel therapeutics to treat CKD. In this review, we describe the method and the challenges of performing GWAS in the pediatric CKD population. We also provide an overview of successful GWAS for kidney disease, and we discuss the established pediatric CKD cohorts in North America and Europe that are poised to identify genetic risk variants associated with CKD progression.

  14. Genome-wide genetic changes during modern breeding of maize.

    Science.gov (United States)

    Jiao, Yinping; Zhao, Hainan; Ren, Longhui; Song, Weibin; Zeng, Biao; Guo, Jinjie; Wang, Baobao; Liu, Zhipeng; Chen, Jing; Li, Wei; Zhang, Mei; Xie, Shaojun; Lai, Jinsheng

    2012-06-03

    The success of modern maize breeding has been demonstrated by remarkable increases in productivity over the last four decades. However, the underlying genetic changes correlated with these gains remain largely unknown. We report here the sequencing of 278 temperate maize inbred lines from different stages of breeding history, including deep resequencing of 4 lines with known pedigree information. The results show that modern breeding has introduced highly dynamic genetic changes into the maize genome. Artificial selection has affected thousands of targets, including genes and non-genic regions, leading to a reduction in nucleotide diversity and an increase in the proportion of rare alleles. Genetic changes during breeding happen rapidly, with extensive variation (SNPs, indels and copy-number variants (CNVs)) occurring, even within identity-by-descent regions. Our genome-wide assessment of genetic changes during modern maize breeding provides new strategies as well as practical targets for future crop breeding and biotechnology.

  15. AID/APOBEC cytosine deaminase induces genome-wide kataegis

    Directory of Open Access Journals (Sweden)

    Lada Artem G

    2012-12-01

    Full Text Available Abstract Clusters of localized hypermutation in human breast cancer genomes, named “kataegis” (from the Greek for thunderstorm, are hypothesized to result from multiple cytosine deaminations catalyzed by AID/APOBEC proteins. However, a direct link between APOBECs and kataegis is still lacking. We have sequenced the genomes of yeast mutants induced in diploids by expression of the gene for PmCDA1, a hypermutagenic deaminase from sea lamprey. Analysis of the distribution of 5,138 induced mutations revealed localized clusters very similar to those found in tumors. Our data provide evidence that unleashed cytosine deaminase activity is an evolutionary conserved, prominent source of genome-wide kataegis events. Reviewers This article was reviewed by: Professor Sandor Pongor, Professor Shamil R. Sunyaev, and Dr Vladimir Kuznetsov.

  16. DNA Break Mapping Reveals Topoisomerase II Activity Genome-Wide

    Directory of Open Access Journals (Sweden)

    Laura Baranello

    2014-07-01

    Full Text Available Genomic DNA is under constant assault by endogenous and exogenous DNA damaging agents. DNA breakage can represent a major threat to genome integrity but can also be necessary for genome function. Here we present approaches to map DNA double-strand breaks (DSBs and single-strand breaks (SSBs at the genome-wide scale by two methods called DSB- and SSB-Seq, respectively. We tested these methods in human colon cancer cells and validated the results using the Topoisomerase II (Top2-poisoning agent etoposide (ETO. Our results show that the combination of ETO treatment with break-mapping techniques is a powerful method to elaborate the pattern of Top2 enzymatic activity across the genome.

  17. Genome-wide association study of serum selenium concentrations

    DEFF Research Database (Denmark)

    Gong, Jian; Hsu, Li; Harrison, Tabitha

    2013-01-01

    Selenium is an essential trace element and circulating selenium concentrations have been associated with a wide range of diseases. Candidate gene studies suggest that circulating selenium concentrations may be impacted by genetic variation; however, no study has comprehensively investigated...... this hypothesis. Therefore, we conducted a two-stage genome-wide association study to identify genetic variants associated with serum selenium concentrations in 1203 European descents from two cohorts: the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening and the Women’s Health Initiative (WHI). We...... tested association between 2,474,333 single nucleotide polymorphisms (SNPs) and serum selenium concentrations using linear regression models. In the first stage (PLCO) 41 SNPs clustered in 15 regions had p

  18. Genome-wide transcriptional reprogramming under drought stress

    KAUST Repository

    Chen, Hao

    2012-01-01

    Soil water deficit is one of the major factors limiting plant productivity. Plants cope with this adverse environmental condition by coordinating the up- or downregulation of an array of stress responsive genes. Reprogramming the expression of these genes leads to rebalanced development and growth that are in concert with the reduced water availability and that ultimately confer enhanced stress tolerance. Currently, several techniques have been employed to monitor genome-wide transcriptional reprogramming under drought stress. The results from these high throughput studies indicate that drought stress-induced transcriptional reprogramming is dynamic, has temporal and spatial specificity, and is coupled with the circadian clock and phytohormone signaling pathways. © 2012 Springer-Verlag Berlin Heidelberg. All rights are reserved.

  19. Genome-Wide Association Study of Coronary Artery Disease

    Directory of Open Access Journals (Sweden)

    Naomi Ogawa

    2010-01-01

    Full Text Available Coronary artery disease (CAD is a multifactorial disease with environmental and genetic determinants. The genetic determinants of CAD have previously been explored by the candidate gene approach. Recently, the data from the International HapMap Project and the development of dense genotyping chips have enabled us to perform genome-wide association studies (GWAS on a large number of subjects without bias towards any particular candidate genes. In 2007, three chip-based GWAS simultaneously revealed the significant association between common variants on chromosome 9p21 and CAD. This association was replicated among other ethnic groups and also in a meta-analysis. Further investigations have detected several other candidate loci associated with CAD. The chip-based GWAS approach has identified novel and unbiased genetic determinants of CAD and these insights provide the important direction to better understand the pathogenesis of CAD and to develop new and improved preventive measures and treatments for CAD.

  20. A comparison of multivariate genome-wide association methods

    DEFF Research Database (Denmark)

    Galesloot, Tessel E; Van Steen, Kristel; Kiemeney, Lambertus A L M

    2014-01-01

    Joint association analysis of multiple traits in a genome-wide association study (GWAS), i.e. a multivariate GWAS, offers several advantages over analyzing each trait in a separate GWAS. In this study we directly compared a number of multivariate GWAS methods using simulated data. We focused on six...... methods that are implemented in the software packages PLINK, SNPTEST, MultiPhen, BIMBAM, PCHAT and TATES, and also compared them to standard univariate GWAS, analysis of the first principal component of the traits, and meta-analysis of univariate results. We simulated data (N = 1000) for three...... correlation. We compared the power of the methods using empirically fixed significance thresholds (α = 0.05). Our results showed that the multivariate methods implemented in PLINK, SNPTEST, MultiPhen and BIMBAM performed best for the majority of the tested scenarios, with a notable increase in power...

  1. Genome-Wide Association Study of Meiotic Recombination Phenotypes

    Science.gov (United States)

    Begum, Ferdouse; Chowdhury, Reshmi; Cheung, Vivian G.; Sherman, Stephanie L.; Feingold, Eleanor

    2016-01-01

    Meiotic recombination is an essential step in gametogenesis, and is one that also generates genetic diversity. Genome-wide association studies (GWAS) and molecular studies have identified genes that influence of human meiotic recombination. RNF212 is associated with total or average number of recombination events, and PRDM9 is associated with the locations of hotspots, or sequences where crossing over appears to cluster. In addition, a common inversion on chromosome 17 is strongly associated with recombination. Other genes have been identified by GWAS, but those results have not been replicated. In this study, using new datasets, we characterized additional recombination phenotypes to uncover novel candidates and further dissect the role of already known loci. We used three datasets totaling 1562 two-generation families, including 3108 parents with 4304 children. We estimated five different recombination phenotypes including two novel phenotypes (average recombination counts within recombination hotspots and outside of hotspots) using dense SNP array genotype data. We then performed gender-specific and combined-sex genome-wide association studies (GWAS) meta-analyses. We replicated associations for several previously reported recombination genes, including RNF212 and PRDM9. By looking specifically at recombination events outside of hotspots, we showed for the first time that PRDM9 has different effects in males and females. We identified several new candidate loci, particularly for recombination events outside of hotspots. These include regions near the genes SPINK6, EVC2, ARHGAP25, and DLGAP2. This study expands our understanding of human meiotic recombination by characterizing additional features that vary across individuals, and identifying regulatory variants influencing the numbers and locations of recombination events. PMID:27733454

  2. Genome-wide significant loci for addiction and anxiety

    Science.gov (United States)

    Hodgson, K.; Almasy, L.; Knowles, E.E.M.; Kent, J.W.; Curran, J.E.; Dyer, T.D.; Göring, H.H.H.; Olvera, R.L.; Fox, P.T.; Pearlson, G.D.; Krystal, J.H.; Duggirala, R.; Blangero, J.; Glahn, D.C.

    2017-01-01

    Background Psychiatric comorbidity is common among individuals with addictive disorders, with patients frequently suffering from anxiety disorders. While the genetic architecture of comorbid addictive and anxiety disorders remains unclear, elucidating the genes involved could provide important insights into the underlying etiology. Methods Here we examine a sample of 1284 Mexican-Americans from randomly selected extended pedigrees. Variance decomposition methods were used to examine the role of genetics in addiction phenotypes (lifetime history of alcohol dependence, drug dependence or chronic smoking) and various forms of clinically relevant anxiety. Genome-wide univariate and bivariate linkage scans were conducted to localize the chromosomal regions influencing these traits. Results Addiction phenotypes and anxiety were shown to be heritable and univariate genome-wide linkage scans revealed significant quantitative trait loci for drug dependence (14q13.2–q21.2, LOD = 3.322) and a broad anxiety phenotype (12q24.32–q24.33, LOD = 2.918). Significant positive genetic correlations were observed between anxiety and each of the addiction subtypes (ρg = 0.550–0.655) and further investigation with bivariate linkage analyses identified significant pleiotropic signals for alcohol dependence-anxiety (9q33.1–q33.2, LOD = 3.054) and drug dependence-anxiety (18p11.23–p11.22, LOD = 3.425). Conclusions This study confirms the shared genetic underpinnings of addiction and anxiety and identifies genomic loci involved in the etiology of these comorbid disorders. The linkage signal for anxiety on 12q24 spans the location of TMEM132D, an emerging gene of interest from previous GWAS of anxiety traits, whilst the bivariate linkage signal identified for anxiety-alcohol on 9q33 peak coincides with a region where rare CNVs have been associated with psychiatric disorders. Other signals identified implicate novel regions of the genome in addiction genetics. PMID:27318301

  3. Genome-wide association studies in asthma: progress and pitfalls

    Directory of Open Access Journals (Sweden)

    March ME

    2015-01-01

    Full Text Available Michael E March,1 Patrick MA Sleiman,1,2 Hakon Hakonarson1,2 1Center for Applied Genomics, Children's Hospital of Philadelphia Research Institute, 2Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Abstract: Genetic studies of asthma have revealed that there is considerable heritability to the phenotype. An extensive history of candidate-gene studies has identified a long list of genes associated with immune function that are potentially involved in asthma pathogenesis. However, many of the results of candidate-gene studies have failed to be replicated, leaving in question the true impact of the implicated biological pathways on asthma. With the advent of genome-wide association studies, geneticists are able to examine the association of hundreds of thousands of genetic markers with a phenotype, allowing the hypothesis-free identification of variants associated with disease. Many such studies examining asthma or related phenotypes have been published, and several themes have begun to emerge regarding the biological pathways underpinning asthma. The results of many genome-wide association studies have currently not been replicated, and the large sample sizes required for this experimental strategy invoke difficulties with sample stratification and phenotypic heterogeneity. Recently, large collaborative groups of researchers have formed consortia focused on asthma, with the goals of sharing material and data and standardizing diagnosis and experimental methods. Additionally, research has begun to focus on genetic variants that affect the response to asthma medications and on the biology that generates the heterogeneity in the asthma phenotype. As this work progresses, it will move asthma patients closer to more specific, personalized medicine. Keywords: asthma, genetics, GWAS, pharmacogenetics, biomarkers

  4. A genome-wide association study of anorexia nervosa

    Science.gov (United States)

    Boraska, Vesna; Franklin, Christopher S; Floyd, James AB; Thornton, Laura M; Huckins, Laura M; Southam, Lorraine; Rayner, N William; Tachmazidou, Ioanna; Klump, Kelly L; Treasure, Janet; Lewis, Cathryn M; Schmidt, Ulrike; Tozzi, Federica; Kiezebrink, Kirsty; Hebebrand, Johannes; Gorwood, Philip; Adan, Roger AH; Kas, Martien JH; Favaro, Angela; Santonastaso, Paolo; Fernández-Aranda, Fernando; Gratacos, Monica; Rybakowski, Filip; Dmitrzak-Weglarz, Monika; Kaprio, Jaakko; Keski-Rahkonen, Anna; Raevuori, Anu; Van Furth, Eric F; Landt, Margarita CT Slof-Op t; Hudson, James I; Reichborn-Kjennerud, Ted; Knudsen, Gun Peggy S; Monteleone, Palmiero; Kaplan, Allan S; Karwautz, Andreas; Hakonarson, Hakon; Berrettini, Wade H; Guo, Yiran; Li, Dong; Schork, Nicholas J.; Komaki, Gen; Ando, Tetsuya; Inoko, Hidetoshi; Esko, Tõnu; Fischer, Krista; Männik, Katrin; Metspalu, Andres; Baker, Jessica H; Cone, Roger D; Dackor, Jennifer; DeSocio, Janiece E; Hilliard, Christopher E; O'Toole, Julie K; Pantel, Jacques; Szatkiewicz, Jin P; Taico, Chrysecolla; Zerwas, Stephanie; Trace, Sara E; Davis, Oliver SP; Helder, Sietske; Bühren, Katharina; Burghardt, Roland; de Zwaan, Martina; Egberts, Karin; Ehrlich, Stefan; Herpertz-Dahlmann, Beate; Herzog, Wolfgang; Imgart, Hartmut; Scherag, André; Scherag, Susann; Zipfel, Stephan; Boni, Claudette; Ramoz, Nicolas; Versini, Audrey; Brandys, Marek K; Danner, Unna N; de Kovel, Carolien; Hendriks, Judith; Koeleman, Bobby PC; Ophoff, Roel A; Strengman, Eric; van Elburg, Annemarie A; Bruson, Alice; Clementi, Maurizio; Degortes, Daniela; Forzan, Monica; Tenconi, Elena; Docampo, Elisa; Escaramís, Geòrgia; Jiménez-Murcia, Susana; Lissowska, Jolanta; Rajewski, Andrzej; Szeszenia-Dabrowska, Neonila; Slopien, Agnieszka; Hauser, Joanna; Karhunen, Leila; Meulenbelt, Ingrid; Slagboom, P Eline; Tortorella, Alfonso; Maj, Mario; Dedoussis, George; Dikeos, Dimitris; Gonidakis, Fragiskos; Tziouvas, Konstantinos; Tsitsika, Artemis; Papezova, Hana; Slachtova, Lenka; Martaskova, Debora; Kennedy, James L.; Levitan, Robert D.; Yilmaz, Zeynep; Huemer, Julia; Koubek, Doris; Merl, Elisabeth; Wagner, Gudrun; Lichtenstein, Paul; Breen, Gerome; Cohen-Woods, Sarah; Farmer, Anne; McGuffin, Peter; Cichon, Sven; Giegling, Ina; Herms, Stefan; Rujescu, Dan; Schreiber, Stefan; Wichmann, H-Erich; Dina, Christian; Sladek, Rob; Gambaro, Giovanni; Soranzo, Nicole; Julia, Antonio; Marsal, Sara; Rabionet, Raquel; Gaborieau, Valerie; Dick, Danielle M; Palotie, Aarno; Ripatti, Samuli; Widén, Elisabeth; Andreassen, Ole A; Espeseth, Thomas; Lundervold, Astri; Reinvang, Ivar; Steen, Vidar M; Le Hellard, Stephanie; Mattingsdal, Morten; Ntalla, Ioanna; Bencko, Vladimir; Foretova, Lenka; Janout, Vladimir; Navratilova, Marie; Gallinger, Steven; Pinto, Dalila; Scherer, Stephen; Aschauer, Harald; Carlberg, Laura; Schosser, Alexandra; Alfredsson, Lars; Ding, Bo; Klareskog, Lars; Padyukov, Leonid; Finan, Chris; Kalsi, Gursharan; Roberts, Marion; Logan, Darren W; Peltonen, Leena; Ritchie, Graham RS; Barrett, Jeffrey C; Estivill, Xavier; Hinney, Anke; Sullivan, Patrick F; Collier, David A; Zeggini, Eleftheria; Bulik, Cynthia M

    2015-01-01

    Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2,907 cases with AN from 14 countries (15 sites) and 14,860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery datasets. Seventy-six (72 independent) SNPs were taken forward for in silico (two datasets) or de novo (13 datasets) replication genotyping in 2,677 independent AN cases and 8,629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication datasets comprised 5,551 AN cases and 21,080 controls. AN subtype analyses (1,606 AN restricting; 1,445 AN binge-purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 (P=3.01×10-7) in SOX2OT and rs17030795 (P=5.84×10-6) in PPP3CA. Two additional signals were specific to Europeans: rs1523921 (P=5.76×10-6) between CUL3 and FAM124B and rs1886797 (P=8.05×10-6) near SPATA13. Comparing discovery to replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance (P=4×10-6), strongly suggesting that true findings exist but that our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field. PMID:24514567

  5. A genome-wide association study of anorexia nervosa.

    Science.gov (United States)

    Boraska, V; Franklin, C S; Floyd, J A B; Thornton, L M; Huckins, L M; Southam, L; Rayner, N W; Tachmazidou, I; Klump, K L; Treasure, J; Lewis, C M; Schmidt, U; Tozzi, F; Kiezebrink, K; Hebebrand, J; Gorwood, P; Adan, R A H; Kas, M J H; Favaro, A; Santonastaso, P; Fernández-Aranda, F; Gratacos, M; Rybakowski, F; Dmitrzak-Weglarz, M; Kaprio, J; Keski-Rahkonen, A; Raevuori, A; Van Furth, E F; Slof-Op 't Landt, M C T; Hudson, J I; Reichborn-Kjennerud, T; Knudsen, G P S; Monteleone, P; Kaplan, A S; Karwautz, A; Hakonarson, H; Berrettini, W H; Guo, Y; Li, D; Schork, N J; Komaki, G; Ando, T; Inoko, H; Esko, T; Fischer, K; Männik, K; Metspalu, A; Baker, J H; Cone, R D; Dackor, J; DeSocio, J E; Hilliard, C E; O'Toole, J K; Pantel, J; Szatkiewicz, J P; Taico, C; Zerwas, S; Trace, S E; Davis, O S P; Helder, S; Bühren, K; Burghardt, R; de Zwaan, M; Egberts, K; Ehrlich, S; Herpertz-Dahlmann, B; Herzog, W; Imgart, H; Scherag, A; Scherag, S; Zipfel, S; Boni, C; Ramoz, N; Versini, A; Brandys, M K; Danner, U N; de Kovel, C; Hendriks, J; Koeleman, B P C; Ophoff, R A; Strengman, E; van Elburg, A A; Bruson, A; Clementi, M; Degortes, D; Forzan, M; Tenconi, E; Docampo, E; Escaramís, G; Jiménez-Murcia, S; Lissowska, J; Rajewski, A; Szeszenia-Dabrowska, N; Slopien, A; Hauser, J; Karhunen, L; Meulenbelt, I; Slagboom, P E; Tortorella, A; Maj, M; Dedoussis, G; Dikeos, D; Gonidakis, F; Tziouvas, K; Tsitsika, A; Papezova, H; Slachtova, L; Martaskova, D; Kennedy, J L; Levitan, R D; Yilmaz, Z; Huemer, J; Koubek, D; Merl, E; Wagner, G; Lichtenstein, P; Breen, G; Cohen-Woods, S; Farmer, A; McGuffin, P; Cichon, S; Giegling, I; Herms, S; Rujescu, D; Schreiber, S; Wichmann, H-E; Dina, C; Sladek, R; Gambaro, G; Soranzo, N; Julia, A; Marsal, S; Rabionet, R; Gaborieau, V; Dick, D M; Palotie, A; Ripatti, S; Widén, E; Andreassen, O A; Espeseth, T; Lundervold, A; Reinvang, I; Steen, V M; Le Hellard, S; Mattingsdal, M; Ntalla, I; Bencko, V; Foretova, L; Janout, V; Navratilova, M; Gallinger, S; Pinto, D; Scherer, S W; Aschauer, H; Carlberg, L; Schosser, A; Alfredsson, L; Ding, B; Klareskog, L; Padyukov, L; Courtet, P; Guillaume, S; Jaussent, I; Finan, C; Kalsi, G; Roberts, M; Logan, D W; Peltonen, L; Ritchie, G R S; Barrett, J C; Estivill, X; Hinney, A; Sullivan, P F; Collier, D A; Zeggini, E; Bulik, C M

    2014-10-01

    Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome-wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2907 cases with AN from 14 countries (15 sites) and 14 860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery data sets. Seventy-six (72 independent) single nucleotide polymorphisms were taken forward for in silico (two data sets) or de novo (13 data sets) replication genotyping in 2677 independent AN cases and 8629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication data sets comprised 5551 AN cases and 21 080 controls. AN subtype analyses (1606 AN restricting; 1445 AN binge-purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 (P=3.01 × 10(-7)) in SOX2OT and rs17030795 (P=5.84 × 10(-6)) in PPP3CA. Two additional signals were specific to Europeans: rs1523921 (P=5.76 × 10(-)(6)) between CUL3 and FAM124B and rs1886797 (P=8.05 × 10(-)(6)) near SPATA13. Comparing discovery with replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance (P=4 × 10(-6)), strongly suggesting that true findings exist but our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field.

  6. Genome-wide expression profiling of complex regional pain syndrome.

    Directory of Open Access Journals (Sweden)

    Eun-Heui Jin

    Full Text Available Complex regional pain syndrome (CRPS is a chronic, progressive, and devastating pain syndrome characterized by spontaneous pain, hyperalgesia, allodynia, altered skin temperature, and motor dysfunction. Although previous gene expression profiling studies have been conducted in animal pain models, there genome-wide expression profiling in the whole blood of CRPS patients has not been reported yet. Here, we successfully identified certain pain-related genes through genome-wide expression profiling in the blood from CRPS patients. We found that 80 genes were differentially expressed between 4 CRPS patients (2 CRPS I and 2 CRPS II and 5 controls (cut-off value: 1.5-fold change and p<0.05. Most of those genes were associated with signal transduction, developmental processes, cell structure and motility, and immunity and defense. The expression levels of major histocompatibility complex class I A subtype (HLA-A29.1, matrix metalloproteinase 9 (MMP9, alanine aminopeptidase N (ANPEP, l-histidine decarboxylase (HDC, granulocyte colony-stimulating factor 3 receptor (G-CSF3R, and signal transducer and activator of transcription 3 (STAT3 genes selected from the microarray were confirmed in 24 CRPS patients and 18 controls by quantitative reverse transcription-polymerase chain reaction (qRT-PCR. We focused on the MMP9 gene that, by qRT-PCR, showed a statistically significant difference in expression in CRPS patients compared to controls with the highest relative fold change (4.0±1.23 times and p = 1.4×10(-4. The up-regulation of MMP9 gene in the blood may be related to the pain progression in CRPS patients. Our findings, which offer a valuable contribution to the understanding of the differential gene expression in CRPS may help in the understanding of the pathophysiology of CRPS pain progression.

  7. A powerful test of independent assortment that determines genome-wide significance quickly and accurately.

    Science.gov (United States)

    Stewart, W C L; Hager, V R

    2016-08-01

    In the analysis of DNA sequences on related individuals, most methods strive to incorporate as much information as possible, with little or no attention paid to the issue of statistical significance. For example, a modern workstation can easily handle the computations needed to perform a large-scale genome-wide inheritance-by-descent (IBD) scan, but accurate assessment of the significance of that scan is often hindered by inaccurate approximations and computationally intensive simulation. To address these issues, we developed gLOD-a test of co-segregation that, for large samples, models chromosome-specific IBD statistics as a collection of stationary Gaussian processes. With this simple model, the parametric bootstrap yields an accurate and rapid assessment of significance-the genome-wide corrected P-value. Furthermore, we show that (i) under the null hypothesis, the limiting distribution of the gLOD is the standard Gumbel distribution; (ii) our parametric bootstrap simulator is approximately 40 000 times faster than gene-dropping methods, and it is more powerful than methods that approximate the adjusted P-value; and, (iii) the gLOD has the same statistical power as the widely used maximum Kong and Cox LOD. Thus, our approach gives researchers the ability to determine quickly and accurately the significance of most large-scale IBD scans, which may contain multiple traits, thousands of families and tens of thousands of DNA sequences.

  8. Computational Prediction of Effector Proteins in Fungi: Opportunities and Challenges

    Directory of Open Access Journals (Sweden)

    Humira eSonah

    2016-02-01

    Full Text Available Effector proteins are mostly secretory proteins that stimulate plant infection by manipulating the host response. Identifying fungal effector proteins and understanding their function is of great importance in efforts to curb losses to plant diseases. Recent advances in high-throughput sequencing technologies have facilitated the availability of several fungal genomes and thousands of transcriptomes. As a result, the growing amount of genomic information has provided great opportunities to identify putative effector proteins in different fungal species. There is little consensus over the annotation and functionality of effector proteins, and mostly small secretory proteins are considered as effector proteins, a concept that tends to overestimate the number of proteins involved in a plant-pathogen interaction. With the characterization of Avr genes, criteria for computational prediction of effector proteins are becoming more efficient. There are hundreds of tools available for the identification of conserved motifs, signature sequences and structural features in the proteins. Many pipelines and online servers, which combine several tools, are made available to perform genome-wide identification of effector proteins. In this review, available tools and pipelines, their strength and limitations for effective identification of fungal effector proteins are discussed. We also present an exhaustive list of classically secreted proteins along with their key conserved motifs found in 12 common plant pathogens (11 fungi and one oomycete through an analytical pipeline.

  9. Comparative analysis of genome-wide divergence, domestication footprints and genome-wide association study of root traits for Gossypium hirsutum and Gossypium barbadense

    Science.gov (United States)

    Use of 10,129 singleton SNPs of known genomic location in tetraploid cotton provided unique opportunities to characterize genome-wide diversity among 440 Gossypium hirsutum and 219 G. barbadense cultivars and landrace accessions of widespread origin. Using genome-wide distributed SNPs, we examined ...

  10. Genome-wide binding and transcriptome analysis of human farnesoid X receptor in primary human hepatocytes.

    Directory of Open Access Journals (Sweden)

    Le Zhan

    Full Text Available Farnesoid X receptor (FXR, NR1H4 is a ligand-activated transcription factor, belonging to the nuclear receptor superfamily. FXR is highly expressed in the liver and is essential in regulating bile acid homeostasis. FXR deficiency is implicated in numerous liver diseases and mice with modulation of FXR have been used as animal models to study liver physiology and pathology. We have reported genome-wide binding of FXR in mice by chromatin immunoprecipitation - deep sequencing (ChIP-seq, with results indicating that FXR may be involved in regulating diverse pathways in liver. However, limited information exists for the functions of human FXR and the suitability of using murine models to study human FXR functions.In the current study, we performed ChIP-seq in primary human hepatocytes (PHHs treated with a synthetic FXR agonist, GW4064 or DMSO control. In parallel, RNA deep sequencing (RNA-seq and RNA microarray were performed for GW4064 or control treated PHHs and wild type mouse livers, respectively.ChIP-seq showed similar profiles of genome-wide FXR binding in humans and mice in terms of motif analysis and pathway prediction. However, RNA-seq and microarray showed more different transcriptome profiles between PHHs and mouse livers upon GW4064 treatment.In summary, we have established genome-wide human FXR binding and transcriptome profiles. These results will aid in determining the human FXR functions, as well as judging to what level the mouse models could be used to study human FXR functions.

  11. Genetic Profiling Using Genome-Wide Significant Coronary Artery Disease Risk Variants Does Not Improve the Prediction of Subclinical Atherosclerosis: The Cardiovascular Risk in Young Finns Study, the Bogalusa Heart Study and the Health 2000 Survey – A Meta-Analysis of Three Independent Studies

    Science.gov (United States)

    Lyytikäinen, Leo-Pekka; Mononen, Nina; Oksala, Niku; Hutri-Kähönen, Nina; Juonala, Markus; Taittonen, Leena; Smith, Erin N.; Schork, Nicholas J.; Chen, Wei; Srinivasan, Sathanur R.; Berenson, Gerald S.; Murray, Sarah S.; Laitinen, Tomi; Jula, Antti; Kettunen, Johannes; Ripatti, Samuli; Laaksonen, Reijo; Viikari, Jorma; Kähönen, Mika; Raitakari, Olli T.; Lehtimäki, Terho

    2012-01-01

    Background Genome-wide association studies (GWASs) have identified a large number of variants (SNPs) associating with an increased risk of coronary artery disease (CAD). Recently, the CARDIoGRAM consortium published a GWAS based on the largest study population so far. They successfully replicated twelve already known associations and discovered thirteen new SNPs associating with CAD. We examined whether the genetic profiling of these variants improves prediction of subclinical atherosclerosis – i.e., carotid intima-media thickness (CIMT) and carotid artery elasticity (CAE) – beyond classical risk factors. Subjects and Methods We genotyped 24 variants found in a population of European ancestry and measured CIMT and CAE in 2001 and 2007 from 2,081, and 2,015 subjects (aged 30–45 years in 2007) respectively, participating in the Cardiovascular Risk in Young Finns Study (YFS). The Bogalusa Heart Study (BHS; n = 1179) was used as a replication cohort (mean age of 37.5). For additional replication, a sub-sample of 5 SNPs was genotyped for 1,291 individuals aged 46–76 years participating in the Health 2000 population survey. We tested the impact of genetic risk score (GRS24SNP/CAD) calculated as a weighted (by allelic odds ratios for CAD) sum of CAD risk alleles from the studied 24 variants on CIMT, CAE, the incidence of carotid atherosclerosis and the progression of CIMT and CAE during a 6-year follow-up. Results CIMT or CAE did not significantly associate with GRS24SNP/CAD before or after adjusting for classical CAD risk factors (p>0.05 for all) in YFS or in the BHS. CIMT and CAE associated with only one SNP each in the YFS. The findings were not replicated in the replication cohorts. In the meta-analysis CIMT or CAE did not associate with any of the SNPs. Conclusion Genetic profiling, by using known CAD risk variants, should not improve risk stratification for subclinical atherosclerosis beyond conventional risk factors among healthy young adults. PMID

  12. Genetic profiling using genome-wide significant coronary artery disease risk variants does not improve the prediction of subclinical atherosclerosis: the Cardiovascular Risk in Young Finns Study, the Bogalusa Heart Study and the Health 2000 Survey--a meta-analysis of three independent studies.

    Directory of Open Access Journals (Sweden)

    Jussi A Hernesniemi

    Full Text Available BACKGROUND: Genome-wide association studies (GWASs have identified a large number of variants (SNPs associating with an increased risk of coronary artery disease (CAD. Recently, the CARDIoGRAM consortium published a GWAS based on the largest study population so far. They successfully replicated twelve already known associations and discovered thirteen new SNPs associating with CAD. We examined whether the genetic profiling of these variants improves prediction of subclinical atherosclerosis--i.e., carotid intima-media thickness (CIMT and carotid artery elasticity (CAE--beyond classical risk factors. SUBJECTS AND METHODS: We genotyped 24 variants found in a population of European ancestry and measured CIMT and CAE in 2001 and 2007 from 2,081, and 2,015 subjects (aged 30-45 years in 2007 respectively, participating in the Cardiovascular Risk in Young Finns Study (YFS. The Bogalusa Heart Study (BHS; n = 1179 was used as a replication cohort (mean age of 37.5. For additional replication, a sub-sample of 5 SNPs was genotyped for 1,291 individuals aged 46-76 years participating in the Health 2000 population survey. We tested the impact of genetic risk score (GRS(24SNP/CAD calculated as a weighted (by allelic odds ratios for CAD sum of CAD risk alleles from the studied 24 variants on CIMT, CAE, the incidence of carotid atherosclerosis and the progression of CIMT and CAE during a 6-year follow-up. RESULTS: CIMT or CAE did not significantly associate with GRS(24SNP/CAD before or after adjusting for classical CAD risk factors (p>0.05 for all in YFS or in the BHS. CIMT and CAE associated with only one SNP each in the YFS. The findings were not replicated in the replication cohorts. In the meta-analysis CIMT or CAE did not associate with any of the SNPs. CONCLUSION: Genetic profiling, by using known CAD risk variants, should not improve risk stratification for subclinical atherosclerosis beyond conventional risk factors among healthy young adults.

  13. Genetic profiling using genome-wide significant coronary artery disease risk variants does not improve the prediction of subclinical atherosclerosis: the Cardiovascular Risk in Young Finns Study, the Bogalusa Heart Study and the Health 2000 Survey--a meta-analysis of three independent studies.

    Science.gov (United States)

    Hernesniemi, Jussi A; Seppälä, Ilkka; Lyytikäinen, Leo-Pekka; Mononen, Nina; Oksala, Niku; Hutri-Kähönen, Nina; Juonala, Markus; Taittonen, Leena; Smith, Erin N; Schork, Nicholas J; Chen, Wei; Srinivasan, Sathanur R; Berenson, Gerald S; Murray, Sarah S; Laitinen, Tomi; Jula, Antti; Kettunen, Johannes; Ripatti, Samuli; Laaksonen, Reijo; Viikari, Jorma; Kähönen, Mika; Raitakari, Olli T; Lehtimäki, Terho

    2012-01-01

    Genome-wide association studies (GWASs) have identified a large number of variants (SNPs) associating with an increased risk of coronary artery disease (CAD). Recently, the CARDIoGRAM consortium published a GWAS based on the largest study population so far. They successfully replicated twelve already known associations and discovered thirteen new SNPs associating with CAD. We examined whether the genetic profiling of these variants improves prediction of subclinical atherosclerosis--i.e., carotid intima-media thickness (CIMT) and carotid artery elasticity (CAE)--beyond classical risk factors. We genotyped 24 variants found in a population of European ancestry and measured CIMT and CAE in 2001 and 2007 from 2,081, and 2,015 subjects (aged 30-45 years in 2007) respectively, participating in the Cardiovascular Risk in Young Finns Study (YFS). The Bogalusa Heart Study (BHS; n = 1179) was used as a replication cohort (mean age of 37.5). For additional replication, a sub-sample of 5 SNPs was genotyped for 1,291 individuals aged 46-76 years participating in the Health 2000 population survey. We tested the impact of genetic risk score (GRS(24SNP/CAD)) calculated as a weighted (by allelic odds ratios for CAD) sum of CAD risk alleles from the studied 24 variants on CIMT, CAE, the incidence of carotid atherosclerosis and the progression of CIMT and CAE during a 6-year follow-up. CIMT or CAE did not significantly associate with GRS(24SNP/CAD) before or after adjusting for classical CAD risk factors (p>0.05 for all) in YFS or in the BHS. CIMT and CAE associated with only one SNP each in the YFS. The findings were not replicated in the replication cohorts. In the meta-analysis CIMT or CAE did not associate with any of the SNPs. Genetic profiling, by using known CAD risk variants, should not improve risk stratification for subclinical atherosclerosis beyond conventional risk factors among healthy young adults.

  14. Potential assessment of genome-wide association study and genomic selection in Japanese pear Pyrus pyrifolia.

    Science.gov (United States)

    Iwata, Hiroyoshi; Hayashi, Takeshi; Terakami, Shingo; Takada, Norio; Sawamura, Yutaka; Yamamoto, Toshiya

    2013-03-01

    Although the potential of marker-assisted selection (MAS) in fruit tree breeding has been reported, bi-parental QTL mapping before MAS has hindered the introduction of MAS to fruit tree breeding programs. Genome-wide association studies (GWAS) are an alternative to bi-parental QTL mapping in long-lived perennials. Selection based on genomic predictions of breeding values (genomic selection: GS) is another alternative for MAS. This study examined the potential of GWAS and GS in pear breeding with 76 Japanese pear cultivars to detect significant associations of 162 markers with nine agronomic traits. We applied multilocus Bayesian models accounting for ordinal categorical phenotypes for GWAS and GS model training. Significant associations were detected at harvest time, black spot resistance and the number of spurs and two of the associations were closely linked to known loci. Genome-wide predictions for GS were accurate at the highest level (0.75) in harvest time, at medium levels (0.38-0.61) in resistance to black spot, firmness of flesh, fruit shape in longitudinal section, fruit size, acid content and number of spurs and at low levels (pear.

  15. Genome-wide conserved consensus transcription factor binding motifs are hyper-methylated

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    Down Thomas A

    2010-09-01

    Full Text Available Abstract Background DNA methylation can regulate gene expression by modulating the interaction between DNA and proteins or protein complexes. Conserved consensus motifs exist across the human genome ("predicted transcription factor binding sites": "predicted TFBS" but the large majority of these are proven by chromatin immunoprecipitation and high throughput sequencing (ChIP-seq not to be biological transcription factor binding sites ("empirical TFBS". We hypothesize that DNA methylation at conserved consensus motifs prevents promiscuous or disorderly transcription factor binding. Results Using genome-wide methylation maps of the human heart and sperm, we found that all conserved consensus motifs as well as the subset of those that reside outside CpG islands have an aggregate profile of hyper-methylation. In contrast, empirical TFBS with conserved consensus motifs have a profile of hypo-methylation. 40% of empirical TFBS with conserved consensus motifs resided in CpG islands whereas only 7% of all conserved consensus motifs were in CpG islands. Finally we further identified a minority subset of TF whose profiles are either hypo-methylated or neutral at their respective conserved consensus motifs implicating that these TF may be responsible for establishing or maintaining an un-methylated DNA state, or whose binding is not regulated by DNA methylation. Conclusions Our analysis supports the hypothesis that at least for a subset of TF, empirical binding to conserved consensus motifs genome-wide may be controlled by DNA methylation.

  16. HITS-CLIP yields genome-wide insights into brain alternative RNA processing

    Science.gov (United States)

    Licatalosi, Donny D.; Mele, Aldo; Fak, John J.; Ule, Jernej; Kayikci, Melis; Chi, Sung Wook; Clark, Tyson A.; Schweitzer, Anthony C.; Blume, John E.; Wang, Xuning; Darnell, Jennifer C.; Darnell, Robert B.

    2008-11-01

    Protein-RNA interactions have critical roles in all aspects of gene expression. However, applying biochemical methods to understand such interactions in living tissues has been challenging. Here we develop a genome-wide means of mapping protein-RNA binding sites in vivo, by high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP). HITS-CLIP analysis of the neuron-specific splicing factor Nova revealed extremely reproducible RNA-binding maps in multiple mouse brains. These maps provide genome-wide in vivo biochemical footprints confirming the previous prediction that the position of Nova binding determines the outcome of alternative splicing; moreover, they are sufficiently powerful to predict Nova action de novo. HITS-CLIP revealed a large number of Nova-RNA interactions in 3' untranslated regions, leading to the discovery that Nova regulates alternative polyadenylation in the brain. HITS-CLIP, therefore, provides a robust, unbiased means to identify functional protein-RNA interactions in vivo.

  17. genipe: an automated genome-wide imputation pipeline with automatic reporting and statistical tools.

    Science.gov (United States)

    Lemieux Perreault, Louis-Philippe; Legault, Marc-André; Asselin, Géraldine; Dubé, Marie-Pierre

    2016-12-01

    Genotype imputation is now commonly performed following genome-wide genotyping experiments. Imputation increases the density of analyzed genotypes in the dataset, enabling fine-mapping across the genome. However, the process of imputation using the most recent publicly available reference datasets can require considerable computation power and the management of hundreds of large intermediate files. We have developed genipe, a complete genome-wide imputation pipeline which includes automatic reporting, imputed data indexing and management, and a suite of statistical tests for imputed data commonly used in genetic epidemiology (Sequence Kernel Association Test, Cox proportional hazards for survival analysis, and linear mixed models for repeated measurements in longitudinal studies). The genipe package is an open source Python software and is freely available for non-commercial use (CC BY-NC 4.0) at https://github.com/pgxcentre/genipe Documentation and tutorials are available at http://pgxcentre.github.io/genipe CONTACT: louis-philippe.lemieux.perreault@statgen.org or marie-pierre.dube@statgen.orgSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  18. Genome-wide analysis of poly(A) site selection in Schizosaccharomyces pombe

    KAUST Repository

    Schlackow, M.

    2013-10-23

    Polyadenylation of pre-mRNAs, a critical step in eukaryotic gene expression, is mediated by cis elements collectively called the polyadenylation signal. Genome-wide analysis of such polyadenylation signals was missing in fission yeast, even though it is an important model organism. We demonstrate that the canonical AATAAA motif is the most frequent and functional polyadenylation signal in Schizosaccharomyces pombe. Using analysis of RNA-Seq data sets from cells grown under various physiological conditions, we identify 3\\' UTRs for nearly 90% of the yeast genes. Heterogeneity of cleavage sites is common, as is alternative polyadenylation within and between conditions. We validated the computationally identified sequence elements likely to promote polyadenylation by functional assays, including qRT-PCR and 3\\'RACE analysis. The biological importance of the AATAAA motif is underlined by functional analysis of the genes containing it. Furthermore, it has been shown that convergent genes require trans elements, like cohesin for efficient transcription termination. Here we show that convergent genes lacking cohesin (on chromosome 2) are generally associated with longer overlapping mRNA transcripts. Our bioinformatic and experimental genome-wide results are summarized and can be accessed and customized in a user-friendly database Pomb(A).

  19. An efficient hierarchical generalized linear mixed model for pathway analysis of genome-wide association studies.

    Science.gov (United States)

    Wang, Lily; Jia, Peilin; Wolfinger, Russell D; Chen, Xi; Grayson, Britney L; Aune, Thomas M; Zhao, Zhongming

    2011-03-01

    In genome-wide association studies (GWAS) of complex diseases, genetic variants having real but weak associations often fail to be detected at the stringent genome-wide significance level. Pathway analysis, which tests disease association with combined association signals from a group of variants in the same pathway, has become increasingly popular. However, because of the complexities in genetic data and the large sample sizes in typical GWAS, pathway analysis remains to be challenging. We propose a new statistical model for pathway analysis of GWAS. This model includes a fixed effects component that models mean disease association for a group of genes, and a random effects component that models how each gene's association with disease varies about the gene group mean, thus belongs to the class of mixed effects models. The proposed model is computationally efficient and uses only summary statistics. In addition, it corrects for the presence of overlapping genes and linkage disequilibrium (LD). Via simulated and real GWAS data, we showed our model improved power over currently available pathway analysis methods while preserving type I error rate. Furthermore, using the WTCCC Type 1 Diabetes (T1D) dataset, we demonstrated mixed model analysis identified meaningful biological processes that agreed well with previous reports on T1D. Therefore, the proposed methodology provides an efficient statistical modeling framework for systems analysis of GWAS. The software code for mixed models analysis is freely available at http://biostat.mc.vanderbilt.edu/LilyWang.

  20. Genome-wide mapping of the cohesin complex in the yeast Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    Earl F Glynn

    2004-09-01

    Full Text Available In eukaryotic cells, cohesin holds sister chromatids together until they separate into daughter cells during mitosis. We have used chromatin immunoprecipitation coupled with microarray analysis (ChIP chip to produce a genome-wide description of cohesin binding to meiotic and mitotic chromosomes of Saccharomyces cerevisiae. A computer program, PeakFinder, enables flexible, automated identification and annotation of cohesin binding peaks in ChIP chip data. Cohesin sites are highly conserved in meiosis and mitosis, suggesting that chromosomes share a common underlying structure during different developmental programs. These sites occur with a semiperiodic spacing of 11 kb that correlates with AT content. The number of sites correlates with chromosome size; however, binding to neighboring sites does not appear to be cooperative. We observed a very strong correlation between cohesin sites and regions between convergent transcription units. The apparent incompatibility between transcription and cohesin binding exists in both meiosis and mitosis. Further experiments reveal that transcript elongation into a cohesin-binding site removes cohesin. A negative correlation between cohesin sites and meiotic recombination sites suggests meiotic exchange is sensitive to the chromosome structure provided by cohesin. The genome-wide view of mitotic and meiotic cohesin binding provides an important framework for the exploration of cohesins and cohesion in other genomes.

  1. Genome-wide alterations of the DNA replication program during tumor progression

    Science.gov (United States)

    Arneodo, A.; Goldar, A.; Argoul, F.; Hyrien, O.; Audit, B.

    2016-08-01

    Oncogenic stress is a major driving force in the early stages of cancer development. Recent experimental findings reveal that, in precancerous lesions and cancers, activated oncogenes may induce stalling and dissociation of DNA replication forks resulting in DNA damage. Replication timing is emerging as an important epigenetic feature that recapitulates several genomic, epigenetic and functional specificities of even closely related cell types. There is increasing evidence that chromosome rearrangements, the hallmark of many cancer genomes, are intimately associated with the DNA replication program and that epigenetic replication timing changes often precede chromosomic rearrangements. The recent development of a novel methodology to map replication fork polarity using deep sequencing of Okazaki fragments has provided new and complementary genome-wide replication profiling data. We review the results of a wavelet-based multi-scale analysis of genomic and epigenetic data including replication profiles along human chromosomes. These results provide new insight into the spatio-temporal replication program and its dynamics during differentiation. Here our goal is to bring to cancer research, the experimental protocols and computational methodologies for replication program profiling, and also the modeling of the spatio-temporal replication program. To illustrate our purpose, we report very preliminary results obtained for the chronic myelogeneous leukemia, the archetype model of cancer. Finally, we discuss promising perspectives on using genome-wide DNA replication profiling as a novel efficient tool for cancer diagnosis, prognosis and personalized treatment.

  2. GStream: improving SNP and CNV coverage on genome-wide association studies.

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    Arnald Alonso

    Full Text Available We present GStream, a method that combines genome-wide SNP and CNV genotyping in the Illumina microarray platform with unprecedented accuracy. This new method outperforms previous well-established SNP genotyping software. More importantly, the CNV calling algorithm of GStream dramatically improves the results obtained by previous state-of-the-art methods and yields an accuracy that is close to that obtained by purely CNV-oriented technologies like Comparative Genomic Hybridization (CGH. We demonstrate the superior performance of GStream using microarray data generated from HapMap samples. Using the reference CNV calls generated by the 1000 Genomes Project (1KGP and well-known studies on whole genome CNV characterization based either on CGH or genotyping microarray technologies, we show that GStream can increase the number of reliably detected variants up to 25% compared to previously developed methods. Furthermore, the increased genome coverage provided by GStream allows the discovery of CNVs in close linkage disequilibrium with SNPs, previously associated with disease risk in published Genome-Wide Association Studies (GWAS. These results could provide important insights into the biological mechanism underlying the detected disease risk association. With GStream, large-scale GWAS will not only benefit from the combined genotyping of SNPs and CNVs at an unprecedented accuracy, but will also take advantage of the computational efficiency of the method.

  3. Semantically enabling a genome-wide association study database

    Directory of Open Access Journals (Sweden)

    Beck Tim

    2012-12-01

    Full Text Available Abstract Background The amount of data generated from genome-wide association studies (GWAS has grown rapidly, but considerations for GWAS phenotype data reuse and interchange have not kept pace. This impacts on the work of GWAS Central – a free and open access resource for the advanced querying and comparison of summary-level genetic association data. The benefits of employing ontologies for standardising and structuring data are widely accepted. The complex spectrum of observed human phenotypes (and traits, and the requirement for cross-species phenotype comparisons, calls for reflection on the most appropriate solution for the organisation of human phenotype data. The Semantic Web provides standards for the possibility of further integration of GWAS data and the ability to contribute to the web of Linked Data. Results A pragmatic consideration when applying phenotype ontologies to GWAS data is the ability to retrieve all data, at the most granular level possible, from querying a single ontology graph. We found the Medical Subject Headings (MeSH terminology suitable for describing all traits (diseases and medical signs and symptoms at various levels of granularity and the Human Phenotype Ontology (HPO most suitable for describing phenotypic abnormalities (medical signs and symptoms at the most granular level. Diseases within MeSH are mapped to HPO to infer the phenotypic abnormalities associated with diseases. Building on the rich semantic phenotype annotation layer, we are able to make cross-species phenotype comparisons and publish a core subset of GWAS data as RDF nanopublications. Conclusions We present a methodology for applying phenotype annotations to a comprehensive genome-wide association dataset and for ensuring compatibility with the Semantic Web. The annotations are used to assist with cross-species genotype and phenotype comparisons. However, further processing and deconstructions of terms may be required to facilitate automatic

  4. Developments in obesity genetics in the era of genome-wide association studies.

    Science.gov (United States)

    Day, Felix R; Loos, Ruth J F

    2011-01-01

    Obesity is an important factor contributing to the global burden of morbidity and mortality. By identifying obesity susceptibility genes, scientists aim to elucidate some of its aetiology. Early studies used candidate gene and genome-wide linkage approaches to search for such genes with limited success. However, the advent of genome-wide association studies (GWAS) has dramatically increased the pace of gene discovery. So far, GWAS have identified at least 50 loci robustly associated with body mass index (BMI), waist-to-hip ratio, body fat percentage and extreme obesity. Some of these have been shown to replicate in non-white populations and in children and adolescents. Furthermore, for some loci interaction studies have shown that the BMI-increasing effect is attenuated in physically active individuals. Despite many successful discoveries, the effect sizes of the established loci are small, and combined they explain only a fraction of the inter-individual variation in BMI. The low predictive value means that their value in mainstream health care is limited. However, as most of these newly established loci were not previously linked to obesity, they may provide new insights into body weight regulation. Continued efforts in gene discovery, using a range of approaches, will be needed to increase our understanding of obesity. Copyright © 2011 S. Karger AG, Basel.

  5. Genome-wide association screens for Achilles tendon and ACL tears and tendinopathy

    Science.gov (United States)

    Roos, Thomas R.; Roos, Andrew K.; Kleimeyer, John P.; Ahmed, Marwa A.; Goodlin, Gabrielle T.; Fredericson, Michael; Ioannidis, John P. A.; Avins, Andrew L.; Dragoo, Jason L.

    2017-01-01

    Achilles tendinopathy or rupture and anterior cruciate ligament (ACL) rupture are substantial injuries affecting athletes, associated with delayed recovery or inability to return to competition. To identify genetic markers that might be used to predict risk for these injuries, we performed genome-wide association screens for these injuries using data from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort consisting of 102,979 individuals. We did not find any single nucleotide polymorphisms (SNPs) associated with either of these injuries with a p-value that was genome-wide significant (pAchilles tendon injury and ACL rupture, respectively. We then tested SNPs previously reported to be associated with either Achilles tendon injury or ACL rupture. None showed an association in our cohort with a false discovery rate of less than 5%. We obtained, however, moderate to weak evidence for replication in one case; specifically, rs4919510 in MIR608 had a p-value of 5.1x10-3 for association with Achilles tendon injury, corresponding to a 7% chance of false replication. Finally, we tested 2855 SNPs in 90 candidate genes for musculoskeletal injury, but did not find any that showed a significant association below a false discovery rate of 5%. We provide data containing summary statistics for the entire genome, which will be useful for future genetic studies on these injuries. PMID:28358823

  6. Active chromatin domains are defined by acetylation islands revealed by genome-wide mapping.

    Science.gov (United States)

    Roh, Tae-Young; Cuddapah, Suresh; Zhao, Keji

    2005-03-01

    The identity and developmental potential of a human cell is specified by its epigenome that is largely defined by patterns of chromatin modifications including histone acetylation. Here we report high-resolution genome-wide mapping of diacetylation of histone H3 at Lys 9 and Lys 14 in resting and activated human T cells by genome-wide mapping technique (GMAT). Our data show that high levels of the H3 acetylation are detected in gene-rich regions. The chromatin accessibility and gene expression of a genetic domain is correlated with hyperacetylation of promoters and other regulatory elements but not with generally elevated acetylation of the entire domain. Islands of acetylation are identified in the intergenic and transcribed regions. The locations of the 46,813 acetylation islands identified in this study are significantly correlated with conserved noncoding sequences (CNSs) and many of them are colocalized with known regulatory elements in T cells. TCR signaling induces 4045 new acetylation loci that may mediate the global chromatin remodeling and gene activation. We propose that the acetylation islands are epigenetic marks that allow prediction of functional regulatory elements.

  7. Genome-wide Selective Sweeps in Natural Bacterial Populations Revealed by Time-series Metagenomics

    Energy Technology Data Exchange (ETDEWEB)

    Chan, Leong-Keat; Bendall, Matthew L.; Malfatti, Stephanie; Schwientek, Patrick; Tremblay, Julien; Schackwitz, Wendy; Martin, Joel; Pati, Amrita; Bushnell, Brian; Foster, Brian; Kang, Dongwan; Tringe, Susannah G.; Bertilsson, Stefan; Moran, Mary Ann; Shade, Ashley; Newton, Ryan J.; Stevens, Sarah; McMahon, Katherine D.; Malmstrom, Rex R.

    2014-06-18

    Multiple evolutionary models have been proposed to explain the formation of genetically and ecologically distinct bacterial groups. Time-series metagenomics enables direct observation of evolutionary processes in natural populations, and if applied over a sufficiently long time frame, this approach could capture events such as gene-specific or genome-wide selective sweeps. Direct observations of either process could help resolve how distinct groups form in natural microbial assemblages. Here, from a three-year metagenomic study of a freshwater lake, we explore changes in single nucleotide polymorphism (SNP) frequencies and patterns of gene gain and loss in populations of Chlorobiaceae and Methylophilaceae. SNP analyses revealed substantial genetic heterogeneity within these populations, although the degree of heterogeneity varied considerably among closely related, co-occurring Methylophilaceae populations. SNP allele frequencies, as well as the relative abundance of certain genes, changed dramatically over time in each population. Interestingly, SNP diversity was purged at nearly every genome position in one of the Chlorobiaceae populations over the course of three years, while at the same time multiple genes either swept through or were swept from this population. These patterns were consistent with a genome-wide selective sweep, a process predicted by the ‘ecotype model’ of diversification, but not previously observed in natural populations.

  8. Genome-wide analysis of alternative splicing during human heart development

    Science.gov (United States)

    Wang, He; Chen, Yanmei; Li, Xinzhong; Chen, Guojun; Zhong, Lintao; Chen, Gangbing; Liao, Yulin; Liao, Wangjun; Bin, Jianping

    2016-01-01

    Alternative splicing (AS) drives determinative changes during mouse heart development. Recent high-throughput technological advancements have facilitated genome-wide AS, while its analysis in human foetal heart transition to the adult stage has not been reported. Here, we present a high-resolution global analysis of AS transitions between human foetal and adult hearts. RNA-sequencing data showed extensive AS transitions occurred between human foetal and adult hearts, and AS events occurred more frequently in protein-coding genes than in long non-coding RNA (lncRNA). A significant difference of AS patterns was found between foetal and adult hearts. The predicted difference in AS events was further confirmed using quantitative reverse transcription-polymerase chain reaction analysis of human heart samples. Functional foetal-specific AS event analysis showed enrichment associated with cell proliferation-related pathways including cell cycle, whereas adult-specific AS events were associated with protein synthesis. Furthermore, 42.6% of foetal-specific AS events showed significant changes in gene expression levels between foetal and adult hearts. Genes exhibiting both foetal-specific AS and differential expression were highly enriched in cell cycle-associated functions. In conclusion, we provided a genome-wide profiling of AS transitions between foetal and adult hearts and proposed that AS transitions and deferential gene expression may play determinative roles in human heart development. PMID:27752099

  9. Genome-wide analysis of alternative splicing during human heart development

    Science.gov (United States)

    Wang, He; Chen, Yanmei; Li, Xinzhong; Chen, Guojun; Zhong, Lintao; Chen, Gangbing; Liao, Yulin; Liao, Wangjun; Bin, Jianping

    2016-10-01

    Alternative splicing (AS) drives determinative changes during mouse heart development. Recent high-throughput technological advancements have facilitated genome-wide AS, while its analysis in human foetal heart transition to the adult stage has not been reported. Here, we present a high-resolution global analysis of AS transitions between human foetal and adult hearts. RNA-sequencing data showed extensive AS transitions occurred between human foetal and adult hearts, and AS events occurred more frequently in protein-coding genes than in long non-coding RNA (lncRNA). A significant difference of AS patterns was found between foetal and adult hearts. The predicted difference in AS events was further confirmed using quantitative reverse transcription-polymerase chain reaction analysis of human heart samples. Functional foetal-specific AS event analysis showed enrichment associated with cell proliferation-related pathways including cell cycle, whereas adult-specific AS events were associated with protein synthesis. Furthermore, 42.6% of foetal-specific AS events showed significant changes in gene expression levels between foetal and adult hearts. Genes exhibiting both foetal-specific AS and differential expression were highly enriched in cell cycle-associated functions. In conclusion, we provided a genome-wide profiling of AS transitions between foetal and adult hearts and proposed that AS transitions and deferential gene expression may play determinative roles in human heart development.

  10. Genome-wide Selective Sweeps in Natural Bacterial Populations Revealed by Time-series Metagenomics

    Energy Technology Data Exchange (ETDEWEB)

    Chan, Leong-Keat; Bendall, Matthew L.; Malfatti, Stephanie; Schwientek, Patrick; Tremblay, Julien; Schackwitz, Wendy; Martin, Joel; Pati, Amrita; Bushnell, Brian; Foster, Brian; Kang, Dongwan; Tringe, Susannah G.; Bertilsson, Stefan; Moran, Mary Ann; Shade, Ashley; Newton, Ryan J.; Stevens, Sarah; McMcahon, Katherine D.; Mamlstrom, Rex R.

    2014-05-12

    Multiple evolutionary models have been proposed to explain the formation of genetically and ecologically distinct bacterial groups. Time-series metagenomics enables direct observation of evolutionary processes in natural populations, and if applied over a sufficiently long time frame, this approach could capture events such as gene-specific or genome-wide selective sweeps. Direct observations of either process could help resolve how distinct groups form in natural microbial assemblages. Here, from a three-year metagenomic study of a freshwater lake, we explore changes in single nucleotide polymorphism (SNP) frequencies and patterns of gene gain and loss in populations of Chlorobiaceae and Methylophilaceae. SNP analyses revealed substantial genetic heterogeneity within these populations, although the degree of heterogeneity varied considerably among closely related, co-occurring Methylophilaceae populations. SNP allele frequencies, as well as the relative abundance of certain genes, changed dramatically over time in each population. Interestingly, SNP diversity was purged at nearly every genome position in one of the Chlorobiaceae populations over the course of three years, while at the same time multiple genes either swept through or were swept from this population. These patterns were consistent with a genome-wide selective sweep, a process predicted by the ecotype model? of diversification, but not previously observed in natural populations.

  11. Using the Pareto principle in genome-wide breeding value estimation

    Directory of Open Access Journals (Sweden)

    Yu Xijiang

    2011-11-01

    Full Text Available Abstract Genome-wide breeding value (GWEBV estimation methods can be classified based on the prior distribution assumptions of marker effects. Genome-wide BLUP methods assume a normal prior distribution for all markers with a constant variance, and are computationally fast. In Bayesian methods, more flexible prior distributions of SNP effects are applied that allow for very large SNP effects although most are small or even zero, but these prior distributions are often also computationally demanding as they rely on Monte Carlo Markov chain sampling. In this study, we adopted the Pareto principle to weight available marker loci, i.e., we consider that x% of the loci explain (100 - x% of the total genetic variance. Assuming this principle, it is also possible to define the variances of the prior distribution of the 'big' and 'small' SNP. The relatively few large SNP explain a large proportion of the genetic variance and the majority of the SNP show small effects and explain a minor proportion of the genetic variance. We name this method MixP, where the prior distribution is a mixture of two normal distributions, i.e. one with a big variance and one with a small variance. Simulation results, using a real Norwegian Red cattle pedigree, show that MixP is at least as accurate as the other methods in all studied cases. This method also reduces the hyper-parameters of the prior distribution from 2 (proportion and variance of SNP with big effects to 1 (proportion of SNP with big effects, assuming the overall genetic variance is known. The mixture of normal distribution prior made it possible to solve the equations iteratively, which greatly reduced computation loads by two orders of magnitude. In the era of marker density reaching million(s and whole-genome sequence data, MixP provides a computationally feasible Bayesian method of analysis.

  12. Genome-wide significant risk associations for mucinous ovarian carcinoma

    Science.gov (United States)

    Kelemen, Linda E.; Lawrenson, Kate; Tyrer, Jonathan; Li, Qiyuan; M. Lee, Janet; Seo, Ji-Heui; Phelan, Catherine M.; Beesley, Jonathan; Chen, Xiaoqin; Spindler, Tassja J.; Aben, Katja K.H.; Anton-Culver, Hoda; Antonenkova, Natalia; Baker, Helen; Bandera, Elisa V.; Bean, Yukie; Beckmann, Matthias W.; Bisogna, Maria; Bjorge, Line; Bogdanova, Natalia; Brinton, Louise A.; Brooks-Wilson, Angela; Bruinsma, Fiona; Butzow, Ralf; Campbell, Ian G.; Carty, Karen; Chang-Claude, Jenny; Chen, Y. Ann; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel W.; Cunningham, Julie M.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas T.; Edwards, Robert P.; Eilber, Ursula; Ekici, Arif B.; Engelholm, Svend Aage; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hasmad, Hanis Nazihah; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A.T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus; Hosono, Satoyo; Iversen, Edwin S.; Jakubowska, Anna; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kellar, Melissa; Kelley, Joseph L.; Kiemeney, Lambertus A.; Krakstad, Camilla; Kjaer, Susanne K.; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon F.A.G.; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; McNeish, Iain; Menon, Usha; Modugno, Francesmary; Moes-Sosnowska, Joanna; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Nevanlinna, Heli; Azmi, Mat Adenan Noor; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Paul, James; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Schildkraut, Joellen M.; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston, Lara; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J; Tworoger, Shelley S.; van Altena, Anne M.; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Wlodzimierz, Sawicki; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna H.; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A.; Freedman, Matthew L.; Chenevix-Trench, Georgia; Pharoah, Paul D.; Gayther, Simon A.; Berchuck, Andrew

    2015-01-01

    Genome-wide association studies have identified several risk associations for ovarian carcinomas (OC) but not for mucinous ovarian carcinomas (MOC). Genotypes from OC cases and controls were imputed into the 1000 Genomes Project reference panel. Analysis of 1,644 MOC cases and 21,693 controls identified three novel risk associations: rs752590 at 2q13 (P = 3.3 × 10−8), rs711830 at 2q31.1 (P = 7.5 × 10−12) and rs688187 at 19q13.2 (P = 6.8 × 10−13). Expression Quantitative Trait Locus (eQTL) analysis in ovarian and colorectal tumors (which are histologically similar to MOC) identified significant eQTL associations for HOXD9 at 2q31.1 in ovarian (P = 4.95 × 10−4, FDR = 0.003) and colorectal (P = 0.01, FDR = 0.09) tumors, and for PAX8 at 2q13 in colorectal tumors (P = 0.03, FDR = 0.09). Chromosome conformation capture analysis identified interactions between the HOXD9 promoter and risk SNPs at 2q31.1. Overexpressing HOXD9 in MOC cells augmented the neoplastic phenotype. These findings provide the first evidence for MOC susceptibility variants and insights into the underlying biology of the disease. PMID:26075790

  13. Genome-Wide Analysis of Human MicroRNA Stability

    Directory of Open Access Journals (Sweden)

    Yang Li

    2013-01-01

    Full Text Available Increasing studies have shown that microRNA (miRNA stability plays important roles in physiology. However, the global picture of miRNA stability remains largely unknown. Here, we had analyzed genome-wide miRNA stability across 10 diverse cell types using miRNA arrays. We found that miRNA stability shows high dynamics and diversity both within individual cells and across cell types. Strikingly, we observed a negative correlation between miRNA stability and miRNA expression level, which is different from current findings on other biological molecules such as proteins and mRNAs that show positive and not negative correlations between stability and expression level. This finding indicates that miRNA has a distinct action mode, which we called “rapid production, rapid turnover; slow production, slow turnover.” This mode further suggests that high expression miRNAs normally degrade fast and may endow the cell with special properties that facilitate cellular status-transition. Moreover, we revealed that the stability of miRNAs is affected by cohorts of factors that include miRNA targets, transcription factors, nucleotide content, evolution, associated disease, and environmental factors. Together, our results provided an extensive description of the global landscape, dynamics, and distinct mode of human miRNA stability, which provide help in investigating their functions in physiology and pathophysiology.

  14. Genome-wide association study and premature ovarian failure.

    Science.gov (United States)

    Christin-Maitre, S; Tachdjian, G

    2010-05-01

    Premature ovarian failure (POF) is defined as an amenorrhea for more than 4months, associated with elevated gonadotropins, usually higher than 20mIU/ml, occurring in a woman before the age of 40. Some candidate genes have been identified in the past 15years, such as FOXL2, FSHR, BMP15, GDF9, Xfra premutation. However, POF etiology remains unknown in more than 90% of cases. The first strategy to identify candidate gene, apart from studying genes involved in ovarian failure in animal models, relies on the study of X chromosome deletions and X;autosome translocations in patients. The second strategy is based on linkage analysis, the third one on Comparative Genomic Hybridization (CGH) array. The latest strategy relies on Genome-Wide Association Studies (GWAS). This technique consists in screening single nucleotide polymorphisms (SNPs) in patients and controls. So far, three studies have been performed and have identified different loci potentially linked to POF, such as PTHB1 and ADAMTS19. However, replications in independent cohorts need to be performed. GWAS studies on large cohorts of women with POF should find new candidate genes in the near future.

  15. Insights into kidney diseases from genome-wide association studies.

    Science.gov (United States)

    Wuttke, Matthias; Köttgen, Anna

    2016-09-01

    Over the past decade, genome-wide association studies (GWAS) have considerably improved our understanding of the genetic basis of kidney function and disease. Population-based studies, used to investigate traits that define chronic kidney disease (CKD), have identified >50 genomic regions in which common genetic variants associate with estimated glomerular filtration rate or urinary albumin-to-creatinine ratio. Case-control studies, used to study specific CKD aetiologies, have yielded risk loci for specific kidney diseases such as IgA nephropathy and membranous nephropathy. In this Review, we summarize important findings from GWAS and clinical and experimental follow-up studies. We also compare risk allele frequency, effect sizes, and specificity in GWAS of CKD-defining traits and GWAS of specific CKD aetiologies and the implications for study design. Genomic regions identified in GWAS of CKD-defining traits can contain causal genes for monogenic kidney diseases. Population-based research on kidney function traits can therefore generate insights into more severe forms of kidney diseases. Experimental follow-up studies have begun to identify causal genes and variants, which are potential therapeutic targets, and suggest mechanisms underlying the high allele frequency of causal variants. GWAS are thus a useful approach to advance knowledge in nephrology.

  16. Genome-Wide Association Study of Serum Selenium Concentrations

    Directory of Open Access Journals (Sweden)

    Ulrike Peters

    2013-05-01

    Full Text Available Selenium is an essential trace element and circulating selenium concentrations have been associated with a wide range of diseases. Candidate gene studies suggest that circulating selenium concentrations may be impacted by genetic variation; however, no study has comprehensively investigated this hypothesis. Therefore, we conducted a two-stage genome-wide association study to identify genetic variants associated with serum selenium concentrations in 1203 European descents from two cohorts: the Prostate, Lung, Colorectal, and Ovarian (PLCO Cancer Screening and the Women’s Health Initiative (WHI. We tested association between 2,474,333 single nucleotide polymorphisms (SNPs and serum selenium concentrations using linear regression models. In the first stage (PLCO 41 SNPs clustered in 15 regions had p < 1 × 10−5. None of these 41 SNPs reached the significant threshold (p = 0.05/15 regions = 0.003 in the second stage (WHI. Three SNPs had p < 0.05 in the second stage (rs1395479 and rs1506807 in 4q34.3/AGA-NEIL3; and rs891684 in 17q24.3/SLC39A11 and had p between 2.62 × 10−7 and 4.04 × 10−7 in the combined analysis (PLCO + WHI. Additional studies are needed to replicate these findings. Identification of genetic variation that impacts selenium concentrations may contribute to a better understanding of which genes regulate circulating selenium concentrations.

  17. Genome-wide search for strabismus susceptibility loci.

    Directory of Open Access Journals (Sweden)

    Fujiwara H

    2003-06-01

    Full Text Available The purpose of this study was to search for chromosomal susceptibility loci for comitant strabismus. Genomic DNA was isolated from 10mL blood taken from each member of 30 nuclear families in which 2 or more siblings are affected by either esotropia or exotropia. A genome-wide search was performed with amplification by polymerase chain reaction of 400 markers in microsatellite regions with approximately 10 cM resolution. For each locus, non-parametric affected sib-pair analysis and non-parametric linkage analysis for multiple pedigrees (Genehunter software, http://linkage.rockefeller.edu/soft/ were used to calculate multipoint lod scores and non-parametric linkage (NPL scores, respectively. In sib-pair analysis, lod scores showed basically flat lines with several peaks of 0.25 on all chromosomes. In non-parametric linkage analysis for multiple pedigrees, NPL scores showed one peak as high as 1.34 on chromosomes 1, 2, 4, 7, 10, 15, and 16, while 2 such peaks were found on chromosomes 3, 9, 11, 12, 18, and 20. Non-parametric linkage analysis for multiple pedigrees of 30 families with comitant strabismus suggested a number of chromosomal susceptibility loci. Our ongoing study involving a larger number of families will refine the accuracy of statistical analysis to pinpoint susceptibility loci for comitant strabismus.

  18. Genome-wide identification of KANADI1 target genes.

    Directory of Open Access Journals (Sweden)

    Paz Merelo

    Full Text Available Plant organ development and polarity establishment is mediated by the action of several transcription factors. Among these, the KANADI (KAN subclade of the GARP protein family plays important roles in polarity-associated processes during embryo, shoot and root patterning. In this study, we have identified a set of potential direct target genes of KAN1 through a combination of chromatin immunoprecipitation/DNA sequencing (ChIP-Seq and genome-wide transcriptional profiling using tiling arrays. Target genes are over-represented for genes involved in the regulation of organ development as well as in the response to auxin. KAN1 affects directly the expression of several genes previously shown to be important in the establishment of polarity during lateral organ and vascular tissue development. We also show that KAN1 controls through its target genes auxin effects on organ development at different levels: transport and its regulation, and signaling. In addition, KAN1 regulates genes involved in the response to abscisic acid, jasmonic acid, brassinosteroids, ethylene, cytokinins and gibberellins. The role of KAN1 in organ polarity is antagonized by HD-ZIPIII transcription factors, including REVOLUTA (REV. A comparison of their target genes reveals that the REV/KAN1 module acts in organ patterning through opposite regulation of shared targets. Evidence of mutual repression between closely related family members is also shown.

  19. Natural selection on functional modules, a genome-wide analysis.

    Science.gov (United States)

    Serra, François; Arbiza, Leonardo; Dopazo, Joaquín; Dopazo, Hernán

    2011-03-01

    Classically, the functional consequences of natural selection over genomes have been analyzed as the compound effects of individual genes. The current paradigm for large-scale analysis of adaptation is based on the observed significant deviations of rates of individual genes from neutral evolutionary expectation. This approach, which assumed independence among genes, has not been able to identify biological functions significantly enriched in positively selected genes in individual species. Alternatively, pooling related species has enhanced the search for signatures of selection. However, grouping signatures does not allow testing for adaptive differences between species. Here we introduce the Gene-Set Selection Analysis (GSSA), a new genome-wide approach to test for evidences of natural selection on functional modules. GSSA is able to detect lineage specific evolutionary rate changes in a notable number of functional modules. For example, in nine mammal and Drosophilae genomes GSSA identifies hundreds of functional modules with significant associations to high and low rates of evolution. Many of the detected functional modules with high evolutionary rates have been previously identified as biological functions under positive selection. Notably, GSSA identifies conserved functional modules with many positively selected genes, which questions whether they are exclusively selected for fitting genomes to environmental changes. Our results agree with previous studies suggesting that adaptation requires positive selection, but not every mutation under positive selection contributes to the adaptive dynamical process of the evolution of species.

  20. Natural selection on functional modules, a genome-wide analysis.

    Directory of Open Access Journals (Sweden)

    François Serra

    2011-03-01

    Full Text Available Classically, the functional consequences of natural selection over genomes have been analyzed as the compound effects of individual genes. The current paradigm for large-scale analysis of adaptation is based on the observed significant deviations of rates of individual genes from neutral evolutionary expectation. This approach, which assumed independence among genes, has not been able to identify biological functions significantly enriched in positively selected genes in individual species. Alternatively, pooling related species has enhanced the search for signatures of selection. However, grouping signatures does not allow testing for adaptive differences between species. Here we introduce the Gene-Set Selection Analysis (GSSA, a new genome-wide approach to test for evidences of natural selection on functional modules. GSSA is able to detect lineage specific evolutionary rate changes in a notable number of functional modules. For example, in nine mammal and Drosophilae genomes GSSA identifies hundreds of functional modules with significant associations to high and low rates of evolution. Many of the detected functional modules with high evolutionary rates have been previously identified as biological functions under positive selection. Notably, GSSA identifies conserved functional modules with many positively selected genes, which questions whether they are exclusively selected for fitting genomes to environmental changes. Our results agree with previous studies suggesting that adaptation requires positive selection, but not every mutation under positive selection contributes to the adaptive dynamical process of the evolution of species.

  1. Identification of differential translation in genome wide studies.

    Science.gov (United States)

    Larsson, Ola; Sonenberg, Nahum; Nadon, Robert

    2010-12-14

    Regulation of gene expression through translational control is a fundamental mechanism implicated in many biological processes ranging from memory formation to innate immunity and whose dysregulation contributes to human diseases. Genome wide analyses of translational control strive to identify differential translation independent of cytosolic mRNA levels. For this reason, most studies measure genes' translation levels as log ratios (translation levels divided by corresponding cytosolic mRNA levels obtained in parallel). Counterintuitively, arising from a mathematical necessity, these log ratios tend to be highly correlated with the cytosolic mRNA levels. Accordingly, they do not effectively correct for cytosolic mRNA level and generate substantial numbers of biological false positives and false negatives. We show that analysis of partial variance, which produces estimates of translational activity that are independent of cytosolic mRNA levels, is a superior alternative. When combined with a variance shrinkage method for estimating error variance, analysis of partial variance has the additional benefit of having greater statistical power and identifying fewer genes as translationally regulated resulting merely from unrealistically low variance estimates rather than from large changes in translational activity. In contrast to log ratios, this formal analytical approach estimates translation effects in a statistically rigorous manner, eliminates the need for inefficient and error-prone heuristics, and produces results that agree with biological function. The method is applicable to datasets obtained from both the commonly used polysome microarray method and the sequencing-based ribosome profiling method.

  2. Genome-Wide Analysis of DNA Methylation in Human Amnion

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    Jinsil Kim

    2013-01-01

    Full Text Available The amnion is a specialized tissue in contact with the amniotic fluid, which is in a constantly changing state. To investigate the importance of epigenetic events in this tissue in the physiology and pathophysiology of pregnancy, we performed genome-wide DNA methylation profiling of human amnion from term (with and without labor and preterm deliveries. Using the Illumina Infinium HumanMethylation27 BeadChip, we identified genes exhibiting differential methylation associated with normal labor and preterm birth. Functional analysis of the differentially methylated genes revealed biologically relevant enriched gene sets. Bisulfite sequencing analysis of the promoter region of the oxytocin receptor (OXTR gene detected two CpG dinucleotides showing significant methylation differences among the three groups of samples. Hypermethylation of the CpG island of the solute carrier family 30 member 3 (SLC30A3 gene in preterm amnion was confirmed by methylation-specific PCR. This work provides preliminary evidence that DNA methylation changes in the amnion may be at least partially involved in the physiological process of labor and the etiology of preterm birth and suggests that DNA methylation profiles, in combination with other biological data, may provide valuable insight into the mechanisms underlying normal and pathological pregnancies.

  3. A genome wide dosage suppressor network reveals genomic robustness

    Science.gov (United States)

    Patra, Biranchi; Kon, Yoshiko; Yadav, Gitanjali; Sevold, Anthony W.; Frumkin, Jesse P.; Vallabhajosyula, Ravishankar R.; Hintze, Arend; Østman, Bjørn; Schossau, Jory; Bhan, Ashish; Marzolf, Bruz; Tamashiro, Jenna K.; Kaur, Amardeep; Baliga, Nitin S.; Grayhack, Elizabeth J.; Adami, Christoph; Galas, David J.; Raval, Alpan; Phizicky, Eric M.; Ray, Animesh

    2017-01-01

    Genomic robustness is the extent to which an organism has evolved to withstand the effects of deleterious mutations. We explored the extent of genomic robustness in budding yeast by genome wide dosage suppressor analysis of 53 conditional lethal mutations in cell division cycle and RNA synthesis related genes, revealing 660 suppressor interactions of which 642 are novel. This collection has several distinctive features, including high co-occurrence of mutant-suppressor pairs within protein modules, highly correlated functions between the pairs and higher diversity of functions among the co-suppressors than previously observed. Dosage suppression of essential genes encoding RNA polymerase subunits and chromosome cohesion complex suggests a surprising degree of functional plasticity of macromolecular complexes, and the existence of numerous degenerate pathways for circumventing the effects of potentially lethal mutations. These results imply that organisms and cancer are likely able to exploit the genomic robustness properties, due the persistence of cryptic gene and pathway functions, to generate variation and adapt to selective pressures. PMID:27899637

  4. Genome-wide transcriptome analysis of 150 cell samples†

    Science.gov (United States)

    Russom, Aman; Xiao, Wenzhong; Wilhelmy, Julie; Wang, Shenglong; Heath, Joe Don; Kurn, Nurith; Tompkins, Ronald G.; Davis, Ronald W.; Toner, Mehmet

    2013-01-01

    A major challenge in molecular biology is interrogating the human transcriptome on a genome wide scale when only a limited amount of biological sample is available for analysis. Current methodologies using microarray technologies for simultaneously monitoring mRNA transcription levels require nanogram amounts of total RNA. To overcome the sample size limitation of current technologies, we have developed a method to probe the global gene expression in biological samples as small as 150 cells, or the equivalent of approximately 300 pg total RNA. The new method employs microfluidic devices for the purification of total RNA from mammalian cells and ultra-sensitive whole transcriptome amplification techniques. We verified that the RNA integrity is preserved through the isolation process, accomplished highly reproducible whole transcriptome analysis, and established high correlation between repeated isolations of 150 cells and the same cell culture sample. We validated the technology by demonstrating that the combined microfluidic and amplification protocol is capable of identifying biological pathways perturbed by stimulation, which are consistent with the information recognized in bulk-isolated samples. PMID:20023796

  5. Genome-wide transcriptome analysis of 150 cell samples.

    Science.gov (United States)

    Irimia, Daniel; Mindrinos, Michael; Russom, Aman; Xiao, Wenzhong; Wilhelmy, Julie; Wang, Shenglong; Heath, Joe Don; Kurn, Nurith; Tompkins, Ronald G; Davis, Ronald W; Toner, Mehmet

    2009-01-01

    A major challenge in molecular biology is interrogating the human transcriptome on a genome wide scale when only a limited amount of biological sample is available for analysis. Current methodologies using microarray technologies for simultaneously monitoring mRNA transcription levels require nanogram amounts of total RNA. To overcome the sample size limitation of current technologies, we have developed a method to probe the global gene expression in biological samples as small as 150 cells, or the equivalent of approximately 300 pg total RNA. The new method employs microfluidic devices for the purification of total RNA from mammalian cells and ultra-sensitive whole transcriptome amplification techniques. We verified that the RNA integrity is preserved through the isolation process, accomplished highly reproducible whole transcriptome analysis, and established high correlation between repeated isolations of 150 cells and the same cell culture sample. We validated the technology by demonstrating that the combined microfluidic and amplification protocol is capable of identifying biological pathways perturbed by stimulation, which are consistent with the information recognized in bulk-isolated samples.

  6. Genome-Wide Association Studies of the Human Gut Microbiota.

    Directory of Open Access Journals (Sweden)

    Emily R Davenport

    Full Text Available The bacterial composition of the human fecal microbiome is influenced by many lifestyle factors, notably diet. It is less clear, however, what role host genetics plays in dictating the composition of bacteria living in the gut. In this study, we examined the association of ~200K host genotypes with the relative abundance of fecal bacterial taxa in a founder population, the Hutterites, during two seasons (n = 91 summer, n = 93 winter, n = 57 individuals collected in both. These individuals live and eat communally, minimizing variation due to environmental exposures, including diet, which could potentially mask small genetic effects. Using a GWAS approach that takes into account the relatedness between subjects, we identified at least 8 bacterial taxa whose abundances were associated with single nucleotide polymorphisms in the host genome in each season (at genome-wide FDR of 20%. For example, we identified an association between a taxon known to affect obesity (genus Akkermansia and a variant near PLD1, a gene previously associated with body mass index. Moreover, we replicate a previously reported association from a quantitative trait locus (QTL mapping study of fecal microbiome abundance in mice (genus Lactococcus, rs3747113, P = 3.13 x 10-7. Finally, based on the significance distribution of the associated microbiome QTLs in our study with respect to chromatin accessibility profiles, we identified tissues in which host genetic variation may be acting to influence bacterial abundance in the gut.

  7. Genome-wide association study of circulating retinol levels.

    Science.gov (United States)

    Mondul, Alison M; Yu, Kai; Wheeler, William; Zhang, Hong; Weinstein, Stephanie J; Major, Jacqueline M; Cornelis, Marilyn C; Männistö, Satu; Hazra, Aditi; Hsing, Ann W; Jacobs, Kevin B; Eliassen, Heather; Tanaka, Toshiko; Reding, Douglas J; Hendrickson, Sara; Ferrucci, Luigi; Virtamo, Jarmo; Hunter, David J; Chanock, Stephen J; Kraft, Peter; Albanes, Demetrius

    2011-12-01

    Retinol is one of the most biologically active forms of vitamin A and is hypothesized to influence a wide range of human diseases including asthma, cardiovascular disease, infectious diseases and cancer. We conducted a genome-wide association study of 5006 Caucasian individuals drawn from two cohorts of men: the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study and the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. We identified two independent single-nucleotide polymorphisms associated with circulating retinol levels, which are located near the transthyretin (TTR) and retinol binding protein 4 (RBP4) genes which encode major carrier proteins of retinol: rs1667255 (P =2.30× 10(-17)) and rs10882272 (P =6.04× 10(-12)). We replicated the association with rs10882272 in RBP4 in independent samples from the Nurses' Health Study and the Invecchiare in Chianti Study (InCHIANTI) that included 3792 women and 504 men (P =9.49× 10(-5)), but found no association for retinol with rs1667255 in TTR among women, thus suggesting evidence for gender dimorphism (P-interaction=1.31× 10(-5)). Discovery of common genetic variants associated with serum retinol levels may provide further insight into the contribution of retinol and other vitamin A compounds to the development of cancer and other complex diseases.

  8. Genome-wide association study of proneness to anger.

    Directory of Open Access Journals (Sweden)

    Eric Mick

    Full Text Available BACKGROUND: Community samples suggest that approximately 1 in 20 children and adults exhibit clinically significant anger, hostility, and aggression. Individuals with dysregulated emotional control have a greater lifetime burden of psychiatric morbidity, severe impairment in role functioning, and premature mortality due to cardiovascular disease. METHODS: With publically available data secured from dbGaP, we conducted a genome-wide association study of proneness to anger using the Spielberger State-Trait Anger Scale in the Atherosclerosis Risk in Communities (ARIC study (n = 8,747. RESULTS: Subjects were, on average, 54 (range 45-64 years old at baseline enrollment, 47% (n = 4,117 were male, and all were of European descent by self-report. The mean Angry Temperament and Angry Reaction scores were 5.8 ± 1.8 and 7.6 ± 2.2. We observed a nominally significant finding (p = 2.9E-08, λ = 1.027 - corrected pgc = 2.2E-07, λ = 1.0015 on chromosome 6q21 in the gene coding for the non-receptor protein-tyrosine kinase, Fyn. CONCLUSIONS: Fyn interacts with NDMA receptors and inositol-1,4,5-trisphosphate (IP3-gated channels to regulate calcium influx and intracellular release in the post-synaptic density. These results suggest that signaling pathways regulating intracellular calcium homeostasis, which are relevant to memory, learning, and neuronal survival, may in part underlie the expression of Angry Temperament.

  9. A genome-wide association study in multiple system atrophy

    Science.gov (United States)

    Sailer, Anna; Nalls, Michael A.; Schulte, Claudia; Federoff, Monica; Price, T. Ryan; Lees, Andrew; Ross, Owen A.; Dickson, Dennis W.; Mok, Kin; Mencacci, Niccolo E.; Schottlaender, Lucia; Chelban, Viorica; Ling, Helen; O'Sullivan, Sean S.; Wood, Nicholas W.; Traynor, Bryan J.; Ferrucci, Luigi; Federoff, Howard J.; Mhyre, Timothy R.; Morris, Huw R.; Deuschl, Günther; Quinn, Niall; Widner, Hakan; Albanese, Alberto; Infante, Jon; Bhatia, Kailash P.; Poewe, Werner; Oertel, Wolfgang; Höglinger, Günter U.; Wüllner, Ullrich; Goldwurm, Stefano; Pellecchia, Maria Teresa; Ferreira, Joaquim; Tolosa, Eduardo; Bloem, Bastiaan R.; Rascol, Olivier; Meissner, Wassilios G.; Hardy, John A.; Revesz, Tamas; Holton, Janice L.; Gasser, Thomas; Wenning, Gregor K.; Singleton, Andrew B.

    2016-01-01

    Objective: To identify genetic variants that play a role in the pathogenesis of multiple system atrophy (MSA), we undertook a genome-wide association study (GWAS). Methods: We performed a GWAS with >5 million genotyped and imputed single nucleotide polymorphisms (SNPs) in 918 patients with MSA of European ancestry and 3,864 controls. MSA cases were collected from North American and European centers, one third of which were neuropathologically confirmed. Results: We found no significant loci after stringent multiple testing correction. A number of regions emerged as potentially interesting for follow-up at p < 1 × 10−6, including SNPs in the genes FBXO47, ELOVL7, EDN1, and MAPT. Contrary to previous reports, we found no association of the genes SNCA and COQ2 with MSA. Conclusions: We present a GWAS in MSA. We have identified several potentially interesting gene loci, including the MAPT locus, whose significance will have to be evaluated in a larger sample set. Common genetic variation in SNCA and COQ2 does not seem to be associated with MSA. In the future, additional samples of well-characterized patients with MSA will need to be collected to perform a larger MSA GWAS, but this initial study forms the basis for these next steps. PMID:27629089

  10. Genome-wide studies of telomere biology in budding yeast

    Directory of Open Access Journals (Sweden)

    Yaniv Harari

    2014-03-01

    Full Text Available Telomeres are specialized DNA-protein structures at the ends of eukaryotic chromosomes. Telomeres are essential for chromosomal stability and integrity, as they prevent chromosome ends from being recognized as double strand breaks. In rapidly proliferating cells, telomeric DNA is synthesized by the enzyme telomerase, which copies a short template sequence within its own RNA moiety, thus helping to solve the “end-replication problem”, in which information is lost at the ends of chromosomes with each DNA replication cycle. The basic mechanisms of telomere length, structure and function maintenance are conserved among eukaryotes. Studies in the yeast Saccharomyces cerevisiae have been instrumental in deciphering the basic aspects of telomere biology. In the last decade, technical advances, such as the availability of mutant collections, have allowed carrying out systematic genome-wide screens for mutants affecting various aspects of telomere biology. In this review we summarize these efforts, and the insights that this Systems Biology approach has produced so far.

  11. Genome-Wide Analysis of DNA Methylation in Human Amnion

    Science.gov (United States)

    Kim, Jinsil; Pitlick, Mitchell M.; Christine, Paul J.; Schaefer, Amanda R.; Saleme, Cesar; Comas, Belén; Cosentino, Viviana; Gadow, Enrique; Murray, Jeffrey C.

    2013-01-01

    The amnion is a specialized tissue in contact with the amniotic fluid, which is in a constantly changing state. To investigate the importance of epigenetic events in this tissue in the physiology and pathophysiology of pregnancy, we performed genome-wide DNA methylation profiling of human amnion from term (with and without labor) and preterm deliveries. Using the Illumina Infinium HumanMethylation27 BeadChip, we identified genes exhibiting differential methylation associated with normal labor and preterm birth. Functional analysis of the differentially methylated genes revealed biologically relevant enriched gene sets. Bisulfite sequencing analysis of the promoter region of the oxytocin receptor (OXTR) gene detected two CpG dinucleotides showing significant methylation differences among the three groups of samples. Hypermethylation of the CpG island of the solute carrier family 30 member 3 (SLC30A3) gene in preterm amnion was confirmed by methylation-specific PCR. This work provides preliminary evidence that DNA methylation changes in the amnion may be at least partially involved in the physiological process of labor and the etiology of preterm birth and suggests that DNA methylation profiles, in combination with other biological data, may provide valuable insight into the mechanisms underlying normal and pathological pregnancies. PMID:23533356

  12. Genome-wide transcription analyses in rice using tiling microarrays

    DEFF Research Database (Denmark)

    Li, Lei; Wang, Xiangfeng; Stolc, Viktor;

    2006-01-01

    Sequencing and computational annotation revealed several features, including high gene numbers, unusual composition of the predicted genes and a large number of genes lacking homology to known genes, that distinguish the rice (Oryza sativa) genome from that of other fully sequenced model species....... We report here a full-genome transcription analysis of the indica rice subspecies using high-density oligonucleotide tiling microarrays. Our results provided expression data support for the existence of 35,970 (81.9%) annotated gene models and identified 5,464 unique transcribed intergenic regions...... activity between duplicated segments of the genome. Collectively, our results provide the first whole-genome transcription map useful for further understanding the rice genome. Udgivelsesdato: 2006-Jan...

  13. Genome-Wide Gene Expression Profile Analyses Identify CTTN as a Potential Prognostic Marker in Esophageal Cancer

    OpenAIRE

    2014-01-01

    Aim Esophageal squamous cell carcinoma (ESCC) is one of the most common fatal malignances of the digestive tract. Its prognosis is poor mainly due to the lack of reliable markers for early detection and prognostic prediction. Here we aim to identify the molecules involved in ESCC carcinogenesis and those as potential markers for prognosis and as new molecular therapeutic targets. Methods We performed genome-wide gene expression profile analyses of 10 primary ESCCs and their adjacent normal ti...

  14. Mosaic paternal genome-wide uniparental isodisomy with down syndrome.

    Science.gov (United States)

    Darcy, Diana; Atwal, Paldeep Singh; Angell, Cathy; Gadi, Inder; Wallerstein, Robert

    2015-10-01

    We report on a 6-month-old girl with two apparent cell lines; one with trisomy 21, and the other with paternal genome-wide uniparental isodisomy (GWUPiD), identified using single nucleotide polymorphism (SNP) based microarray and microsatellite analysis of polymorphic loci. The patient has Beckwith-Wiedemann syndrome (BWS) due to paternal uniparental disomy (UPD) at chromosome location 11p15 (UPD 11p15), which was confirmed through methylation analysis. Hyperinsulinemic hypoglycemia is present, which is associated with paternal UPD 11p15.5; and she likely has medullary nephrocalcinosis, which is associated with paternal UPD 20, although this was not biochemically confirmed. Angelman syndrome (AS) analysis was negative but this testing is not completely informative; she has no specific features of AS. Clinical features of this patient include: dysmorphic features consistent with trisomy 21, tetralogy of Fallot, hemihypertrophy, swirled skin hyperpigmentation, hepatoblastoma, and Wilms tumor. Her karyotype is 47,XX,+21[19]/46,XX[4], and microarray results suggest that the cell line with trisomy 21 is biparentally inherited and represents 40-50% of the genomic material in the tested specimen. The difference in the level of cytogenetically detected mosaicism versus the level of mosaicism observed via microarray analysis is likely caused by differences in the test methodologies. While a handful of cases of mosaic paternal GWUPiD have been reported, this patient is the only reported case that also involves trisomy 21. Other GWUPiD patients have presented with features associated with multiple imprinted regions, as does our patient. © 2015 Wiley Periodicals, Inc.

  15. Susceptibility to Chronic Mucus Hypersecretion, a Genome Wide Association Study

    Science.gov (United States)

    Dijkstra, Akkelies E.; Smolonska, Joanna; van den Berge, Maarten; Wijmenga, Ciska; Zanen, Pieter; Luinge, Marjan A.; Platteel, Mathieu; Lammers, Jan-Willem; Dahlback, Magnus; Tosh, Kerrie; Hiemstra, Pieter S.; Sterk, Peter J.; Spira, Avi; Vestbo, Jorgen; Nordestgaard, Borge G.; Benn, Marianne; Nielsen, Sune F.; Dahl, Morten; Verschuren, W. Monique; Picavet, H. Susan J.; Smit, Henriette A.; Owsijewitsch, Michael; Kauczor, Hans U.; de Koning, Harry J.; Nizankowska-Mogilnicka, Eva; Mejza, Filip; Nastalek, Pawel; van Diemen, Cleo C.; Cho, Michael H.; Silverman, Edwin K.; Crapo, James D.; Beaty, Terri H.; Lomas, David A.; Bakke, Per; Gulsvik, Amund; Bossé, Yohan; Obeidat, M. A.; Loth, Daan W.; Lahousse, Lies; Rivadeneira, Fernando; Uitterlinden, Andre G.; Hofman, Andre; Stricker, Bruno H.; Brusselle, Guy G.; van Duijn, Cornelia M.; Brouwer, Uilke; Koppelman, Gerard H.; Vonk, Judith M.; Nawijn, Martijn C.; Groen, Harry J. M.; Timens, Wim; Boezen, H. Marike; Postma, Dirkje S.

    2014-01-01

    Background Chronic mucus hypersecretion (CMH) is associated with an increased frequency of respiratory infections, excess lung function decline, and increased hospitalisation and mortality rates in the general population. It is associated with smoking, but it is unknown why only a minority of smokers develops CMH. A plausible explanation for this phenomenon is a predisposing genetic constitution. Therefore, we performed a genome wide association (GWA) study of CMH in Caucasian populations. Methods GWA analysis was performed in the NELSON-study using the Illumina 610 array, followed by replication and meta-analysis in 11 additional cohorts. In total 2,704 subjects with, and 7,624 subjects without CMH were included, all current or former heavy smokers (≥20 pack-years). Additional studies were performed to test the functional relevance of the most significant single nucleotide polymorphism (SNP). Results A strong association with CMH, consistent across all cohorts, was observed with rs6577641 (p = 4.25×10−6, OR = 1.17), located in intron 9 of the special AT-rich sequence-binding protein 1 locus (SATB1) on chromosome 3. The risk allele (G) was associated with higher mRNA expression of SATB1 (4.3×10−9) in lung tissue. Presence of CMH was associated with increased SATB1 mRNA expression in bronchial biopsies from COPD patients. SATB1 expression was induced during differentiation of primary human bronchial epithelial cells in culture. Conclusions Our findings, that SNP rs6577641 is associated with CMH in multiple cohorts and is a cis-eQTL for SATB1, together with our additional observation that SATB1 expression increases during epithelial differentiation provide suggestive evidence that SATB1 is a gene that affects CMH. PMID:24714607

  16. Genome-wide promoter methylome of small renal masses.

    Directory of Open Access Journals (Sweden)

    Ilsiya Ibragimova

    Full Text Available The majority of renal cell carcinoma (RCC is now incidentally detected and presents as small renal masses (SRMs defined as ≤ 4 cm in size. SRMs are heterogeneous comprising several histological types of RCC each with different biology and behavior, and benign tumors mainly oncocytoma. The varied prognosis of the different types of renal tumor has implications for management options. A key epigenetic alteration involved in the initiation and progression of cancer is aberrant methylation in the promoter region of a gene. The hypermethylation is associated with transcriptional repression and is an important mechanism of inactivation of tumor suppressor genes in neoplastic cells. We have determined the genome-wide promoter methylation profiles of 47 pT1a and 2 pT1b clear cell, papillary or chromophobe RCC, 25 benign renal oncocytoma ≤ 4 cm and 4 normal renal parenchyma specimens by Infinium HumanMethylation27 beadchip technology. We identify gene promoter hypermethylation signatures that distinguish clear cell and papillary from each other, from chromophobe and oncocytoma, and from normal renal cells. Pairwise comparisons revealed genes aberrantly hypermethylated in a tumor type but unmethylated in normal, and often unmethylated in the other renal tumor types. About 0.4% to 1.7% of genes comprised the promoter methylome in SRMs. The Infinium methylation score for representative genes was verified by gold standard technologies. The genes identified as differentially methylated implicate pathways involved in metabolism, tissue response to injury, epithelial to mesenchymal transition (EMT, signal transduction and G-protein coupled receptors (GPCRs, cancer, and stem cell regulation in the biology of RCC. Our findings contribute towards an improved understanding of the development of RCC, the different biology and behavior of histological types, and discovery of molecular subtypes. The differential methylation signatures may have utility in early

  17. Genome-wide examination of myoblast cell cycle withdrawal duringdifferentiation

    Energy Technology Data Exchange (ETDEWEB)

    Shen, Xun; Collier, John Michael; Hlaing, Myint; Zhang, Leanne; Delshad, Elizabeth H.; Bristow, James; Bernstein, Harold S.

    2002-12-02

    Skeletal and cardiac myocytes cease division within weeks of birth. Although skeletal muscle retains limited capacity for regeneration through recruitment of satellite cells, resident populations of adult myocardial stem cells have not been identified. Because cell cycle withdrawal accompanies myocyte differentiation, we hypothesized that C2C12 cells, a mouse myoblast cell line previously used to characterize myocyte differentiation, also would provide a model for studying cell cycle withdrawal during differentiation. C2C12 cells were differentiated in culture medium containing horse serum and harvested at various time points to characterize the expression profiles of known cell cycle and myogenic regulatory factors by immunoblot analysis. BrdU incorporation decreased dramatically in confluent cultures 48 hr after addition of horse serum, as cells started to form myotubes. This finding was preceded by up-regulation of MyoD, followed by myogenin, and activation of Bcl-2. Cyclin D1 was expressed in proliferating cultures and became undetectable in cultures containing 40 percent fused myotubes, as levels of p21(WAF1/Cip1) increased and alpha-actin became detectable. Because C2C12 myoblasts withdraw from the cell cycle during myocyte differentiation following a course that recapitulates this process in vivo, we performed a genome-wide screen to identify other gene products involved in this process. Using microarrays containing approximately 10,000 minimally redundant mouse sequences that map to the UniGene database of the National Center for Biotechnology Information, we compared gene expression profiles between proliferating, differentiating, and differentiated C2C12 cells and verified candidate genes demonstrating differential expression by RT-PCR. Cluster analysis of differentially expressed genes revealed groups of gene products involved in cell cycle withdrawal, muscle differentiation, and apoptosis. In addition, we identified several genes, including DDAH2 and Ly

  18. Susceptibility to chronic mucus hypersecretion, a genome wide association study.

    Directory of Open Access Journals (Sweden)

    Akkelies E Dijkstra

    Full Text Available BACKGROUND: Chronic mucus hypersecretion (CMH is associated with an increased frequency of respiratory infections, excess lung function decline, and increased hospitalisation and mortality rates in the general population. It is associated with smoking, but it is unknown why only a minority of smokers develops CMH. A plausible explanation for this phenomenon is a predisposing genetic constitution. Therefore, we performed a genome wide association (GWA study of CMH in Caucasian populations. METHODS: GWA analysis was performed in the NELSON-study using the Illumina 610 array, followed by replication and meta-analysis in 11 additional cohorts. In total 2,704 subjects with, and 7,624 subjects without CMH were included, all current or former heavy smokers (≥20 pack-years. Additional studies were performed to test the functional relevance of the most significant single nucleotide polymorphism (SNP. RESULTS: A strong association with CMH, consistent across all cohorts, was observed with rs6577641 (p = 4.25×10(-6, OR = 1.17, located in intron 9 of the special AT-rich sequence-binding protein 1 locus (SATB1 on chromosome 3. The risk allele (G was associated with higher mRNA expression of SATB1 (4.3×10(-9 in lung tissue. Presence of CMH was associated with increased SATB1 mRNA expression in bronchial biopsies from COPD patients. SATB1 expression was induced during differentiation of primary human bronchial epithelial cells in culture. CONCLUSIONS: Our findings, that SNP rs6577641 is associated with CMH in multiple cohorts and is a cis-eQTL for SATB1, together with our additional observation that SATB1 expression increases during epithelial differentiation provide suggestive evidence that SATB1 is a gene that affects CMH.

  19. Genephony: a knowledge management tool for genome-wide research

    Science.gov (United States)

    Nuzzo, Angelo; Riva, Alberto

    2009-01-01

    Background One of the consequences of the rapid and widespread adoption of high-throughput experimental technologies is an exponential increase of the amount of data produced by genome-wide experiments. Researchers increasingly need to handle very large volumes of heterogeneous data, including both the data generated by their own experiments and the data retrieved from publicly available repositories of genomic knowledge. Integration, exploration, manipulation and interpretation of data and information therefore need to become as automated as possible, since their scale and breadth are, in general, beyond the limits of what individual researchers and the basic data management tools in normal use can handle. This paper describes Genephony, a tool we are developing to address these challenges. Results We describe how Genephony can be used to manage large datesets of genomic information, integrating them with existing knowledge repositories. We illustrate its functionalities with an example of a complex annotation task, in which a set of SNPs coming from a genotyping experiment is annotated with genes known to be associated to a phenotype of interest. We show how, thanks to the modular architecture of Genephony and its user-friendly interface, this task can be performed in a few simple steps. Conclusion Genephony is an online tool for the manipulation of large datasets of genomic information. It can be used as a browser for genomic data, as a high-throughput annotation tool, and as a knowledge discovery tool. It is designed to be easy to use, flexible and extensible. Its knowledge management engine provides fine-grained control over individual data elements, as well as efficient operations on large datasets. PMID:19728881

  20. Genome-Wide Association Study of Schizophrenia in Japanese Population

    Science.gov (United States)

    Yamada, Kazuo; Iwayama, Yoshimi; Hattori, Eiji; Iwamoto, Kazuya; Toyota, Tomoko; Ohnishi, Tetsuo; Ohba, Hisako; Maekawa, Motoko; Kato, Tadafumi; Yoshikawa, Takeo

    2011-01-01

    Schizophrenia is a devastating neuropsychiatric disorder with genetically complex traits. Genetic variants should explain a considerable portion of the risk for schizophrenia, and genome-wide association study (GWAS) is a potentially powerful tool for identifying the risk variants that underlie the disease. Here, we report the results of a three-stage analysis of three independent cohorts consisting of a total of 2,535 samples from Japanese and Chinese populations for searching schizophrenia susceptibility genes using a GWAS approach. Firstly, we examined 115,770 single nucleotide polymorphisms (SNPs) in 120 patient-parents trio samples from Japanese schizophrenia pedigrees. In stage II, we evaluated 1,632 SNPs (1,159 SNPs of p<0.01 and 473 SNPs of p<0.05 that located in previously reported linkage regions). The second sample consisted of 1,012 case-control samples of Japanese origin. The most significant p value was obtained for the SNP in the ELAVL2 [(embryonic lethal, abnormal vision, Drosophila)-like 2] gene located on 9p21.3 (p = 0.00087). In stage III, we scrutinized the ELAVL2 gene by genotyping gene-centric tagSNPs in the third sample set of 293 family samples (1,163 individuals) of Chinese descent and the SNP in the gene showed a nominal association with schizophrenia in Chinese population (p = 0.026). The current data in Asian population would be helpful for deciphering ethnic diversity of schizophrenia etiology. PMID:21674006

  1. Genome-wide survey for biologically functional pseudogenes.

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    Orjan Svensson

    2006-05-01

    Full Text Available According to current estimates there exist about 20,000 pseudogenes in a mammalian genome. The vast majority of these are disabled and nonfunctional copies of protein-coding genes which, therefore, evolve neutrally. Recent findings that a Makorin1 pseudogene, residing on mouse Chromosome 5, is, indeed, in vivo vital and also evolutionarily preserved, encouraged us to conduct a genome-wide survey for other functional pseudogenes in human, mouse, and chimpanzee. We identify to our knowledge the first examples of conserved pseudogenes common to human and mouse, originating from one duplication predating the human-mouse species split and having evolved as pseudogenes since the species split. Functionality is one possible way to explain the apparently contradictory properties of such pseudogene pairs, i.e., high conservation and ancient origin. The hypothesis of functionality is tested by comparing expression evidence and synteny of the candidates with proper test sets. The tests suggest potential biological function. Our candidate set includes a small set of long-lived pseudogenes whose unknown potential function is retained since before the human-mouse species split, and also a larger group of primate-specific ones found from human-chimpanzee searches. Two processed sequences are notable, their conservation since the human-mouse split being as high as most protein-coding genes; one is derived from the protein Ataxin 7-like 3 (ATX7NL3, and one from the Spinocerebellar ataxia type 1 protein (ATX1. Our approach is comparative and can be applied to any pair of species. It is implemented by a semi-automated pipeline based on cross-species BLAST comparisons and maximum-likelihood phylogeny estimations. To separate pseudogenes from protein-coding genes, we use standard methods, utilizing in-frame disablements, as well as a probabilistic filter based on Ka/Ks ratios.

  2. Genome-wide identification of direct HBx genomic targets

    KAUST Repository

    Guerrieri, Francesca

    2017-02-17

    Background The Hepatitis B Virus (HBV) HBx regulatory protein is required for HBV replication and involved in HBV-related carcinogenesis. HBx interacts with chromatin modifying enzymes and transcription factors to modulate histone post-translational modifications and to regulate viral cccDNA transcription and cellular gene expression. Aiming to identify genes and non-coding RNAs (ncRNAs) directly targeted by HBx, we performed a chromatin immunoprecipitation sequencing (ChIP-Seq) to analyse HBV recruitment on host cell chromatin in cells replicating HBV. Results ChIP-Seq high throughput sequencing of HBx-bound fragments was used to obtain a high-resolution, unbiased, mapping of HBx binding sites across the genome in HBV replicating cells. Protein-coding genes and ncRNAs involved in cell metabolism, chromatin dynamics and cancer were enriched among HBx targets together with genes/ncRNAs known to modulate HBV replication. The direct transcriptional activation of genes/miRNAs that potentiate endocytosis (Ras-related in brain (RAB) GTPase family) and autophagy (autophagy related (ATG) genes, beclin-1, miR-33a) and the transcriptional repression of microRNAs (miR-138, miR-224, miR-576, miR-596) that directly target the HBV pgRNA and would inhibit HBV replication, contribute to HBx-mediated increase of HBV replication. Conclusions Our ChIP-Seq analysis of HBx genome wide chromatin recruitment defined the repertoire of genes and ncRNAs directly targeted by HBx and led to the identification of new mechanisms by which HBx positively regulates cccDNA transcription and HBV replication.

  3. Genome-wide methylation analyses in glioblastoma multiforme.

    Directory of Open Access Journals (Sweden)

    Rose K Lai

    Full Text Available Few studies had investigated genome-wide methylation in glioblastoma multiforme (GBM. Our goals were to study differential methylation across the genome in gene promoters using an array-based method, as well as repetitive elements using surrogate global methylation markers. The discovery sample set for this study consisted of 54 GBM from Columbia University and Case Western Reserve University, and 24 brain controls from the New York Brain Bank. We assembled a validation dataset using methylation data of 162 TCGA GBM and 140 brain controls from dbGAP. HumanMethylation27 Analysis Bead-Chips (Illumina were used to interrogate 26,486 informative CpG sites in both the discovery and validation datasets. Global methylation levels were assessed by analysis of L1 retrotransposon (LINE1, 5 methyl-deoxycytidine (5m-dC and 5 hydroxylmethyl-deoxycytidine (5hm-dC in the discovery dataset. We validated a total of 1548 CpG sites (1307 genes that were differentially methylated in GBM compared to controls. There were more than twice as many hypomethylated genes as hypermethylated ones. Both the discovery and validation datasets found 5 tumor methylation classes. Pathway analyses showed that the top ten pathways in hypomethylated genes were all related to functions of innate and acquired immunities. Among hypermethylated pathways, transcriptional regulatory network in embryonic stem cells was the most significant. In the study of global methylation markers, 5m-dC level was the best discriminant among methylation classes, whereas in survival analyses, high level of LINE1 methylation was an independent, favorable prognostic factor in the discovery dataset. Based on a pathway approach, hypermethylation in genes that control stem cell differentiation were significant, poor prognostic factors of overall survival in both the discovery and validation datasets. Approaches that targeted these methylated genes may be a future therapeutic goal.

  4. Genome-Wide Associations of Gene Expression Variation in Humans.

    Directory of Open Access Journals (Sweden)

    2005-12-01

    Full Text Available The exploration of quantitative variation in human populations has become one of the major priorities for medical genetics. The successful identification of variants that contribute to complex traits is highly dependent on reliable assays and genetic maps. We have performed a genome-wide quantitative trait analysis of 630 genes in 60 unrelated Utah residents with ancestry from Northern and Western Europe using the publicly available phase I data of the International HapMap project. The genes are located in regions of the human genome with elevated functional annotation and disease interest including the ENCODE regions spanning 1% of the genome, Chromosome 21 and Chromosome 20q12-13.2. We apply three different methods of multiple test correction, including Bonferroni, false discovery rate, and permutations. For the 374 expressed genes, we find many regions with statistically significant association of single nucleotide polymorphisms (SNPs with expression variation in lymphoblastoid cell lines after correcting for multiple tests. Based on our analyses, the signal proximal (cis- to the genes of interest is more abundant and more stable than distal and trans across statistical methodologies. Our results suggest that regulatory polymorphism is widespread in the human genome and show that the 5-kb (phase I HapMap has sufficient density to enable linkage disequilibrium mapping in humans. Such studies will significantly enhance our ability to annotate the non-coding part of the genome and interpret functional variation. In addition, we demonstrate that the HapMap cell lines themselves may serve as a useful resource for quantitative measurements at the cellular level.

  5. Genome-wide associations of gene expression variation in humans.

    Directory of Open Access Journals (Sweden)

    Barbara E Stranger

    2005-12-01

    Full Text Available The exploration of quantitative variation in human populations has become one of the major priorities for medical genetics. The successful identification of variants that contribute to complex traits is highly dependent on reliable assays and genetic maps. We have performed a genome-wide quantitative trait analysis of 630 genes in 60 unrelated Utah residents with ancestry from Northern and Western Europe using the publicly available phase I data of the International HapMap project. The genes are located in regions of the human genome with elevated functional annotation and disease interest including the ENCODE regions spanning 1% of the genome, Chromosome 21 and Chromosome 20q12-13.2. We apply three different methods of multiple test correction, including Bonferroni, false discovery rate, and permutations. For the 374 expressed genes, we find many regions with statistically significant association of single nucleotide polymorphisms (SNPs with expression variation in lymphoblastoid cell lines after correcting for multiple tests. Based on our analyses, the signal proximal (cis- to the genes of interest is more abundant and more stable than distal and trans across statistical methodologies. Our results suggest that regulatory polymorphism is widespread in the human genome and show that the 5-kb (phase I HapMap has sufficient density to enable linkage disequilibrium mapping in humans. Such studies will significantly enhance our ability to annotate the non-coding part of the genome and interpret functional variation. In addition, we demonstrate that the HapMap cell lines themselves may serve as a useful resource for quantitative measurements at the cellular level.

  6. Genome-wide signatures of convergent evolution in echolocating mammals.

    Science.gov (United States)

    Parker, Joe; Tsagkogeorga, Georgia; Cotton, James A; Liu, Yuan; Provero, Paolo; Stupka, Elia; Rossiter, Stephen J

    2013-10-10

    Evolution is typically thought to proceed through divergence of genes, proteins and ultimately phenotypes. However, similar traits might also evolve convergently in unrelated taxa owing to similar selection pressures. Adaptive phenotypic convergence is widespread in nature, and recent results from several genes have suggested that this phenomenon is powerful enough to also drive recurrent evolution at the sequence level. Where homoplasious substitutions do occur these have long been considered the result of neutral processes. However, recent studies have demonstrated that adaptive convergent sequence evolution can be detected in vertebrates using statistical methods that model parallel evolution, although the extent to which sequence convergence between genera occurs across genomes is unknown. Here we analyse genomic sequence data in mammals that have independently evolved echolocation and show that convergence is not a rare process restricted to several loci but is instead widespread, continuously distributed and commonly driven by natural selection acting on a small number of sites per locus. Systematic analyses of convergent sequence evolution in 805,053 amino acids within 2,326 orthologous coding gene sequences compared across 22 mammals (including four newly sequenced bat genomes) revealed signatures consistent with convergence in nearly 200 loci. Strong and significant support for convergence among bats and the bottlenose dolphin was seen in numerous genes linked to hearing or deafness, consistent with an involvement in echolocation. Unexpectedly, we also found convergence in many genes linked to vision: the convergent signal of many sensory genes was robustly correlated with the strength of natural selection. This first attempt to detect genome-wide convergent sequence evolution across divergent taxa reveals the phenomenon to be much more pervasive than previously recognized.

  7. Genome-wide association study of schizophrenia in Japanese population.

    Directory of Open Access Journals (Sweden)

    Kazuo Yamada

    Full Text Available Schizophrenia is a devastating neuropsychiatric disorder with genetically complex traits. Genetic variants should explain a considerable portion of the risk for schizophrenia, and genome-wide association study (GWAS is a potentially powerful tool for identifying the risk variants that underlie the disease. Here, we report the results of a three-stage analysis of three independent cohorts consisting of a total of 2,535 samples from Japanese and Chinese populations for searching schizophrenia susceptibility genes using a GWAS approach. Firstly, we examined 115,770 single nucleotide polymorphisms (SNPs in 120 patient-parents trio samples from Japanese schizophrenia pedigrees. In stage II, we evaluated 1,632 SNPs (1,159 SNPs of p<0.01 and 473 SNPs of p<0.05 that located in previously reported linkage regions. The second sample consisted of 1,012 case-control samples of Japanese origin. The most significant p value was obtained for the SNP in the ELAVL2 [(embryonic lethal, abnormal vision, Drosophila-like 2] gene located on 9p21.3 (p = 0.00087. In stage III, we scrutinized the ELAVL2 gene by genotyping gene-centric tagSNPs in the third sample set of 293 family samples (1,163 individuals of Chinese descent and the SNP in the gene showed a nominal association with schizophrenia in Chinese population (p = 0.026. The current data in Asian population would be helpful for deciphering ethnic diversity of schizophrenia etiology.

  8. Identification of neural outgrowth genes using genome-wide RNAi.

    Directory of Open Access Journals (Sweden)

    Katharine J Sepp

    2008-07-01

    Full Text Available While genetic screens have identified many genes essential for neurite outgrowth, they have been limited in their ability to identify neural genes that also have earlier critical roles in the gastrula, or neural genes for which maternally contributed RNA compensates for gene mutations in the zygote. To address this, we developed methods to screen the Drosophila genome using RNA-interference (RNAi on primary neural cells and present the results of the first full-genome RNAi screen in neurons. We used live-cell imaging and quantitative image analysis to characterize the morphological phenotypes of fluorescently labelled primary neurons and glia in response to RNAi-mediated gene knockdown. From the full genome screen, we focused our analysis on 104 evolutionarily conserved genes that when downregulated by RNAi, have morphological defects such as reduced axon extension, excessive branching, loss of fasciculation, and blebbing. To assist in the phenotypic analysis of the large data sets, we generated image analysis algorithms that could assess the statistical significance of the mutant phenotypes. The algorithms were essential for the analysis of the thousands of images generated by the screening process and will become a valuable tool for future genome-wide screens in primary neurons. Our analysis revealed unexpected, essential roles in neurite outgrowth for genes representing a wide range of functional categories including signalling molecules, enzymes, channels, receptors, and cytoskeletal proteins. We also found that genes known to be involved in protein and vesicle trafficking showed similar RNAi phenotypes. We confirmed phenotypes of the protein trafficking genes Sec61alpha and Ran GTPase using Drosophila embryo and mouse embryonic cerebral cortical neurons, respectively. Collectively, our results showed that RNAi phenotypes in primary neural culture can parallel in vivo phenotypes, and the screening technique can be used to identify many new

  9. Genome-Wide Association Mapping for Intelligence in Military Working Dogs: Development of Advanced Classification Algorithm for Genome-Wide Single Nucleotide Polymorphism (SNP) Data Analysis

    Science.gov (United States)

    2011-04-01

    al. (2007) “Efficient mapping of mendelian traits in dogs through genome-wide association.” Nat Genet 39:1321-1328. 12 Distribution A...collected data to genetically map superior intelligence in the military working dog. A behavioral testing regimen was developed by canine cognitive expert Dr...TERMS Military working dog genome-wide association study genetic marker intelligence 16

  10. Discovering Genome-Wide Tag SNPs Based on the Mutual Information of the Variants

    Science.gov (United States)

    Elmas, Abdulkadir; Ou Yang, Tai-Hsien; Wang, Xiaodong

    2016-01-01

    Exploring linkage disequilibrium (LD) patterns among the single nucleotide polymorphism (SNP) sites can improve the accuracy and cost-effectiveness of genomic association studies, whereby representative (tag) SNPs are identified to sufficiently represent the genomic diversity in populations. There has been considerable amount of effort in developing efficient algorithms to select tag SNPs from the growing large-scale data sets. Methods using the classical pairwise-LD and multi-locus LD measures have been proposed that aim to reduce the computational complexity and to increase the accuracy, respectively. The present work solves the tag SNP selection problem by efficiently balancing the computational complexity and accuracy, and improves the coverage in genomic diversity in a cost-effective manner. The employed algorithm makes use of mutual information to explore the multi-locus association between SNPs and can handle different data types and conditions. Experiments with benchmark HapMap data sets show comparable or better performance against the state-of-the-art algorithms. In particular, as a novel application, the genome-wide SNP tagging is performed in the 1000 Genomes Project data sets, and produced a well-annotated database of tagging variants that capture the common genotype diversity in 2,504 samples from 26 human populations. Compared to conventional methods, the algorithm requires as input only the genotype (or haplotype) sequences, can scale up to genome-wide analyses, and produces accurate solutions with more information-rich output, providing an improved platform for researchers towards the subsequent association studies. PMID:27992465

  11. Genome-wide analysis of potential cross-reactive endogenous allergens in rice (Oryza sativa L.

    Directory of Open Access Journals (Sweden)

    Fang Chao Zhu

    2015-01-01

    Full Text Available The proteins in the food are the source of common allergic components to certain patients. Current lists of plant endogenous allergens were based on the medical/clinical reports as well as laboratory results. Plant genome sequences made it possible to predict and characterize the genome-wide of putative endogenous allergens in rice (Oryza sativa L.. In this work, we identified and characterized 122 candidate rice allergens including the 22 allergens in present databases. Conserved domain analysis also revealed 37 domains among rice allergens including one novel domain (histidine kinase-, DNA gyrase B-, and HSP90-like ATPase, PF13589 adding to the allergen protein database. Phylogenetic analysis of the allergens revealed the diversity among the Prolamin superfamily and DnaK protein family, respectively. Additionally, some allergens proteins clustered on the rice chromosome might suggest the molecular function during the evolution.

  12. An Empirical Bayes Mixture Model for Effect Size Distributions in Genome-Wide Association Studies

    DEFF Research Database (Denmark)

    Thompson, Wesley K.; Wang, Yunpeng; Schork, Andrew J.

    2015-01-01

    Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power...... for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome...... of variance explained by genotyped SNPs, CD and SZ have a broadly dissimilar genetic architecture, due to differing mean effect size and proportion of non-null loci....

  13. Genome-Wide Analysis and Molecular Characterization of Heat Shock Transcription Factor Family in Glycine max

    Institute of Scientific and Technical Information of China (English)

    Eunsook Chung; Kyoung-Mi Kim; Jai-Heon Lee

    2013-01-01

    Heat shock transcription factors (Hsfs) play an essential role on the increased tolerance against heat stress by regulating the expression of heat-responsive genes.In this study,a genome-wide analysis was performed to identify all of the soybean (Glycine max) GmHsfgenes based on the latest soybean genome sequence.Chromosomal location,protein domain,motif organization,and phylogenetic relationships of 26 non-redundant GmHsf genes were analyzed compared with AtHsfs (Arabidopsis thaliana Hsfs).According to their structural features,the predicted members were divided into the previously defined classes A-C,as described for AtHsfs.Transcript levels and subcellular localization of five GmHsfs responsive to abiotic stresses were analyzed by real-time RT-PCR.These results provide a fundamental clue for understanding the complexity of the soybean GmHsfgene family and cloning the functional genes in future studies.

  14. Genome-wide analysis of the synonymous codon usage patterns in apple

    Institute of Scientific and Technical Information of China (English)

    LI Ning; SUN Mei-hong; JIANG Ze-sheng; SHU Huai-rui; ZHANG Shi-zhong

    2016-01-01

    Apple (Malus×domestica) has been proposed as an important woody plant and the major cultivated fruit trees in temperate regions. Apple whole genome sequencing has been completed, which provided an excelent opportunity for genome-wide analysis of the synonymous codon usage patterns. In this study, a multivariate bioinformatics analysis was performed to reveal the characteristics of synonymous codon usage and the main factors affecting codon bias in apple. The neutrality, correspondence, and correlation analyses were performed by CodonW and SPSS (Statistical Product and Service Solu-tions) programs, indicating that the apple genome codon usage patterns were affected by mutational pressure and selective constraint. Meanwhile, coding sequence length and the hydrophobicity of proteins could also inlfuence the codon usage patterns. In short, codon usage pattern analysis and determination of optimal codons has laid an important theoretical basis for genetic engineering, gene prediction and molecular evolution studies in apple.

  15. Genome wide association mapping for grain shape traits in indica rice.

    Science.gov (United States)

    Feng, Yue; Lu, Qing; Zhai, Rongrong; Zhang, Mengchen; Xu, Qun; Yang, Yaolong; Wang, Shan; Yuan, Xiaoping; Yu, Hanyong; Wang, Yiping; Wei, Xinghua

    2016-10-01

    Using genome-wide association mapping, 47 SNPs within 27 significant loci were identified for four grain shape traits, and 424 candidate genes were predicted from public database. Grain shape is a key determinant of grain yield and quality in rice (Oryza sativa L.). However, our knowledge of genes controlling rice grain shape remains limited. Genome-wide association mapping based on linkage disequilibrium (LD) has recently emerged as an effective approach for identifying genes or quantitative trait loci (QTL) underlying complex traits in plants. In this study, association mapping based on 5291 single nucleotide polymorphisms (SNPs) was conducted to identify significant loci associated with grain shape traits in a global collection of 469 diverse rice accessions. A total of 47 SNPs were located in 27 significant loci for four grain traits, and explained ~44.93-65.90 % of the phenotypic variation for each trait. In total, 424 candidate genes within a 200 kb extension region (±100 kb of each locus) of these loci were predicted. Of them, the cloned genes GS3 and qSW5 showed very strong effects on grain length and grain width in our study. Comparing with previously reported QTLs for grain shape traits, we found 11 novel loci, including 3, 3, 2 and 3 loci for grain length, grain width, grain length-width ratio and thousand grain weight, respectively. Validation of these new loci would be performed in the future studies. These results revealed that besides GS3 and qSW5, multiple novel loci and mechanisms were involved in determining rice grain shape. These findings provided valuable information for understanding of the genetic control of grain shape and molecular marker assistant selection (MAS) breeding in rice.

  16. Genome-wide identification of significant aberrations in cancer genome

    Directory of Open Access Journals (Sweden)

    Yuan Xiguo

    2012-07-01

    Full Text Available Abstract Background Somatic Copy Number Alterations (CNAs in human genomes are present in almost all human cancers. Systematic efforts to characterize such structural variants must effectively distinguish significant consensus events from random background aberrations. Here we introduce Significant Aberration in Cancer (SAIC, a new method for characterizing and assessing the statistical significance of recurrent CNA units. Three main features of SAIC include: (1 exploiting the intrinsic correlation among consecutive probes to assign a score to each CNA unit instead of single probes; (2 performing permutations on CNA units that preserve correlations inherent in the copy number data; and (3 iteratively detecting Significant Copy Number Aberrations (SCAs and estimating an unbiased null distribution by applying an SCA-exclusive permutation scheme. Results We test and compare the performance of SAIC against four peer methods (GISTIC, STAC, KC-SMART, CMDS on a large number of simulation datasets. Experimental results show that SAIC outperforms peer methods in terms of larger area under the Receiver Operating Characteristics curve and increased detection power. We then apply SAIC to analyze structural genomic aberrations acquired in four real cancer genome-wide copy number data sets (ovarian cancer, metastatic prostate cancer, lung adenocarcinoma, glioblastoma. When compared with previously reported results, SAIC successfully identifies most SCAs known to be of biological significance and associated with oncogenes (e.g., KRAS, CCNE1, and MYC or tumor suppressor genes (e.g., CDKN2A/B. Furthermore, SAIC identifies a number of novel SCAs in these copy number data that encompass tumor related genes and may warrant further studies. Conclusions Supported by a well-grounded theoretical framework, SAIC has been developed and used to identify SCAs in various cancer copy number data sets, providing useful information to study the landscape of cancer genomes

  17. A Genome-wide Pleiotropy Scan for Prostate Cancer Risk

    Science.gov (United States)

    Panagiotou, Orestis A; Travis, Ruth C; Campa, Daniele; Berndt, Sonja I.; Lindstrom, Sara; Kraft, Peter; Schumacher, Fredrick R.; Siddiq, Afshan; Papatheodorou, Stefania I.; Stanford, Janet L.; Albanes, Demetrius; Virtamo, Jarmo; Weinstein, Stephanie J.; Diver, W. Ryan; Gapstur, Susan M.; Stevens, Victoria L.; Boeing, Heiner; Bueno-de-Mesquita, H. Bas; Gurrea, Aurelio Barricarte; Kaaks, Rudolf; Khaw, Kay-Tee; Krogh, Vittorio; Overvad, Kim; Riboli, Elio; Trichopoulos, Dimitrios; Giovannucci, Edward; Stampfer, Meir; Haiman, Christopher; Henderson, Brian; Le Marchand, Loic; Gaziano, J. Michael; Hunter, DavidJ.; Koutros, Stella; Yeager, Meredith; Hoover, Robert N.; Chanock, Stephen J.; Wacholder, Sholom; Key, Timothy J.; Tsilidis, Konstantinos K

    2014-01-01

    Background No single-nucleotide polymorphisms (SNPs) specific for aggressive prostate cancer have been identified in genome-wide association studies (GWAS). Objective To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer. Design, setting, and participants SNPs implicated in any phenotype other than prostate cancer (p ≤ 10−7) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24 534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. Outcome measurements and statistical analysis Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated. Results and limitations A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p = 1.6 × 10-6), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95%CI 1.16–1.27; p = 3.22 × 10−18). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86–0.94; p = 2.5 × 10−6). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12,95% CI 1.06–1.19; p = 4.67 × 10−5); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL. Conclusions We did

  18. Genome-wide classification and expression analysis of MYB transcription factor families in rice and Arabidopsis

    Directory of Open Access Journals (Sweden)

    Katiyar Amit

    2012-10-01

    Full Text Available Abstract Background The MYB gene family comprises one of the richest groups of transcription factors in plants. Plant MYB proteins are characterized by a highly conserved MYB DNA-binding domain. MYB proteins are classified into four major groups namely, 1R-MYB, 2R-MYB, 3R-MYB and 4R-MYB based on the number and position of MYB repeats. MYB transcription factors are involved in plant development, secondary metabolism, hormone signal transduction, disease resistance and abiotic stress tolerance. A comparative analysis of MYB family genes in rice and Arabidopsis will help reveal the evolution and function of MYB genes in plants. Results A genome-wide analysis identified at least 155 and 197 MYB genes in rice and Arabidopsis, respectively. Gene structure analysis revealed that MYB family genes possess relatively more number of introns in the middle as compared with C- and N-terminal regions of the predicted genes. Intronless MYB-genes are highly conserved both in rice and Arabidopsis. MYB genes encoding R2R3 repeat MYB proteins retained conserved gene structure with three exons and two introns, whereas genes encoding R1R2R3 repeat containing proteins consist of six exons and five introns. The splicing pattern is similar among R1R2R3 MYB genes in Arabidopsis. In contrast, variation in splicing pattern was observed among R1R2R3 MYB members of rice. Consensus motif analysis of 1kb upstream region (5′ to translation initiation codon of MYB gene ORFs led to the identification of conserved and over-represented cis-motifs in both rice and Arabidopsis. Real-time quantitative RT-PCR analysis showed that several members of MYBs are up-regulated by various abiotic stresses both in rice and Arabidopsis. Conclusion A comprehensive genome-wide analysis of chromosomal distribution, tandem repeats and phylogenetic relationship of MYB family genes in rice and Arabidopsis suggested their evolution via duplication. Genome-wide comparative analysis of MYB genes and

  19. Dating the age of admixture via wavelet transform analysis of genome-wide data

    NARCIS (Netherlands)

    I. Pugach (Irina); R. Matveyev (Rostislav); A. Wollstein (Andreas); M.H. Kayser (Manfred); M. Stoneking (Mark)

    2011-01-01

    textabstractWe describe a PCA-based genome scan approach to analyze genome-wide admixture structure, and introduce wavelet transform analysis as a method for estimating the time of admixture. We test the wavelet transform method with simulations and apply it to genome-wide SNP data from eight admixe

  20. Case-Control Genome-Wide Association Study of Attention-Deficit/Hyperactivity Disorder

    Science.gov (United States)

    Neale, Benjamin M.; Medland, Sarah; Ripke, Stephan; Anney, Richard J. L.; Asherson, Philip; Buitelaar, Jan; Franke, Barbara; Gill, Michael; Kent, Lindsey; Holmans, Peter; Middleton, Frank; Thapar, Anita; Lesch, Klaus-Peter; Faraone, Stephen V.; Daly, Mark; Nguyen, Thuy Trang; Schafer, Helmut; Steinhausen, Hans-Christoph; Reif, Andreas; Renner, Tobias J.; Romanos, Marcel; Romanos, Jasmin; Warnke, Andreas; Walitza, Susanne; Freitag, Christine; Meyer, Jobst; Palmason, Haukur; Rothenberger, Aribert; Hawi, Ziarih; Sergeant, Joseph; Roeyers, Herbert; Mick, Eric; Biederman, Joseph

    2010-01-01

    Objective: Although twin and family studies have shown attention-deficit/hyperactivity disorder (ADHD) to be highly heritable, genetic variants influencing the trait at a genome-wide significant level have yet to be identified. Thus additional genome-wide association studies (GWAS) are needed. Method: We used case-control analyses of 896 cases…

  1. Family-Based Genome-Wide Association Scan of Attention-Deficit/Hyperactivity Disorder

    Science.gov (United States)

    Mick, Eric; Todorov, Alexandre; Smalley, Susan; Hu, Xiaolan; Loo, Sandra; Todd, Richard D.; Biederman, Joseph; Byrne, Deirdre; Dechairo, Bryan; Guiney, Allan; McCracken, James; McGough, James; Nelson, Stanley F.; Reiersen, Angela M.; Wilens, Timothy E.; Wozniak, Janet; Neale, Benjamin M.; Faraone, Stephen V.

    2010-01-01

    Objective: Genes likely play a substantial role in the etiology of attention-deficit/hyperactivity disorder (ADHD). However, the genetic architecture of the disorder is unknown, and prior genome-wide association studies (GWAS) have not identified a genome-wide significant association. We have conducted a third, independent, multisite GWAS of…

  2. Meta-Analysis of Genome-Wide Association Studies of Attention-Deficit/Hyperactivity Disorder

    Science.gov (United States)

    Neale, Benjamin M.; Medland, Sarah E.; Ripke, Stephan; Asherson, Philip; Franke, Barbara; Lesch, Klaus-Peter; Faraone, Stephen V.; Nguyen, Thuy Trang; Schafer, Helmut; Holmans, Peter; Daly, Mark; Steinhausen, Hans-Christoph; Freitag, Christine; Reif, Andreas; Renner, Tobias J.; Romanos, Marcel; Romanos, Jasmin; Walitza, Susanne; Warnke, Andreas; Meyer, Jobst; Palmason, Haukur; Buitelaar, Jan; Vasquez, Alejandro Arias; Lambregts-Rommelse, Nanda; Gill, Michael; Anney, Richard J. L.; Langely, Kate; O'Donovan, Michael; Williams, Nigel; Owen, Michael; Thapar, Anita; Kent, Lindsey; Sergeant, Joseph; Roeyers, Herbert; Mick, Eric; Biederman, Joseph; Doyle, Alysa; Smalley, Susan; Loo, Sandra; Hakonarson, Hakon; Elia, Josephine; Todorov, Alexandre; Miranda, Ana; Mulas, Fernando; Ebstein, Richard P.; Rothenberger, Aribert; Banaschewski, Tobias; Oades, Robert D.; Sonuga-Barke, Edmund; McGough, James; Nisenbaum, Laura; Middleton, Frank; Hu, Xiaolan; Nelson, Stan

    2010-01-01

    Objective: Although twin and family studies have shown attention-deficit/hyperactivity disorder (ADHD) to be highly heritable, genetic variants influencing the trait at a genome-wide significant level have yet to be identified. As prior genome-wide association studies (GWAS) have not yielded significant results, we conducted a meta-analysis of…

  3. Genome-wide screening and identification of antigens for rickettsial vaccine development

    Science.gov (United States)

    The capacity to identify immunogens for vaccine development by genome-wide screening has been markedly enhanced by the availability of complete microbial genome sequences coupled to rapid proteomic and bioinformatic analysis. Critical to this genome-wide screening is in vivo testing in the context o...

  4. A Genome-Wide Association Search for Type 2 Diabetes Genes in African Americans

    NARCIS (Netherlands)

    Palmer, Nicholette D.; McDonough, Caitrin W.; Hicks, Pamela J.; Roh, Bong H.; Wing, Maria R.; An, S. Sandy; Hester, Jessica M.; Cooke, Jessica N.; Bostrom, Meredith A.; Rudock, Megan E.; Talbert, Matthew E.; Lewis, Joshua P.; Ferrara, Assiamira; Lu, Lingyi; Ziegler, Julie T.; Sale, Michele M.; Divers, Jasmin; Shriner, Daniel; Adeyemo, Adebowale; Rotimi, Charles N.; Ng, Maggie C. Y.; Langefeld, Carl D.; Freedman, Barry I.; Bowden, Donald W.

    2012-01-01

    African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide A

  5. Genome-Wide Association Study and Linkage Analysis of the Healthy Aging Index

    DEFF Research Database (Denmark)

    Minster, Ryan L; Sanders, Jason L; Singh, Jatinder;

    2015-01-01

    BACKGROUND: The Healthy Aging Index (HAI) is a tool for measuring the extent of health and disease across multiple systems. METHODS: We conducted a genome-wide association study and a genome-wide linkage analysis to map quantitative trait loci associated with the HAI and a modified HAI weighted...

  6. Meta-analysis of genome-wide association studies of attention-deficit/hyperactivity disorder.

    NARCIS (Netherlands)

    Neale, B.M.; Medland, S.E.; Ripke, S.; Asherson, P.; Franke, B.; Lesch, K.P.; Faraone, S.V.; Nguyen, T.T.; Schafer, H.; Holmans, P.; Daly, M.; Steinhausen, H.C.; Freitag, C.; Reif, A.; Renner, T.J.; Romanos, M.; Romanos, J.; Walitza, S.; Warnke, A.; Meyer, J.; Palmason, H.; Buitelaar, J.K.; Vasquez, A.A.; Lambregts-Rommelse, N.N.J.; Gill, M.; Anney, R.J.; Langely, K.; O'Donovan, M.; Williams, N.; Owen, M.; Thapar, A.; Kent, L.; Sergeant, J.A.; Roeyers, H.; Mick, E.; Biederman, J.; Doyle, A.; Smalley, S.; Loo, S.; Hakonarson, H.; Elia, J.; Todorov, A.; Miranda, A.; Mulas, F.; Ebstein, R.P.; Rothenberger, A.; Banaschewski, T.; Oades, R.D.; Sonuga-Barke, E.; McGough, J.; Nisenbaum, L.; Middleton, F.; Hu, X.; Nelson, S.

    2010-01-01

    OBJECTIVE: Although twin and family studies have shown attention-deficit/hyperactivity disorder (ADHD) to be highly heritable, genetic variants influencing the trait at a genome-wide significant level have yet to be identified. As prior genome-wide association studies (GWAS) have not yielded signifi

  7. Meta-Analysis of Genome-Wide Association Studies of Attention-Deficit/Hyperactivity Disorder

    Science.gov (United States)

    Neale, Benjamin M.; Medland, Sarah E.; Ripke, Stephan; Asherson, Philip; Franke, Barbara; Lesch, Klaus-Peter; Faraone, Stephen V.; Nguyen, Thuy Trang; Schafer, Helmut; Holmans, Peter; Daly, Mark; Steinhausen, Hans-Christoph; Freitag, Christine; Reif, Andreas; Renner, Tobias J.; Romanos, Marcel; Romanos, Jasmin; Walitza, Susanne; Warnke, Andreas; Meyer, Jobst; Palmason, Haukur; Buitelaar, Jan; Vasquez, Alejandro Arias; Lambregts-Rommelse, Nanda; Gill, Michael; Anney, Richard J. L.; Langely, Kate; O'Donovan, Michael; Williams, Nigel; Owen, Michael; Thapar, Anita; Kent, Lindsey; Sergeant, Joseph; Roeyers, Herbert; Mick, Eric; Biederman, Joseph; Doyle, Alysa; Smalley, Susan; Loo, Sandra; Hakonarson, Hakon; Elia, Josephine; Todorov, Alexandre; Miranda, Ana; Mulas, Fernando; Ebstein, Richard P.; Rothenberger, Aribert; Banaschewski, Tobias; Oades, Robert D.; Sonuga-Barke, Edmund; McGough, James; Nisenbaum, Laura; Middleton, Frank; Hu, Xiaolan; Nelson, Stan

    2010-01-01

    Objective: Although twin and family studies have shown attention-deficit/hyperactivity disorder (ADHD) to be highly heritable, genetic variants influencing the trait at a genome-wide significant level have yet to be identified. As prior genome-wide association studies (GWAS) have not yielded significant results, we conducted a meta-analysis of…

  8. Stepwise Distributed Open Innovation Contests for Software Development: Acceleration of Genome-Wide Association Analysis.

    Science.gov (United States)

    Hill, Andrew; Loh, Po-Ru; Bharadwaj, Ragu B; Pons, Pascal; Shang, Jingbo; Guinan, Eva; Lakhani, Karim; Kilty, Iain; Jelinsky, Scott A

    2017-05-01

    The association of differing genotypes with disease-related phenotypic traits offers great potential to both help identify new therapeutic targets and support stratification of patients who would gain the greatest benefit from specific drug classes. Development of low-cost genotyping and sequencing has made collecting large-scale genotyping data routine in population and therapeutic intervention studies. In addition, a range of new technologies is being used to capture numerous new and complex phenotypic descriptors. As a result, genotype and phenotype datasets have grown exponentially. Genome-wide association studies associate genotypes and phenotypes using methods such as logistic regression. As existing tools for association analysis limit the efficiency by which value can be extracted from increasing volumes of data, there is a pressing need for new software tools that can accelerate association analyses on large genotype-phenotype datasets. Using open innovation (OI) and contest-based crowdsourcing, the logistic regression analysis in a leading, community-standard genetics software package (PLINK 1.07) was substantially accelerated. OI allowed us to do this in computational, numeric, and algorithmic approaches was identified that accelerated the logistic regression in PLINK 1.07 by 18- to 45-fold. Combining contest-derived logistic regression code with coarse-grained parallelization, multithreading, and associated changes to data initialization code further developed through distributed innovation, we achieved an end-to-end speedup of 591-fold for a data set size of 6678 subjects by 645 863 variants, compared to PLINK 1.07's logistic regression. This represents a reduction in run time from 4.8 hours to 29 seconds. Accelerated logistic regression code developed in this project has been incorporated into the PLINK2 project. Using iterative competition-based OI, we have developed a new, faster implementation of logistic regression for genome-wide association

  9. Genome-wide interaction-based association analysis identified multiple new susceptibility Loci for common diseases.

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2011-03-01

    Full Text Available Genome-wide interaction-based association (GWIBA analysis has the potential to identify novel susceptibility loci. These interaction effects could be missed with the prevailing approaches in genome-wide association studies (GWAS. However, no convincing loci have been discovered exclusively from GWIBA methods, and the intensive computation involved is a major barrier for application. Here, we developed a fast, multi-thread/parallel program named "pair-wise interaction-based association mapping" (PIAM for exhaustive two-locus searches. With this program, we performed a complete GWIBA analysis on seven diseases with stringent control for false positives, and we validated the results for three of these diseases. We identified one pair-wise interaction between a previously identified locus, C1orf106, and one new locus, TEC, that was specific for Crohn's disease, with a Bonferroni corrected P < 0.05 (P = 0.039. This interaction was replicated with a pair of proxy linked loci (P = 0.013 on an independent dataset. Five other interactions had corrected P < 0.5. We identified the allelic effect of a locus close to SLC7A13 for coronary artery disease. This was replicated with a linked locus on an independent dataset (P = 1.09 × 10⁻⁷. Through a local validation analysis that evaluated association signals, rather than locus-based associations, we found that several other regions showed association/interaction signals with nominal P < 0.05. In conclusion, this study demonstrated that the GWIBA approach was successful for identifying novel loci, and the results provide new insights into the genetic architecture of common diseases. In addition, our PIAM program was capable of handling very large GWAS datasets that are likely to be produced in the future.

  10. More heritability probably captured by psoriasis genome-wide association study in Han Chinese.

    Science.gov (United States)

    Jiang, Long; Liu, Lu; Cheng, Yuyan; Lin, Yan; Shen, Changbing; Zhu, Caihong; Yang, Sen; Yin, Xianyong; Zhang, Xuejun

    2015-11-15

    Missing heritability is a common problem in genome-wide association studies in complex diseases/traits. To quantify the unbiased heritability estimate, we applied the phenotype correlation-genotype correlation regression in psoriasis genome-wide association data in Han Chinese which comprises 1139 cases and 1132 controls. We estimated that 45.7% heritability of psoriasis in Han Chinese were captured by common variants (s.e.=12.5%), which reinforced that the majority of psoriasis heritability can be covered by common variants in genome-wide association data (68.2%). The results provided evidence that the heritability covered by psoriasis genome-wide genotyping data was probably underestimated in previous restricted maximum likelihood method. Our study highlights the broad role of common variants in the etiology of psoriasis and sheds light on the possibility to identify more common variants of small effect by increasing the sample size in psoriasis genome-wide association studies.

  11. Genome-wide identification of genes essential for the survival of Streptococcus pneumoniae in human saliva.

    Directory of Open Access Journals (Sweden)

    Lilly M Verhagen

    Full Text Available Since Streptococcus pneumoniae transmits through droplet spread, this respiratory tract pathogen may be able to survive in saliva. Here, we show that saliva supports survival of clinically relevant S. pneumoniae strains for more than 24 h in a capsule-independent manner. Moreover, saliva induced growth of S. pneumoniae in growth-permissive conditions, suggesting that S. pneumoniae is well adapted for uptake of nutrients from this bodily fluid. By using Tn-seq, a method for genome-wide negative selection screening, we identified 147 genes potentially required for growth and survival of S. pneumoniae in saliva, among which genes predicted to be involved in cell envelope biosynthesis, cell transport, amino acid metabolism, and stress response predominated. The Tn-seq findings were validated by testing a panel of directed gene deletion mutants for their ability to survive in saliva under two testing conditions: at room temperature without CO2, representing transmission, and at 37 °C with CO2, representing in-host carriage. These validation experiments confirmed that the plsX gene and the amiACDEF and aroDEBC operons, involved in respectively fatty acid metabolism, oligopeptide transport, and biosynthesis of aromatic amino acids play an important role in the growth and survival of S. pneumoniae in saliva at 37 °C. In conclusion, this study shows that S. pneumoniae is well-adapted for growth and survival in human saliva and provides a genome-wide list of genes potentially involved in adaptation. This notion supports earlier evidence that S. pneumoniae can use human saliva as a vector for transmission.

  12. Dry and wet approaches for genome-wide functional annotation of conventional and unconventional transcriptional activators

    Directory of Open Access Journals (Sweden)

    Elisabetta Levati

    2016-01-01

    Full Text Available Transcription factors (TFs are master gene products that regulate gene expression in response to a variety of stimuli. They interact with DNA in a sequence-specific manner using a variety of DNA-binding domain (DBD modules. This allows to properly position their second domain, called “effector domain”, to directly or indirectly recruit positively or negatively acting co-regulators including chromatin modifiers, thus modulating preinitiation complex formation as well as transcription elongation. At variance with the DBDs, which are comprised of well-defined and easily recognizable DNA binding motifs, effector domains are usually much less conserved and thus considerably more difficult to predict. Also not so easy to identify are the DNA-binding sites of TFs, especially on a genome-wide basis and in the case of overlapping binding regions. Another emerging issue, with many potential regulatory implications, is that of so-called “moonlighting” transcription factors, i.e., proteins with an annotated function unrelated to transcription and lacking any recognizable DBD or effector domain, that play a role in gene regulation as their second job. Starting from bioinformatic and experimental high-throughput tools for an unbiased, genome-wide identification and functional characterization of TFs (especially transcriptional activators, we describe both established (and usually well affordable as well as newly developed platforms for DNA-binding site identification. Selected combinations of these search tools, some of which rely on next-generation sequencing approaches, allow delineating the entire repertoire of TFs and unconventional regulators encoded by the any sequenced genome.

  13. A genome-wide methylation study on obesity: differential variability and differential methylation.

    Science.gov (United States)

    Xu, Xiaojing; Su, Shaoyong; Barnes, Vernon A; De Miguel, Carmen; Pollock, Jennifer; Ownby, Dennis; Shi, Hidong; Zhu, Haidong; Snieder, Harold; Wang, Xiaoling

    2013-05-01

    Besides differential methylation, DNA methylation variation has recently been proposed and demonstrated to be a potential contributing factor to cancer risk. Here we aim to examine whether differential variability in methylation is also an important feature of obesity, a typical non-malignant common complex disease. We analyzed genome-wide methylation profiles of over 470,000 CpGs in peripheral blood samples from 48 obese and 48 lean African-American youth aged 14-20 y old. A substantial number of differentially variable CpG sites (DVCs), using statistics based on variances, as well as a substantial number of differentially methylated CpG sites (DMCs), using statistics based on means, were identified. Similar to the findings in cancers, DVCs generally exhibited an outlier structure and were more variable in cases than in controls. By randomly splitting the current sample into a discovery and validation set, we observed that both the DVCs and DMCs identified from the first set could independently predict obesity status in the second set. Furthermore, both the genes harboring DMCs and the genes harboring DVCs showed significant enrichment of genes identified by genome-wide association studies on obesity and related diseases, such as hypertension, dyslipidemia, type 2 diabetes and certain types of cancers, supporting their roles in the etiology and pathogenesis of obesity. We generalized the recent finding on methylation variability in cancer research to obesity and demonstrated that differential variability is also an important feature of obesity-related methylation changes. Future studies on the epigenetics of obesity will benefit from both statistics based on means and statistics based on variances.

  14. Genome-Wide Identification of Genes Essential for the Survival of Streptococcus pneumoniae in Human Saliva

    Science.gov (United States)

    Verhagen, Lilly M.; de Jonge, Marien I.; Burghout, Peter; Schraa, Kiki; Spagnuolo, Lorenza; Mennens, Svenja; Eleveld, Marc J.; van der Gaast-de Jongh, Christa E.; Zomer, Aldert; Hermans, Peter W. M.; Bootsma, Hester J.

    2014-01-01

    Since Streptococcus pneumoniae transmits through droplet spread, this respiratory tract pathogen may be able to survive in saliva. Here, we show that saliva supports survival of clinically relevant S. pneumoniae strains for more than 24 h in a capsule-independent manner. Moreover, saliva induced growth of S. pneumoniae in growth-permissive conditions, suggesting that S. pneumoniae is well adapted for uptake of nutrients from this bodily fluid. By using Tn-seq, a method for genome-wide negative selection screening, we identified 147 genes potentially required for growth and survival of S. pneumoniae in saliva, among which genes predicted to be involved in cell envelope biosynthesis, cell transport, amino acid metabolism, and stress response predominated. The Tn-seq findings were validated by testing a panel of directed gene deletion mutants for their ability to survive in saliva under two testing conditions: at room temperature without CO2, representing transmission, and at 37°C with CO2, representing in-host carriage. These validation experiments confirmed that the plsX gene and the amiACDEF and aroDEBC operons, involved in respectively fatty acid metabolism, oligopeptide transport, and biosynthesis of aromatic amino acids play an important role in the growth and survival of S. pneumoniae in saliva at 37°C. In conclusion, this study shows that S. pneumoniae is well-adapted for growth and survival in human saliva and provides a genome-wide list of genes potentially involved in adaptation. This notion supports earlier evidence that S. pneumoniae can use human saliva as a vector for transmission. PMID:24586856

  15. A method for detecting epistasis in genome-wide studies using case-control multi-locus association analysis

    Directory of Open Access Journals (Sweden)

    Galan Jose

    2008-07-01

    Full Text Available Abstract Background The difficulty in elucidating the genetic basis of complex diseases roots in the many factors that can affect the development of a disease. Some of these genetic effects may interact in complex ways, proving undetectable by current single-locus methodology. Results We have developed an analysis tool called Hypothesis Free Clinical Cloning (HFCC to search for genome-wide epistasis in a case-control design. HFCC combines a relatively fast computing algorithm for genome-wide epistasis detection, with the flexibility to test a variety of different epistatic models in multi-locus combinations. HFCC has good power to detect multi-locus interactions simulated under a variety of genetic models and noise conditions. Most importantly, HFCC can accomplish exhaustive genome-wide epistasis search with large datasets as demonstrated with a 400,000 SNP set typed on a cohort of Parkinson's disease patients and controls. Conclusion With the current availability of genetic studies with large numbers of individuals and genetic markers, HFCC can have a great impact in the identification of epistatic effects that escape the standard single-locus association analyses.

  16. Digenome-seq: genome-wide profiling of CRISPR-Cas9 off-target effects in human cells.

    Science.gov (United States)

    Kim, Daesik; Bae, Sangsu; Park, Jeongbin; Kim, Eunji; Kim, Seokjoong; Yu, Hye Ryeong; Hwang, Jinha; Kim, Jong-Il; Kim, Jin-Soo

    2015-03-01

    Although RNA-guided genome editing via the CRISPR-Cas9 system is now widely used in biomedical research, genome-wide target specificities of Cas9 nucleases remain controversial. Here we present Digenome-seq, in vitro Cas9-digested whole-genome sequencing, to profile genome-wide Cas9 off-target effects in human cells. This in vitro digest yields sequence reads with the same 5' ends at cleavage sites that can be computationally identified. We validated off-target sites at which insertions or deletions were induced with frequencies below 0.1%, near the detection limit of targeted deep sequencing. We also showed that Cas9 nucleases can be highly specific, inducing off-target mutations at merely several, rather than thousands of, sites in the entire genome and that Cas9 off-target effects can be avoided by replacing 'promiscuous' single guide RNAs (sgRNAs) with modified sgRNAs. Digenome-seq is a robust, sensitive, unbiased and cost-effective method for profiling genome-wide off-target effects of programmable nucleases including Cas9.

  17. The challenges of genome-wide interaction studies: lessons to learn from the analysis of HDL blood levels.

    Science.gov (United States)

    van Leeuwen, Elisabeth M; Smouter, Françoise A S; Kam-Thong, Tony; Karbalai, Nazanin; Smith, Albert V; Harris, Tamara B; Launer, Lenore J; Sitlani, Colleen M; Li, Guo; Brody, Jennifer A; Bis, Joshua C; White, Charles C; Jaiswal, Alok; Oostra, Ben A; Hofman, Albert; Rivadeneira, Fernando; Uitterlinden, Andre G; Boerwinkle, Eric; Ballantyne, Christie M; Gudnason, Vilmundur; Psaty, Bruce M; Cupples, L Adrienne; Järvelin, Marjo-Riitta; Ripatti, Samuli; Isaacs, Aaron; Müller-Myhsok, Bertram; Karssen, Lennart C; van Duijn, Cornelia M

    2014-01-01

    Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-valueSPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS.

  18. Effects of environment, genetics and data analysis pitfalls in an esophageal cancer genome-wide association study.

    Directory of Open Access Journals (Sweden)

    Alexander Statnikov

    Full Text Available BACKGROUND: The development of new high-throughput genotyping technologies has allowed fast evaluation of single nucleotide polymorphisms (SNPs on a genome-wide scale. Several recent genome-wide association studies employing these technologies suggest that panels of SNPs can be a useful tool for predicting cancer susceptibility and discovery of potentially important new disease loci. METHODOLOGY/PRINCIPAL FINDINGS: In the present paper we undertake a careful examination of the relative significance of genetics, environmental factors, and biases of the data analysis protocol that was used in a previously published genome-wide association study. That prior study reported a nearly perfect discrimination of esophageal cancer patients and healthy controls on the basis of only genetic information. On the other hand, our results strongly suggest that SNPs in this dataset are not statistically linked to the phenotype, while several environmental factors and especially family history of esophageal cancer (a proxy to both environmental and genetic factors have only a modest association with the disease. CONCLUSIONS/SIGNIFICANCE: The main component of the previously claimed strong discriminatory signal is due to several data analysis pitfalls that in combination led to the strongly optimistic results. Such pitfalls are preventable and should be avoided in future studies since they create misleading conclusions and generate many false leads for subsequent research.

  19. Experimental evidence of genome-wide impact of ecological selection during early stages of speciation-with-gene-flow.

    Science.gov (United States)

    Egan, Scott P; Ragland, Gregory J; Assour, Lauren; Powell, Thomas H Q; Hood, Glen R; Emrich, Scott; Nosil, Patrik; Feder, Jeffrey L

    2015-08-01

    Theory predicts that speciation-with-gene-flow is more likely when the consequences of selection for population divergence transitions from mainly direct effects of selection acting on individual genes to a collective property of all selected genes in the genome. Thus, understanding the direct impacts of ecologically based selection, as well as the indirect effects due to correlations among loci, is critical to understanding speciation. Here, we measure the genome-wide impacts of host-associated selection between hawthorn and apple host races of Rhagoletis pomonella (Diptera: Tephritidae), a model for contemporary speciation-with-gene-flow. Allele frequency shifts of 32 455 SNPs induced in a selection experiment based on host phenology were genome wide and highly concordant with genetic divergence between co-occurring apple and hawthorn flies in nature. This striking genome-wide similarity between experimental and natural populations of R. pomonella underscores the importance of ecological selection at early stages of divergence and calls for further integration of studies of eco-evolutionary dynamics and genome divergence. © 2015 The Authors Ecology Letters published by John Wiley & Sons Ltd and CNRS.

  20. Web-based genome-wide association study identifies two novel loci and a substantial genetic component for Parkinson's disease.

    Directory of Open Access Journals (Sweden)

    Chuong B Do

    2011-06-01

    Full Text Available Although the causes of Parkinson's disease (PD are thought to be primarily environmental, recent studies suggest that a number of genes influence susceptibility. Using targeted case recruitment and online survey instruments, we conducted the largest case-control genome-wide association study (GWAS of PD based on a single collection of individuals to date (3,426 cases and 29,624 controls. We discovered two novel, genome-wide significant associations with PD-rs6812193 near SCARB2 (p = 7.6 × 10(-10, OR = 0.84 and rs11868035 near SREBF1/RAI1 (p = 5.6 × 10(-8, OR = 0.85-both replicated in an independent cohort. We also replicated 20 previously discovered genetic associations (including LRRK2, GBA, SNCA, MAPT, GAK, and the HLA region, providing support for our novel study design. Relying on a recently proposed method based on genome-wide sharing estimates between distantly related individuals, we estimated the heritability of PD to be at least 0.27. Finally, using sparse regression techniques, we constructed predictive models that account for 6%-7% of the total variance in liability and that suggest the presence of true associations just beyond genome-wide significance, as confirmed through both internal and external cross-validation. These results indicate a substantial, but by no means total, contribution of genetics underlying susceptibility to both early-onset and late-onset PD, suggesting that, despite the novel associations discovered here and elsewhere, the majority of the genetic component for Parkinson's disease remains to be discovered.

  1. Genome-Wide Association Mapping for Intelligence in Military Working Dogs: Canine Cohort, Canine Intelligence Assessment Regimen, Genome-Wide Single Nucleotide Polymorphism (SNP) Typing, and Unsupervised Classification Algorithm for Genome-Wide Association Data Analysis

    Science.gov (United States)

    2011-09-01

    Almasy, L, Blangero, J. (2009) Human QTL linkage mapping. Genetica 136:333-340. Amos, CI. (2007) Successful design and conduct of genome-wide...quantitative trait loci. Genetica 136:237-243. Skol AD, Scott LJ, Abecasis GR, Boehnke M. (2006) Joint analysis is more efficient than replication

  2. CMIP: a software package capable of reconstructing genome-wide regulatory networks using gene expression data.

    Science.gov (United States)

    Zheng, Guangyong; Xu, Yaochen; Zhang, Xiujun; Liu, Zhi-Ping; Wang, Zhuo; Chen, Luonan; Zhu, Xin-Guang

    2016-12-23

    A gene regulatory network (GRN) represents interactions of genes inside a cell or tissue, in which vertexes and edges stand for genes and their regulatory interactions respectively. Reconstruction of gene regulatory networks, in particular, genome-scale networks, is essential for comparative exploration of different species and mechanistic investigation of biological processes. Currently, most of network inference methods are computationally intensive, which are usually effective for small-scale tasks (e.g., networks with a few hundred genes), but are difficult to construct GRNs at genome-scale. Here, we present a software package for gene regulatory network reconstruction at a genomic level, in which gene interaction is measured by the conditional mutual information measurement using a parallel computing framework (so the package is named CMIP). The package is a greatly improved implementation of our previous PCA-CMI algorithm. In CMIP, we provide not only an automatic threshold determination method but also an effective parallel computing framework for network inference. Performance tests on benchmark datasets show that the accuracy of CMIP is comparable to most current network inference methods. Moreover, running tests on synthetic datasets demonstrate that CMIP can handle large datasets especially genome-wide datasets within an acceptable time period. In addition, successful application on a real genomic dataset confirms its practical applicability of the package. This new software package provides a powerful tool for genomic network reconstruction to biological community. The software can be accessed at http://www.picb.ac.cn/CMIP/ .

  3. Privacy-preserving genome-wide association studies on cloud environment using fully homomorphic encryption.

    Science.gov (United States)

    Lu, Wen-Jie; Yamada, Yoshiji; Sakuma, Jun

    2015-01-01

    Developed sequencing techniques are yielding large-scale genomic data at low cost. A genome-wide association study (GWAS) targeting genetic variations that are significantly associated with a particular disease offers great potential for medical improvement. However, subjects who volunteer their genomic data expose themselves to the risk of privacy invasion; these privacy concerns prevent efficient genomic data sharing. Our goal is to presents a cryptographic solution to this problem. To maintain the privacy of subjects, we propose encryption of all genotype and phenotype data. To allow the cloud to perform meaningful computation in relation to the encrypted data, we use a fully homomorphic encryption scheme. Noting that we can evaluate typical statistics for GWAS from a frequency table, our solution evaluates frequency tables with encrypted genomic and clinical data as input. We propose to use a packing technique for efficient evaluation of these frequency tables. Our solution supports evaluation of the D' measure of linkage disequilibrium, the Hardy-Weinberg Equilibrium, the χ2 test, etc. In this paper, we take χ2 test and linkage disequilibrium as examples and demonstrate how we can conduct these algorithms securely and efficiently in an outsourcing setting. We demonstrate with experimentation that secure outsourcing computation of one χ2 test with 10, 000 subjects requires about 35 ms and evaluation of one linkage disequilibrium with 10, 000 subjects requires about 80 ms. With appropriate encoding and packing technique, cryptographic solutions based on fully homomorphic encryption for secure computations of GWAS can be practical.

  4. A genome-wide association study of pulmonary function measures in the Framingham Heart Study.

    Directory of Open Access Journals (Sweden)

    Jemma B Wilk

    2009-03-01

    Full Text Available The ratio of forced expiratory volume in one second to forced vital capacity (FEV(1/FVC is a measure used to diagnose airflow obstruction and is highly heritable. We performed a genome-wide association study in 7,691 Framingham Heart Study participants to identify single-nucleotide polymorphisms (SNPs associated with the FEV(1/FVC ratio, analyzed as a percent of the predicted value. Identified SNPs were examined in an independent set of 835 Family Heart Study participants enriched for airflow obstruction. Four SNPs in tight linkage disequilibrium on chromosome 4q31 were associated with the percent predicted FEV(1/FVC ratio with p-values of genome-wide significance in the Framingham sample (best p-value = 3.6e-09. One of the four chromosome 4q31 SNPs (rs13147758; p-value 2.3e-08 in Framingham was genotyped in the Family Heart Study and produced evidence of association with the same phenotype, percent predicted FEV(1/FVC (p-value = 2.0e-04. The effect estimates for association in the Framingham and Family Heart studies were in the same direction, with the minor allele (G associated with higher FEV(1/FVC ratio levels. Results from the Family Heart Study demonstrated that the association extended to FEV(1 and dichotomous airflow obstruction phenotypes, particularly among smokers. The SNP rs13147758 was associated with the percent predicted FEV(1/FVC ratio in independent samples from the Framingham and Family Heart Studies producing a combined p-value of 8.3e-11, and this region of chromosome 4 around 145.68 megabases was associated with COPD in three additional populations reported in the accompanying manuscript. The associated SNPs do not lie within a gene transcript but are near the hedgehog-interacting protein (HHIP gene and several expressed sequence tags cloned from fetal lung. Though it is unclear what gene or regulatory effect explains the association, the region warrants further investigation.

  5. Understanding and Predicting Attitudes towards Computers.

    Science.gov (United States)

    Pancer, S. Mark; And Others

    1992-01-01

    The ability of the theory of reasoned action to predict computer-related attitudes and behavior was demonstrated through two studies: a questionnaire on computer behaviors and attitudes; and word processing training involving various levels of persuasive communication based on belief statements identified in the first study. (22 references) (MES)

  6. FunCoup 3.0: database of genome-wide functional coupling networks.

    Science.gov (United States)

    Schmitt, Thomas; Ogris, Christoph; Sonnhammer, Erik L L

    2014-01-01

    We present an update of the FunCoup database (http://FunCoup.sbc.su.se) of functional couplings, or functional associations, between genes and gene products. Identifying these functional couplings is an important step in the understanding of higher level mechanisms performed by complex cellular processes. FunCoup distinguishes between four classes of couplings: participation in the same signaling cascade, participation in the same metabolic process, co-membership in a protein complex and physical interaction. For each of these four classes, several types of experimental and statistical evidence are combined by Bayesian integration to predict genome-wide functional coupling networks. The FunCoup framework has been completely re-implemented to allow for more frequent future updates. It contains many improvements, such as a regularization procedure to automatically downweight redundant evidences and a novel method to incorporate phylogenetic profile similarity. Several datasets have been updated and new data have been added in FunCoup 3.0. Furthermore, we have developed a new Web site, which provides powerful tools to explore the predicted networks and to retrieve detailed information about the data underlying each prediction.

  7. Genome-Wide Arrays in Routine Diagnostics of Hematological Malignancies

    NARCIS (Netherlands)

    Simons, Annet; Sikkema-Raddatz, Birgit; de Leeuw, Nicole; Konrad, Nicole Claudia; Hastings, Rosalind J.; Schoumans, Jacqueline

    2012-01-01

    Over the last three decades, cytogenetic analysis of malignancies has become an integral part of disease evaluation and prediction of prognosis or responsiveness to therapy. In most diagnostic laboratories, conventional karyotyping, in conjunction with targeted fluorescence in situ hybridization ana

  8. Genome-wide arrays in routine diagnostics of hematological malignancies

    NARCIS (Netherlands)

    Simons, A.; Sikkema-Raddatz, B.; Leeuw, N. de; Konrad, N.C.; Hastings, R.J.; Schoumans, J.

    2012-01-01

    Over the last three decades, cytogenetic analysis of malignancies has become an integral part of disease evaluation and prediction of prognosis or responsiveness to therapy. In most diagnostic laboratories, conventional karyotyping, in conjunction with targeted fluorescence in situ hybridization ana

  9. Unidimensional nonnegative scaling for genome-wide linkage disequilibrium maps.

    Science.gov (United States)

    Liao, Haiyong; Ng, Michael; Fung, Eric; Sham, Pak C

    2008-01-01

    The main aim of this paper is to propose and develop a unidimensional nonnegative scaling model to construct Linkage Disequilibrium (LD) maps. The proposed constrained scaling model can be efficiently solved by transforming it to an unconstrained model. The method is implemented in PC Clusters at Hong Kong Baptist University. The LD maps are constructed for four populations from Hapmap data sets with chromosomes of several ten thousand Single Nucleotide Polymorphisms (SNPs). The similarities and dissimilarities of the LD maps are studied and analysed. Computational results are also reported to show the effectiveness of the method using parallel computation.

  10. Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque

    NARCIS (Netherlands)

    J.C. Bis (Joshua); M. Kavousi (Maryam); N. Franceschini (Nora); A.J. Isaacs (Aaron); G.R. Abecasis (Gonçalo); U. Schminke (Ulf); W.S. Post (Wendy S.); A.V. Smith (Albert Vernon); L.A. Cupples (Adrienne); H.S. Markus (Hugh S.); R. Schmidt (Reinhold); J.E. Huffman (Jennifer); T. Lehtimäki (Terho); J. Baumert (Jens); T. Münzel (Thomas); S.R. Heckbert (Susan); A. Dehghan (Abbas); K.E. North (Kari); B.A. Oostra (Ben); S. Bevan (Steve); E.M. Stoegerer (Eva Maria); C. Hayward (Caroline); O. Raitakari (Olli); C. Meisinger (Christa); A. Schillert (Arne); S. Sanna (Serena); H. Völzke (Henry); Y.C. Cheng (Yu Ching); B. Thorsson (Bolli); C.S. Fox (Caroline); K. Rice (Kenneth); F. Rivadeneira Ramirez (Fernando); V. Nambi (Vijay); E. Halperin (Eran); K. Petrovic (Katja); L. Peltonen (Leena Johanna); H.E. Wichmann (Heinz Erich); R.B. Schnabel (Renate); M. Dörr (Marcus); A. Parsa (Afshin); T. Aspelund (Thor); S. Demissie (Serkalem); S. Kathiresan (Sekar); M.P. Reilly (Muredach); K.D. Taylor (Kent); A.G. Uitterlinden (André); D.J. Couper (David); M. Sitzer (Matthias); M. Kähönen (Mika); T. Illig (Thomas); P.S. Wild (Philipp); M. Orrù (Marco); J. Lüdemann (Jan); A.R. Shuldiner (Alan); G. Eiriksdottir (Gudny); C.C. White (Charles); J.I. Rotter (Jerome); A. Hofman (Albert); J. Seissler (Jochen); T. Zeller (Tanja); G. Usala; F.D.J. Ernst (Florian); L.J. Launer (Lenore); R.B. D'Agostino (Ralph); D.H. O'Leary (Daniel H.); C. Ballantyne (Christie); J.P. Thiery (Joachim); A. Ziegler (Andreas); E. Lakatta (Edward); R.K. Chilukoti (Ravi Kumar); T.B. Harris (Tamara); P.A. Wolf (Philip); B.M. Psaty (Bruce); J.F. Polak (Joseph F.); X. Li (Xiaohui); W. Rathmann (Wolfgang); M. Uda (Manuela); E.A. Boerwinkle (Eric); N. Klopp (Norman); J.F. Wilson (James); J. Viikari (Jorma); W. Koenig (Wolfgang); S. Blankenberg (Stefan); A.B. Newman (Anne); J.C.M. Witteman (Jacqueline); G. Heiss (Gerardo); C.M. van Duijn (Cock); A. Scuteri (Angelo); G. Homuth (Georg); B.D. Mitchell (Braxton); V. Gudnason (Vilmundur); C.J. O'Donnell (Christopher)

    2011-01-01

    textabstractCarotid intima media thickness (cIMT) and plaque determined by ultrasonography are established measures of subclinical atherosclerosis that each predicts future cardiovascular disease events. We conducted a meta-analysis of genome-wide association data in 31,211 participants of European

  11. A novel algorithm for simultaneous SNP selection in high-dimensional genome-wide association studies

    Directory of Open Access Journals (Sweden)

    Zuber Verena

    2012-10-01

    Full Text Available Abstract Background Identification of causal SNPs in most genome wide association studies relies on approaches that consider each SNP individually. However, there is a strong correlation structure among SNPs that needs to be taken into account. Hence, increasingly modern computationally expensive regression methods are employed for SNP selection that consider all markers simultaneously and thus incorporate dependencies among SNPs. Results We develop a novel multivariate algorithm for large scale SNP selection using CAR score regression, a promising new approach for prioritizing biomarkers. Specifically, we propose a computationally efficient procedure for shrinkage estimation of CAR scores from high-dimensional data. Subsequently, we conduct a comprehensive comparison study including five advanced regression approaches (boosting, lasso, NEG, MCP, and CAR score and a univariate approach (marginal correlation to determine the effectiveness in finding true causal SNPs. Conclusions Simultaneous SNP selection is a challenging task. We demonstrate that our CAR score-based algorithm consistently outperforms all competing approaches, both uni- and multivariate, in terms of correctly recovered causal SNPs and SNP ranking. An R package implementing the approach as well as R code to reproduce the complete study presented here is available from http://strimmerlab.org/software/care/.

  12. A Probabilistic Genome-Wide Gene Reading Frame Sequence Model

    DEFF Research Database (Denmark)

    Have, Christian Theil; Mørk, Søren

    using the probabilistic logic programming language and machine learning system PRISM - a fast and efficient model prototyping environment, using bacterial gene finding performance as a benchmark of signal strength. The model is used to prune a set of gene predictions from an underlying gene finder...

  13. Genome-wide screens for expressed hypothetical proteins

    DEFF Research Database (Denmark)

    Madsen, Claus Desler; Durhuus, Jon Ambæk; Rasmussen, Lene Juel

    2012-01-01

    A hypothetical protein (HP) is defined as a protein that is predicted to be expressed from an open reading frame, but for which there is no experimental evidence of translation. HPs constitute a substantial fraction of proteomes of human as well as of other organisms. With the general belief...

  14. Bayesian variable selection in searching for additive and dominant effects in genome-wide data.

    Directory of Open Access Journals (Sweden)

    Tomi Peltola

    Full Text Available Although complex diseases and traits are thought to have multifactorial genetic basis, the common methods in genome-wide association analyses test each variant for association independent of the others. This computational simplification may lead to reduced power to identify variants with small effect sizes and requires correcting for multiple hypothesis tests with complex relationships. However, advances in computational methods and increase in computational resources are enabling the computation of models that adhere more closely to the theory of multifactorial inheritance. Here, a Bayesian variable selection and model averaging approach is formulated for searching for additive and dominant genetic effects. The approach considers simultaneously all available variants for inclusion as predictors in a linear genotype-phenotype mapping and averages over the uncertainty in the variable selection. This leads to naturally interpretable summary quantities on the significances of the variants and their contribution to the genetic basis of the studied trait. We first characterize the behavior of the approach in simulations. The results indicate a gain in the causal variant identification performance when additive and dominant variation are simulated, with a negligible loss of power in purely additive case. An application to the analysis of high- and low-density lipoprotein cholesterol levels in a dataset of 3895 Finns is then presented, demonstrating the feasibility of the approach at the current scale of single-nucleotide polymorphism data. We describe a Markov chain Monte Carlo algorithm for the computation and give suggestions on the specification of prior parameters using commonly available prior information. An open-source software implementing the method is available at http://www.lce.hut.fi/research/mm/bmagwa/ and https://github.com/to-mi/.

  15. Genome-wide protein-protein interactions and protein function exploration in cyanobacteria.

    Science.gov (United States)

    Lv, Qi; Ma, Weimin; Liu, Hui; Li, Jiang; Wang, Huan; Lu, Fang; Zhao, Chen; Shi, Tieliu

    2015-10-22

    Genome-wide network analysis is well implemented to study proteins of unknown function. Here, we effectively explored protein functions and the biological mechanism based on inferred high confident protein-protein interaction (PPI) network in cyanobacteria. We integrated data from seven different sources and predicted 1,997 PPIs, which were evaluated by experiments in molecular mechanism, text mining of literatures in proved direct/indirect evidences, and "interologs" in conservation. Combined the predicted PPIs with known PPIs, we obtained 4,715 no-redundant PPIs (involving 3,231 proteins covering over 90% of genome) to generate the PPI network. Based on the PPI network, terms in Gene ontology (GO) were assigned to function-unknown proteins. Functional modules were identified by dissecting the PPI network into sub-networks and analyzing pathway enrichment, with which we investigated novel function of underlying proteins in protein complexes and pathways. Examples of photosynthesis and DNA repair indicate that the network approach is a powerful tool in protein function analysis. Overall, this systems biology approach provides a new insight into posterior functional analysis of PPIs in cyanobacteria.

  16. Simultaneous genome-wide inference of physical, genetic, regulatory, and functional pathway components.

    Directory of Open Access Journals (Sweden)

    Christopher Y Park

    Full Text Available Biomolecular pathways are built from diverse types of pairwise interactions, ranging from physical protein-protein interactions and modifications to indirect regulatory relationships. One goal of systems biology is to bridge three aspects of this complexity: the growing body of high-throughput data assaying these interactions; the specific interactions in which individual genes participate; and the genome-wide patterns of interactions in a system of interest. Here, we describe methodology for simultaneously predicting specific types of biomolecular interactions using high-throughput genomic data. This results in a comprehensive compendium of whole-genome networks for yeast, derived from ∼3,500 experimental conditions and describing 30 interaction types, which range from general (e.g. physical or regulatory to specific (e.g. phosphorylation or transcriptional regulation. We used these networks to investigate molecular pathways in carbon metabolism and cellular transport, proposing a novel connection between glycogen breakdown and glucose utilization supported by recent publications. Additionally, 14 specific predicted interactions in DNA topological change and protein biosynthesis were experimentally validated. We analyzed the systems-level network features within all interactomes, verifying the presence of small-world properties and enrichment for recurring network motifs. This compendium of physical, synthetic, regulatory, and functional interaction networks has been made publicly available through an interactive web interface for investigators to utilize in future research at http://function.princeton.edu/bioweaver/.

  17. Exploiting SNP correlations within random forest for genome-wide association studies.

    Directory of Open Access Journals (Sweden)

    Vincent Botta

    Full Text Available The primary goal of genome-wide association studies (GWAS is to discover variants that could lead, in isolation or in combination, to a particular trait or disease. Standard approaches to GWAS, however, are usually based on univariate hypothesis tests and therefore can account neither for correlations due to linkage disequilibrium nor for combinations of several markers. To discover and leverage such potential multivariate interactions, we propose in this work an extension of the Random Forest algorithm tailored for structured GWAS data. In terms of risk prediction, we show empirically on several GWAS datasets that the proposed T-Trees method significantly outperforms both the original Random Forest algorithm and standard linear models, thereby suggesting the actual existence of multivariate non-linear effects due to the combinations of several SNPs. We also demonstrate that variable importances as derived from our method can help identify relevant loci. Finally, we highlight the strong impact that quality control procedures may have, both in terms of predictive power and loci identification. Variable importance results and T-Trees source code are all available at www.montefiore.ulg.ac.be/~botta/ttrees/ and github.com/0asa/TTree-source respectively.

  18. Genome-wide analyses of Epstein-Barr virus reveal conserved RNA structures and a novel stable intronic sequence RNA

    OpenAIRE

    2013-01-01

    Background Epstein-Barr virus (EBV) is a human herpesvirus implicated in cancer and autoimmune disorders. Little is known concerning the roles of RNA structure in this important human pathogen. This study provides the first comprehensive genome-wide survey of RNA and RNA structure in EBV. Results Novel EBV RNAs and RNA structures were identified by computational modeling and RNA-Seq analyses of EBV. Scans of the genomic sequences of four EBV strains (EBV-1, EBV-2, GD1, and GD2) and of the clo...

  19. Genome-wide association studies of female reproduction in tropically adapted beef cattle

    National Research Council Canada - National Science Library

    Hawken, R J; Zhang, Y D; Fortes, M R S; Collis, E; Barris, W C; Corbet, N J; Williams, P J; Fordyce, G; Holroyd, R G; Walkley, J R W; Barendse, W; Johnston, D J; Prayaga, K C; Tier, B; Reverter, A; Lehnert, S A

    2012-01-01

    .... To elucidate the genetics underlying reproduction in beef cattle, we performed a genome-wide association study using the bovine SNP50 chip in 2 tropically adapted beef cattle breeds, Brahman and Tropical Composite...

  20. Mammalian RNA polymerase II core promoters: insights from genome-wide studies

    DEFF Research Database (Denmark)

    Sandelin, Albin; Carninci, Piero; Lenhard, Boris

    2007-01-01

    The identification and characterization of mammalian core promoters and transcription start sites is a prerequisite to understanding how RNA polymerase II transcription is controlled. New experimental technologies have enabled genome-wide discovery and characterization of core promoters, revealin...

  1. Genome-wide association study of smoking initiation and current smoking

    DEFF Research Database (Denmark)

    Vink, Jacqueline M; Smit, August B; de Geus, Eco J C;

    2009-01-01

    For the identification of genes associated with smoking initiation and current smoking, genome-wide association analyses were carried out in 3497 subjects. Significant genes that replicated in three independent samples (n = 405, 5810, and 1648) were visualized into a biologically meaningful network......) and cell-adhesion molecules (e.g., CDH23). We conclude that a network-based genome-wide association approach can identify genes influencing smoking behavior....

  2. Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci

    OpenAIRE

    Stahl, Eli A; Raychaudhuri, Soumya; Remmers, Elaine F.; Xie, Gang; Eyre, Stephen; Thomson, Brian P.; Li, Yonghong; Kurreeman, Fina A. S.; Zhernakova, Alexandra; Hinks, Anne; Guiducci, Candace; Chen, Robert; Alfredsson, Lars; Amos, Christopher I.; Ardlie, Kristin G.

    2010-01-01

    To identify novel genetic risk factors for rheumatoid arthritis (RA), we conducted a genome-wide association study (GWAS) meta-analysis of 5,539 autoantibody positive RA cases and 20,169 controls of European descent, followed by replication in an independent set of 6,768 RA cases and 8,806 controls. Of 34 SNPs selected for replication, 7 novel RA risk alleles were identified at genome-wide significance (P

  3. A genome-wide 20 K citrus microarray for gene expression analysis

    OpenAIRE

    Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

    2008-01-01

    Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA...

  4. BioMet Toolbox: genome-wide analysis of metabolism

    OpenAIRE

    Cvijovic, M.; R. Olivares-Hernandez; Agren, R.; Dahr, N.; Vongsangnak, W.; Nookaew, I.; K. R. Patil; Nielsen, J.

    2010-01-01

    The rapid progress of molecular biology tools for directed genetic modifications, accurate quantitative experimental approaches, high-throughput measurements, together with development of genome sequencing has made the foundation for a new area of metabolic engineering that is driven by metabolic models. Systematic analysis of biological processes by means of modelling and simulations has made the identification of metabolic networks and prediction of metabolic capabilities under different co...

  5. Genome-wide association analysis of imputed rare variants: application to seven common complex diseases.

    Science.gov (United States)

    Mägi, Reedik; Asimit, Jennifer L; Day-Williams, Aaron G; Zeggini, Eleftheria; Morris, Andrew P

    2012-12-01

    Genome-wide association studies have been successful in identifying loci contributing effects to a range of complex human traits. The majority of reproducible associations within these loci are with common variants, each of modest effect, which together explain only a small proportion of heritability. It has been suggested that much of the unexplained genetic component of complex traits can thus be attributed to rare variation. However, genome-wide association study genotyping chips have been designed primarily to capture common variation, and thus are underpowered to detect the effects of rare variants. Nevertheless, we demonstrate here, by simulation, that imputation from an existing scaffold of genome-wide genotype data up to high-density reference panels has the potential to identify rare variant associations with complex traits, without the need for costly re-sequencing experiments. By application of this approach to genome-wide association studies of seven common complex diseases, imputed up to publicly available reference panels, we identify genome-wide significant evidence of rare variant association in PRDM10 with coronary artery disease and multiple genes in the major histocompatibility complex (MHC) with type 1 diabetes. The results of our analyses highlight that genome-wide association studies have the potential to offer an exciting opportunity for gene discovery through association with rare variants, conceivably leading to substantial advancements in our understanding of the genetic architecture underlying complex human traits.

  6. The relative value of operon predictions

    NARCIS (Netherlands)

    Brouwer, Rutger W. W.; Kuipers, Oscar P.; van Hijum, Sacha A. F. T.

    2008-01-01

    For most organisms, computational operon predictions are the only source of genome-wide operon information. Operon prediction methods described in literature are based on (a combination of) the following five criteria: (i) intergenic distance, (ii) conserved gene clusters, (iii) functional relation,

  7. Prediction of Radiation Fog by DNA Computing

    OpenAIRE

    Ray, Kumar Sankar; Mondal, Mandrita

    2015-01-01

    In this paper we propose a wet lab algorithm for prediction of radiation fog by DNA computing. The concept of DNA computing is essentially exploited for generating the classifier algorithm in the wet lab. The classifier is based on a new concept of similarity based fuzzy reasoning suitable for wet lab implementation. This new concept of similarity based fuzzy reasoning is different from conventional approach to fuzzy reasoning based on similarity measure and also replaces the logical aspect o...

  8. Genome-wide and expression analysis of protein phosphatase 2C in rice and Arabidopsis

    Directory of Open Access Journals (Sweden)

    Jakab Stephen

    2008-11-01

    Full Text Available Abstract Background The protein phosphatase 2Cs (PP2Cs from various organisms have been implicated to act as negative modulators of protein kinase pathways involved in diverse environmental stress responses and developmental processes. A genome-wide overview of the PP2C gene family in plants is not yet available. Results A comprehensive computational analysis identified 80 and 78 PP2C genes in Arabidopsis thaliana (AtPP2Cs and Oryza sativa (OsPP2Cs, respectively, which denotes the PP2C gene family as one of the largest families identified in plants. Phylogenic analysis divided PP2Cs in Arabidopsis and rice into 13 and 11 subfamilies, respectively, which are supported by the analyses of gene structures and protein motifs. Comparative analysis between the PP2C genes in Arabidopsis and rice identified common and lineage-specific subfamilies and potential 'gene birth-and-death' events. Gene duplication analysis reveals that whole genome and chromosomal segment duplications mainly contributed to the expansion of both OsPP2Cs and AtPP2Cs, but tandem or local duplication occurred less frequently in Arabidopsis than rice. Some protein motifs are widespread among the PP2C proteins, whereas some other motifs are specific to only one or two subfamilies. Expression pattern analysis suggests that 1 most PP2C genes play functional roles in multiple tissues in both species, 2 the induced expression of most genes in subfamily A by diverse stimuli indicates their primary role in stress tolerance, especially ABA response, and 3 the expression pattern of subfamily D members suggests that they may constitute positive regulators in ABA-mediated signaling pathways. The analyses of putative upstream regulatory elements by two approaches further support the functions of subfamily A in ABA signaling, and provide insights into the shared and different transcriptional regulation machineries in dicots and monocots. Conclusion This comparative genome-wide overview of the PP

  9. Genome-Wide Analysis of the Aquaporin Gene Family in Chickpea (Cicer arietinum L.).

    Science.gov (United States)

    Deokar, Amit A; Tar'an, Bunyamin

    2016-01-01

    Aquaporins (AQPs) are essential membrane proteins that play critical role in the transport of water and many other solutes across cell membranes. In this study, a comprehensive genome-wide analysis identified 40 AQP genes in chickpea (Cicer arietinum L.). A complete overview of the chickpea AQP (CaAQP) gene family is presented, including their chromosomal locations, gene structure, phylogeny, gene duplication, conserved functional motifs, gene expression, and conserved promoter motifs. To understand AQP's evolution, a comparative analysis of chickpea AQPs with AQP orthologs from soybean, Medicago, common bean, and Arabidopsis was performed. The chickpea AQP genes were found on all of the chickpea chromosomes, except chromosome 7, with a maximum of six genes on chromosome 6, and a minimum of one gene on chromosome 5. Gene duplication analysis indicated that the expansion of chickpea AQP gene family might have been due to segmental and tandem duplications. CaAQPs were grouped into four subfamilies including 15 NOD26-like intrinsic proteins (NIPs), 13 tonoplast intrinsic proteins (TIPs), eight plasma membrane intrinsic proteins (PIPs), and four small basic intrinsic proteins (SIPs) based on sequence similarities and phylogenetic position. Gene structure analysis revealed a highly conserved exon-intron pattern within CaAQP subfamilies supporting the CaAQP family classification. Functional prediction based on conserved Ar/R selectivity filters, Froger's residues, and specificity-determining positions suggested wide differences in substrate specificity among the subfamilies of CaAQPs. Expression analysis of the AQP genes indicated that some of the genes are tissue-specific, whereas few other AQP genes showed differential expression in response to biotic and abiotic stresses. Promoter profiling of CaAQP genes for conserved cis-acting regulatory elements revealed enrichment of cis-elements involved in circadian control, light response, defense and stress responsiveness

  10. Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data.

    Science.gov (United States)

    Wang, Joanne H; Pappas, Derek; De Jager, Philip L; Pelletier, Daniel; de Bakker, Paul Iw; Kappos, Ludwig; Polman, Chris H; Chibnik, Lori B; Hafler, David A; Matthews, Paul M; Hauser, Stephen L; Baranzini, Sergio E; Oksenberg, Jorge R

    2011-01-18

    Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant

  11. Genome-wide survey of allele-specific splicing in humans

    Directory of Open Access Journals (Sweden)

    Scheffler Konrad

    2008-06-01

    Full Text Available Abstract Background Accurate mRNA splicing depends on multiple regulatory signals encoded in the transcribed RNA sequence. Many examples of mutations within human splice regulatory regions that alter splicing qualitatively or quantitatively have been reported and allelic differences in mRNA splicing are likely to be a common and important source of phenotypic diversity at the molecular level, in addition to their contribution to genetic disease susceptibility. However, because the effect of a mutation on the efficiency of mRNA splicing is often difficult to predict, many mutations that cause disease through an effect on splicing are likely to remain undiscovered. Results We have combined a genome-wide scan for sequence polymorphisms likely to affect mRNA splicing with analysis of publicly available Expressed Sequence Tag (EST and exon array data. The genome-wide scan uses published tools and identified 30,977 SNPs located within donor and acceptor splice sites, branch points and exonic splicing enhancer elements. For 1,185 candidate splicing polymorphisms the difference in splicing between alternative alleles was corroborated by publicly available exon array data from 166 lymphoblastoid cell lines. We developed a novel probabilistic method to infer allele-specific splicing from EST data. The method uses SNPs and alternative mRNA isoforms mapped to EST sequences and models both regulated alternative splicing as well as allele-specific splicing. We have also estimated heritability of splicing and report that a greater proportion of genes show evidence of splicing heritability than show heritability of overall gene expression level. Our results provide an extensive resource that can be used to assess the possible effect on splicing of human polymorphisms in putative splice-regulatory sites. Conclusion We report a set of genes showing evidence of allele-specific splicing from an integrated analysis of genomic polymorphisms, EST data and exon array

  12. Software engineering the mixed model for genome-wide association studies on large samples.

    Science.gov (United States)

    Zhang, Zhiwu; Buckler, Edward S; Casstevens, Terry M; Bradbury, Peter J

    2009-11-01

    Mixed models improve the ability to detect phenotype-genotype associations in the presence of population stratification and multiple levels of relatedness in genome-wide association studies (GWAS), but for large data sets the resource consumption becomes impractical. At the same time, the sample size and number of markers used for GWAS is increasing dramatically, resulting in greater statistical power to detect those associations. The use of mixed models with increasingly large data sets depends on the availability of software for analyzing those models. While multiple software packages implement the mixed model method, no single package provides the best combination of fast computation, ability to handle large samples, flexible modeling and ease of use. Key elements of association analysis with mixed models are reviewed, including modeling phenotype-genotype associations using mixed models, population stratification, kinship and its estimation, variance component estimation, use of best linear unbiased predictors or residuals in place of raw phenotype, improving efficiency and software-user interaction. The available software packages are evaluated, and suggestions made for future software development.

  13. BioSMACK: a linux live CD for genome-wide association analyses.

    Science.gov (United States)

    Hong, Chang Bum; Kim, Young Jin; Moon, Sanghoon; Shin, Young-Ah; Go, Min Jin; Kim, Dong-Joon; Lee, Jong-Young; Cho, Yoon Shin

    2012-01-01

    Recent advances in high-throughput genotyping technologies have enabled us to conduct a genome-wide association study (GWAS) on a large cohort. However, analyzing millions of single nucleotide polymorphisms (SNPs) is still a difficult task for researchers conducting a GWAS. Several difficulties such as compatibilities and dependencies are often encountered by researchers using analytical tools, during the installation of software. This is a huge obstacle to any research institute without computing facilities and specialists. Therefore, a proper research environment is an urgent need for researchers working on GWAS. We developed BioSMACK to provide a research environment for GWAS that requires no configuration and is easy to use. BioSMACK is based on the Ubuntu Live CD that offers a complete Linux-based operating system environment without installation. Moreover, we provide users with a GWAS manual consisting of a series of guidelines for GWAS and useful examples. BioSMACK is freely available at http://ksnp.cdc. go.kr/biosmack.

  14. Pseudo-Seq: Genome-Wide Detection of Pseudouridine Modifications in RNA.

    Science.gov (United States)

    Carlile, Thomas M; Rojas-Duran, Maria F; Gilbert, Wendy V

    2015-01-01

    RNA molecules contain a variety of chemically diverse, posttranscriptionally modified bases. The most abundant modified base found in cellular RNAs, pseudouridine (Ψ), has recently been mapped to hundreds of sites in mRNAs, many of which are dynamically regulated. Though the pseudouridine landscape has been determined in only a few cell types and growth conditions, the enzymes responsible for mRNA pseudouridylation are universally conserved, suggesting many novel pseudouridylated sites remain to be discovered. Here, we present Pseudo-seq, a technique that allows the identification of sites of pseudouridylation genome-wide with single-nucleotide resolution. In this chapter, we provide a detailed description of Pseudo-seq. We include protocols for RNA isolation from Saccharomyces cerevisiae, Pseudo-seq library preparation, and data analysis, including descriptions of processing and mapping of sequencing reads, computational identification of sites of pseudouridylation, and assignment of sites to specific pseudouridine synthases. The approach presented here is readily adaptable to any cell or tissue type from which high-quality mRNA can be isolated. Identification of novel pseudouridylation sites is an important first step in elucidating the regulation and functions of these modifications.

  15. A variational Bayes algorithm for fast and accurate multiple locus genome-wide association analysis

    Directory of Open Access Journals (Sweden)

    Mezey Jason G

    2010-01-01

    Full Text Available Abstract Background The success achieved by genome-wide association (GWA studies in the identification of candidate loci for complex diseases has been accompanied by an inability to explain the bulk of heritability. Here, we describe the algorithm V-Bay, a variational Bayes algorithm for multiple locus GWA analysis, which is designed to identify weaker associations that may contribute to this missing heritability. Results V-Bay provides a novel solution to the computational scaling constraints of most multiple locus methods and can complete a simultaneous analysis of a million genetic markers in a few hours, when using a desktop. Using a range of simulated genetic and GWA experimental scenarios, we demonstrate that V-Bay is highly accurate, and reliably identifies associations that are too weak to be discovered by single-marker testing approaches. V-Bay can also outperform a multiple locus analysis method based on the lasso, which has similar scaling properties for large numbers of genetic markers. For demonstration purposes, we also use V-Bay to confirm associations with gene expression in cell lines derived from the Phase II individuals of HapMap. Conclusions V-Bay is a versatile, fast, and accurate multiple locus GWA analysis tool for the practitioner interested in identifying weaker associations without high false positive rates.

  16. Gowinda: unbiased analysis of gene set enrichment for genome-wide association studies.

    Science.gov (United States)

    Kofler, Robert; Schlötterer, Christian

    2012-08-01

    An analysis of gene set [e.g. Gene Ontology (GO)] enrichment assumes that all genes are sampled independently from each other with the same probability. These assumptions are violated in genome-wide association (GWA) studies since (i) longer genes typically have more single-nucleotide polymorphisms resulting in a higher probability of being sampled and (ii) overlapping genes are sampled in clusters. Herein, we introduce Gowinda, a software specifically designed to test for enrichment of gene sets in GWA studies. We show that GO tests on GWA data could result in a substantial number of false-positive GO terms. Permutation tests implemented in Gowinda eliminate these biases, but maintain sufficient power to detect enrichment of GO terms. Since sufficient resolution for large datasets requires millions of permutations, we use multi-threading to keep computation times reasonable. Gowinda is implemented in Java (v1.6) and freely available on http://code.google.com/p/gowinda/ christian.schloetterer@vetmeduni.ac.at Manual: http://code.google.com/p/gowinda/wiki/Manual. Test data and tutorial: http://code.google.com/p/gowinda/wiki/Tutorial. http://code.google.com/p/gowinda/wiki/VALIDATION.

  17. Genome-wide survey of ds exonization to enrich transcriptomes and proteomes in plants.

    Science.gov (United States)

    Liu, Li-Yu Daisy; Charng, Yuh-Chyang

    2012-01-01

    Insertion of transposable elements (TEs) into introns can lead to their activation as alternatively spliced cassette exons, an event called exonization which can enrich the complexity of transcriptomes and proteomes. Previously, we performed the first experimental assessment of TE exonization by inserting a Ds element into each intron of the rice epsps gene. Exonization of Ds in plants was biased toward providing splice donor sites from the beginning of the inserted Ds sequence. Additionally, Ds inserted in the reverse direction resulted in a continuous splice donor consensus region by offering 4 donor sites in the same intron. The current study involved genome-wide computational analysis of Ds exonization events in the dicot Arabidopsis thaliana and the monocot Oryza sativa (rice). Up to 71% of the exonized transcripts were putative targets for the nonsense-mediated decay (NMD) pathway. The insertion patterns of Ds and the polymorphic splice donor sites increased the transcripts and subsequent protein isoforms. Protein isoforms contain protein sequence due to unspliced intron-TE region and/or a shift of the reading frame. The number of interior protein isoforms would be twice that of C-terminal isoforms, on average. TE exonization provides a promising way for functional expansion of the plant proteome.

  18. Genome-wide association studies and the genetic dissection of complex traits

    Science.gov (United States)

    Sebastiani, Paola; Timofeev, Nadia; Dworkis, Daniel A.; Perls, Thomas T.; Steinberg, Martin H.

    2010-01-01

    The availability of affordable high throughput technology for parallel genotyping has opened the field of genetics to genome-wide association studies (GWAS), and in the last few years hundreds of articles reporting results of GWAS for a variety of heritable traits have been published. What do these results tell us? Although GWAS have discovered a few hundred reproducible associations, this number is underwhelming in relation to the huge amount of data produced, and challenges the conjecture that common variants may be the genetic causes of common diseases. We argue that the massive amount of genetic data that result from these studies remains largely unexplored and unexploited because of the challenge of mining and modeling enormous data sets, the difficulty of using nontraditional computational techniques and the focus of accepted statistical analyses on controlling the false positive rate rather than limiting the false negative rate. In this article, we will review the common approach to analysis of GWAS data and then discuss options to learn more from these data. We will use examples from our ongoing studies of sickle cell anemia and also GWAS in multigenic traits. PMID:19569043

  19. Imputation and quality control steps for combining multiple genome-wide datasets

    Directory of Open Access Journals (Sweden)

    Shefali S Verma

    2014-12-01

    Full Text Available The electronic MEdical Records and GEnomics (eMERGE network brings together DNA biobanks linked to electronic health records (EHRs from multiple institutions. Approximately 52,000 DNA samples from distinct individuals have been genotyped using genome-wide SNP arrays across the nine sites of the network. The eMERGE Coordinating Center and the Genomics Workgroup developed a pipeline to impute and merge genomic data across the different SNP arrays to maximize sample size and power to detect associations with a variety of clinical endpoints. The 1000 Genomes cosmopolitan reference panel was used for imputation. Imputation results were evaluated using the following metrics: accuracy of imputation, allelic R2 (estimated correlation between the imputed and true genotypes, and the relationship between allelic R2 and minor allele frequency. Computation time and memory resources required by two different software packages (BEAGLE and IMPUTE2 were also evaluated. A number of challenges were encountered due to the complexity of using two different imputation software packages, multiple ancestral populations, and many different genotyping platforms. We present lessons learned and describe the pipeline implemented here to impute and merge genomic data sets. The eMERGE imputed dataset will serve as a valuable resource for discovery, leveraging the clinical data that can be mined from the EHR.

  20. Incorporating group correlations in genome-wide association studies using smoothed group Lasso.

    Science.gov (United States)

    Liu, Jin; Huang, Jian; Ma, Shuangge; Wang, Kai

    2013-04-01

    In genome-wide association studies, penalization is an important approach for identifying genetic markers associated with disease. Motivated by the fact that there exists natural grouping structure in single nucleotide polymorphisms and, more importantly, such groups are correlated, we propose a new penalization method for group variable selection which can properly accommodate the correlation between adjacent groups. This method is based on a combination of the group Lasso penalty and a quadratic penalty on the difference of regression coefficients of adjacent groups. The new method is referred to as smoothed group Lasso (SGL). It encourages group sparsity and smoothes regression coefficients for adjacent groups. Canonical correlations are applied to the weights between groups in the quadratic difference penalty. We first derive a GCD algorithm for computing the solution path with linear regression model. The SGL method is further extended to logistic regression for binary response. With the assistance of the majorize-minimization algorithm, the SGL penalized logistic regression turns out to be an iteratively penalized least-square problem. We also suggest conducting principal component analysis to reduce the dimensionality within groups. Simulation studies are used to evaluate the finite sample performance. Comparison with group Lasso shows that SGL is more effective in selecting true positives. Two datasets are analyzed using the SGL method.

  1. The CHR site: definition and genome-wide identification of a cell cycle transcriptional element.

    Science.gov (United States)

    Müller, Gerd A; Wintsche, Axel; Stangner, Konstanze; Prohaska, Sonja J; Stadler, Peter F; Engeland, Kurt

    2014-01-01

    The cell cycle genes homology region (CHR) has been identified as a DNA element with an important role in transcriptional regulation of late cell cycle genes. It has been shown that such genes are controlled by DREAM, MMB and FOXM1-MuvB and that these protein complexes can contact DNA via CHR sites. However, it has not been elucidated which sequence variations of the canonical CHR are functional and how frequent CHR-based regulation is utilized in mammalian genomes. Here, we define the spectrum of functional CHR elements. As the basis for a computational meta-analysis, we identify new CHR sequences and compile phylogenetic motif conservation as well as genome-wide protein-DNA binding and gene expression data. We identify CHR elements in most late cell cycle genes binding DREAM, MMB, or FOXM1-MuvB. In contrast, Myb- and forkhead-binding sites are underrepresented in both early and late cell cycle genes. Our findings support a general mechanism: sequential binding of DREAM, MMB and FOXM1-MuvB complexes to late cell cycle genes requires CHR elements. Taken together, we define the group of CHR-regulated genes in mammalian genomes and provide evidence that the CHR is the central promoter element in transcriptional regulation of late cell cycle genes by DREAM, MMB and FOXM1-MuvB. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  2. Efficient Genome-Wide Sequencing and Low-Coverage Pedigree Analysis from Noninvasively Collected Samples.

    Science.gov (United States)

    Snyder-Mackler, Noah; Majoros, William H; Yuan, Michael L; Shaver, Amanda O; Gordon, Jacob B; Kopp, Gisela H; Schlebusch, Stephen A; Wall, Jeffrey D; Alberts, Susan C; Mukherjee, Sayan; Zhou, Xiang; Tung, Jenny

    2016-06-01

    Research on the genetics of natural populations was revolutionized in the 1990s by methods for genotyping noninvasively collected samples. However, these methods have remained largely unchanged for the past 20 years and lag far behind the genomics era. To close this gap, here we report an optimized laboratory protocol for genome-wide capture of endogenous DNA from noninvasively collected samples, coupled with a novel computational approach to reconstruct pedigree links from the resulting low-coverage data. We validated both methods using fecal samples from 62 wild baboons, including 48 from an independently constructed extended pedigree. We enriched fecal-derived DNA samples up to 40-fold for endogenous baboon DNA and reconstructed near-perfect pedigree relationships even with extremely low-coverage sequencing. We anticipate that these methods will be broadly applicable to the many research systems for which only noninvasive samples are available. The lab protocol and software ("WHODAD") are freely available at www.tung-lab.org/protocols-and-software.html and www.xzlab.org/software.html, respectively. Copyright © 2016 by the Genetics Society of America.

  3. A Probabilistic Genome-Wide Gene Reading Frame Sequence Model

    DEFF Research Database (Denmark)

    Have, Christian Theil; Mørk, Søren

    We introduce a new type of probabilistic sequence model, that model the sequential composition of reading frames of genes in a genome. Our approach extends gene finders with a model of the sequential composition of genes at the genome-level -- effectively producing a sequential genome annotation...... and are evaluated by the effect on prediction performance. Since bacterial gene finding to a large extent is a solved problem it forms an ideal proving ground for evaluating the explicit modeling of larger scale gene sequence composition of genomes. We conclude that the sequential composition of gene reading frames...... as output. The model can be used to obtain the most probable genome annotation based on a combination of i: a gene finder score of each gene candidate and ii: the sequence of the reading frames of gene candidates through a genome. The model --- as well as a higher order variant --- is developed and tested...

  4. BioMet Toolbox: genome-wide analysis of metabolism

    DEFF Research Database (Denmark)

    Cvijovic, M.; Olivares Hernandez, Roberto; Agren, R.

    2010-01-01

    models. Systematic analysis of biological processes by means of modelling and simulations has made the identification of metabolic networks and prediction of metabolic capabilities under different conditions possible. For facilitating such systemic analysis, we have developed the BioMet Toolbox, a web......-based resource for stoichiometric analysis and for integration of transcriptome and interactome data, thereby exploiting the capabilities of genome-scale metabolic models. The BioMet Toolbox provides an effective user-friendly way to perform linear programming simulations towards maximized or minimized growth...... rates, substrate uptake rates and metabolic production rates by detecting relevant fluxes, simulate single and double gene deletions or detect metabolites around which major transcriptional changes are concentrated. These tools can be used for high-throughput in silico screening and allows fully...

  5. [Importance of modern genome-wide studies for the risk of myocardial infarction].

    Science.gov (United States)

    Kessler, T; Erdmann, J; Schunkert, H

    2014-02-01

    The individual genetic susceptibility is a cornerstone in the pathogenesis of coronary artery disease (CAD). The search for the genetic background and the subsequently altered molecular mechanisms has been ineffective for several years. The increase in genome-wide association studies in recent years has changed the scenario and more than 40 variants have so far been identified to be highly significantly associated with CAD and the risk of myocardial infarction (MI). Whereas most of these findings affect frequent polymorphisms, exome-wide sequencing in families with a high prevalence of CAD revealed mutations with a high penetrance and as a consequence a high risk of suffering from MI. The findings allow a deeper insight into functional mechanisms involved in the pathogenesis of atherosclerosis. Furthermore, the data enables validation of the numerous epidemiologically identified risk markers with respect to the causal role in the development of CAD, making the genetic architecture of CAD much more transparent. Nevertheless, individual risk prediction has only made weak progress in the face of the new findings. Every individual without exception carries numerous risk alleles even when the number and effect strength shows individual differences. Thus, a varying degree of genetic susceptibility is shared by all of us. Current research is therefore focusing on the functional integration of genetic information to discover new approaches to prevention and therapy.

  6. Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia

    Science.gov (United States)

    Legge, Sophie E; Hamshere, Marian L; Ripke, Stephan; Pardinas, Antonio F; Goldstein, Jacqueline I; Rees, Elliott; Richards, Alexander L; Leonenko, Ganna; Jorskog, L Fredrik; Chambert, Kimberly D; Collier, David A; Genovese, Giulio; Giegling, Ina; Holmans, Peter; Jonasdottir, Adalbjorg; Kirov, George; McCarroll, Steven A; MacCabe, James H; Mantripragada, Kiran; Moran, Jennifer L; Neale, Benjamin M; Stefansson, Hreinn; Rujescu, Dan; Daly, Mark J; Sullivan, Patrick F; Owen, Michael J; O’Donovan, Michael C; Walters, James T R

    2016-01-01

    The antipsychotic clozapine is uniquely effective in the management of schizophrenia, but its use is limited by its potential to induce agranulocytosis. The causes of this, and of its precursor neutropenia, are largely unknown although genetic factors play an important role. We sought risk alleles for clozapine-associated neutropenia in a sample of 66 cases and 5583 clozapine-treated controls, through a genome-wide association study (GWAS), imputed HLA alleles, exome array, and copy number variation analyses. We then combined associated variants in a meta-analysis with data from the Clozapine-Induced Agranulocytosis Consortium (up to 163 cases and 7970 controls). In the largest combined sample to date, we identified a novel association with rs149104283 (OR=4.32, P=1.79×10-8), intronic to transcripts of SLCO1B3 and SLCO1B7, members of a family of hepatic transporter genes previously implicated in adverse drug reactions including simvastatin-induced myopathy and docetaxel-induced neutropenia. Exome array analysis identified gene-wide associations of uncommon non-synonymous variants within UBAP2 and STARD9. We additionally provide independent replication of a previously identified variant in HLA-DQB1 (OR=15.6, P = 0.015, positive predictive value = 35.1%). These results implicate biological pathways through which clozapine may act to cause this serious adverse effect. PMID:27400856

  7. Genome-wide analysis of complex wheat gliadins, the dominant carriers of celiac disease epitopes.

    Science.gov (United States)

    Wang, Da-Wei; Li, Da; Wang, Junjun; Zhao, Yue; Wang, Zhaojun; Yue, Guidong; Liu, Xin; Qin, Huanju; Zhang, Kunpu; Dong, Lingli; Wang, Daowen

    2017-03-16

    Gliadins, specified by six compound chromosomal loci (Gli-A1/B1/D1 and Gli-A2/B2/D2) in hexaploid bread wheat, are the dominant carriers of celiac disease (CD) epitopes. Because of their complexity, genome-wide characterization of gliadins is a strong challenge. Here, we approached this challenge by combining transcriptomic, proteomic and bioinformatic investigations. Through third-generation RNA sequencing, full-length transcripts were identified for 52 gliadin genes in the bread wheat cultivar Xiaoyan 81. Of them, 42 were active and predicted to encode 25 α-, 11 γ-, one δ- and five ω-gliadins. Comparative proteomic analysis between Xiaoyan 81 and six newly-developed mutants each lacking one Gli locus indicated the accumulation of 38 gliadins in the mature grains. A novel group of α-gliadins (the CSTT group) was recognized to contain very few or no CD epitopes. The δ-gliadins identified here or previously did not carry CD epitopes. Finally, the mutant lacking Gli-D2 showed significant reductions in the most celiac-toxic α-gliadins and derivative CD epitopes. The insights and resources generated here should aid further studies on gliadin functions in CD and the breeding of healthier wheat.

  8. Recent advances in the genome-wide study of DNA replication origins in yeast

    Directory of Open Access Journals (Sweden)

    Chong ePeng

    2015-02-01

    Full Text Available DNA replication, one of the central events in the cell cycle, is the basis of biological inheritance. In order to be duplicated, a DNA double helix must be opened at defined sites, which are called DNA replication origins (ORIs. Unlike in bacteria, where replication initiates from a single replication origin, multiple origins are utilized in the eukaryotic genome. Among them, the ORIs in budding yeast Saccharomyces cerevisiae and the fission yeast Schizosaccharomyces pombe have been best characterized. In recent years, advances in DNA microarray and next-generation sequencing technologies have increased the number of yeast species involved in ORIs research dramatically. The ORIs in some nonconventional yeast species such as Kluyveromyces lactis and Pichia pastoris have also been genome-widely identified. Relevant databases of replication origins in yeast were constructed, then the comparative genomic analysis can be carried out. Here, we review several experimental approaches that have been used to map replication origins in yeast and some of the available web resources related to yeast ORIs. We also discuss the sequence characteristics and chromosome structures of ORIs in the four yeast species, which can be utilized to improve the replication origins prediction.

  9. Quantifying the underestimation of relative risks from genome-wide association studies.

    Directory of Open Access Journals (Sweden)

    Chris Spencer

    2011-03-01

    Full Text Available Genome-wide association studies (GWAS have identified hundreds of associated loci across many common diseases. Most risk variants identified by GWAS will merely be tags for as-yet-unknown causal variants. It is therefore possible that identification of the causal variant, by fine mapping, will identify alleles with larger effects on genetic risk than those currently estimated from GWAS replication studies. We show that under plausible assumptions, whilst the majority of the per-allele relative risks (RR estimated from GWAS data will be close to the true risk at the causal variant, some could be considerable underestimates. For example, for an estimated RR in the range 1.2-1.3, there is approximately a 38% chance that it exceeds 1.4 and a 10% chance that it is over 2. We show how these probabilities can vary depending on the true effects associated with low-frequency variants and on the minor allele frequency (MAF of the most associated SNP. We investigate the consequences of the underestimation of effect sizes for predictions of an individual's disease risk and interpret our results for the design of fine mapping experiments. Although these effects mean that the amount of heritability explained by known GWAS loci is expected to be larger than current projections, this increase is likely to explain a relatively small amount of the so-called "missing" heritability.

  10. A genome-wide longitudinal transcriptome analysis of the aging model Podospora anserina.

    Directory of Open Access Journals (Sweden)

    Oliver Philipp

    Full Text Available Aging of biological systems is controlled by various processes which have a potential impact on gene expression. Here we report a genome-wide transcriptome analysis of the fungal aging model Podospora anserina. Total RNA of three individuals of defined age were pooled and analyzed by SuperSAGE (serial analysis of gene expression. A bioinformatics analysis identified different molecular pathways to be affected during aging. While the abundance of transcripts linked to ribosomes and to the proteasome quality control system were found to decrease during aging, those associated with autophagy increase, suggesting that autophagy may act as a compensatory quality control pathway. Transcript profiles associated with the energy metabolism including mitochondrial functions were identified to fluctuate during aging. Comparison of wild-type transcripts, which are continuously down-regulated during aging, with those down-regulated in the long-lived, copper-uptake mutant grisea, validated the relevance of age-related changes in cellular copper metabolism. Overall, we (i present a unique age-related data set of a longitudinal study of the experimental aging model P. anserina which represents a reference resource for future investigations in a variety of organisms, (ii suggest autophagy to be a key quality control pathway that becomes active once other pathways fail, and (iii present testable predictions for subsequent experimental investigations.

  11. Beef cattle body temperature during climatic stress: a genome-wide association study

    Science.gov (United States)

    Howard, Jeremy T.; Kachman, Stephen D.; Snelling, Warren M.; Pollak, E. John; Ciobanu, Daniel C.; Kuehn, Larry A.; Spangler, Matthew L.

    2014-09-01

    Cattle are reared in diverse environments and collecting phenotypic body temperature (BT) measurements to characterize BT variation across diverse environments is difficult and expensive. To better understand the genetic basis of BT regulation, a genome-wide association study was conducted utilizing crossbred steers and heifers totaling 239 animals of unknown pedigree and breed fraction. During predicted extreme heat and cold stress events, hourly tympanic and vaginal BT devices were placed in steers and heifers, respectively. Individuals were genotyped with the BovineSNP50K_v2 assay and data analyzed using Bayesian models for area under the curve (AUC), a measure of BT over time, using hourly BT observations summed across 5-days (AUC summer 5-day (AUCS5D) and AUC winter 5-day (AUCW5D)). Posterior heritability estimates were moderate to high and were estimated to be 0.68 and 0.21 for AUCS5D and AUCW5D, respectively. Moderately positive correlations between direct genomic values for AUCS5D and AUCW5D (0.40) were found, although a small percentage of the top 5 % 1-Mb windows were in common. Different sets of genes were associated with BT during winter and summer, thus simultaneous selection for animals tolerant to both heat and cold appears possible.

  12. Genome-wide analysis of complex wheat gliadins, the dominant carriers of celiac disease epitopes

    Science.gov (United States)

    Wang, Da-Wei; Li, Da; Wang, Junjun; Zhao, Yue; Wang, Zhaojun; Yue, Guidong; Liu, Xin; Qin, Huanju; Zhang, Kunpu; Dong, Lingli; Wang, Daowen

    2017-01-01

    Gliadins, specified by six compound chromosomal loci (Gli-A1/B1/D1 and Gli-A2/B2/D2) in hexaploid bread wheat, are the dominant carriers of celiac disease (CD) epitopes. Because of their complexity, genome-wide characterization of gliadins is a strong challenge. Here, we approached this challenge by combining transcriptomic, proteomic and bioinformatic investigations. Through third-generation RNA sequencing, full-length transcripts were identified for 52 gliadin genes in the bread wheat cultivar Xiaoyan 81. Of them, 42 were active and predicted to encode 25 α-, 11 γ-, one δ- and five ω-gliadins. Comparative proteomic analysis between Xiaoyan 81 and six newly-developed mutants each lacking one Gli locus indicated the accumulation of 38 gliadins in the mature grains. A novel group of α-gliadins (the CSTT group) was recognized to contain very few or no CD epitopes. The δ-gliadins identified here or previously did not carry CD epitopes. Finally, the mutant lacking Gli-D2 showed significant reductions in the most celiac-toxic α-gliadins and derivative CD epitopes. The insights and resources generated here should aid further studies on gliadin functions in CD and the breeding of healthier wheat. PMID:28300172

  13. Targeted genome-wide enrichment of functional regions.

    Directory of Open Access Journals (Sweden)

    Periannan Senapathy

    Full Text Available Only a small fraction of large genomes such as that of the human contains the functional regions such as the exons, promoters, and polyA sites. A platform technique for selective enrichment of functional genomic regions will enable several next-generation sequencing applications that include the discovery of causal mutations for disease and drug response. Here, we describe a powerful platform technique, termed "functional genomic fingerprinting" (FGF, for the multiplexed genomewide isolation and analysis of targeted regions such as the exome, promoterome, or exon splice enhancers. The technique employs a fixed part of a uniquely designed Fixed-Randomized primer, while the randomized part contains all the possible sequence permutations. The Fixed-Randomized primers bind with full sequence complementarity at multiple sites where the fixed sequence (such as the splice signals occurs within the genome, and multiplex amplify many regions bounded by the fixed sequences (e.g., exons. Notably, validation of this technique using cardiac myosin binding protein-C (MYBPC3 gene as an example strongly supports the application and efficacy of this method. Further, assisted by genomewide computational analyses of such sequences, the FGF technique may provide a unique platform for high-throughput sample production and analysis of targeted genomic regions by the next-generation sequencing techniques, with powerful applications in discovering disease and drug response genes.

  14. Genome-wide analysis of TCP family in tobacco.

    Science.gov (United States)

    Chen, L; Chen, Y Q; Ding, A M; Chen, H; Xia, F; Wang, W F; Sun, Y H

    2016-05-23

    The TCP family is a transcription factor family, members of which are extensively involved in plant growth and development as well as in signal transduction in the response against many physiological and biochemical stimuli. In the present study, 61 TCP genes were identified in tobacco (Nicotiana tabacum) genome. Bioinformatic methods were employed for predicting and analyzing the gene structure, gene expression, phylogenetic analysis, and conserved domains of TCP proteins in tobacco. The 61 NtTCP genes were divided into three diverse groups, based on the division of TCP genes in tomato and Arabidopsis, and the results of the conserved domain and sequence analyses further confirmed the classification of the NtTCP genes. The expression pattern of NtTCP also demonstrated that majority of these genes play important roles in all the tissues, while some special genes exercise their functions only in specific tissues. In brief, the comprehensive and thorough study of the TCP family in other plants provides sufficient resources for studying the structure and functions of TCPs in tobacco.

  15. Discovery and replication of microRNAs for breast cancer risk using genome-wide profiling.

    Science.gov (United States)

    Taslim, Cenny; Weng, Daniel Y; Brasky, Theodore M; Dumitrescu, Ramona G; Huang, Kun; Kallakury, Bhaskar V S; Krishnan, Shiva; Llanos, Adana A; Marian, Catalin; McElroy, Joseph; Schneider, Sallie S; Spear, Scott L; Troester, Melissa A; Freudenheim, Jo L; Geyer, Susan; Shields, Peter G

    2016-12-27

    Genome-wide miRNA expression may be useful for predicting breast cancer risk and/or for the early detection of breast cancer. A 41-miRNA model distinguished breast cancer risk in the discovery study (accuracy of 83.3%), which was replicated in the independent study (accuracy = 63.4%, P=0.09). Among the 41 miRNA, 20 miRNAs were detectable in serum, and predicted breast cancer occurrence within 18 months of blood draw (accuracy 53%, P=0.06). These risk-related miRNAs were enriched for HER-2 and estrogen-dependent breast cancer signaling. MiRNAs were assessed in two cross-sectional studies of women without breast cancer and a nested case-control study of breast cancer. Using breast tissues, a multivariate analysis was used to model women with high and low breast cancer risk (based upon Gail risk model) in a discovery study of women without breast cancer (n=90), and applied to an independent replication study (n=71). The model was then assessed using serum samples from the nested case-control study (n=410). Studying breast tissues of women without breast cancer revealed miRNAs correlated with breast cancer risk, which were then found to be altered in the serum of women who later developed breast cancer. These results serve as proof-of-principle that miRNAs in women without breast cancer may be useful for predicting breast cancer risk and/or as an adjunct for breast cancer early detection. The miRNAs identified herein may be involved in breast carcinogenic pathways because they were first identified in the breast tissues of healthy women.

  16. Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits.

    Directory of Open Access Journals (Sweden)

    Elizabeth K Speliotes

    2011-03-01

    Full Text Available Nonalcoholic fatty liver disease (NAFLD clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA analysis of computed tomography (CT measured hepatic steatosis, a non-invasive measure of NAFLD, in large population based samples. Using variance components methods, we show that CT hepatic steatosis is heritable (∼26%-27% in family-based Amish, Family Heart, and Framingham Heart Studies (n = 880 to 3,070. By carrying out a fixed-effects meta-analysis of genome-wide association (GWA results between CT hepatic steatosis and ∼2.4 million imputed or genotyped SNPs in 7,176 individuals from the Old Order Amish, Age, Gene/Environment Susceptibility-Reykjavik study (AGES, Family Heart, and Framingham Heart Studies, we identify variants associated at genome-wide significant levels (p<5×10(-8 in or near PNPLA3, NCAN, and PPP1R3B. We genotype these and 42 other top CT hepatic steatosis-associated SNPs in 592 subjects with biopsy-proven NAFLD from the NASH Clinical Research Network (NASH CRN. In comparisons with 1,405 healthy controls from the Myocardial Genetics Consortium (MIGen, we observe significant associations with histologic NAFLD at variants in or near NCAN, GCKR, LYPLAL1, and PNPLA3, but not PPP1R3B. Variants at these five loci exhibit distinct patterns of association with serum lipids, as well as glycemic and anthropometric traits. We identify common genetic variants influencing CT-assessed steatosis and risk of NAFLD. Hepatic steatosis associated variants are not uniformly associated with NASH/fibrosis or result in abnormalities in serum lipids or glycemic and anthropometric traits, suggesting genetic heterogeneity in the pathways influencing these traits.

  17. The challenges of genome-wide interaction studies: lessons to learn from the analysis of HDL blood levels.

    Directory of Open Access Journals (Sweden)

    Elisabeth M van Leeuwen

    Full Text Available Genome-wide association studies (GWAS have revealed 74 single nucleotide polymorphisms (SNPs associated with high-density lipoprotein cholesterol (HDL blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS cohort I (RS-I using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III, we were able to filter 181 interaction terms with a p-value<1 · 10-8 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30,011 when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098 and rs12442098 in SPATA8 (ENSG00000185594 being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS.

  18. Genome-Wide Analysis of Seed Acid Detergent Lignin (ADL) and Hull Content in Rapeseed (Brassica napus L.)

    Science.gov (United States)

    Wei, Lijuan; Qu, Cunmin; Xu, Xinfu; Lu, Kun; Qian, Wei; Li, Jiana; Li, Maoteng; Liu, Liezhao

    2015-01-01

    A stable yellow-seeded variety is the breeding goal for obtaining the ideal rapeseed (Brassica napus L.) plant, and the amount of acid detergent lignin (ADL) in the seeds and the hull content (HC) are often used as yellow-seeded rapeseed screening indices. In this study, a genome-wide association analysis of 520 accessions was performed using the Q + K model with a total of 31,839 single-nucleotide polymorphism (SNP) sites. As a result, three significant associations on the B. napus chromosomes A05, A09, and C05 were detected for seed ADL content. The peak SNPs were within 9.27, 14.22, and 20.86 kb of the key genes BnaA.PAL4, BnaA.CAD2/BnaA.CAD3, and BnaC.CCR1, respectively. Further analyses were performed on the major locus of A05, which was also detected in the seed HC examination. A comparison of our genome-wide association study (GWAS) results and previous linkage mappings revealed a common chromosomal region on A09, which indicates that GWAS can be used as a powerful complementary strategy for dissecting complex traits in B. napus. Genomic selection (GS) utilizing the significant SNP markers based on the GWAS results exhibited increased predictive ability, indicating that the predictive ability of a given model can be substantially improved by using GWAS and GS. PMID:26673885

  19. Genome-wide association for abdominal subcutaneous and visceral adipose reveals a novel locus for visceral fat in women.

    Directory of Open Access Journals (Sweden)

    Caroline S Fox

    Full Text Available Body fat distribution, particularly centralized obesity, is associated with metabolic risk above and beyond total adiposity. We performed genome-wide association of abdominal adipose depots quantified using computed tomography (CT to uncover novel loci for body fat distribution among participants of European ancestry. Subcutaneous and visceral fat were quantified in 5,560 women and 4,997 men from 4 population-based studies. Genome-wide genotyping was performed using standard arrays and imputed to ~2.5 million Hapmap SNPs. Each study performed a genome-wide association analysis of subcutaneous adipose tissue (SAT, visceral adipose tissue (VAT, VAT adjusted for body mass index, and VAT/SAT ratio (a metric of the propensity to store fat viscerally as compared to subcutaneously in the overall sample and in women and men separately. A weighted z-score meta-analysis was conducted. For the VAT/SAT ratio, our most significant p-value was rs11118316 at LYPLAL1 gene (p = 3.1 × 10E-09, previously identified in association with waist-hip ratio. For SAT, the most significant SNP was in the FTO gene (p = 5.9 × 10E-08. Given the known gender differences in body fat distribution, we performed sex-specific analyses. Our most significant finding was for VAT in women, rs1659258 near THNSL2 (p = 1.6 × 10-08, but not men (p = 0.75. Validation of this SNP in the GIANT consortium data demonstrated a similar sex-specific pattern, with observed significance in women (p = 0.006 but not men (p = 0.24 for BMI and waist circumference (p = 0.04 [women], p = 0.49 [men]. Finally, we interrogated our data for the 14 recently published loci for body fat distribution (measured by waist-hip ratio adjusted for BMI; associations were observed at 7 of these loci. In contrast, we observed associations at only 7/32 loci previously identified in association with BMI; the majority of overlap was observed with SAT. Genome-wide association for visceral and subcutaneous fat revealed a

  20. Genome-wide association study for subclinical atherosclerosis in major arterial territories in the NHLBI's Framingham Heart Study

    Directory of Open Access Journals (Sweden)

    Hwang Shih-Jen

    2007-09-01

    Full Text Available Abstract Introduction Subclinical atherosclerosis (SCA measures in multiple arterial beds are heritable phenotypes that are associated with increased incidence of cardiovascular disease. We conducted a genome-wide association study (GWAS for SCA measurements in the community-based Framingham Heart Study. Methods Over 100,000 single nucleotide polymorphisms (SNPs were genotyped (Human 100K GeneChip, Affymetrix in 1345 subjects from 310 families. We calculated sex-specific age-adjusted and multivariable-adjusted residuals in subjects tested for quantitative SCA phenotypes, including ankle-brachial index, coronary artery calcification and abdominal aortic calcification using multi-detector computed tomography, and carotid intimal medial thickness (IMT using carotid ultrasonography. We evaluated associations of these phenotypes with 70,987 autosomal SNPs with minor allele frequency ≥ 0.10, call rate ≥ 80%, and Hardy-Weinberg p-value ≥ 0.001 in samples ranging from 673 to 984 subjects, using linear regression with generalized estimating equations (GEE methodology and family-based association testing (FBAT. Variance components LOD scores were also calculated. Results There was no association result meeting criteria for genome-wide significance, but our methods identified 11 SNPs with p -5 by GEE and five SNPs with p -5 by FBAT for multivariable-adjusted phenotypes. Among the associated variants were SNPs in or near genes that may be considered candidates for further study, such as rs1376877 (GEE p ABI2 for maximum internal carotid artery IMT and rs4814615 (FBAT p = 0.000003, located in PCSK2 for maximum common carotid artery IMT. Modest significant associations were noted with various SCA phenotypes for variants in previously reported atherosclerosis candidate genes, including NOS3 and ESR1. Associations were also noted of a region on chromosome 9p21 with CAC phenotypes that confirm associations with coronary heart disease and CAC in two

  1. Integrative Tissue-Specific Functional Annotations in the Human Genome Provide Novel Insights on Many Complex Traits and Improve Signal Prioritization in Genome Wide Association Studies.

    Directory of Open Access Journals (Sweden)

    Qiongshi Lu

    2016-04-01

    Full Text Available Extensive efforts have been made to understand genomic function through both experimental and computational approaches, yet proper annotation still remains challenging, especially in non-coding regions. In this manuscript, we introduce GenoSkyline, an unsupervised learning framework to predict tissue-specific functional regions through integrating high-throughput epigenetic annotations. GenoSkyline successfully identified a variety of non-coding regulatory machinery including enhancers, regulatory miRNA, and hypomethylated transposable elements in extensive case studies. Integrative analysis of GenoSkyline annotations and results from genome-wide association studies (GWAS led to novel biological insights on the etiologies of a number of human complex traits. We also explored using tissue-specific functional annotations to prioritize GWAS signals and predict relevant tissue types for each risk locus. Brain and blood-specific annotations led to better prioritization performance for schizophrenia than standard GWAS p-values and non-tissue-specific annotations. As for coronary artery disease, heart-specific functional regions was highly enriched of GWAS signals, but previously identified risk loci were found to be most functional in other tissues, suggesting a substantial proportion of still undetected heart-related loci. In summary, GenoSkyline annotations can guide genetic studies at multiple resolutions and provide valuable insights in understanding complex diseases. GenoSkyline is available at http://genocanyon.med.yale.edu/GenoSkyline.

  2. Multivariate optical computation for predictive spectroscopy.

    Science.gov (United States)

    Nelson, M P; Aust, J F; Dobrowolski, J A; Verly, P G; Myrick, M L

    1998-01-01

    A novel optical approach to predicting chemical and physical properties based on principal component analysis (PCA) is proposed and evaluated using a data set from earlier work. In our approach, a regression vector produced by PCA is designed into the structure of a set of paired optical filters. Light passing through the paired filters produces an analog detector signal that is directly proportional to the chemical/physical property for which the regression vector was designed. This simple optical computational method for predictive spectroscopy is evaluated in several ways, using the example data for numeric simulation. First, we evaluate the sensitivity of the method to various types of spectroscopic errors commonly encountered and find the method to have the same susceptibilities toward error as standard methods. Second, we use propagation of errors to determine the effects of detector noise on the predictive power of the method, finding the optical computation approach to have a large multiplex advantage over conventional methods. Third, we use two different design approaches to the construction of the paired filter set for the example measurement to evaluate manufacturability, finding that adequate methods exist to design appropriate optical devices. Fourth, we numerically simulate the predictive errors introduced by design errors in the paired filters, finding that predictive errors are not increased over conventional methods. Fifth, we consider how the performance of the method is affected by light intensities that are not linearly related to chemical composition (as in transmission spectroscopy) and find that the method is only marginally affected. In summary, we conclude that many types of predictive measurements based on use of regression (or other) vectors and linear mathematics can be performed more rapidly, more effectly, and at considerably lower cost by the proposed optical computation method than by traditional dispersive or interferometric

  3. Genome wide association studies for body conformation traits in the Chinese Holstein cattle population

    DEFF Research Database (Denmark)

    Wu, Xiaoping; Fang, Ming; Liu, Lin;

    2013-01-01

    Background: Genome-wide association study (GWAS) is a powerful tool for revealing the genetic basis of quantitative traits. However, studies using GWAS for conformation traits of cattle is comparatively less. This study aims to use GWAS to find the candidates genes for body conformation traits.......Results: The Illumina BovineSNP50 BeadChip was used to identify single nucleotide polymorphisms (SNPs) that are associated with body conformation traits. A least absolute shrinkage and selection operator (LASSO) was applied to detect multiple SNPs simultaneously for 29 body conformation traits with 1,314 Chinese...... Holstein cattle and 52,166 SNPs. Totally, 59 genome-wide significant SNPs associated with 26 conformation traits were detected by genome-wide association analysis; five SNPs were within previously reported QTL regions (Animal Quantitative Trait Loci (QTL) database) and 11 were very close to the reported...

  4. Genetic link between family socioeconomic status and children's educational achievement estimated from genome-wide SNPs.

    Science.gov (United States)

    Krapohl, E; Plomin, R

    2016-03-01

    One of the best predictors of children's educational achievement is their family's socioeconomic status (SES), but the degree to which this association is genetically mediated remains unclear. For 3000 UK-representative unrelated children we found that genome-wide single-nucleotide polymorphisms could explain a third of the variance of scores on an age-16 UK national examination of educational achievement and half of the correlation between their scores and family SES. Moreover, genome-wide polygenic scores based on a previously published genome-wide association meta-analysis of total number of years in education accounted for ~3.0% variance in educational achievement and ~2.5% in family SES. This study provides the first molecular evidence for substantial genetic influence on differences in children's educational achievement and its association with family SES.

  5. Genome-wide analyses of aggressiveness in attention-deficit hyperactivity disorder.

    Science.gov (United States)

    Brevik, Erlend J; van Donkelaar, Marjolein M J; Weber, Heike; Sánchez-Mora, Cristina; Jacob, Christian; Rivero, Olga; Kittel-Schneider, Sarah; Garcia-Martínez, Iris; Aebi, Marcel; van Hulzen, Kimm; Cormand, Bru; Ramos-Quiroga, Josep A; Lesch, Klaus-Peter; Reif, Andreas; Ribasés, Marta; Franke, Barbara; Posserud, Maj-Britt; Johansson, Stefan; Lundervold, Astri J; Haavik, Jan; Zayats, Tetyana

    2016-07-01

    Aggressiveness is a behavioral trait that has the potential to be harmful to individuals and society. With an estimated heritability of about 40%, genetics is important in its development. We performed an exploratory genome-wide association (GWA) analysis of childhood aggressiveness in attention deficit hyperactivity disorder (ADHD) to gain insight into the underlying biological processes associated with this trait. Our primary sample consisted of 1,060 adult ADHD patients (aADHD). To further explore the genetic architecture of childhood aggressiveness, we performed enrichment analyses of suggestive genome-wide associations observed in aADHD among GWA signals of dimensions of oppositionality (defiant/vindictive and irritable dimensions) in childhood ADHD (cADHD). No single polymorphism reached genome-wide significance (P aggressiveness and provide targets for further genetic exploration of aggressiveness across psychiatric disorders. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

  6. Reconstructing Genome-Wide Protein–Protein Interaction Networks Using Multiple Strategies with Homologous Mapping

    Science.gov (United States)

    Lo, Yu-Shu; Huang, Sing-Han; Luo, Yong-Chun; Lin, Chun-Yu; Yang, Jinn-Moon

    2015-01-01

    PPIs share similar biological processes and cellular components, and the reconstructed genome-wide PPI network can reflect network topology and modularity. We believe that our method is useful for inferring reliable PPIs and reconstructing a comprehensive PPI network of an interesting organism. PMID:25602759

  7. Computationally efficient prediction of area per lipid

    DEFF Research Database (Denmark)

    Chaban, Vitaly V.

    2014-01-01

    Area per lipid (APL) is an important property of biological and artificial membranes. Newly constructed bilayers are characterized by their APL and newly elaborated force fields must reproduce APL. Computer simulations of APL are very expensive due to slow conformational dynamics. The simulated d....... Thus, sampling times to predict accurate APL are reduced by a factor of 10. (C) 2014 Elsevier B.V. All rights reserved....

  8. Meta-Analysis in Genome-Wide Association Datasets: Strategies and Application in Parkinson Disease

    Science.gov (United States)

    Evangelou, Evangelos; Maraganore, Demetrius M.; Ioannidis, John P.A.

    2007-01-01

    Background Genome-wide association studies hold substantial promise for identifying common genetic variants that regulate susceptibility to complex diseases. However, for the detection of small genetic effects, single studies may be underpowered. Power may be improved by combining genome-wide datasets with meta-analytic techniques. Methodology/Principal Findings Both single and two-stage genome-wide data may be combined and there are several possible strategies. In the two-stage framework, we considered the options of (1) enhancement of replication data and (2) enhancement of first-stage data, and then, we also considered (3) joint meta-analyses including all first-stage and second-stage data. These strategies were examined empirically using data from two genome-wide association studies (three datasets) on Parkinson disease. In the three strategies, we derived 12, 5, and 49 single nucleotide polymorphisms that show significant associations at conventional levels of statistical significance. None of these remained significant after conservative adjustment for the number of performed analyses in each strategy. However, some may warrant further consideration: 6 SNPs were identified with at least 2 of the 3 strategies and 3 SNPs [rs1000291 on chromosome 3, rs2241743 on chromosome 4 and rs3018626 on chromosome 11] were identified with all 3 strategies and had no or minimal between-dataset heterogeneity (I2 = 0, 0 and 15%, respectively). Analyses were primarily limited by the suboptimal overlap of tested polymorphisms across different datasets (e.g., only 31,192 shared polymorphisms between the two tier 1 datasets). Conclusions/Significance Meta-analysis may be used to improve the power and examine the between-dataset heterogeneity of genome-wide association studies. Prospective designs may be most efficient, if they try to maximize the overlap of genotyping platforms and anticipate the combination of data across many genome-wide association studies. PMID:17332845

  9. Meta-analysis in genome-wide association datasets: strategies and application in Parkinson disease.

    Science.gov (United States)

    Evangelou, Evangelos; Maraganore, Demetrius M; Ioannidis, John P A

    2007-02-07

    Genome-wide association studies hold substantial promise for identifying common genetic variants that regulate susceptibility to complex diseases. However, for the detection of small genetic effects, single studies may be underpowered. Power may be improved by combining genome-wide datasets with meta-analytic techniques. Both single and two-stage genome-wide data may be combined and there are several possible strategies. In the two-stage framework, we considered the options of (1) enhancement of replication data and (2) enhancement of first-stage data, and then, we also considered (3) joint meta-analyses including all first-stage and second-stage data. These strategies were examined empirically using data from two genome-wide association studies (three datasets) on Parkinson disease. In the three strategies, we derived 12, 5, and 49 single nucleotide polymorphisms that show significant associations at conventional levels of statistical significance. None of these remained significant after conservative adjustment for the number of performed analyses in each strategy. However, some may warrant further consideration: 6 SNPs were identified with at least 2 of the 3 strategies and 3 SNPs [rs1000291 on chromosome 3, rs2241743 on chromosome 4 and rs3018626 on chromosome 11] were identified with all 3 strategies and had no or minimal between-dataset heterogeneity (I(2) = 0, 0 and 15%, respectively). Analyses were primarily limited by the suboptimal overlap of tested polymorphisms across different datasets (e.g., only 31,192 shared polymorphisms between the two tier 1 datasets). Meta-analysis may be used to improve the power and examine the between-dataset heterogeneity of genome-wide association studies. Prospective designs may be most efficient, if they try to maximize the overlap of genotyping platforms and anticipate the combination of data across many genome-wide association studies.

  10. Genome wide association analysis of the 16th QTL- MAS Workshop dataset using the Random Forest machine learning approach

    Science.gov (United States)

    2014-01-01

    Background Genome wide association studies are now widely used in the livestock sector to estimate the association among single nucleotide polymorphisms (SNPs) distributed across the whole genome and one or more trait. As computational power increases, the use of machine learning techniques to analyze large genome wide datasets becomes possible. Methods The objective of this study was to identify SNPs associated with the three traits simulated in the 16th MAS-QTL workshop dataset using the Random Forest (RF) approach. The approach was applied to single and multiple trait estimated breeding values, and on yield deviations and to compare them with the results of the GRAMMAR-CG method. Results The two QTL mapping methods used, GRAMMAR-CG and RF, were successful in identifying the main QTLs for trait 1 on chromosomes 1 and 4, for trait 2 on chromosomes 1, 4 and 5 and for trait 3 on chromosomes 1, 2 and 3. Conclusions The results of the RF approach were confirmed by the GRAMMAR-CG method and validated by the effective QTL position, even if their approach to unravel cryptic genetic structure is different. Furthermore, both methods showed complementary findings. However, when the variance explained by the QTL is low, they both failed to detect significant associations. PMID:25519518

  11. Is ""predictability"" in computational sciences a myth?

    Energy Technology Data Exchange (ETDEWEB)

    Hemez, Francois M [Los Alamos National Laboratory

    2011-01-31

    Within the last two decades, Modeling and Simulation (M&S) has become the tool of choice to investigate the behavior of complex phenomena. Successes encountered in 'hard' sciences are prompting interest to apply a similar approach to Computational Social Sciences in support, for example, of national security applications faced by the Intelligence Community (IC). This manuscript attempts to contribute to the debate on the relevance of M&S to IC problems by offering an overview of what it takes to reach 'predictability' in computational sciences. Even though models developed in 'soft' and 'hard' sciences are different, useful analogies can be drawn. The starting point is to view numerical simulations as 'filters' capable to represent information only within specific length, time or energy bandwidths. This simplified view leads to the discussion of resolving versus modeling which motivates the need for sub-scale modeling. The role that modeling assumptions play in 'hiding' our lack-of-knowledge about sub-scale phenomena is explained which leads to discussing uncertainty in simulations. It is argued that the uncertainty caused by resolution and modeling assumptions should be dealt with differently than uncertainty due to randomness or variability. The corollary is that a predictive capability cannot be defined solely as accuracy, or ability of predictions to match the available physical observations. We propose that 'predictability' is the demonstration that predictions from a class of 'equivalent' models are as consistent as possible. Equivalency stems from defining models that share a minimum requirement of accuracy, while being equally robust to the sources of lack-of-knowledge in the problem. Examples in computational physics and engineering are given to illustrate the discussion.

  12. Constitutional mosaic genome-wide uniparental disomy due to diploidisation: an unusual cancer-predisposing mechanism.

    Science.gov (United States)

    Romanelli, Valeria; Nevado, Julián; Fraga, Mario; Trujillo, Alex Martín; Mori, Maria Ángeles; Fernández, Luis; Pérez de Nanclares, Guiomar; Martínez-Glez, Víctor; Pita, Guillermo; Meneses, Heloisa; Gracia, Ricardo; García-Miñaur, Sixto; García de Miguel, Purificación; Lecumberri, Beatriz; Rodríguez, José Ignacio; González Neira, Anna; Monk, David; Lapunzina, Pablo

    2011-03-01

    Molecular studies in a patient with Beckwith-Wiedemann syndrome phenotype who developed two different tumours revealed an unexpected observation of almost complete loss of heterozygosity of all chromosomes. It is shown, by means of numerous molecular methods, that the absence of maternal contribution in somatic cells is due to high-degree (∼ 85%) genome-wide paternal uniparental disomy (UPD). The observations indicate that the genome-wide UPD results from diploidisation, and have important implications for genetic counselling and tumour surveillance for the growing number of UPD associated imprinting disorders.

  13. Genome-wide mapping of Polycomb target genes unravels their roles in cell fate transitions

    DEFF Research Database (Denmark)

    Bracken, Adrian P; Dietrich, Nikolaj; Pasini, Diego;

    2006-01-01

    The Polycomb group (PcG) proteins form chromatin-modifying complexes that are essential for embryonic development and stem cell renewal and are commonly deregulated in cancer. Here, we identify their target genes using genome-wide location analysis in human embryonic fibroblasts. We find that Pol......The Polycomb group (PcG) proteins form chromatin-modifying complexes that are essential for embryonic development and stem cell renewal and are commonly deregulated in cancer. Here, we identify their target genes using genome-wide location analysis in human embryonic fibroblasts. We find...

  14. Generation of meiomaps of genome-wide recombination and chromosome segregation in human oocytes

    DEFF Research Database (Denmark)

    Ottolini, Christian S; Capalbo, Antonio; Newnham, Louise

    2016-01-01

    We have developed a protocol for the generation of genome-wide maps (meiomaps) of recombination and chromosome segregation for the three products of human female meiosis: the first and second polar bodies (PB1 and PB2) and the corresponding oocyte. PB1 is biopsied and the oocyte is artificially......-nucleotide polymorphisms (SNPs) genome-wide by microarray. Informative maternal heterozygous SNPs are phased using a haploid PB2 or oocyte as a reference. A simple algorithm is then used to identify the maternal haplotypes for each chromosome, in all of the products of meiosis for each oocyte. This allows mapping...

  15. Quality control and conduct of genome-wide association meta-analyses

    DEFF Research Database (Denmark)

    Winkler, Thomas W; Day, Felix R; Croteau-Chonka, Damien C

    2014-01-01

    Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for (i) organizational aspects of GWAMAs, and for (ii) QC...... at the study file level, the meta-level across studies and the meta-analysis output level. Real-world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide...

  16. A Genome-wide Association Study of Nonsyndromic Cleft Palate Identifies an Etiologic Missense Variant in GRHL3

    Science.gov (United States)

    Leslie, Elizabeth J.; Liu, Huan; Carlson, Jenna C.; Shaffer, John R.; Feingold, Eleanor; Wehby, George; Laurie, Cecelia A.; Jain, Deepti; Laurie, Cathy C.; Doheny, Kimberly F.; McHenry, Toby; Resick, Judith; Sanchez, Carla; Jacobs, Jennifer; Emanuele, Beth; Vieira, Alexandre R.; Neiswanger, Katherine; Standley, Jennifer; Czeizel, Andrew E.; Deleyiannis, Frederic; Christensen, Kaare; Munger, Ronald G.; Lie, Rolv T.; Wilcox, Allen; Romitti, Paul A.; Field, L. Leigh; Padilla, Carmencita D.; Cutiongco-de la Paz, Eva Maria C.; Lidral, Andrew C.; Valencia-Ramirez, Luz Consuelo; Lopez-Palacio, Ana Maria; Valencia, Dora Rivera; Arcos-Burgos, Mauricio; Castilla, Eduardo E.; Mereb, Juan C.; Poletta, Fernando A.; Orioli, Iêda M.; Carvalho, Flavia M.; Hecht, Jacqueline T.; Blanton, Susan H.; Buxó, Carmen J.; Butali, Azeez; Mossey, Peter A.; Adeyemo, Wasiu L.; James, Olutayo; Braimah, Ramat O.; Aregbesola, Babatunde S.; Eshete, Mekonen A.; Deribew, Milliard; Koruyucu, Mine; Seymen, Figen; Ma, Lian; de Salamanca, Javier Enríquez; Weinberg, Seth M.; Moreno, Lina; Cornell, Robert A.; Murray, Jeffrey C.; Marazita, Mary L.

    2016-01-01

    Cleft palate (CP) is a common birth defect occurring in 1 in 2,500 live births. Approximately half of infants with CP have a syndromic form, exhibiting other physical and cognitive disabilities. The other half have nonsyndromic CP, and to date, few genes associated with risk for nonsyndromic CP have been characterized. To identify such risk factors, we performed a genome-wide association study of this disorder. We discovered a genome-wide significant association with a missense variant in GRHL3 (p.Thr454Met [c.1361C>T]; rs41268753; p = 4.08 × 10−9) and replicated the result in an independent sample of case and control subjects. In both the discovery and replication samples, rs41268753 conferred increased risk for CP (OR = 8.3, 95% CI 4.1–16.8; OR = 2.16, 95% CI 1.43–3.27, respectively). In luciferase transactivation assays, p.Thr454Met had about one-third of the activity of wild-type GRHL3, and in zebrafish embryos, perturbed periderm development. We conclude that this mutation is an etiologic variant for nonsyndromic CP and is one of few functional variants identified to date for nonsyndromic orofacial clefting. This finding advances our understanding of the genetic basis of craniofacial development and might ultimately lead to improvements in recurrence risk prediction, treatment, and prognosis. PMID:27018472

  17. The Csr system regulates genome-wide mRNA stability and transcription and thus gene expression in Escherichia coli.

    Science.gov (United States)

    Esquerré, Thomas; Bouvier, Marie; Turlan, Catherine; Carpousis, Agamemnon J; Girbal, Laurence; Cocaign-Bousquet, Muriel

    2016-04-26

    Bacterial adaptation requires large-scale regulation of gene expression. We have performed a genome-wide analysis of the Csr system, which regulates many important cellular functions. The Csr system is involved in post-transcriptional regulation, but a role in transcriptional regulation has also been suggested. Two proteins, an RNA-binding protein CsrA and an atypical signaling protein CsrD, participate in the Csr system. Genome-wide transcript stabilities and levels were compared in wildtype E. coli (MG1655) and isogenic mutant strains deficient in CsrA or CsrD activity demonstrating for the first time that CsrA and CsrD are global negative and positive regulators of transcription, respectively. The role of CsrA in transcription regulation may be indirect due to the 4.6-fold increase in csrD mRNA concentration in the CsrA deficient strain. Transcriptional action of CsrA and CsrD on a few genes was validated by transcriptional fusions. In addition to an effect on transcription, CsrA stabilizes thousands of mRNAs. This is the first demonstration that CsrA is a global positive regulator of mRNA stability. For one hundred genes, we predict that direct control of mRNA stability by CsrA might contribute to metabolic adaptation by regulating expression of genes involved in carbon metabolism and transport independently of transcriptional regulation.

  18. Statistical correction of the Winner's Curse explains replication variability in quantitative trait genome-wide association studies.

    Directory of Open Access Journals (Sweden)

    Cameron Palmer

    2017-07-01

    Full Text Available Genome-wide association studies (GWAS have identified hundreds of SNPs responsible for variation in human quantitative traits. However, genome-wide-significant associations often fail to replicate across independent cohorts, in apparent inconsistency with their apparent strong effects in discovery cohorts. This limited success of replication raises pervasive questions about the utility of the GWAS field. We identify all 332 studies of quantitative traits from the NHGRI-EBI GWAS Database with attempted replication. We find that the majority of studies provide insufficient data to evaluate replication rates. The remaining papers replicate significantly worse than expected (p < 10-14, even when adjusting for regression-to-the-mean of effect size between discovery- and replication-cohorts termed the Winner's Curse (p < 10-16. We show this is due in part to misreporting replication cohort-size as a maximum number, rather than per-locus one. In 39 studies accurately reporting per-locus cohort-size for attempted replication of 707 loci in samples with similar ancestry, replication rate matched expectation (predicted 458, observed 457, p = 0.94. In contrast, ancestry differences between replication and discovery (13 studies, 385 loci cause the most highly-powered decile of loci to replicate worse than expected, due to difference in linkage disequilibrium.

  19. Vive la résistance: genome-wide selection against introduced alleles in invasive hybrid zones.

    Science.gov (United States)

    Kovach, Ryan P; Hand, Brian K; Hohenlohe, Paul A; Cosart, Ted F; Boyer, Matthew C; Neville, Helen H; Muhlfeld, Clint C; Amish, Stephen J; Carim, Kellie; Narum, Shawn R; Lowe, Winsor H; Allendorf, Fred W; Luikart, Gordon

    2016-11-30

    Evolutionary and ecological consequences of hybridization between native and invasive species are notoriously complicated because patterns of selection acting on non-native alleles can vary throughout the genome and across environments. Rapid advances in genomics now make it feasible to assess locus-specific and genome-wide patterns of natural selection acting on invasive introgression within and among natural populations occupying diverse environments. We quantified genome-wide patterns of admixture across multiple independent hybrid zones of native westslope cutthroat trout and invasive rainbow trout, the world's most widely introduced fish, by genotyping 339 individuals from 21 populations using 9380 species-diagnostic loci. A significantly greater proportion of the genome appeared to be under selection favouring native cutthroat trout (rather than rainbow trout), and this pattern was pervasive across the genome (detected on most chromosomes). Furthermore, selection against invasive alleles was consistent across populations and environments, even in those where rainbow trout were predicted to have a selective advantage (warm environments). These data corroborate field studies showing that hybrids between these species have lower fitness than the native taxa, and show that these fitness differences are due to selection favouring many native genes distributed widely throughout the genome. © 2016 The Author(s).

  20. A genome-wide association study of COPD identifies a susceptibility locus on chromosome 19q13.

    Science.gov (United States)

    Cho, Michael H; Castaldi, Peter J; Wan, Emily S; Siedlinski, Mateusz; Hersh, Craig P; Demeo, Dawn L; Himes, Blanca E; Sylvia, Jody S; Klanderman, Barbara J; Ziniti, John P; Lange, Christoph; Litonjua, Augusto A; Sparrow, David; Regan, Elizabeth A; Make, Barry J; Hokanson, John E; Murray, Tanda; Hetmanski, Jacqueline B; Pillai, Sreekumar G; Kong, Xiangyang; Anderson, Wayne H; Tal-Singer, Ruth; Lomas, David A; Coxson, Harvey O; Edwards, Lisa D; MacNee, William; Vestbo, Jørgen; Yates, Julie C; Agusti, Alvar; Calverley, Peter M A; Celli, Bartolome; Crim, Courtney; Rennard, Stephen; Wouters, Emiel; Bakke, Per; Gulsvik, Amund; Crapo, James D; Beaty, Terri H; Silverman, Edwin K

    2012-02-15

    The genetic risk factors for chronic obstructive pulmonary disease (COPD) are still largely unknown. To date, genome-wide association studies (GWASs) of limited size have identified several novel risk loci for COPD at CHRNA3/CHRNA5/IREB2, HHIP and FAM13A; additional loci may be identified through larger studies. We performed a GWAS using a total of 3499 cases and 1922 control subjects from four cohorts: the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE); the Normative Aging Study (NAS) and National Emphysema Treatment Trial (NETT); Bergen, Norway (GenKOLS); and the COPDGene study. Genotyping was performed on Illumina platforms with additional markers imputed using 1000 Genomes data; results were summarized using fixed-effect meta-analysis. We identified a new genome-wide significant locus on chromosome 19q13 (rs7937, OR = 0.74, P = 2.9 × 10(-9)). Genotyping this single nucleotide polymorphism (SNP) and another nearby SNP in linkage disequilibrium (rs2604894) in 2859 subjects from the family-based International COPD Genetics Network study (ICGN) demonstrated supportive evidence for association for COPD (P = 0.28 and 0.11 for rs7937 and rs2604894), pre-bronchodilator FEV(1) (P = 0.08 and 0.04) and severe (GOLD 3&4) COPD (P = 0.09 and 0.017). This region includes RAB4B, EGLN2, MIA and CYP2A6, and has previously been identified in association with cigarette smoking behavior.

  1. Genome-Wide Analyses of the Soybean F-Box Gene Family in Response to Salt Stress.

    Science.gov (United States)

    Jia, Qi; Xiao, Zhi-Xia; Wong, Fuk-Ling; Sun, Song; Liang, Kang-Jing; Lam, Hon-Ming

    2017-04-12

    The F-box family is one of the largest gene families in plants that regulate diverse life processes, including salt responses. However, the knowledge of the soybean F-box genes and their roles in salt tolerance remains limited. Here, we conducted a genome-wide survey of the soybean F-box family, and their expression analysis in response to salinity via in silico analysis of online RNA-sequencing (RNA-seq) data and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) to predict their potential functions. A total of 725 potential F-box proteins encoded by 509 genes were identified and classified into 9 subfamilies. The gene structures, conserved domains and chromosomal distributions were characterized. There are 76 pairs of duplicate genes identified, including genome-wide segmental and tandem duplication events, which lead to the expansion of the number of F-box genes. The in silico expression analysis showed that these genes would be involved in diverse developmental functions and play an important role in salt response. Our qRT-PCR analysis confirmed 12 salt-responding F-box genes. Overall, our results provide useful information on soybean F-box genes, especially their potential roles in salt tolerance.

  2. Meta-analyses of genome-wide association studies identify multiple novel loci associated with pulmonary function

    Science.gov (United States)

    Hancock, Dana B.; Eijgelsheim, Mark; Wilk, Jemma B.; Gharib, Sina A.; Loehr, Laura R.; Marciante, Kristin D.; Franceschini, Nora; van Durme, Yannick M.T.A.; Chen, Ting-hsu; Barr, R. Graham; Schabath, Matthew B.; Couper, David J.; Brusselle, Guy G.; Psaty, Bruce M.; van Duijn, Cornelia M.; Rotter, Jerome I.; Uitterlinden, André G.; Hofman, Albert; Punjabi, Naresh M.; Rivadeneira, Fernando; Morrison, Alanna C.; Enright, Paul L.; North, Kari E.; Heckbert, Susan R.; Lumley, Thomas; Stricker, Bruno H.Ch.; O’Connor, George T.; London, Stephanie J.

    2010-01-01

    Measurements of lung function by spirometry are heritable traits that reflect respiratory health and predict morbidity and mortality. We meta-analyzed genome-wide association studies for two clinically important measures, forced expiratory volume in the first second (FEV1) and its ratio to forced vital capacity (FEV1/FVC), an indicator of airflow obstruction. This meta-analysis included 20,890 participants of European ancestry from four CHARGE consortium studies: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health Study (CHS), Framingham Heart Study (FHS), and Rotterdam Study (RS). We identified eight loci associated with FEV1/FVC (HHIP, GPR126, ADAM19, AGER-PPT2, FAM13A, PTCH1, PID1, and HTR4) and one locus associated with FEV1 (INTS12-GSTCD-NPNT) at or near genome-wide significance (PPID1) replicated with the SpiroMeta consortium. Our findings of novel loci influencing pulmonary function may offer insights into chronic lung disease pathogenesis. PMID:20010835

  3. Genome-wide association study of chemotherapeutic agent-induced severe neutropenia/leucopenia for patients in Biobank Japan.

    Science.gov (United States)

    Low, Siew-Kee; Chung, Suyoun; Takahashi, Atsushi; Zembutsu, Hitoshi; Mushiroda, Taisei; Kubo, Michiaki; Nakamura, Yusuke

    2013-08-01

    Chemotherapeutic agents are notoriously known to have a narrow therapeutic range that often results in life-threatening toxicity. Hence, it is clinically important to identify the patients who are at high risk for severe toxicity to certain chemotherapy through a pharmacogenomics approach. In this study, we carried out multiple genome-wide association studies (GWAS) of 13 122 cancer patients who received different chemotherapy regimens, including cyclophosphamide- and platinum-based (cisplatin and carboplatin), anthracycline-based (doxorubicin and epirubicin), and antimetabolite-based (5-fluorouracil and gemcitabine) treatment, antimicrotubule agents (paclitaxel and docetaxel), and topoisomerase inhibitors (camptothecin and etoposide), as well as combination therapy with paclitaxel and carboplatin, to identify genetic variants that are associated with the risk of severe neutropenia/leucopenia in the Japanese population. In addition, we used a weighted genetic risk scoring system to evaluate the cumulative effects of the suggestive genetic variants identified from GWAS in order to predict the risk levels of individuals who carry multiple risk alleles. Although we failed to identify genetic variants that surpassed the genome-wide significance level (P < 5.0 × 10(-8) ) through GWAS, probably due to insufficient statistical power and complex clinical features, we were able to shortlist some of the suggestive associated loci. The current study is at the relatively preliminary stage, but does highlight the complexity and problematic issues associated with retrospective pharmacogenomics studies. However, we hope that verification of these genetic variants through local and international collaborations could improve the clinical outcome for cancer patients.

  4. Genome-wide analysis of signal peptide functionality in Lactobacillus plantarum WCFS1

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    Axelsson Lars

    2009-09-01

    Full Text Available Abstract Background Lactobacillus plantarum is a normal, potentially probiotic, inhabitant of the human gastrointestinal (GI tract. The bacterium has great potential as food-grade cell factory and for in situ delivery of biomolecules. Since protein secretion is important both for probiotic activity and in biotechnological applications, we have carried out a genome-wide experimental study of signal peptide (SP functionality. Results We have constructed a library of 76 Sec-type signal peptides from L. plantarum WCFS1 that were predicted to be cleaved by signal peptidase I. SP functionality was studied using staphylococcal nuclease (NucA as a reporter protein. 82% of the SPs gave significant extracellular NucA activity. Levels of secreted NucA varied by a dramatic 1800-fold and this variation was shown not to be the result of different mRNA levels. For the best-performing SPs all produced NucA was detected in the culture supernatant, but the secretion efficiency decreased for the less well performing SPs. Sequence analyses of the SPs and their cognate proteins revealed four properties that correlated positively with SP performance for NucA: high hydrophobicity, the presence of a transmembrane helix predicted by TMHMM, the absence of an anchoring motif in the cognate protein, and the length of the H+C domain. Analysis of a subset of SPs with a lactobacillal amylase (AmyA showed large variation in production levels and secretion efficiencies. Importantly, there was no correlation between SP performance with NucA and the performance with AmyA. Conclusion This is the first comprehensive experimental study showing that predicted SPs in the L. plantarum genome actually are capable of driving protein secretion. The results reveal considerable variation between the SPs that is at least in part dependent on the protein that is secreted. Several SPs stand out as promising candidates for efficient secretion of heterologous proteins in L. plantarum. The

  5. A genome-wide characterization of microRNA genes in maize.

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    Lifang Zhang

    2009-11-01

    Full Text Available MicroRNAs (miRNAs are small, non-coding RNAs that play essential roles in plant growth, development, and stress response. We conducted a genome-wide survey of maize miRNA genes, characterizing their structure, expression, and evolution. Computational approaches based on homology and secondary structure modeling identified 150 high-confidence genes within 26 miRNA families. For 25 families, expression was verified by deep-sequencing of small RNA libraries that were prepared from an assortment of maize tissues. PCR-RACE amplification of 68 miRNA transcript precursors, representing 18 families conserved across several plant species, showed that splice variation and the use of alternative transcriptional start and stop sites is common within this class of genes. Comparison of sequence variation data from diverse maize inbred lines versus teosinte accessions suggest that the mature miRNAs are under strong purifying selection while the flanking sequences evolve equivalently to other genes. Since maize is derived from an ancient tetraploid, the effect of whole-genome duplication on miRNA evolution was examined. We found that, like protein-coding genes, duplicated miRNA genes underwent extensive gene-loss, with approximately 35% of ancestral sites retained as duplicate homoeologous miRNA genes. This number is higher than that observed with protein-coding genes. A search for putative miRNA targets indicated bias towards genes in regulatory and metabolic pathways. As maize is one of the principal models for plant growth and development, this study will serve as a foundation for future research into the functional roles of miRNA genes.

  6. Genome-Wide Scan for Adaptive Divergence and Association with Population-Specific Covariates.

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    Gautier, Mathieu

    2015-12-01

    In population genomics studies, accounting for the neutral covariance structure across population allele frequencies is critical to improve the robustness of genome-wide scan approaches. Elaborating on the BayEnv model, this study investigates several modeling extensions (i) to improve the estimation accuracy of the population covariance matrix and all the related measures, (ii) to identify significantly overly differentiated SNPs based on a calibration procedure of the XtX statistics, and (iii) to consider alternative covariate models for analyses of association with population-specific covariables. In particular, the auxiliary variable model allows one to deal with multiple testing issues and, providing the relative marker positions are available, to capture some linkage disequilibrium information. A comprehensive simulation study was carried out to evaluate the performances of these different models. Also, when compared in terms of power, robustness, and computational efficiency to five other state-of-the-art genome-scan methods (BayEnv2, BayScEnv, BayScan, flk, and lfmm), the proposed approaches proved highly effective. For illustration purposes, genotyping data on 18 French cattle breeds were analyzed, leading to the identification of 13 strong signatures of selection. Among these, four (surrounding the KITLG, KIT, EDN3, and ALB genes) contained SNPs strongly associated with the piebald coloration pattern while a fifth (surrounding PLAG1) could be associated to morphological differences across the populations. Finally, analysis of Pool-Seq data from 12 populations of Littorina saxatilis living in two different ecotypes illustrates how the proposed framework might help in addressing relevant ecological issues in nonmodel species. Overall, the proposed methods define a robust Bayesian framework to characterize adaptive genetic differentiation across populations. The BayPass program implementing the different models is available at http://www1.montpellier.inra.fr/CBGP/software/baypass/.

  7. Genome-wide analysis of alternative transcripts in human breast cancer

    Science.gov (United States)

    Wen, Ji; Toomer, Kevin H.

    2016-01-01

    Transcript variants play a critical role in diversifying gene expression. Alternative splicing is a major mechanism for generating transcript variants. A number of genes have been implicated in breast cancer pathogenesis with their aberrant expression of alternative transcripts. In this study, we performed genome-wide analyses of transcript variant expression in breast cancer. With RNA-Seq data from 105 patients, we characterized the transcriptome of breast tumors, by pairwise comparison of gene expression in the breast tumor versus matched healthy tissue from each patient. We identified 2839 genes, ~10 % of protein-coding genes in the human genome, that had differential expression of transcript variants between tumors and healthy tissues. The validity of the computational analysis was confirmed by quantitative RT-PCR assessment of transcript variant expression from four top candidate genes. The alternative transcript profiling led to classification of breast cancer into two subgroups and yielded a novel molecular signature that could be prognostic of patients’ tumor burden and survival. We uncovered nine splicing factors (FOX2, MBNL1, QKI, PTBP1, ELAVL1, HNRNPC, KHDRBS1, SFRS2, and TIAR) that were involved in aberrant splicing in breast cancer. Network analyses for the coordinative patterns of transcript variant expression identified twelve “hub” genes that differentiated the cancerous and normal transcriptomes. Dysregulated expression of alternative transcripts may reveal novel biomarkers for tumor development. It may also suggest new therapeutic targets, such as the “hub” genes identified through the network analyses of transcript variant expression, or splicing factors implicated in the formation of the tumor transcriptome. PMID:25913416

  8. A hidden two-locus disease association pattern in genome-wide association studies

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    Xue Hong

    2011-05-01

    Full Text Available Abstract Background Recent association analyses in genome-wide association studies (GWAS mainly focus on single-locus association tests (marginal tests and two-locus interaction detections. These analysis methods have provided strong evidence of associations between genetics variances and complex diseases. However, there exists a type of association pattern, which often occurs within local regions in the genome and is unlikely to be detected by either marginal tests or interaction tests. This association pattern involves a group of correlated single-nucleotide polymorphisms (SNPs. The correlation among SNPs can lead to weak marginal effects and the interaction does not play a role in this association pattern. This phenomenon is due to the existence of unfaithfulness: the marginal effects of correlated SNPs do not express their significant joint effects faithfully due to the correlation cancelation. Results In this paper, we develop a computational method to detect this association pattern masked by unfaithfulness. We have applied our method to analyze seven data sets from the Wellcome Trust Case Control Consortium (WTCCC. The analysis for each data set takes about one week to finish the examination of all pairs of SNPs. Based on the empirical result of these real data, we show that this type of association masked by unfaithfulness widely exists in GWAS. Conclusions These newly identified associations enrich the discoveries of GWAS, which may provide new insights both in the analysis of tagSNPs and in the experiment design of GWAS. Since these associations may be easily missed by existing analysis tools, we can only connect some of them to publicly available findings from other association studies. As independent data set is limited at this moment, we also have difficulties to replicate these findings. More biological implications need further investigation. Availability The software is freely available at http://bioinformatics.ust.hk/hidden_pattern_finder.zip.

  9. Genome-wide fine-scale recombination rate variation in Drosophila melanogaster.

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    Andrew H Chan

    Full Text Available Estimating fine-scale recombination maps of Drosophila from population genomic data is a challenging problem, in particular because of the high background recombination rate. In this paper, a new computational method is developed to address this challenge. Through an extensive simulation study, it is demonstrated that the method allows more accurate inference, and exhibits greater robustness to the effects of natural selection and noise, compared to a well-used previous method developed for studying fine-scale recombination rate variation in the human genome. As an application, a genome-wide analysis of genetic variation data is performed for two Drosophila melanogaster populations, one from North America (Raleigh, USA and the other from Africa (Gikongoro, Rwanda. It is shown that fine-scale recombination rate variation is widespread throughout the D. melanogaster genome, across all chromosomes and in both populations. At the fine-scale, a conservative, systematic search for evidence of recombination hotspots suggests the existence of a handful of putative hotspots each with at least a tenfold increase in intensity over the background rate. A wavelet analysis is carried out to compare the estimated recombination maps in the two populations and to quantify the extent to which recombination rates are conserved. In general, similarity is observed at very broad scales, but substantial differences are seen at fine scales. The average recombination rate of the X chromosome appears to be higher than that of the autosomes in both populations, and this pattern is much more pronounced in the African population than the North American population. The correlation between various genomic features-including recombination rates, diversity, divergence, GC content, gene content, and sequence quality-is examined using the wavelet analysis, and it is shown that the most notable difference between D. melanogaster and humans is in the correlation between

  10. High resolution genome wide binding event finding and motif discovery reveals transcription factor spatial binding constraints.

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    Yuchun Guo

    Full Text Available An essential component of genome function is the syntax of genomic regulatory elements that determine how diverse transcription factors interact to orchestrate a program of regulatory control. A precise characterization of in vivo spacing constraints between key transcription factors would reveal key aspects of this genomic regulatory language. To discover novel transcription factor spatial binding constraints in vivo, we developed a new integrative computational method, genome wide event finding and motif discovery (GEM. GEM resolves ChIP data into explanatory motifs and binding events at high spatial resolution by linking binding event discovery and motif discovery with positional priors in the context of a generative probabilistic model of ChIP data and genome sequence. GEM analysis of 63 transcription factors in 214 ENCODE human ChIP-Seq experiments recovers more known factor motifs than other contemporary methods, and discovers six new motifs for factors with unknown binding specificity. GEM's adaptive learning of binding-event read distributions allows it to further improve upon previous methods for processing ChIP-Seq and ChIP-exo data to yield unsurpassed spatial resolution and discovery of closely spaced binding events of the same factor. In a systematic analysis of in vivo sequence-specific transcription factor binding using GEM, we have found hundreds of spatial binding constraints between factors. GEM found 37 examples of factor binding constraints in mouse ES cells, including strong distance-specific constraints between Klf4 and other key regulatory factors. In human ENCODE data, GEM found 390 examples of spatially constrained pair-wise binding, including such novel pairs as c-Fos:c-Jun/USF1, CTCF/Egr1, and HNF4A/FOXA1. The discovery of new factor-factor spatial constraints in ChIP data is significant because it proposes testable models for regulatory factor interactions that will help elucidate genome function and the

  11. High resolution genome wide binding event finding and motif discovery reveals transcription factor spatial binding constraints.

    Science.gov (United States)

    Guo, Yuchun; Mahony, Shaun; Gifford, David K

    2012-01-01

    An essential component of genome function is the syntax of genomic regulatory elements that determine how diverse transcription factors interact to orchestrate a program of regulatory control. A precise characterization of in vivo spacing constraints between key transcription factors would reveal key aspects of this genomic regulatory language. To discover novel transcription factor spatial binding constraints in vivo, we developed a new integrative computational method, genome wide event finding and motif discovery (GEM). GEM resolves ChIP data into explanatory motifs and binding events at high spatial resolution by linking binding event discovery and motif discovery with positional priors in the context of a generative probabilistic model of ChIP data and genome sequence. GEM analysis of 63 transcription factors in 214 ENCODE human ChIP-Seq experiments recovers more known factor motifs than other contemporary methods, and discovers six new motifs for factors with unknown binding specificity. GEM's adaptive learning of binding-event read distributions allows it to further improve upon previous methods for processing ChIP-Seq and ChIP-exo data to yield unsurpassed spatial resolution and discovery of closely spaced binding events of the same factor. In a systematic analysis of in vivo sequence-specific transcription factor binding using GEM, we have found hundreds of spatial binding constraints between factors. GEM found 37 examples of factor binding constraints in mouse ES cells, including strong distance-specific constraints between Klf4 and other key regulatory factors. In human ENCODE data, GEM found 390 examples of spatially constrained pair-wise binding, including such novel pairs as c-Fos:c-Jun/USF1, CTCF/Egr1, and HNF4A/FOXA1. The discovery of new factor-factor spatial constraints in ChIP data is significant because it proposes testable models for regulatory factor interactions that will help elucidate genome function and the implementation of combinatorial

  12. Genome-Wide Association Study for Indicator Traits of Sexual Precocity in Nellore Cattle

    Science.gov (United States)

    Irano, Natalia; de Camargo, Gregório Miguel Ferreira; Costa, Raphael Bermal; Terakado, Ana Paula Nascimento; Magalhães, Ana Fabrícia Braga; Silva, Rafael Medeiros de Oliveira; Dias, Marina Mortati; Bignardi, Annaiza Braga; Baldi, Fernando; Carvalheiro, Roberto; de Oliveira, Henrique Nunes; de Albuquerque, Lucia Galvão

    2016-01-01

    The objective of this study was to perform a genome-wide association study (GWAS) to detect chromosome regions associated with indicator traits of sexual precocity in Nellore cattle. Data from Nellore animals belonging to farms which participate in the DeltaGen® and Paint® animal breeding programs, were used. The traits used in this study were the occurrence of early pregnancy (EP) and scrotal circumference (SC). Data from 72,675 females and 83,911 males with phenotypes were used; of these, 1,770 females and 1,680 males were genotyped. The SNP effects were estimated with a single-step procedure (WssGBLUP) and the observed phenotypes were used as dependent variables. All animals with available genotypes and phenotypes, in addition to those with only phenotypic information, were used. A single-trait animal model was applied to predict breeding values and the solutions of SNP effects were obtained from these breeding values. The results of GWAS are reported as the proportion of variance explained by windows with 150 adjacent SNPs. The 10 windows that explained the highest proportion of variance were identified. The results of this study indicate the polygenic nature of EP and SC, demonstrating that the indicator traits of sexual precocity studied here are probably controlled by many genes, including some of moderate effect. The 10 windows with large effects obtained for EP are located on chromosomes 5, 6, 7, 14, 18, 21 and 27, and together explained 7.91% of the total genetic variance. For SC, these windows are located on chromosomes 4, 8, 11, 13, 14, 19, 22 and 23, explaining 6.78% of total variance. GWAS permitted to identify chromosome regions associated with EP and SC. The identification of these regions contributes to a better understanding and evaluation of these traits, and permits to indicate candidate genes for future investigation of causal mutations. PMID:27494397

  13. A genome-wide association study identifies five loci influencing facial morphology in Europeans.

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    Fan Liu

    2012-09-01

    Full Text Available Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes--PRDM16, PAX3, TP63, C5orf50, and COL17A1--in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.

  14. Genome-wide analyses reveal a role for peptide hormones in planarian germline development.

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    James J Collins

    Full Text Available Bioactive peptides (i.e., neuropeptides or peptide hormones represent the largest class of cell-cell signaling molecules in metazoans and are potent regulators of neural and physiological function. In vertebrates, peptide hormones play an integral role in endocrine signaling between the brain and the gonads that controls reproductive development, yet few of these molecules have been shown to influence reproductive development in invertebrates. Here, we define a role for peptide hormones in controlling reproductive physiology of the model flatworm, the planarian Schmidtea mediterranea. Based on our observation that defective neuropeptide processing results in defects in reproductive system development, we employed peptidomic and functional genomic approaches to characterize the planarian peptide hormone complement, identifying 51 prohormone genes and validating 142 peptides biochemically. Comprehensive in situ hybridization analyses of prohormone gene expression revealed the unanticipated complexity of the flatworm nervous system and identified a prohormone specifically expressed in the nervous system of sexually reproducing planarians. We show that this member of the neuropeptide Y superfamily is required for the maintenance of mature reproductive organs and differentiated germ cells in the testes. Additionally, comparative analyses of our biochemically validated prohormones with the genomes of the parasitic flatworms Schistosoma mansoni and Schistosoma japonicum identified new schistosome prohormones and validated half of all predicted peptide-encoding genes in these parasites. These studies describe the peptide hormone complement of a flatworm on a genome-wide scale and reveal a previously uncharacterized role for peptide hormones in flatworm reproduction. Furthermore, they suggest new opportunities for using planarians as free-living models for understanding the reproductive biology of flatworm parasites.

  15. Genome-wide association study of metabolic traits reveals novel gene-metabolite-disease links.

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    Rico Rueedi

    2014-02-01

    Full Text Available Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. Here, we report results from a metabolome- and genome-wide association study on (1H-NMR urine metabolic profiles. The study was conducted within an untargeted approach, employing a novel method for compound identification. From our discovery cohort of 835 Caucasian individuals who participated in the CoLaus study, we identified 139 suggestively significant (P<5×10(-8 and independent associations between single nucleotide polymorphisms (SNP and metabolome features. Fifty-six of these associations replicated in the TasteSensomics cohort, comprising 601 individuals from São Paulo of vastly diverse ethnic background. They correspond to eleven gene-metabolite associations, six of which had been previously identified in the urine metabolome and three in the serum metabolome. Our key novel findings are the associations of two SNPs with NMR spectral signatures pointing to fucose (rs492602, P = 6.9×10(-44 and lysine (rs8101881, P = 1.2×10(-33, respectively. Fine-mapping of the first locus pinpointed the FUT2 gene, which encodes a fucosyltransferase enzyme and has previously been associated with Crohn's disease. This implicates fucose as a potential prognostic disease marker, for which there is already published evidence from a mouse model. The second SNP lies within the SLC7A9 gene, rare mutations of which have been linked to severe kidney damage. The replication of previous associations and our new discoveries demonstrate the potential of untargeted metabolomics GWAS to robustly identify molecular disease markers.

  16. Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links

    Science.gov (United States)

    Nicholls, Andrew W.; Salek, Reza M.; Marques-Vidal, Pedro; Morya, Edgard; Sameshima, Koichi; Montoliu, Ivan; Da Silva, Laeticia; Collino, Sebastiano; Martin, François-Pierre; Rezzi, Serge; Steinbeck, Christoph; Waterworth, Dawn M.; Waeber, Gérard; Vollenweider, Peter; Beckmann, Jacques S.; Le Coutre, Johannes; Mooser, Vincent; Bergmann, Sven; Genick, Ulrich K.; Kutalik, Zoltán

    2014-01-01

    Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. Here, we report results from a metabolome- and genome-wide association study on 1H-NMR urine metabolic profiles. The study was conducted within an untargeted approach, employing a novel method for compound identification. From our discovery cohort of 835 Caucasian individuals who participated in the CoLaus study, we identified 139 suggestively significant (P<5×10−8) and independent associations between single nucleotide polymorphisms (SNP) and metabolome features. Fifty-six of these associations replicated in the TasteSensomics cohort, comprising 601 individuals from São Paulo of vastly diverse ethnic background. They correspond to eleven gene-metabolite associations, six of which had been previously identified in the urine metabolome and three in the serum metabolome. Our key novel findings are the associations of two SNPs with NMR spectral signatures pointing to fucose (rs492602, P = 6.9×10−44) and lysine (rs8101881, P = 1.2×10−33), respectively. Fine-mapping of the first locus pinpointed the FUT2 gene, which encodes a fucosyltransferase enzyme and has previously been associated with Crohn's disease. This implicates fucose as a potential prognostic disease marker, for which there is already published evidence from a mouse model. The second SNP lies within the SLC7A9 gene, rare mutations of which have been linked to severe kidney damage. The replication of previous associations and our new discoveries demonstrate the potential of untargeted metabolomics GWAS to robustly identify molecular disease markers. PMID:24586186

  17. Genomic-wide analysis of lymphatic metastasis-associated genes in human hepatocellular carcinoma

    Institute of Scientific and Technical Information of China (English)

    Chun-Feng Lee; Zhi-Qiang Ling; Ting Zhao; Shih-Hua Fang; Weng-Cheng Chang; San-Chih Lee; Kuan-Rong Lee

    2009-01-01

    AIM: To identify the genes related to lymph node metastasis in human hepatocellular carcinoma (HCC), 32 HCC patients with or without lymph node metastasis were investigated by high-throughput microarray comprising 886 genes.METHODS: The samples of cancerous and non-cancerouspaired tissue were taken from 32 patients with HCC who underwent hepatectomy with lymph node dissection. Total RNA was extracted from the cells obtained by means of laser microdissection (LCM) and was amplified by the T7-based amplification system. Then, the amplified samples were applied in the cDNA microarray comprising of 886 genes.RESULTS: The results demonstrated that 25 upregulated genes such as cell membrane receptor,intracellular signaling and cell adhesion related genes,and 48 down-regulated genes such as intracellular signaling and cell cycle regulator-related genes,were correlated with lymph node metastasis in HCC. Amongst them were included some interesting genes, such as MET, EPHA2, CCND1, MMP2, MMP13,CASP3, CDH1, and PTPN2. Expression of 16 genes ( MET, CCND1, CCND2, VEGF, KRT18, RFC4, BIRC5,CDC6, MMP2, BCL2A1, CDH1, VIM, PDGFRA, PTPN2,SLC25A5 and DSP) were further confirmed by real-time quantitative reverse transcriptional polymerase chain reaction (RT-PCR).CONCLUSION: Tumor metastasis is an important biological characteristic, which involves multiple genetic changes and cumulation. This genome-wide information contributes to an improved understanding of molecular alterations during lymph node metastasis in HCC. It may help clinicians to predict metastasis of lymph nodes and assist researchers in identifying novel therapeutic targets for metastatic HCC patients.

  18. Genome-wide definition of the SigF regulon in Mycobacterium tuberculosis.

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    Hartkoorn, Ruben C; Sala, Claudia; Uplekar, Swapna; Busso, Philippe; Rougemont, Jacques; Cole, Stewart T

    2012-04-01

    In Mycobacterium tuberculosis the alternative sigma factor SigF controls the expression of a particular subset of genes by altering RNA polymerase specificity. Here, we utilize two genome-wide approaches to identify SigF-binding sites: chromatin immunoprecipitation (ChIP-on-chip) and microarray analysis of SigF-mediated transcripts. Since SigF is not an abundant protein in the logarithmic phase of growth, a pristinamyin IA-inducible system was used to control its expression. We identified 67 high-affinity SigF-binding sites and 16 loci where a SigF promoter directs the expression of a transcript. These loci include sigF itself, genes involved in lipid and intermediary metabolism and virulence, and at least one transcriptional regulator (Rv2884), possibly acting downstream of SigF. In addition, SigF was also found to direct the transcription of the gene for small RNA F6. Many loci were also found where SigF may be involved in antisense transcription, and in two cases (Rv1358 and Rv1870c) the SigF-dependent promoter was located within the predicted coding sequence. Quantitative PCR confirmed the microarray findings and 5'-rapid amplification of cDNA ends was used to map the SigF-specific transcriptional start points. A canonical SigF consensus promoter sequence GGTTT-N((15-17))-GGGTA was found prior to 11 genes. Together, these data help to define the SigF regulon and show that SigF not only governs expression of proteins such as the virulence factor, HbhA, but also impacts novel functions, such as noncoding RNAs and antisense transcripts.

  19. Genome-Wide Association Mapping and Genomic Selection for Alfalfa (Medicago sativa) Forage Quality Traits.

    Science.gov (United States)

    Biazzi, Elisa; Nazzicari, Nelson; Pecetti, Luciano; Brummer, E Charles; Palmonari, Alberto; Tava, Aldo; Annicchiarico, Paolo

    2017-01-01

    Genetic progress for forage quality has been poor in alfalfa (Medicago sativa L.), the most-grown forage legume worldwide. This study aimed at exploring opportunities for marker-assisted selection (MAS) and genomic selection of forage quality traits based on breeding values of parent plants. Some 154 genotypes from a broadly-based reference population were genotyped by genotyping-by-sequencing (GBS), and phenotyped for leaf-to-stem ratio, leaf and stem contents of protein, neutral detergent fiber (NDF) and acid detergent lignin (ADL), and leaf and stem NDF digestibility after 24 hours (NDFD), of their dense-planted half-sib progenies in three growing conditions (summer harvest, full irrigation; summer harvest, suspended irrigation; autumn harvest). Trait-marker analyses were performed on progeny values averaged over conditions, owing to modest germplasm × condition interaction. Genomic selection exploited 11,450 polymorphic SNP markers, whereas a subset of 8,494 M. truncatula-aligned markers were used for a genome-wide association study (GWAS). GWAS confirmed the polygenic control of quality traits and, in agreement with phenotypic correlations, indicated substantially different genetic control of a given trait in stems and leaves. It detected several SNPs in different annotated genes that were highly linked to stem protein content. Also, it identified a small genomic region on chromosome 8 with high concentration of annotated genes associated with leaf ADL, including one gene probably involved in the lignin pathway. Three genomic selection models, i.e., Ridge-regression BLUP, Bayes B and Bayesian Lasso, displayed similar prediction accuracy, whereas SVR-lin was less accurate. Accuracy values were moderate (0.3-0.4) for stem NDFD and leaf protein content, modest for leaf ADL and NDFD, and low to very low for the other traits. Along with previous results for the same germplasm set, this study indicates that GBS data can be exploited to improve both quality traits

  20. Human genome-wide RNAi screen for host factors that modulate intracellular Salmonella growth.

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    Thornbrough, Joshua M; Hundley, Tom; Valdivia, Raphael; Worley, Micah J

    2012-01-01

    Salmonella enterica is a bacterial pathogen of humans that can proliferate within epithelial cells as well as professional phagocytes of the immune system. While much has been learned about the microbial genes that influence the infectious process through decades of intensive research, relatively little is known about the host factors that affect infection. We performed a genome-wide siRNA screen to identify host genes that Salmonella enterica serovar Typhimurium (S. typhimurium) utilizes to facilitate growth within human epithelial cells. In this screen, with siRNAs targeting every predicted gene in the human genome, we identified 252 new human-host-susceptibility factors (HSFs) for S. typhimurium. We also identified 39 genes whose silencing results in increased intracellular growth of S. typhimurium. The HSFs identified are regulated most centrally by NFκB and associate with each other through an extremely dense network of interactions that center around a group of kinases. Most genes identified were not previously appreciated as playing roles in the intracellular lifecycle of S. enterica. Numerous HSFs identified with interesting characteristics that could play plausible roles in mediating intracellular microbial growth are discussed. Importantly, this study reveals significant overlap between the host network that supports S. typhimurium growth within human epithelial cells and the one that promotes the growth of Mycobacterium tuberculosis within human macrophages. In addition to providing much new information about the molecular mechanisms underlying S. enterica-host cell interplay, all 252 HSFs identified are candidates for new anti-microbial targets for controlling S. enterica infections, and some may provide broad-spectrum anti-microbial activity.

  1. Genome-wide identification of genes regulated by the Rcs phosphorelay system in Erwinia amylovora.

    Science.gov (United States)

    Wang, Dongping; Qi, Mingsheng; Calla, Bernarda; Korban, Schuyler S; Clough, Steven J; Cock, Peter J A; Sundin, George W; Toth, Ian; Zhao, Youfu

    2012-01-01

    The exopolysaccharide amylovoran is one of the major pathogenicity factors in Erwinia amylovora, the causal agent of fire blight of apples and pears. We have previously demonstrated that the RcsBCD phosphorelay system is essential for virulence by controlling amylovoran biosynthesis. We have also found that the hybrid sensor kinase RcsC differentially regulates amylovoran production in vitro and in vivo. To further understand how the Rcs system regulates E. amylovora virulence gene expression, we conducted genome-wide microarray analyses to determine the regulons of RcsB and RcsC in liquid medium and on immature pear fruit. Array analyses identified a total of 648 genes differentially regulated by RcsCB in vitro and in vivo. Consistent with our previous findings, RcsB acts as a positive regulator in both conditions, while RcsC positively controls expression of amylovoran biosynthetic genes in vivo but negatively controls expression in vitro. Besides amylovoran biosynthesis and regulatory genes, cell-wall and cell-envelope (membrane) as well as regulatory genes were identified as the major components of the RcsBC regulon, including many novel genes. We have also demonstrated that transcripts of rcsA, rcsC, and rcsD genes but not the rcsB gene were up-regulated when bacterial cells were grown in minimal medium or following infection of pear fruits compared with those grown in Luria Bertani medium. Furthermore, using the genome of E. amylovora ATCC 49946, a hidden Markov model predicted 60 genes with a candidate RcsB binding site in the intergenic region, 28 of which were identified in the microarray assay. Based on these findings as well as previous reported data, a working model has been proposed to illustrate how the Rcs phosphorelay system regulates virulence gene expression in E. amylovora.

  2. Inverted Low-Copy Repeats and Genome Instability—A Genome-Wide Analysis

    Science.gov (United States)

    Dittwald, Piotr; Gambin, Tomasz; Gonzaga-Jauregui, Claudia; Carvalho, Claudia M.B.; Lupski, James R.; Stankiewicz, Paweł; Gambin, Anna

    2013-01-01

    Inverse paralogous low-copy repeats (IP-LCRs) can cause genome instability by nonallelic homologous recombination (NAHR)-mediated balanced inversions. When disrupting a dosage-sensitive gene(s), balanced inversions can lead to abnormal phenotypes. We delineated the genome-wide distribution of IP-LCRs >1 kB in size with >95% sequence identity and mapped the genes, potentially intersected by an inversion, that overlap at least one of the IP-LCRs. Remarkably, our results show that 12.0% of the human genome is potentially susceptible to such inversions and 942 genes, 99 of which are on the X chromosome, are predicted to be disrupted secondary to such an inversion! In addition, IP-LCRs larger than 800 bp with at least 98% sequence identity (duplication/triplication facilitating IP-LCRs, DTIP-LCRs) were recently implicated in the formation of complex genomic rearrangements with a duplication-inverted triplication–duplication (DUP-TRP/INV-DUP) structure by a replication-based mechanism involving a template switch between such inverted repeats. We identified 1,551 DTIP-LCRs that could facilitate DUP-TRP/INV-DUP formation. Remarkably, 1,445 disease-associated genes are at risk of undergoing copy-number gain as they map to genomic intervals susceptible to the formation of DUP-TRP/INV-DUP complex rearrangements. We implicate inverted LCRs as a human genome architectural feature that could potentially be responsible for genomic instability associated with many human disease traits. PMID:22965494

  3. Dissection of the inflammatory bowel disease transcriptome using genome-wide cDNA microarrays.

    Directory of Open Access Journals (Sweden)

    Christine M Costello

    2005-08-01

    Full Text Available BACKGROUND: The differential pathophysiologic mechanisms that trigger and maintain the two forms of inflammatory bowel disease (IBD, Crohn disease (CD, and ulcerative colitis (UC are only partially understood. cDNA microarrays can be used to decipher gene regulation events at a genome-wide level and to identify novel unknown genes that might be involved in perpetuating inflammatory disease progression. METHODS AND FINDINGS: High-density cDNA microarrays representing 33,792 UniGene clusters were prepared. Biopsies were taken from the sigmoid colon of normal controls (n = 11, CD patients (n = 10 and UC patients (n = 10. 33P-radiolabeled cDNA from purified poly(A+ RNA extracted from biopsies (unpooled was hybridized to the arrays. We identified 500 and 272 transcripts differentially regulated in CD and UC, respectively. Interesting hits were independently verified by real-time PCR in a second sample of 100 individuals, and immunohistochemistry was used for exemplary localization. The main findings point to novel molecules important in abnormal immune regulation and the highly disturbed cell biology of colonic epithelial cells in IBD pathogenesis, e.g., CYLD (cylindromatosis, turban tumor syndrome and CDH11 (cadherin 11, type 2. By the nature of the array setup, many of the genes identified were to our knowledge previously uncharacterized, and prediction of the putative function of a subsection of these genes indicate that some could be involved in early events in disease pathophysiology. CONCLUSION: A comprehensive set of candidate genes not previously associated with IBD was revealed, which underlines the polygenic and complex nature of the disease. It points out substantial differences in pathophysiology between CD and UC. The multiple unknown genes identified may stimulate new research in the fields of barrier mechanisms and cell signalling in the context of IBD, and ultimately new therapeutic approaches.

  4. Genome-wide analysis and molecular dissection of the SPL gene family in Salvia miltiorrhiza

    Institute of Scientific and Technical Information of China (English)

    Linsu Zhang; Bin Wu; Degang Zhao; Caili Li; Fenjuan Shao; Shanfa Lu

    2014-01-01

    SQUAMOSA promoter binding protein-likes (SPLs) are plant-specific transcription factors playing vital regulatory roles in plant growth and development. There is no information about SPLs in Salvia miltiorrhiza (Danshen), a significant medicinal plant widely used in Traditional Chinese medicine (TCM) for>1,700 years and an emerging model plant for TCM studies. Through genome-wide identification and subsequent molecular cloning, we identified a total 15 SmSPLs with divergent sequence features, gene structures, and motifs. Comparative analysis showed sequence conservation between SmSPLs and their Arabidopsis counterparts. A phylogenetic tree clusters SmSPLs into six groups. Many of the motifs identified commonly exist in a group/subgroup, implying their functional redundancy. Eight SmSPLs were predicted and experimental y validated to be targets of miR156/157. SmSPLs were differen-tial y expressed in various tissues of S. milltiorrhiza. The expression of miR156/157-targeted SmSPLs was increased with the maturation of S. miltiorrhiza, whereas the expression of miR156/157 was decreased, confirming the regulatory roles of miR156/157 in SmSPLs and suggesting the functions of SmSPLs in S. miltiorrhiza development. The expression of miR156/157 was negatively correlated with miR172 during the maturation of S. miltiorrhiza. The results indicate the significance and complexity of SmSPL-, miR156-, and miR172-mediated regula-tion of developmental timing in S. miltiorrhiza.

  5. Fast Genome-Wide QTL Association Mapping on Pedigree and Population Data.

    Science.gov (United States)

    Zhou, Hua; Blangero, John; Dyer, Thomas D; Chan, Kei-Hang K; Lange, Kenneth; Sobel, Eric M

    2017-04-01

    Since most analysis software for genome-wide association studies (GWAS) currently exploit only unrelated individuals, there is a need for efficient applications that can handle general pedigree data or mixtures of both population and pedigree data. Even datasets thought to consist of only unrelated individuals may include cryptic relationships that can lead to false positives if not discovered and controlled for. In addition, family designs possess compelling advantages. They are better equipped to detect rare variants, control for population stratification, and facilitate the study of parent-of-origin effects. Pedigrees selected for extreme trait values often segregate a single gene with strong effect. Finally, many pedigrees are available as an important legacy from the era of linkage analysis. Unfortunately, pedigree likelihoods are notoriously hard to compute. In this paper, we reexamine the computational bottlenecks and implement ultra-fast pedigree-based GWAS analysis. Kinship coefficients can either be based on explicitly provided pedigrees or automatically estimated from dense markers. Our strategy (a) works for random sample data, pedigree data, or a mix of both; (b) entails no loss of power; (c) allows for any number of covariate adjustments, including correction for population stratification; (d) allows for testing SNPs under additive, dominant, and recessive models; and (e) accommodates both univariate and multivariate quantitative traits. On a typical personal computer (six CPU cores at 2.67 GHz), analyzing a univariate HDL (high-density lipoprotein) trait from the San Antonio Family Heart Study (935,392 SNPs on 1,388 individuals in 124 pedigrees) takes less than 2 min and 1.5 GB of memory. Complete multivariate QTL analysis of the three time-points of the longitudinal HDL multivariate trait takes less than 5 min and 1.5 GB of memory. The algorithm is implemented as the Ped-GWAS Analysis (Option 29) in the Mendel statistical genetics package, which is

  6. Meta-analysis of genome-wide association studies identifies ten loci influencing allergic sensitization

    NARCIS (Netherlands)

    Bonnelykke, Klaus; Matheson, Melanie C.; Pers, Tune H.; Granell, Raquel; Strachan, David P.; Alves, Alexessander Couto; Linneberg, Allan; Curtin, John A.; Warrington, Nicole M.; Standl, Marie; Kerkhof, Marjan; Jonsdottir, Ingileif; Bukvic, Blazenka K.; Kaakinen, Marika; Sleimann, Patrick; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Schramm, Katharina; Baltic, Svetlana; Kreiner-Moller, Eskil; Simpson, Angela; St Pourcain, Beate; Coin, Lachlan; Hui, Jennie; Walters, Eugene H.; Tiesler, Carla M. T.; Duffy, David L.; Jones, Graham; Ring, Susan M.; McArdle, Wendy L.; Price, Loren; Robertson, Colin F.; Pekkanen, Juha; Tang, Clara S.; Thiering, Elisabeth; Montgomery, Grant W.; Hartikainen, Anna-Liisa; Dharmage, Shyamali C.; Husemoen, Lise L.; Herder, Christian; Kemp, John P.; Elliot, Paul; James, Alan; Waldenberger, Melanie; Abramson, Michael J.; Fairfax, Benjamin P.; Knight, Julian C.; Gupta, Ramneek; Thompson, Philip J.; Holt, Patrick; Sly, Peter; Hirschhorn, Joel N.; Blekic, Mario; Weidinger, Stephan; Hakonarsson, Hakon; Stefansson, Kari; Heinrich, Joachim; Postma, Dirkje S.; Custovic, Adnan; Pennell, Craig E.; Jarvelin, Marjo-Riitta; Koppelman, Gerard H.; Timpson, Nicholas; Ferreira, Manuel A.; Bisgaard, Hans; Henderson, A. John

    2013-01-01

    Allergen-specific immunoglobulin E (present in allergic sensitization) has a central role in the pathogenesis of allergic disease. We performed the first large-scale genome-wide association study (GWAS) of allergic sensitization in 5,789 affected individuals and 10,056 controls and followed up the t

  7. Genome-wide association analysis identifies three new breast cancer susceptibility loci

    NARCIS (Netherlands)

    Ghoussaini, M.; Fletcher, O.; Michailidou, K.; Turnbull, C.; Schmidt, M.K.; Dicks, E.; Dennis, J.; Wang, Q.; Humphreys, M.K.; Luccarini, C.; Baynes, C.; Conroy, D.; Maranian, M.; Ahmed, S.; Driver, K.; Johnson, N.; Orr, N.; dos Santos Silva, I.; Waisfisz, Q.; Meijers-Heijboer, H.; Uitterlinden, A.G.; Rivadeneira, F.; Hall, P.; Czene, K.; Irwanto, A.; Liu, J.; Nevanlinna, H.; Aittomaki, K.; Blomqvist, C.; Meindl, A.; Schmutzler, R.K.; Muller-Myhsok, B.; Lichtner, P.; Chang-Claude, J.; Hein, R.; Nickels, S.; Flesch-Janys, D.; Tsimiklis, H.; Makalic, E.; Schmidt, D.; Bui, M.; Hopper, J.L.; Apicella, C.; Park, D.J.; Southey, M.; Hunter, D.J.; Chanock, S.J.; Broeks, A.; Verhoef, S.; Hogervorst, F.B.; Fasching, P.A.; Lux, M.P.; Beckmann, M.W.; Ekici, A.B.; Sawyer, E.; Tomlinson, I.; Kerin, M.; Marme, F.; Schneeweiss, A.; Sohn, C.; Burwinkel, B.; Guenel, P.; Truong, T.; Cordina-Duverger, E.; Menegaux, F.; Bojesen, S.E.; Nordestgaard, B.G.; Nielsen, S.F.; Flyger, H.; Milne, R.L.; Alonso, M.R.; Gonzalez-Neira, A.; Benitez, J.; Anton-Culver, H.; Ziogas, A.; Bernstein, L.; Dur, C.C.; Brenner, H.; Muller, H.; Arndt, V.; Stegmaier, C.; Justenhoven, C.; Brauch, H.; Bruning, T.; Wang-Gohrke, S.; Eilber, U.; Dork, T.; Schurmann, P.; Bremer, M.; Hillemanns, P.; Bogdanova, N.V.; Antonenkova, N.N.; Rogov, Y.I.; Karstens, J.H.; Bermisheva, M.; Prokofieva, D.; Ligtenberg, M.J.

    2012-01-01

    Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for approximately 8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies

  8. Genome-wide association analysis identifies three new breast cancer susceptibility loci

    DEFF Research Database (Denmark)

    Ghoussaini, Maya; Fletcher, Olivia; Michailidou, Kyriaki

    2012-01-01

    Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ∼8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies (GWAS) in ...

  9. Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma

    NARCIS (Netherlands)

    Chambers, John C; Zhang, Weihua; Sehmi, Joban; Li, Xinzhong; Wass, Mark N; Van der Harst, Pim; Holm, Hilma; Sanna, Serena; Kavousi, Maryam; Baumeister, Sebastian E; Coin, Lachlan J; Deng, Guohong; Gieger, Christian; Heard-Costa, Nancy L; Hottenga, Jouke-Jan; Kühnel, Brigitte; Kumar, Vinod; Lagou, Vasiliki; Liang, Liming; Luan, Jian'an; Vidal, Pedro Marques; Mateo Leach, Irene; O'Reilly, Paul F; Peden, John F; Rahmioglu, Nilufer; Soininen, Pasi; Speliotes, Elizabeth K; Yuan, Xin; Thorleifsson, Gudmar; Alizadeh, Behrooz Z; Atwood, Larry D; Borecki, Ingrid B; Brown, Morris J; Charoen, Pimphen; Cucca, Francesco; Das, Debashish; de Geus, Eco J C; Dixon, Anna L; Döring, Angela; Ehret, Georg; Eyjolfsson, Gudmundur I; Farrall, Martin; Forouhi, Nita G; Friedrich, Nele; Goessling, Wolfram; Gudbjartsson, Daniel F; Harris, Tamara B; Hartikainen, Anna-Liisa; Heath, Simon; Hirschfield, Gideon M; Hofman, Albert; Homuth, Georg; Hyppönen, Elina; Janssen, Harry L A; Johnson, Toby; Kangas, Antti J; Kema, Ido P; Kühn, Jens P; Lai, Sandra; Lathrop, Mark; Lerch, Markus M; Li, Yun; Liang, T Jake; Lin, Jing-Ping; Loos, Ruth J F; Martin, Nicholas G; Moffatt, Miriam F; Montgomery, Grant W; Munroe, Patricia B; Musunuru, Kiran; Nakamura, Yusuke; O'Donnell, Christopher J; Olafsson, Isleifur; Penninx, Brenda W; Pouta, Anneli; Prins, Bram P; Prokopenko, Inga; Puls, Ralf; Ruokonen, Aimo; Savolainen, Markku J; Schlessinger, David; Schouten, Jeoffrey N L; Seedorf, Udo; Sen-Chowdhry, Srijita; Siminovitch, Katherine A; Smit, Johannes H; Spector, Timothy D; Tan, Wenting; Teslovich, Tanya M; Tukiainen, Taru; Uitterlinden, Andre G; Van der Klauw, Melanie M; Vasan, Ramachandran S; Wallace, Chris; Wallaschofski, Henri; Wichmann, H-Erich; Willemsen, Gonneke; Würtz, Peter; Xu, Chun; Yerges-Armstrong, Laura M; Abecasis, Goncalo R; Ahmadi, Kourosh R; Boomsma, Dorret I; Caulfield, Mark; Cookson, William O; van Duijn, Cornelia M; Froguel, Philippe; Matsuda, Koichi; McCarthy, Mark I; Meisinger, Christa; Mooser, Vincent; Pietiläinen, Kirsi H; Schumann, Gunter; Snieder, Harold; Sternberg, Michael J E; Stolk, Ronald P; Thomas, Howard C; Thorsteinsdottir, Unnur; Uda, Manuela; Waeber, Gérard; Wareham, Nicholas J; Waterworth, Dawn M; Watkins, Hugh; Whitfield, John B; Witteman, Jacqueline C M; Wolffenbuttel, Bruce H R; Fox, Caroline S; Ala-Korpela, Mika; Stefansson, Kari; Vollenweider, Peter; Völzke, Henry; Schadt, Eric E; Scott, James; Järvelin, Marjo-Riitta; Elliott, Paul; Kooner, Jaspal S

    2011-01-01

    Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10(-8) to P = 10(-190))

  10. Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways

    DEFF Research Database (Denmark)

    O'Dushlaine, Colm; Rossin, Lizzy; Lee, Phil H.

    2015-01-01

    Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from ...

  11. Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways

    NARCIS (Netherlands)

    O'Dushlaine, Colm; Rossin, Lizzy; Lee, Phil H.; Duncan, Laramie; Parikshak, Neelroop N.; Newhouse, Stephen; Ripke, Stephan; Neale, Benjamin M.; Purcell, Shaun M.; Posthuma, Danielle; Nurnberger, John I.; Lee, S. Hong; Faraone, Stephen V.; Perlis, Roy H.; Mowry, Bryan J.; Thapar, Anita; Goddard, Michael E.; Witte, John S.; Absher, Devin; Agartz, Ingrid; Akil, Huda; Amin, Farooq; Andreassen, Ole A.; Anjorin, Adebayo; Anney, Richard; Anttila, Verneri; Arking, Dan E.; Asherson, Philip; Azevedo, Maria H.; Backlund, Lena; Badner, Judith A.; Bailey, Anthony J.; Banaschewski, Tobias; Barchas, Jack D.; Barnes, Michael R.; Barrett, Thomas B.; Bass, Nicholas; Battaglia, Agatino; Bauer, Michael; Bayes, Monica; Bellivier, Frank; Bergen, Sarah E.; Berrettini, Wade; Betancur, Catalina; Bettecken, Thomas; Biederman, Joseph; Binder, Elisabeth B.; Black, Donald W.; Blackwood, Douglas H. R.; Bloss, Cinnamon S.; Boehnke, Michael; Boomsma, Dorret I.; Breuer, Rene; Bruggeman, Richard; Cormican, Paul; Buccola, Nancy G.; Buitelaar, Jan K.; Bunney, William E.; Buxbaum, Joseph D.; Byerley, William F.; Byrne, Enda M.; Caesar, Sian; Cahn, Wiepke; Cantor, Rita M.; Casas, Miguel; Chakravarti, Aravinda; Chambert, Kimberly; Choudhury, Khalid; Cichon, Sven; Mattheisen, Manuel; Cloninger, C. Robert; Collier, David A.; Cook, Edwin H.; Coon, Hilary; Cormand, Bru; Corvin, Aiden; Coryell, William H.; Craig, David W.; Craig, Ian W.; Crosbie, Jennifer; Cuccaro, Michael L.; Curtis, David; Czamara, Darina; Datta, Susmita; Dawson, Geraldine; Day, Richard; De Geus, Eco J.; Degenhardt, Franziska; Djurovic, Srdjan; Donohoe, Gary J.; Doyle, Alysa E.; Duan, Jubao; Dudbridge, Frank; Duketis, Eftichia; Ebstein, Richard P.; Edenberg, Howard J.; Elia, Josephine; Ennis, Sean; Etain, Bruno; Fanous, Ayman; Farmer, Anne E.; Ferrier, I. Nicol; Flicldnger, Matthew; Fombonne, Eric; Foroud, Tatiana; Frank, Josef; Franke, Barbara; Fraser, Christine; Freedman, Robert; Freimer, Nelson B.; Freitag, Christine M.; Friedl, Marion; Frisen, Louise; Gailagher, Louise; Gejman, Pablo V.; Georgieva, Lyudmila; Gershon, Elliot S.; Giegling, Ina; Gill, Michael; Gordon, Scott D.; Gordon-Smith, Katherine; Green, Elaine K.; Greenwood, Tiffany A.; Grice, Dorothy E.; Gross, Magdalena; Grozeva, Detelina; Guan, Weihua; Gurling, Hugh; De Haan, Lieuwe; Haines, Jonathan L.; Hakonarson, Hakon; Hallmayer, Joachim; Hamilton, Steven P.; Hamshere, Marian L.; Hansen, Thomas F.; Hartmann, Annette M.; Hautzinger, Martin; Heath, Andrew C.; Henders, Anjali K.; Herms, Stefan; Hickie, Ian B.; Hipolito, Maria; Hoefels, Susanne; Holsboer, Florian; Hoogendijk, Witte J.; Hottenga, Jouke-Jan; Hultman, Christina M.; Hus, Vanessa; Ingason, Andres; Ising, Marcus; Jamain, Stephane; Jones, Edward G.; Jones, Ian; Jones, Lisa; Tzeng, Jung-Ying; Kaehler, Anna K.; Kahn, Rene S.; Kandaswamy, Radhika; Keller, Matthew C.; Kennedy, James L.; Kenny, Elaine; Kent, Lindsey; Kim, Yunjung; Kirov, George K.; Klauck, Sabine M.; Klei, Lambertus; Knowles, James A.; Kohli, Martin A.; Koller, Daniel L.; Konte, Bettina; Korszun, Ania; Krabbendam, Lydia; Krasucki, Robert; Kuntsi, Jonna; Kwan, Phoenix; Landen, Mikael; Laengstroem, Niklas; Lathrop, Mark; Lawrence, Jacob; Lawson, William B.; Leboyer, Marion; Ledbetter, David H.; Lencz, Todd; Lesch, Klaus-Peter; Levinson, Douglas F.; Lewis, Cathryn M.; Li, Jun; Lichtenstein, Paul; Lieberman, Jeffrey A.; Lin, Dan-Yu; Linszen, Don H.; Liu, Chunyu; Lohoff, Falk W.; Loo, Sandra K.; Lord, Catherine; Lowe, Jennifer K.; Lucae, Susanne; MacIntyre, Donald J.; Madden, Pamela A. F.; Maestrini, Elena; Magnusson, Patrik K. E.; Mahon, Pamela B.; Maier, Wolfgang; Malhotra, Anil K.; Mane, Shrikant M.; Martin, Christa L.; Martin, Nicholas G.; Matthews, Keith; Mattingsdal, Morten; McCarroll, Steven A.; McGhee, Kevin A.; McGough, James J.; McGrath, Patrick J.; McGuffin, Peter; McInnis, Melvin G.; McIntosh, Andrew; McKinney, Rebecca; McLean, Alan W.; McMahon, Francis J.; McMahon, William M.; McQuillin, Andrew; Medeiros, Helena; Medland, Sarah E.; Meier, Sandra; Melle, Ingrid; Meng, Fan; Meyer, Jobst; Middeldorp, Christel M.; Middleton, Lefkos; Milanova, Vihra; Miranda, Ana; Monaco, Anthony P.; Montgomery, Grant W.; Moran, Jennifer L.; Moreno-De-Luca, Daniel; Morken, Gunnar; Morris, Derek W.; Morrow, Eric M.; Moskvina, Valentina; Muglia, Pierandrea; Muehleisen, Thomas W.; Muir, Walter J.; Mueller-Myhsok, Bertram; Murtha, Michael; Myers, Richard M.; Myin-Germeys, Inez; Neale, Michael C.; Nelson, Stan F.; Nievergelt, Caroline M.; Nikolov, Ivan; Nimgaonkar, Vishwajit; Nolen, Willem A.; Noethen, Markus M.; Nwulia, Evaristus A.; Nyholt, Dale R.; Oades, Robert D.; Olincy, Ann; Oliveira, Guiomar; Olsen, Line; Ophoff, Roel A.; Osby, Urban; Owen, Michael J.; Palotie, Aarno; Parr, Jeremy R.; Paterson, Andrew D.; Pato, Carlos N.; Pato, Michele T.; Penninx, Brenda W.; Pergadia, Michele L.; Pericak-Vance, Margaret A.; Pickard, Benjamin S.; Pimm, Jonathan; Piven, Joseph; Potash, James B.; Poustka, Fritz; Propping, Peter; Puri, Vinay; Quested, Digby J.; Quinn, Emma M.; Ramos-Quiroga, Josep Antoni; Rasmussen, Henrik B.; Raychaudhuri, Soumya; Rehnstroem, Karola; Reif, Andreas; Ribases, Marta; Rice, John P.; Rietschel, Marcella; Roeder, Kathryn; Roeyers, Herbert; Rothenberger, Aribert; Rouleau, Guy; Ruderfer, Douglas; Rujescu, Dan; Sanders, Alan R.; Sanders, Stephan J.; Santangelo, Susan L.; Sergeant, Joseph A.; Schachar, Russell; Schalling, Martin; Schatzberg, Alan F.; Scheftner, William A.; Schellenberg, Gerard D.; Scherer, Stephen W.; Schork, Nicholas J.; Schulze, Thomas G.; Schumacher, Johannes; Schwarz, Markus; Scolnick, Edward; Scott, Laura J.; Shi, Jianxin; Shilling, Paul D.; Shyn, Stanley I.; Silverman, Jeremy M.; Slager, Susan L.; Smalley, Susan L.; Smit, Johannes H.; Smith, Erin N.; Sonuga-Barke, Edmund J. S.; Cair, David St.; State, Matthew; Steffens, Michael; Steinhausen, Hans-Christoph; Strauss, John S.; Strohmaier, Jana; Stroup, T. Scott; Sutdiffe, James S.; Szatmari, Peter; Szelinger, Szabocls; Thirumalai, Srinivasa; Thompson, Robert C.; Todorov, Alexandre A.; Tozzi, Federica; Treutlein, Jens; Uhr, Manfred; Van den Oord, Edwin J. C. G.; Van Grootheest, Gerard; Van Os, Jim; Vicente, Astrid M.; Vieland, Veronica J.; Vincent, John B.; Visscher, Peter M.; Walsh, Christopher A.; Wassink, Thomas H.; Watson, Stanley J.; Weissman, Myrna M.; Werge, Thomas; Wienker, Thomas F.; Wijsman, Ellen M.; Willemsen, Gonneke; Williams, Nigel; Willsey, A. Jeremy; Witt, Stephanie H.; Xu, Wei; Young, Allan H.; Yu, Timothy W.; Zammit, Stanley; Zandi, Peter P.; Zhang, Peng; Zitman, Frans G.; Zoellner, Sebastian; Devlin, Bernie; Kelsoe, John R.; Sklar, Pamela; Daly, Mark J.; O'Donovan, Michael C.; Craddock, Nicholas; Kendler, Kenneth S.; Weiss, Lauren A.; Wray, Naomi R.; Zhao, Zhaoming; Geschwind, Daniel H.; Sullivan, Patrick F.; Smoller, Jordan W.; Holmans, Peter A.; Breen, Gerome

    2015-01-01

    Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from ove

  12. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs

    NARCIS (Netherlands)

    Lee, S. Hong; Ripke, Stephan; Neale, Benjamin M.; Faraone, Stephen V.; Purcell, Shaun M.; Perlis, Roy H.; Mowry, Bryan J.; Thapar, Anita; Goddard, Michael E.; Witte, John S.; Absher, Devin; Agartz, Ingrid; Akil, Huda; Amin, Farooq; Andreassen, Ole A.; Anjorin, Adebayo; Anney, Richard; Anttila, Verneri; Arking, Dan E.; Asherson, Philip; Azevedo, Maria H.; Backlund, Lena; Badner, Judith A.; Bailey, Anthony J.; Banaschewski, Tobias; Barchas, Jack D.; Barnes, Michael R.; Barrett, Thomas B.; Bass, Nicholas; Battaglia, Agatino; Bauer, Michael; Bayes, Monica; Bellivier, Frank; Bergen, Sarah E.; Berrettini, Wade; Betancur, Catalina; Bettecken, Thomas; Biederman, Joseph; Binder, Elisabeth B.; Black, Donald W.; Blackwood, Douglas H. R.; Bloss, Cinnamon S.; Boehnke, Michael; Boomsma, Dorret I.; Breen, Gerome; Breuer, Rene; Bruggeman, Richard; Cormican, Paul; Buccola, Nancy G.; Buitelaar, Jan K.; Bunney, William E.; Buxbaum, Joseph D.; Byerley, William F.; Byrne, Enda M.; Caesar, Sian; Cahn, Wiepke; Cantor, Rita M.; Casas, Miguel; Chakravarti, Aravinda; Chambert, Kimberly; Choudhury, Khalid; Cichon, Sven; Cloninger, C. Robert; Collier, David A.; Cook, Edwin H.; Coon, Hilary; Cormand, Bru; Corvin, Aiden; Coryell, William H.; Craig, David W.; Craig, Ian W.; Crosbie, Jennifer; Cuccaro, Michael L.; Curtis, David; Czamara, Darina; Datta, Susmita; Dawson, Geraldine; Day, Richard; De Geus, Eco J.; Degenhardt, Franziska; Djurovic, Srdjan; Donohoe, Gary J.; Doyle, Alysa E.; Duan, Jubao; Dudbridge, Frank; Duketis, Eftichia; Ebstein, Richard P.; Edenberg, Howard J.; Elia, Josephine; Ennis, Sean; Etain, Bruno; Fanous, Ayman; Farmer, Anne E.; Ferrier, I. Nicol; Flickinger, Matthew; Fombonne, Eric; Foroud, Tatiana; Frank, Josef; Franke, Barbara; Fraser, Christine; Freedman, Robert; Freimer, Nelson B.; Freitag, Christine M.; Friedl, Marion; Frisen, Louise; Gallagher, Louise; Gejman, Pablo V.; Georgieva, Lyudmila; Gershon, Elliot S.; Geschwind, Daniel H.; Giegling, Ina; Gill, Michael; Gordon, Scott D.; Gordon-Smith, Katherine; Green, Elaine K.; Greenwood, Tiffany A.; Grice, Dorothy E.; Gross, Magdalena; Grozeva, Detelina; Guan, Weihua; Gurling, Hugh; De Haan, Lieuwe; Haines, Jonathan L.; Hakonarson, Hakon; Hallmayer, Joachim; Hamilton, Steven P.; Hamshere, Marian L.; Hansen, Thomas F.; Hartmann, Annette M.; Hautzinger, Martin; Heath, Andrew C.; Henders, Anjali K.; Herms, Stefan; Hickie, Ian B.; Hipolito, Maria; Hoefels, Susanne; Holmans, Peter A.; Holsboer, Florian; Hoogendijk, Witte J.; Hottenga, Jouke-Jan; Hultman, Christina M.; Hus, Vanessa; Ingason, Andres; Ising, Marcus; Jamain, Stephane; Jones, Edward G.; Jones, Ian; Jones, Lisa; Tzeng, Jung-Ying; Kaehler, Anna K.; Kahn, Rene S.; Kandaswamy, Radhika; Keller, Matthew C.; Kennedy, James L.; Kenny, Elaine; Kent, Lindsey; Kim, Yunjung; Kirov, George K.; Klauck, Sabine M.; Klei, Lambertus; Knowles, James A.; Kohli, Martin A.; Koller, Daniel L.; Konte, Bettina; Korszun, Ania; Krabbendam, Lydia; Krasucki, Robert; Kuntsi, Jonna; Kwan, Phoenix; Landen, Mikael; Langstrom, Niklas; Lathrop, Mark; Lawrence, Jacob; Lawson, William B.; Leboyer, Marion; Ledbetter, David H.; Lee, Phil H.; Lencz, Todd; Lesch, Klaus-Peter; Levinson, Douglas F.; Lewis, Cathryn M.; Li, Jun; Lichtenstein, Paul; Lieberman, Jeffrey A.; Lin, Dan-Yu; Linszen, Don H.; Liu, Chunyu; Lohoff, Falk W.; Loo, Sandra K.; Lord, Catherine; Lowe, Jennifer K.; Lucae, Susanne; MacIntyre, Donald J.; Madden, Pamela A. F.; Maestrini, Elena; Magnusson, Patrik K. E.; Mahon, Pamela B.; Maier, Wolfgang; Malhotra, Anil K.; Mane, Shrikant M.; Martin, Christa L.; Martin, Nicholas G.; Mattheisen, Manuel; Matthews, Keith; Mattingsdal, Morten; McCarroll, Steven A.; McGhee, Kevin A.; McGough, James J.; McGrath, Patrick J.; McGuffin, Peter; McInnis, Melvin G.; McIntosh, Andrew; McKinney, Rebecca; McLean, Alan W.; McMahon, Francis J.; McMahon, William M.; McQuillin, Andrew; Medeiros, Helena; Medland, Sarah E.; Meier, Sandra; Melle, Ingrid; Meng, Fan; Meyer, Jobst; Middeldorp, Christel M.; Middleton, Lefkos; Milanova, Vihra; Miranda, Ana; Monaco, Anthony P.; Montgomery, Grant W.; Moran, Jennifer L.; Moreno-De-Luca, Daniel; Morken, Gunnar; Morris, Derek W.; Morrow, Eric M.; Moskvina, Valentina; Muglia, Pierandrea; Muehleisen, Thomas W.; Muir, Walter J.; Mueller-Myhsok, Bertram; Murtha, Michael; Myers, Richard M.; Myin-Germeys, Inez; Neale, Michael C.; Nelson, Stan F.; Nievergelt, Caroline M.; Nikolov, Ivan; Nimgaonkar, Vishwajit; Nolen, Willem A.; Noethen, Markus M.; Nurnberger, John I.; Nwulia, Evaristus A.; Nyholt, Dale R.; O'Dushlaine, Colm; Oades, Robert D.; Olincy, Ann; Oliveira, Guiomar; Olsen, Line; Ophoff, Roel A.; Osby, Urban; Owen, Michael J.; Palotie, Aarno; Parr, Jeremy R.; Paterson, Andrew D.; Pato, Carlos N.; Pato, Michele T.; Penninx, Brenda W.; Pergadia, Michele L.; Pericak-Vance, Margaret A.; Pickard, Benjamin S.; Pimm, Jonathan; Piven, Joseph; Posthuma, Danielle; Potash, James B.; Poustka, Fritz; Propping, Peter; Puri, Vinay; Quested, Digby J.; Quinn, Emma M.; Antoni Ramos-Quiroga, Josep; Rasmussen, Henrik B.; Raychaudhuri, Soumya; Rehnstroem, Karola; Reif, Andreas; Ribases, Marta; Rice, John P.; Rietschel, Marcella; Roeder, Kathryn; Roeyers, Herbert; Rossin, Lizzy; Rothenberger, Aribert; Rouleau, Guy; Ruderfer, Douglas; Rujescu, Dan; Sanders, Alan R.; Sanders, Stephan J.; Santangelo, Susan L.; Sergeant, Joseph A.; Schachar, Russell; Schalling, Martin; Schatzberg, Alan F.; Scheftner, William A.; Schellenberg, Gerard D.; Scherer, Stephen W.; Schork, Nicholas J.; Schulze, Thomas G.; Schumacher, Johannes; Schwarz, Markus; Scolnick, Edward; Scott, Laura J.; Shi, Jianxin; Shilling, Paul D.; Shyn, Stanley I.; Silverman, Jeremy M.; Slager, Susan L.; Smalley, Susan L.; Smit, Johannes H.; Smith, Erin N.; Sonuga-Barke, Edmund J. S.; St Clair, David; State, Matthew; Steffens, Michael; Steinhausen, Hans-Christoph; Strauss, John S.; Strohmaier, Jana; Stroup, T. Scott; Sutcliffe, James S.; Szatmari, Peter; Szelinger, Szabocls; Thirumalai, Srinivasa; Thompson, Robert C.; Todorov, Alexandre A.; Tozzi, Federica; Treutlein, Jens; Uhr, Manfred; van den Oord, Edwin J. C. G.; Van Grootheest, Gerard; Van Os, Jim; Vicente, Astrid M.; Vieland, Veronica J.; Vincent, John B.; Visscher, Peter M.; Walsh, Christopher A.; Wassink, Thomas H.; Watson, Stanley J.; Weissman, Myrna M.; Werge, Thomas; Wienker, Thomas F.; Wijsman, Ellen M.; Willemsen, Gonneke; Williams, Nigel; Willsey, A. Jeremy; Witt, Stephanie H.; Xu, Wei; Young, Allan H.; Yu, Timothy W.; Zammit, Stanley; Zandi, Peter P.; Zhang, Peng; Zitman, Frans G.; Zoellner, Sebastian; Devlin, Bernie; Kelsoe, John R.; Sklar, Pamela; Daly, Mark J.; O'Donovan, Michael C.; Craddock, Nicholas; Sullivan, Patrick F.; Smoller, Jordan W.; Kendler, Kenneth S.; Wray, Naomi R.

    2013-01-01

    Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases

  13. Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci

    NARCIS (Netherlands)

    Stahl, Eli A.; Raychaudhuri, Soumya; Remmers, Elaine F.; Xie, Gang; Eyre, Stephen; Thomson, Brian P.; Li, Yonghong; Kurreeman, Fina A. S.; Zhernakova, Alexandra; Hinks, Anne; Guiducci, Candace; Chen, Robert; Alfredsson, Lars; Amos, Christopher I.; Ardlie, Kristin G.; Barton, Anne; Bowes, John; Brouwer, Elisabeth; Burtt, Noel P.; Catanese, Joseph J.; Coblyn, Jonathan; Coenen, Marieke J. H.; Costenbader, Karen H.; Criswell, Lindsey A.; Crusius, J. Bart A.; Cui, Jing; de Bakker, Paul I. W.; De Jager, Philip L.; Ding, Bo; Emery, Paul; Flynn, Edward; Harrison, Pille; Hocking, Lynne J.; Huizinga, Tom W. J.; Kastner, Daniel L.; Ke, Xiayi; Lee, Annette T.; Liu, Xiangdong; Martin, Paul; Morgan, Ann W.; Padyukov, Leonid; Posthumus, Marcel D.; Radstake, Timothy R. D. J.; Reid, David M.; Seielstad, Mark; Seldin, Michael F.; Shadick, Nancy A.; Steer, Sophia; Tak, Paul P.; Thomson, Wendy; van der Helm-van Mil, Annette H. M.; van der Horst-Bruinsma, Irene E.; van der Schoot, C. Ellen; van Riel, Piet L. C. M.; Weinblatt, Michael E.; Wilson, Anthony G.; Wolbink, Gert Jan; Wordsworth, B. Paul; Wijmenga, Cisca; Karlson, Elizabeth W.; Toes, Rene E. M.; de Vries, Niek; Begovich, Ann B.; Worthington, Jane; Siminovitch, Katherine A.; Gregersen, Peter K.; Klareskog, Lars; Plenge, Robert M.

    2010-01-01

    To identify new genetic risk factors for rheumatoid arthritis, we conducted a genome-wide association study meta-analysis of 5,539 autoantibody-positive individuals with rheumatoid arthritis (cases) and 20,169 controls of European descent, followed by replication in an independent set of 6,768 rheum

  14. Genome-wide association study identifies 74 loci associated with educational attainment

    NARCIS (Netherlands)

    Okbay, Aysu; Beauchamp, Jonathan P.; Fontana, Mark Alan; Lee, James J.; Pers, Tune H.; Rietveld, Cornelius A.; Turley, Patrick; Chen, Guo-Bo; Emilsson, Valur; Meddens, S. Fleur W.; Oskarsson, Sven; Pickrell, Joseph K.; Thom, Kevin; Timshel, Pascal; de Vlaming, Ronald; Abdellaoui, Abdel; Ahluwalia, Tarunveer S.; Bacelis, Jonas; Baumbach, Clemens; Bjornsdottir, Gyda; Brandsma, Johannes H.; Concas, Maria Pina; Derringer, Jaime; Furlotte, Nicholas A.; Galesloot, Tessel E.; Girotto, Giorgia; Gupta, Richa; Hall, Leanne M.; Harris, Sarah E.; Hofer, Edith; Horikoshi, Momoko; Huffman, Jennifer E.; Kaasik, Kadri; Kalafati, Ioanna P.; Karlsson, Robert; Kong, Augustine; Lahti, Jari; van der Lee, Sven J.; de Leeuw, Christiaan; Lind, Penelope A.; Lindgren, Karl-Oskar; Liu, Tian; Mangino, Massimo; Marten, Jonathan; Mihailov, Evelin; Miller, Michael B.; van der Most, Peter J.; Oldmeadow, Christopher; Payton, Antony; Pervjakova, Natalia; Peyrot, Wouter J.; Qian, Yong; Raitakari, Olli; Rueedi, Rico; Salvi, Erika; Schmidt, Brge; Schraut, Katharina E.; Shi, Jianxin; Smith, Albert V.; Poot, Raymond A.; St Pourcain, Beate; Teumer, Alexander; Thorleifsson, Gudmar; Verweij, Niek; Vuckovic, Dragana; Wellmann, Juergen; Westra, Harm-Jan; Yang, Jingyun; Zhao, Wei; Zhu, Zhihong; Alizadeh, Behrooz Z.; Amin, Najaf; Bakshi, Andrew; Baumeister, Sebastian E.; Biino, Ginevra; Bonnelykke, Klaus; Boyle, Patricia A.; Campbell, Harry; Cappuccio, Francesco P.; Davies, Gail; De Neve, Jan-Emmanuel; Deloukas, Panos; Demuth, Ilja; Ding, Jun; Eibich, Peter; Eisele, Lewin; Eklund, Niina; Evans, David M.; Faul, Jessica D.; Feitosa, Mary F.; Forstner, Andreas J.; Gandin, Ilaria; Gunnarsson, Bjarni; Halldorsson, Bjarni V.; Harris, Tamara B.; Heath, Andrew C.; Hocking, Lynne J.; Holliday, Elizabeth G.; Homuth, Georg; Horan, Michael A.; Hottenga, Jouke-Jan; de Jager, Philip L.; Joshi, Peter K.; Jugessur, Astanand; Kaakinen, Marika A.; Kahonen, Mika; Kanoni, Stavroula; Keltigangas-Jarvinen, Liisa; Kiemeney, Lambertus A. L. M.; Kolcic, Ivana; Koskinen, Seppo; Kraja, Aldi T.; Kroh, Martin; Kutalik, Zoltan; Latvala, Antti; Launer, Lenore J.; Lebreton, Mael P.; Levinson, Douglas F.; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C. M.; Loukola, Anu; Madden, Pamela A.; Magi, Reedik; Maki-Opas, Tomi; Marioni, Riccardo E.; Marques-Vidal, Pedro; Meddens, Gerardus A.; McMahon, George; Meisinger, Christa; Meitinger, Thomas; Milaneschi, Yusplitri; Milani, Lili; Montgomery, Grant W.; Myhre, Ronny; Nelson, Christopher P.; Nyholt, Dale R.; Ollier, William E. R.; Palotie, Aarno; Paternoster, Lavinia; Pedersen, Nancy L.; Petrovic, Katja E.; Porteous, David J.; Raikkonen, Katri; Ring, Susan M.; Robino, Antonietta; Rostapshova, Olga; Rudan, Igor; Rustichini, Aldo; Salomaa, Veikko; Sanders, Alan R.; Sarin, Antti-Pekka; Schmidt, Helena; Scott, Rodney J.; Smith, Blair H.; Smith, Jennifer A.; Staessen, Jan A.; Steinhagen-Thiessen, Elisabeth; Strauch, Konstantin; Terracciano, Antonio; Tobin, Martin D.; Ulivi, Sheila; Vaccargiu, Simona; Quaye, Lydia; van Rooij, Frank J. A.; Venturini, Cristina; Vinkhuyzen, Anna A. E.; Volker, Uwe; Volzke, Henry; Vonk, Judith M.; Waage, Johannes; Ware, Erin B.; Willemsen, Gonneke; Attia, John R.; Bennett, David A.; Berger, Klaus; Bertram, Lars; Bisgaard, Hans; Boomsma, Dorret I.; Borecki, Ingrid B.; Bultmann, Ute; Chabris, Christopher F.; Cucca, Francesco; Cusi, Daniele; Deary, Ian J.; Dedoussis, George V.; van Duijn, Cornelia M.; Eriksson, Johan G.; Franke, Barbara; Franke, Lude; Gasparini, Paolo; Gejman, Pablo V.; Gieger, Christian; Grabe, Hans-Jorgen; Gratten, Jacob; Groenen, Patrick J. F.; Gudnason, Vilmundur; van der Harst, Pim; Hayward, Caroline; Hinds, David A.; Hoffmann, Wolfgang; Hyppnen, Elina; Iacono, William G.; Jacobsson, Bo; Jarvelin, Marjo-Riitta; Jockel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L. R.; Lehtimaki, Terho; Lehrer, Steven F.; Magnusson, Patrik K. E.; Martin, Nicholas G.; McGue, Matt; Metspalu, Andres; Pendleton, Neil; Penninx, Brenda W. J. H.; Perola, Markus; Pirastu, Nicola; Pirastu, Mario; Polasek, Ozren; Posthuma, Danielle; Power, Christine; Province, Michael A.; Samani, Nilesh J.; Schlessinger, David; Schmidt, Reinhold; Sorensen, Thorkild I. A.; Spector, Tim D.; Stefansson, Kari; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tiemeier, Henning; Tung, Joyce Y.; Uitterlinden, Andre G.; Vitart, Veronique; Vollenweider, Peter; Weir, David R.; Wilson, James F.; Wright, Alan F.; Conley, Dalton C.; Krueger, Robert F.; Smith, George Davey; Hofman, Albert; Laibson, David I.; Medland, Sarah E.; Meyer, Michelle N.; Yang, Jian; Johannesson, Magnus; Visscher, Peter M.; Esko, Tonu; Koellinger, Philipp D.; Cesarini, David; Benjamin, Daniel J.

    2016-01-01

    Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals(1). Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends

  15. Genome-wide meta-analysis identifies new susceptibility loci for migraine

    NARCIS (Netherlands)

    Anttila, Verneri; Winsvold, Bendik S.; Gormley, Padhraig; Kurth, Tobias; Bettella, Francesco; McMahon, George; Kallela, Mikko; Malik, Rainer; de Vries, Boukje; Terwindt, Gisela; Medland, Sarah E.; Todt, Unda; McArdle, Wendy L.; Quaye, Lydia; Koiranen, Markku; Ikram, M. Arfan; Lehtimaki, Terho; Stam, Anine H.; Ligthart, Lannie; Wedenoja, Juho; Dunham, Ian; Neale, Benjamin M.; Palta, Priit; Hamalainen, Eija; Schuerks, Markus; Rose, Lynda M.; Buring, Julie E.; Ridker, Paul M.; Steinberg, Stacy; Stefansson, Hreinn; Jakobsson, Finnbogi; Lawlor, Debbie A.; Evans, David M.; Ring, Susan M.; Farkkila, Markus; Artto, Ville; Kaunisto, Mari A.; Freilinger, Tobias; Schoenen, Jean; Frants, Rune R.; Pelzer, Nadine; Weller, Claudia M.; Zielman, Ronald; Heath, Andrew C.; Madden, Pamela A. F.; Montgomery, Grant W.; Martin, Nicholas G.; Borck, Guntram; Goebel, Hartmut; Heinze, Axel; Heinze-Kuhn, Katja; Williams, Frances M. K.; Hartikainen, Anna-Liisa; Pouta, Anneli; van den Ende, Joyce; Uitterlinden, Andre G.; Hofman, Albert; Amin, Najaf; Hottenga, Jouke-Jan; Vink, Jacqueline M.; Heikkila, Kauko; Alexander, Michael; Muller-Myhsok, Bertram; Schreiber, Stefan; Meitinger, Thomas; Wichmann, Heinz Erich; Aromaa, Arpo; Eriksson, Johan G.; Traynor, Bryan J.; Trabzuni, Daniah; Rossin, Elizabeth; Lage, Kasper; Jacobs, Suzanne B. R.; Gibbs, J. Raphael; Birney, Ewan; Kaprio, Jaakko; Penninx, Brenda W.; Boomsma, Dorret I.; van Duijn, Cornelia; Raitakari, Olli; Jarvelin, Marjo-Riitta; Zwart, John-Anker; Cherkas, Lynn; Strachan, David P.; Kubisch, Christian; Ferrari, Michel D.; van den Maagdenberg, Arn M. J. M.; Dichgans, Martin; Wessman, Maija; Smith, George Davey; Stefansson, Kari; Daly, Mark J.; Nyholt, Dale R.; Chasman, Daniel I.; Palotie, Aarno

    2013-01-01

    Migraine is the most common brain disorder, affecting approximately 14% of the adult population, but its molecular mechanisms are poorly understood. We report the results of a meta-analysis across 29 genome-wide association studies, including a total of 23,285 individuals with migraine (cases) and 9

  16. Genome-wide association analyses identify 18 new loci associated with serum urate concentrations

    NARCIS (Netherlands)

    Köttgen, Anna; Albrecht, Eva; Teumer, Alexander; Vitart, Veronique; Krumsiek, Jan; Hundertmark, Claudia; Pistis, Giorgio; Ruggiero, Daniela; O'Seaghdha, Conall M; Haller, Toomas; Yang, Qiong; Tanaka, Toshiko; Johnson, Andrew D; Kutalik, Zoltán; Smith, Albert V; Shi, Julia; Struchalin, Maksim; Middelberg, Rita P S; Brown, Morris J; Gaffo, Angelo L; Pirastu, Nicola; Li, Guo; Hayward, Caroline; Zemunik, Tatijana; Huffman, Jennifer; Yengo, Loic; Zhao, Jing Hua; Demirkan, Ayse; Feitosa, Mary F; Liu, Xuan; Malerba, Giovanni; Lopez, Lorna M; van der Harst, Pim; Li, Xinzhong; Kleber, Marcus E; Hicks, Andrew A; Nolte, Ilja M; Johansson, Asa; Murgia, Federico; Wild, Sarah H; Bakker, Stephan J L; Peden, John F; Dehghan, Abbas; Steri, Maristella; Tenesa, Albert; Lagou, Vasiliki; Salo, Perttu; Mangino, Massimo; Rose, Lynda M; Lehtimäki, Terho; Woodward, Owen M; Okada, Yukinori; Tin, Adrienne; Müller, Christian; Oldmeadow, Christopher; Putku, Margus; Czamara, Darina; Kraft, Peter; Frogheri, Laura; Thun, Gian Andri; Grotevendt, Anne; Gislason, Gauti Kjartan; Harris, Tamara B; Launer, Lenore J; McArdle, Patrick; Shuldiner, Alan R; Boerwinkle, Eric; Coresh, Josef; Schmidt, Helena; Schallert, Michael; Martin, Nicholas G; Montgomery, Grant W; Kubo, Michiaki; Nakamura, Yusuke; Tanaka, Toshihiro; Munroe, Patricia B; Samani, Nilesh J; Jacobs, David R; Liu, Kiang; D'Adamo, Pio; Ulivi, Sheila; Rotter, Jerome I; Psaty, Bruce M; Vollenweider, Peter; Waeber, Gerard; Campbell, Susan; Devuyst, Olivier; Navarro, Pau; Kolcic, Ivana; Hastie, Nicholas; Balkau, Beverley; Froguel, Philippe; Esko, Tõnu; Salumets, Andres; Khaw, Kay Tee; Langenberg, Claudia; Wareham, Nicholas J; Isaacs, Aaron; Kraja, Aldi; Zhang, Qunyuan; Wild, Philipp S; Scott, Rodney J; Holliday, Elizabeth G; Org, Elin; Viigimaa, Margus; Bandinelli, Stefania; Metter, Jeffrey E; Lupo, Antonio; Trabetti, Elisabetta; Sorice, Rossella; Döring, Angela; Lattka, Eva; Strauch, Konstantin; Theis, Fabian; Waldenberger, Melanie; Wichmann, H-Erich; Davies, Gail; Gow, Alan J; Bruinenberg, Marcel; Stolk, Ronald P; Kooner, Jaspal S; Zhang, Weihua; Winkelmann, Bernhard R; Boehm, Bernhard O; Lucae, Susanne; Penninx, Brenda W; Smit, Johannes H; Curhan, Gary; Mudgal, Poorva; Plenge, Robert M; Portas, Laura; Persico, Ivana; Kirin, Mirna; Wilson, James F; Mateo Leach, Irene; van Gilst, Wiek H; Goel, Anuj; Ongen, Halit; Hofman, Albert; Rivadeneira, Fernando; Uitterlinden, Andre G; Imboden, Medea; von Eckardstein, Arnold; Cucca, Francesco; Nagaraja, Ramaiah; Piras, Maria Grazia; Nauck, Matthias; Schurmann, Claudia; Budde, Kathrin; Ernst, Florian; Farrington, Susan M; Theodoratou, Evropi; Prokopenko, Inga; Stumvoll, Michael; Jula, Antti; Perola, Markus; Salomaa, Veikko; Shin, So-Youn; Spector, Tim D; Sala, Cinzia; Ridker, Paul M; Kähönen, Mika; Viikari, Jorma; Hengstenberg, Christian; Nelson, Christopher P; Meschia, James F; Nalls, Michael A; Sharma, Pankaj; Singleton, Andrew B; Kamatani, Naoyuki; Zeller, Tanja; Burnier, Michel; Attia, John; Laan, Maris; Klopp, Norman; Hillege, Hans L; Kloiber, Stefan; Choi, Hyon; Pirastu, Mario; Tore, Silvia; Probst-Hensch, Nicole M; Völzke, Henry; Gudnason, Vilmundur; Parsa, Afshin; Schmidt, Reinhold; Whitfield, John B; Fornage, Myriam; Gasparini, Paolo; Siscovick, David S; Polašek, Ozren; Campbell, Harry; Rudan, Igor; Bouatia-Naji, Nabila; Metspalu, Andres; Loos, Ruth J F; van Duijn, Cornelia M; Borecki, Ingrid B; Ferrucci, Luigi; Gambaro, Giovanni; Deary, Ian J; Wolffenbuttel, Bruce H R; Chambers, John C; März, Winfried; Pramstaller, Peter P; Snieder, Harold; Gyllensten, Ulf; Wright, Alan F; Navis, Gerjan; Watkins, Hugh; Witteman, Jacqueline C M; Sanna, Serena; Schipf, Sabine; Dunlop, Malcolm G; Tönjes, Anke; Ripatti, Samuli; Soranzo, Nicole; Toniolo, Daniela; Chasman, Daniel I; Raitakari, Olli; Kao, W H Linda; Ciullo, Marina; Fox, Caroline S; Caulfield, Mark; Bochud, Murielle; Gieger, Christian

    2013-01-01

    Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with se

  17. Novel loci associated with usual sleep duration: The CHARGE Consortium Genome-Wide Association Study

    NARCIS (Netherlands)

    Gottlieb, D.J.; Hek, K.; Chen, T.H.; Watson, N.F.; Eiriksdottir, G.; Byrne, E.M.; Cornelis, M.; Warby, S.C.; Bandinelli, S.; Cherkas, L.; Evans, D.S.; Grabe, H.J.; Lahti, J.; Li, M.; Lehtimaki, T.; Lumley, T.; Marciante, K.D.; Pérusse, L.; Psaty, B.M.; Robbins, J.; Tranah, G.J.; Vink, J.M.; Wilk, J.B.; Stafford, J.M.; Bellis, C.; Biffar, R.; Bouchard, C.; Cade, B.; Curhan, G.C.; Eriksson, J.G.; Ewert, R.; Ferrucci, L.; Fulop, T.; Gehrman, P.R.; Goodloe, R.; Harris, T.B.; Heath, A.C.; Hernandez, D.G.; Hofman, A.; Hottenga, J.J.; Hunter, D.J.; Jensen, M.K.; Johnson, A.D.; Kahonen, M.; Kao, L.; Kraft, P.; Larkin, E.K.; Lauderdale, D.S.; Luik, A.I.; Medici, M.; Montgomery, G.W.; Palotie, A.; Patel, S.R.; Pistis, G.; Porcu, E.; Quaye, L.; Raitakari, O.; Redline, S.; Rimm, E.B.; Rotter, J.I.; Smith, A.V.; Spector, T.D.; Teumer, A.; Uitterlinden, A.G.; Vohl, M.C.; Widen, E.; Willemsen, G.; Young, T.; Zhang, X.; Liu, Y.; Blangero, J.; Boomsma, D.I.; Gudnason, V.; Hu, F.; Mangino, M.; Martin, N.G.; O'Connor, G.T.; Stone, K.L.; Tanaka, T.; Viikari, J.; Gharib, S.A.; Punjabi, N.M.; Raikkonen, K.; Völzke, H.; Mignot, E.; Tiemeier, H.

    2015-01-01

    Usual sleep duration is a heritable trait correlated with psychiatric morbidity, cardiometabolic disease and mortality, although little is known about the genetic variants influencing this trait. A genome-wide association study (GWAS) of usual sleep duration was conducted using 18 population-based

  18. Meta-analysis of genome-wide association studies discovers multiple loci for chronic lymphocytic leukemia

    NARCIS (Netherlands)

    Berndt, Sonja I; Camp, Nicola J; Skibola, Christine F; Vijai, Joseph; Wang, Zhaoming; Gu, Jian; Nieters, Alexandra; Kelly, Rachel S; Smedby, Karin E; Monnereau, Alain; Cozen, Wendy; Cox, Angela; Wang, Sophia S; Lan, Qing; Teras, Lauren R; Machado, Moara; Yeager, Meredith; Brooks-Wilson, Angela R; Hartge, Patricia; Purdue, Mark P; Birmann, Brenda M; Vajdic, Claire M; Cocco, Pierluigi; Zhang, Yawei; Giles, Graham G; Zeleniuch-Jacquotte, Anne; Lawrence, Charles; Montalvan, Rebecca; Burdett, Laurie; Hutchinson, Amy; Ye, Yuanqing; Call, Timothy G; Shanafelt, Tait D; Novak, Anne J; Kay, Neil E; Liebow, Mark; Cunningham, Julie M; Allmer, Cristine; Hjalgrim, Henrik; Adami, Hans-Olov; Melbye, Mads; Glimelius, Bengt; Chang, Ellen T; Glenn, Martha; Curtin, Karen; Cannon-Albright, Lisa A; Diver, W Ryan; Link, Brian K; Weiner, George J; Conde, Lucia; Bracci, Paige M; Riby, Jacques; Arnett, Donna K; Zhi, Degui; Leach, Justin M; Holly, Elizabeth A; Jackson, Rebecca D; Tinker, Lesley F; Benavente, Yolanda; Sala, Núria; Casabonne, Delphine; Becker, Nikolaus; Boffetta, Paolo; Brennan, Paul; Foretova, Lenka; Maynadie, Marc; McKay, James; Staines, Anthony; Chaffee, Kari G; Achenbach, Sara J; Vachon, Celine M; Goldin, Lynn R; Strom, Sara S; Leis, Jose F; Weinberg, J Brice; Caporaso, Neil E; Norman, Aaron D; De Roos, Anneclaire J; Morton, Lindsay M; Severson, Richard K; Riboli, Elio; Vineis, Paolo; Kaaks, Rudolph; Masala, Giovanna; Weiderpass, Elisabete; Chirlaque, María-Dolores; Vermeulen, Roel C H|info:eu-repo/dai/nl/216532620; Travis, Ruth C; Southey, Melissa C; Milne, Roger L; Albanes, Demetrius; Virtamo, Jarmo; Weinstein, Stephanie; Clavel, Jacqueline; Zheng, Tongzhang; Holford, Theodore R; Villano, Danylo J; Maria, Ann; Spinelli, John J; Gascoyne, Randy D; Connors, Joseph M; Bertrand, Kimberly A; Giovannucci, Edward; Kraft, Peter; Kricker, Anne; Turner, Jenny; Ennas, Maria Grazia; Ferri, Giovanni M; Miligi, Lucia; Liang, Liming; Ma, Baoshan; Huang, Jinyan; Crouch, Simon; Park, Ju-Hyun; Chatterjee, Nilanjan; North, Kari E; Snowden, John A; Wright, Josh; Fraumeni, Joseph F; Offit, Kenneth; Wu, Xifeng; de Sanjose, Silvia; Cerhan, James R; Chanock, Stephen J; Rothman, Nathaniel; Slager, Susan L

    2016-01-01

    Chronic lymphocytic leukemia (CLL) is a common lymphoid malignancy with strong heritability. To further understand the genetic susceptibility for CLL and identify common loci associated with risk, we conducted a meta-analysis of four genome-wide association studies (GWAS) composed of 3,100 cases and

  19. Genome-wide association study identifies six new loci influencing pulse pressure and mean arterial pressure

    NARCIS (Netherlands)

    Wain, Louise V.; Verwoert, Germaine C.; O'Reilly, Paul F.; Shi, Gang; Johnson, Toby; Johnson, Andrew D.; Bochud, Murielle; Rice, Kenneth M.; Henneman, Peter; Smith, Albert V.; Ehret, Georg B.; Amin, Najaf; Larson, Martin G.; Mooser, Vincent; Hadley, David; Doerr, Marcus; Bis, Joshua C.; Aspelund, Thor; Esko, Tonu; Janssens, A. Cecile J. W.; Zhao, Jing Hua; Heath, Simon; Laan, Maris; Fu, Jingyuan; Pistis, Giorgio; Luan, Jian'an; Arora, Pankaj; Lucas, Gavin; Pirastu, Nicola; Pichler, Irene; Jackson, Anne U.; Webster, Rebecca J.; Zhang, Feng; Peden, John F.; Schmidt, Helena; Tanaka, Toshiko; Campbell, Harry; Igl, Wilmar; Milaneschi, Yuri; Hottenga, Jouke-Jan; Vitart, Veronique; Chasman, Daniel I.; Trompet, Stella; Bragg-Gresham, Jennifer L.; Alizadeh, Behrooz Z.; Chambers, John C.; Guo, Xiuqing; Lehtimaki, Terho; Kuehnel, Brigitte; Lopez, Lorna M.; Polasek, Ozren; Boban, Mladen; Nelson, Christopher P.; Morrison, Alanna C.; Pihur, Vasyl; Ganesh, Santhi K.; Hofman, Albert; Kundu, Suman; Mattace-Raso, Francesco U. S.; Rivadeneira, Fernando; Sijbrands, Eric J. G.; Uitterlinden, Andre G.; Hwang, Shih-Jen; Vasan, Ramachandran S.; Wang, Thomas J.; Bergmann, Sven; Vollenweider, Peter; Waeber, Gerard; Laitinen, Jaana; Pouta, Anneli; Zitting, Paavo; McArdle, Wendy L.; Kroemer, Heyo K.; Voelker, Uwe; Voelzke, Henry; Glazer, Nicole L.; Taylor, Kent D.; Harris, Tamara B.; Alavere, Helene; Haller, Toomas; Keis, Aime; Tammesoo, Mari-Liis; Aulchenko, Yurii; Barroso, Ines; Khaw, Kay-Tee; Galan, Pilar; Hercberg, Serge; Lathrop, Mark; Eyheramendy, Susana; Org, Elin; Sober, Siim; Lu, Xiaowen; Nolte, Ilja M.; Penninx, Brenda W.; Corre, Tanguy; Masciullo, Corrado; Sala, Cinzia; Groop, Leif; Voight, Benjamin F.; Melander, Olle; O'Donnell, Christopher J.; Salomaa, Veikko; d'Adamo, Adamo Pio; Fabretto, Antonella; Faletra, Flavio; Ulivi, Sheila; Del Greco, Fabiola M.; Facheris, Maurizio; Collins, Francis S.; Bergman, Richard N.; Beilby, John P.; Hung, Joseph; Musk, A. William; Mangino, Massimo; Shin, So-Youn; Soranzo, Nicole; Watkins, Hugh; Goel, Anuj; Hamsten, Anders; Gider, Pierre; Loitfelder, Marisa; Zeginigg, Marion; Hernandez, Dena; Najjar, Samer S.; Navarro, Pau; Wild, Sarah H.; Corsi, Anna Maria; Singleton, Andrew; de Geus, Eco J. C.; Willemsen, Gonneke; Parker, Alex N.; Rose, Lynda M.; Buckley, Brendan; Stott, David; Orru, Marco; Uda, Manuela; van der Klauw, Melanie M.; Zhang, Weihua; Li, Xinzhong; Scott, James; Chen, Yii-Der Ida; Burke, Gregory L.; Kahonen, Mika; Viikari, Jorma; Doering, Angela; Meitinger, Thomas; Davies, Gail; Starr, John M.; Emilsson, Valur; Plump, Andrew; Lindeman, Jan H.; 't Hoen, Peter A. C.; Koenig, Inke R.; Felix, Janine F.; Clarke, Robert; Hopewell, Jemma C.; Ongen, Halit; Breteler, Monique; Debette, Stephanie; DeStefano, Anita L.; Fornage, Myriam; Mitchell, Gary F.; Smith, Nicholas L.; Holm, Hilma; Stefansson, Kari; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Samani, Nilesh J.; Preuss, Michael; Rudan, Igor; Hayward, Caroline; Deary, Ian J.; Wichmann, H-Erich; Raitakari, Olli T.; Palmas, Walter; Kooner, Jaspal S.; Stolk, Ronald P.; Jukema, J. Wouter; Wright, Alan F.; Boomsma, Dorret I.; Bandinelli, Stefania; Gyllensten, Ulf B.; Wilson, James F.; Ferrucci, Luigi; Schmidt, Reinhold; Farrall, Martin; Spector, Tim D.; Palmer, Lyle J.; Tuomilehto, Jaakko; Pfeufer, Arne; Gasparini, Paolo; Siscovick, David; Altshuler, David; Loos, Ruth J. F.; Toniolo, Daniela; Snieder, Harold; Gieger, Christian; Meneton, Pierre; Wareham, Nicholas J.; Oostra, Ben A.; Metspalu, Andres; Launer, Lenore; Rettig, Rainer; Strachan, David P.; Beckmann, Jacques S.; Witteman, Jacqueline C. M.; Erdmann, Jeanette; van Dijk, Ko Willems; Boerwinkle, Eric; Boehnke, Michael; Ridker, Paul M.; Jarvelin, Marjo-Riitta; Chakravarti, Aravinda; Abecasis, Goncalo R.; Gudnason, Vilmundur; Newton-Cheh, Christopher; Levy, Daniel; Munroe, Patricia B.; Psaty, Bruce M.; Caulfield, Mark J.; Rao, Dabeeru C.; Tobin, Martin D.; Elliott, Paul; van Duijn, Cornelia M.

    2011-01-01

    Numerous genetic loci have been associated with systolic blood pressure (SBP) and diastolic blood pressure (DBP) in Europeans(1-3). We now report genome-wide association studies of pulse pressure (PP) and mean arterial pressure (MAP). In discovery (N = 74,064) and follow-up studies (N = 48,607), we

  20. Genome-wide association study identifies multiple susceptibility loci for diffuse large B cell lymphoma

    NARCIS (Netherlands)

    Cerhan, James R.; Berndt, Sonja I.; Vijai, Joseph; Ghesquières, Hervé; McKay, James; Wang, Sophia S.; Wang, Zhaoming; Yeager, Meredith; Conde, Lucia; De Bakker, Paul I W; Nieters, Alexandra; Cox, David; Burdett, Laurie; Monnereau, Alain; Flowers, Christopher R.; De Roos, Anneclaire J.; Brooks-Wilson, Angela R.; Lan, Qing; Severi, Gianluca; Melbye, Mads; Gu, Jian; Jackson, Rebecca D.; Kane, Eleanor; Teras, Lauren R.; Purdue, Mark P.; Vajdic, Claire M.; Spinelli, John J.; Giles, Graham G.; Albanes, Demetrius; Kelly, Rachel S.; Zucca, Mariagrazia; Bertrand, Kimberly A.; Zeleniuch-Jacquotte, Anne; Lawrence, Charles; Hutchinson, Amy; Zhi, Degui; Habermann, Thomas M.; Link, Brian K.; Novak, Anne J.; Dogan, Ahmet; Asmann, Yan W.; Liebow, Mark; Thompson, Carrie A.; Ansell, Stephen M.; Witzig, Thomas E.; Weiner, George J.; Veron, Amelie S.; Zelenika, Diana; Tilly, Hervé; Haioun, Corinne; Molina, Thierry Jo; Hjalgrim, Henrik; Glimelius, Bengt; Adami, Hans Olov; Bracci, Paige M.; Riby, Jacques; Smith, Martyn T.; Holly, Elizabeth A.; Cozen, Wendy; Hartge, Patricia; Morton, Lindsay M.; Severson, Richard K.; Tinker, Lesley F.; North, Kari E.; Becker, Nikolaus; Benavente, Yolanda; Boffetta, Paolo; Brennan, Paul; Foretova, Lenka; Maynadie, Marc; Staines, Anthony; Lightfoot, Tracy; Crouch, Simon; Smith, Alex; Roman, Eve; Diver, W. Ryan; Offit, Kenneth; Zelenetz, Andrew; Klein, Robert J.; Villano, Danylo J.; Zheng, Tongzhang; Zhang, Yawei; Holford, Theodore R.; Kricker, Anne; Turner, Jenny; Southey, Melissa C.; Clavel, Jacqueline; Virtamo, Jarmo; Weinstein, Stephanie; Riboli, Elio; Vineis, Paolo; Kaaks, Rudolph; Trichopoulos, Dimitrios; Vermeulen, Roel C H; Boeing, Heiner; Tjonneland, Anne; Angelucci, Emanuele; Di Lollo, Simonetta; Rais, Marco; Birmann, Brenda M.; Laden, Francine; Giovannucci, Edward; Kraft, Peter; Huang, Jinyan; Ma, Baoshan; Ye, Yuanqing; Chiu, Brian C H; Sampson, Joshua; Liang, Liming; Park, Ju Hyun; Chung, Charles C.; Weisenburger, Dennis D.; Chatterjee, Nilanjan; Fraumeni, Joseph F.; Slager, Susan L.; Wu, Xifeng; De Sanjose, Silvia; Smedby, Karin E.; Salles, Gilles; Skibola, Christine F.; Rothman, Nathaniel; Chanock, Stephen J.

    2014-01-01

    Diffuse large B cell lymphoma (DLBCL) is the most common lymphoma subtype and is clinically aggressive. To identify genetic susceptibility loci for DLBCL, we conducted a meta-analysis of 3 new genome-wide association studies (GWAS) and 1 previous scan, totaling 3,857 cases and 7,666 controls of Euro

  1. Genome-Wide Association Study of Receptive Language Ability of 12-Year-Olds

    Science.gov (United States)

    Harlaar, Nicole; Meaburn, Emma L.; Hayiou-Thomas, Marianna E.; Davis, Oliver S. P.; Docherty, Sophia; Hanscombe, Ken B.; Haworth, Claire M. A.; Price, Thomas S.; Trzaskowski, Maciej; Dale, Philip S.; Plomin, Robert

    2014-01-01

    Purpose: Researchers have previously shown that individual differences in measures of receptive language ability at age 12 are highly heritable. In the current study, the authors attempted to identify some of the genes responsible for the heritability of receptive language ability using a "genome-wide association" approach. Method: The…

  2. Genome wide association analysis for residual feed intake in Danish Duroc boars

    DEFF Research Database (Denmark)

    Do, Duy Ngoc; Ostersen, Tage; Strathe, Anders Bjerring;

    2013-01-01

    gain (30-100 kg). RFI2 was the same as RFI1 except that it was also regressed on backfat (BF). A total of 868 boars had phenotypic and genotype (i.e. Illumina Porcine SNP60 BeadChip) records. A total of 33945 SNPs were available for genome wide association studies (GWAS) after quality control...

  3. Seven prostate cancer susceptibility loci identified by a multi-stage genome-wide association study

    DEFF Research Database (Denmark)

    Kote-Jarai, Zsofia; Olama, Ali Amin Al; Giles, Graham G

    2011-01-01

    Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. We conducted a multi-stage genome-wide association study for PrCa and previously reported the results of the first two stages, which identified 16 PrCa susceptibility loci. We report here the results of st...

  4. Identification of six Loci associated with pelvic organ prolapse using genome-wide association analysis.

    NARCIS (Netherlands)

    Allen-Brady, K.; Cannon-Albright, L.; Farnham, J.M.; Teerlink, C.; Vierhout, M.E.; Kempen, L.C.L.T. van; Kluivers, K.B.; Norton, P.A.

    2011-01-01

    OBJECTIVE: : There is evidence that both environmental and genetic factors contribute to pelvic organ prolapse. We conducted a genome-wide association study to investigate whether common genetic variants modify the risk of pelvic organ prolapse. METHODS: : We recruited women who had been evaluated

  5. Genome-wide association analysis in primary sclerosing cholangitis identifies two non-HLA susceptibility loci

    NARCIS (Netherlands)

    Melum, Espen; Franke, Andre; Schramm, Christoph; Weismueller, Tobias J.; Gotthardt, Daniel Nils; Offner, Felix A.; Juran, Brian D.; Laerdahl, Jon K.; Labi, Verena; Bjoernsson, Einar; Weersma, Rinse K.; Henckaerts, Liesbet; Teufel, Andreas; Rust, Christian; Ellinghaus, Eva; Balschun, Tobias; Boberg, Kirsten Muri; Ellinghaus, David; Bergquist, Annika; Sauer, Peter; Ryu, Euijung; Hov, Johannes Roksund; Wedemeyer, Jochen; Lindkvist, Bjoern; Wittig, Michael; Porte, Robert J.; Holm, Kristian; Gieger, Christian; Wichmann, H-Erich; Stokkers, Pieter; Ponsioen, Cyriel Y.; Runz, Heiko; Stiehl, Adolf; Wijmenga, Cisca; Sterneck, Martina; Vermeire, Severine; Beuers, Ulrich; Villunger, Andreas; Schrumpf, Erik; Lazaridis, Konstantinos N.; Manns, Michael P.; Schreiber, Stefan; Karlsen, Tom H.

    Primary sclerosing cholangitis (PSC) is a chronic bile duct disease affecting 2.4-7.5% of individuals with inflammatory bowel disease. We performed a genome-wide association analysis of 2,466,182 SNPs in 715 individuals with PSC and 2,962 controls, followed by replication in 1,025 PSC cases and

  6. Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption

    NARCIS (Netherlands)

    Cornelis, M. C.; Byrne, E. M.; Esko, T.; Nalls, M. A.; Ganna, A.; Paynter, N.; Monda, K. L.; Amin, N.; Fischer, K.; Renstrom, F.; Ngwa, J. S.; Huikari, V.; Cavadino, A.; Nolte, I. M.; Teumer, A.; Yu, K.; Marques-Vidal, P.; Rawal, R.; Manichaikul, A.; Wojczynski, M. K.; Vink, J. M.; Zhao, J. H.; Burlutsky, G.; Lahti, J.; Mikkila, V.; Lemaitre, R. N.; Eriksson, J.; Musani, S. K.; Tanaka, T.; Geller, F.; Luan, J.; Hui, J.; Maegi, R.; Dimitriou, M.; Garcia, M. E.; Ho, W-K; Wright, M. J.; Rose, L. M.; Magnusson, P. K. E.; Pedersen, N. L.; Couper, D.; Oostra, B. A.; Hofman, A.; Ikram, M. A.; Tiemeier, H. W.; Uitterlinden, A. G.; van Rooij, F. J. A.; Barroso, I.; Johansson, I.; Xue, L.; Kaakinen, M.; Milani, L.; Power, C.; Snieder, H.; Stolk, R. P.; Baumeister, S. E.; Biffar, R.; Gu, F.; Bastardot, F.; Kutalik, Z.; Jacobs, D. R.; Forouhi, N. G.; Mihailov, E.; Lind, L.; Lindgren, C.; Michaelsson, K.; Morris, A.; Jensen, M.; Khaw, K-T; Luben, R. N.; Wang, J. J.; Mannisto, S.; Perala, M-M; Kahonen, M.; Lehtimaki, T.; Viikari, J.; Mozaffarian, D.; Mukamal, K.; Psaty, B. M.; Doering, A.; Heath, A. C.; Montgomery, G. W.; Dahmen, N.; Carithers, T.; Tucker, K. L.; Ferrucci, L.; Boyd, H. A.; Melbye, M.; Treur, J. L.; Mellstrom, D.; Hottenga, J. J.; Prokopenko, I.; Toenjes, A.; Deloukas, P.; Kanoni, S.; Lorentzon, M.; Houston, D. K.; Liu, Y.; Danesh, J.; Rasheed, A.; Mason, M. A.; Zonderman, A. B.; Franke, L.; Kristal, B. S.; Karjalainen, J.; Reed, D. R.; Westra, H-J; Evans, M. K.; Saleheen, D.; Harris, T. B.; Dedoussis, G.; Curhan, G.; Stumvoll, M.; Beilby, J.; Pasquale, L. R.; Feenstra, B.; Bandinelli, S.; Ordovas, J. M.; Chan, A. T.; Peters, U.; Ohlsson, C.; Gieger, C.; Martin, N. G.; Waldenberger, M.; Siscovick, D. S.; Raitakari, O.; Eriksson, J. G.; Mitchell, P.; Hunter, D. J.; Kraft, P.; Rimm, E. B.; Boomsma, D. I.; Borecki, I. B.; Loos, R. J. F.; Wareham, N. J.; Vollenweider, P.; Caporaso, N.; Grabe, H. J.; Neuhouser, M. L.; Wolffenbuttel, B. H. R.; Hu, F. B.; Hyppoenen, E.; Jarvelin, M-R; Cupples, L. A.; Franks, P. W.; Ridker, P. M.; van Duijn, C. M.; Heiss, G.; Metspalu, A.; North, K. E.; Ingelsson, E.; Nettleton, J. A.; van Dam, R. M.; Chasman, D. I.

    Coffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to

  7. Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption

    NARCIS (Netherlands)

    M. Cornelis (Marilyn); E.M. Byrne; T. Esko (Tõnu); M.A. Nalls (Michael); A. Ganna (Andrea); N.P. Paynter (Nina); K.L. Monda (Keri); N. Amin; K. Fischer (Krista); F. Renström (Frida); J.S. Ngwa; V. Huikari (Ville); A. Cavadino (Alana); I.M. Nolte (Ilja M.); A. Teumer (Alexander); K. Yu; P. Marques-Vidal; R. Rawal; A. Manichaikul (Ani); M.K. Wojczynski (Mary ); J.M. Vink; J.H. Zhao; G. Burlutsky (George); J. Lahti (Jari); V. Mikkilä (Vera); R.N. Lemaitre (Rozenn ); J. Eriksson; S. Musani (Solomon); T. Tanaka; F. Geller (Frank); J. Luan; J. Hui; R. Mägi (Reedik); M. Dimitriou (Maria); M. Garcia (Melissa); W.-K. Ho; M.J. Wright (Margaret); L.M. Rose (Lynda M.); P.K.E. Magnusson (Patrik K. E.); N.L. Pedersen (Nancy L.); D.J. Couper (David); B.A. Oostra (Ben); A. Hofman (Albert); M.A. Ikram (Arfan); H.W. Tiemeier (Henning); A.G. Uitterlinden (André); F.J.A. van Rooij (Frank); I. Barroso; I. Johansson (Ingegerd); L. Xue (Luting); M. Kaakinen (Marika); L. Milani (Lili); C. Power (Christine); H. Snieder (Harold); R.P. Stolk; S.E. Baumeister (Sebastian); R. Biffar; F. Gu; F. Bastardot (Francois); Z. Kutalik; D.R. Jacobs (David); N.G. Forouhi (Nita G.); E. Mihailov (Evelin); L. Lind (Lars); C. Lindgren; K. Michaëlsson; A.P. Morris (Andrew); M.K. Jensen (Majken K.); K.T. Khaw; R.N. Luben (Robert); J.J. Wang; S. Männistö (Satu); M.-M. Perälä; M. Kähönen (Mika); T. Lehtimäki (Terho); J. Viikari (Jorma); D. Mozaffarian; K. Mukamal (Kenneth); B.M. Psaty (Bruce); A. Döring; A.C. Heath (Andrew C.); G.W. Montgomery (Grant W.); N. Dahmen (N.); T. Carithers; K.L. Tucker; L. Ferrucci (Luigi); H.A. Boyd; M. Melbye (Mads); J.L. Treur; D. Mellström (Dan); J.J. Hottenga (Jouke Jan); I. Prokopenko (Inga); A. Tönjes (Anke); P. Deloukas (Panagiotis); S. Kanoni (Stavroula); M. Lorentzon (Mattias); D.K. Houston; Y. Liu; J. Danesh (John); A. Rasheed; M.A. Mason; A.B. Zonderman; L. Franke (Lude); B.S. Kristal; J. Karjalainen (Juha); D.R. Reed; H.-J. Westra; M.K. Evans; D. Saleheen; T.B. Harris (Tamara B.); G.V. Dedoussis (George V.); G.C. Curhan (Gary); M. Stumvoll (Michael); J. Beilby (John); L.R. Pasquale; B. Feenstra; S. Bandinelli; J.M. Ordovas; A.T. Chan; U. Peters (Ulrike); C. Ohlsson (Claes); C. Gieger (Christian); N.G. Martin (Nicholas); M. Waldenberger (Melanie); D.S. Siscovick (David); O. Raitakari (Olli); J.G. Eriksson (Johan G.); P. Mitchell (Paul); D. Hunter (David); P. Kraft (Peter); E.B. Rimm (Eric B.); D.I. Boomsma (Dorret); I.B. Borecki (Ingrid); R.J.F. Loos (Ruth); N.J. Wareham (Nick); P.K. Vollenweider (Peter K.); N. Caporaso; H.J. Grabe (Hans Jörgen); M.L. Neuhouser (Marian L.); B.H.R. Wolffenbuttel (Bruce H. R.); F.B. Hu (Frank); E. Hypponen (Elina); M.-R. Jarvelin (Marjo-Riitta); L.A. Cupples (Adrienne); P.W. Franks; P.M. Ridker (Paul); C.M. van Duijn (Cock); G. Heiss (Gerardo); A. Metspalu (Andres); K.E. North (Kari); E. Ingelsson (Erik); J.A. Nettleton; R.M. van Dam (Rob); D.I. Chasman (Daniel)

    2015-01-01

    textabstractCoffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day)

  8. Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption

    NARCIS (Netherlands)

    Cornelis, M.C.; Byrne, E.M.; Esko, T.; Nalls, M.A.; Ganna, A.; Paynter, N.; Monda, K.L.; Amin, N.; Fischer, K.; Renstrom, F.; Ngwa, J.S.; Huikari, V.; Cavadino, A.; Nolte, I.M.; Teumer, A.; Yu, K.; Marques-Vidal, P.; Rawal, R.; Manichaikul, A.; Wojczynski, M.K.; Vink, J.M.; Zhao, J.H.; Burlutsky, G.; Lahti, J.; Mikkila, V.; Lemaitre, R.N.; Eriksson, J.; Musani, S.K.; Tanaka, T.; Geller, F.; Luan, J.; Hui, J.; Magi, R.; Dimitriou, M.; Garcia, M.E.; Ho, W.K.; Wright, M.J.; Rose, L.M.; Magnusson, P.K.E.; Pedersen, N.L.; Couper, D.; Oostra, B.A.; Hofman, A.; Ikram, M.A.; Tiemeier, H.W.; Uitterlinden, A.G.; Rooij, F.J. van; Barroso, I.; Johansson, I.; Xue, L.; Kaakinen, M.; Milani, L.; Power, C.; Snieder, H.; Stolk, R.P.; Baumeister, S.E.; Biffar, R.; Gu, F.; Bastardot, F.; Kutalik, Z.; Jacobs, D.R., Jr.; Forouhi, N.G.; Mihailov, E.; Lind, L.; Lindgren, C.; Michaelsson, K.; Morris, A.; Jensen, M.; Khaw, K.T.; Luben, R.N.; Wang, J.J.; Mannisto, S.; Perala, M.M.; Kahonen, M.; Lehtimaki, T.; Viikari, J.; Mozaffarian, D.; Mukamal, K.; Psaty, B.M.; Doring, A.; Heath, A.C.; Montgomery, G.W.; Dahmen, N.; Carithers, T.; Tucker, K.L.; Ferrucci, L.; Boyd, H.A.; Melbye, M.; Treur, J.L.; Mellstrom, D.; Hottenga, J.J.; Prokopenko, I.; Tonjes, A.; Deloukas, P.; Kanoni, S.; Lorentzon, M.; Houston, D.K.; Liu, Y.; Danesh, J.; Rasheed, A.; Mason, M.A.; Zonderman, A.B.; Franke, L.; Kristal, B.S.; Karjalainen, J.; Reed, D.R.; Westra, H.J.; Evans, M.K.; Saleheen, D.; Harris, T.B.; Dedoussis, G.; Curhan, G.; Stumvoll, M.; Beilby, J.; Pasquale, L.R.; Feenstra, B.; Bandinelli, S.; Ordovas, J.M.; Chan, A.T.; Peters, U.; Ohlsson, C.; Gieger, C.; Martin, N.G.; Waldenberger, M.; Siscovick, D.S.; Raitakari, O.; Eriksson, J.G.; Mitchell, P.; Hunter, D.J.; Kraft, P.; Rimm, E.B.; Boomsma, D.I.; Borecki, I.B.; Loos, R.J.F.; Wareham, N.J.; Vollenweider, P.; Caporaso, N.; Grabe, H.J.; Neuhouser, M.L.; Wolffenbuttel, B.H.R.; Hu, F.B.; Hypponen, E.; Jarvelin, M.R.; Cupples, L.A.; Franks, P.W.; Ridker, P.M.; Duijn, C.M. van; Heiss, G.; Metspalu, A.; North, K.E.; Ingelsson, E.; Nettleton, J.A.; Dam, R.M. van; Chasman, D.I.

    2015-01-01

    Coffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to

  9. Genome-Wide Association Study for Response to Eimeria maxima Challenge in Broilers

    DEFF Research Database (Denmark)

    Hamzic, Edin; Bed'hom, Bertrand; Hérault, Frédéric

    Use of genetic tools for improvement of host’s response is considered as a promising complementary approach for coccidiosis control. Therefore, we performed genome wide association study (GWAS) for response to Eimeria maxima challenge in broilers. The challenge was done on 2024 Cobb500 broilers. ...

  10. Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics

    NARCIS (Netherlands)

    Lundby, Alicia; Rossin, Elizabeth J.; Steffensen, Annette B.; Acha, Moshe Ray; Newton-Cheh, Christopher; Pfeufer, Arne; Lyneh, Stacey N.; Olesen, Soren-Peter; Brunak, Soren; Ellinor, Patrick T.; Jukema, J. Wouter; Trompet, Stella; Ford, Ian; Macfarlane, Peter W.; Krijthe, Bouwe P.; Hofman, Albert; Uitterlinden, Andre G.; Stricker, Bruno H.; Nathoe, Hendrik M.; Spiering, Wilko; Daly, Mark J.; Asselbergs, Ikea W.; van der Harst, Pim; Milan, David J.; de Bakker, Paul I. W.; Lage, Kasper; Olsen, Jesper V.

    2014-01-01

    Genome-wide association studies (GWAS) have identified thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes

  11. Genome-Wide Association Study of Intelligence: Additive Effects of Novel Brain Expressed Genes

    Science.gov (United States)

    Loo, Sandra K.; Shtir, Corina; Doyle, Alysa E.; Mick, Eric; McGough, James J.; McCracken, James; Biederman, Joseph; Smalley, Susan L.; Cantor, Rita M.; Faraone, Stephen V.; Nelson, Stanley F.

    2012-01-01

    Objective: The purpose of the present study was to identify common genetic variants that are associated with human intelligence or general cognitive ability. Method: We performed a genome-wide association analysis with a dense set of 1 million single-nucleotide polymorphisms (SNPs) and quantitative intelligence scores within an ancestrally…

  12. Genome-Wide Association Study of Receptive Language Ability of 12-Year-Olds

    Science.gov (United States)

    Harlaar, Nicole; Meaburn, Emma L.; Hayiou-Thomas, Marianna E.; Davis, Oliver S. P.; Docherty, Sophia; Hanscombe, Ken B.; Haworth, Claire M. A.; Price, Thomas S.; Trzaskowski, Maciej; Dale, Philip S.; Plomin, Robert

    2014-01-01

    Purpose: Researchers have previously shown that individual differences in measures of receptive language ability at age 12 are highly heritable. In the current study, the authors attempted to identify some of the genes responsible for the heritability of receptive language ability using a "genome-wide association" approach. Method: The…

  13. Genome-wide Association Analysis of Kernel Weight in Hard Winter Wheat

    Science.gov (United States)

    Wheat kernel weight is an important and heritable component of wheat grain yield and a key predictor of flour extraction. Genome-wide association analysis was conducted to identify genomic regions associated with kernel weight and kernel weight environmental response in 8 trials of 299 hard winter ...

  14. Novel genetic loci underlying human intracranial volume identified through genome-wide association

    NARCIS (Netherlands)

    Adams, Hieab H. H.; Hibar, Derrek P.; Chouraki, Vincent; Stein, Jason L.; Nyquist, Paul A.; Renteria, Miguel E.; Trompet, Stella; Arias-Vasquez, Alejandro; Seshadri, Sudha; Desrivieres, Sylvane; Beecham, Ashley H.; Jahanshad, Neda; Wittfeld, Katharine; Van der Lee, Sven J.; Abramovic, Lucija; Alhusaini, Saud; Amin, Najaf; Andersson, Micael; Arfanakis, Konstantinos; Aribisala, Benjamin S.; Armstrong, Nicola J.; Athanasiu, Lavinia; Axelsson, Tomas; Beiser, Alexa; Bernard, Manon; Bis, Joshua C.; Blanken, Laura M. E.; Blanton, Susan H.; Bohlken, Marc M.; Boks, Marco P.; Bralten, Janita; Brickman, Adam M.; Carmichael, Owen; Chakravarty, M. Mallar; Chauhan, Ganesh; Chen, Qiang; Ching, Christopher R. K.; Cuellar-Partida, Gabriel; Den Braber, Anouk; Doan, Nhat Trung; Ehrlich, Stefan; Filippi, Irina; Ge, Tian; Giddaluru, Sudheer; Goldman, Aaron L.; Gottesman, Rebecca F.; Greven, Corina U.; Grimm, Oliver; Griswold, Michael E.; Guadalupe, Tulio; Hass, Johanna; Haukvik, Unn K.; Hilal, Saima; Hofer, Edith; Hoehn, David; Holmes, Avram J.; Hoogman, Martine; Janowitz, Deborah; Jia, Tianye; Kasperaviciute, Dalia; Kim, Sungeun; Klein, Marieke; Kraemer, Bernd; Lee, Phil H.; Liao, Jiemin; Liewald, David C. M.; Lopez, Lorna M.; Luciano, Michelle; Macare, Christine; Marquand, Andre; Matarin, Mar; Mather, Karen A.; Mattheisen, Manuel; Mazoyer, Bernard; Mckay, David R.; McWhirter, Rebekah; Milaneschi, Yuri; Mirza-Schreiber, Nazanin; Muetzel, Ryan L.; Maniega, Susana Munoz; Nho, Kwangsik; Nugent, Allison C.; Loohuis, Loes M. Olde; Oosterlaan, Jaap; Papmeyer, Martina; Pappa, Irene; Pirpamer, Lukas; Pudas, Sara; Puetz, Benno; Rajan, Kumar B.; Ramasamy, Adaikalavan; Richards, Jennifer S.; Risacher, Shannon L.; Roiz-Santianez, Roberto; Rommelse, Nanda; Rose, Emma J.; Royle, Natalie A.; Rundek, Tatjana; Saemann, Philipp G.; Satizabal, Claudia L.; Schmaal, Lianne; Schork, Andrew J.; Shen, Li; Shin, Jean; Shumskaya, Elena; Smith, Albert V.; Sprooten, Emma; Strike, Lachlan T.; Teumer, Alexander; Thomson, Russell; Tordesillas-Gutierrez, Diana; Toro, Roberto; Trabzuni, Daniah; Vaidya, Dhananjay; Van der Grond, Jeroen; Van der Meer, Dennis; Van Donkelaar, Marjolein M. J.; Van Eijk, Kristel R.; Van Erp, Theo G. M.; Van Rooij, Daan; Walton, Esther; Westlye, Lars T.; Whelan, Christopher D.; Windham, Beverly G.; Winkler, Anderson M.; Woldehawariat, Girma; Wolf, Christiane; Wolfers, Thomas; Xu, Bing; Yanek, Lisa R.; Yang, Jingyun; Zijdenbos, Alex; Zwiers, Marcel P.; Agartz, Ingrid; Aggarwal, Neelum T.; Almasy, Laura; Ames, David; Amouyel, Philippe; Andreassen, Ole A.; Arepalli, Sampath; Assareh, Amelia A.; Barral, Sandra; Bastin, Mark E.; Becker, Diane M.; Becker, James T.; Bennett, David A.; Blangero, John; van Bokhoven, Hans; Boomsma, Dorret I.; Brodaty, Henry; Brouwer, Rachel M.; Brunner, Han G.; Buckner, Randy L.; Buitelaar, Jan K.; Bulayeva, Kazima B.; Cahn, Wiepke; Calhoun, Vince D.; Cannon, Dara M.; Cavalleri, Gianpiero L.; Chen, Christopher; Cheng, Ching -Yu; Cichon, Sven; Cookson, Mark R.; Corvin, Aiden; Crespo-Facorro, Benedicto; Curran, Joanne E.; Czisch, Michael; Dale, Anders M.; Davies, Gareth E.; De Geus, Eco J. C.; De Jager, Philip L.; de Zubicaray, Greig I.; Delanty, Norman; Depondt, Chantal; DeStefano, Anita L.; Dillman, Allissa; Djurovic, Srdjan; Donohoe, Gary; Drevets, Wayne C.; Duggirala, Ravi; Dyer, Thomas D.; Erk, Susanne; Espeseth, Thomas; Evans, Denis A.; Fedko, Iryna; Fernandez, Guillen; Ferrucci, Luigi; Fisher, Simon E.; Fleischman, Debra A.; Ford, Ian; Foroud, Tatiana M.; Fox, Peter T.; Francks, Clyde; Fukunaga, Masaki; Gibbs, J. Raphael; Glahn, David C.; Gollub, Randy L.; Goring, Harald H. H.; Grabe, Hans J.; Green, Robert C.; Gruber, Oliver; Gudnason, Vilmundur; Guelfi, Sebastian; Hansell, Narelle K.; Hardy, John; Hartman, Catharina A.; Hashimoto, Ryota; Hegenscheid, Katrin; Heinz, Andreas; Le Hellard, Stephanie; Hernandez, Dena G.; Heslenfeld, Dirk J.; Ho, Beng-Choon; Hoekstra, Pieter J.; Hoffmann, Wolfgang; Hofman, Albert; Holsboer, Florian; Homuth, Georg; Hosten, Norbert; Hottenga, Jouke-Jan; Pol, Hilleke E. Hulshoff; Ikeda, Masashi; Ikram, M. Kamran; Jack, Clifford R.; Jenldnson, Mark; Johnson, Robert; Jonsson, Erik G.; Jukema, J. Wouter; Kahn, Rene S.; Kanai, Ryota; Kloszewska, Iwona; Knopman, David S.; Kochunov, Peter; Kwok, John B.; Lawrie, Stephen M.; Lemaitre, Herve; Liu, Xinmin; Longo, Dan L.; Longstreth, W. T.; Lopez, Oscar L.; Lovestone, Simon; Martinez, Oliver; Martinot, Jean-Luc; Mattay, Venkata S.; McDonald, Colm; McIntosh, Andrew M.; McMahon, Katie L.; McMahon, Francis J.; Mecocci, Patrizia; Melle, Ingrid; Meyer-Lindenberg, Andreas; Mohnke, Sebastian; Montgomery, Grant W.; Morris, Derek W.; Mosley, Thomas H.; Muhleisen, Thomas W.; Mueller-Myhsok, Bertram; Nalls, Michael A.; Nauck, Matthias; Nichols, Thomas E.; Niessen, Wiro J.; Noethen, Markus M.; Nyberg, Lars; Ohi, Kazutaka; Olvera, Rene L.; Ophoff, Roel A.; Pandolfo, Massimo; Paus, Tomas; Pausova, Zdenka; Penninx, Brenda W. J. H.; Pike, G. Bruce; Potkin, Steven G.; Psaty, Bruce M.; Reppermund, Simone; Rietschel, Marcella; Roffman, Joshua L.; Romanczuk-Seiferth, Nina; Rotter, Jerome I.; Ryten, Mina; Sacco, Ralph L.; Sachdev, Perminder S.; Saykin, Andrew J.; Schmidt, Reinhold; Schofield, Peter R.; Sigurdsson, Sigurdur; Simmons, Andy; Singleton, Andrew; Sisodiya, Sanjay M.; Smith, Colin; Smoller, Jordan W.; Soininen, Hindu.; Srikanth, Velandai; Steen, Vidar M.; Stott, David J.; Sussmann, Jessika E.; Thalamuthu, Anbupalam; Tiemeier, Henning; Toga, Arthur W.; Traynor, Bryan J.; Troncoso, Juan; Turner, Jessica A.; Tzourio, Christophe; Uitterlinden, Andre G.; Hernandez, Maria C. Valdes; Van der Brug, Marcel; Van der Lugt, Aad; Van der Wee, Nic J. A.; Van Duijn, Cornelia M.; Van Haren, Neeltje E. M.; Van't Ent, Dennis; Van Tol, Marie Jose; Vardarajan, Badri N.; Veltman, Dick J.; Vernooij, Meike W.; Voelzke, Henry; Walter, Henrik; Wardlaw, Joanna M.; Wassink, Thomas H.; Weale, Michael E.; Weinberger, Daniel R.; Weiner, Michael W.; Wen, Wei; Westman, Eric; White, Tonya; Wong, Tien Y.; Wright, Clinton B.; Zielke, H. Ronald; Zonderman, Alan B.; Deary, Ian J.; DeCarli, Charles; Schmidt, Helena; Martin, Nicholas G.; De Craen, Anton J. M.; Wright, Margaret J.; Launer, Lenore J.; Schumann, Gunter; Fornage, Myriam; Franke, Barbara; Debette, Stephanie; Medland, Sarah E.; Ikram, M. Arfan; Thompson, Paul M.

    2016-01-01

    Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unk

  15. Using Genome-Wide Pathway Analysis to Unravel the Etiology of Complex Diseases

    NARCIS (Netherlands)

    Elbers, Clara C.; van Eijk, Kristel R.; Franke, Lude; Mulder, Flip; van der Schouw, Yvonne T.; Wijmenga, Cisca; Onland-Moret, N. Charlotte

    2009-01-01

    Several genome-wide association studies (GWAS) have been published on various complex diseases. Although, new loci are found to be associated with these diseases, still only very little of the genetic risk for these diseases can be explained. As GWAS are still underpowered to find small main effects

  16. Genome-wide association and functional studies identify a role for IGFBP3 in hip osteoarthritis

    NARCIS (Netherlands)

    D.S. Evans (Daniel); F. Cailotto (Frederic); N. Parimi (Neeta); A.M. Valdes (Ana Maria); M.C. Castaño Betancourt (Martha); Y. Liu (Youfang); R.C. Kaplan (Robert); M. Bidlingmaier (Martin); R.S. Vasan (Ramachandran Srini); A. Teumer (Alexander); G.J. Tranah (Gregory); M.C. Nevitt (Michael); S. Cummings; E.S. Orwoll (Eric); E. Barrett-Connor (Elizabeth); J.B. Renner (Jordan); J.M. Jordan (Joanne); M. Doherty (Michael); S. Doherty (Sally); A.G. Uitterlinden (André); J.B.J. van Meurs (Joyce); T.D. Spector (Timothy); R.J. Lories (Rik); N.E. Lane

    2014-01-01

    textabstractObjectives To identify genetic associations with hip osteoarthritis (HOA), we performed a meta-analysis of genome-wide association studies (GWAS) of HOA. Methods The GWAS meta-analysis included approximately 2.5 million imputed HapMap single nucleotide polymorphisms (SNPs). HOA cases and

  17. Genome-wide transcriptional response of a Saccharomyces cerevisiae strain with an altered redox metabolism

    DEFF Research Database (Denmark)

    Bro, Christoffer; Regenberg, Birgitte; Nielsen, Jens

    2004-01-01

    The genome-wide transcriptional response of a Saccharomyces cerevisiae strain deleted in GDH1 that encodes a NADP(+)-dependent glutamate dehydrogenase was compared to a wild-type strain under anaerobic steady-state conditions. The GDH1-deleted strain has a significantly reduced NADPH requirement...

  18. Genome-Wide Association Study of Intelligence: Additive Effects of Novel Brain Expressed Genes

    Science.gov (United States)

    Loo, Sandra K.; Shtir, Corina; Doyle, Alysa E.; Mick, Eric; McGough, James J.; McCracken, James; Biederman, Joseph; Smalley, Susan L.; Cantor, Rita M.; Faraone, Stephen V.; Nelson, Stanley F.

    2012-01-01

    Objective: The purpose of the present study was to identify common genetic variants that are associated with human intelligence or general cognitive ability. Method: We performed a genome-wide association analysis with a dense set of 1 million single-nucleotide polymorphisms (SNPs) and quantitative intelligence scores within an ancestrally…

  19. Genome-wide association mapping in Arabidopsis identifies previously known flowering time and pathogen resistance genes.

    Directory of Open Access Journals (Sweden)

    María José Aranzana

    2005-11-01

    Full Text Available There is currently tremendous interest in the possibility of using genome-wide association mapping to identify genes responsible for natural variation, particularly for human disease susceptibility. The model plant Arabidopsis thaliana is in many ways an ideal candidate for such studies, because it is a highly selfing hermaphrodite. As a result, the species largely exists as a collection of naturally occurring inbred lines, or accessions, which can be genotyped once and phenotyped repeatedly. Furthermore, linkage disequilibrium in such a species will be much more extensive than in a comparable outcrossing species. We tested the feasibility of genome-wide association mapping in A. thaliana by searching for associations with flowering time and pathogen resistance in a sample of 95 accessions for which genome-wide polymorphism data were available. In spite of an extremely high rate of false positives due to population structure, we were able to identify known major genes for all phenotypes tested, thus demonstrating the potential of genome-wide association mapping in A. thaliana and other species with similar patterns of variation. The rate of false positives differed strongly between traits, with more clinal traits showing the highest rate. However, the false positive rates were always substantial regardless of the trait, highlighting the necessity of an appropriate genomic control in association studies.

  20. Critical reasoning on causal inference in genome-wide linkage and association studies

    NARCIS (Netherlands)

    Li, Yang; Tesson, Bruno M.; Churchill, Gary A.; Jansen, Ritsert C.

    2010-01-01

    Genome-wide linkage and association studies of tens of thousands of clinical and molecular traits are currently underway, offering rich data for inferring causality between traits and genetic variation. However, the inference process is based on discovering subtle patterns in the correlation between

  1. Genome-wide association study of systemic sclerosis identifies CD247 as a new susceptibility locus

    NARCIS (Netherlands)

    Radstake, Timothy R D J; Gorlova, Olga; Rueda, Blanca; Martin, Jose-Ezequiel; Alizadeh, Behrooz Z; Palomino-Morales, Rogelio; Coenen, Marieke J; Vonk, Madelon C; Voskuyl, Alexandre E; Schuerwegh, Annemie J; Broen, Jasper C; van Riel, Piet L C M; van 't Slot, Ruben; Italiaander, Annet; Ophoff, Roel A; Riemekasten, Gabriela; Hunzelmann, Nico; Simeon, Carmen P; Ortego-Centeno, Norberto; González-Gay, Miguel A; González-Escribano, María F; Airo, Paolo; van Laar, Jaap; Herrick, Ariane; Worthington, Jane; Hesselstrand, Roger; Smith, Vanessa; de Keyser, Filip; Houssiau, Fredric; Chee, Meng May; Madhok, Rajan; Shiels, Paul; Westhovens, Rene; Kreuter, Alexander; Kiener, Hans; de Baere, Elfride; Witte, Torsten; Padykov, Leonid; Klareskog, Lars; Beretta, Lorenzo; Scorza, Rafaella; Lie, Benedicte A; Hoffmann-Vold, Anna-Maria; Carreira, Patricia; Varga, John; Hinchcliff, Monique; Gregersen, Peter K; Lee, Annette T; Ying, Jun; Han, Younghun; Weng, Shih-Feng; Amos, Christopher I; Wigley, Fredrick M; Hummers, Laura; Nelson, J Lee; Agarwal, Sandeep K; Assassi, Shervin; Gourh, Pravitt; Tan, Filemon K; Koeleman, Bobby P C; Arnett, Frank C; Martin, Javier; Mayes, Maureen D

    2010-01-01

    Systemic sclerosis (SSc) is an autoimmune disease characterized by fibrosis of the skin and internal organs that leads to profound disability and premature death. To identify new SSc susceptibility loci, we conducted the first genome-wide association study in a population of European ancestry includ

  2. Genome-wide association analyses identify variants in developmental genes associated with hypospadias

    DEFF Research Database (Denmark)

    Geller, Frank; Feenstra, Bjarke; Carstensen, Lisbeth

    2014-01-01

    Hypospadias is a common congenital condition in boys in which the urethra opens on the underside of the penis. We performed a genome-wide association study on 1,006 surgery-confirmed hypospadias cases and 5,486 controls from Denmark. After replication genotyping of an additional 1,972 cases and 1...

  3. Genome-wide association analysis identifies six new loci associated with forced vital capacity

    NARCIS (Netherlands)

    Loth, Daan W.; Artigas, Maria Soler; Gharib, Sina A.; Wain, Louise V.; Franceschini, Nora; Koch, Beate; Pottinger, Tess D.; Smith, Albert Vernon; Duan, Qing; Oldmeadow, Chris; Lee, Mi Kyeong; Strachan, David P.; James, Alan L.; Huffman, Jennifer E.; Vitart, Veronique; Ramasamy, Adaikalavan; Wareham, Nicholas J.; Kaprio, Jaakko; Wang, Xin-Qun; Trochet, Holly; Kaonen, Mika; Flexeder, Claudia; Albrecht, Eva; Lopez, Lorna M.; de Jong, Kim; Thyagarajan, Bharat; Alves, Alexessander Couto; Enroth, Stefan; Omenaas, Ernst; Joshi, Peter K.; Fall, Tove; Vinuela, Ana; Launer, Lenore J.; Loehr, Laura R.; Fornage, Myriam; Li, Guo; Wik, Jemma B.; Tang, Wenbo; Manichaikul, Ani; Lahousse, Lies; Harris, Tamara B.; North, Kari E.; Rudnicka, Alicja R.; Hui, Jennie; Gu, Xiangjun; Lumley, Thomas; Wright, Alan F.; Hastie, Nicholas D.; Campbell, Susan; Kumar, Rajesh; Pin, Isabelle; Scott, Robert A.; Pietilainen, Kirsi H.; Surakka, Ida; Liu, Yongmei; Holliday, Elizabeth G.; Schulz, Holger; Heinrich, Joachim; Davies, Gail; Vonk, Judith M.; Wojczynski, Mary; Pouta, Anneli; Johansson, Asa; Wild, Sarah H.; Ingelsson, Erik; Rivadeneira, Fernando; Voezke, Henry; Hysi, Pirro G.; Eiriksdottir, Gudny; Morrison, Alanna C.; Rotter, Jerome I.; Gao, Wei; Postma, Dirkje S.; White, Wendy B.; Rich, Stephen S.; Hofman, Albert; Aspelund, Thor; Couper, David; Smith, Lewis J.; Psaty, Bruce M.; Lohman, Kurt; Burchard, Esteban G.; Uitterlinden, Andre G.; Garcia, Melissa; Joubert, Bonnie R.; McArdle, Wendy L.; Musk, A. Bill; Hansel, Nadia; Heckbert, Susan R.; Zgaga, Lina; van Meurs, Joyce B. J.; Navarro, Pau; Rudan, Igor; Oh, Yeon-Mok; Redline, Susan; Jarvis, Deborah L.; Rantanen, Taina; O'Connor, George T.; Ripatti, Samuli; Scott, Rodney J.; Karrasch, Stefan; Grallert, Harald; Gaddis, Nathan C.; Starr, John M.; Wijmenga, Cisca; Minster, Ryan L.; Lederer, David J.; Pekkanen, Juha; Gyllensten, Ulf; Campbe, Harry; Morris, Andrew P.; Glaeser, Sven; Hammond, Christopher J.; Burkart, Kristin M.; Beilby, John; Kritchevsky, Stephen B.; Gucinason, Vilrnundur; Hancock, Dana B.; Williams, Dale; Polasek, Ozren; Zemunik, Tatijana; Kolcic, Ivana; Petrini, Marcy F.; Wjst, Matthias; Kim, Woo Jin; Porteous, David J.; Scotland, Generation; Smith, Blair H.; Villanen, Anne; Heliovaara, Markku; Attia, John R.; Sayers, Ian; Hampel, Regina; Gieger, Christian; Deary, Ian J.; Boezen, Hendrika; Newman, Anne; Jarvelin, Marjo-Riitta; Wilson, James F.; Lind, Lars; Stricker, Bruno H.; Teumer, Alexander; Spector, Timothy D.; Melen, Erik; Peters, Marjolein J.; Lange, Leslie A.; Barr, R. Graham; Bracke, Ken R.; Verhamme, Fien M.; Sung, Joohon; Hiemstra, Pieter S.; Cassano, Patricia A.; Sood, Akshay; Hayward, Caroline; Dupuis, Josee; Hall, Ian P.; Brusselle, Guy G.; Tobin, Martin D.; London, Stephanie J.

    2014-01-01

    Forced vital capacity (FVC), a spirometric measure of pulmonary function, reflects lung volume and is used to diagnose and monitor lung diseases. We performed genome-wide association study meta-analysis of FVC in 52,253 individuals from 26 studies and followed up the top associations in 32,917 addit

  4. Genome-wide association study identifies multiple susceptibility loci for multiple myeloma

    DEFF Research Database (Denmark)

    Mitchell, Jonathan S; Li, Ni; Weinhold, Niels;

    2016-01-01

    Multiple myeloma (MM) is a plasma cell malignancy with a significant heritable basis. Genome-wide association studies have transformed our understanding of MM predisposition, but individual studies have had limited power to discover risk loci. Here we perform a meta-analysis of these GWAS, add a ...

  5. Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways

    NARCIS (Netherlands)

    O'Dushlaine, Colm; Rossin, Lizzy; Lee, Phil H.; Duncan, Laramie; Parikshak, Neelroop N.; Newhouse, Stephen; Ripke, Stephan; Neale, Benjamin M.; Purcell, Shaun M.; Posthuma, Danielle; Nurnberger, John I.; Lee, S. Hong; Faraone, Stephen V.; Perlis, Roy H.; Mowry, Bryan J.; Thapar, Anita; Goddard, Michael E.; Witte, John S.; Absher, Devin; Agartz, Ingrid; Akil, Huda; Amin, Farooq; Andreassen, Ole A.; Anjorin, Adebayo; Anney, Richard; Anttila, Verneri; Arking, Dan E.; Asherson, Philip; Azevedo, Maria H.; Backlund, Lena; Badner, Judith A.; Bailey, Anthony J.; Banaschewski, Tobias; Barchas, Jack D.; Barnes, Michael R.; Barrett, Thomas B.; Bass, Nicholas; Battaglia, Agatino; Bauer, Michael; Bayes, Monica; Bellivier, Frank; Bergen, Sarah E.; Berrettini, Wade; Betancur, Catalina; Bettecken, Thomas; Biederman, Joseph; Binder, Elisabeth B.; Black, Donald W.; Blackwood, Douglas H. R.; Bloss, Cinnamon S.; Boehnke, Michael; Boomsma, Dorret I.; Breuer, Rene; Bruggeman, Richard; Cormican, Paul; Buccola, Nancy G.; Buitelaar, Jan K.; Bunney, William E.; Buxbaum, Joseph D.; Byerley, William F.; Byrne, Enda M.; Caesar, Sian; Cahn, Wiepke; Cantor, Rita M.; Casas, Miguel; Chakravarti, Aravinda; Chambert, Kimberly; Choudhury, Khalid; Cichon, Sven; Mattheisen, Manuel; Cloninger, C. Robert; Collier, David A.; Cook, Edwin H.; Coon, Hilary; Cormand, Bru; Corvin, Aiden; Coryell, William H.; Craig, David W.; Craig, Ian W.; Crosbie, Jennifer; Cuccaro, Michael L.; Curtis, David; Czamara, Darina; Datta, Susmita; Dawson, Geraldine; Day, Richard; De Geus, Eco J.; Degenhardt, Franziska; Djurovic, Srdjan; Donohoe, Gary J.; Doyle, Alysa E.; Duan, Jubao; Dudbridge, Frank; Duketis, Eftichia; Ebstein, Richard P.; Edenberg, Howard J.; Elia, Josephine; Ennis, Sean; Etain, Bruno; Fanous, Ayman; Farmer, Anne E.; Ferrier, I. Nicol; Flicldnger, Matthew; Fombonne, Eric; Foroud, Tatiana; Frank, Josef; Franke, Barbara; Fraser, Christine; Freedman, Robert; Freimer, Nelson B.; Freitag, Christine M.; Friedl, Marion; Frisen, Louise; Gailagher, Louise; Gejman, Pablo V.; Georgieva, Lyudmila; Gershon, Elliot S.; Giegling, Ina; Gill, Michael; Gordon, Scott D.; Gordon-Smith, Katherine; Green, Elaine K.; Greenwood, Tiffany A.; Grice, Dorothy E.; Gross, Magdalena; Grozeva, Detelina; Guan, Weihua; Gurling, Hugh; De Haan, Lieuwe; Haines, Jonathan L.; Hakonarson, Hakon; Hallmayer, Joachim; Hamilton, Steven P.; Hamshere, Marian L.; Hansen, Thomas F.; Hartmann, Annette M.; Hautzinger, Martin; Heath, Andrew C.; Henders, Anjali K.; Herms, Stefan; Hickie, Ian B.; Hipolito, Maria; Hoefels, Susanne; Holsboer, Florian; Hoogendijk, Witte J.; Hottenga, Jouke-Jan; Hultman, Christina M.; Hus, Vanessa; Ingason, Andres; Ising, Marcus; Jamain, Stephane; Jones, Edward G.; Jones, Ian; Jones, Lisa; Tzeng, Jung-Ying; Kaehler, Anna K.; Kahn, Rene S.; Kandaswamy, Radhika; Keller, Matthew C.; Kennedy, James L.; Kenny, Elaine; Kent, Lindsey; Kim, Yunjung; Kirov, George K.; Klauck, Sabine M.; Klei, Lambertus; Knowles, James A.; Kohli, Martin A.; Koller, Daniel L.; Konte, Bettina; Korszun, Ania; Krabbendam, Lydia; Krasucki, Robert; Kuntsi, Jonna; Kwan, Phoenix; Landen, Mikael; Laengstroem, Niklas; Lathrop, Mark; Lawrence, Jacob; Lawson, William B.; Leboyer, Marion; Ledbetter, David H.; Lencz, Todd; Lesch, Klaus-Peter; Levinson, Douglas F.; Lewis, Cathryn M.; Li, Jun; Lichtenstein, Paul; Lieberman, Jeffrey A.; Lin, Dan-Yu; Linszen, Don H.; Liu, Chunyu; Lohoff, Falk W.; Loo, Sandra K.; Lord, Catherine; Lowe, Jennifer K.; Lucae, Susanne; MacIntyre, Donald J.; Madden, Pamela A. F.; Maestrini, Elena; Magnusson, Patrik K. E.; Mahon, Pamela B.; Maier, Wolfgang; Malhotra, Anil K.; Mane, Shrikant M.; Martin, Christa L.; Martin, Nicholas G.; Matthews, Keith; Mattingsdal, Morten; McCarroll, Steven A.; McGhee, Kevin A.; McGough, James J.; McGrath, Patrick J.; McGuffin, Peter; McInnis, Melvin G.; McIntosh, Andrew; McKinney, Rebecca; McLean, Alan W.; McMahon, Francis J.; McMahon, William M.; McQuillin, Andrew; Medeiros, Helena; Medland, Sarah E.; Meier, Sandra; Melle, Ingrid; Meng, Fan; Meyer, Jobst; Middeldorp, Christel M.; Middleton, Lefkos; Milanova, Vihra; Miranda, Ana; Monaco, Anthony P.; Montgomery, Grant W.; Moran, Jennifer L.; Moreno-De-Luca, Daniel; Morken, Gunnar; Morris, Derek W.; Morrow, Eric M.; Moskvina, Valentina; Muglia, Pierandrea; Muehleisen, Thomas W.; Muir, Walter J.; Mueller-Myhsok, Bertram; Murtha, Michael; Myers, Richard M.; Myin-Germeys, Inez; Neale, Michael C.; Nelson, Stan F.; Nievergelt, Caroline M.; Nikolov, Ivan; Nimgaonkar, Vishwajit; Nolen, Willem A.; Noethen, Markus M.

    Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from

  6. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs

    NARCIS (Netherlands)

    Lee, S. Hong; Ripke, Stephan; Neale, Benjamin M.; Faraone, Stephen V.; Purcell, Shaun M.; Perlis, Roy H.; Mowry, Bryan J.; Thapar, Anita; Goddard, Michael E.; Witte, John S.; Absher, Devin; Agartz, Ingrid; Akil, Huda; Amin, Farooq; Andreassen, Ole A.; Anjorin, Adebayo; Anney, Richard; Anttila, Verneri; Arking, Dan E.; Asherson, Philip; Azevedo, Maria H.; Backlund, Lena; Badner, Judith A.; Bailey, Anthony J.; Banaschewski, Tobias; Barchas, Jack D.; Barnes, Michael R.; Barrett, Thomas B.; Bass, Nicholas; Battaglia, Agatino; Bauer, Michael; Bayes, Monica; Bellivier, Frank; Bergen, Sarah E.; Berrettini, Wade; Betancur, Catalina; Bettecken, Thomas; Biederman, Joseph; Binder, Elisabeth B.; Black, Donald W.; Blackwood, Douglas H. R.; Bloss, Cinnamon S.; Boehnke, Michael; Boomsma, Dorret I.; Breen, Gerome; Breuer, Rene; Bruggeman, Richard; Cormican, Paul; Buccola, Nancy G.; Buitelaar, Jan K.; Bunney, William E.; Buxbaum, Joseph D.; Byerley, William F.; Byrne, Enda M.; Caesar, Sian; Cahn, Wiepke; Cantor, Rita M.; Casas, Miguel; Chakravarti, Aravinda; Chambert, Kimberly; Choudhury, Khalid; Cichon, Sven; Cloninger, C. Robert; Collier, David A.; Cook, Edwin H.; Coon, Hilary; Cormand, Bru; Corvin, Aiden; Coryell, William H.; Craig, David W.; Craig, Ian W.; Crosbie, Jennifer; Cuccaro, Michael L.; Curtis, David; Czamara, Darina; Datta, Susmita; Dawson, Geraldine; Day, Richard; De Geus, Eco J.; Degenhardt, Franziska; Djurovic, Srdjan; Donohoe, Gary J.; Doyle, Alysa E.; Duan, Jubao; Dudbridge, Frank; Duketis, Eftichia; Ebstein, Richard P.; Edenberg, Howard J.; Elia, Josephine; Ennis, Sean; Etain, Bruno; Fanous, Ayman; Farmer, Anne E.; Ferrier, I. Nicol; Flickinger, Matthew; Fombonne, Eric; Foroud, Tatiana; Frank, Josef; Franke, Barbara; Fraser, Christine; Freedman, Robert; Freimer, Nelson B.; Freitag, Christine M.; Friedl, Marion; Frisen, Louise; Gallagher, Louise; Gejman, Pablo V.; Georgieva, Lyudmila; Gershon, Elliot S.; Geschwind, Daniel H.; Giegling, Ina; Gill, Michael; Gordon, Scott D.; Gordon-Smith, Katherine; Green, Elaine K.; Greenwood, Tiffany A.; Grice, Dorothy E.; Gross, Magdalena; Grozeva, Detelina; Guan, Weihua; Gurling, Hugh; De Haan, Lieuwe; Haines, Jonathan L.; Hakonarson, Hakon; Hallmayer, Joachim; Hamilton, Steven P.; Hamshere, Marian L.; Hansen, Thomas F.; Hartmann, Annette M.; Hautzinger, Martin; Heath, Andrew C.; Henders, Anjali K.; Herms, Stefan; Hickie, Ian B.; Hipolito, Maria; Hoefels, Susanne; Holmans, Peter A.; Holsboer, Florian; Hoogendijk, Witte J.; Hottenga, Jouke-Jan; Hultman, Christina M.; Hus, Vanessa; Ingason, Andres; Ising, Marcus; Jamain, Stephane; Jones, Edward G.; Jones, Ian; Jones, Lisa; Tzeng, Jung-Ying; Kaehler, Anna K.; Kahn, Rene S.; Kandaswamy, Radhika; Keller, Matthew C.; Kennedy, James L.; Kenny, Elaine; Kent, Lindsey; Kim, Yunjung; Kirov, George K.; Klauck, Sabine M.; Klei, Lambertus; Knowles, James A.; Kohli, Martin A.; Koller, Daniel L.; Konte, Bettina; Korszun, Ania; Krabbendam, Lydia; Krasucki, Robert; Kuntsi, Jonna; Kwan, Phoenix; Landen, Mikael; Langstrom, Niklas; Lathrop, Mark; Lawrence, Jacob; Lawson, William B.; Leboyer, Marion; Ledbetter, David H.; Lee, Phil H.; Lencz, Todd; Lesch, Klaus-Peter; Levinson, Douglas F.; Lewis, Cathryn M.; Li, Jun; Lichtenstein, Paul; Lieberman, Jeffrey A.; Lin, Dan-Yu; Linszen, Don H.; Liu, Chunyu; Lohoff, Falk W.; Loo, Sandra K.; Lord, Catherine; Lowe, Jennifer K.; Lucae, Susanne; MacIntyre, Donald J.; Madden, Pamela A. F.; Maestrini, Elena; Magnusson, Patrik K. E.; Mahon, Pamela B.; Maier, Wolfgang; Malhotra, Anil K.; Mane, Shrikant M.; Martin, Christa L.; Martin, Nicholas G.; Mattheisen, Manuel; Matthews, Keith; Mattingsdal, Morten; McCarroll, Steven A.; McGhee, Kevin A.; McGough, James J.; McGrath, Patrick J.; McGuffin, Peter; McInnis, Melvin G.; McIntosh, Andrew; McKinney, Rebecca; McLean, Alan W.; McMahon, Francis J.; McMahon, William M.; McQuillin, Andrew; Medeiros, Helena; Medland, Sarah E.; Meier, Sandra; Melle, Ingrid; Meng, Fan; Meyer, Jobst; Middeldorp, Christel M.; Middleton, Lefkos; Milanova, Vihra; Miranda, Ana; Monaco, Anthony P.; Montgomery, Grant W.; Moran, Jennifer L.; Moreno-De-Luca, Daniel; Morken, Gunnar; Morris, Derek W.; Morrow, Eric M.; Moskvina, Valentina; Muglia, Pierandrea; Muehleisen, Thomas W.; Muir, Walter J.; Mueller-Myhsok, Bertram; Murtha, Michael; Myers, Richard M.; Myin-Germeys, Inez; Neale, Michael C.; Nelson, Stan F.; Nievergelt, Caroline M.; Nikolov, Ivan; Nimgaonkar, Vishwajit; Nolen, Willem A.; Noethen, Markus M.; Nurnberger, John I.; Nwulia, Evaristus A.; Nyholt, Dale R.; O'Dushlaine, Colm; Oades, Robert D.

    Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases

  7. A mega-analysis of genome-wide association studies for major depressive disorder

    NARCIS (Netherlands)

    Sullivan, Patrick F.; Daly, Mark J.; Ripke, Stephan; Lewis, Cathryn M.; Lin, Dan-Yu; Wray, Naomi R.; Neale, Benjamin; Levinson, Douglas F.; Breen, Gerome; Byrne, Enda M.; Wray, Naomi R.; Levinson, Douglas F.; Rietschel, Marcella; Hoogendijk, Witte; Ripke, Stephan; Sullivan, Patrick F.; Hamilton, Steven P.; Levinson, Douglas F.; Lewis, Cathryn M.; Ripke, Stephan; Weissman, Myrna M.; Wray, Naomi R.; Breuer, Rene; Cichon, Sven; Degenhardt, Franziska; Frank, Josef; Gross, Magdalena; Herms, Stefan; Hoefels, Susanne; Maier, Wolfgang; Mattheisen, Manuel; Noeethen, Markus M.; Rietschel, Marcella; Schulze, Thomas G.; Steffens, Michael; Treutlein, Jens; Boomsma, Dorret I.; De Geus, Eco J.; Hoogendijk, Witte; Hottenga, Jouke Jan; Jung-Ying, Tzeng; Lin, Dan-Yu; Middeldorp, Christel M.; Nolen, Willem A.; Penninx, Brenda P.; Smit, Johannes H.; Sullivan, Patrick F.; van Grootheest, Gerard; Willemsen, Gonneke; Zitman, Frans G.; Coryell, William H.; Knowles, James A.; Lawson, William B.; Levinson, Douglas F.; Potash, James B.; Scheftner, William A.; Shi, Jianxin; Weissman, Myrna M.; Holsboer, Florian; Muglia, Pierandrea; Tozzi, Federica; Blackwood, Douglas H. R.; Boomsma, Dorret I.; De Geus, Eco J.; Hottenga, Jouke Jan; MacIntyre, Donald J.; McIntosh, Andrew; McLean, Alan; Middeldorp, Christel M.; Penninx, Brenda P.; Ripke, Stephan; Smit, Johannes H.; Sullivan, Patrick F.; van Grootheest, Gerard; Willemsen, Gonneke; Zitman, Frans G.; van den Oord, Edwin J. C. G.; Holsboer, Florian; Lucae, Susanne; Binder, Elisabeth; Mueller-Myhsok, Bertram; Ripke, Stephan; Czamara, Darina; Kohli, Martin A.; Ising, Marcus; Uhr, Manfred; Bettecken, Thomas; Barnes, Michael R.; Breen, Gerome; Craig, Ian W.; Farmer, Anne E.; Lewis, Cathryn M.; McGuffin, Peter; Muglia, Pierandrea; Byrne, Enda; Gordon, Scott D.; Heath, Andrew C.; Henders, Anjali K.; Hickie, Ian B.; Madden, Pamela A. F.; Martin, Nicholas G.; Montgomery, Grant M.; Nyholt, Dale R.; Pergadia, Michele L.; Wray, Naomi R.; Hamilton, Steven P.; McGrath, Patrick J.; Shyn, Stanley I.; Slager, Susan L.; Oskarsson, Hoegni; Sigurdsson, Engilbert; Stefansson, Hreinn; Stefansson, Kari; Steinberg, Stacy; Thorgeirsson, Thorgeir; Levinson, Douglas F.; Potash, James B.; Shi, Jianxin; Weissman, Myrna M.; Guipponi, Michel; Lewis, Glyn; O'Donovan, Michael; Tansey, Katherine E.; Uher, Rudolf; Coryell, William H.; Knowles, James A.; Lawson, William B.; Levinson, Douglas F.; Potash, James B.; Scheftner, William A.; Shi, Jianxin; Weissman, Myrna M.; Castro, Victor M.; Churchill, Susanne E.; Fava, Maurizio; Gainer, Vivian S.; Gallagher, Patience J.; Goryachev, Sergey; Iosifescu, Dan V.; Kohane, Isaac S.; Murphy, Shawn N.; Perlis, Roy H.; Smoller, Jordan W.; Weilburg, Jeffrey B.; Kutalik, Zoltan; Preisig, Martin; Grabe, Hans J.; Nauck, Matthias; Schulz, Andrea; Teumer, Alexander; Voelzke, Henry; Landen, Mikael; Lichtenstein, Paul; Magnusson, Patrik; Pedersen, Nancy; Viktorin, Alexander

    Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X

  8. Genome-wide gene expression profiling of testicular carcinoma in situ progression into overt tumours

    DEFF Research Database (Denmark)

    Almstrup, K; Hoei-Hansen, C E; Nielsen, J E

    2005-01-01

    into CIS occurs early during foetal life. Progression into an overt tumour, however, typically first happens after puberty, where CIS cells transform into either a seminoma (SEM) or a nonseminoma (N-SEM). Here, we have compared the genome-wide gene expression of CIS cells to that of testicular SEM...

  9. Single-tube linear DNA amplification for genome-wide studies using a few thousand cells

    NARCIS (Netherlands)

    Shankaranarayanan, P.; Mendoza-Parra, M.A.; Gool, van W.; Trindade, L.M.; Gronemeyer, H.

    2012-01-01

    Linear amplification of DNA (LinDA) by T7 polymerase is a versatile and robust method for generating sufficient amounts of DNA for genome-wide studies with minute amounts of cells. LinDA can be coupled to a great number of global profiling technologies. Indeed, chromatin immunoprecipitation coupled

  10. Genome-wide association study of insect bite hypersensitivity in Dutch Shetland pony mares

    NARCIS (Netherlands)

    Schurink, A.; Ducro, B.J.; Bastiaansen, J.W.M.; Frankena, K.; Arendonk, van J.A.M.

    2013-01-01

    Insect bite hypersensitivity (IBH) is the most common allergic disease present in horses worldwide. It has been shown that IBH is under genetic control, but the knowledge of associated genes is limited. We conducted a genome-wide association study to id