Step-wise and punctuated genome evolution drive phenotype changes of tumor cells

Energy Technology Data Exchange (ETDEWEB)

Stepanenko, Aleksei, E-mail: a.a.stepanenko@gmail.com [Department of Biosynthesis of Nucleic Acids, Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, Kyiv 03680 (Ukraine); Andreieva, Svitlana; Korets, Kateryna; Mykytenko, Dmytro [Department of Biosynthesis of Nucleic Acids, Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, Kyiv 03680 (Ukraine); Huleyuk, Nataliya [Institute of Hereditary Pathology, National Academy of Medical Sciences of Ukraine, Lviv 79008 (Ukraine); Vassetzky, Yegor [CNRS UMR8126, Université Paris-Sud 11, Institut de Cancérologie Gustave Roussy, Villejuif 94805 (France); Kavsan, Vadym [Department of Biosynthesis of Nucleic Acids, Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, Kyiv 03680 (Ukraine)

2015-01-15

Highlights: • There are the step-wise continuous and punctuated phases of cancer genome evolution. • The system stresses during the different phases may lead to very different responses. • Stable transfection of an empty vector can result in genome and phenotype changes. • Functions of a (trans)gene can be opposite/versatile in cells with different genomes. • Contextually, temozolomide can both promote and suppress tumor cell aggressiveness. - Abstract: The pattern of genome evolution can be divided into two phases: the step-wise continuous phase (step-wise clonal evolution, stable dominant clonal chromosome aberrations (CCAs), and low frequency of non-CCAs, NCCAs) and punctuated phase (marked by elevated NCCAs and transitional CCAs). Depending on the phase, system stresses (the diverse CIN promoting factors) may lead to the very different phenotype responses. To address the contribution of chromosome instability (CIN) to phenotype changes of tumor cells, we characterized CCAs/NCCAs of HeLa and HEK293 cells, and their derivatives after genotoxic stresses (a stable plasmid transfection, ectopic expression of cancer-associated CHI3L1 gene or treatment with temozolomide) by conventional cytogenetics, copy number alterations (CNAs) by array comparative genome hybridization, and phenotype changes by cell viability and soft agar assays. Transfection of either the empty vector pcDNA3.1 or pcDNA3.1-CHI3L1 into 293 cells initiated the punctuated genome changes. In contrast, HeLa-CHI3L1 cells demonstrated the step-wise genome changes. Increased CIN correlated with lower viability of 293-pcDNA3.1 cells but higher colony formation efficiency (CFE). Artificial CHI3L1 production in 293-CHI3L1 cells increased viability and further contributed to CFE. The opposite growth characteristics of 293-CHI3L1 and HeLa-CHI3L1 cells were revealed. The effect and function of a (trans)gene can be opposite and versatile in cells with different genetic network, which is defined by

Phenotypic Heterogeneity of Genomically-Diverse Isolates of Streptococcus mutans

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Palmer, Sara R.; Miller, James H.; Abranches, Jacqueline; Zeng, Lin; Lefebure, Tristan; Richards, Vincent P.; Lemos, José A.; Stanhope, Michael J.; Burne, Robert A.

2013-01-01

High coverage, whole genome shotgun (WGS) sequencing of 57 geographically- and genetically-diverse isolates of Streptococcus mutans from individuals of known dental caries status was recently completed. Of the 57 sequenced strains, fifteen isolates, were selected based primarily on differences in gene content and phenotypic characteristics known to affect virulence and compared with the reference strain UA159. A high degree of variability in these properties was observed between strains, with a broad spectrum of sensitivities to low pH, oxidative stress (air and paraquat) and exposure to competence stimulating peptide (CSP). Significant differences in autolytic behavior and in biofilm development in glucose or sucrose were also observed. Natural genetic competence varied among isolates, and this was correlated to the presence or absence of competence genes, comCDE and comX, and to bacteriocins. In general strains that lacked the ability to become competent possessed fewer genes for bacteriocins and immunity proteins or contained polymorphic variants of these genes. WGS sequence analysis of the pan-genome revealed, for the first time, components of a Type VII secretion system in several S. mutans strains, as well as two putative ORFs that encode possible collagen binding proteins located upstream of the cnm gene, which is associated with host cell invasiveness. The virulence of these particular strains was assessed in a wax-worm model. This is the first study to combine a comprehensive analysis of key virulence-related phenotypes with extensive genomic analysis of a pathogen that evolved closely with humans. Our analysis highlights the phenotypic diversity of S. mutans isolates and indicates that the species has evolved a variety of adaptive strategies to persist in the human oral cavity and, when conditions are favorable, to initiate disease. PMID:23613838

Phenotypic heterogeneity of genomically-diverse isolates of Streptococcus mutans.

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Sara R Palmer

Full Text Available High coverage, whole genome shotgun (WGS sequencing of 57 geographically- and genetically-diverse isolates of Streptococcus mutans from individuals of known dental caries status was recently completed. Of the 57 sequenced strains, fifteen isolates, were selected based primarily on differences in gene content and phenotypic characteristics known to affect virulence and compared with the reference strain UA159. A high degree of variability in these properties was observed between strains, with a broad spectrum of sensitivities to low pH, oxidative stress (air and paraquat and exposure to competence stimulating peptide (CSP. Significant differences in autolytic behavior and in biofilm development in glucose or sucrose were also observed. Natural genetic competence varied among isolates, and this was correlated to the presence or absence of competence genes, comCDE and comX, and to bacteriocins. In general strains that lacked the ability to become competent possessed fewer genes for bacteriocins and immunity proteins or contained polymorphic variants of these genes. WGS sequence analysis of the pan-genome revealed, for the first time, components of a Type VII secretion system in several S. mutans strains, as well as two putative ORFs that encode possible collagen binding proteins located upstream of the cnm gene, which is associated with host cell invasiveness. The virulence of these particular strains was assessed in a wax-worm model. This is the first study to combine a comprehensive analysis of key virulence-related phenotypes with extensive genomic analysis of a pathogen that evolved closely with humans. Our analysis highlights the phenotypic diversity of S. mutans isolates and indicates that the species has evolved a variety of adaptive strategies to persist in the human oral cavity and, when conditions are favorable, to initiate disease.

Genome-wide association analyses of expression phenotypes.

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Chen, Gary K; Zheng, Tian; Witte, John S; Goode, Ellen L; Gao, Lei; Hu, Pingzhao; Suh, Young Ju; Suktitipat, Bhoom; Szymczak, Silke; Woo, Jung Hoon; Zhang, Wei

2007-01-01

A number of issues arise when analyzing the large amount of data from high-throughput genotype and expression microarray experiments, including design and interpretation of genome-wide association studies of expression phenotypes. These issues were considered by contributions submitted to Group 1 of the Genetic Analysis Workshop 15 (GAW15), which focused on the association of quantitative expression data. These contributions evaluated diverse hypotheses, including those relevant to cancer and obesity research, and used various analytic techniques, many of which were derived from information theory. Several observations from these reports stand out. First, one needs to consider the genetic model of the trait of interest and carefully select which single nucleotide polymorphisms and individuals are included early in the design stage of a study. Second, by targeting specific pathways when analyzing genome-wide data, one can generate more interpretable results than agnostic approaches. Finally, for datasets with small sample sizes but a large number of features like the Genetic Analysis Workshop 15 dataset, machine learning approaches may be more practical than traditional parametric approaches. (c) 2007 Wiley-Liss, Inc.

Genomics technologies to study structural variations in the grapevine genome

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Cardone Maria Francesca

2016-01-01

Full Text Available Grapevine is one of the most important crop plants in the world. Recently there was great expansion of genomics resources about grapevine genome, thus providing increasing efforts for molecular breeding. Current cultivars display a great level of inter-specific differentiation that needs to be investigated to reach a comprehensive understanding of the genetic basis of phenotypic differences, and to find responsible genes selected by cross breeding programs. While there have been significant advances in resolving the pattern and nature of single nucleotide polymorphisms (SNPs on plant genomes, few data are available on copy number variation (CNV. Furthermore association between structural variations and phenotypes has been described in only a few cases. We combined high throughput biotechnologies and bioinformatics tools, to reveal the first inter-varietal atlas of structural variation (SV for the grapevine genome. We sequenced and compared four table grape cultivars with the Pinot noir inbred line PN40024 genome as the reference. We detected roughly 8% of the grapevine genome affected by genomic variations. Taken into account phenotypic differences existing among the studied varieties we performed comparison of SVs among them and the reference and next we performed an in-depth analysis of gene content of polymorphic regions. This allowed us to identify genes showing differences in copy number as putative functional candidates for important traits in grapevine cultivation.

Genome-wide association study identifies HLA 8.1 ancestral haplotype alleles as major genetic risk factors for myositis phenotypes.

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Miller, F W; Chen, W; O'Hanlon, T P; Cooper, R G; Vencovsky, J; Rider, L G; Danko, K; Wedderburn, L R; Lundberg, I E; Pachman, L M; Reed, A M; Ytterberg, S R; Padyukov, L; Selva-O'Callaghan, A; Radstake, T R; Isenberg, D A; Chinoy, H; Ollier, W E R; Scheet, P; Peng, B; Lee, A; Byun, J; Lamb, J A; Gregersen, P K; Amos, C I

2015-10-01

Autoimmune muscle diseases (myositis) comprise a group of complex phenotypes influenced by genetic and environmental factors. To identify genetic risk factors in patients of European ancestry, we conducted a genome-wide association study (GWAS) of the major myositis phenotypes in a total of 1710 cases, which included 705 adult dermatomyositis, 473 juvenile dermatomyositis, 532 polymyositis and 202 adult dermatomyositis, juvenile dermatomyositis or polymyositis patients with anti-histidyl-tRNA synthetase (anti-Jo-1) autoantibodies, and compared them with 4724 controls. Single-nucleotide polymorphisms showing strong associations (Pmyositis phenotypes together, as well as for the four clinical and autoantibody phenotypes studied separately. Imputation and regression analyses found that alleles comprising the human leukocyte antigen (HLA) 8.1 ancestral haplotype (AH8.1) defined essentially all the genetic risk in the phenotypes studied. Although the HLA DRB1*03:01 allele showed slightly stronger associations with adult and juvenile dermatomyositis, and HLA B*08:01 with polymyositis and anti-Jo-1 autoantibody-positive myositis, multiple alleles of AH8.1 were required for the full risk effects. Our findings establish that alleles of the AH8.1 comprise the primary genetic risk factors associated with the major myositis phenotypes in geographically diverse Caucasian populations.

Utilization of genomic signatures to identify phenotype-specific drugs.

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Seiichi Mori

2009-08-01

Full Text Available Genetic and genomic studies highlight the substantial complexity and heterogeneity of human cancers and emphasize the general lack of therapeutics that can match this complexity. With the goal of expanding opportunities for drug discovery, we describe an approach that makes use of a phenotype-based screen combined with the use of multiple cancer cell lines. In particular, we have used the NCI-60 cancer cell line panel that includes drug sensitivity measures for over 40,000 compounds assayed on 59 independent cells lines. Targets are cancer-relevant phenotypes represented as gene expression signatures that are used to identify cells within the NCI-60 panel reflecting the signature phenotype and then connect to compounds that are selectively active against those cells. As a proof-of-concept, we show that this strategy effectively identifies compounds with selectivity to the RAS or PI3K pathways. We have then extended this strategy to identify compounds that have activity towards cells exhibiting the basal phenotype of breast cancer, a clinically-important breast cancer characterized as ER-, PR-, and Her2- that lacks viable therapeutic options. One of these compounds, Simvastatin, has previously been shown to inhibit breast cancer cell growth in vitro and importantly, has been associated with a reduction in ER-, PR- breast cancer in a clinical study. We suggest that this approach provides a novel strategy towards identification of therapeutic agents based on clinically relevant phenotypes that can augment the conventional strategies of target-based screens.

Metabolic profiles to define the genome: can we hear the phenotypes?

OpenAIRE

Griffin, Julian L

2004-01-01

There is an increased reliance on genetically modified organisms as a functional genomic tool to elucidate the role of genes and their protein products. Despite this, many models do not express the expected phenotype thought to be associated with the gene or protein. There is thus an increased need to further define the phenotype resultant from a genetic modification to understand how the transcriptional or proteomic network may conspire to alter the expected phenotype. This is best typified ...

Impact of phenotype definition on genome-wide association signals: empirical evaluation in human immunodeficiency virus type 1 infection

DEFF Research Database (Denmark)

Evangelou, Evangelos; Fellay, Jacques; Colombo, Sara

2011-01-01

Discussion on improving the power of genome-wide association studies to identify candidate variants and genes is generally centered on issues of maximizing sample size; less attention is given to the role of phenotype definition and ascertainment. The authors used genome-wide data from patients...... infected with human immunodeficiency virus type 1 (HIV-1) to assess whether differences in type of population (622 seroconverters vs. 636 seroprevalent subjects) or the number of measurements available for defining the phenotype resulted in differences in the effect sizes of associations between single...... available, particularly among seroconverters and for variants that achieved genome-wide significance. Differences in phenotype definition and ascertainment may affect the estimated magnitude of genetic effects and should be considered in optimizing power for discovering new associations....

Using whole-genome sequence data to predict quantitative trait phenotypes in Drosophila melanogaster.

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Ulrike Ober

Full Text Available Predicting organismal phenotypes from genotype data is important for plant and animal breeding, medicine, and evolutionary biology. Genomic-based phenotype prediction has been applied for single-nucleotide polymorphism (SNP genotyping platforms, but not using complete genome sequences. Here, we report genomic prediction for starvation stress resistance and startle response in Drosophila melanogaster, using ∼2.5 million SNPs determined by sequencing the Drosophila Genetic Reference Panel population of inbred lines. We constructed a genomic relationship matrix from the SNP data and used it in a genomic best linear unbiased prediction (GBLUP model. We assessed predictive ability as the correlation between predicted genetic values and observed phenotypes by cross-validation, and found a predictive ability of 0.239±0.008 (0.230±0.012 for starvation resistance (startle response. The predictive ability of BayesB, a Bayesian method with internal SNP selection, was not greater than GBLUP. Selection of the 5% SNPs with either the highest absolute effect or variance explained did not improve predictive ability. Predictive ability decreased only when fewer than 150,000 SNPs were used to construct the genomic relationship matrix. We hypothesize that predictive power in this population stems from the SNP-based modeling of the subtle relationship structure caused by long-range linkage disequilibrium and not from population structure or SNPs in linkage disequilibrium with causal variants. We discuss the implications of these results for genomic prediction in other organisms.

Primer in Genetics and Genomics, Article 5-Further Defining the Concepts of Genotype and Phenotype and Exploring Genotype-Phenotype Associations.

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Wright, Fay; Fessele, Kristen

2017-10-01

As nurses begin to incorporate genetic and genomic sciences into clinical practice, education, and research, it is essential that they have a working knowledge of the terms foundational to the science. The first article in this primer series provided brief definitions of the basic terms (e.g., genetics and genomics) and introduced the concept of phenotype during the discussion of Mendelian inheritance. These terms, however, are inconsistently used in publications and conversations, and the linkage between genotype and phenotype requires clarification. The goal of this fifth article in the series is to elucidate these terms, provide an overview of the research methods used to determine genotype-phenotype associations, and discuss their significance to nursing through examples from the current nursing literature.

Towards precision medicine-based therapies for glioblastoma: interrogating human disease genomics and mouse phenotypes.

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Chen, Yang; Gao, Zhen; Wang, Bingcheng; Xu, Rong

2016-08-22

Glioblastoma (GBM) is the most common and aggressive brain tumors. It has poor prognosis even with optimal radio- and chemo-therapies. Since GBM is highly heterogeneous, drugs that target on specific molecular profiles of individual tumors may achieve maximized efficacy. Currently, the Cancer Genome Atlas (TCGA) projects have identified hundreds of GBM-associated genes. We develop a drug repositioning approach combining disease genomics and mouse phenotype data towards predicting targeted therapies for GBM. We first identified disease specific mouse phenotypes using the most recently discovered GBM genes. Then we systematically searched all FDA-approved drugs for candidates that share similar mouse phenotype profiles with GBM. We evaluated the ranks for approved and novel GBM drugs, and compared with an existing approach, which also use the mouse phenotype data but not the disease genomics data. We achieved significantly higher ranks for the approved and novel GBM drugs than the earlier approach. For all positive examples of GBM drugs, we achieved a median rank of 9.2 45.6 of the top predictions have been demonstrated effective in inhibiting the growth of human GBM cells. We developed a computational drug repositioning approach based on both genomic and phenotypic data. Our approach prioritized existing GBM drugs and outperformed a recent approach. Overall, our approach shows potential in discovering new targeted therapies for GBM.

Lessons from a phenotyping center revealed by the genome-guided mapping of powdery mildew resistance loci

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The genomics era brought unprecedented tools for genetic analysis of host resistance, but careful attention is needed on obtaining accurate and reproducible phenotypes so that genomic results appropriately reflect biology. Phenotyping host resistance by natural infection in the field can produce var...

OligoPVP: Phenotype-driven analysis of individual genomic information to prioritize oligogenic disease variants

KAUST Repository

Boudellioua, Imene

2018-05-02

Purpose: An increasing number of Mendelian disorders have been identified for which two or more variants in one or more genes are required to cause the disease, or significantly modify its severity or phenotype. It is difficult to discover such interactions using existing approaches. The purpose of our work is to develop and evaluate a system that can identify combinations of variants underlying oligogenic diseases in individual whole exome or whole genome sequences. Methods: Information that links patient phenotypes to databases of gene-phenotype associations observed in clinical research can provide useful information and improve variant prioritization for Mendelian diseases. Additionally, background knowledge about interactions between genes can be utilized to guide and restrict the selection of candidate disease modules. Results: We developed OligoPVP, an algorithm that can be used to identify variants in oligogenic diseases and their interactions, using whole exome or whole genome sequences together with patient phenotypes as input. We demonstrate that OligoPVP has significantly improved performance when compared to state of the art pathogenicity detection methods. Conclusions: Our results show that OligoPVP can efficiently detect oligogenic interactions using a phenotype-driven approach and identify etiologically important variants in whole genomes.

Skipper genome sheds light on unique phenotypic traits and phylogeny.

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Cong, Qian; Borek, Dominika; Otwinowski, Zbyszek; Grishin, Nick V

2015-08-27

Butterflies and moths are emerging as model organisms in genetics and evolutionary studies. The family Hesperiidae (skippers) was traditionally viewed as a sister to other butterflies based on its moth-like morphology and darting flight habits with fast wing beats. However, DNA studies suggest that the family Papilionidae (swallowtails) may be the sister to other butterflies including skippers. The moth-like features and the controversial position of skippers in Lepidoptera phylogeny make them valuable targets for comparative genomics. We obtained the 310 Mb draft genome of the Clouded Skipper (Lerema accius) from a wild-caught specimen using a cost-effective strategy that overcomes the high (1.6 %) heterozygosity problem. Comparative analysis of Lerema accius and the highly heterozygous genome of Papilio glaucus revealed differences in patterns of SNP distribution, but similarities in functions of genes that are enriched in non-synonymous SNPs. Comparison of Lepidoptera genomes revealed possible molecular bases for unique traits of skippers: a duplication of electron transport chain components could result in efficient energy supply for their rapid flight; a diversified family of predicted cellulases might allow them to feed on cellulose-enriched grasses; an expansion of pheromone-binding proteins and enzymes for pheromone synthesis implies a more efficient mate-recognition system, which compensates for the lack of clear visual cues due to the similarities in wing colors and patterns of many species of skippers. Phylogenetic analysis of several Lepidoptera genomes suggested that the position of Hesperiidae remains uncertain as the tree topology varied depending on the evolutionary model. Completion of the first genome from the family Hesperiidae allowed comparative analyses with other Lepidoptera that revealed potential genetic bases for the unique phenotypic traits of skippers. This work lays the foundation for future experimental studies of skippers and

A “Forward Genomics” Approach Links Genotype to Phenotype using Independent Phenotypic Losses among Related Species

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Michael Hiller

2012-10-01

Full Text Available Genotype-phenotype mapping is hampered by countless genomic changes between species. We introduce a computational “forward genomics” strategy that—given only an independently lost phenotype and whole genomes—matches genomic and phenotypic loss patterns to associate specific genomic regions with this phenotype. We conducted genome-wide screens for two metabolic phenotypes. First, our approach correctly matches the inactivated Gulo gene exactly with the species that lost the ability to synthesize vitamin C. Second, we attribute naturally low biliary phospholipid levels in guinea pigs and horses to the inactivated phospholipid transporter Abcb4. Human ABCB4 mutations also result in low phospholipid levels but lead to severe liver disease, suggesting compensatory mechanisms in guinea pig and horse. Our simulation studies, counts of independent changes in existing phenotype surveys, and the forthcoming availability of many new genomes all suggest that forward genomics can be applied to many phenotypes, including those relevant for human evolution and disease.

Integrative Genomics: Quantifying significance of phenotype-genotype relationships from multiple sources of high-throughput data

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Eric eGamazon

2013-05-01

Full Text Available Given recent advances in the generation of high-throughput data such as whole genome genetic variation and transcriptome expression, it is critical to come up with novel methods to integrate these heterogeneous datasets and to assess the significance of identified phenotype-genotype relationships. Recent studies show that genome-wide association findings are likely to fall in loci with gene regulatory effects such as expression quantitative trait loci (eQTLs, demonstrating the utility of such integrative approaches. When genotype and gene expression data are available on the same individuals, we developed methods wherein top phenotype-associated genetic variants are prioritized if they are associated, as eQTLs, with gene expression traits that are themselves associated with the phenotype. Yet there has been no method to determine an overall p-value for the findings that arise specifically from the integrative nature of the approach. We propose a computationally feasible permutation method that accounts for the assimilative nature of the method and the correlation structure among gene expression traits and among genotypes. We apply the method to data from a study of cellular sensitivity to etoposide, one of the most widely used chemotherapeutic drugs. To our knowledge, this study is the first statistically sound quantification of the significance of the genotype-phenotype relationships resulting from applying an integrative approach. This method can be easily extended to cases in which gene expression data are replaced by other molecular phenotypes of interest, e.g., microRNA or proteomic data. This study has important implications for studies seeking to expand on genetic association studies by the use of omics data. Finally, we provide an R code to compute the empirical FDR when p-values for the observed and simulated phenotypes are available.

Mining Genome-Scale Growth Phenotype Data through Constant-Column Biclustering

KAUST Repository

Alzahrani, Majed A.

2017-07-10

Growth phenotype profiling of genome-wide gene-deletion strains over stress conditions can offer a clear picture that the essentiality of genes depends on environmental conditions. Systematically identifying groups of genes from such recently emerging high-throughput data that share similar patterns of conditional essentiality and dispensability under various environmental conditions can elucidate how genetic interactions of the growth phenotype are regulated in response to the environment. In this dissertation, we first demonstrate that detecting such “co-fit” gene groups can be cast as a less well-studied problem in biclustering, i.e., constant-column biclustering. Despite significant advances in biclustering techniques, very few were designed for mining in growth phenotype data. Here, we propose Gracob, a novel, efficient graph-based method that casts and solves the constant-column biclustering problem as a maximal clique finding problem in a multipartite graph. We compared Gracob with a large collection of widely used biclustering methods that cover different types of algorithms designed to detect different types of biclusters. Gracob showed superior performance on finding co-fit genes over all the existing methods on both a variety of synthetic data sets with a wide range of settings, and three real growth phenotype data sets for E. coli, proteobacteria, and yeast.

Association Study of Three Gene Polymorphisms Recently Identified by a Genome-Wide Association Study with Obesity-Related Phenotypes in Chinese Children.

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Song, Qi-Ying; Song, Jie-Yun; Wang, Yang; Wang, Shuo; Yang, Yi-De; Meng, Xiang-Rui; Ma, Jun; Wang, Hai-Jun; Wang, Yan

2017-01-01

This study aimed to examine associations of three single-nucleotide polymorphisms (SNPs) with obesity-related phenotypes in Chinese children. These SNPs were identified by a recent genome-wide association (GWA) study among European children. Given that varied genetic backgrounds across different ethnicity may result in different association, it is necessary to study these associations in a different ethnic population. A total of 3,922 children, including 2,191 normal-weight, 873 overweight and 858 obese children, from three independent studies were included in the study. Logistic and linear regressions were performed, and meta-analyses were conducted to assess the associations between the SNPs and obesity-related phenotypes. The pooled odds ratios of the A-allele of rs564343 in PACS1 for obesity and severe obesity were 1.180 (p = 0.03) and 1.312 (p = 0.004), respectively. We also found that rs564343 was nominally associated with BMI, BMI standard deviation score (BMI-SDS), waist circumference, and waist-to-height ratio (p obesity in a non-European population. This SNP was also found to be associated with common obesity and various obesity-related phenotypes in Chinese children, which had not been reported in the original study. The results demonstrated the value of conducting genetic researches in populations with different ethnicity. © 2017 The Author(s) Published by S. Karger GmbH, Freiburg.

Whole-genome sequencing reveals mutational landscape underlying phenotypic differences between two widespread Chinese cattle breeds.

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Yao Xu

Full Text Available Whole-genome sequencing provides a powerful tool to obtain more genetic variability that could produce a range of benefits for cattle breeding industry. Nanyang (Bos indicus and Qinchuan (Bos taurus are two important Chinese indigenous cattle breeds with distinct phenotypes. To identify the genetic characteristics responsible for variation in phenotypes between the two breeds, in the present study, we for the first time sequenced the genomes of four Nanyang and four Qinchuan cattle with 10 to 12 fold on average of 97.86% and 98.98% coverage of genomes, respectively. Comparison with the Bos_taurus_UMD_3.1 reference assembly yielded 9,010,096 SNPs for Nanyang, and 6,965,062 for Qinchuan cattle, 51% and 29% of which were novel SNPs, respectively. A total of 154,934 and 115,032 small indels (1 to 3 bp were found in the Nanyang and Qinchuan genomes, respectively. The SNP and indel distribution revealed that Nanyang showed a genetically high diversity as compared to Qinchuan cattle. Furthermore, a total of 2,907 putative cases of copy number variation (CNV were identified by aligning Nanyang to Qinchuan genome, 783 of which (27% encompassed the coding regions of 495 functional genes. The gene ontology (GO analysis revealed that many CNV genes were enriched in the immune system and environment adaptability. Among several CNV genes related to lipid transport and fat metabolism, Lepin receptor gene (LEPR overlapping with CNV_1815 showed remarkably higher copy number in Qinchuan than Nanyang (log2 (ratio = -2.34988; P value = 1.53E-102. Further qPCR and association analysis investigated that the copy number of the LEPR gene presented positive correlations with transcriptional expression and phenotypic traits, suggesting the LEPR CNV may contribute to the higher fat deposition in muscles of Qinchuan cattle. Our findings provide evidence that the distinct phenotypes of Nanyang and Qinchuan breeds may be due to the different genetic variations including SNPs

Genomic structural variation contributes to phenotypic change of industrial bioethanol yeast Saccharomyces cerevisiae.

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Zhang, Ke; Zhang, Li-Jie; Fang, Ya-Hong; Jin, Xin-Na; Qi, Lei; Wu, Xue-Chang; Zheng, Dao-Qiong

2016-03-01

Genomic structural variation (GSV) is a ubiquitous phenomenon observed in the genomes of Saccharomyces cerevisiae strains with different genetic backgrounds; however, the physiological and phenotypic effects of GSV are not well understood. Here, we first revealed the genetic characteristics of a widely used industrial S. cerevisiae strain, ZTW1, by whole genome sequencing. ZTW1 was identified as an aneuploidy strain and a large-scale GSV was observed in the ZTW1 genome compared with the genome of a diploid strain YJS329. These GSV events led to copy number variations (CNVs) in many chromosomal segments as well as one whole chromosome in the ZTW1 genome. Changes in the DNA dosage of certain functional genes directly affected their expression levels and the resultant ZTW1 phenotypes. Moreover, CNVs of large chromosomal regions triggered an aneuploidy stress in ZTW1. This stress decreased the proliferation ability and tolerance of ZTW1 to various stresses, while aneuploidy response stress may also provide some benefits to the fermentation performance of the yeast, including increased fermentation rates and decreased byproduct generation. This work reveals genomic characters of the bioethanol S. cerevisiae strain ZTW1 and suggests that GSV is an important kind of mutation that changes the traits of industrial S. cerevisiae strains. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Genomic and phenotypic characteristics of Swedish C. jejuni water isolates.

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Anna Nilsson

Full Text Available Campylobacter jejuni is the most common cause of bacterial gastroenteritis. Major reservoirs are warm-blooded animals, poultry in particular, but Campylobacter can also be transmitted via water. In this paper, we have taken a closer look at the biology and potential virulence of C. jejuni water isolates. Seven C. jejuni isolates from incoming surface water at water plants in Sweden were characterized with whole genome sequencing and phenotypical testing. Multi locus sequence typing analysis revealed that these isolates belonged to groups known to include both common (ST48CC and uncommon (ST1275CC, ST683, ST793 and ST8853 human pathogens. Further genomic characterization revealed that these isolates had potential for arsenic resistance (due to presence of arsB gene in all isolates, an anaerobic dimethyl sulfoxide oxidoreductase (in three isolates and lacked the MarR-type transcriptional regulator gene rrpB (in all but one isolate earlier shown to be involved in better survival under oxidative and aerobic stress. As putative virulence factors were concerned, there were differences between the water isolates in the presence of genes coding for cytolethal distending toxin (cdtABC, Type VI secretion system and sialylated LOS, as well as in biofilm formation. However, all isolates were motile and could adhere to and invade the human HT-29 colon cancer cell line in vitro and induce IL-8 secretion suggesting potential to infect humans. This is, to the best of our knowledge, the first study where C. jejuni water isolates have been characterized using whole genome sequencing and phenotypical assays. We found differences and shared traits among the isolates but also potential to infect humans.

Identification of genomic regions associated with phenotypic variation between dog breeds using selection mapping.

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Amaury Vaysse

2011-10-01

Full Text Available The extraordinary phenotypic diversity of dog breeds has been sculpted by a unique population history accompanied by selection for novel and desirable traits. Here we perform a comprehensive analysis using multiple test statistics to identify regions under selection in 509 dogs from 46 diverse breeds using a newly developed high-density genotyping array consisting of >170,000 evenly spaced SNPs. We first identify 44 genomic regions exhibiting extreme differentiation across multiple breeds. Genetic variation in these regions correlates with variation in several phenotypic traits that vary between breeds, and we identify novel associations with both morphological and behavioral traits. We next scan the genome for signatures of selective sweeps in single breeds, characterized by long regions of reduced heterozygosity and fixation of extended haplotypes. These scans identify hundreds of regions, including 22 blocks of homozygosity longer than one megabase in certain breeds. Candidate selection loci are strongly enriched for developmental genes. We chose one highly differentiated region, associated with body size and ear morphology, and characterized it using high-throughput sequencing to provide a list of variants that may directly affect these traits. This study provides a catalogue of genomic regions showing extreme reduction in genetic variation or population differentiation in dogs, including many linked to phenotypic variation. The many blocks of reduced haplotype diversity observed across the genome in dog breeds are the result of both selection and genetic drift, but extended blocks of homozygosity on a megabase scale appear to be best explained by selection. Further elucidation of the variants under selection will help to uncover the genetic basis of complex traits and disease.

Moving into a new era of periodontal genetic studies: relevance of large case-control samples using severe phenotypes for genome-wide association studies.

Science.gov (United States)

Vaithilingam, R D; Safii, S H; Baharuddin, N A; Ng, C C; Cheong, S C; Bartold, P M; Schaefer, A S; Loos, B G

2014-12-01

Studies to elucidate the role of genetics as a risk factor for periodontal disease have gone through various phases. In the majority of cases, the initial 'hypothesis-dependent' candidate-gene polymorphism studies did not report valid genetic risk loci. Following a large-scale replication study, these initially positive results are believed to be caused by type 1 errors. However, susceptibility genes, such as CDKN2BAS (Cyclin Dependend KiNase 2B AntiSense RNA; alias ANRIL [ANtisense Rna In the Ink locus]), glycosyltransferase 6 domain containing 1 (GLT6D1) and cyclooxygenase 2 (COX2), have been reported as conclusive risk loci of periodontitis. The search for genetic risk factors accelerated with the advent of 'hypothesis-free' genome-wide association studies (GWAS). However, despite many different GWAS being performed for almost all human diseases, only three GWAS on periodontitis have been published - one reported genome-wide association of GLT6D1 with aggressive periodontitis (a severe phenotype of periodontitis), whereas the remaining two, which were performed on patients with chronic periodontitis, were not able to find significant associations. This review discusses the problems faced and the lessons learned from the search for genetic risk variants of periodontitis. Current and future strategies for identifying genetic variance in periodontitis, and the importance of planning a well-designed genetic study with large and sufficiently powered case-control samples of severe phenotypes, are also discussed. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A Comparative Pan-Genome Perspective of Niche-Adaptable Cell-Surface Protein Phenotypes in Lactobacillus rhamnosus

Science.gov (United States)

Kant, Ravi; Sigvart-Mattila, Pia; Paulin, Lars; Mecklin, Jukka-Pekka; Saarela, Maria; Palva, Airi; von Ossowski, Ingemar

2014-01-01

Lactobacillus rhamnosus is a ubiquitously adaptable Gram-positive bacterium and as a typical commensal can be recovered from various microbe-accessible bodily orifices and cavities. Then again, other isolates are food-borne, with some of these having been long associated with naturally fermented cheeses and yogurts. Additionally, because of perceived health benefits to humans and animals, numerous L. rhamnosus strains have been selected for use as so-called probiotics and are often taken in the form of dietary supplements and functional foods. At the genome level, it is anticipated that certain genetic variances will have provided the niche-related phenotypes that augment the flexible adaptiveness of this species, thus enabling its strains to grow and survive in their respective host environments. For this present study, we considered it functionally informative to examine and catalogue the genotype-phenotype variation existing at the cell surface between different L. rhamnosus strains, with the presumption that this might be relatable to habitat preferences and ecological adaptability. Here, we conducted a pan-genomic study involving 13 genomes from L. rhamnosus isolates with various origins. In using a benchmark strain (gut-adapted L. rhamnosus GG) for our pan-genome comparison, we had focused our efforts on a detailed examination and description of gene products for certain functionally relevant surface-exposed proteins, each of which in effect might also play a part in niche adaptability among the other strains. Perhaps most significantly of the surface protein loci we had analyzed, it would appear that the spaCBA operon (known to encode SpaCBA-called pili having a mucoadhesive phenotype) is a genomic rarity and an uncommon occurrence in L. rhamnosus. However, for any of the so-piliated L. rhamnosus strains, they will likely possess an increased niche-specific fitness, which functionally might presumably be manifested by a protracted transient colonization of

Leveraging Comparative Genomics to Identify and Functionally Characterize Genes Associated with Sperm Phenotypes in Python bivittatus (Burmese Python

Directory of Open Access Journals (Sweden)

Kristopher J. L. Irizarry

2016-01-01

Full Text Available Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism’s genome (such as the mouse genome in order to make physiological inferences about the role of genes and proteins in a less characterized organism’s genome (such as the Burmese python. We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1 production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2 enhanced assisted reproduction technology for endangered and captive reptiles; and (3 novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value.

Genome Sequencing Reveals Loci under Artificial Selection that Underlie Disease Phenotypes in the Laboratory Rat

NARCIS (Netherlands)

Atanur, Santosh S.; Diaz, Ana Garcia; Maratou, Klio; Sarkis, Allison; Rotival, Maxime; Game, Laurence; Tschannen, Michael R.; Kaisaki, Pamela J.; Otto, Georg W.; Ma, Man Chun John; Keane, Thomas M.; Hummel, Oliver; Saar, Kathrin; Chen, Wei; Guryev, Victor; Gopalakrishnan, Kathirvel; Garrett, Michael R.; Joe, Bina; Citterio, Lorena; Bianchi, Giuseppe; McBride, Martin; Dominiczak, Anna; Adams, David J.; Serikawa, Tadao; Flicek, Paul; Cuppen, Edwin; Hubner, Norbert; Petretto, Enrico; Gauguier, Dominique; Kwitek, Anne; Jacob, Howard; Aitman, Timothy J.

2013-01-01

Large numbers of inbred laboratory rat strains have been developed for a range of complex disease phenotypes. To gain insights into the evolutionary pressures underlying selection for these phenotypes, we sequenced the genomes of 27 rat strains, including 11 models of hypertension, diabetes, and

Familial Case of Pelizaeus-Merzbacher Disorder Detected by Oligoarray Comparative Genomic Hybridization: Genotype-to-Phenotype Diagnosis

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Kimia Najafi

2017-01-01

Full Text Available Introduction. Pelizaeus-Merzbacher disease (PMD is an X-linked recessive hypomyelinating leukodystrophy characterized by nystagmus, spastic quadriplegia, ataxia, and developmental delay. It is caused by mutation in the PLP1 gene. Case Description. We report a 9-year-old boy referred for oligoarray comparative genomic hybridization (OA-CGH because of intellectual delay, seizures, microcephaly, nystagmus, and spastic paraplegia. Similar clinical findings were reported in his older brother and maternal uncle. Both parents had normal phenotypes. OA-CGH was performed and a 436 Kb duplication was detected and the diagnosis of PMD was made. The mother was carrier of this 436 Kb duplication. Conclusion. Clinical presentation has been accepted as being the mainstay of diagnosis for most conditions. However, recent developments in genetic diagnosis have shown that, in many congenital and sporadic disorders lacking specific phenotypic manifestations, a genotype-to-phenotype approach can be conclusive. In this case, a diagnosis was reached by universal genomic testing, namely, whole genomic array.

Genome duplication and mutations in ACE2 cause multicellular, fast-sedimenting phenotypes in evolved Saccharomyces cerevisiae.

Science.gov (United States)

Oud, Bart; Guadalupe-Medina, Victor; Nijkamp, Jurgen F; de Ridder, Dick; Pronk, Jack T; van Maris, Antonius J A; Daran, Jean-Marc

2013-11-05

Laboratory evolution of the yeast Saccharomyces cerevisiae in bioreactor batch cultures yielded variants that grow as multicellular, fast-sedimenting clusters. Knowledge of the molecular basis of this phenomenon may contribute to the understanding of natural evolution of multicellularity and to manipulating cell sedimentation in laboratory and industrial applications of S. cerevisiae. Multicellular, fast-sedimenting lineages obtained from a haploid S. cerevisiae strain in two independent evolution experiments were analyzed by whole genome resequencing. The two evolved cell lines showed different frameshift mutations in a stretch of eight adenosines in ACE2, which encodes a transcriptional regulator involved in cell cycle control and mother-daughter cell separation. Introduction of the two ace2 mutant alleles into the haploid parental strain led to slow-sedimenting cell clusters that consisted of just a few cells, thus representing only a partial reconstruction of the evolved phenotype. In addition to single-nucleotide mutations, a whole-genome duplication event had occurred in both evolved multicellular strains. Construction of a diploid reference strain with two mutant ace2 alleles led to complete reconstruction of the multicellular-fast sedimenting phenotype. This study shows that whole-genome duplication and a frameshift mutation in ACE2 are sufficient to generate a fast-sedimenting, multicellular phenotype in S. cerevisiae. The nature of the ace2 mutations and their occurrence in two independent evolution experiments encompassing fewer than 500 generations of selective growth suggest that switching between unicellular and multicellular phenotypes may be relevant for competitiveness of S. cerevisiae in natural environments.

Genetic susceptibility markers for a breast-colorectal cancer phenotype: Exploratory results from genome-wide association studies

Science.gov (United States)

Joon, Aron; Brewster, Abenaa M.; Chen, Wei V.; Eng, Cathy; Shete, Sanjay; Casey, Graham; Schumacher, Fredrick; Lin, Yi; Harrison, Tabitha A.; White, Emily; Ahsan, Habibul; Andrulis, Irene L.; Whittemore, Alice S.; Ko Win, Aung; Schmidt, Daniel F.; Kapuscinski, Miroslaw K.; Ochs-Balcom, Heather M.; Gallinger, Steven; Jenkins, Mark A.; Newcomb, Polly A.; Lindor, Noralane M.; Peters, Ulrike; Amos, Christopher I.; Lynch, Patrick M.

2018-01-01

Background Clustering of breast and colorectal cancer has been observed within some families and cannot be explained by chance or known high-risk mutations in major susceptibility genes. Potential shared genetic susceptibility between breast and colorectal cancer, not explained by high-penetrance genes, has been postulated. We hypothesized that yet undiscovered genetic variants predispose to a breast-colorectal cancer phenotype. Methods To identify variants associated with a breast-colorectal cancer phenotype, we analyzed genome-wide association study (GWAS) data from cases and controls that met the following criteria: cases (n = 985) were women with breast cancer who had one or more first- or second-degree relatives with colorectal cancer, men/women with colorectal cancer who had one or more first- or second-degree relatives with breast cancer, and women diagnosed with both breast and colorectal cancer. Controls (n = 1769), were unrelated, breast and colorectal cancer-free, and age- and sex- frequency-matched to cases. After imputation, 6,220,060 variants were analyzed using the discovery set and variants associated with the breast-colorectal cancer phenotype at Pcolorectal cancer phenotype in the discovery and replication data (most significant; rs7430339, Pdiscovery = 1.2E-04; rs7429100, Preplication = 2.8E-03). In meta-analysis of the discovery and replication data, the most significant association remained at rs7429100 (P = 1.84E-06). Conclusion The results of this exploratory analysis did not find clear evidence for a susceptibility locus with a pleiotropic effect on hereditary breast and colorectal cancer risk, although the suggestive association of genetic variation in the region of ROBO1, a potential tumor suppressor gene, merits further investigation. PMID:29698419

Widespread differential maternal and paternal genome effects on fetal bone phenotype at mid-gestation.

Science.gov (United States)

Xiang, Ruidong; Lee, Alice M C; Eindorf, Tanja; Javadmanesh, Ali; Ghanipoor-Samami, Mani; Gugger, Madeleine; Fitzsimmons, Carolyn J; Kruk, Zbigniew A; Pitchford, Wayne S; Leviton, Alison J; Thomsen, Dana A; Beckman, Ian; Anderson, Gail I; Burns, Brian M; Rutley, David L; Xian, Cory J; Hiendleder, Stefan

2014-11-01

Parent-of-origin-dependent (epi)genetic factors are important determinants of prenatal development that program adult phenotype. However, data on magnitude and specificity of maternal and paternal genome effects on fetal bone are lacking. We used an outbred bovine model to dissect and quantify effects of parental genomes, fetal sex, and nongenetic maternal effects on the fetal skeleton and analyzed phenotypic and molecular relationships between fetal muscle and bone. Analysis of 51 bone morphometric and weight parameters from 72 fetuses recovered at day 153 gestation (54% term) identified six principal components (PC1-6) that explained 80% of the variation in skeletal parameters. Parental genomes accounted for most of the variation in bone wet weight (PC1, 72.1%), limb ossification (PC2, 99.8%), flat bone size (PC4, 99.7%), and axial skeletal growth (PC5, 96.9%). Limb length showed lesser effects of parental genomes (PC3, 40.8%) and a significant nongenetic maternal effect (gestational weight gain, 29%). Fetal sex affected bone wet weight (PC1, p maternal genome effects on bone wet weight (74.1%, p paternal genome controlled limb ossification (95.1%, p maternal genome effects on growth plate height (98.6%, p maternal genome effects on fetal serum 25-hydroxyvitamin D (96.9%, p paternal genome effects on alkaline phosphatase (90.0%, p maternally controlled bone wet weight and paternally controlled limb ossification, respectively. Bone wet weight and flat bone size correlated positively with muscle weight (r = 0.84 and 0.77, p maternally expressed H19 regulates growth factors by miRNA interference, this suggests muscle-bone interaction via epigenetic factors. © 2014 American Society for Bone and Mineral Research.

Genomic agonism and phenotypic antagonism between estrogen and progesterone receptors in breast cancer

OpenAIRE

Singhal, Hari; Greene, Marianne E.; Tarulli, Gerard; Zarnke, Allison L.; Bourgo, Ryan J.; Laine, Muriel; Chang, Ya-Fang; Ma, Shihong; Dembo, Anna G.; Raj, Ganesh V.; Hickey, Theresa E.; Tilley, Wayne D.; Greene, Geoffrey L.

2016-01-01

The functional role of progesterone receptor (PR) and its impact on estrogen signaling in breast cancer remain controversial. In primary ER+ (estrogen receptor?positive)/PR+ human tumors, we report that PR reprograms estrogen signaling as a genomic agonist and a phenotypic antagonist. In isolation, estrogen and progestin act as genomic agonists by regulating the expression of common target genes in similar directions, but at different levels. Similarly, in isolation, progestin is also a weak ...

Matching phenotypes to whole genomes: Lessons learned from four iterations of the personal genome project community challenges.

Science.gov (United States)

Cai, Binghuang; Li, Biao; Kiga, Nikki; Thusberg, Janita; Bergquist, Timothy; Chen, Yun-Ching; Niknafs, Noushin; Carter, Hannah; Tokheim, Collin; Beleva-Guthrie, Violeta; Douville, Christopher; Bhattacharya, Rohit; Yeo, Hui Ting Grace; Fan, Jean; Sengupta, Sohini; Kim, Dewey; Cline, Melissa; Turner, Tychele; Diekhans, Mark; Zaucha, Jan; Pal, Lipika R; Cao, Chen; Yu, Chen-Hsin; Yin, Yizhou; Carraro, Marco; Giollo, Manuel; Ferrari, Carlo; Leonardi, Emanuela; Tosatto, Silvio C E; Bobe, Jason; Ball, Madeleine; Hoskins, Roger A; Repo, Susanna; Church, George; Brenner, Steven E; Moult, John; Gough, Julian; Stanke, Mario; Karchin, Rachel; Mooney, Sean D

2017-09-01

The advent of next-generation sequencing has dramatically decreased the cost for whole-genome sequencing and increased the viability for its application in research and clinical care. The Personal Genome Project (PGP) provides unrestricted access to genomes of individuals and their associated phenotypes. This resource enabled the Critical Assessment of Genome Interpretation (CAGI) to create a community challenge to assess the bioinformatics community's ability to predict traits from whole genomes. In the CAGI PGP challenge, researchers were asked to predict whether an individual had a particular trait or profile based on their whole genome. Several approaches were used to assess submissions, including ROC AUC (area under receiver operating characteristic curve), probability rankings, the number of correct predictions, and statistical significance simulations. Overall, we found that prediction of individual traits is difficult, relying on a strong knowledge of trait frequency within the general population, whereas matching genomes to trait profiles relies heavily upon a small number of common traits including ancestry, blood type, and eye color. When a rare genetic disorder is present, profiles can be matched when one or more pathogenic variants are identified. Prediction accuracy has improved substantially over the last 6 years due to improved methodology and a better understanding of features. © 2017 Wiley Periodicals, Inc.

Genome-wide association studies in asthma: progress and pitfalls

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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

Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations.

Science.gov (United States)

Shi, Hongbo; Zhang, Guangde; Zhou, Meng; Cheng, Liang; Yang, Haixiu; Wang, Jing; Sun, Jie; Wang, Zhenzhen

2016-01-01

MicroRNAs (miRNAs) play an important role in the development and progression of human diseases. The identification of disease-associated miRNAs will be helpful for understanding the molecular mechanisms of diseases at the post-transcriptional level. Based on different types of genomic data sources, computational methods for miRNA-disease association prediction have been proposed. However, individual source of genomic data tends to be incomplete and noisy; therefore, the integration of various types of genomic data for inferring reliable miRNA-disease associations is urgently needed. In this study, we present a computational framework, CHNmiRD, for identifying miRNA-disease associations by integrating multiple genomic and phenotype data, including protein-protein interaction data, gene ontology data, experimentally verified miRNA-target relationships, disease phenotype information and known miRNA-disease connections. The performance of CHNmiRD was evaluated by experimentally verified miRNA-disease associations, which achieved an area under the ROC curve (AUC) of 0.834 for 5-fold cross-validation. In particular, CHNmiRD displayed excellent performance for diseases without any known related miRNAs. The results of case studies for three human diseases (glioblastoma, myocardial infarction and type 1 diabetes) showed that all of the top 10 ranked miRNAs having no known associations with these three diseases in existing miRNA-disease databases were directly or indirectly confirmed by our latest literature mining. All these results demonstrated the reliability and efficiency of CHNmiRD, and it is anticipated that CHNmiRD will serve as a powerful bioinformatics method for mining novel disease-related miRNAs and providing a new perspective into molecular mechanisms underlying human diseases at the post-transcriptional level. CHNmiRD is freely available at http://www.bio-bigdata.com/CHNmiRD.

Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations.

Directory of Open Access Journals (Sweden)

Hongbo Shi

Full Text Available MicroRNAs (miRNAs play an important role in the development and progression of human diseases. The identification of disease-associated miRNAs will be helpful for understanding the molecular mechanisms of diseases at the post-transcriptional level. Based on different types of genomic data sources, computational methods for miRNA-disease association prediction have been proposed. However, individual source of genomic data tends to be incomplete and noisy; therefore, the integration of various types of genomic data for inferring reliable miRNA-disease associations is urgently needed. In this study, we present a computational framework, CHNmiRD, for identifying miRNA-disease associations by integrating multiple genomic and phenotype data, including protein-protein interaction data, gene ontology data, experimentally verified miRNA-target relationships, disease phenotype information and known miRNA-disease connections. The performance of CHNmiRD was evaluated by experimentally verified miRNA-disease associations, which achieved an area under the ROC curve (AUC of 0.834 for 5-fold cross-validation. In particular, CHNmiRD displayed excellent performance for diseases without any known related miRNAs. The results of case studies for three human diseases (glioblastoma, myocardial infarction and type 1 diabetes showed that all of the top 10 ranked miRNAs having no known associations with these three diseases in existing miRNA-disease databases were directly or indirectly confirmed by our latest literature mining. All these results demonstrated the reliability and efficiency of CHNmiRD, and it is anticipated that CHNmiRD will serve as a powerful bioinformatics method for mining novel disease-related miRNAs and providing a new perspective into molecular mechanisms underlying human diseases at the post-transcriptional level. CHNmiRD is freely available at http://www.bio-bigdata.com/CHNmiRD.

Genomic and Phenotypic Characterization of Yeast Biosensor for Deep-space Radiation

Science.gov (United States)

Marina, Diana B.; Santa Maria, Sergio; Bhattacharya, Sharmila

2016-01-01

The BioSentinel mission was selected to launch as a secondary payload onboard NASA Exploration Mission 1 (EM-1) in 2018. In BioSentinel, the budding yeast Saccharomyces cerevisiae will be used as a biosensor to measure the long-term impact of deep-space radiation to living organisms. In the 4U-payload, desiccated yeast cells from different strains will be stored inside microfluidic cards equipped with 3-color LED optical detection system to monitor cell growth and metabolic activity. At different times throughout the 12-month mission, these cards will be filled with liquid yeast growth media to rehydrate and grow the desiccated cells. The growth and metabolic rates of wild-type and radiation-sensitive strains in deep-space radiation environment will be compared to the rates measured in the ground- and microgravity-control units. These rates will also be correlated with measurements obtained from onboard physical dosimeters. In our preliminary long-term desiccation study, we found that air-drying yeast cells in 10% trehalose is the best method of cell preservation in order to survive the entire 18-month mission duration (6-month pre-launch plus 12-month full-mission periods). However, our study also revealed that desiccated yeast cells have decreasing viability over time when stored in payload-like environment. This suggests that the yeast biosensor will have different population of cells at different time points during the long-term mission. In this study, we are characterizing genomic and phenotypic changes in our yeast biosensor due to long-term storage and desiccation. For each yeast strain that will be part of the biosensor, several clones were reisolated after long-term storage by desiccation. These clones were compared to their respective original isolate in terms of genomic composition, desiccation tolerance and radiation sensitivity. Interestingly, clones from a radiation-sensitive mutant have better desiccation tolerance compared to their original isolate

Quantitative Seq-LGS: Genome-Wide Identification of Genetic Drivers of Multiple Phenotypes in Malaria Parasites

KAUST Repository

Abkallo, Hussein M.

2016-10-01

Identifying the genetic determinants of phenotypes that impact on disease severity is of fundamental importance for the design of new interventions against malaria. Traditionally, such discovery has relied on labor-intensive approaches that require significant investments of time and resources. By combining Linkage Group Selection (LGS), quantitative whole genome population sequencing and a novel mathematical modeling approach (qSeq-LGS), we simultaneously identified multiple genes underlying two distinct phenotypes, identifying novel alleles for growth rate and strain specific immunity (SSI), while removing the need for traditionally required steps such as cloning, individual progeny phenotyping and marker generation. The detection of novel variants, verified by experimental phenotyping methods, demonstrates the remarkable potential of this approach for the identification of genes controlling selectable phenotypes in malaria and other apicomplexan parasites for which experimental genetic crosses are amenable.

Advanced phenotyping and phenotype data analysis for the plant growth and development study

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Md. Matiur eRahaman

2015-08-01

Full Text Available Due to increase in the consumption of food, feed, fuel and to ensure global food security for rapidly growing human population, there is need to breed high yielding crops that can adapt to future climate. To solve these global issues, novel approaches are required to provide quantitative phenotypes to elucidate the genetic basis of agriculturally import traits and to screen germplasm with super performance in function under resource-limited environment. At present, plant phenomics has offered and integrated suite technologies for understanding the complete set of phenotypes of plants, towards the progression of the full characteristics of plants with whole sequenced genomes. In this aspect, high-throughput phenotyping platforms have been developed that enables to capture extensive and intensive phenotype data from non-destructive imaging over time. These developments advance our view on plant growth and performance with responses to the changing climate and environment. In this paper, we present a brief review on currently developed high-throughput plant phenotyping infrastructures based on imaging techniques and corresponding principles for phenotype data analysis.

A Genome-Wide Association Study Suggests Novel Loci Associated with a Schizophrenia-Related Brain-Based Phenotype.

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Johanna Hass

Full Text Available Patients with schizophrenia and their siblings typically show subtle changes of brain structures, such as a reduction of hippocampal volume. Hippocampal volume is heritable, may explain a variety of cognitive symptoms of schizophrenia and is thus considered an intermediate phenotype for this mental illness. The aim of our analyses was to identify single-nucleotide polymorphisms (SNP related to hippocampal volume without making prior assumptions about possible candidate genes. In this study, we combined genetics, imaging and neuropsychological data obtained from the Mind Clinical Imaging Consortium study of schizophrenia (n = 328. A total of 743,591 SNPs were tested for association with hippocampal volume in a genome-wide association study. Gene expression profiles of human hippocampal tissue were investigated for gene regions of significantly associated SNPs. None of the genetic markers reached genome-wide significance. However, six highly correlated SNPs (rs4808611, rs35686037, rs12982178, rs1042178, rs10406920, rs8170 on chromosome 19p13.11, located within or in close proximity to the genes NR2F6, USHBP1, and BABAM1, as well as four SNPs in three other genomic regions (chromosome 1, 2 and 10 had p-values between 6.75×10(-6 and 8.3×10(-7. Using existing data of a very recently published GWAS of hippocampal volume and additional data of a multicentre study in a large cohort of adolescents of European ancestry, we found supporting evidence for our results. Furthermore, allelic differences in rs4808611 and rs8170 were highly associated with differential mRNA expression in the cis-acting region. Associations with memory functioning indicate a possible functional importance of the identified risk variants. Our findings provide new insights into the genetic architecture of a brain structure closely linked to schizophrenia. In silico replication, mRNA expression and cognitive data provide additional support for the relevance of our findings

Uncovering genomic causes of co-morbidity in epilepsy: gene-driven phenotypic characterization of rare microdeletions.

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Dalia Kasperavičiūtė

Full Text Available Patients with epilepsy often suffer from other important conditions. The existence of such co-morbidities is frequently not recognized and their relationship with epilepsy usually remains unexplained.We describe three patients with common, sporadic, non-syndromic epilepsies in whom large genomic microdeletions were found during a study of genetic susceptibility to epilepsy. We performed detailed gene-driven clinical investigations in each patient. Disruption of the function of genes in the deleted regions can explain co-morbidities in these patients.Co-morbidities in patients with epilepsy can be part of a genomic abnormality even in the absence of (known congenital malformations or intellectual disabilities. Gene-driven phenotype examination can also reveal clinically significant unsuspected condition.

Renal cell carcinoma primary cultures maintain genomic and phenotypic profile of parental tumor tissues

International Nuclear Information System (INIS)

Cifola, Ingrid; Magni, Fulvio; Signorini, Stefano; Battaglia, Cristina; Perego, Roberto A; Bianchi, Cristina; Mangano, Eleonora; Bombelli, Silvia; Frascati, Fabio; Fasoli, Ester; Ferrero, Stefano; Di Stefano, Vitalba; Zipeto, Maria A

2011-01-01

Clear cell renal cell carcinoma (ccRCC) is characterized by recurrent copy number alterations (CNAs) and loss of heterozygosity (LOH), which may have potential diagnostic and prognostic applications. Here, we explored whether ccRCC primary cultures, established from surgical tumor specimens, maintain the DNA profile of parental tumor tissues allowing a more confident CNAs and LOH discrimination with respect to the original tissues. We established a collection of 9 phenotypically well-characterized ccRCC primary cell cultures. Using the Affymetrix SNP array technology, we performed the genome-wide copy number (CN) profiling of both cultures and corresponding tumor tissues. Global concordance for each culture/tissue pair was assayed evaluating the correlations between whole-genome CN profiles and SNP allelic calls. CN analysis was performed using the two CNAG v3.0 and Partek software, and comparing results returned by two different algorithms (Hidden Markov Model and Genomic Segmentation). A very good overlap between the CNAs of each culture and corresponding tissue was observed. The finding, reinforced by high whole-genome CN correlations and SNP call concordances, provided evidence that each culture was derived from its corresponding tissue and maintained the genomic alterations of parental tumor. In addition, primary culture DNA profile remained stable for at least 3 weeks, till to third passage. These cultures showed a greater cell homogeneity and enrichment in tumor component than original tissues, thus enabling a better discrimination of CNAs and LOH. Especially for hemizygous deletions, primary cultures presented more evident CN losses, typically accompanied by LOH; differently, in original tissues the intensity of these deletions was weaken by normal cell contamination and LOH calls were missed. ccRCC primary cultures are a reliable in vitro model, well-reproducing original tumor genetics and phenotype, potentially useful for future functional approaches

Complete genome sequence of the cystic fibrosis pathogen Achromobacter xylosoxidans NH44784-1996 complies with important pathogenic phenotypes

DEFF Research Database (Denmark)

Jakobsen, Tim Holm; Hansen, Martin Asser; Jensen, Peter Østrup

2013-01-01

Achromobacter xylosoxidans is an environmental opportunistic pathogen, which infects an increasing number of immunocompromised patients. In this study we combined genomic analysis of a clinical isolated A. xylosoxidans strain with phenotypic investigations of its important pathogenic features. We...... that render it an opportunistic human pathogen, We found genes involved in anaerobic growth and the pgaABCD operon encoding the biofilm adhesin poly-β-1,6-N-acetyl-D-glucosamin. Furthermore, the genome contains a range of antibiotic resistance genes coding efflux pump systems and antibiotic modifying enzymes....... In vitro studies of A. xylosoxidans NH44784-1996 confirmed the genomic evidence for its ability to form biofilms, anaerobic growth via denitrification, and resistance to a broad range of antibiotics. Our investigation enables further studies of the functionality of important identified genes contributing...

A genome-wide analysis of promoter-mediated phenotypic noise in Escherichia coli.

Directory of Open Access Journals (Sweden)

Olin K Silander

2012-01-01

Full Text Available Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as "phenotypic noise." In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alone.

Genome-wide association analysis identifies 11 risk variants associated with the asthma with hay fever phenotype.

Science.gov (United States)

Ferreira, Manuel A R; Matheson, Melanie C; Tang, Clara S; Granell, Raquel; Ang, Wei; Hui, Jennie; Kiefer, Amy K; Duffy, David L; Baltic, Svetlana; Danoy, Patrick; Bui, Minh; Price, Loren; Sly, Peter D; Eriksson, Nicholas; Madden, Pamela A; Abramson, Michael J; Holt, Patrick G; Heath, Andrew C; Hunter, Michael; Musk, Bill; Robertson, Colin F; Le Souëf, Peter; Montgomery, Grant W; Henderson, A John; Tung, Joyce Y; Dharmage, Shyamali C; Brown, Matthew A; James, Alan; Thompson, Philip J; Pennell, Craig; Martin, Nicholas G; Evans, David M; Hinds, David A; Hopper, John L

2014-06-01

To date, no genome-wide association study (GWAS) has considered the combined phenotype of asthma with hay fever. Previous analyses of family data from the Tasmanian Longitudinal Health Study provide evidence that this phenotype has a stronger genetic cause than asthma without hay fever. We sought to perform a GWAS of asthma with hay fever to identify variants associated with having both diseases. We performed a meta-analysis of GWASs comparing persons with both physician-diagnosed asthma and hay fever (n = 6,685) with persons with neither disease (n = 14,091). At genome-wide significance, we identified 11 independent variants associated with the risk of having asthma with hay fever, including 2 associations reaching this level of significance with allergic disease for the first time: ZBTB10 (rs7009110; odds ratio [OR], 1.14; P = 4 × 10(-9)) and CLEC16A (rs62026376; OR, 1.17; P = 1 × 10(-8)). The rs62026376:C allele associated with increased asthma with hay fever risk has been found to be associated also with decreased expression of the nearby DEXI gene in monocytes. The 11 variants were associated with the risk of asthma and hay fever separately, but the estimated associations with the individual phenotypes were weaker than with the combined asthma with hay fever phenotype. A variant near LRRC32 was a stronger risk factor for hay fever than for asthma, whereas the reverse was observed for variants in/near GSDMA and TSLP. Single nucleotide polymorphisms with suggestive evidence for association with asthma with hay fever risk included rs41295115 near IL2RA (OR, 1.28; P = 5 × 10(-7)) and rs76043829 in TNS1 (OR, 1.23; P = 2 × 10(-6)). By focusing on the combined phenotype of asthma with hay fever, variants associated with the risk of allergic disease can be identified with greater efficiency. Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

Phenotypic and Genomic Analysis of Hypervirulent Human-associated Bordetella bronchiseptica

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Ahuja Umesh

2012-08-01

Full Text Available Abstract Background B. bronchiseptica infections are usually associated with wild or domesticated animals, but infrequently with humans. A recent phylogenetic analysis distinguished two distinct B. bronchiseptica subpopulations, designated complexes I and IV. Complex IV isolates appear to have a bias for infecting humans; however, little is known regarding their epidemiology, virulence properties, or comparative genomics. Results Here we report a characterization of the virulence of human-associated complex IV B. bronchiseptica strains. In in vitro cytotoxicity assays, complex IV strains showed increased cytotoxicity in comparison to a panel of complex I strains. Some complex IV isolates were remarkably cytotoxic, resulting in LDH release levels in A549 cells that were 10- to 20-fold greater than complex I strains. In vivo, a subset of complex IV strains was found to be hypervirulent, with an increased ability to cause lethal pulmonary infections in mice. Hypercytotoxicity in vitro and hypervirulence in vivo were both dependent on the activity of the bsc T3SS and the BteA effector. To clarify differences between lineages, representative complex IV isolates were sequenced and their genomes were compared to complex I isolates. Although our analysis showed there were no genomic sequences that can be considered unique to complex IV strains, there were several loci that were predominantly found in complex IV isolates. Conclusion Our observations reveal a T3SS-dependent hypervirulence phenotype in human-associated complex IV isolates, highlighting the need for further studies on the epidemiology and evolutionary dynamics of this B. bronchiseptica lineage.

A genome-wide association study of anorexia nervosa suggests a risk locus implicated in dysregulated leptin signaling

NARCIS (Netherlands)

Li, Dong; Chang, Xiao; Connolly, John J.; Tian, Lifeng; Liu, Yichuan; Bhoj, Elizabeth J.; Robinson, Nora; Abrams, Debra; Li, Yun R.; Bradfield, Jonathan P.; Kim, Cecilia E.; Li, Jin; Wang, Fengxiang; Snyder, James; Lemma, Maria; Hou, Cuiping; Wei, Zhi; Guo, Yiran; Qiu, Haijun; Mentch, Frank D.; Thomas, Kelly A.; Chiavacci, Rosetta M.; Cone, Roger; Li, Bingshan; Sleiman, Patrick A.; Hakonarson, Hakon; Perica, Vesna Boraska; Franklin, Christopher S.; Floyd, James A.B.; Thornton, Laura M.; Huckins, Laura M.; Southam, Lorraine; Rayner, William N; Tachmazidou, Ioanna; Schmidt, Ulrike; Tozzi, Federica; Kiezebrink, Kirsty; Hebebrand, Johannes; Gorwood, Philip; Adan, Roger A.H.; Kas, Martien J.H.; Favaro, Angela; Santonastaso, Paolo; Fernánde-Aranda, Fernando; Gratacos, Monica; Rybakowski, Filip; Dmitrzak-Weglarz, Monika; Kaprio, Jaakko; Keski-Rahkonen, Anna; Raevuori-Helkamaa, Anu; Furth, Eric F.Van; Slof-Opt Landt, Margarita C.T.; Hudson, James I.; Reichborn-Kjennerud, Ted; Knudsen, Gun Peggy S.; Monteleone, Palmiero; Karwautz, Andreas; Berrettini, Wade H.; Schork, Nicholas J.; Ando, Tetsuya; Inoko, Hidetoshi; Esko, Toñu; Fischer, Krista; Männik, Katrin; Metspalu, Andres; Baker, Jessica H.; DeSocio, Janiece E.; Hilliard, Christopher E.; O'Toole, Julie K.; Pantel, Jacques; Szatkiewicz, Jin P.; Zerwas, Stephanie; Davis, Oliver S P; Helder, Sietske; Bühren, Katharina; Burghardt, Roland; De Zwaan, Martina; Egberts, Karin; Ehrlich, Stefan; Herpertz-Dahlmann, Beate; Herzog, Wolfgang; Imgart, Hartmut; Scherag, André; Zipfel, Stephan; Boni, Claudette; Ramoz, Nicolas; Versini, Audrey; Danner, Unna N.; Hendriks, Judith; Koeleman, Bobby P.C.; 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 J; 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 W.; Aschauer, Harald; Carlberg, Laura; Schosser, Alexandra; Alfredsson, Lars; Ding, Bo; Klareskog, Lars; Padyukov, Leonid; Finan, Chris; Kalsi, Gursharan; Roberts, Marion; Barrett, Jeff C.; Estivill, Xavier; Hinney, Anke; Sullivan, Patrick F; Zeggini, Eleftheria; Bulik, Cynthia M.; Brandt, Harry; Crawford, Steve; Crow, Scott; Fichter, Manfred M.; Halmi, Katherine A.; Johnson, Craig; Kaplan, Allan S.; La Via, Maria C.; Mitchell, James R.; Strober, Michael; Rotondo, Alessandro; Treasure, Janet; Woodside, D. Blake; Keel, Pamela K.; Klump, Kelly L.; Lilenfeld, Lisa; Bergen, Andrew W.; Kaye, Walter; Magistretti, Pierre

2017-01-01

We conducted a genome-wide association study (GWAS) of anorexia nervosa (AN) using a stringently defined phenotype. Analysis of phenotypic variability led to the identification of a specific genetic risk factor that approached genome-wide significance (rs929626 in EBF1 (Early B-Cell Factor 1); P =

Genomic analysis of natural selection and phenotypic variation in high-altitude mongolians.

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Jinchuan Xing

Full Text Available Deedu (DU Mongolians, who migrated from the Mongolian steppes to the Qinghai-Tibetan Plateau approximately 500 years ago, are challenged by environmental conditions similar to native Tibetan highlanders. Identification of adaptive genetic factors in this population could provide insight into coordinated physiological responses to this environment. Here we examine genomic and phenotypic variation in this unique population and present the first complete analysis of a Mongolian whole-genome sequence. High-density SNP array data demonstrate that DU Mongolians share genetic ancestry with other Mongolian as well as Tibetan populations, specifically in genomic regions related with adaptation to high altitude. Several selection candidate genes identified in DU Mongolians are shared with other Asian groups (e.g., EDAR, neighboring Tibetan populations (including high-altitude candidates EPAS1, PKLR, and CYP2E1, as well as genes previously hypothesized to be associated with metabolic adaptation (e.g., PPARG. Hemoglobin concentration, a trait associated with high-altitude adaptation in Tibetans, is at an intermediate level in DU Mongolians compared to Tibetans and Han Chinese at comparable altitude. Whole-genome sequence from a DU Mongolian (Tianjiao1 shows that about 2% of the genomic variants, including more than 300 protein-coding changes, are specific to this individual. Our analyses of DU Mongolians and the first Mongolian genome provide valuable insight into genetic adaptation to extreme environments.

Convergent functional genomics in addiction research - a translational approach to study candidate genes and gene networks.

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Spanagel, Rainer

2013-01-01

Convergent functional genomics (CFG) is a translational methodology that integrates in a Bayesian fashion multiple lines of evidence from studies in human and animal models to get a better understanding of the genetics of a disease or pathological behavior. Here the integration of data sets that derive from forward genetics in animals and genetic association studies including genome wide association studies (GWAS) in humans is described for addictive behavior. The aim of forward genetics in animals and association studies in humans is to identify mutations (e.g. SNPs) that produce a certain phenotype; i.e. "from phenotype to genotype". Most powerful in terms of forward genetics is combined quantitative trait loci (QTL) analysis and gene expression profiling in recombinant inbreed rodent lines or genetically selected animals for a specific phenotype, e.g. high vs. low drug consumption. By Bayesian scoring genomic information from forward genetics in animals is then combined with human GWAS data on a similar addiction-relevant phenotype. This integrative approach generates a robust candidate gene list that has to be functionally validated by means of reverse genetics in animals; i.e. "from genotype to phenotype". It is proposed that studying addiction relevant phenotypes and endophenotypes by this CFG approach will allow a better determination of the genetics of addictive behavior.

Study of genetics, phenotypic and behavioral properties of eubacteria and archaebacteria

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Hamid Kazemian

2016-06-01

Full Text Available Background: The genome of the bacteria has considerable diversity in terms of sequence of nucleotide bases and change over the time. With the advancement of bioinformatics science possibility of the vast comparison to living organisms has risen. During the last two decades many information about genome sequencing of pathogenic and non-pathogenic bacteria have been published. Using this information and to find connections between them and many phenotypic characteristics and behavior of bacteria could be used in many studies. In this study we compared some of the genetic, phenotypic and behavioral properties of archaebacteria and eubacteria. Methods: In this analytical study, genomic Information of 286 species of archaebacteria and 122 species of eubacteria were collected from the NCBI (National Center for Biotechnology Information site which was conducted in April to June 2015. Mean of gene size, gene number, protein number and C+G content compared in the two groups of archaebacteria and eubacteria. Association of genomic characterization of bacteria with several other characteristics were analyzed using SPSS statistical software version 19 (Chicago, IL, USA. For this purpose, the Pearson correlation coefficient (Pearson, Student’s t-test and ANOVA test (One-way analysis of variance was used. The P values less than 0.05 was considered as significant level. Results: There was significant association between means discrepancy in two group (P= 0.01. The genome size of eubacteria and archaebacteria have significant association with some of the characteristics of bacteria, such as the C+G content, the number of proteins, genes and habitats of the bacteria (P= 0.01. As well as there was significant association between genome size and features such as number of pseudogene, mobility and type of breathing in eubacteria (P= 0.01 but not in archaebacterial (P˃ 0.05. Conclusion: Many characteristics of eubacteria and archaebacteria are significantly

Phenotypic and genomic analysis of serotype 3 Sabin poliovirus vaccine produced in MRC-5 cell substrate.

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Alirezaie, Behnam; Taqavian, Mohammad; Aghaiypour, Khosrow; Esna-Ashari, Fatemeh; Shafyi, Abbas

2011-05-01

The cell substrate has a pivotal role in live virus vaccines production. It is necessary to evaluate the effects of the cell substrate on the properties of the propagated viruses, especially in the case of viruses which are unstable genetically such as polioviruses, by monitoring the molecular and phenotypical characteristics of harvested viruses. To investigate the presence/absence of mutation(s), the near full-length genomic sequence of different harvests of the type 3 Sabin strain of poliovirus propagated in MRC-5 cells were determined. The sequences were compared with genomic sequences of different virus seeds, vaccines, and OPV-like isolates. Nearly complete genomic sequencing results, however, revealed no detectable mutations throughout the genome RNA-plaque purified (RSO)-derived monopool of type 3 OPVs manufactured in MRC-5. Thirty-six years of experience in OPV production, trend analysis, and vaccine surveillance also suggest that: (i) different monopools of serotype 3 OPV produced in MRC-5 retained their phenotypic characteristics (temperature sensitivity and neuroattenuation), (ii) MRC-5 cells support the production of acceptable virus yields, (iii) OPV replicated in the MRC-5 cell substrate is a highly efficient and safe vaccine. These results confirm previous reports that MRC-5 is a desirable cell substrate for the production of OPV. Copyright © 2011 Wiley-Liss, Inc.

Regenerant arabidopsis lineages display a distinct genome-wide spectrum of mutations conferring variant phenotypes

KAUST Repository

Jiang, Caifu

2011-07-28

Multicellular organisms can be regenerated from totipotent differentiated somatic cell or nuclear founders [1-3]. Organisms regenerated from clonally related isogenic founders might a priori have been expected to be phenotypically invariant. However, clonal regenerant animals display variant phenotypes caused by defective epigenetic reprogramming of gene expression [2], and clonal regenerant plants exhibit poorly understood heritable phenotypic ("somaclonal") variation [4-7]. Here we show that somaclonal variation in regenerant Arabidopsis lineages is associated with genome-wide elevation in DNA sequence mutation rate. We also show that regenerant mutations comprise a distinctive molecular spectrum of base substitutions, insertions, and deletions that probably results from decreased DNA repair fidelity. Finally, we show that while regenerant base substitutions are a likely major genetic cause of the somaclonal variation of regenerant Arabidopsis lineages, transposon movement is unlikely to contribute substantially to that variation. We conclude that the phenotypic variation of regenerant plants, unlike that of regenerant animals, is substantially due to DNA sequence mutation. 2011 Elsevier Ltd. All rights reserved.

Regenerant arabidopsis lineages display a distinct genome-wide spectrum of mutations conferring variant phenotypes

KAUST Repository

Jiang, Caifu; Mithani, Aziz; Gan, Xiangchao; Belfield, Eric J.; Klingler, John  P.; Zhu, Jian-Kang; Ragoussis, Jiannis; Mott, Richard; Harberd, Nicholas  P.

2011-01-01

Multicellular organisms can be regenerated from totipotent differentiated somatic cell or nuclear founders [1-3]. Organisms regenerated from clonally related isogenic founders might a priori have been expected to be phenotypically invariant. However, clonal regenerant animals display variant phenotypes caused by defective epigenetic reprogramming of gene expression [2], and clonal regenerant plants exhibit poorly understood heritable phenotypic ("somaclonal") variation [4-7]. Here we show that somaclonal variation in regenerant Arabidopsis lineages is associated with genome-wide elevation in DNA sequence mutation rate. We also show that regenerant mutations comprise a distinctive molecular spectrum of base substitutions, insertions, and deletions that probably results from decreased DNA repair fidelity. Finally, we show that while regenerant base substitutions are a likely major genetic cause of the somaclonal variation of regenerant Arabidopsis lineages, transposon movement is unlikely to contribute substantially to that variation. We conclude that the phenotypic variation of regenerant plants, unlike that of regenerant animals, is substantially due to DNA sequence mutation. 2011 Elsevier Ltd. All rights reserved.

Renal cell carcinoma primary cultures maintain genomic and phenotypic profile of parental tumor tissues.

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Cifola, Ingrid; Bianchi, Cristina; Mangano, Eleonora; Bombelli, Silvia; Frascati, Fabio; Fasoli, Ester; Ferrero, Stefano; Di Stefano, Vitalba; Zipeto, Maria A; Magni, Fulvio; Signorini, Stefano; Battaglia, Cristina; Perego, Roberto A

2011-06-13

Clear cell renal cell carcinoma (ccRCC) is characterized by recurrent copy number alterations (CNAs) and loss of heterozygosity (LOH), which may have potential diagnostic and prognostic applications. Here, we explored whether ccRCC primary cultures, established from surgical tumor specimens, maintain the DNA profile of parental tumor tissues allowing a more confident CNAs and LOH discrimination with respect to the original tissues. We established a collection of 9 phenotypically well-characterized ccRCC primary cell cultures. Using the Affymetrix SNP array technology, we performed the genome-wide copy number (CN) profiling of both cultures and corresponding tumor tissues. Global concordance for each culture/tissue pair was assayed evaluating the correlations between whole-genome CN profiles and SNP allelic calls. CN analysis was performed using the two CNAG v3.0 and Partek software, and comparing results returned by two different algorithms (Hidden Markov Model and Genomic Segmentation). A very good overlap between the CNAs of each culture and corresponding tissue was observed. The finding, reinforced by high whole-genome CN correlations and SNP call concordances, provided evidence that each culture was derived from its corresponding tissue and maintained the genomic alterations of parental tumor. In addition, primary culture DNA profile remained stable for at least 3 weeks, till to third passage. These cultures showed a greater cell homogeneity and enrichment in tumor component than original tissues, thus enabling a better discrimination of CNAs and LOH. Especially for hemizygous deletions, primary cultures presented more evident CN losses, typically accompanied by LOH; differently, in original tissues the intensity of these deletions was weaken by normal cell contamination and LOH calls were missed. ccRCC primary cultures are a reliable in vitro model, well-reproducing original tumor genetics and phenotype, potentially useful for future functional approaches

From Genome to Phenotype: An Integrative Approach to Evaluate the Biodiversity of Lactococcus lactis

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Laroute, Valérie; Tormo, Hélène; Couderc, Christel; Mercier-Bonin, Muriel; Le Bourgeois, Pascal; Cocaign-Bousquet, Muriel; Daveran-Mingot, Marie-Line

2017-01-01

Lactococcus lactis is one of the most extensively used lactic acid bacteria for the manufacture of dairy products. Exploring the biodiversity of L. lactis is extremely promising both to acquire new knowledge and for food and health-driven applications. L. lactis is divided into four subspecies: lactis, cremoris, hordniae and tructae, but only subsp. lactis and subsp. cremoris are of industrial interest. Due to its various biotopes, Lactococcus subsp. lactis is considered the most diverse. The diversity of L. lactis subsp. lactis has been assessed at genetic, genomic and phenotypic levels. Multi-Locus Sequence Type (MLST) analysis of strains from different origins revealed that the subsp. lactis can be classified in two groups: “domesticated” strains with low genetic diversity, and “environmental” strains that are the main contributors of the genetic diversity of the subsp. lactis. As expected, the phenotype investigation of L. lactis strains reported here revealed highly diverse carbohydrate metabolism, especially in plant- and gut-derived carbohydrates, diacetyl production and stress survival. The integration of genotypic and phenotypic studies could improve the relevance of screening culture collections for the selection of strains dedicated to specific functions and applications. PMID:28534821

Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa.

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Duncan, Laramie; Yilmaz, Zeynep; Gaspar, Helena; Walters, Raymond; Goldstein, Jackie; Anttila, Verneri; Bulik-Sullivan, Brendan; Ripke, Stephan; Thornton, Laura; Hinney, Anke; Daly, Mark; Sullivan, Patrick F; Zeggini, Eleftheria; Breen, Gerome; Bulik, Cynthia M

2017-09-01

The authors conducted a genome-wide association study of anorexia nervosa and calculated genetic correlations with a series of psychiatric, educational, and metabolic phenotypes. Following uniform quality control and imputation procedures using the 1000 Genomes Project (phase 3) in 12 case-control cohorts comprising 3,495 anorexia nervosa cases and 10,982 controls, the authors performed standard association analysis followed by a meta-analysis across cohorts. Linkage disequilibrium score regression was used to calculate genome-wide common variant heritability (single-nucleotide polymorphism [SNP]-based heritability [h 2 SNP ]), partitioned heritability, and genetic correlations (r g ) between anorexia nervosa and 159 other phenotypes. Results were obtained for 10,641,224 SNPs and insertion-deletion variants with minor allele frequencies >1% and imputation quality scores >0.6. The h 2 SNP of anorexia nervosa was 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability arises from common genetic variation. The authors identified one genome-wide significant locus on chromosome 12 (rs4622308) in a region harboring a previously reported type 1 diabetes and autoimmune disorder locus. Significant positive genetic correlations were observed between anorexia nervosa and schizophrenia, neuroticism, educational attainment, and high-density lipoprotein cholesterol, and significant negative genetic correlations were observed between anorexia nervosa and body mass index, insulin, glucose, and lipid phenotypes. Anorexia nervosa is a complex heritable phenotype for which this study has uncovered the first genome-wide significant locus. Anorexia nervosa also has large and significant genetic correlations with both psychiatric phenotypes and metabolic traits. The study results encourage a reconceptualization of this frequently lethal disorder as one with both psychiatric and metabolic etiology.

Puzzling sequences: studying microbial genomes from 'Ötzi'

International Nuclear Information System (INIS)

Rattei, T.

2012-01-01

Ancient remains, and mummies in particular, are of central value for archaeological research. The Tyrolean iceman “Ötzi” was conserved in a glacier of the Ötztal Alps about 5000 years ago. Aside from morphological and phenotypical classification, the determination of DNA sequences and the subsequent genome analyses have been first applied to mitochondrial DNA and then been extended to genomic DNA. Typically also ancient microbial DNA is sequenced. These sequences allow the identification of pathogens as well as studying the evolution of microorganisms. The talk will explain the metagenomic aspects of the “Ötzi” genome project and discuss the first results. (author)

Genome-wide recombination dynamics are associated with phenotypic variation in maize.

Science.gov (United States)

Pan, Qingchun; Li, Lin; Yang, Xiaohong; Tong, Hao; Xu, Shutu; Li, Zhigang; Li, Weiya; Muehlbauer, Gary J; Li, Jiansheng; Yan, Jianbing

2016-05-01

Meiotic recombination is a major driver of genetic diversity, species evolution, and agricultural improvement. Thus, an understanding of the genetic recombination landscape across the maize (Zea mays) genome will provide insight and tools for further study of maize evolution and improvement. Here, we used c. 50 000 single nucleotide polymorphisms to precisely map recombination events in 12 artificial maize segregating populations. We observed substantial variation in the recombination frequency and distribution along the ten maize chromosomes among the 12 populations and identified 143 recombination hot regions. Recombination breakpoints were partitioned into intragenic and intergenic events. Interestingly, an increase in the number of genes containing recombination events was accompanied by a decrease in the number of recombination events per gene. This kept the overall number of intragenic recombination events nearly invariable in a given population, suggesting that the recombination variation observed among populations was largely attributed to intergenic recombination. However, significant associations between intragenic recombination events and variation in gene expression and agronomic traits were observed, suggesting potential roles for intragenic recombination in plant phenotypic diversity. Our results provide a comprehensive view of the maize recombination landscape, and show an association between recombination, gene expression and phenotypic variation, which may enhance crop genetic improvement. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Genomic Selection Using Extreme Phenotypes and Pre-Selection of SNPs in Large Yellow Croaker (Larimichthys crocea).

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Dong, Linsong; Xiao, Shijun; Chen, Junwei; Wan, Liang; Wang, Zhiyong

2016-10-01

Genomic selection (GS) is an effective method to improve predictive accuracies of genetic values. However, high cost in genotyping will limit the application of this technology in some species. Therefore, it is necessary to find some methods to reduce the genotyping costs in genomic selection. Large yellow croaker is one of the most commercially important marine fish species in southeast China and Eastern Asia. In this study, genotyping-by-sequencing was used to construct the libraries for the NGS sequencing and find 29,748 SNPs in the genome. Two traits, eviscerated weight (EW) and the ratio between eviscerated weight and whole body weight (REW), were chosen to study. Two strategies to reduce the costs were proposed as follows: selecting extreme phenotypes (EP) for genotyping in reference population or pre-selecting SNPs to construct low-density marker panels in candidates. Three methods of pre-selection of SNPs, i.e., pre-selecting SNPs by absolute effects (SE), by single marker analysis (SMA), and by fixed intervals of sequence number (EL), were studied. The results showed that using EP was a feasible method to save the genotyping costs in reference population. Heritability did not seem to have obvious influences on the predictive abilities estimated by EP. Using SMA was the most feasible method to save the genotyping costs in candidates. In addition, the combination of EP and SMA in genomic selection also showed good results, especially for trait of REW. We also described how to apply the new methods in genomic selection and compared the genotyping costs before and after using the new methods. Our study may not only offer a reference for aquatic genomic breeding but also offer a reference for genomic prediction in other species including livestock and plants, etc.

Evolution of molecular phenotypes under stabilizing selection

International Nuclear Information System (INIS)

Nourmohammad, Armita; Schiffels, Stephan; Lässig, Michael

2013-01-01

Molecular phenotypes are important links between genomic information and organismic functions, fitness, and evolution. Complex phenotypes, which are also called quantitative traits, often depend on multiple genomic loci. Their evolution builds on genome evolution in a complicated way, which involves selection, genetic drift, mutations and recombination. Here we develop a coarse-grained evolutionary statistics for phenotypes, which decouples from details of the underlying genotypes. We derive approximate evolution equations for the distribution of phenotype values within and across populations. This dynamics covers evolutionary processes at high and low recombination rates, that is, it applies to sexual and asexual populations. In a fitness landscape with a single optimal phenotype value, the phenotypic diversity within populations and the divergence between populations reach evolutionary equilibria, which describe stabilizing selection. We compute the equilibrium distributions of both quantities analytically and we show that the ratio of mean divergence and diversity depends on the strength of selection in a universal way: it is largely independent of the phenotype’s genomic encoding and of the recombination rate. This establishes a new method for the inference of selection on molecular phenotypes beyond the genome level. We discuss the implications of our findings for the predictability of evolutionary processes. (paper)

Genome-wide association mapping including phenotypes from relatives without genotypes in a single-step (ssGWAS for 6-week body weight in broiler chickens

Directory of Open Access Journals (Sweden)

Huiyu eWang

2014-05-01

Full Text Available The purpose of this study was to compare results obtained from various methodologies for genome-wide association studies, when applied to real data, in terms of number and commonality of regions identified and their genetic variance explained, computational speed, and possible pitfalls in interpretations of results. Methodologies include: two iteratively reweighted single-step genomic BLUP procedures (ssGWAS1 and ssGWAS2, a single-marker model (CGWAS, and BayesB. The ssGWAS methods utilize genomic breeding values (GEBVs based on combined pedigree, genomic and phenotypic information, while CGWAS and BayesB only utilize phenotypes from genotyped animals or pseudo-phenotypes. In this study, ssGWAS was performed by converting GEBVs to SNP marker effects. Unequal variances for markers were incorporated for calculating weights into a new genomic relationship matrix. SNP weights were refined iteratively. The data was body weight at 6 weeks on 274,776 broiler chickens, of which 4553 were genotyped using a 60k SNP chip. Comparison of genomic regions was based on genetic variances explained by local SNP regions (20 SNPs. After 3 iterations, the noise was greatly reduced of ssGWAS1 and results are similar to that of CGWAS, with 4 out of the top 10 regions in common. In contrast, for BayesB, the plot was dominated by a single region explaining 23.1% of the genetic variance. This same region was found by ssGWAS1 with the same rank, but the amount of genetic variation attributed to the region was only 3%. These finding emphasize the need for caution when comparing and interpreting results from various methods, and highlight that detected associations, and strength of association, strongly depends on methodologies and details of implementations. BayesB appears to overly shrink regions to zero, while overestimating the amount of genetic variation attributed to the remaining SNP effects. The real world is most likely a compromise between methods and remains to

Genome-wide association study identifies 74 loci associated with educational attainment

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Okbay, Aysu; Beauchamp, Jonathan P.; Fontana, Mark A.; 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, Börge; Schraut, Katharina E.; Shi, Jianxin; Smith, Albert V.; Poot, Raymond A.; 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; Bønnelykke, 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; Evans68, David M.; Faul, Jessica D.; Feitosa, Mary F.; Forstner, Andreas J.; Gandin, Ilaria; Gunnarsson, Bjarni; Halldórsson, 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.; Kähönen, Mika; Kanoni, Stavroula; Keltigangas-Järvinen, Liisa; Kiemeney, Lambertus A.L.M.; Kolcic, Ivana; Koskinen, Seppo; Kraja, Aldi T.; Kroh, Martin; Kutalik, Zoltan; Latvala, Antti; Launer, Lenore J.; Lebreton, Maël P.; Levinson, Douglas F.; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C.M.; Loukola, Anu; Madden, Pamela A.; Mägi, Reedik; Mäki-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.; Räikkönen, 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.; Völker, Uwe; Völzke, Henry; Vonk, Judith M.; Vozzi, Diego; 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-Jörgen; Gratten, Jacob; Groenen, Patrick J.F.; Gudnason, Vilmundur; van der Harst, Pim; Hayward, Caroline; Hinds, David A.; Hoffmann, Wolfgang; Hyppönen, Elina; Iacono, William G.; Jacobsson, Bo; Järvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L.R.; Lehtimäki, 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; Sørensen, Thorkild I.A.; Spector, Tim D.; Stefansson, Kari; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tiemeier, Henning; Tung, Joyce Y.; Uitterlinden, André 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, Tõnu; Koellinger, Philipp D.; Cesarini, David; Benjamin, Daniel J.

2016-01-01

Summary Educational attainment (EA) is strongly influenced by social and other environmental factors, but genetic factors are also estimated to account for at least 20% of the variation across individuals1. We report the results of a genome-wide association study (GWAS) for EA that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication in an independent sample of 111,349 individuals from the UK Biobank. We now identify 74 genome-wide significant loci associated with number of years of schooling completed. Single-nucleotide polymorphisms (SNPs) associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioral phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because EA is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric disease. PMID:27225129

Polymicrogyria-associated epilepsy: a multi-center phenotypic study from the Epilepsy Phenome/Genome Project

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Shain, Catherine; Ramgopal, Sriram; Fallil, Zianka; Parulkar, Isha; Alongi, Richard; Knowlton, Robert; Poduri, Annapurna

2013-01-01

Purpose Polymicrogyria (PMG) is an epileptogenic malformation of cortical development. We describe the clinical epilepsy and imaging features of a large cohort with PMG-related epilepsy. Methods Participants were recruited through the Epilepsy Phenome/Genome Project, a multi-center collaborative effort to collect detailed phenotypic data on individuals with epilepsy. We reviewed phenotypic data from participants with epilepsy and PMG. Key Findings We identified 87 participants, 43 female and 44 male, with PMG and epilepsy. Median age of seizure onset was 3 years (range <1 month-37 years). Most presented with focal epilepsy (87.4%), some in combination with seizures generalized from onset (23.0%). Focal seizures with dyscognitive features were most common (54.3%). Of those presenting with generalized seizure types, infantile spasms were most prevalent (45.2%). The most common topographic pattern was perisylvian PMG (77.0%), of which the majority was bilateral (56.7%). Generalized PMG presented with an earlier age of seizure onset (median age of 8 months) and an increased prevalence of developmental delay prior to seizure onset (57.1%). Of the focal, unilateral and asymmetric bilateral groups where PMG was more involved in one hemisphere, the majority (71.4%) of participants had seizures that lateralized to the same hemisphere as the PMG or the hemisphere with greater involvement. Significance Participants with PMG had both focal and generalized onset of seizures. Our data confirm the involvement of known topographic patterns of PMG and suggest that more extensive distributions of PMG present with an earlier age of seizure onset and increased prevalence of developmental delay prior to seizure onset. PMID:23750890

Genome-wide association study of multiple congenital heart disease phenotypes identifies a susceptibility locus for atrial septal defect at chromosome 4p16

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Cordell, Heather J.; Bentham, Jamie; Topf, Ana; Zelenika, Diana; Heath, Simon; Mamasoula, Chrysovalanto; Cosgrove, Catherine; Blue, Gillian; Granados-Riveron, Javier; Setchfield, Kerry; Thornborough, Chris; Breckpot, Jeroen; Soemedi, Rachel; Martin, Ruairidh; Rahman, Thahira J.; Hall, Darroch; van Engelen, Klaartje; Moorman, Antoon F.M.; Zwinderman, Aelko H; Barnett, Phil; Koopmann, Tamara T.; Adriaens, Michiel E.; Varro, Andras; George, Alfred L.; dos Remedios, Christobal; Bishopric, Nanette H.; Bezzina, Connie R.; O’Sullivan, John; Gewillig, Marc; Bu’Lock, Frances A.; Winlaw, David; Bhattacharya, Shoumo; Devriendt, Koen; Brook, J. David; Mulder, Barbara J.M.; Mital, Seema; Postma, Alex V.; Lathrop, G. Mark; Farrall, Martin; Goodship, Judith A.; Keavney, Bernard D.

2013-01-01

We carried out a genome-wide association study (GWAS) of congenital heart disease (CHD). Our discovery cohort comprised 1,995 CHD cases and 5,159 controls, and included patients from each of the three major clinical CHD categories (septal, obstructive and cyanotic defects). When all CHD phenotypes were considered together, no regions achieved genome-wide significant association. However, a region on chromosome 4p16, adjacent to the MSX1 and STX18 genes, was associated (P=9.5×10−7) with the risk of ostium secundum atrial septal defect (ASD) in the discovery cohort (N=340 cases), and this was replicated in a further 417 ASD cases and 2520 controls (replication P=5.0×10−5; OR in replication cohort 1.40 [95% CI 1.19-1.65]; combined P=2.6×10−10). Genotype accounted for ~9% of the population attributable risk of ASD. PMID:23708191

Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa

NARCIS (Netherlands)

Duncan, Laramie; Yilmaz, Zeynep; Gaspar, Helena; Walters, Raymond K.; Goldstein, Jackie; Anttila, Verneri; Bulik-Sullivan, Brendan; Ripke, Stephan; Thornton, Laura M.; Hinney, Anke; Daly, Mark J.; Sullivan, Patrick F; Zeggini, Eleftheria; Breen, Gerome; Bulik, Cynthia M.; Adan, RAH

2017-01-01

Objective: The authors conducted a genome-wide association study of anorexia nervosa and calculated genetic correlations with a series of psychiatric, educational, and metabolic phenotypes. Method: Following uniformquality control and imputation procedures using the 1000 Genomes Project (phase 3) in

Significant locus and metabolic genetic correlations revealed in genome-wide association study of anorexia nervosa

NARCIS (Netherlands)

Duncan, Laramie; Yilmaz, Zeynep; Gaspar, Helena; Walters, Raymond; Goldstein, Jackie; Anttila, Verneri; Bulik-Sullivan, Brendan; Ripke, Stephan; Thornton, Laura; Hinney, Anke; Daly, Mark; Sullivan, Patrick F; Zeggini, Eleftheria; Breen, Gerome; Bulik, Cynthia M; Kas, Martinus J.H.

2017-01-01

OBJECTIVE: The authors conducted a genome-wide association study of anorexia nervosa and calculated genetic correlations with a series of psychiatric, educational, and metabolic phenotypes. METHOD: Following uniform quality control and imputation procedures using the 1000 Genomes Project (phase 3)

Genomic and Phenomic Study of Mammary Pathogenic Escherichia coli

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Blum, Shlomo E.; Heller, Elimelech D.; Sela, Shlomo; Elad, Daniel; Edery, Nir; Leitner, Gabriel

2015-01-01

Escherichia coli is a major etiological agent of intra-mammary infections (IMI) in cows, leading to acute mastitis and causing great economic losses in dairy production worldwide. Particular strains cause persistent IMI, leading to recurrent mastitis. Virulence factors of mammary pathogenic E. coli (MPEC) involved pathogenesis of mastitis as well as those differentiating strains causing acute or persistent mastitis are largely unknown. This study aimed to identify virulence markers in MPEC through whole genome and phenome comparative analysis. MPEC strains causing acute (VL2874 and P4) or persistent (VL2732) mastitis were compared to an environmental strain (K71) and to the genomes of strains representing different E. coli pathotypes. Intra-mammary challenge in mice confirmed experimentally that the strains studied here have different pathogenic potential, and that the environmental strain K71 is non-pathogenic in the mammary gland. Analysis of whole genome sequences and predicted proteomes revealed high similarity among MPEC, whereas MPEC significantly differed from the non-mammary pathogenic strain K71, and from E. coli genomes from other pathotypes. Functional features identified in MPEC genomes and lacking in the non-mammary pathogenic strain were associated with synthesis of lipopolysaccharide and other membrane antigens, ferric-dicitrate iron acquisition and sugars metabolism. Features associated with cytotoxicity or intra-cellular survival were found specifically in the genomes of strains from severe and acute (VL2874) or persistent (VL2732) mastitis, respectively. MPEC genomes were relatively similar to strain K-12, which was subsequently shown here to be possibly pathogenic in the mammary gland. Phenome analysis showed that the persistent MPEC was the most versatile in terms of nutrients metabolized and acute MPEC the least. Among phenotypes unique to MPEC compared to the non-mammary pathogenic strain were uric acid and D-serine metabolism. This study

Inference of the ancestral vertebrate phenotype through vestiges of the whole-genome duplications.

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Onimaru, Koh; Kuraku, Shigehiro

2018-03-16

Inferring the phenotype of the last common ancestor of living vertebrates is a challenging problem because of several unresolvable factors. They include the lack of reliable out-groups of living vertebrates, poor information about less fossilizable organs and specialized traits of phylogenetically important species, such as lampreys and hagfishes (e.g. secondary loss of vertebrae in adult hagfishes). These factors undermine the reliability of ancestral reconstruction by traditional character mapping approaches based on maximum parsimony. In this article, we formulate an approach to hypothesizing ancestral vertebrate phenotypes using information from the phylogenetic and functional properties of genes duplicated by genome expansions in early vertebrate evolution. We named the conjecture as 'chronological reconstruction of ohnolog functions (CHROF)'. This CHROF conjecture raises the possibility that the last common ancestor of living vertebrates may have had more complex traits than currently thought.

Genome-wide association study identifies chromosome 10q24.32 variants associated with arsenic metabolism and toxicity phenotypes in Bangladesh.

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Brandon L Pierce

Full Text Available Arsenic contamination of drinking water is a major public health issue in many countries, increasing risk for a wide array of diseases, including cancer. There is inter-individual variation in arsenic metabolism efficiency and susceptibility to arsenic toxicity; however, the basis of this variation is not well understood. Here, we have performed the first genome-wide association study (GWAS of arsenic-related metabolism and toxicity phenotypes to improve our understanding of the mechanisms by which arsenic affects health. Using data on urinary arsenic metabolite concentrations and approximately 300,000 genome-wide single nucleotide polymorphisms (SNPs for 1,313 arsenic-exposed Bangladeshi individuals, we identified genome-wide significant association signals (P<5×10(-8 for percentages of both monomethylarsonic acid (MMA and dimethylarsinic acid (DMA near the AS3MT gene (arsenite methyltransferase; 10q24.32, with five genetic variants showing independent associations. In a follow-up analysis of 1,085 individuals with arsenic-induced premalignant skin lesions (the classical sign of arsenic toxicity and 1,794 controls, we show that one of these five variants (rs9527 is also associated with skin lesion risk (P = 0.0005. Using a subset of individuals with prospectively measured arsenic (n = 769, we show that rs9527 interacts with arsenic to influence incident skin lesion risk (P = 0.01. Expression quantitative trait locus (eQTL analyses of genome-wide expression data from 950 individual's lymphocyte RNA suggest that several of our lead SNPs represent cis-eQTLs for AS3MT (P = 10(-12 and neighboring gene C10orf32 (P = 10(-44, which are involved in C10orf32-AS3MT read-through transcription. This is the largest and most comprehensive genomic investigation of arsenic metabolism and toxicity to date, the only GWAS of any arsenic-related trait, and the first study to implicate 10q24.32 variants in both arsenic metabolism and arsenical

Identification of QTL for UV-protective eye area pigmentation in cattle by progeny phenotyping and genome-wide association analysis.

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Hubert Pausch

Full Text Available Pigmentation patterns allow for the differentiation of cattle breeds. A dominantly inherited white head is characteristic for animals of the Fleckvieh (FV breed. However, a minority of the FV animals exhibits peculiar pigmentation surrounding the eyes (ambilateral circumocular pigmentation, ACOP. In areas where animals are exposed to increased solar ultraviolet radiation, ACOP is associated with a reduced susceptibility to bovine ocular squamous cell carcinoma (BOSCC, eye cancer. Eye cancer is the most prevalent malignant tumour affecting cattle. Selection for animals with ACOP rapidly reduces the incidence of BOSCC. To identify quantitative trait loci (QTL underlying ACOP, we performed a genome-wide association study using 658,385 single nucleotide polymorphisms (SNPs. The study population consisted of 3579 bulls of the FV breed with a total of 320,186 progeny with phenotypes for ACOP. The proportion of progeny with ACOP was used as a quantitative trait with high heritability (h(2 = 0.79. A variance component based approach to account for population stratification uncovered twelve QTL regions on seven chromosomes. The identified QTL point to MCM6, PAX3, ERBB3, KITLG, LEF1, DKK2, KIT, CRIM1, ATRN, GSDMC, MITF and NBEAL2 as underlying genes for eye area pigmentation in cattle. The twelve QTL regions explain 44.96% of the phenotypic variance of the proportion of daughters with ACOP. The chromosomes harbouring significantly associated SNPs account for 54.13% of the phenotypic variance, while another 19.51% of the phenotypic variance is attributable to chromosomes without identified QTL. Thus, the missing heritability amounts to 7% only. Our results support a polygenic inheritance pattern of ACOP in cattle and provide the basis for efficient genomic selection of animals that are less susceptible to serious eye diseases.

Comparing Mycobacterium tuberculosis genomes using genome topology networks.

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Jiang, Jianping; Gu, Jianlei; Zhang, Liang; Zhang, Chenyi; Deng, Xiao; Dou, Tonghai; Zhao, Guoping; Zhou, Yan

2015-02-14

Over the last decade, emerging research methods, such as comparative genomic analysis and phylogenetic study, have yielded new insights into genotypes and phenotypes of closely related bacterial strains. Several findings have revealed that genomic structural variations (SVs), including gene gain/loss, gene duplication and genome rearrangement, can lead to different phenotypes among strains, and an investigation of genes affected by SVs may extend our knowledge of the relationships between SVs and phenotypes in microbes, especially in pathogenic bacteria. In this work, we introduce a 'Genome Topology Network' (GTN) method based on gene homology and gene locations to analyze genomic SVs and perform phylogenetic analysis. Furthermore, the concept of 'unfixed ortholog' has been proposed, whose members are affected by SVs in genome topology among close species. To improve the precision of 'unfixed ortholog' recognition, a strategy to detect annotation differences and complete gene annotation was applied. To assess the GTN method, a set of thirteen complete M. tuberculosis genomes was analyzed as a case study. GTNs with two different gene homology-assigning methods were built, the Clusters of Orthologous Groups (COG) method and the orthoMCL clustering method, and two phylogenetic trees were constructed accordingly, which may provide additional insights into whole genome-based phylogenetic analysis. We obtained 24 unfixable COG groups, of which most members were related to immunogenicity and drug resistance, such as PPE-repeat proteins (COG5651) and transcriptional regulator TetR gene family members (COG1309). The GTN method has been implemented in PERL and released on our website. The tool can be downloaded from http://homepage.fudan.edu.cn/zhouyan/gtn/ , and allows re-annotating the 'lost' genes among closely related genomes, analyzing genes affected by SVs, and performing phylogenetic analysis. With this tool, many immunogenic-related and drug resistance-related genes

Optimizing the creation of base populations for aquaculture breeding programs using phenotypic and genomic data and its consequences on genetic progress.

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Fernández, Jesús; Toro, Miguel Á; Sonesson, Anna K; Villanueva, Beatriz

2014-01-01

The success of an aquaculture breeding program critically depends on the way in which the base population of breeders is constructed since all the genetic variability for the traits included originally in the breeding goal as well as those to be included in the future is contained in the initial founders. Traditionally, base populations were created from a number of wild strains by sampling equal numbers from each strain. However, for some aquaculture species improved strains are already available and, therefore, mean phenotypic values for economically important traits can be used as a criterion to optimize the sampling when creating base populations. Also, the increasing availability of genome-wide genotype information in aquaculture species could help to refine the estimation of relationships within and between candidate strains and, thus, to optimize the percentage of individuals to be sampled from each strain. This study explores the advantages of using phenotypic and genome-wide information when constructing base populations for aquaculture breeding programs in terms of initial and subsequent trait performance and genetic diversity level. Results show that a compromise solution between diversity and performance can be found when creating base populations. Up to 6% higher levels of phenotypic performance can be achieved at the same level of global diversity in the base population by optimizing the selection of breeders instead of sampling equal numbers from each strain. The higher performance observed in the base population persisted during 10 generations of phenotypic selection applied in the subsequent breeding program.

Genomic and phenotypic characterization of myxoma virus from Great Britain reveals multiple evolutionary pathways distinct from those in Australia.

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Peter J Kerr

2017-03-01

Full Text Available The co-evolution of myxoma virus (MYXV and the European rabbit occurred independently in Australia and Europe from different progenitor viruses. Although this is the canonical study of the evolution of virulence, whether the genomic and phenotypic outcomes of MYXV evolution in Europe mirror those observed in Australia is unknown. We addressed this question using viruses isolated in the United Kingdom early in the MYXV epizootic (1954-1955 and between 2008-2013. The later UK viruses fell into three distinct lineages indicative of a long period of separation and independent evolution. Although rates of evolutionary change were almost identical to those previously described for MYXV in Australia and strongly clock-like, genome evolution in the UK and Australia showed little convergence. The phenotypes of eight UK viruses from three lineages were characterized in laboratory rabbits and compared to the progenitor (release Lausanne strain. Inferred virulence ranged from highly virulent (grade 1 to highly attenuated (grade 5. Two broad disease types were seen: cutaneous nodular myxomatosis characterized by multiple raised secondary cutaneous lesions, or an amyxomatous phenotype with few or no secondary lesions. A novel clinical outcome was acute death with pulmonary oedema and haemorrhage, often associated with bacteria in many tissues but an absence of inflammatory cells. Notably, reading frame disruptions in genes defined as essential for virulence in the progenitor Lausanne strain were compatible with the acquisition of high virulence. Combined, these data support a model of ongoing host-pathogen co-evolution in which multiple genetic pathways can produce successful outcomes in the field that involve both different virulence grades and disease phenotypes, with alterations in tissue tropism and disease mechanisms.

Genomic and phenotypic characterization of myxoma virus from Great Britain reveals multiple evolutionary pathways distinct from those in Australia.

Science.gov (United States)

Kerr, Peter J; Cattadori, Isabella M; Rogers, Matthew B; Fitch, Adam; Geber, Adam; Liu, June; Sim, Derek G; Boag, Brian; Eden, John-Sebastian; Ghedin, Elodie; Read, Andrew F; Holmes, Edward C

2017-03-01

The co-evolution of myxoma virus (MYXV) and the European rabbit occurred independently in Australia and Europe from different progenitor viruses. Although this is the canonical study of the evolution of virulence, whether the genomic and phenotypic outcomes of MYXV evolution in Europe mirror those observed in Australia is unknown. We addressed this question using viruses isolated in the United Kingdom early in the MYXV epizootic (1954-1955) and between 2008-2013. The later UK viruses fell into three distinct lineages indicative of a long period of separation and independent evolution. Although rates of evolutionary change were almost identical to those previously described for MYXV in Australia and strongly clock-like, genome evolution in the UK and Australia showed little convergence. The phenotypes of eight UK viruses from three lineages were characterized in laboratory rabbits and compared to the progenitor (release) Lausanne strain. Inferred virulence ranged from highly virulent (grade 1) to highly attenuated (grade 5). Two broad disease types were seen: cutaneous nodular myxomatosis characterized by multiple raised secondary cutaneous lesions, or an amyxomatous phenotype with few or no secondary lesions. A novel clinical outcome was acute death with pulmonary oedema and haemorrhage, often associated with bacteria in many tissues but an absence of inflammatory cells. Notably, reading frame disruptions in genes defined as essential for virulence in the progenitor Lausanne strain were compatible with the acquisition of high virulence. Combined, these data support a model of ongoing host-pathogen co-evolution in which multiple genetic pathways can produce successful outcomes in the field that involve both different virulence grades and disease phenotypes, with alterations in tissue tropism and disease mechanisms.

Genomic and phenotypic characterization of myxoma virus from Great Britain reveals multiple evolutionary pathways distinct from those in Australia

Science.gov (United States)

Kerr, Peter J.; Cattadori, Isabella M.; Fitch, Adam; Geber, Adam; Liu, June; Sim, Derek G.; Boag, Brian; Ghedin, Elodie

2017-01-01

The co-evolution of myxoma virus (MYXV) and the European rabbit occurred independently in Australia and Europe from different progenitor viruses. Although this is the canonical study of the evolution of virulence, whether the genomic and phenotypic outcomes of MYXV evolution in Europe mirror those observed in Australia is unknown. We addressed this question using viruses isolated in the United Kingdom early in the MYXV epizootic (1954–1955) and between 2008–2013. The later UK viruses fell into three distinct lineages indicative of a long period of separation and independent evolution. Although rates of evolutionary change were almost identical to those previously described for MYXV in Australia and strongly clock-like, genome evolution in the UK and Australia showed little convergence. The phenotypes of eight UK viruses from three lineages were characterized in laboratory rabbits and compared to the progenitor (release) Lausanne strain. Inferred virulence ranged from highly virulent (grade 1) to highly attenuated (grade 5). Two broad disease types were seen: cutaneous nodular myxomatosis characterized by multiple raised secondary cutaneous lesions, or an amyxomatous phenotype with few or no secondary lesions. A novel clinical outcome was acute death with pulmonary oedema and haemorrhage, often associated with bacteria in many tissues but an absence of inflammatory cells. Notably, reading frame disruptions in genes defined as essential for virulence in the progenitor Lausanne strain were compatible with the acquisition of high virulence. Combined, these data support a model of ongoing host-pathogen co-evolution in which multiple genetic pathways can produce successful outcomes in the field that involve both different virulence grades and disease phenotypes, with alterations in tissue tropism and disease mechanisms. PMID:28253375

A Genome-Wide Association Study on the Seedless Phenotype in Banana (Musa spp. Reveals the Potential of a Selected Panel to Detect Candidate Genes in a Vegetatively Propagated Crop.

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Julie Sardos

Full Text Available Banana (Musa sp. is a vegetatively propagated, low fertility, potentially hybrid and polyploid crop. These qualities make the breeding and targeted genetic improvement of this crop a difficult and long process. The Genome-Wide Association Study (GWAS approach is becoming widely used in crop plants and has proven efficient to detecting candidate genes for traits of interest, especially in cereals. GWAS has not been applied yet to a vegetatively propagated crop. However, successful GWAS in banana would considerably help unravel the genomic basis of traits of interest and therefore speed up this crop improvement. We present here a dedicated panel of 105 accessions of banana, freely available upon request, and their corresponding GBS data. A set of 5,544 highly reliable markers revealed high levels of admixture in most accessions, except for a subset of 33 individuals from Papua. A GWAS on the seedless phenotype was then successfully applied to the panel. By applying the Mixed Linear Model corrected for both kinship and structure as implemented in TASSEL, we detected 13 candidate genomic regions in which we found a number of genes potentially linked with the seedless phenotype (i.e. parthenocarpy combined with female sterility. An additional GWAS performed on the unstructured Papuan subset composed of 33 accessions confirmed six of these regions as candidate. Out of both sets of analyses, one strong candidate gene for female sterility, a putative orthologous gene to Histidine Kinase CKI1, was identified. The results presented here confirmed the feasibility and potential of GWAS when applied to small sets of banana accessions, at least for traits underpinned by a few loci. As phenotyping in banana is extremely space and time-consuming, this latest finding is of particular importance in the context of banana improvement.

A Genome-Wide Association Study on the Seedless Phenotype in Banana (Musa spp.) Reveals the Potential of a Selected Panel to Detect Candidate Genes in a Vegetatively Propagated Crop.

Science.gov (United States)

Sardos, Julie; Rouard, Mathieu; Hueber, Yann; Cenci, Alberto; Hyma, Katie E; van den Houwe, Ines; Hribova, Eva; Courtois, Brigitte; Roux, Nicolas

2016-01-01

Banana (Musa sp.) is a vegetatively propagated, low fertility, potentially hybrid and polyploid crop. These qualities make the breeding and targeted genetic improvement of this crop a difficult and long process. The Genome-Wide Association Study (GWAS) approach is becoming widely used in crop plants and has proven efficient to detecting candidate genes for traits of interest, especially in cereals. GWAS has not been applied yet to a vegetatively propagated crop. However, successful GWAS in banana would considerably help unravel the genomic basis of traits of interest and therefore speed up this crop improvement. We present here a dedicated panel of 105 accessions of banana, freely available upon request, and their corresponding GBS data. A set of 5,544 highly reliable markers revealed high levels of admixture in most accessions, except for a subset of 33 individuals from Papua. A GWAS on the seedless phenotype was then successfully applied to the panel. By applying the Mixed Linear Model corrected for both kinship and structure as implemented in TASSEL, we detected 13 candidate genomic regions in which we found a number of genes potentially linked with the seedless phenotype (i.e. parthenocarpy combined with female sterility). An additional GWAS performed on the unstructured Papuan subset composed of 33 accessions confirmed six of these regions as candidate. Out of both sets of analyses, one strong candidate gene for female sterility, a putative orthologous gene to Histidine Kinase CKI1, was identified. The results presented here confirmed the feasibility and potential of GWAS when applied to small sets of banana accessions, at least for traits underpinned by a few loci. As phenotyping in banana is extremely space and time-consuming, this latest finding is of particular importance in the context of banana improvement.

Accumulated environmental risk determining age at schizophrenia onset: a deep phenotyping-based study.

Science.gov (United States)

Stepniak, Beata; Papiol, Sergi; Hammer, Christian; Ramin, Anna; Everts, Sarah; Hennig, Lena; Begemann, Martin; Ehrenreich, Hannelore

2014-11-01

Schizophrenia is caused by a combination of genetic and environmental factors, as first evidenced by twin studies. Extensive efforts have been made to identify the genetic roots of schizophrenia, including large genome-wide association studies, but these yielded very small effect sizes for individual markers. In this study, we aimed to assess the relative contribution of genome-wide association study-derived genetic versus environmental risk factors to crucial determinants of schizophrenia severity: disease onset, disease severity, and socioeconomic measures. In this parallel analysis, we studied 750 male patients from the Göttingen Research Association for Schizophrenia (GRAS) dataset (Germany) with schizophrenia for whom both genome-wide coverage of single-nucleotide polymorphisms and deep clinical phenotyping data were available. Specifically, we investigated the potential effect of schizophrenia risk alleles as identified in the most recent large genome-wide association study versus the effects of environmental hazards (ie, perinatal brain insults, cannabis use, neurotrauma, psychotrauma, urbanicity, and migration), alone and upon accumulation, on age at disease onset, age at prodrome, symptom expression, and socioeconomic parameters. In this study, we could show that frequent environmental factors become a major risk for early schizophrenia onset when accumulated (prodrome begins up to 9 years earlier; p=2·9×10(-10)). In particular, cannabis use-an avoidable environmental risk factor-is highly significantly associated with earlier age at prodrome (p=3·8×10(-20)). By contrast, polygenic genome-wide association study risk scores did not have any detectable effects on schizophrenia phenotypes. These findings should be translated to preventive measures to reduce environmental risk factors, since age at onset of schizophrenia is a crucial determinant of an affected individual's fate and the total socioeconomic cost of the illness. German Research Foundation

Genotyping using whole-genome sequencing is a realistic alternative to surveillance based on phenotypic antimicrobial susceptibility testing

DEFF Research Database (Denmark)

Zankari, Ea; Hasman, Henrik; Kaas, Rolf Sommer

2013-01-01

-genome sequencing (WGS) may soon be within reach even for routine surveillance and clinical diagnostics. The aim of this study was to evaluate WGS as a routine tool for surveillance of antimicrobial resistance compared with current phenotypic procedures. Methods: Antimicrobial susceptibility tests were performed...... to the categorizing of isolates as resistant and 2569 as susceptible. Seven cases of disagreement between tested and predicted susceptibility were observed, six of which were related to spectinomycin resistance in Escherichia coli. Correlation between MLST type and resistance profiles was only observed in Salmonella...

Efficient Breeding by Genomic Mating.

Science.gov (United States)

Akdemir, Deniz; Sánchez, Julio I

2016-01-01

Selection in breeding programs can be done by using phenotypes (phenotypic selection), pedigree relationship (breeding value selection) or molecular markers (marker assisted selection or genomic selection). All these methods are based on truncation selection, focusing on the best performance of parents before mating. In this article we proposed an approach to breeding, named genomic mating, which focuses on mating instead of truncation selection. Genomic mating uses information in a similar fashion to genomic selection but includes information on complementation of parents to be mated. Following the efficiency frontier surface, genomic mating uses concepts of estimated breeding values, risk (usefulness) and coefficient of ancestry to optimize mating between parents. We used a genetic algorithm to find solutions to this optimization problem and the results from our simulations comparing genomic selection, phenotypic selection and the mating approach indicate that current approach for breeding complex traits is more favorable than phenotypic and genomic selection. Genomic mating is similar to genomic selection in terms of estimating marker effects, but in genomic mating the genetic information and the estimated marker effects are used to decide which genotypes should be crossed to obtain the next breeding population.

Genome-wide DNA methylation alterations of Alternanthera philoxeroides in natural and manipulated habitats: implications for epigenetic regulation of rapid responses to environmental fluctuation and phenotypic variation.

Science.gov (United States)

Gao, Lexuan; Geng, Yupeng; Li, Bo; Chen, Jiakuan; Yang, Ji

2010-11-01

Alternanthera philoxeroides (alligator weed) is an invasive weed that can colonize both aquatic and terrestrial habitats. Individuals growing in different habitats exhibit extensive phenotypic variation but little genetic differentiation in its introduced range. The mechanisms underpinning the wide range of phenotypic variation and rapid adaptation to novel and changing environments remain uncharacterized. In this study, we examined the epigenetic variation and its correlation with phenotypic variation in plants exposed to natural and manipulated environmental variability. Genome-wide methylation profiling using methylation-sensitive amplified fragment length polymorphism (MSAP) revealed considerable DNA methylation polymorphisms within and between natural populations. Plants of different source populations not only underwent significant morphological changes in common garden environments, but also underwent a genome-wide epigenetic reprogramming in response to different treatments. Methylation alterations associated with response to different water availability were detected in 78.2% (169/216) of common garden induced polymorphic sites, demonstrating the environmental sensitivity and flexibility of the epigenetic regulatory system. These data provide evidence of the correlation between epigenetic reprogramming and the reversible phenotypic response of alligator weed to particular environmental factors. © 2010 Blackwell Publishing Ltd.

Genomic selection: genome-wide prediction in plant improvement.

Science.gov (United States)

Desta, Zeratsion Abera; Ortiz, Rodomiro

2014-09-01

Association analysis is used to measure relations between markers and quantitative trait loci (QTL). Their estimation ignores genes with small effects that trigger underpinning quantitative traits. By contrast, genome-wide selection estimates marker effects across the whole genome on the target population based on a prediction model developed in the training population (TP). Whole-genome prediction models estimate all marker effects in all loci and capture small QTL effects. Here, we review several genomic selection (GS) models with respect to both the prediction accuracy and genetic gain from selection. Phenotypic selection or marker-assisted breeding protocols can be replaced by selection, based on whole-genome predictions in which phenotyping updates the model to build up the prediction accuracy. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multiplexed precision genome editing with trackable genomic barcodes in yeast.

Science.gov (United States)

Roy, Kevin R; Smith, Justin D; Vonesch, Sibylle C; Lin, Gen; Tu, Chelsea Szu; Lederer, Alex R; Chu, Angela; Suresh, Sundari; Nguyen, Michelle; Horecka, Joe; Tripathi, Ashutosh; Burnett, Wallace T; Morgan, Maddison A; Schulz, Julia; Orsley, Kevin M; Wei, Wu; Aiyar, Raeka S; Davis, Ronald W; Bankaitis, Vytas A; Haber, James E; Salit, Marc L; St Onge, Robert P; Steinmetz, Lars M

2018-07-01

Our understanding of how genotype controls phenotype is limited by the scale at which we can precisely alter the genome and assess the phenotypic consequences of each perturbation. Here we describe a CRISPR-Cas9-based method for multiplexed accurate genome editing with short, trackable, integrated cellular barcodes (MAGESTIC) in Saccharomyces cerevisiae. MAGESTIC uses array-synthesized guide-donor oligos for plasmid-based high-throughput editing and features genomic barcode integration to prevent plasmid barcode loss and to enable robust phenotyping. We demonstrate that editing efficiency can be increased more than fivefold by recruiting donor DNA to the site of breaks using the LexA-Fkh1p fusion protein. We performed saturation editing of the essential gene SEC14 and identified amino acids critical for chemical inhibition of lipid signaling. We also constructed thousands of natural genetic variants, characterized guide mismatch tolerance at the genome scale, and ascertained that cryptic Pol III termination elements substantially reduce guide efficacy. MAGESTIC will be broadly useful to uncover the genetic basis of phenotypes in yeast.

Patient-controlled encrypted genomic data: an approach to advance clinical genomics

Directory of Open Access Journals (Sweden)

Trakadis Yannis J

2012-07-01

Full Text Available Abstract Background The revolution in DNA sequencing technologies over the past decade has made it feasible to sequence an individual’s whole genome at a relatively low cost. The potential value of the information generated by genomic technologies for medicine and society is enormous. However, in order for exome sequencing, and eventually whole genome sequencing, to be implemented clinically, a number of major challenges need to be overcome. For instance, obtaining meaningful informed-consent, managing incidental findings and the great volume of data generated (including multiple findings with uncertain clinical significance, re-interpreting the genomic data and providing additional counselling to patients as genetic knowledge evolves are issues that need to be addressed. It appears that medical genetics is shifting from the present “phenotype-first” medical model to a “data-first” model which leads to multiple complexities. Discussion This manuscript discusses the different challenges associated with integrating genomic technologies into clinical practice and describes a “phenotype-first” approach, namely, “Individualized Mutation-weighed Phenotype Search”, and its benefits. The proposed approach allows for a more efficient prioritization of the genes to be tested in a clinical lab based on both the patient’s phenotype and his/her entire genomic data. It simplifies “informed-consent” for clinical use of genomic technologies and helps to protect the patient’s autonomy and privacy. Overall, this approach could potentially render widespread use of genomic technologies, in the immediate future, practical, ethical and clinically useful. Summary The “Individualized Mutation-weighed Phenotype Search” approach allows for an incremental integration of genomic technologies into clinical practice. It ensures that we do not over-medicalize genomic data but, rather, continue our current medical model which is based on serving

Impact of phenotype definition on genome-wide association signals: empirical evaluation in human immunodeficiency virus type 1 infection

DEFF Research Database (Denmark)

Evangelou, Evangelos; Fellay, Jacques; Colombo, Sara

2011-01-01

infected with human immunodeficiency virus type 1 (HIV-1) to assess whether differences in type of population (622 seroconverters vs. 636 seroprevalent subjects) or the number of measurements available for defining the phenotype resulted in differences in the effect sizes of associations between single...... nucleotide polymorphisms and the phenotype, HIV-1 viral load at set point. The effect estimate for the top 100 single nucleotide polymorphisms was 0.092 (95% confidence interval: 0.074, 0.110) log(10) viral load (log(10) copies of HIV-1 per mL of blood) greater in seroconverters than in seroprevalent...... available, particularly among seroconverters and for variants that achieved genome-wide significance. Differences in phenotype definition and ascertainment may affect the estimated magnitude of genetic effects and should be considered in optimizing power for discovering new associations....

Discovering susceptibility genes for allergic rhinitis and allergy using a genome-wide association study strategy.

Science.gov (United States)

Li, Jingyun; Zhang, Yuan; Zhang, Luo

2015-02-01

Allergic rhinitis and allergy are complex conditions, in which both genetic and environmental factors contribute to the pathogenesis. Genome-wide association studies (GWASs) employing common single-nucleotide polymorphisms have accelerated the search for novel and interesting genes, and also confirmed the role of some previously described genes which may be involved in the cause of allergic rhinitis and allergy. The aim of this review is to provide an overview of the genetic basis of allergic rhinitis and the associated allergic phenotypes, with particular focus on GWASs. The last decade has been marked by the publication of more than 20 GWASs of allergic rhinitis and the associated allergic phenotypes. Allergic diseases and traits have been shown to share a large number of genetic susceptibility loci, of which IL33/IL1RL1, IL-13-RAD50 and C11orf30/LRRC32 appear to be important for more than two allergic phenotypes. GWASs have further reflected the genetic heterogeneity underlying allergic phenotypes. Large-scale genome-wide association strategies are underway to discover new susceptibility variants for allergic rhinitis and allergic phenotypes. Characterization of the underlying genetics provides us with an insight into the potential targets for future studies and the corresponding interventions.

Characterizing Protein Interactions Employing a Genome-Wide siRNA Cellular Phenotyping Screen

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Suratanee, Apichat; Schaefer, Martin H.; Betts, Matthew J.; Soons, Zita; Mannsperger, Heiko; Harder, Nathalie; Oswald, Marcus; Gipp, Markus; Ramminger, Ellen; Marcus, Guillermo; Männer, Reinhard; Rohr, Karl; Wanker, Erich; Russell, Robert B.; Andrade-Navarro, Miguel A.; Eils, Roland; König, Rainer

2014-01-01

Characterizing the activating and inhibiting effect of protein-protein interactions (PPI) is fundamental to gain insight into the complex signaling system of a human cell. A plethora of methods has been suggested to infer PPI from data on a large scale, but none of them is able to characterize the effect of this interaction. Here, we present a novel computational development that employs mitotic phenotypes of a genome-wide RNAi knockdown screen and enables identifying the activating and inhibiting effects of PPIs. Exemplarily, we applied our technique to a knockdown screen of HeLa cells cultivated at standard conditions. Using a machine learning approach, we obtained high accuracy (82% AUC of the receiver operating characteristics) by cross-validation using 6,870 known activating and inhibiting PPIs as gold standard. We predicted de novo unknown activating and inhibiting effects for 1,954 PPIs in HeLa cells covering the ten major signaling pathways of the Kyoto Encyclopedia of Genes and Genomes, and made these predictions publicly available in a database. We finally demonstrate that the predicted effects can be used to cluster knockdown genes of similar biological processes in coherent subgroups. The characterization of the activating or inhibiting effect of individual PPIs opens up new perspectives for the interpretation of large datasets of PPIs and thus considerably increases the value of PPIs as an integrated resource for studying the detailed function of signaling pathways of the cellular system of interest. PMID:25255318

OryzaGenome: Genome Diversity Database of Wild Oryza Species

KAUST Repository

Ohyanagi, Hajime

2015-11-18

The species in the genus Oryza, encompassing nine genome types and 23 species, are a rich genetic resource and may have applications in deeper genomic analyses aiming to understand the evolution of plant genomes. With the advancement of next-generation sequencing (NGS) technology, a flood of Oryza species reference genomes and genomic variation information has become available in recent years. This genomic information, combined with the comprehensive phenotypic information that we are accumulating in our Oryzabase, can serve as an excellent genotype-phenotype association resource for analyzing rice functional and structural evolution, and the associated diversity of the Oryza genus. Here we integrate our previous and future phenotypic/habitat information and newly determined genotype information into a united repository, named OryzaGenome, providing the variant information with hyperlinks to Oryzabase. The current version of OryzaGenome includes genotype information of 446 O. rufipogon accessions derived by imputation and of 17 accessions derived by imputation-free deep sequencing. Two variant viewers are implemented: SNP Viewer as a conventional genome browser interface and Variant Table as a textbased browser for precise inspection of each variant one by one. Portable VCF (variant call format) file or tabdelimited file download is also available. Following these SNP (single nucleotide polymorphism) data, reference pseudomolecules/ scaffolds/contigs and genome-wide variation information for almost all of the closely and distantly related wild Oryza species from the NIG Wild Rice Collection will be available in future releases. All of the resources can be accessed through http://viewer.shigen.info/oryzagenome/.

Phenotypic Data Collection and Sample Preparation for Genomics of Wood Formation and Cellulosic Biomass Traits in Sunflower: Ames, IA location.

Energy Technology Data Exchange (ETDEWEB)

Marek, Laura F.

2011-06-17

Three fields were planted in Ames in 2010, two association mapping fields, N3 and A, and a recombinant inbred line field, N13. Phenotype data and images were transferred to UGA to support genetic and genomic analyses of woody biomass-related traits.

High proportion of large genomic deletions and a genotype phenotype update in 80 unrelated families with juvenile polyposis syndrome

DEFF Research Database (Denmark)

Aretz, S; Stienen, D; Uhlhaas, S

2007-01-01

BACKGROUND: In patients with juvenile polyposis syndrome (JPS) the frequency of large genomic deletions in the SMAD4 and BMPR1A genes was unknown. METHODS: Mutation and phenotype analysis was used in 80 unrelated patients of whom 65 met the clinical criteria for JPS (typical JPS) and 15 were susp...

Rapid scoring of genes in microbial pan-genome-wide association studies with Scoary.

Science.gov (United States)

Brynildsrud, Ola; Bohlin, Jon; Scheffer, Lonneke; Eldholm, Vegard

2016-11-25

Genome-wide association studies (GWAS) have become indispensable in human medicine and genomics, but very few have been carried out on bacteria. Here we introduce Scoary, an ultra-fast, easy-to-use, and widely applicable software tool that scores the components of the pan-genome for associations to observed phenotypic traits while accounting for population stratification, with minimal assumptions about evolutionary processes. We call our approach pan-GWAS to distinguish it from traditional, single nucleotide polymorphism (SNP)-based GWAS. Scoary is implemented in Python and is available under an open source GPLv3 license at https://github.com/AdmiralenOla/Scoary .

Prediction of Phenotypic Antimicrobial Resistance Profiles From Whole Genome Sequences of Non-typhoidal Salmonella enterica.

Science.gov (United States)

Neuert, Saskia; Nair, Satheesh; Day, Martin R; Doumith, Michel; Ashton, Philip M; Mellor, Kate C; Jenkins, Claire; Hopkins, Katie L; Woodford, Neil; de Pinna, Elizabeth; Godbole, Gauri; Dallman, Timothy J

2018-01-01

Surveillance of antimicrobial resistance (AMR) in non-typhoidal Salmonella enterica (NTS), is essential for monitoring transmission of resistance from the food chain to humans, and for establishing effective treatment protocols. We evaluated the prediction of phenotypic resistance in NTS from genotypic profiles derived from whole genome sequencing (WGS). Genes and chromosomal mutations responsible for phenotypic resistance were sought in WGS data from 3,491 NTS isolates received by Public Health England's Gastrointestinal Bacteria Reference Unit between April 2014 and March 2015. Inferred genotypic AMR profiles were compared with phenotypic susceptibilities determined for fifteen antimicrobials using EUCAST guidelines. Discrepancies between phenotypic and genotypic profiles for one or more antimicrobials were detected for 76 isolates (2.18%) although only 88/52,365 (0.17%) isolate/antimicrobial combinations were discordant. Of the discrepant results, the largest number were associated with streptomycin (67.05%, n = 59). Pan-susceptibility was observed in 2,190 isolates (62.73%). Overall, resistance to tetracyclines was most common (26.27% of isolates, n = 917) followed by sulphonamides (23.72%, n = 828) and ampicillin (21.43%, n = 748). Multidrug resistance (MDR), i.e., resistance to three or more antimicrobial classes, was detected in 848 isolates (24.29%) with resistance to ampicillin, streptomycin, sulphonamides and tetracyclines being the most common MDR profile ( n = 231; 27.24%). For isolates with this profile, all but one were S . Typhimurium and 94.81% ( n = 219) had the resistance determinants bla TEM-1, strA-strB, sul2 and tet (A). Extended-spectrum β-lactamase genes were identified in 41 isolates (1.17%) and multiple mutations in chromosomal genes associated with ciprofloxacin resistance in 82 isolates (2.35%). This study showed that WGS is suitable as a rapid means of determining AMR patterns of NTS for public health surveillance.

Integrate genome-based assessment of safety for probiotic strains: Bacillus coagulans GBI-30, 6086 as a case study.

Science.gov (United States)

Salvetti, Elisa; Orrù, Luigi; Capozzi, Vittorio; Martina, Alessia; Lamontanara, Antonella; Keller, David; Cash, Howard; Felis, Giovanna E; Cattivelli, Luigi; Torriani, Sandra; Spano, Giuseppe

2016-05-01

Probiotics are microorganisms that confer beneficial effects on the host; nevertheless, before being allowed for human consumption, their safety must be verified with accurate protocols. In the genomic era, such procedures should take into account the genomic-based approaches. This study aims at assessing the safety traits of Bacillus coagulans GBI-30, 6086 integrating the most updated genomics-based procedures and conventional phenotypic assays. Special attention was paid to putative virulence factors (VF), antibiotic resistance (AR) genes and genes encoding enzymes responsible for harmful metabolites (i.e. biogenic amines, BAs). This probiotic strain was phenotypically resistant to streptomycin and kanamycin, although the genome analysis suggested that the AR-related genes were not easily transferrable to other bacteria, and no other genes with potential safety risks, such as those related to VF or BA production, were retrieved. Furthermore, no unstable elements that could potentially lead to genomic rearrangements were detected. Moreover, a workflow is proposed to allow the proper taxonomic identification of a microbial strain and the accurate evaluation of risk-related gene traits, combining whole genome sequencing analysis with updated bioinformatics tools and standard phenotypic assays. The workflow presented can be generalized as a guideline for the safety investigation of novel probiotic strains to help stakeholders (from scientists to manufacturers and consumers) to meet regulatory requirements and avoid misleading information.

Resolution of Disease Phenotypes Resulting from Multilocus Genomic Variation.

Science.gov (United States)

Posey, Jennifer E; Harel, Tamar; Liu, Pengfei; Rosenfeld, Jill A; James, Regis A; Coban Akdemir, Zeynep H; Walkiewicz, Magdalena; Bi, Weimin; Xiao, Rui; Ding, Yan; Xia, Fan; Beaudet, Arthur L; Muzny, Donna M; Gibbs, Richard A; Boerwinkle, Eric; Eng, Christine M; Sutton, V Reid; Shaw, Chad A; Plon, Sharon E; Yang, Yaping; Lupski, James R

2017-01-05

Whole-exome sequencing can provide insight into the relationship between observed clinical phenotypes and underlying genotypes. We conducted a retrospective analysis of data from a series of 7374 consecutive unrelated patients who had been referred to a clinical diagnostic laboratory for whole-exome sequencing; our goal was to determine the frequency and clinical characteristics of patients for whom more than one molecular diagnosis was reported. The phenotypic similarity between molecularly diagnosed pairs of diseases was calculated with the use of terms from the Human Phenotype Ontology. A molecular diagnosis was rendered for 2076 of 7374 patients (28.2%); among these patients, 101 (4.9%) had diagnoses that involved two or more disease loci. We also analyzed parental samples, when available, and found that de novo variants accounted for 67.8% (61 of 90) of pathogenic variants in autosomal dominant disease genes and 51.7% (15 of 29) of pathogenic variants in X-linked disease genes; both variants were de novo in 44.7% (17 of 38) of patients with two monoallelic variants. Causal copy-number variants were found in 12 patients (11.9%) with multiple diagnoses. Phenotypic similarity scores were significantly lower among patients in whom the phenotype resulted from two distinct mendelian disorders that affected different organ systems (50 patients) than among patients with disorders that had overlapping phenotypic features (30 patients) (median score, 0.21 vs. 0.36; P=1.77×10 -7 ). In our study, we found multiple molecular diagnoses in 4.9% of cases in which whole-exome sequencing was informative. Our results show that structured clinical ontologies can be used to determine the degree of overlap between two mendelian diseases in the same patient; the diseases can be distinct or overlapping. Distinct disease phenotypes affect different organ systems, whereas overlapping disease phenotypes are more likely to be caused by two genes encoding proteins that interact within

Whole genome sequencing reveals a novel deletion variant in the KIT gene in horses with white spotted coat colour phenotypes.

Science.gov (United States)

Dürig, N; Jude, R; Holl, H; Brooks, S A; Lafayette, C; Jagannathan, V; Leeb, T

2017-08-01

White spotting phenotypes in horses can range in severity from the common white markings up to completely white horses. EDNRB, KIT, MITF, PAX3 and TRPM1 represent known candidate genes for such phenotypes in horses. For the present study, we re-investigated a large horse family segregating a variable white spotting phenotype, for which conventional Sanger sequencing of the candidate genes' individual exons had failed to reveal the causative variant. We obtained whole genome sequence data from an affected horse and specifically searched for structural variants in the known candidate genes. This analysis revealed a heterozygous ~1.9-kb deletion spanning exons 10-13 of the KIT gene (chr3:77,740,239_77,742,136del1898insTATAT). In continuity with previously named equine KIT variants we propose to designate the newly identified deletion variant W22. We had access to 21 horses carrying the W22 allele. Four of them were compound heterozygous W20/W22 and had a completely white phenotype. Our data suggest that W22 represents a true null allele of the KIT gene, whereas the previously identified W20 leads to a partial loss of function. These findings will enable more precise genetic testing for depigmentation phenotypes in horses. © 2017 Stichting International Foundation for Animal Genetics.

Unsupervised Analysis of Array Comparative Genomic Hybridization Data from Early-Onset Colorectal Cancer Reveals Equivalence with Molecular Classification and Phenotypes

Directory of Open Access Journals (Sweden)

María Arriba

2017-01-01

Full Text Available AIM: To investigate whether chromosomal instability (CIN is associated with tumor phenotypes and/or with global genomic status based on MSI (microsatellite instability and CIMP (CpG island methylator phenotype in early-onset colorectal cancer (EOCRC. METHODS: Taking as a starting point our previous work in which tumors from 60 EOCRC cases (≤45 years at the time of diagnosis were analyzed by array comparative genomic hybridization (aCGH, in the present study we performed an unsupervised hierarchical clustering analysis of those aCGH data in order to unveil possible associations between the CIN profile and the clinical features of the tumors. In addition, we evaluated the MSI and the CIMP statuses of the samples with the aim of investigating a possible relationship between copy number alterations (CNAs and the MSI/CIMP condition in EOCRC. RESULTS: Based on the similarity of the CNAs detected, the unsupervised analysis stratified samples into two main clusters (A, B and four secondary clusters (A1, A2, B3, B4. The different subgroups showed a certain correspondence with the molecular classification of colorectal cancer (CRC, which enabled us to outline an algorithm to categorize tumors according to their CIMP status. Interestingly, each subcluster showed some distinctive clinicopathological features. But more interestingly, the CIN of each subcluster mainly affected particular chromosomes, allowing us to define chromosomal regions more specifically affected depending on the CIMP/MSI status of the samples. CONCLUSIONS: Our findings may provide a basis for a new form of classifying EOCRC according to the genomic status of the tumors.

Impact of QTL minor allele frequency on genomic evaluation using real genotype data and simulated phenotypes in Japanese Black cattle.

Science.gov (United States)

Uemoto, Yoshinobu; Sasaki, Shinji; Kojima, Takatoshi; Sugimoto, Yoshikazu; Watanabe, Toshio

2015-11-19

Genetic variance that is not captured by single nucleotide polymorphisms (SNPs) is due to imperfect linkage disequilibrium (LD) between SNPs and quantitative trait loci (QTLs), and the extent of LD between SNPs and QTLs depends on different minor allele frequencies (MAF) between them. To evaluate the impact of MAF of QTLs on genomic evaluation, we performed a simulation study using real cattle genotype data. In total, 1368 Japanese Black cattle and 592,034 SNPs (Illumina BovineHD BeadChip) were used. We simulated phenotypes using real genotypes under different scenarios, varying the MAF categories, QTL heritability, number of QTLs, and distribution of QTL effect. After generating true breeding values and phenotypes, QTL heritability was estimated and the prediction accuracy of genomic estimated breeding value (GEBV) was assessed under different SNP densities, prediction models, and population size by a reference-test validation design. The extent of LD between SNPs and QTLs in this population was higher in the QTLs with high MAF than in those with low MAF. The effect of MAF of QTLs depended on the genetic architecture, evaluation strategy, and population size in genomic evaluation. In genetic architecture, genomic evaluation was affected by the MAF of QTLs combined with the QTL heritability and the distribution of QTL effect. The number of QTL was not affected on genomic evaluation if the number of QTL was more than 50. In the evaluation strategy, we showed that different SNP densities and prediction models affect the heritability estimation and genomic prediction and that this depends on the MAF of QTLs. In addition, accurate QTL heritability and GEBV were obtained using denser SNP information and the prediction model accounted for the SNPs with low and high MAFs. In population size, a large sample size is needed to increase the accuracy of GEBV. The MAF of QTL had an impact on heritability estimation and prediction accuracy. Most genetic variance can be captured

Genomic and Transcriptomic Associations Identify a New Insecticide Resistance Phenotype for the Selective Sweep at the Cyp6g1 Locus of Drosophila melanogaster.

Science.gov (United States)

Battlay, Paul; Schmidt, Joshua M; Fournier-Level, Alexandre; Robin, Charles

2016-08-09

Scans of the Drosophila melanogaster genome have identified organophosphate resistance loci among those with the most pronounced signature of positive selection. In this study, the molecular basis of resistance to the organophosphate insecticide azinphos-methyl was investigated using the Drosophila Genetic Reference Panel, and genome-wide association. Recently released full transcriptome data were used to extend the utility of the Drosophila Genetic Reference Panel resource beyond traditional genome-wide association studies to allow systems genetics analyses of phenotypes. We found that both genomic and transcriptomic associations independently identified Cyp6g1, a gene involved in resistance to DDT and neonicotinoid insecticides, as the top candidate for azinphos-methyl resistance. This was verified by transgenically overexpressing Cyp6g1 using natural regulatory elements from a resistant allele, resulting in a 6.5-fold increase in resistance. We also identified four novel candidate genes associated with azinphos-methyl resistance, all of which are involved in either regulation of fat storage, or nervous system development. In Cyp6g1, we find a demonstrable resistance locus, a verification that transcriptome data can be used to identify variants associated with insecticide resistance, and an overlap between peaks of a genome-wide association study, and a genome-wide selective sweep analysis. Copyright © 2016 Battlay et al.

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

Science.gov (United States)

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 siz...

Global assessment of genomic variation in cattle by genome resequencing and high-throughput genotyping

DEFF Research Database (Denmark)

Zhan, Bujie; Fadista, João; Thomsen, Bo

2011-01-01

Background Integration of genomic variation with phenotypic information is an effective approach for uncovering genotype-phenotype associations. This requires an accurate identification of the different types of variation in individual genomes. Results We report the integration of the whole genome...... of split-read and read-pair approaches proved to be complementary in finding different signatures. CNVs were identified on the basis of the depth of sequenced reads, and by using SNP and CGH arrays. Conclusions Our results provide high resolution mapping of diverse classes of genomic variation...

A haplotype map of genomic variations and genome-wide association studies of agronomic traits in foxtail millet (Setaria italica).

Science.gov (United States)

Jia, Guanqing; Huang, Xuehui; Zhi, Hui; Zhao, Yan; Zhao, Qiang; Li, Wenjun; Chai, Yang; Yang, Lifang; Liu, Kunyan; Lu, Hengyun; Zhu, Chuanrang; Lu, Yiqi; Zhou, Congcong; Fan, Danlin; Weng, Qijun; Guo, Yunli; Huang, Tao; Zhang, Lei; Lu, Tingting; Feng, Qi; Hao, Hangfei; Liu, Hongkuan; Lu, Ping; Zhang, Ning; Li, Yuhui; Guo, Erhu; Wang, Shujun; Wang, Suying; Liu, Jinrong; Zhang, Wenfei; Chen, Guoqiu; Zhang, Baojin; Li, Wei; Wang, Yongfang; Li, Haiquan; Zhao, Baohua; Li, Jiayang; Diao, Xianmin; Han, Bin

2013-08-01

Foxtail millet (Setaria italica) is an important grain crop that is grown in arid regions. Here we sequenced 916 diverse foxtail millet varieties, identified 2.58 million SNPs and used 0.8 million common SNPs to construct a haplotype map of the foxtail millet genome. We classified the foxtail millet varieties into two divergent groups that are strongly correlated with early and late flowering times. We phenotyped the 916 varieties under five different environments and identified 512 loci associated with 47 agronomic traits by genome-wide association studies. We performed a de novo assembly of deeply sequenced genomes of a Setaria viridis accession (the wild progenitor of S. italica) and an S. italica variety and identified complex interspecies and intraspecies variants. We also identified 36 selective sweeps that seem to have occurred during modern breeding. This study provides fundamental resources for genetics research and genetic improvement in foxtail millet.

Comparative Genome Analyses of Streptococcus suis Isolates from Endocarditis Demonstrate Persistence of Dual Phenotypic Clones.

Science.gov (United States)

Tohya, Mari; Watanabe, Takayasu; Maruyama, Fumito; Arai, Sakura; Ota, Atsushi; Athey, Taryn B T; Fittipaldi, Nahuel; Nakagawa, Ichiro; Sekizaki, Tsutomu

2016-01-01

Many bacterial species coexist in the same niche as heterogeneous clones with different phenotypes; however, understanding of infectious diseases by polyphenotypic bacteria is still limited. In the present study, encapsulation in isolates of the porcine pathogen Streptococcus suis from persistent endocarditis lesions was examined. Coexistence of both encapsulated and unencapsulated S. suis isolates was found in 26 out of 59 endocarditis samples. The isolates were serotype 2, and belonged to two different sequence types (STs), ST1 and ST28. The genomes of each of the 26 pairs of encapsulated and unencapsulated isolates from the 26 samples were sequenced. The data showed that each pair of isolates had one or more unique nonsynonymous mutations in the cps gene, and the encapsulated and unencapsulated isolates from the same samples were closest to each other. Pairwise comparisons of the sequences of cps genes in 7 pairs of encapsulated and unencapsulated isolates identified insertion/deletions (indels) ranging from one to 104 bp in different cps genes of unencapsulated isolates. Capsule expression was restored in a subset of unencapsulated isolates by complementation in trans with cps expression vectors. Examination of gene content common to isolates indicated that mutation frequency was higher in ST28 pairs than in ST1 pairs. Genes within mobile genetic elements were mutation hot spots among ST28 isolates. Taken all together, our results demonstrate the coexistence of dual phenotype (encapsulated and unencapsulated) bacterial clones and suggest that the dual phenotypes arose independently in each farm by means of spontaneous mutations in cps genes.

Comparative Genome Analyses of Streptococcus suis Isolates from Endocarditis Demonstrate Persistence of Dual Phenotypic Clones.

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Mari Tohya

Full Text Available Many bacterial species coexist in the same niche as heterogeneous clones with different phenotypes; however, understanding of infectious diseases by polyphenotypic bacteria is still limited. In the present study, encapsulation in isolates of the porcine pathogen Streptococcus suis from persistent endocarditis lesions was examined. Coexistence of both encapsulated and unencapsulated S. suis isolates was found in 26 out of 59 endocarditis samples. The isolates were serotype 2, and belonged to two different sequence types (STs, ST1 and ST28. The genomes of each of the 26 pairs of encapsulated and unencapsulated isolates from the 26 samples were sequenced. The data showed that each pair of isolates had one or more unique nonsynonymous mutations in the cps gene, and the encapsulated and unencapsulated isolates from the same samples were closest to each other. Pairwise comparisons of the sequences of cps genes in 7 pairs of encapsulated and unencapsulated isolates identified insertion/deletions (indels ranging from one to 104 bp in different cps genes of unencapsulated isolates. Capsule expression was restored in a subset of unencapsulated isolates by complementation in trans with cps expression vectors. Examination of gene content common to isolates indicated that mutation frequency was higher in ST28 pairs than in ST1 pairs. Genes within mobile genetic elements were mutation hot spots among ST28 isolates. Taken all together, our results demonstrate the coexistence of dual phenotype (encapsulated and unencapsulated bacterial clones and suggest that the dual phenotypes arose independently in each farm by means of spontaneous mutations in cps genes.

Comparative Genome Analyses of Streptococcus suis Isolates from Endocarditis Demonstrate Persistence of Dual Phenotypic Clones

Science.gov (United States)

Tohya, Mari; Watanabe, Takayasu; Maruyama, Fumito; Arai, Sakura; Ota, Atsushi; Athey, Taryn B. T.; Fittipaldi, Nahuel; Nakagawa, Ichiro; Sekizaki, Tsutomu

2016-01-01

Many bacterial species coexist in the same niche as heterogeneous clones with different phenotypes; however, understanding of infectious diseases by polyphenotypic bacteria is still limited. In the present study, encapsulation in isolates of the porcine pathogen Streptococcus suis from persistent endocarditis lesions was examined. Coexistence of both encapsulated and unencapsulated S. suis isolates was found in 26 out of 59 endocarditis samples. The isolates were serotype 2, and belonged to two different sequence types (STs), ST1 and ST28. The genomes of each of the 26 pairs of encapsulated and unencapsulated isolates from the 26 samples were sequenced. The data showed that each pair of isolates had one or more unique nonsynonymous mutations in the cps gene, and the encapsulated and unencapsulated isolates from the same samples were closest to each other. Pairwise comparisons of the sequences of cps genes in 7 pairs of encapsulated and unencapsulated isolates identified insertion/deletions (indels) ranging from one to 104 bp in different cps genes of unencapsulated isolates. Capsule expression was restored in a subset of unencapsulated isolates by complementation in trans with cps expression vectors. Examination of gene content common to isolates indicated that mutation frequency was higher in ST28 pairs than in ST1 pairs. Genes within mobile genetic elements were mutation hot spots among ST28 isolates. Taken all together, our results demonstrate the coexistence of dual phenotype (encapsulated and unencapsulated) bacterial clones and suggest that the dual phenotypes arose independently in each farm by means of spontaneous mutations in cps genes. PMID:27433935

A refined model of the genomic basis for phenotypic variation in vertebrate hemostasis.

Science.gov (United States)

Ribeiro, Ângela M; Zepeda-Mendoza, M Lisandra; Bertelsen, Mads F; Kristensen, Annemarie T; Jarvis, Erich D; Gilbert, M Thomas P; da Fonseca, Rute R

2015-06-30

Hemostasis is a defense mechanism that enhances an organism's survival by minimizing blood loss upon vascular injury. In vertebrates, hemostasis has been evolving with the cardio-vascular and hemodynamic systems over the last 450 million years. Birds and mammals have very similar vascular and hemodynamic systems, thus the mechanism that blocks ruptures in the vasculature is expected to be the same. However, the speed of the process varies across vertebrates, and is particularly slow for birds. Understanding the differences in the hemostasis pathway between birds and mammals, and placing them in perspective to other vertebrates may provide clues to the genetic contribution to variation in blood clotting phenotype in vertebrates. We compiled genomic data corresponding to key elements involved in hemostasis across vertebrates to investigate its genetic basis and understand how it affects fitness. We found that: i) fewer genes are involved in hemostasis in birds compared to mammals; and ii) the largest differences concern platelet membrane receptors and components from the kallikrein-kinin system. We propose that lack of the cytoplasmic domain of the GPIb receptor subunit alpha could be a strong contributor to the prolonged bleeding phenotype in birds. Combined analysis of laboratory assessments of avian hemostasis with the first avian phylogeny based on genomic-scale data revealed that differences in hemostasis within birds are not explained by phylogenetic relationships, but more so by genetic variation underlying components of the hemostatic process, suggestive of natural selection. This work adds to our understanding of the evolution of hemostasis in vertebrates. The overlap with the inflammation, complement and renin-angiotensin (blood pressure regulation) pathways is a potential driver of rapid molecular evolution in the hemostasis network. Comparisons between avian species and mammals allowed us to hypothesize that the observed mammalian innovations might have

Genome-wide association studies on HIV susceptibility, pathogenesis and pharmacogenomics

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van Manen Daniëlle

2012-08-01

Full Text Available Abstract Susceptibility to HIV-1 and the clinical course after infection show a substantial heterogeneity between individuals. Part of this variability can be attributed to host genetic variation. Initial candidate gene studies have revealed interesting host factors that influence HIV infection, replication and pathogenesis. Recently, genome-wide association studies (GWAS were utilized for unbiased searches at a genome-wide level to discover novel genetic factors and pathways involved in HIV-1 infection. This review gives an overview of findings from the GWAS performed on HIV infection, within different cohorts, with variable patient and phenotype selection. Furthermore, novel techniques and strategies in research that might contribute to the complete understanding of virus-host interactions and its role on the pathogenesis of HIV infection are discussed.

Genome-Wide Association Study for Nine Plant Architecture Traits in Sorghum

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Jing Zhao

2016-07-01

Full Text Available Sorghum [ (L Moench], an important grain and forage crop, is receiving significant attention as a lignocellulosic feedstock because of its water-use efficiency and high biomass yield potential. Because of the advancement of genotyping and sequencing technologies, genome-wide association study (GWAS has become a routinely used method to investigate the genetic mechanisms underlying natural phenotypic variation. In this study, we performed a GWAS for nine grain and biomass-related plant architecture traits to determine their overall genetic architecture and the specific association of allelic variants in gibberellin (GA biosynthesis and signaling genes with these phenotypes. A total of 101 single-nucleotide polymorphism (SNP representative regions were associated with at least one of the nine traits, and two of the significant markers correspond to GA candidate genes, ( and (, affecting plant height and seed number, respectively. The resolution of a previously reported quantitative trait loci (QTL for leaf angle on chromosome 7 was increased to a 1.67 Mb region containing seven candidate genes with good prospects for further investigation. This study provides new knowledge of the association of GA genes with plant architecture traits and the genomic regions controlling variation in leaf angle, stem circumference, internode number, tiller number, seed number, panicle exsertion, and panicle length. The GA gene affecting seed number variation ( and the genomic region on chromosome 7 associated with variation in leaf angle are also important outcomes of this study and represent the foundation of future validation studies needed to apply this knowledge in breeding programs.

The Intersection of HPV Epidemiology, Genomics and Mechanistic Studies of HPV-Mediated Carcinogenesis.

Science.gov (United States)

Mirabello, Lisa; Clarke, Megan A; Nelson, Chase W; Dean, Michael; Wentzensen, Nicolas; Yeager, Meredith; Cullen, Michael; Boland, Joseph F; Schiffman, Mark; Burk, Robert D

2018-02-13

Of the ~60 human papillomavirus (HPV) genotypes that infect the cervicovaginal epithelium, only 12-13 "high-risk" types are well-established as causing cervical cancer, with HPV16 accounting for over half of all cases worldwide. While HPV16 is the most important carcinogenic type, variants of HPV16 can differ in their carcinogenicity by 10-fold or more in epidemiologic studies. Strong genotype-phenotype associations embedded in the small 8-kb HPV16 genome motivate molecular studies to understand the underlying molecular mechanisms. Understanding the mechanisms of HPV genomic findings is complicated by the linkage of HPV genome variants. A panel of experts in various disciplines gathered on 21 November 2016 to discuss the interdisciplinary science of HPV oncogenesis. Here, we summarize the discussion of the complexity of the viral-host interaction and highlight important next steps for selected applied basic laboratory studies guided by epidemiological genomic findings.

Clustering patterns of LOD scores for asthma-related phenotypes revealed by a genome-wide screen in 295 French EGEA families.

Science.gov (United States)

Bouzigon, Emmanuelle; Dizier, Marie-Hélène; Krähenbühl, Christine; Lemainque, Arnaud; Annesi-Maesano, Isabella; Betard, Christine; Bousquet, Jean; Charpin, Denis; Gormand, Frédéric; Guilloud-Bataille, Michel; Just, Jocelyne; Le Moual, Nicole; Maccario, Jean; Matran, Régis; Neukirch, Françoise; Oryszczyn, Marie-Pierre; Paty, Evelyne; Pin, Isabelle; Rosenberg-Bourgin, Myriam; Vervloet, Daniel; Kauffmann, Francine; Lathrop, Mark; Demenais, Florence

2004-12-15

A genome-wide scan for asthma phenotypes was conducted in the whole sample of 295 EGEA families selected through at least one asthmatic subject. In addition to asthma, seven phenotypes involved in the main asthma physiopathological pathways were considered: SPT (positive skin prick test response to at least one of 11 allergens), SPTQ score being the number of positive skin test responses to 11 allergens, Phadiatop (positive specific IgE response to a mixture of allergens), total IgE levels, eosinophils, bronchial responsiveness (BR) to methacholine challenge and %predicted FEV(1). Four regions showed evidence for linkage (Pphenotypes are more likely to share common genetic determinants, a principal component analysis was applied to the genome-wide LOD scores. This analysis revealed clustering of LODs for asthma, SPT and Phadiatop on one axis and clustering of LODs for %FEV(1), BR and SPTQ on the other, while LODs for IgE and eosinophils appeared to be independent from all other LODs. These results provide new insights into the potential sharing of genetic determinants by asthma-related phenotypes.

Genomic and Phenotypic Variation in Morphogenetic Networks of Two Candida albicans Isolates Subtends Their Different Pathogenic Potential

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Duccio Cavalieri

2018-01-01

Full Text Available The transition from commensalism to pathogenicity of Candida albicans reflects both the host inability to mount specific immune responses and the microorganism’s dimorphic switch efficiency. In this study, we used whole genome sequencing and microarray analysis to investigate the genomic determinants of the phenotypic changes observed in two C. albicans clinical isolates (YL1 and YQ2. In vitro experiments employing epithelial, microglial, and peripheral blood mononuclear cells were thus used to evaluate C. albicans isolates interaction with first line host defenses, measuring adhesion, susceptibility to phagocytosis, and induction of secretory responses. Moreover, a murine model of peritoneal infection was used to compare the in vivo pathogenic potential of the two isolates. Genome sequence and gene expression analysis of C. albicans YL1 and YQ2 showed significant changes in cellular pathways involved in environmental stress response, adhesion, filamentous growth, invasiveness, and dimorphic transition. This was in accordance with the observed marked phenotypic differences in biofilm production, dimorphic switch efficiency, cell adhesion, invasion, and survival to phagocyte-mediated host defenses. The mutations in key regulators of the hyphal growth pathway in the more virulent strain corresponded to an overall greater number of budding yeast cells released. Compared to YQ2, YL1 consistently showed enhanced pathogenic potential, since in vitro, it was less susceptible to ingestion by phagocytic cells and more efficient in invading epithelial cells, while in vivo YL1 was more effective than YQ2 in recruiting inflammatory cells, eliciting IL-1β response and eluding phagocytic cells. Overall, these results indicate an unexpected isolate-specific variation in pathways important for host invasion and colonization, showing how the genetic background of C. albicans may greatly affect its behavior both in vitro and in vivo. Based on this approach, we

Genome-Wide Association Studies In Plant Pathosystems: Toward an Ecological Genomics Approach

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Claudia Bartoli

2017-05-01

Full Text Available The emergence and re-emergence of plant pathogenic microorganisms are processes that imply perturbations in both host and pathogen ecological niches. Global change is largely assumed to drive the emergence of new etiological agents by altering the equilibrium of the ecological habitats which in turn places hosts more in contact with pathogen reservoirs. In this context, the number of epidemics is expected to increase dramatically in the next coming decades both in wild and crop plants. Under these considerations, the identification of the genetic variants underlying natural variation of resistance is a pre-requisite to estimate the adaptive potential of wild plant populations and to develop new breeding resistant cultivars. On the other hand, the prediction of pathogen's genetic determinants underlying disease emergence can help to identify plant resistance alleles. In the genomic era, whole genome sequencing combined with the development of statistical methods led to the emergence of Genome Wide Association (GWA mapping, a powerful tool for detecting genomic regions associated with natural variation of disease resistance in both wild and cultivated plants. However, GWA mapping has been less employed for the detection of genetic variants associated with pathogenicity in microbes. Here, we reviewed GWA studies performed either in plants or in pathogenic microorganisms (bacteria, fungi and oomycetes. In addition, we highlighted the benefits and caveats of the emerging joint GWA mapping approach that allows for the simultaneous identification of genes interacting between genomes of both partners. Finally, based on co-evolutionary processes in wild populations, we highlighted a phenotyping-free joint GWA mapping approach as a promising tool for describing the molecular landscape underlying plant - microbe interactions.

Powerful bivariate genome-wide association analyses suggest the SOX6 gene influencing both obesity and osteoporosis phenotypes in males.

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Yao-Zhong Liu

2009-08-01

Full Text Available Current genome-wide association studies (GWAS are normally implemented in a univariate framework and analyze different phenotypes in isolation. This univariate approach ignores the potential genetic correlation between important disease traits. Hence this approach is difficult to detect pleiotropic genes, which may exist for obesity and osteoporosis, two common diseases of major public health importance that are closely correlated genetically.To identify such pleiotropic genes and the key mechanistic links between the two diseases, we here performed the first bivariate GWAS of obesity and osteoporosis. We searched for genes underlying co-variation of the obesity phenotype, body mass index (BMI, with the osteoporosis risk phenotype, hip bone mineral density (BMD, scanning approximately 380,000 SNPs in 1,000 unrelated homogeneous Caucasians, including 499 males and 501 females. We identified in the male subjects two SNPs in intron 1 of the SOX6 (SRY-box 6 gene, rs297325 and rs4756846, which were bivariately associated with both BMI and hip BMD, achieving p values of 6.82x10(-7 and 1.47x10(-6, respectively. The two SNPs ranked at the top in significance for bivariate association with BMI and hip BMD in the male subjects among all the approximately 380,000 SNPs examined genome-wide. The two SNPs were replicated in a Framingham Heart Study (FHS cohort containing 3,355 Caucasians (1,370 males and 1,985 females from 975 families. In the FHS male subjects, the two SNPs achieved p values of 0.03 and 0.02, respectively, for bivariate association with BMI and femoral neck BMD. Interestingly, SOX6 was previously found to be essential to both cartilage formation/chondrogenesis and obesity-related insulin resistance, suggesting the gene's dual role in both bone and fat.Our findings, together with the prior biological evidence, suggest the SOX6 gene's importance in co-regulation of obesity and osteoporosis.

Powerful Bivariate Genome-Wide Association Analyses Suggest the SOX6 Gene Influencing Both Obesity and Osteoporosis Phenotypes in Males

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Liu, Yao-Zhong; Pei, Yu-Fang; Liu, Jian-Feng; Yang, Fang; Guo, Yan; Zhang, Lei; Liu, Xiao-Gang; Yan, Han; Wang, Liang; Zhang, Yin-Ping; Levy, Shawn; Recker, Robert R.; Deng, Hong-Wen

2009-01-01

Background Current genome-wide association studies (GWAS) are normally implemented in a univariate framework and analyze different phenotypes in isolation. This univariate approach ignores the potential genetic correlation between important disease traits. Hence this approach is difficult to detect pleiotropic genes, which may exist for obesity and osteoporosis, two common diseases of major public health importance that are closely correlated genetically. Principal Findings To identify such pleiotropic genes and the key mechanistic links between the two diseases, we here performed the first bivariate GWAS of obesity and osteoporosis. We searched for genes underlying co-variation of the obesity phenotype, body mass index (BMI), with the osteoporosis risk phenotype, hip bone mineral density (BMD), scanning ∼380,000 SNPs in 1,000 unrelated homogeneous Caucasians, including 499 males and 501 females. We identified in the male subjects two SNPs in intron 1 of the SOX6 (SRY-box 6) gene, rs297325 and rs4756846, which were bivariately associated with both BMI and hip BMD, achieving p values of 6.82×10−7 and 1.47×10−6, respectively. The two SNPs ranked at the top in significance for bivariate association with BMI and hip BMD in the male subjects among all the ∼380,000 SNPs examined genome-wide. The two SNPs were replicated in a Framingham Heart Study (FHS) cohort containing 3,355 Caucasians (1,370 males and 1,985 females) from 975 families. In the FHS male subjects, the two SNPs achieved p values of 0.03 and 0.02, respectively, for bivariate association with BMI and femoral neck BMD. Interestingly, SOX6 was previously found to be essential to both cartilage formation/chondrogenesis and obesity-related insulin resistance, suggesting the gene's dual role in both bone and fat. Conclusions Our findings, together with the prior biological evidence, suggest the SOX6 gene's importance in co-regulation of obesity and osteoporosis. PMID:19714249

Plant phenomics and the need for physiological phenotyping across scales to narrow the genotype-to-phenotype knowledge gap

DEFF Research Database (Denmark)

Grosskinsky, Dominik Kilian; Svensgaard, Jesper; Christensen, Svend

2015-01-01

Plants are affected by complex genome×environment×management interactions which determine phenotypic plasticity as a result of the variability of genetic components. Whereas great advances have been made in the cost-efficient and high-throughput analyses of genetic information and non-invasive ph......Plants are affected by complex genome×environment×management interactions which determine phenotypic plasticity as a result of the variability of genetic components. Whereas great advances have been made in the cost-efficient and high-throughput analyses of genetic information and non......-invasive phenotyping, the large-scale analyses of the underlying physiological mechanisms lag behind. The external phenotype is determined by the sum of the complex interactions of metabolic pathways and intracellular regulatory networks that is reflected in an internal, physiological, and biochemical phenotype......, ultimately enabling the in silico assessment of responses under defined environments with advanced crop models. This will allow generation of robust physiological predictors also for complex traits to bridge the knowledge gap between genotype and phenotype for applications in breeding, precision farming...

The whole genome sequences and experimentally phased haplotypes of over 100 personal genomes.

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Mao, Qing; Ciotlos, Serban; Zhang, Rebecca Yu; Ball, Madeleine P; Chin, Robert; Carnevali, Paolo; Barua, Nina; Nguyen, Staci; Agarwal, Misha R; Clegg, Tom; Connelly, Abram; Vandewege, Ward; Zaranek, Alexander Wait; Estep, Preston W; Church, George M; Drmanac, Radoje; Peters, Brock A

2016-10-11

Since the completion of the Human Genome Project in 2003, it is estimated that more than 200,000 individual whole human genomes have been sequenced. A stunning accomplishment in such a short period of time. However, most of these were sequenced without experimental haplotype data and are therefore missing an important aspect of genome biology. In addition, much of the genomic data is not available to the public and lacks phenotypic information. As part of the Personal Genome Project, blood samples from 184 participants were collected and processed using Complete Genomics' Long Fragment Read technology. Here, we present the experimental whole genome haplotyping and sequencing of these samples to an average read coverage depth of 100X. This is approximately three-fold higher than the read coverage applied to most whole human genome assemblies and ensures the highest quality results. Currently, 114 genomes from this dataset are freely available in the GigaDB repository and are associated with rich phenotypic data; the remaining 70 should be added in the near future as they are approved through the PGP data release process. For reproducibility analyses, 20 genomes were sequenced at least twice using independent LFR barcoded libraries. Seven genomes were also sequenced using Complete Genomics' standard non-barcoded library process. In addition, we report 2.6 million high-quality, rare variants not previously identified in the Single Nucleotide Polymorphisms database or the 1000 Genomes Project Phase 3 data. These genomes represent a unique source of haplotype and phenotype data for the scientific community and should help to expand our understanding of human genome evolution and function.

Genome profiling (GP method based classification of insects: congruence with that of classical phenotype-based one.

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Shamim Ahmed

Full Text Available Ribosomal RNAs have been widely used for identification and classification of species, and have produced data giving new insights into phylogenetic relationships. Recently, multilocus genotyping and even whole genome sequencing-based technologies have been adopted in ambitious comparative biology studies. However, such technologies are still far from routine-use in species classification studies due to their high costs in terms of labor, equipment and consumables.Here, we describe a simple and powerful approach for species classification called genome profiling (GP. The GP method composed of random PCR, temperature gradient gel electrophoresis (TGGE and computer-aided gel image processing is highly informative and less laborious. For demonstration, we classified 26 species of insects using GP and 18S rDNA-sequencing approaches. The GP method was found to give a better correspondence to the classical phenotype-based approach than did 18S rDNA sequencing employing a congruence value. To our surprise, use of a single probe in GP was sufficient to identify the relationships between the insect species, making this approach more straightforward.The data gathered here, together with those of previous studies show that GP is a simple and powerful method that can be applied for actually universally identifying and classifying species. The current success supported our previous proposal that GP-based web database can be constructible and effective for the global identification/classification of species.

Genome-wide and gene-based association studies of anxiety disorders in European and African American samples.

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Takeshi Otowa

Full Text Available Anxiety disorders (ADs are common mental disorders caused by a combination of genetic and environmental factors. Since ADs are highly comorbid with each other, partially due to shared genetic basis, studying AD phenotypes in a coordinated manner may be a powerful strategy for identifying potential genetic loci for ADs. To detect these loci, we performed genome-wide association studies (GWAS of ADs. In addition, as a complementary approach to single-locus analysis, we also conducted gene- and pathway-based analyses. GWAS data were derived from the control sample of the Molecular Genetics of Schizophrenia (MGS project (2,540 European American and 849 African American subjects genotyped on the Affymetrix GeneChip 6.0 array. We applied two phenotypic approaches: (1 categorical case-control comparisons (CC based upon psychiatric diagnoses, and (2 quantitative phenotypic factor scores (FS derived from a multivariate analysis combining information across the clinical phenotypes. Linear and logistic models were used to analyse the association with ADs using FS and CC traits, respectively. At the single locus level, no genome-wide significant association was found. A trans-population gene-based meta-analysis across both ethnic subsamples using FS identified three genes (MFAP3L on 4q32.3, NDUFAB1 and PALB2 on 16p12 with genome-wide significance (false discovery rate (FDR] <5%. At the pathway level, several terms such as transcription regulation, cytokine binding, and developmental process were significantly enriched in ADs (FDR <5%. Our approaches studying ADs as quantitative traits and utilizing the full GWAS data may be useful in identifying susceptibility genes and pathways for ADs.

Sequence-Based Mapping and Genome Editing Reveal Mutations in Stickleback Hps5 Cause Oculocutaneous Albinism and the casper Phenotype

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James C. Hart

2017-09-01

Full Text Available Here, we present and characterize the spontaneous X-linked recessive mutation casper, which causes oculocutaneous albinism in threespine sticklebacks (Gasterosteus aculeatus. In humans, Hermansky-Pudlak syndrome results in pigmentation defects due to disrupted formation of the melanin-containing lysosomal-related organelle (LRO, the melanosome. casper mutants display not only reduced pigmentation of melanosomes in melanophores, but also reductions in the iridescent silver color from iridophores, while the yellow pigmentation from xanthophores appears unaffected. We mapped casper using high-throughput sequencing of genomic DNA from bulked casper mutants to a region of the stickleback X chromosome (chromosome 19 near the stickleback ortholog of Hermansky-Pudlak syndrome 5 (Hps5. casper mutants have an insertion of a single nucleotide in the sixth exon of Hps5, predicted to generate an early frameshift. Genome editing using CRISPR/Cas9 induced lesions in Hps5 and phenocopied the casper mutation. Injecting single or paired Hps5 guide RNAs revealed higher incidences of genomic deletions from paired guide RNAs compared to single gRNAs. Stickleback Hps5 provides a genetic system where a hemizygous locus in XY males and a diploid locus in XX females can be used to generate an easily scored visible phenotype, facilitating quantitative studies of different genome editing approaches. Lastly, we show the ability to better visualize patterns of fluorescent transgenic reporters in Hps5 mutant fish. Thus, Hps5 mutations present an opportunity to study pigmented LROs in the emerging stickleback model system, as well as a tool to aid in assaying genome editing and visualizing enhancer activity in transgenic fish.

Phenomics, Genomics and Genetics in Plasmodium vinckei

KAUST Repository

Ramaprasad, Abhinay

2017-11-01

Rodent malaria parasites (RMPs) serve as tractable models for experimental genetics, and as valuable tools to study malaria parasite biology and host-parasitevector interactions. Plasmodium vinckei, one of four RMPs adapted to laboratory mice, is the most geographically widespread species and displays considerable phenotypic and genotypic diversity amongst its subspecies and strains. The phenotypes and genotypes of P. vinckei isolates have been relatively less characterized compared to other RMPs, hampering its use as an experimental model for malaria. Here, we have studied the phenotypes and sequenced the genomes and transcriptomes of ten P. vinckei isolates including representatives of all five subspecies, all of which were collected from wild thicket rats (Thamnomys rutilans) in sub-Saharan Central Africa between the late 1940s and mid 1960s. We have generated a comprehensive resource for P. vinckei comprising of five high-quality reference genomes, growth profiles and genotypes of P. vinckei isolates, and expression profiles of genes across the intra-erythrocytic developmental stages of the parasite. We observe significant phenotypic and genotypic diversity among P. vinckei isolates, making them particularly suitable for classical genetics and genomics-driven studies on malaria parasite biology. As part of a proof of concept study, we have shown that experimental genetic crosses can be performed between P. vinckei parasites to potentially identify genotype-phenotype relationships. We have also shown that they are amenable to genetic manipulation in the laboratory.

The Intersection of HPV Epidemiology, Genomics and Mechanistic Studies of HPV-Mediated Carcinogenesis

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Lisa Mirabello

2018-02-01

Full Text Available Of the ~60 human papillomavirus (HPV genotypes that infect the cervicovaginal epithelium, only 12–13 “high-risk” types are well-established as causing cervical cancer, with HPV16 accounting for over half of all cases worldwide. While HPV16 is the most important carcinogenic type, variants of HPV16 can differ in their carcinogenicity by 10-fold or more in epidemiologic studies. Strong genotype-phenotype associations embedded in the small 8-kb HPV16 genome motivate molecular studies to understand the underlying molecular mechanisms. Understanding the mechanisms of HPV genomic findings is complicated by the linkage of HPV genome variants. A panel of experts in various disciplines gathered on 21 November 2016 to discuss the interdisciplinary science of HPV oncogenesis. Here, we summarize the discussion of the complexity of the viral–host interaction and highlight important next steps for selected applied basic laboratory studies guided by epidemiological genomic findings.

Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives

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Guijun Yang

2017-06-01

Full Text Available Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypic information to increase the crop yield. Traditional methods for acquiring crop traits, such as plant height, leaf color, leaf area index (LAI, chlorophyll content, biomass and yield, rely on manual sampling, which is time-consuming and laborious. Unmanned aerial vehicle remote sensing platforms (UAV-RSPs equipped with different sensors have recently become an important approach for fast and non-destructive high throughput phenotyping and have the advantage of flexible and convenient operation, on-demand access to data and high spatial resolution. UAV-RSPs are a powerful tool for studying phenomics and genomics. As the methods and applications for field phenotyping using UAVs to users who willing to derive phenotypic parameters from large fields and tests with the minimum effort on field work and getting highly reliable results are necessary, the current status and perspectives on the topic of UAV-RSPs for field-based phenotyping were reviewed based on the literature survey of crop phenotyping using UAV-RSPs in the Web of Science™ Core Collection database and cases study by NERCITA. The reference for the selection of UAV platforms and remote sensing sensors, the commonly adopted methods and typical applications for analyzing phenotypic traits by UAV-RSPs, and the challenge for crop phenotyping by UAV-RSPs were considered. The review can provide theoretical and technical support to promote the applications of UAV-RSPs for crop phenotyping.

Inference of gene-phenotype associations via protein-protein interaction and orthology.

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Panwen Wang

Full Text Available One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.

Using rice genome-wide association studies to identify DNA markers for marker-assisted selection

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Rice association mapping panels are collections of rice (Oryza sativa L.) accessions developed for genome-wide association (GWA) studies. One of these panels, the Rice Diversity Panel 1 (RDP1) was phenotyped by various research groups for several traits of interest, and more recently, genotyped with...

Phenotyping for drought tolerance of crops in the genomics era

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Roberto eTuberosa

2012-09-01

Full Text Available Improving crops yield under water-limited conditions is the most daunting challenge faced by breeders. To this end, accurate, relevant phenotyping plays an increasingly pivotal role for the selection of drought-resilient genotypes and, more in general, for a meaningful dissection of the quantitative genetic landscape that underscores the adaptive response of crops to drought. A major and universally recognised obstacle to a more effective translation of the results produced by drought-related studies into improved cultivars is the difficulty in properly phenotyping in a high-throughput fashion in order to identify the quantitative trait loci that govern yield and related traits across different water regimes. This review provides basic principles and a broad set of references useful for the management of phenotyping practices for the study and genetic dissection of drought tolerance and, ultimately, for the release of drought-tolerant cultivars.

Using Nematostella vectensis to study the interactions between genome, epigenome and bacteria in a changing environment

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Sebastian Fraune

2016-08-01

Full Text Available The phenotype of an animal cannot be explained entirely by its genes. It is now clear that factors other than the genome contribute to the ecology and evolution of animals. Two fundamentally important factors are the associated microbiota and epigenetic regulations. Unlike the genes and regulatory regions of the genome, epigenetics and microbial composition can be rapidly modified, and may thus represent mechanisms for rapid acclimation to a changing environment. At present, the individual functions of epigenetics, microbiomes, and genomic mutations are largely studied in isolation, particularly for species in marine ecosystems. This single variable approach leaves significant questions open for how these mechanisms intersect in the acclimation and adaptation of organisms in different environments. Here, we propose that the starlet sea anemone, Nematostella vectensis, is a model of choice to investigate the complex interplay between adaptation as well as physiological and molecular plasticity in coastal ecosystems. N. vectensis’ geographic range spans four distinct coastlines, including a wide thermocline along the Atlantic coast of North America. N. vectensis is a particularly powerful invertebrate model for studying genome-environment interactions due to (1 the availability of a well-annotated genome, including preexisting data on genome methylation, histone modifications and miRNAs, (2 an extensive molecular toolkit including well-developed protocols for gene suppression and transgenesis, and (3 the simplicity of culture and experimentation in the laboratory. Taken together, N. vectensis has the tractability to connect the functional relationships between a host animal, microbes, and genome modifications to determine mechanisms underlying phenotypic plasticity and local adaptation.

Complete genomes of Hairstreak butterflies, their speciation, and nucleo-mitochondrial incongruence.

Science.gov (United States)

Cong, Qian; Shen, Jinhui; Borek, Dominika; Robbins, Robert K; Otwinowski, Zbyszek; Grishin, Nick V

2016-04-28

Comparison of complete genomes of closely related species enables research on speciation and how phenotype is determined by genotype. Lepidoptera, an insect order of 150,000 species with diverse phenotypes, is well-suited for such comparative genomics studies if new genomes, which cover additional Lepidoptera families are acquired. We report a 729 Mbp genome assembly of the Calycopis cecrops, the first genome from the family Lycaenidae and the largest available Lepidoptera genome. As detritivore, Calycopis shows expansion in detoxification and digestion enzymes. We further obtained complete genomes of 8 Calycopis specimens: 3 C. cecrops and 5 C. isobeon, including a dry specimen stored in the museum for 30 years. The two species differ subtly in phenotype and cannot be differentiated by mitochondrial DNA. However, nuclear genomes revealed a deep split between them. Genes that can clearly separate the two species (speciation hotspots) mostly pertain to circadian clock, mating behavior, transcription regulation, development and cytoskeleton. The speciation hotspots and their function significantly overlap with those we previously found in Pterourus, suggesting common speciation mechanisms in these butterflies.

GEnomes Management Application (GEM.app): a new software tool for large-scale collaborative genome analysis.

Science.gov (United States)

Gonzalez, Michael A; Lebrigio, Rafael F Acosta; Van Booven, Derek; Ulloa, Rick H; Powell, Eric; Speziani, Fiorella; Tekin, Mustafa; Schüle, Rebecca; Züchner, Stephan

2013-06-01

Novel genes are now identified at a rapid pace for many Mendelian disorders, and increasingly, for genetically complex phenotypes. However, new challenges have also become evident: (1) effectively managing larger exome and/or genome datasets, especially for smaller labs; (2) direct hands-on analysis and contextual interpretation of variant data in large genomic datasets; and (3) many small and medium-sized clinical and research-based investigative teams around the world are generating data that, if combined and shared, will significantly increase the opportunities for the entire community to identify new genes. To address these challenges, we have developed GEnomes Management Application (GEM.app), a software tool to annotate, manage, visualize, and analyze large genomic datasets (https://genomics.med.miami.edu/). GEM.app currently contains ∼1,600 whole exomes from 50 different phenotypes studied by 40 principal investigators from 15 different countries. The focus of GEM.app is on user-friendly analysis for nonbioinformaticians to make next-generation sequencing data directly accessible. Yet, GEM.app provides powerful and flexible filter options, including single family filtering, across family/phenotype queries, nested filtering, and evaluation of segregation in families. In addition, the system is fast, obtaining results within 4 sec across ∼1,200 exomes. We believe that this system will further enhance identification of genetic causes of human disease. © 2013 Wiley Periodicals, Inc.

Genome-Wide Linkage Analysis of Hemodynamic Parameters Under Mental and Physical Stress in Extended Omani Arab Pedigrees : The Oman Family Study

NARCIS (Netherlands)

Hassan, Mohammed O.; Jaju, Deepali; Voruganti, V. Saroja; Bayoumi, Riad A.; Albarwani, Sulayma; Al-Yahyaee, Saeed; Aslani, Afshin; Snieder, Harold; Lopez-Alvarenga, Juan C.; Al-Anqoudi, Zahir M.; Alizadeh, Behrooz Z.; Comuzzie, Anthony G.

Background: We performed a genome-wide scan in a homogeneous Arab population to identify genomic regions linked to blood pressure (BP) and its intermediate phenotypes during mental and physical stress tests. Methods: The Oman Family Study subjects (N = 1277) were recruited from five extended

A genome-wide association study identifies CDHR3 as a susceptibility locus for early childhood asthma with severe exacerbations

DEFF Research Database (Denmark)

Bønnelykke, Klaus; Sleiman, Patrick; Nielsen, Kasper

2014-01-01

Asthma exacerbations are among the most frequent causes of hospitalization during childhood, but the underlying mechanisms are poorly understood. We performed a genome-wide association study of a specific asthma phenotype characterized by recurrent, severe exacerbations occurring between 2 and 6......1RL1, were previously reported as asthma susceptibility loci, but the effect sizes for these loci in our cohort were considerably larger than in the previous genome-wide association studies of asthma. We also obtained strong evidence for a new susceptibility gene, CDHR3 (encoding cadherin......-related family member 3), which is highly expressed in airway epithelium. These results demonstrate the strength of applying specific phenotyping in the search for asthma susceptibility genes....

Technical note: Equivalent genomic models with a residual polygenic effect.

Science.gov (United States)

Liu, Z; Goddard, M E; Hayes, B J; Reinhardt, F; Reents, R

2016-03-01

Routine genomic evaluations in animal breeding are usually based on either a BLUP with genomic relationship matrix (GBLUP) or single nucleotide polymorphism (SNP) BLUP model. For a multi-step genomic evaluation, these 2 alternative genomic models were proven to give equivalent predictions for genomic reference animals. The model equivalence was verified also for young genotyped animals without phenotypes. Due to incomplete linkage disequilibrium of SNP markers to genes or causal mutations responsible for genetic inheritance of quantitative traits, SNP markers cannot explain all the genetic variance. A residual polygenic effect is normally fitted in the genomic model to account for the incomplete linkage disequilibrium. In this study, we start by showing the proof that the multi-step GBLUP and SNP BLUP models are equivalent for the reference animals, when they have a residual polygenic effect included. Second, the equivalence of both multi-step genomic models with a residual polygenic effect was also verified for young genotyped animals without phenotypes. Additionally, we derived formulas to convert genomic estimated breeding values of the GBLUP model to its components, direct genomic values and residual polygenic effect. Third, we made a proof that the equivalence of these 2 genomic models with a residual polygenic effect holds also for single-step genomic evaluation. Both the single-step GBLUP and SNP BLUP models lead to equal prediction for genotyped animals with phenotypes (e.g., reference animals), as well as for (young) genotyped animals without phenotypes. Finally, these 2 single-step genomic models with a residual polygenic effect were proven to be equivalent for estimation of SNP effects, too. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Quantitative Assessment of Eye Phenotypes for Functional Genetic Studies Using Drosophila melanogaster

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Janani Iyer

2016-05-01

Full Text Available About two-thirds of the vital genes in the Drosophila genome are involved in eye development, making the fly eye an excellent genetic system to study cellular function and development, neurodevelopment/degeneration, and complex diseases such as cancer and diabetes. We developed a novel computational method, implemented as Flynotyper software (http://flynotyper.sourceforge.net, to quantitatively assess the morphological defects in the Drosophila eye resulting from genetic alterations affecting basic cellular and developmental processes. Flynotyper utilizes a series of image processing operations to automatically detect the fly eye and the individual ommatidium, and calculates a phenotypic score as a measure of the disorderliness of ommatidial arrangement in the fly eye. As a proof of principle, we tested our method by analyzing the defects due to eye-specific knockdown of Drosophila orthologs of 12 neurodevelopmental genes to accurately document differential sensitivities of these genes to dosage alteration. We also evaluated eye images from six independent studies assessing the effect of overexpression of repeats, candidates from peptide library screens, and modifiers of neurotoxicity and developmental processes on eye morphology, and show strong concordance with the original assessment. We further demonstrate the utility of this method by analyzing 16 modifiers of sine oculis obtained from two genome-wide deficiency screens of Drosophila and accurately quantifying the effect of its enhancers and suppressors during eye development. Our method will complement existing assays for eye phenotypes, and increase the accuracy of studies that use fly eyes for functional evaluation of genes and genetic interactions.

Text-based phenotypic profiles incorporating biochemical phenotypes of inborn errors of metabolism improve phenomics-based diagnosis.

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Lee, Jessica J Y; Gottlieb, Michael M; Lever, Jake; Jones, Steven J M; Blau, Nenad; van Karnebeek, Clara D M; Wasserman, Wyeth W

2018-05-01

Phenomics is the comprehensive study of phenotypes at every level of biology: from metabolites to organisms. With high throughput technologies increasing the scope of biological discoveries, the field of phenomics has been developing rapid and precise methods to collect, catalog, and analyze phenotypes. Such methods have allowed phenotypic data to be widely used in medical applications, from assisting clinical diagnoses to prioritizing genomic diagnoses. To channel the benefits of phenomics into the field of inborn errors of metabolism (IEM), we have recently launched IEMbase, an expert-curated knowledgebase of IEM and their disease-characterizing phenotypes. While our efforts with IEMbase have realized benefits, taking full advantage of phenomics requires a comprehensive curation of IEM phenotypes in core phenomics projects, which is dependent upon contributions from the IEM clinical and research community. Here, we assess the inclusion of IEM biochemical phenotypes in a core phenomics project, the Human Phenotype Ontology. We then demonstrate the utility of biochemical phenotypes using a text-based phenomics method to predict gene-disease relationships, showing that the prediction of IEM genes is significantly better using biochemical rather than clinical profiles. The findings herein provide a motivating goal for the IEM community to expand the computationally accessible descriptions of biochemical phenotypes associated with IEM in phenomics resources.

Comparative genomics and transcriptomics of trait-gene association

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Pierlé Sebastián

2012-11-01

Full Text Available Abstract Background The Order Rickettsiales includes important tick-borne pathogens, from Rickettsia rickettsii, which causes Rocky Mountain spotted fever, to Anaplasma marginale, the most prevalent vector-borne pathogen of cattle. Although most pathogens in this Order are transmitted by arthropod vectors, little is known about the microbial determinants of transmission. A. marginale provides unique tools for studying the determinants of transmission, with multiple strain sequences available that display distinct and reproducible transmission phenotypes. The closed core A. marginale genome suggests that any phenotypic differences are due to single nucleotide polymorphisms (SNPs. We combined DNA/RNA comparative genomic approaches using strains with different tick transmission phenotypes and identified genes that segregate with transmissibility. Results Comparison of seven strains with different transmission phenotypes generated a list of SNPs affecting 18 genes and nine promoters. Transcriptional analysis found two candidate genes downstream from promoter SNPs that were differentially transcribed. To corroborate the comparative genomics approach we used three RNA-seq platforms to analyze the transcriptomes from two A. marginale strains with different transmission phenotypes. RNA-seq analysis confirmed the comparative genomics data and found 10 additional genes whose transcription between strains with distinct transmission efficiencies was significantly different. Six regions of the genome that contained no annotation were found to be transcriptionally active, and two of these newly identified transcripts were differentially transcribed. Conclusions This approach identified 30 genes and two novel transcripts potentially involved in tick transmission. We describe the transcriptome of an obligate intracellular bacterium in depth, while employing massive parallel sequencing to dissect an important trait in bacterial pathogenesis.

On the analysis of genome-wide association studies in family-based designs: a universal, robust analysis approach and an application to four genome-wide association studies.

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Sungho Won

2009-11-01

Full Text Available For genome-wide association studies in family-based designs, we propose a new, universally applicable approach. The new test statistic exploits all available information about the association, while, by virtue of its design, it maintains the same robustness against population admixture as traditional family-based approaches that are based exclusively on the within-family information. The approach is suitable for the analysis of almost any trait type, e.g. binary, continuous, time-to-onset, multivariate, etc., and combinations of those. We use simulation studies to verify all theoretically derived properties of the approach, estimate its power, and compare it with other standard approaches. We illustrate the practical implications of the new analysis method by an application to a lung-function phenotype, forced expiratory volume in one second (FEV1 in 4 genome-wide association studies.

Using Extreme Phenotype Sampling to Identify the Rare Causal Variants of Quantitative Traits in Association Studies

OpenAIRE

Li, Dalin; Lewinger, Juan Pablo; Gauderman, William J.; Murcray, Cassandra Elizabeth; Conti, David

2011-01-01

Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach fo...

Gene networks underlying convergent and pleiotropic phenotypes in a large and systematically-phenotyped cohort with heterogeneous developmental disorders.

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Tallulah Andrews

2015-03-01

Full Text Available Readily-accessible and standardised capture of genotypic variation has revolutionised our understanding of the genetic contribution to disease. Unfortunately, the corresponding systematic capture of patient phenotypic variation needed to fully interpret the impact of genetic variation has lagged far behind. Exploiting deep and systematic phenotyping of a cohort of 197 patients presenting with heterogeneous developmental disorders and whose genomes harbour de novo CNVs, we systematically applied a range of commonly-used functional genomics approaches to identify the underlying molecular perturbations and their phenotypic impact. Grouping patients into 408 non-exclusive patient-phenotype groups, we identified a functional association amongst the genes disrupted in 209 (51% groups. We find evidence for a significant number of molecular interactions amongst the association-contributing genes, including a single highly-interconnected network disrupted in 20% of patients with intellectual disability, and show using microcephaly how these molecular networks can be used as baits to identify additional members whose genes are variant in other patients with the same phenotype. Exploiting the systematic phenotyping of this cohort, we observe phenotypic concordance amongst patients whose variant genes contribute to the same functional association but note that (i this relationship shows significant variation across the different approaches used to infer a commonly perturbed molecular pathway, and (ii that the phenotypic similarities detected amongst patients who share the same inferred pathway perturbation result from these patients sharing many distinct phenotypes, rather than sharing a more specific phenotype, inferring that these pathways are best characterized by their pleiotropic effects.

Gene networks underlying convergent and pleiotropic phenotypes in a large and systematically-phenotyped cohort with heterogeneous developmental disorders.

Science.gov (United States)

Andrews, Tallulah; Meader, Stephen; Vulto-van Silfhout, Anneke; Taylor, Avigail; Steinberg, Julia; Hehir-Kwa, Jayne; Pfundt, Rolph; de Leeuw, Nicole; de Vries, Bert B A; Webber, Caleb

2015-03-01

Readily-accessible and standardised capture of genotypic variation has revolutionised our understanding of the genetic contribution to disease. Unfortunately, the corresponding systematic capture of patient phenotypic variation needed to fully interpret the impact of genetic variation has lagged far behind. Exploiting deep and systematic phenotyping of a cohort of 197 patients presenting with heterogeneous developmental disorders and whose genomes harbour de novo CNVs, we systematically applied a range of commonly-used functional genomics approaches to identify the underlying molecular perturbations and their phenotypic impact. Grouping patients into 408 non-exclusive patient-phenotype groups, we identified a functional association amongst the genes disrupted in 209 (51%) groups. We find evidence for a significant number of molecular interactions amongst the association-contributing genes, including a single highly-interconnected network disrupted in 20% of patients with intellectual disability, and show using microcephaly how these molecular networks can be used as baits to identify additional members whose genes are variant in other patients with the same phenotype. Exploiting the systematic phenotyping of this cohort, we observe phenotypic concordance amongst patients whose variant genes contribute to the same functional association but note that (i) this relationship shows significant variation across the different approaches used to infer a commonly perturbed molecular pathway, and (ii) that the phenotypic similarities detected amongst patients who share the same inferred pathway perturbation result from these patients sharing many distinct phenotypes, rather than sharing a more specific phenotype, inferring that these pathways are best characterized by their pleiotropic effects.

Functional genomics of physiological plasticity and local adaptation in killifish.

Science.gov (United States)

Whitehead, Andrew; Galvez, Fernando; Zhang, Shujun; Williams, Larissa M; Oleksiak, Marjorie F

2011-01-01

Evolutionary solutions to the physiological challenges of life in highly variable habitats can span the continuum from evolution of a cosmopolitan plastic phenotype to the evolution of locally adapted phenotypes. Killifish (Fundulus sp.) have evolved both highly plastic and locally adapted phenotypes within different selective contexts, providing a comparative system in which to explore the genomic underpinnings of physiological plasticity and adaptive variation. Importantly, extensive variation exists among populations and species for tolerance to a variety of stressors, and we exploit this variation in comparative studies to yield insights into the genomic basis of evolved phenotypic variation. Notably, species of Fundulus occupy the continuum of osmotic habitats from freshwater to marine and populations within Fundulus heteroclitus span far greater variation in pollution tolerance than across all species of fish. Here, we explore how transcriptome regulation underpins extreme physiological plasticity on osmotic shock and how genomic and transcriptomic variation is associated with locally evolved pollution tolerance. We show that F. heteroclitus quickly acclimate to extreme osmotic shock by mounting a dramatic rapid transcriptomic response including an early crisis control phase followed by a tissue remodeling phase involving many regulatory pathways. We also show that convergent evolution of locally adapted pollution tolerance involves complex patterns of gene expression and genome sequence variation, which is confounded with body-weight dependence for some genes. Similarly, exploiting the natural phenotypic variation associated with other established and emerging model organisms is likely to greatly accelerate the pace of discovery of the genomic basis of phenotypic variation.

Insights into structural variations and genome rearrangements in prokaryotic genomes.

Science.gov (United States)

Periwal, Vinita; Scaria, Vinod

2015-01-01

Structural variations (SVs) are genomic rearrangements that affect fairly large fragments of DNA. Most of the SVs such as inversions, deletions and translocations have been largely studied in context of genetic diseases in eukaryotes. However, recent studies demonstrate that genome rearrangements can also have profound impact on prokaryotic genomes, leading to altered cell phenotype. In contrast to single-nucleotide variations, SVs provide a much deeper insight into organization of bacterial genomes at a much better resolution. SVs can confer change in gene copy number, creation of new genes, altered gene expression and many other functional consequences. High-throughput technologies have now made it possible to explore SVs at a much refined resolution in bacterial genomes. Through this review, we aim to highlight the importance of the less explored field of SVs in prokaryotic genomes and their impact. We also discuss its potential applicability in the emerging fields of synthetic biology and genome engineering where targeted SVs could serve to create sophisticated and accurate genome editing. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Root phenotyping: from component trait in the lab to breeding.

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Kuijken, René C P; van Eeuwijk, Fred A; Marcelis, Leo F M; Bouwmeester, Harro J

2015-09-01

In the last decade cheaper and faster sequencing methods have resulted in an enormous increase in genomic data. High throughput genotyping, genotyping by sequencing and genomic breeding are becoming a standard in plant breeding. As a result, the collection of phenotypic data is increasingly becoming a limiting factor in plant breeding. Genetic studies on root traits are being hampered by the complexity of these traits and the inaccessibility of the rhizosphere. With an increasing interest in phenotyping, breeders and scientists try to overcome these limitations, resulting in impressive developments in automated phenotyping platforms. Recently, many such platforms have been thoroughly described, yet their efficiency to increase genetic gain often remains undiscussed. This efficiency depends on the heritability of the phenotyped traits as well as the correlation of these traits with agronomically relevant breeding targets. This review provides an overview of the latest developments in root phenotyping and describes the environmental and genetic factors influencing root phenotype and heritability. It also intends to give direction to future phenotyping and breeding strategies for optimizing root system functioning. A quantitative framework to determine the efficiency of phenotyping platforms for genetic gain is described. By increasing heritability, managing effects caused by interactions between genotype and environment and by quantifying the genetic relation between traits phenotyped in platforms and ultimate breeding targets, phenotyping platforms can be utilized to their maximum potential. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Imputation of variants from the 1000 Genomes Project modestly improves known associations and can identify low-frequency variant-phenotype associations undetected by HapMap based imputation.

Science.gov (United States)

Wood, Andrew R; Perry, John R B; Tanaka, Toshiko; Hernandez, Dena G; Zheng, Hou-Feng; Melzer, David; Gibbs, J Raphael; Nalls, Michael A; Weedon, Michael N; Spector, Tim D; Richards, J Brent; Bandinelli, Stefania; Ferrucci, Luigi; Singleton, Andrew B; Frayling, Timothy M

2013-01-01

Genome-wide association (GWA) studies have been limited by the reliance on common variants present on microarrays or imputable from the HapMap Project data. More recently, the completion of the 1000 Genomes Project has provided variant and haplotype information for several million variants derived from sequencing over 1,000 individuals. To help understand the extent to which more variants (including low frequency (1% ≤ MAF 1000 Genomes imputation, respectively, and 9 and 11 that reached a stricter, likely conservative, threshold of P1000 Genomes genotype data modestly improved the strength of known associations. Of 20 associations detected at P1000 Genomes imputed data and one was nominally more strongly associated in HapMap imputed data. We also detected an association between a low frequency variant and phenotype that was previously missed by HapMap based imputation approaches. An association between rs112635299 and alpha-1 globulin near the SERPINA gene represented the known association between rs28929474 (MAF = 0.007) and alpha1-antitrypsin that predisposes to emphysema (P = 2.5×10(-12)). Our data provide important proof of principle that 1000 Genomes imputation will detect novel, low frequency-large effect associations.

Copy Number Variations in Tilapia Genomes.

Science.gov (United States)

Li, Bi Jun; Li, Hong Lian; Meng, Zining; Zhang, Yong; Lin, Haoran; Yue, Gen Hua; Xia, Jun Hong

2017-02-01

Discovering the nature and pattern of genome variation is fundamental in understanding phenotypic diversity among populations. Although several millions of single nucleotide polymorphisms (SNPs) have been discovered in tilapia, the genome-wide characterization of larger structural variants, such as copy number variation (CNV) regions has not been carried out yet. We conducted a genome-wide scan for CNVs in 47 individuals from three tilapia populations. Based on 254 Gb of high-quality paired-end sequencing reads, we identified 4642 distinct high-confidence CNVs. These CNVs account for 1.9% (12.411 Mb) of the used Nile tilapia reference genome. A total of 1100 predicted CNVs were found overlapping with exon regions of protein genes. Further association analysis based on linear model regression found 85 CNVs ranging between 300 and 27,000 base pairs significantly associated to population types (R 2  > 0.9 and P > 0.001). Our study sheds first insights on genome-wide CNVs in tilapia. These CNVs among and within tilapia populations may have functional effects on phenotypes and specific adaptation to particular environments.

Transposable element activity, genome regulation and human health.

Science.gov (United States)

Wang, Lu; Jordan, I King

2018-03-02

A convergence of novel genome analysis technologies is enabling population genomic studies of human transposable elements (TEs). Population surveys of human genome sequences have uncovered thousands of individual TE insertions that segregate as common genetic variants, i.e. TE polymorphisms. These recent TE insertions provide an important source of naturally occurring human genetic variation. Investigators are beginning to leverage population genomic data sets to execute genome-scale association studies for assessing the phenotypic impact of human TE polymorphisms. For example, the expression quantitative trait loci (eQTL) analytical paradigm has recently been used to uncover hundreds of associations between human TE insertion variants and gene expression levels. These include population-specific gene regulatory effects as well as coordinated changes to gene regulatory networks. In addition, analyses of linkage disequilibrium patterns with previously characterized genome-wide association study (GWAS) trait variants have uncovered TE insertion polymorphisms that are likely causal variants for a variety of common complex diseases. Gene regulatory mechanisms that underlie specific disease phenotypes have been proposed for a number of these trait associated TE polymorphisms. These new population genomic approaches hold great promise for understanding how ongoing TE activity contributes to functionally relevant genetic variation within and between human populations. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Genome-Wide Association Study Primer for Clinicians

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Tzu-Hao Wang

2009-06-01

Full Text Available Genome-wide association studies (GWAS use high-throughput genotyping technology to relate hundreds of thousands of genetic markers (genotypes to clinical conditions and measurable traits (phenotypes. This review is intended to serve as an introduction to GWAS for clinicians, to allow them to better appreciate the value and limitations of GWAS for genotype-disease association studies. The input of clinicians is vital for GWAS, since disease heterogeneity is frequently a confounding factor that can only really be solved by clinicians. For diseases that are difficult to diagnose, clinicians should ensure that the cases do indeed have the disease; for common diseases, clinicians should ensure that the controls are truly disease-free.

Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization

Science.gov (United States)

Liu, Jin; Huang, Jian; Ma, Shuangge

2012-01-01

Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092

Genome-wide association study for claw disorders and trimming status in dairy cattle.

Science.gov (United States)

van der Spek, D; van Arendonk, J A M; Bovenhuis, H

2015-02-01

Performing a genome-wide association study (GWAS) might add to a better understanding of the development of claw disorders and the need for trimming. Therefore, the aim of the current study was to perform a GWAS on claw disorders and trimming status and to validate the results for claw disorders based on an independent data set. Data consisted of 20,474 cows with phenotypes for claw disorders and 50,238 cows with phenotypes for trimming status. Recorded claw disorders used in the current study were double sole (DS), interdigital hyperplasia (IH), sole hemorrhage (SH), sole ulcer (SU), white line separation (WLS), a combination of infectious claw disorders consisting of (inter-)digital dermatitis and heel erosion, and a combination of laminitis-related claw disorders (DS, SH, SU, and WLS). Of the cows with phenotypes for claw disorders, 1,771 cows were genotyped and these cow data were used for the GWAS on claw disorders. A SNP was considered significant when the false discovery rate≤0.05 and suggestive when the false discovery rate≤0.20. An independent data set of 185 genotyped bulls having at least 5 daughters with phenotypes (6,824 daughters in total) for claw disorders was used to validate significant and suggestive SNP detected based on the cow data. To analyze the trait "trimming status" (i.e., the need for claw trimming), a data set with 327 genotyped bulls having at least 5 daughters with phenotypes (18,525 daughters in total) was used. Based on the cow data, in total 10 significant and 45 suggestive SNP were detected for claw disorders. The 10 significant SNP were associated with SU, and mainly located on BTA8. The suggestive SNP were associated with DS, IH, SU, and laminitis-related claw disorders. Three of the suggestive SNP were validated in the data set of 185 bulls, and were located on BTA13, BTA14, and BTA17. For infectious claw disorders, SH, and WLS, no significant or suggestive SNP associations were detected. For trimming status, 1 significant

Family genome browser: visualizing genomes with pedigree information.

Science.gov (United States)

Juan, Liran; Liu, Yongzhuang; Wang, Yongtian; Teng, Mingxiang; Zang, Tianyi; Wang, Yadong

2015-07-15

Families with inherited diseases are widely used in Mendelian/complex disease studies. Owing to the advances in high-throughput sequencing technologies, family genome sequencing becomes more and more prevalent. Visualizing family genomes can greatly facilitate human genetics studies and personalized medicine. However, due to the complex genetic relationships and high similarities among genomes of consanguineous family members, family genomes are difficult to be visualized in traditional genome visualization framework. How to visualize the family genome variants and their functions with integrated pedigree information remains a critical challenge. We developed the Family Genome Browser (FGB) to provide comprehensive analysis and visualization for family genomes. The FGB can visualize family genomes in both individual level and variant level effectively, through integrating genome data with pedigree information. Family genome analysis, including determination of parental origin of the variants, detection of de novo mutations, identification of potential recombination events and identical-by-decent segments, etc., can be performed flexibly. Diverse annotations for the family genome variants, such as dbSNP memberships, linkage disequilibriums, genes, variant effects, potential phenotypes, etc., are illustrated as well. Moreover, the FGB can automatically search de novo mutations and compound heterozygous variants for a selected individual, and guide investigators to find high-risk genes with flexible navigation options. These features enable users to investigate and understand family genomes intuitively and systematically. The FGB is available at http://mlg.hit.edu.cn/FGB/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Functional validation of candidate genes detected by genomic feature models

DEFF Research Database (Denmark)

Rohde, Palle Duun; Østergaard, Solveig; Kristensen, Torsten Nygaard

2018-01-01

to investigate locomotor activity, and applied genomic feature prediction models to identify gene ontology (GO) cate- gories predictive of this phenotype. Next, we applied the covariance association test to partition the genomic variance of the predictive GO terms to the genes within these terms. We...... then functionally assessed whether the identified candidate genes affected locomotor activity by reducing gene expression using RNA interference. In five of the seven candidate genes tested, reduced gene expression altered the phenotype. The ranking of genes within the predictive GO term was highly correlated......Understanding the genetic underpinnings of complex traits requires knowledge of the genetic variants that contribute to phenotypic variability. Reliable statistical approaches are needed to obtain such knowledge. In genome-wide association studies, variants are tested for association with trait...

Putting the Function in Maize Genomics

Directory of Open Access Journals (Sweden)

Stephen P. Moose

2009-07-01

Full Text Available The 51st Maize Genetics Conference was held March 12–15, 2009 at Pheasant Run Resort in St. Charles, Illinois. Nearly 500 attendees participated in a scientific program (available at covering a wide range of topics which integrate the rich biology of maize with recent discoveries in our understanding of the highly dynamic maize genome. Among the many research themes highlighted at the conference, the historical emphasis on studying the tremendous phenotypic diversity of maize now serves as the foundation for maize as a leading experimental system to characterize the mechanisms that generate variation in complex plant genomes and associate evolutionary change with phenotypes of interest.

Loss of Heterozygosity at an Unlinked Genomic Locus Is Responsible for the Phenotype of a Candida albicans sap4Δ sap5Δ sap6Δ Mutant ▿

OpenAIRE

Dunkel, Nico; Morschhäuser, Joachim

2011-01-01

The diploid genome of the pathogenic yeast Candida albicans exhibits a high degree of heterozygosity. Genomic alterations that result in a loss of heterozygosity at specific loci may affect phenotypes and confer a selective advantage under certain conditions. Such genomic rearrangements can also occur during the construction of C. albicans mutants and remain undetected. The SAP2 gene on chromosome R encodes a secreted aspartic protease that is induced and required for growth of C. albicans wh...

Adaptive evolution of molecular phenotypes

International Nuclear Information System (INIS)

Held, Torsten; Nourmohammad, Armita; Lässig, Michael

2014-01-01

Molecular phenotypes link genomic information with organismic functions, fitness, and evolution. Quantitative traits are complex phenotypes that depend on multiple genomic loci. In this paper, we study the adaptive evolution of a quantitative trait under time-dependent selection, which arises from environmental changes or through fitness interactions with other co-evolving phenotypes. We analyze a model of trait evolution under mutations and genetic drift in a single-peak fitness seascape. The fitness peak performs a constrained random walk in the trait amplitude, which determines the time-dependent trait optimum in a given population. We derive analytical expressions for the distribution of the time-dependent trait divergence between populations and of the trait diversity within populations. Based on this solution, we develop a method to infer adaptive evolution of quantitative traits. Specifically, we show that the ratio of the average trait divergence and the diversity is a universal function of evolutionary time, which predicts the stabilizing strength and the driving rate of the fitness seascape. From an information-theoretic point of view, this function measures the macro-evolutionary entropy in a population ensemble, which determines the predictability of the evolutionary process. Our solution also quantifies two key characteristics of adapting populations: the cumulative fitness flux, which measures the total amount of adaptation, and the adaptive load, which is the fitness cost due to a population's lag behind the fitness peak. (paper)

Simultaneous improvement of grain yield and protein content in durum wheat by different phenotypic indices and genomic selection.

Science.gov (United States)

Rapp, M; Lein, V; Lacoudre, F; Lafferty, J; Müller, E; Vida, G; Bozhanova, V; Ibraliu, A; Thorwarth, P; Piepho, H P; Leiser, W L; Würschum, T; Longin, C F H

2018-06-01

Simultaneous improvement of protein content and grain yield by index selection is possible but its efficiency largely depends on the weighting of the single traits. The genetic architecture of these indices is similar to that of the primary traits. Grain yield and protein content are of major importance in durum wheat breeding, but their negative correlation has hampered their simultaneous improvement. To account for this in wheat breeding, the grain protein deviation (GPD) and the protein yield were proposed as targets for selection. The aim of this work was to investigate the potential of different indices to simultaneously improve grain yield and protein content in durum wheat and to evaluate their genetic architecture towards genomics-assisted breeding. To this end, we investigated two different durum wheat panels comprising 159 and 189 genotypes, which were tested in multiple field locations across Europe and genotyped by a genotyping-by-sequencing approach. The phenotypic analyses revealed significant genetic variances for all traits and heritabilities of the phenotypic indices that were in a similar range as those of grain yield and protein content. The GPD showed a high and positive correlation with protein content, whereas protein yield was highly and positively correlated with grain yield. Thus, selecting for a high GPD would mainly increase the protein content whereas a selection based on protein yield would mainly improve grain yield, but a combination of both indices allows to balance this selection. The genome-wide association mapping revealed a complex genetic architecture for all traits with most QTL having small effects and being detected only in one germplasm set, thus limiting the potential of marker-assisted selection for trait improvement. By contrast, genome-wide prediction appeared promising but its performance strongly depends on the relatedness between training and prediction sets.

The effect of waaL genes deletion from Yersinia enterocolitica O:3 genome on bacteria LPS’ phenotype

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Shevchenko J. I.

2014-11-01

Full Text Available Aim. To estimate WaaL ligase contribution in the lipopolysaccharide (LPS phenotype profile formation of Y. enterocolitica O:3 (YeO3 bacteria. Methods. The waaL-knock-out mutants were created by an allelic exchange strategy. The LPS phenotypes of created mutants were visualized by silver-stained DOC-PAGE and immunoblotting with specific outer core (core oligosaccharide, hexasaccharide, OC and O-polysaccharide (OPS or O-Ag monoclonal antibodies. Results. Deletion of waaLOS gene from YeO3 genome has a marked effect on OC ligation in either single or double mutants. The waaLPS deletion has an opposite effect on the OPS ligation – barely detected increasing of OPS bands. Conclusions. The LPS ligases of YeO3 exhibit relaxed donor substrate specificity. Under given conditions the effect of WaaLOS ligase is more significant for OC and OPS ligation onto lipid A than that of WaaLPS.

Genome-wide association study identifies 74 loci associated with educational attainment

DEFF Research Database (Denmark)

Okbay, Aysu; P. Beauchamp, Jonathan; Alan Fontana, Mark

2016-01-01

-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural......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 individuals1. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends...... development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals...

Convergent evolution of the genomes of marine mammals

Science.gov (United States)

Foote, Andrew D.; Liu, Yue; Thomas, Gregg W.C.; Vinař, Tomáš; Alföldi, Jessica; Deng, Jixin; Dugan, Shannon; van Elk, Cornelis E.; Hunter, Margaret; Joshi, Vandita; Khan, Ziad; Kovar, Christie; Lee, Sandra L.; Lindblad-Toh, Kerstin; Mancia, Annalaura; Nielsen, Rasmus; Qin, Xiang; Qu, Jiaxin; Raney, Brian J.; Vijay, Nagarjun; Wolf, Jochen B. W.; Hahn, Matthew W.; Muzny, Donna M.; Worley, Kim C.; Gilbert, M. Thomas P.; Gibbs, Richard A.

2015-01-01

Marine mammals from different mammalian orders share several phenotypic traits adapted to the aquatic environment and therefore represent a classic example of convergent evolution. To investigate convergent evolution at the genomic level, we sequenced and performed de novo assembly of the genomes of three species of marine mammals (the killer whale, walrus and manatee) from three mammalian orders that share independently evolved phenotypic adaptations to a marine existence. Our comparative genomic analyses found that convergent amino acid substitutions were widespread throughout the genome and that a subset of these substitutions were in genes evolving under positive selection and putatively associated with a marine phenotype. However, we found higher levels of convergent amino acid substitutions in a control set of terrestrial sister taxa to the marine mammals. Our results suggest that, whereas convergent molecular evolution is relatively common, adaptive molecular convergence linked to phenotypic convergence is comparatively rare.

GWAMA: software for genome-wide association meta-analysis

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Mägi Reedik

2010-05-01

Full Text Available Abstract Background Despite the recent success of genome-wide association studies in identifying novel loci contributing effects to complex human traits, such as type 2 diabetes and obesity, much of the genetic component of variation in these phenotypes remains unexplained. One way to improving power to detect further novel loci is through meta-analysis of studies from the same population, increasing the sample size over any individual study. Although statistical software analysis packages incorporate routines for meta-analysis, they are ill equipped to meet the challenges of the scale and complexity of data generated in genome-wide association studies. Results We have developed flexible, open-source software for the meta-analysis of genome-wide association studies. The software incorporates a variety of error trapping facilities, and provides a range of meta-analysis summary statistics. The software is distributed with scripts that allow simple formatting of files containing the results of each association study and generate graphical summaries of genome-wide meta-analysis results. Conclusions The GWAMA (Genome-Wide Association Meta-Analysis software has been developed to perform meta-analysis of summary statistics generated from genome-wide association studies of dichotomous phenotypes or quantitative traits. Software with source files, documentation and example data files are freely available online at http://www.well.ox.ac.uk/GWAMA.

An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice

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Liu Lili

2013-06-01

Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

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Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

2017-07-01

High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

Genome plasticity and systems evolution in Streptomyces

Science.gov (United States)

2012-01-01

Background Streptomycetes are filamentous soil-dwelling bacteria. They are best known as the producers of a great variety of natural products such as antibiotics, antifungals, antiparasitics, and anticancer agents and the decomposers of organic substances for carbon recycling. They are also model organisms for the studies of gene regulatory networks, morphological differentiation, and stress response. The availability of sets of genomes from closely related Streptomyces strains makes it possible to assess the mechanisms underlying genome plasticity and systems adaptation. Results We present the results of a comprehensive analysis of the genomes of five Streptomyces species with distinct phenotypes. These streptomycetes have a pan-genome comprised of 17,362 orthologous families which includes 3,096 components in the core genome, 5,066 components in the dispensable genome, and 9,200 components that are uniquely present in only one species. The core genome makes up about 33%-45% of each genome repertoire. It contains important genes for Streptomyces biology including those involved in gene regulation, secretion, secondary metabolism and morphological differentiation. Abundant duplicate genes have been identified, with 4%-11% of the whole genomes composed of lineage-specific expansions (LSEs), suggesting that frequent gene duplication or lateral gene transfer events play a role in shaping the genome diversification within this genus. Two patterns of expansion, single gene expansion and chromosome block expansion are observed, representing different scales of duplication. Conclusions Our results provide a catalog of genome components and their potential functional roles in gene regulatory networks and metabolic networks. The core genome components reveal the minimum requirement for streptomycetes to sustain a successful lifecycle in the soil environment, reflecting the effects of both genome evolution and environmental stress acting upon the expressed phenotypes. A

Phenotypic, molecular characterization, antimicrobial susceptibility and draft genome sequence of Corynebacterium argentoratense strains isolated from clinical samples

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I. Fernández-Natal

2016-03-01

Full Text Available During a 12-year period we isolated five Corynebacterium argentoratense strains identified by phenotypic methods, including the use of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF and 16S rRNA gene sequencing. In addition, antimicrobial susceptibility was determined, and genome sequencing for the detection of antibiotic resistance genes was performed. The organisms were isolated from blood and throat cultures and could be identified by all methods used. All strains were resistant to cotrimoxazole, and resistance to β-lactams was partly present. Two strains were resistant to erythromycin and clindamycin. The draft genome sequences of theses isolates revealed the presence of the erm(X resistance gene that is embedded in the genetic structure of the transposable element Tn5423. Although rarely reported as a human pathogen, C. argentoratense can be involved in bacteraemia and probably in other infections. Our results also show that horizontal transfer of genes responsible for antibiotic resistance is occurring in this species.

Genomic Comparative Study of Bovine Mastitis Escherichia coli.

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Kempf, Florent; Slugocki, Cindy; Blum, Shlomo E; Leitner, Gabriel; Germon, Pierre

2016-01-01

Escherichia coli, one of the main causative agents of bovine mastitis, is responsible for significant losses on dairy farms. In order to better understand the pathogenicity of E. coli mastitis, an accurate characterization of E. coli strains isolated from mastitis cases is required. By using phylogenetic analyses and whole genome comparison of 5 currently available mastitis E. coli genome sequences, we searched for genotypic traits specific for mastitis isolates. Our data confirm that there is a bias in the distribution of mastitis isolates in the different phylogenetic groups of the E. coli species, with the majority of strains belonging to phylogenetic groups A and B1. An interesting feature is that clustering of strains based on their accessory genome is very similar to that obtained using the core genome. This finding illustrates the fact that phenotypic properties of strains from different phylogroups are likely to be different. As a consequence, it is possible that different strategies could be used by mastitis isolates of different phylogroups to trigger mastitis. Our results indicate that mastitis E. coli isolates analyzed in this study carry very few of the virulence genes described in other pathogenic E. coli strains. A more detailed analysis of the presence/absence of genes involved in LPS synthesis, iron acquisition and type 6 secretion systems did not uncover specific properties of mastitis isolates. Altogether, these results indicate that mastitis E. coli isolates are rather characterized by a lack of bona fide currently described virulence genes.

Personal genomics services: whose genomes?

Science.gov (United States)

Gurwitz, David; Bregman-Eschet, Yael

2009-07-01

New companies offering personal whole-genome information services over the internet are dynamic and highly visible players in the personal genomics field. For fees currently ranging from US$399 to US$2500 and a vial of saliva, individuals can now purchase online access to their individual genetic information regarding susceptibility to a range of chronic diseases and phenotypic traits based on a genome-wide SNP scan. Most of the companies offering such services are based in the United States, but their clients may come from nearly anywhere in the world. Although the scientific validity, clinical utility and potential future implications of such services are being hotly debated, several ethical and regulatory questions related to direct-to-consumer (DTC) marketing strategies of genetic tests have not yet received sufficient attention. For example, how can we minimize the risk of unauthorized third parties from submitting other people's DNA for testing? Another pressing question concerns the ownership of (genotypic and phenotypic) information, as well as the unclear legal status of customers regarding their own personal information. Current legislation in the US and Europe falls short of providing clear answers to these questions. Until the regulation of personal genomics services catches up with the technology, we call upon commercial providers to self-regulate and coordinate their activities to minimize potential risks to individual privacy. We also point out some specific steps, along the trustee model, that providers of DTC personal genomics services as well as regulators and policy makers could consider for addressing some of the concerns raised below.

Genome-Wide Association Studies and Comparison of Models and Cross-Validation Strategies for Genomic Prediction of Quality Traits in Advanced Winter Wheat Breeding Lines

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Peter S. Kristensen

2018-02-01

Full Text Available The aim of the this study was to identify SNP markers associated with five important wheat quality traits (grain protein content, Zeleny sedimentation, test weight, thousand-kernel weight, and falling number, and to investigate the predictive abilities of GBLUP and Bayesian Power Lasso models for genomic prediction of these traits. In total, 635 winter wheat lines from two breeding cycles in the Danish plant breeding company Nordic Seed A/S were phenotyped for the quality traits and genotyped for 10,802 SNPs. GWAS were performed using single marker regression and Bayesian Power Lasso models. SNPs with large effects on Zeleny sedimentation were found on chromosome 1B, 1D, and 5D. However, GWAS failed to identify single SNPs with significant effects on the other traits, indicating that these traits were controlled by many QTL with small effects. The predictive abilities of the models for genomic prediction were studied using different cross-validation strategies. Leave-One-Out cross-validations resulted in correlations between observed phenotypes corrected for fixed effects and genomic estimated breeding values of 0.50 for grain protein content, 0.66 for thousand-kernel weight, 0.70 for falling number, 0.71 for test weight, and 0.79 for Zeleny sedimentation. Alternative cross-validations showed that the genetic relationship between lines in training and validation sets had a bigger impact on predictive abilities than the number of lines included in the training set. Using Bayesian Power Lasso instead of GBLUP models, gave similar or slightly higher predictive abilities. Genomic prediction based on all SNPs was more effective than prediction based on few associated SNPs.

Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults.

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Fang Chen

Full Text Available Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419, we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010, and estimated an additive heritability of 44.7% (se: 3.7% for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1 whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2 whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the

Application of Genomic Tools in Plant Breeding

OpenAIRE

Pérez-de-Castro, A.M.; Vilanova, S.; Cañizares, J.; Pascual, L.; Blanca, J.M.; Díez, M.J.; Prohens, J.; Picó, B.

2012-01-01

Plant breeding has been very successful in developing improved varieties using conventional tools and methodologies. Nowadays, the availability of genomic tools and resources is leading to a new revolution of plant breeding, as they facilitate the study of the genotype and its relationship with the phenotype, in particular for complex traits. Next Generation Sequencing (NGS) technologies are allowing the mass sequencing of genomes and transcriptomes, which is producing a vast array of genomic...

FGWAS: Functional genome wide association analysis.

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Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-10-01

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.

Sandwich corrected standard errors in family-based genome-wide association studies

NARCIS (Netherlands)

Minica, C.C.; Dolan, C.V.; Kampert, M.M.D.; Boomsma, D.I.; Vink, J.M.

2015-01-01

Given the availability of genotype and phenotype data collected in family members, the question arises which estimator ensures the most optimal use of such data in genome-wide scans. Using simulations, we compared the Unweighted Least Squares (ULS) and Maximum Likelihood (ML) procedures. The former

The Arab genome: Health and wealth.

Science.gov (United States)

Zayed, Hatem

2016-11-05

The 22 Arab nations have a unique genetic structure, which reflects both conserved and diverse gene pools due to the prevalent endogamous and consanguineous marriage culture and the long history of admixture among different ethnic subcultures descended from the Asian, European, and African continents. Human genome sequencing has enabled large-scale genomic studies of different populations and has become a powerful tool for studying disease predictions and diagnosis. Despite the importance of the Arab genome for better understanding the dynamics of the human genome, discovering rare genetic variations, and studying early human migration out of Africa, it is poorly represented in human genome databases, such as HapMap and the 1000 Genomes Project. In this review, I demonstrate the significance of sequencing the Arab genome and setting an Arab genome reference(s) for better understanding the molecular pathogenesis of genetic diseases, discovering novel/rare variants, and identifying a meaningful genotype-phenotype correlation for complex diseases. Copyright © 2016. Published by Elsevier B.V.

a potential source of spurious associations in genome-wide ...

Indian Academy of Sciences (India)

2010-04-01

Apr 1, 2010 ... Genome-wide association studies (GWAS) examine the entire human genome with the goal of identifying genetic variants. (usually single nucleotide polymorphisms (SNPs)) that are associated with phenotypic traits such as disease status and drug response. The discordance of significantly associated ...

Deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data

NARCIS (Netherlands)

Mobegi, Fredrick M; Cremers, Amelieke J H; de Jonge, Marien I; Bentley, Stephen D; van Hijum, Sacha A F T; Zomer, Aldert|info:eu-repo/dai/nl/304642754

2017-01-01

Advances in genome sequencing technologies and genome-wide association studies (GWAS) have provided unprecedented insights into the molecular basis of microbial phenotypes and enabled the identification of the underlying genetic variants in real populations. However, utilization of genome sequencing

Genomic Prediction of Manganese Efficiency in Winter Barley

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Florian Leplat

2016-07-01

Full Text Available Manganese efficiency is a quantitative abiotic stress trait controlled by several genes each with a small effect. Manganese deficiency leads to yield reduction in winter barley ( L.. Breeding new cultivars for this trait remains difficult because of the lack of visual symptoms and the polygenic features of the trait. Hence, Mn efficiency is a potential suitable trait for a genomic selection (GS approach. A collection of 248 winter barley varieties was screened for Mn efficiency using Chlorophyll (Chl fluorescence in six environments prone to induce Mn deficiency. Two models for genomic prediction were implemented to predict future performance and breeding value of untested varieties. Predictions were obtained using multivariate mixed models: best linear unbiased predictor (BLUP and genomic best linear unbiased predictor (G-BLUP. In the first model, predictions were based on the phenotypic evaluation, whereas both phenotypic and genomic marker data were included in the second model. Accuracy of predicting future phenotype, , and accuracy of predicting true breeding values, , were calculated and compared for both models using six cross-validation (CV schemes; these were designed to mimic plant breeding programs. Overall, the CVs showed that prediction accuracies increased when using the G-BLUP model compared with the prediction accuracies using the BLUP model. Furthermore, the accuracies [] of predicting breeding values were more accurate than accuracy of predicting future phenotypes []. The study confirms that genomic data may enhance the prediction accuracy. Moreover it indicates that GS is a suitable breeding approach for quantitative abiotic stress traits.

The genetic basis of alcoholism: multiple phenotypes, many genes, complex networks

Science.gov (United States)

2012-01-01

Alcoholism is a significant public health problem. A picture of the genetic architecture underlying alcohol-related phenotypes is emerging from genome-wide association studies and work on genetically tractable model organisms. PMID:22348705

Toward integration of genomic selection with crop modelling: the development of an integrated approach to predicting rice heading dates.

Science.gov (United States)

Onogi, Akio; Watanabe, Maya; Mochizuki, Toshihiro; Hayashi, Takeshi; Nakagawa, Hiroshi; Hasegawa, Toshihiro; Iwata, Hiroyoshi

2016-04-01

It is suggested that accuracy in predicting plant phenotypes can be improved by integrating genomic prediction with crop modelling in a single hierarchical model. Accurate prediction of phenotypes is important for plant breeding and management. Although genomic prediction/selection aims to predict phenotypes on the basis of whole-genome marker information, it is often difficult to predict phenotypes of complex traits in diverse environments, because plant phenotypes are often influenced by genotype-environment interaction. A possible remedy is to integrate genomic prediction with crop/ecophysiological modelling, which enables us to predict plant phenotypes using environmental and management information. To this end, in the present study, we developed a novel method for integrating genomic prediction with phenological modelling of Asian rice (Oryza sativa, L.), allowing the heading date of untested genotypes in untested environments to be predicted. The method simultaneously infers the phenological model parameters and whole-genome marker effects on the parameters in a Bayesian framework. By cultivating backcross inbred lines of Koshihikari × Kasalath in nine environments, we evaluated the potential of the proposed method in comparison with conventional genomic prediction, phenological modelling, and two-step methods that applied genomic prediction to phenological model parameters inferred from Nelder-Mead or Markov chain Monte Carlo algorithms. In predicting heading dates of untested lines in untested environments, the proposed and two-step methods tended to provide more accurate predictions than the conventional genomic prediction methods, particularly in environments where phenotypes from environments similar to the target environment were unavailable for training genomic prediction. The proposed method showed greater accuracy in prediction than the two-step methods in all cross-validation schemes tested, suggesting the potential of the integrated approach in

Delineation of C12orf65-related phenotypes: a genotype-phenotype relationship.

Science.gov (United States)

Spiegel, Ronen; Mandel, Hanna; Saada, Ann; Lerer, Issy; Burger, Ayala; Shaag, Avraham; Shalev, Stavit A; Jabaly-Habib, Haneen; Goldsher, Dorit; Gomori, John M; Lossos, Alex; Elpeleg, Orly; Meiner, Vardiella

2014-08-01

C12orf65 participates in the process of mitochondrial translation and has been shown to be associated with a spectrum of phenotypes, including early onset optic atrophy, progressive encephalomyopathy, peripheral neuropathy, and spastic paraparesis.We used whole-genome homozygosity mapping as well as exome sequencing and targeted gene sequencing to identify novel C12orf65 disease-causing mutations in seven affected individuals originating from two consanguineous families. In four family members affected with childhood-onset optic atrophy accompanied by slowly progressive peripheral neuropathy and spastic paraparesis, we identified a homozygous frame shift mutation c.413_417 delAACAA, which predicts a truncated protein lacking the C-terminal portion. In the second family, we studied three affected individuals who presented with early onset optic atrophy, peripheral neuropathy, and spastic gait in addition to moderate intellectual disability. Muscle biopsy in two of the patients revealed decreased activities of the mitochondrial respiratory chain complexes I and IV. In these patients, we identified a homozygous splice mutation, g.21043 T>A (c.282+2 T>A) which leads to skipping of exon 2. Our study broadens the phenotypic spectrum of C12orf65 defects and highlights the triad of optic atrophy, axonal neuropathy and spastic paraparesis as its key clinical features. In addition, a clear genotype-phenotype correlation is anticipated in which deleterious mutations which disrupt the GGQ-containing domain in the first coding exon are expected to result in a more severe phenotype, whereas down-stream C-terminal mutations may result in a more favorable phenotype, typically lacking cognitive impairment.

Population genomics of parallel adaptation in threespine stickleback using sequenced RAD tags.

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Paul A Hohenlohe

2010-02-01

Full Text Available Next-generation sequencing technology provides novel opportunities for gathering genome-scale sequence data in natural populations, laying the empirical foundation for the evolving field of population genomics. Here we conducted a genome scan of nucleotide diversity and differentiation in natural populations of threespine stickleback (Gasterosteus aculeatus. We used Illumina-sequenced RAD tags to identify and type over 45,000 single nucleotide polymorphisms (SNPs in each of 100 individuals from two oceanic and three freshwater populations. Overall estimates of genetic diversity and differentiation among populations confirm the biogeographic hypothesis that large panmictic oceanic populations have repeatedly given rise to phenotypically divergent freshwater populations. Genomic regions exhibiting signatures of both balancing and divergent selection were remarkably consistent across multiple, independently derived populations, indicating that replicate parallel phenotypic evolution in stickleback may be occurring through extensive, parallel genetic evolution at a genome-wide scale. Some of these genomic regions co-localize with previously identified QTL for stickleback phenotypic variation identified using laboratory mapping crosses. In addition, we have identified several novel regions showing parallel differentiation across independent populations. Annotation of these regions revealed numerous genes that are candidates for stickleback phenotypic evolution and will form the basis of future genetic analyses in this and other organisms. This study represents the first high-density SNP-based genome scan of genetic diversity and differentiation for populations of threespine stickleback in the wild. These data illustrate the complementary nature of laboratory crosses and population genomic scans by confirming the adaptive significance of previously identified genomic regions, elucidating the particular evolutionary and demographic history of such

From genomes to in silico cells via metabolic networks

DEFF Research Database (Denmark)

Borodina, Irina; Nielsen, Jens

2005-01-01

Genome-scale metabolic models are the focal point of systems biology as they allow the collection of various data types in a form suitable for mathematical analysis. High-quality metabolic networks and metabolic networks with incorporated regulation have been successfully used for the analysis...... of phenotypes from phenotypic arrays and in gene-deletion studies. They have also been used for gene expression analysis guided by metabolic network structure, leading to the identification of commonly regulated genes. Thus, genome-scale metabolic modeling currently stands out as one of the most promising...

Exploring causal networks underlying fat deposition and muscularity in pigs through the integration of phenotypic, genotypic and transcriptomic data.

Science.gov (United States)

Peñagaricano, Francisco; Valente, Bruno D; Steibel, Juan P; Bates, Ronald O; Ernst, Catherine W; Khatib, Hasan; Rosa, Guilherme J M

2015-09-16

Joint modeling and analysis of phenotypic, genotypic and transcriptomic data have the potential to uncover the genetic control of gene activity and phenotypic variation, as well as shed light on the manner and extent of connectedness among these variables. Current studies mainly report associations, i.e. undirected connections among variables without causal interpretation. Knowledge regarding causal relationships among genes and phenotypes can be used to predict the behavior of complex systems, as well as to optimize management practices and selection strategies. Here, we performed a multistep procedure for inferring causal networks underlying carcass fat deposition and muscularity in pigs using multi-omics data obtained from an F2 Duroc x Pietrain resource pig population. We initially explored marginal associations between genotypes and phenotypic and expression traits through whole-genome scans, and then, in genomic regions with multiple significant hits, we assessed gene-phenotype network reconstruction using causal structural learning algorithms. One genomic region on SSC6 showed significant associations with three relevant phenotypes, off-midline10th-rib backfat thickness, loin muscle weight, and average intramuscular fat percentage, and also with the expression of seven genes, including ZNF24, SSX2IP, and AKR7A2. The inferred network indicated that the genotype affects the three phenotypes mainly through the expression of several genes. Among the phenotypes, fat deposition traits negatively affected loin muscle weight. Our findings shed light on the antagonist relationship between carcass fat deposition and lean meat content in pigs. In addition, the procedure described in this study has the potential to unravel gene-phenotype networks underlying complex phenotypes.

Imaging-genomics reveals driving pathways of MRI derived volumetric tumor phenotype features in Glioblastoma

International Nuclear Information System (INIS)

Grossmann, Patrick; Gutman, David A.; Dunn, William D. Jr; Holder, Chad A.; Aerts, Hugo J. W. L.

2016-01-01

Glioblastoma (GBM) tumors exhibit strong phenotypic differences that can be quantified using magnetic resonance imaging (MRI), but the underlying biological drivers of these imaging phenotypes remain largely unknown. An Imaging-Genomics analysis was performed to reveal the mechanistic associations between MRI derived quantitative volumetric tumor phenotype features and molecular pathways. One hundred fourty one patients with presurgery MRI and survival data were included in our analysis. Volumetric features were defined, including the necrotic core (NE), contrast-enhancement (CE), abnormal tumor volume assessed by post-contrast T1w (tumor bulk or TB), tumor-associated edema based on T2-FLAIR (ED), and total tumor volume (TV), as well as ratios of these tumor components. Based on gene expression where available (n = 91), pathway associations were assessed using a preranked gene set enrichment analysis. These results were put into context of molecular subtypes in GBM and prognostication. Volumetric features were significantly associated with diverse sets of biological processes (FDR < 0.05). While NE and TB were enriched for immune response pathways and apoptosis, CE was associated with signal transduction and protein folding processes. ED was mainly enriched for homeostasis and cell cycling pathways. ED was also the strongest predictor of molecular GBM subtypes (AUC = 0.61). CE was the strongest predictor of overall survival (C-index = 0.6; Noether test, p = 4x10 −4 ). GBM volumetric features extracted from MRI are significantly enriched for information about the biological state of a tumor that impacts patient outcomes. Clinical decision-support systems could exploit this information to develop personalized treatment strategies on the basis of noninvasive imaging. The online version of this article (doi:10.1186/s12885-016-2659-5) contains supplementary material, which is available to authorized users

An efficient Bayesian meta-analysis approach for studying cross-phenotype genetic associations.

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Arunabha Majumdar

2018-02-01

Full Text Available Simultaneous analysis of genetic associations with multiple phenotypes may reveal shared genetic susceptibility across traits (pleiotropy. For a locus exhibiting overall pleiotropy, it is important to identify which specific traits underlie this association. We propose a Bayesian meta-analysis approach (termed CPBayes that uses summary-level data across multiple phenotypes to simultaneously measure the evidence of aggregate-level pleiotropic association and estimate an optimal subset of traits associated with the risk locus. This method uses a unified Bayesian statistical framework based on a spike and slab prior. CPBayes performs a fully Bayesian analysis by employing the Markov Chain Monte Carlo (MCMC technique Gibbs sampling. It takes into account heterogeneity in the size and direction of the genetic effects across traits. It can be applied to both cohort data and separate studies of multiple traits having overlapping or non-overlapping subjects. Simulations show that CPBayes can produce higher accuracy in the selection of associated traits underlying a pleiotropic signal than the subset-based meta-analysis ASSET. We used CPBayes to undertake a genome-wide pleiotropic association study of 22 traits in the large Kaiser GERA cohort and detected six independent pleiotropic loci associated with at least two phenotypes. This includes a locus at chromosomal region 1q24.2 which exhibits an association simultaneously with the risk of five different diseases: Dermatophytosis, Hemorrhoids, Iron Deficiency, Osteoporosis and Peripheral Vascular Disease. We provide an R-package 'CPBayes' implementing the proposed method.

Microenvironment-dependent phenotypic changes in a SCID mouse model for malignant mesothelioma

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Eva eDarai-Ramqvist

2013-08-01

Full Text Available Background and Aims: Malignant mesothelioma is an aggressive, therapy-resistant tumor. Mesothelioma cells may assume an epithelioid or a sarcomatoid phenotype, and presence of sarcomatoid cells predicts poor prognosis. In this study, we investigated differentiation of mesothelioma cells in a xenograft model, where mesothelioma cells of both phenotypes were induced to form tumors in SCID mice. Methods: Xenografts were established and thoroughly characterized using a comprehensive immunohistochemical panel, array comparative genomic hybridization of chromosome 3, fluorescent in situ hybridization and electron microscopy.Results: Epithelioid and sarcomatoid cells gave rise to xenografts of similar epithelioid morphology. While sarcomatoid-derived xenografts had higher growth rates, the morphology and expression of differentiation-related markers was similar between xenografts derived from both phenotypes. Array comparative genomic hybridization showed a convergent genotype for both xenografts, resembling the original aggressive sarcomatoid cell sub-line.Conclusions: Human mesothelioma xenografts from sarcomatoid and epithelioid phenotypes converged to a similar differentiation state, and genetic analyses suggested that clonal selection in the mouse microenvironment was a major contributing factor. This thoroughly characterized animal model can be used for further studies of molecular events underlying tumor cell differentiation.

The Qatar genome project: translation of whole-genome sequencing into clinical practice.

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Zayed, Hatem

2016-10-01

Qatar Genome Project was launched in 2013 with the intent to sequence the genome of each Qatari citizen in an effort to protect Qataris from the high rate of indigenous genetic diseases by allowing the mapping of disease-causing variants/rare variants and establishing a Qatari reference genome. Indeed, this project is expected to have numerous global benefits because the elevated homogeneity of the Qatari population, that will make Qatar an excellent genetic laboratory that will generate a wealth of data that will allow us to make sense of the genotype-phenotype correlations of many diseases, especially the complex multifactorial diseases, and will pave the way for changing the traditional medical practice of looking first at the phenotype rather than the genotype. © 2016 John Wiley & Sons Ltd.

Reporting of Human Genome Epidemiology (HuGE association studies: An empirical assessment

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Gwinn Marta

2008-05-01

Full Text Available Abstract Background Several thousand human genome epidemiology association studies are published every year investigating the relationship between common genetic variants and diverse phenotypes. Transparent reporting of study methods and results allows readers to better assess the validity of study findings. Here, we document reporting practices of human genome epidemiology studies. Methods Articles were randomly selected from a continuously updated database of human genome epidemiology association studies to be representative of genetic epidemiology literature. The main analysis evaluated 315 articles published in 2001–2003. For a comparative update, we evaluated 28 more recent articles published in 2006, focusing on issues that were poorly reported in 2001–2003. Results During both time periods, most studies comprised relatively small study populations and examined one or more genetic variants within a single gene. Articles were inconsistent in reporting the data needed to assess selection bias and the methods used to minimize misclassification (of the genotype, outcome, and environmental exposure or to identify population stratification. Statistical power, the use of unrelated study participants, and the use of replicate samples were reported more often in articles published during 2006 when compared with the earlier sample. Conclusion We conclude that many items needed to assess error and bias in human genome epidemiology association studies are not consistently reported. Although some improvements were seen over time, reporting guidelines and online supplemental material may help enhance the transparency of this literature.

The Mouse Genome Database (MGD): facilitating mouse as a model for human biology and disease.

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Eppig, Janan T; Blake, Judith A; Bult, Carol J; Kadin, James A; Richardson, Joel E

2015-01-01

The Mouse Genome Database (MGD, http://www.informatics.jax.org) serves the international biomedical research community as the central resource for integrated genomic, genetic and biological data on the laboratory mouse. To facilitate use of mouse as a model in translational studies, MGD maintains a core of high-quality curated data and integrates experimentally and computationally generated data sets. MGD maintains a unified catalog of genes and genome features, including functional RNAs, QTL and phenotypic loci. MGD curates and provides functional and phenotype annotations for mouse genes using the Gene Ontology and Mammalian Phenotype Ontology. MGD integrates phenotype data and associates mouse genotypes to human diseases, providing critical mouse-human relationships and access to repositories holding mouse models. MGD is the authoritative source of nomenclature for genes, genome features, alleles and strains following guidelines of the International Committee on Standardized Genetic Nomenclature for Mice. A new addition to MGD, the Human-Mouse: Disease Connection, allows users to explore gene-phenotype-disease relationships between human and mouse. MGD has also updated search paradigms for phenotypic allele attributes, incorporated incidental mutation data, added a module for display and exploration of genes and microRNA interactions and adopted the JBrowse genome browser. MGD resources are freely available to the scientific community. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Confluence of genes, environment, development, and behavior in a post Genome-Wide Association Study world.

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Vrieze, Scott I; Iacono, William G; McGue, Matt

2012-11-01

This article serves to outline a research paradigm to investigate main effects and interactions of genes, environment, and development on behavior and psychiatric illness. We provide a historical context for candidate gene studies and genome-wide association studies, including benefits, limitations, and expected payoffs. Using substance use and abuse as our driving example, we then turn to the importance of etiological psychological theory in guiding genetic, environmental, and developmental research, as well as the utility of refined phenotypic measures, such as endophenotypes, in the pursuit of etiological understanding and focused tests of genetic and environmental associations. Phenotypic measurement has received considerable attention in the history of psychology and is informed by psychometrics, whereas the environment remains relatively poorly measured and is often confounded with genetic effects (i.e., gene-environment correlation). Genetically informed designs, which are no longer limited to twin and adoption studies thanks to ever-cheaper genotyping, are required to understand environmental influences. Finally, we outline the vast amount of individual difference in structural genomic variation, most of which remains to be leveraged in genetic association tests. Although the genetic data can be massive and burdensome (tens of millions of variants per person), we argue that improved understanding of genomic structure and function will provide investigators with new tools to test specific a priori hypotheses derived from etiological psychological theory, much like current candidate gene research but with less confusion and more payoff than candidate gene research has to date.

Accelerating the Switchgrass (Panicum virgatum L.) Breeding Cycle Using Genomic Selection Approaches

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Lipka, Alexander E.; Lu, Fei; Cherney, Jerome H.; Buckler, Edward S.; Casler, Michael D.; Costich, Denise E.

2014-01-01

Switchgrass (Panicum virgatum L.) is a perennial grass undergoing development as a biofuel feedstock. One of the most important factors hindering breeding efforts in this species is the need for accurate measurement of biomass yield on a per-hectare basis. Genomic selection on simple-to-measure traits that approximate biomass yield has the potential to significantly speed up the breeding cycle. Recent advances in switchgrass genomic and phenotypic resources are now making it possible to evaluate the potential of genomic selection of such traits. We leveraged these resources to study the ability of three widely-used genomic selection models to predict phenotypic values of morphological and biomass quality traits in an association panel consisting of predominantly northern adapted upland germplasm. High prediction accuracies were obtained for most of the traits, with standability having the highest ten-fold cross validation prediction accuracy (0.52). Moreover, the morphological traits generally had higher prediction accuracies than the biomass quality traits. Nevertheless, our results suggest that the quality of current genomic and phenotypic resources available for switchgrass is sufficiently high for genomic selection to significantly impact breeding efforts for biomass yield. PMID:25390940

Phenotype variations affect genetic association studies of degenerative disc disease: conclusions of analysis of genetic association of 58 single nucleotide polymorphisms with highly specific phenotypes for disc degeneration in 332 subjects.

Science.gov (United States)

Rajasekaran, S; Kanna, Rishi Mugesh; Senthil, Natesan; Raveendran, Muthuraja; Cheung, Kenneth M C; Chan, Danny; Subramaniam, Sakthikanal; Shetty, Ajoy Prasad

2013-10-01

Although the influence of genetics on the process of disc degeneration is well recognized, in recently published studies, there is a wide variation in the race and selection criteria for such study populations. More importantly, the radiographic features of disc degeneration that are selected to represent the disc degeneration phenotype are variable in these studies. The study presented here evaluates the association between single nucleotide polymorphisms (SNPs) of candidate genes and three distinct radiographic features that can be defined as the degenerative disc disease (DDD) phenotype. The study objectives were to examine the allelic diversity of 58 SNPs related to 35 candidate genes related to lumbar DDD, to evaluate the association in a hitherto unevaluated ethnic Indian population that represents more than one-sixth of the world population, and to analyze how genetic associations can vary in the same study subjects with the choice of phenotype. A cross-sectional, case-control study of an ethnic Indian population was carried out. Fifty-eight SNPs in 35 potential candidate genes were evaluated in 342 subjects and the associations were analyzed against three highly specific markers for DDD, namely disc degeneration by Pfirrmann grading, end-plate damage evaluated by total end-plate damage score, and annular tears evaluated by disc herniations and hyperintense zones. Genotyping of cases and controls was performed on a genome-wide SNP array to identify potential associated disease loci. The results from the genome-wide SNP array were then used to facilitate SNP selection and genotype validation was conducted using Sequenom-based genotyping. Eleven of the 58 SNPs provided evidence of association with one of the phenotypes. For annular tears, rs1042631 SNP of AGC1 and rs467691 SNP of ADAMTS5 were highly significantly associated (p<.01) and SNPs in NGFB, IL1B, IL18RAP, and MMP10 were also significantly associated (p<.05). The rs4076018 SNP of NGFB was highly

New genes as drivers of phenotypic evolution

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Chen, Sidi; Krinsky, Benjamin H.; Long, Manyuan

2014-01-01

During the course of evolution, genomes acquire novel genetic elements as sources of functional and phenotypic diversity, including new genes that originated in recent evolution. In the past few years, substantial progress has been made in understanding the evolution and phenotypic effects of new genes. In particular, an emerging picture is that new genes, despite being present in the genomes of only a subset of species, can rapidly evolve indispensable roles in fundamental biological processes, including development, reproduction, brain function and behaviour. The molecular underpinnings of how new genes can develop these roles are starting to be characterized. These recent discoveries yield fresh insights into our broad understanding of biological diversity at refined resolution. PMID:23949544

The Human Phenotype Ontology in 2017

International Nuclear Information System (INIS)

Köhler, Sebastian; Vasilevsky, Nicole A.; Engelstad, Mark; Foster, Erin; McMurry, Julie

2016-01-01

Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human PhenotypeOntology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology.

Comparative genome analysis of Bacillus cereus group genomes withBacillus subtilis

Energy Technology Data Exchange (ETDEWEB)

Anderson, Iain; Sorokin, Alexei; Kapatral, Vinayak; Reznik, Gary; Bhattacharya, Anamitra; Mikhailova, Natalia; Burd, Henry; Joukov, Victor; Kaznadzey, Denis; Walunas, Theresa; D' Souza, Mark; Larsen, Niels; Pusch,Gordon; Liolios, Konstantinos; Grechkin, Yuri; Lapidus, Alla; Goltsman,Eugene; Chu, Lien; Fonstein, Michael; Ehrlich, S. Dusko; Overbeek, Ross; Kyrpides, Nikos; Ivanova, Natalia

2005-09-14

Genome features of the Bacillus cereus group genomes (representative strains of Bacillus cereus, Bacillus anthracis and Bacillus thuringiensis sub spp israelensis) were analyzed and compared with the Bacillus subtilis genome. A core set of 1,381 protein families among the four Bacillus genomes, with an additional set of 933 families common to the B. cereus group, was identified. Differences in signal transduction pathways, membrane transporters, cell surface structures, cell wall, and S-layer proteins suggesting differences in their phenotype were identified. The B. cereus group has signal transduction systems including a tyrosine kinase related to two-component system histidine kinases from B. subtilis. A model for regulation of the stress responsive sigma factor sigmaB in the B. cereus group different from the well studied regulation in B. subtilis has been proposed. Despite a high degree of chromosomal synteny among these genomes, significant differences in cell wall and spore coat proteins that contribute to the survival and adaptation in specific hosts has been identified.

Cow genotyping strategies for genomic selection in a small dairy cattle population.

Science.gov (United States)

Jenko, J; Wiggans, G R; Cooper, T A; Eaglen, S A E; Luff, W G de L; Bichard, M; Pong-Wong, R; Woolliams, J A

2017-01-01

This study compares how different cow genotyping strategies increase the accuracy of genomic estimated breeding values (EBV) in dairy cattle breeds with low numbers. In these breeds, few sires have progeny records, and genotyping cows can improve the accuracy of genomic EBV. The Guernsey breed is a small dairy cattle breed with approximately 14,000 recorded individuals worldwide. Predictions of phenotypes of milk yield, fat yield, protein yield, and calving interval were made for Guernsey cows from England and Guernsey Island using genomic EBV, with training sets including 197 de-regressed proofs of genotyped bulls, with cows selected from among 1,440 genotyped cows using different genotyping strategies. Accuracies of predictions were tested using 10-fold cross-validation among the cows. Genomic EBV were predicted using 4 different methods: (1) pedigree BLUP, (2) genomic BLUP using only bulls, (3) univariate genomic BLUP using bulls and cows, and (4) bivariate genomic BLUP. Genotyping cows with phenotypes and using their data for the prediction of single nucleotide polymorphism effects increased the correlation between genomic EBV and phenotypes compared with using only bulls by 0.163±0.022 for milk yield, 0.111±0.021 for fat yield, and 0.113±0.018 for protein yield; a decrease of 0.014±0.010 for calving interval from a low base was the only exception. Genetic correlation between phenotypes from bulls and cows were approximately 0.6 for all yield traits and significantly different from 1. Only a very small change occurred in correlation between genomic EBV and phenotypes when using the bivariate model. It was always better to genotype all the cows, but when only half of the cows were genotyped, a divergent selection strategy was better compared with the random or directional selection approach. Divergent selection of 30% of the cows remained superior for the yield traits in 8 of 10 folds. Copyright © 2017 American Dairy Science Association. Published by

Improving Microbial Genome Annotations in an Integrated Database Context

Science.gov (United States)

Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken; Anderson, Iain; Mavromatis, Konstantinos; Kyrpides, Nikos C.; Ivanova, Natalia N.

2013-01-01

Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG) family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/. PMID:23424620

Improving microbial genome annotations in an integrated database context.

Directory of Open Access Journals (Sweden)

I-Min A Chen

Full Text Available Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/.

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.

Genome-enabled prediction models for yield related traits in chickpea

Science.gov (United States)

Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped...

Genome Variation Map: a data repository of genome variations in BIG Data Center.

Science.gov (United States)

Song, Shuhui; Tian, Dongmei; Li, Cuiping; Tang, Bixia; Dong, Lili; Xiao, Jingfa; Bao, Yiming; Zhao, Wenming; He, Hang; Zhang, Zhang

2018-01-04

The Genome Variation Map (GVM; http://bigd.big.ac.cn/gvm/) is a public data repository of genome variations. As a core resource in the BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, GVM dedicates to collect, integrate and visualize genome variations for a wide range of species, accepts submissions of different types of genome variations from all over the world and provides free open access to all publicly available data in support of worldwide research activities. Unlike existing related databases, GVM features integration of a large number of genome variations for a broad diversity of species including human, cultivated plants and domesticated animals. Specifically, the current implementation of GVM not only houses a total of ∼4.9 billion variants for 19 species including chicken, dog, goat, human, poplar, rice and tomato, but also incorporates 8669 individual genotypes and 13 262 manually curated high-quality genotype-to-phenotype associations for non-human species. In addition, GVM provides friendly intuitive web interfaces for data submission, browse, search and visualization. Collectively, GVM serves as an important resource for archiving genomic variation data, helpful for better understanding population genetic diversity and deciphering complex mechanisms associated with different phenotypes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Genome Variation Map: a data repository of genome variations in BIG Data Center

Science.gov (United States)

Tian, Dongmei; Li, Cuiping; Tang, Bixia; Dong, Lili; Xiao, Jingfa; Bao, Yiming; Zhao, Wenming; He, Hang

2018-01-01

Abstract The Genome Variation Map (GVM; http://bigd.big.ac.cn/gvm/) is a public data repository of genome variations. As a core resource in the BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, GVM dedicates to collect, integrate and visualize genome variations for a wide range of species, accepts submissions of different types of genome variations from all over the world and provides free open access to all publicly available data in support of worldwide research activities. Unlike existing related databases, GVM features integration of a large number of genome variations for a broad diversity of species including human, cultivated plants and domesticated animals. Specifically, the current implementation of GVM not only houses a total of ∼4.9 billion variants for 19 species including chicken, dog, goat, human, poplar, rice and tomato, but also incorporates 8669 individual genotypes and 13 262 manually curated high-quality genotype-to-phenotype associations for non-human species. In addition, GVM provides friendly intuitive web interfaces for data submission, browse, search and visualization. Collectively, GVM serves as an important resource for archiving genomic variation data, helpful for better understanding population genetic diversity and deciphering complex mechanisms associated with different phenotypes. PMID:29069473

Genetic Mapping of Novel Loci Affecting Canine Blood Phenotypes.

Directory of Open Access Journals (Sweden)

Michelle E White

Full Text Available Since the publication of the dog genome and the construction of high-quality genome-wide SNP arrays, thousands of dogs have been genotyped for disease studies. For many of these dogs, additional clinical phenotypes are available, such as hematological and clinical chemistry results collected during routine veterinary care. Little is known about the genetic basis of variation in blood phenotypes, but this variation may play an important role in the etiology and progression of many diseases. From a cohort of dogs that had been previously genotyped on a semi-custom Illumina CanineHD array for various genome-wide association studies (GWAS at Cornell University Hospital for Animals, we chose 353 clinically healthy, adult dogs for our analysis of clinical pathologic test results (14 hematological tests and 25 clinical chemistry tests. After correcting for age, body weight and sex, genetic associations were identified for amylase, segmented neutrophils, urea nitrogen, glucose, and mean corpuscular hemoglobin. Additionally, a strong genetic association (P = 8.1×10-13 was evident between a region of canine chromosome 13 (CFA13 and alanine aminotransferase (ALT, explaining 23% of the variation in ALT levels. This region of CFA13 encompasses the GPT gene that encodes the transferase. Dogs homozygous for the derived allele exhibit lower ALT activity, making increased ALT activity a less useful marker of hepatic injury in these individuals. Overall, these associations provide a roadmap for identifying causal variants that could improve interpretation of clinical blood tests and understanding of genetic risk factors associated with diseases such as canine diabetes and anemia, and demonstrate the utility of holistic phenotyping of dogs genotyped for disease mapping studies.

Genetic Mapping of Novel Loci Affecting Canine Blood Phenotypes.

Science.gov (United States)

White, Michelle E; Hayward, Jessica J; Stokol, Tracy; Boyko, Adam R

2015-01-01

Since the publication of the dog genome and the construction of high-quality genome-wide SNP arrays, thousands of dogs have been genotyped for disease studies. For many of these dogs, additional clinical phenotypes are available, such as hematological and clinical chemistry results collected during routine veterinary care. Little is known about the genetic basis of variation in blood phenotypes, but this variation may play an important role in the etiology and progression of many diseases. From a cohort of dogs that had been previously genotyped on a semi-custom Illumina CanineHD array for various genome-wide association studies (GWAS) at Cornell University Hospital for Animals, we chose 353 clinically healthy, adult dogs for our analysis of clinical pathologic test results (14 hematological tests and 25 clinical chemistry tests). After correcting for age, body weight and sex, genetic associations were identified for amylase, segmented neutrophils, urea nitrogen, glucose, and mean corpuscular hemoglobin. Additionally, a strong genetic association (P = 8.1×10-13) was evident between a region of canine chromosome 13 (CFA13) and alanine aminotransferase (ALT), explaining 23% of the variation in ALT levels. This region of CFA13 encompasses the GPT gene that encodes the transferase. Dogs homozygous for the derived allele exhibit lower ALT activity, making increased ALT activity a less useful marker of hepatic injury in these individuals. Overall, these associations provide a roadmap for identifying causal variants that could improve interpretation of clinical blood tests and understanding of genetic risk factors associated with diseases such as canine diabetes and anemia, and demonstrate the utility of holistic phenotyping of dogs genotyped for disease mapping studies.

Accuracy of genomic selection in European maize elite breeding populations.

Science.gov (United States)

Zhao, Yusheng; Gowda, Manje; Liu, Wenxin; Würschum, Tobias; Maurer, Hans P; Longin, Friedrich H; Ranc, Nicolas; Reif, Jochen C

2012-03-01

Genomic selection is a promising breeding strategy for rapid improvement of complex traits. The objective of our study was to investigate the prediction accuracy of genomic breeding values through cross validation. The study was based on experimental data of six segregating populations from a half-diallel mating design with 788 testcross progenies from an elite maize breeding program. The plants were intensively phenotyped in multi-location field trials and fingerprinted with 960 SNP markers. We used random regression best linear unbiased prediction in combination with fivefold cross validation. The prediction accuracy across populations was higher for grain moisture (0.90) than for grain yield (0.58). The accuracy of genomic selection realized for grain yield corresponds to the precision of phenotyping at unreplicated field trials in 3-4 locations. As for maize up to three generations are feasible per year, selection gain per unit time is high and, consequently, genomic selection holds great promise for maize breeding programs.

Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

OpenAIRE

Okbay, Aysu; Baselmans, B.M.L. (Bart M.L.); Neve, Jan-Emmanuel; Turley, Patrick; Nivard, Michel; Fontana, M.A. (Mark Alan); Meddens, S.F.W. (S. Fleur W.); Linnér, R.K. (Richard Karlsson); Rietveld, C.A. (Cornelius A); Derringer, J.; Gratten, Jacob; Lee, James J.; Liu, J.Z. (Jimmy Z); Vlaming, Ronald; SAhluwalia, T. (Tarunveer)

2016-01-01

textabstractVery few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associ...

From genomic variation to personalized medicine

DEFF Research Database (Denmark)

Wesolowska, Agata; Schmiegelow, Kjeld

Genomic variation is the basis of interindividual differences in observable traits and disease susceptibility. Genetic studies are the driving force of personalized medicine, as many of the differences in treatment efficacy can be attributed to our genomic background. The rapid development...... a considerable amount of the phenotype variability, hence the major difficulty of interpretation lies in the complexity of molecular interactions. This PhD thesis describes the state-of-art of the functional human variation research (Chapter 1) and introduces childhood acute lymphoblastic leukaemia (ALL...... the thesis and includes some final remarks on the perspectives of genomic variation research and personalized medicine. In summary, this thesis demonstrates the feasibility of integrative analyses of genomic variations and introduces large-scale hypothesis-driven SNP exploration studies as an emerging...

Genome-wide association mapping and agronomic impact of cowpea root architecture.

Science.gov (United States)

Burridge, James D; Schneider, Hannah M; Huynh, Bao-Lam; Roberts, Philip A; Bucksch, Alexander; Lynch, Jonathan P

2017-02-01

Genetic analysis of data produced by novel root phenotyping tools was used to establish relationships between cowpea root traits and performance indicators as well between root traits and Striga tolerance. Selection and breeding for better root phenotypes can improve acquisition of soil resources and hence crop production in marginal environments. We hypothesized that biologically relevant variation is measurable in cowpea root architecture. This study implemented manual phenotyping (shovelomics) and automated image phenotyping (DIRT) on a 189-entry diversity panel of cowpea to reveal biologically important variation and genome regions affecting root architecture phenes. Significant variation in root phenes was found and relatively high heritabilities were detected for root traits assessed manually (0.4 for nodulation and 0.8 for number of larger laterals) as well as repeatability traits phenotyped via DIRT (0.5 for a measure of root width and 0.3 for a measure of root tips). Genome-wide association study identified 11 significant quantitative trait loci (QTL) from manually scored root architecture traits and 21 QTL from root architecture traits phenotyped by DIRT image analysis. Subsequent comparisons of results from this root study with other field studies revealed QTL co-localizations between root traits and performance indicators including seed weight per plant, pod number, and Striga (Striga gesnerioides) tolerance. The data suggest selection for root phenotypes could be employed by breeding programs to improve production in multiple constraint environments.

All SNPs Are Not Created Equal: Genome-Wide Association Studies Reveal a Consistent Pattern of Enrichment among Functionally Annotated SNPs

NARCIS (Netherlands)

Schork, Andrew J.; Thompson, Wesley K.; Pham, Phillip; Torkamani, Ali; Roddey, J. Cooper; Sullivan, Patrick F.; Kelsoe, John R.; O'Donovan, Michael C.; Furberg, Helena; Schork, Nicholas J.; Andreassen, Ole A.; Dale, Anders M.; Absher, Devin; Agudo, Antonio; Almgren, Peter; Ardissino, Diego; Assimes, Themistocles L.; Bandinelli, Stephania; Barzan, Luigi; Bencko, Vladimir; Benhamou, Simone; Benjamin, Emelia J.; Bernardinelli, Luisa; Bis, Joshua; Boehnke, Michael; Boerwinkle, Eric; Boomsma, Dorret I.; Brennan, Paul; Canova, Cristina; Castellsagué, Xavier; Chanock, Stephen; Chasman, Daniel; Conway, David I.; Dackor, Jennifer; de Geus, Eco J. C.; Duan, Jubao; Elosua, Roberto; Everett, Brendan; Fabianova, Eleonora; Ferrucci, Luigi; Foretova, Lenka; Fortmann, Stephen P.; Franceschini, Nora; Frayling, Timothy; Furberg, Curt; Gejman, Pablo V.; Groop, Leif; Gu, Fangyi; de Haan, Lieuwe; Linszen, Don H.

2013-01-01

Recent results indicate that genome-wide association studies (GWAS) have the potential to explain much of the heritability of common complex phenotypes, but methods are lacking to reliably identify the remaining associated single nucleotide polymorphisms (SNPs). We applied stratified False Discovery

All SNPs are not created equal: Genome-wide association studies reveal a consistent pattern of enrichment among functionally annotated SNPs

NARCIS (Netherlands)

Schork, A.J.; Thompson, W.K.; Pham, P.; Torkamani, A.; Roddey, J.C.; Sullivan, P.F.; Kelsoe, J.; O'Donovan, M.C.; Furberg, H.; Absher, D.; Agudo, A.; Almgren, P.; Ardissino, D.; Assimes, T.L.; Bandinelli, S.; Barzan, L.; Bencko, V.; Benhamou, S.; Benjamin, E.J.; Bernardinelli, L.; Bis, J.; Boehnke, M.; Boerwinkle, E.; Boomsma, D.I.; Brennan, P.; Canova, C.; Castellsagué, X.; Chanock, S.; Chasman, D.I.; Conway, D.I.; Dackor, J.; de Geus, E.J.C.; Duan, J.; Elosua, R.; Everett, B.; Fabianova, E.; Ferrucci, L.; Foretova, L.; Fortmann, S.P.; Franceschini, N.; Frayling, T.M.; Furberg, C.; Gejman, P.V.; Groop, L.; Gu, F.; Guralnik, J.; Hankinson, S.E.; Haritunians, T.; Healy, C.; Hofman, A.; Holcátová, I.; Hunter, D.J.; Hwang, S.J.; Ioannidis, J.P.A.; Iribarren, C.; Jackson, A.U.; Janout, V.; Kaprio, J.; Kim, Y.; Kjaerheim, K.; Knowles, J.W.; Kraft, P.; Ladenvall, C.; Lagiou, P.; Lanthrop, M.; Lerman, C.; Levinson, D.F.; Levy, D.; Li, M.D.; Lin, D.Y.; Lips, E.H.; Lissowska, J.; Lowry, R.B.; Lucas, G.; Macfarlane, T.V.; Maes, H.H.M.; Mannucci, P.M.; Mates, D.; Mauri, F.; McGovern, J.A.; McKay, J.D.; McKnight, B.; Melander, O.; Merlini, P.A.; Milaneschi, Y.; Mohlke, K.L.; O'Donnell, C.J.; Pare, G.; Penninx, B.W.J.H.; Perry, J.R.B.; Posthuma, D.; Preis, S.R.; Psaty, B.; Quertermous, T.; Ramachandran, V.S.; Richiardi, L.; Ridker, P.M.; Rose, J.; Rudnai, P.; Salomaa, V.; Sanders, A.R.; Schwartz, S.M.; Shi, J.; Smit, J.H.; Stringham, H.M.; Szeszenia-Dabrowska, N.; Tanaka, T.; Taylor, K.; Thacker, E.E.; Thornton, L.; Tiemeier, H.; Tuomilehto, J.; Uitterlinden, A.G.; van Duijn, C.M.; Vink, J.M.; Vogelzangs, N.; Voight, B.F.; Walter, S.; Willemsen, G.; Zaridze, D.; Znaor, A.; Akil, H.; Anjorin, A.; Backlund, L.; Badner, J.A.; Barchas, J.D.; Barrett, T.; Bass, N.; Bauer, M.; Bellivier, F.; Bergen, S.E.; Berrettini, W.; Blackwood, D.; Bloss, C.S.; Breen, G.; Breuer, R.; Bunner, W.E.; Burmeister, M.; Byerley, W. F.; Caesar, S.; Chambert, K.; Cichon, S.; St Clair, D.; Collier, D.A.; Corvin, A.; Coryell, W.H.; Craddock, N.; Craig, D.W.; Daly, M.; Day, R.; Degenhardt, F.; Djurovic, S.; Dudbridge, F.; Edenberg, H.J.; Elkin, A.; Etain, B.; Farmer, A.E.; Ferreira, M.A.; Ferrier, I.; Flickinger, M.; Foroud, T.; Frank, J.; Fraser, C.; Frisén, L.; Gershon, E.S.; Gill, M.; Gordon-Smith, K.; Green, E.K.; Greenwood, T.A.; Grozeva, D.; Guan, W.; Gurling, H.; Gustafsson, O.; Hamshere, M.L.; Hautzinger, M.; Herms, S.; Hipolito, M.; Holmans, P.A.; Hultman, C. M.; Jamain, S.; Jones, E.G.; Jones, I.; Jones, L.; Kandaswamy, R.; Kennedy, J.L.; Kirov, G. K.; Koller, D.L.; Kwan, P.; Landén, M.; Langstrom, N.; Lathrop, M.; Lawrence, J.; Lawson, W.B.; Leboyer, M.; Lee, P.H.; Li, J.; Lichtenstein, P.; Lin, D.; Liu, C.; Lohoff, F.W.; Lucae, S.; Mahon, P.B.; Maier, W.; Martin, N.G.; Mattheisen, M.; Matthews, K.; Mattingsdal, M.; McGhee, K.A.; McGuffin, P.; McInnis, M.G.; McIntosh, A.; McKinney, R.; McLean, A.W.; McMahon, F.J.; McQuillin, A.; Meier, S.; Melle, I.; Meng, F.; Mitchell, P.B.; Montgomery, G.W.; Moran, J.; Morken, G.; Morris, D.W.; Moskvina, V.; Muglia, P.; Mühleisen, T.W.; Muir, W.J.; Müller-Myhsok, B.; Myers, R.M.; Nievergelt, C.M.; Nikolov, I.; Nimgaonkar, V.L.; Nöthen, M.M.; Nurnberger, J.I.; Nwulia, E.A.; O'Dushlaine, C.; Osby, U.; Óskarsson, H.; Owen, M.J.; Petursson, H.; Pickard, B.S.; Porgeirsson, P.; Potash, J.B.; Propping, P.; Purcell, S.M.; Quinn, E.; Raychaudhuri, S.; Rice, J.; Rietschel, M.; Ruderfer, D.; Schalling, M.; Schatzberg, A.F.; Scheftner, W.A.; Schofield, P.R.; Schulze, T.G.; Schumacher, J.; Schwarz, M.M.; Scolnick, E.; Scott, L.J.; Shilling, P.D.; Sigurdsson, E.; Sklar, P.; Smith, E.N.; Stefansson, H.; Stefansson, K.; Steffens, M; Steinberg, S.; Strauss, J.; Strohmaier, J.; Szelinger, S.; Thompson, R.C.; Tozzi, F.; Treutlein, J.; Vincent, J.B.; Watson, S.J.; Wienker, T.F.; Williamson, R.; Witt, S.H.; Wright, A.; Xu, W.; Young, A.H.; Zandi, P.P.; Zhang, P.; Zöllner, S.; Agartz, I.; Albus, M.; Alexander, M.; Amdur, R. L.; Amin, F.; Bitter, I.; Black, D.W.; Børglum, A.D.; Brown, M.A.; Bruggeman, R.; Buccola, N.G.; Cahn, W.; Cantor, R.M.; Carr, V.J.; Catts, S. V.; Choudhury, K.; Cloninger, C. R.; Cormican, P.; Danoy, P. A.; Datta, S.; DeHert, M.; Demontis, D.; Dikeos, D.; Donnelly, P.; Donohoe, G.; Duong, L.; Dwyer, S.; Fanous, A.; Fink-Jensen, A.; Freedman, R.; Freimer, N.B.; Friedl, M.; Georgieva, L.; Giegling, I.; Glenthoj, B.; Godard, S.; Golimbet, V.; de Haan, L.; Hansen, M.; Hansen, T.; Hartmann, A.M.; Henskens, F. A.; Hougaard, D. M.; Ingason, A.; Jablensky, A. V.; Jakobsen, K.D.; Jay, M.; Jönsson, E.G.; Jürgens, G.; Kahn, R.S.; Keller, M.C.; Kendler, K.S.; Kenis, G.; Kenny, E.; Konnerth, H.; Konte, B.; Krabbendam, L.; Krasucki, R.; Lasseter, V. K.; Laurent, C.; Lencz, T.; Lerer, F. B.; Liang, K. Y.; Lieberman, J. A.; Linszen, D.H.; Lönnqvist, J.; Loughland, C. M.; Maclean, A. W.; Maher, B.S.; Malhotra, A.K.; Mallet, J.; Malloy, P.; McGrath, J. J.; McLean, D. E.; Michie, P. T.; Milanova, V.; Mors, O.; Mortensen, P.B.; Mowry, B. J.; Myin-Germeys, I.; Neale, B.; Nertney, D. A.; Nestadt, G.; Nielsen, J.; Nordentoft, M.; Norton, N.; O'Neill, F.; Olincy, A.; Olsen, L.; Ophoff, R.A.; Orntoft, T. F.; van Os, J.; Pantelis, C.; Papadimitriou, G.; Pato, C.N.; Peltonen, L.; Pickard, B.; Pietilainen, O.P.; Pimm, J.; Pulver, A. E.; Puri, V.; Quested, D.; Rasmussen, H.B.; Rethelyi, J.M.; Ribble, R.; Riley, B.P.; Rossin, L.; Ruggeri, M.; Rujescu, D.; Schall, U.; Schwab, S. G.; Scott, R.J.; Silverman, J.M.; Spencer, C. C.; Strange, A.; Strengman, E.; Stroup, T.S.; Suvisaari, J.; Terenius, L.; Thirumalai, S.; Timm, S.; Toncheva, D.; Tosato, S.; van den Oord, E.J.; Veldink, J.; Visscher, P.M.; Walsh, D.; Wang, A. G.; Werge, T.; Wiersma, D.; Wildenauer, D. B.; Williams, H.J.; Williams, N.M.; van Winkel, R.; Wormley, B.; Zammit, S.; Schork, N.J.; Andreassen, O.A.; Dale, A.M.

2013-01-01

Recent results indicate that genome-wide association studies (GWAS) have the potential to explain much of the heritability of common complex phenotypes, but methods are lacking to reliably identify the remaining associated single nucleotide polymorphisms (SNPs). We applied stratified False Discovery

Genome-Wide Association Study of Piglet Uniformity and Farrowing Interval

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Yuan Wang

2017-11-01

Full Text Available Piglet uniformity (PU and farrowing interval (FI are important reproductive traits related to production and economic profits in the pig industry. However, the genetic architecture of the longitudinal trends of reproductive traits still remains elusive. Herein, we performed a genome-wide association study (GWAS to detect potential genetic variation and candidate genes underlying the phenotypic records at different parities for PU and FI in a population of 884 Large White pigs. In total, 12 significant SNPs were detected on SSC1, 3, 4, 9, and 14, which collectively explained 1–1.79% of the phenotypic variance for PU from parity 1 to 4, and 2.58–4.11% for FI at different stages. Of these, seven SNPs were located within 16 QTL regions related to swine reproductive traits. One QTL region was associated with birth body weight (related to PU and contained the peak SNP MARC0040730, and another was associated with plasma FSH concentration (related to FI and contained the SNP MARC0031325. Finally, some positional candidate genes for PU and FI were identified because of their roles in prenatal skeletal muscle development, fetal energy substrate, pre-implantation, and the expression of mammary gland epithelium. Identification of novel variants and candidate genes will greatly advance our understanding of the genetic mechanisms of PU and FI, and suggest a specific opportunity for improving marker assisted selection or genomic selection in pigs.

HEK293 in cell biology and cancer research: phenotype, karyotype, tumorigenicity, and stress-induced genome-phenotype evolution.

Science.gov (United States)

Stepanenko, A A; Dmitrenko, V V

2015-09-15

293 cell line (widely known as the Human Embryonic Kidney 293 cells) and its derivatives were the most used cells after HeLa in cell biology studies and after CHO in biotechnology as a vehicle for the production of adenoviral vaccines and recombinant proteins, for analysis of the neuronal synapse formation, in electrophysiology and neuropharmacology. Despite the historically long-term productive exploitation, the origin, phenotype, karyotype, and tumorigenicity of 293 cells are still debated. 293 cells were considered the kidney epithelial cells or even fibroblasts. However, 293 cells demonstrate no evident tissue-specific gene expression signature and express the markers of renal progenitor cells, neuronal cells and adrenal gland. This complicates efforts to reveal the authentic cell type/tissue of origin. On the other hand, the potential to propagate the highly neurotropic viruses, inducible synaptogenesis, functionality of the endogenous neuron-specific voltage-gated channels, and response to the diverse agonists implicated in neuronal signaling give credibility to consider 293 cells of neuronal lineage phenotype. The compound phenotype of 293 cells can be due to heterogeneous, unstable karyotype. The mean chromosome number and chromosome aberrations differ between 293 cells and derivatives as well as between 293 cells from the different cell banks/labs. 293 cells are tumorigenic, whereas acute changes of expression of the cancer-associated genes aggravate tumorigenicity by promoting chromosome instability. Importantly, the procedure of a stable empty vector transfection can also impact karyotype and phenotype. The discussed issues caution against misinterpretations and pitfalls during the different experimental manipulations with 293 cells. Copyright © 2015 Elsevier B.V. All rights reserved.

Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean.

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Fang, Chao; Ma, Yanming; Wu, Shiwen; Liu, Zhi; Wang, Zheng; Yang, Rui; Hu, Guanghui; Zhou, Zhengkui; Yu, Hong; Zhang, Min; Pan, Yi; Zhou, Guoan; Ren, Haixiang; Du, Weiguang; Yan, Hongrui; Wang, Yanping; Han, Dezhi; Shen, Yanting; Liu, Shulin; Liu, Tengfei; Zhang, Jixiang; Qin, Hao; Yuan, Jia; Yuan, Xiaohui; Kong, Fanjiang; Liu, Baohui; Li, Jiayang; Zhang, Zhiwu; Wang, Guodong; Zhu, Baoge; Tian, Zhixi

2017-08-24

Soybean (Glycine max [L.] Merr.) is one of the most important oil and protein crops. Ever-increasing soybean consumption necessitates the improvement of varieties for more efficient production. However, both correlations among different traits and genetic interactions among genes that affect a single trait pose a challenge to soybean breeding. To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits. This study provides insights into the genetic correlation among complex traits and will facilitate future soybean functional studies and breeding through molecular design.

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

Science.gov (United States)

Cook, James P; Mahajan, Anubha; Morris, Andrew P

2017-02-01

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

To What Extent Does DNA Methylation Affect Phenotypic Variation in Cattle?

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Stephanie McKAY

2015-07-01

Full Text Available DNA methylation is an environmentally influenced epigenetic modification that regulates gene transcription and has the potential to influence variation in economically important phenotypes in agricultural species. We have utilized a novel approach to evaluate the relationship between genetic and epigenetic variation and downstream phenotypes. To begin with, we have integrated RNA-Seq and methyl binding domain sequencing (MBD-Seq data in order to determine the extent to which DNA methylation affects phenotypic variation in economically important traits of cattle. MBD-Seq is a technique that involves the sample enrichment of methylated genomic regions followed by their next-generation sequencing. This study utilized Illumina next generation sequencing technology to perform both RNA-Seq and MBD-Seq. NextGENe software (SoftGenetics, State College, PA was employed for quality trimming and aligning the sequence reads to the UMD3.1 bovine reference genome, generating counts of matched reads and methylated peak identification. Subsequently, we identified and quantified genome-wide methylated regions and characterized the extent of differential methylation and differential expression between two groups of animals with extreme phenotypes. The program edgeR from the R software package (version 3.0.1 was employed for identifying differentially methylated regions and regions of differential expression. Finally, Partial Correlation with Information Theory (PCIT was performed to identify transcripts and methylation events that exhibit differential hubbing. A differential hub is defined as a gene network hub that is more highly connected in one treatment group than the other. This analysis produced every possible pair-wise interaction that subsequently enabled us to look at network interactions of how methylation affects expression. (co-expression, co-methylation, methylation x expression. Genomic regions of interest derived from this analysis were then aligned

Towards a database for genotype-phenotype association research: mining data from encyclopaedia

NARCIS (Netherlands)

Pajić, V.S.; Pavlović-Lažetić, G.M.; Beljanski, M.V.; Brandt, B.W.; Pajić, M.B.

2013-01-01

To associate phenotypic characteristics of an organism to molecules encoded by its genome, there is a need for well-structured genotype and phenotype data. We use a novel method for extracting data on phenotype and genotype characteristics of microorganisms from text. As a resource, we use an

Genome-Wide Association Study for Traits Related to Plant and Grain Morphology, and Root Architecture in Temperate Rice Accessions.

Science.gov (United States)

Biscarini, Filippo; Cozzi, Paolo; Casella, Laura; Riccardi, Paolo; Vattari, Alessandra; Orasen, Gabriele; Perrini, Rosaria; Tacconi, Gianni; Tondelli, Alessandro; Biselli, Chiara; Cattivelli, Luigi; Spindel, Jennifer; McCouch, Susan; Abbruscato, Pamela; Valé, Giampiero; Piffanelli, Pietro; Greco, Raffaella

2016-01-01

In this study we carried out a genome-wide association analysis for plant and grain morphology and root architecture in a unique panel of temperate rice accessions adapted to European pedo-climatic conditions. This is the first study to assess the association of selected phenotypic traits to specific genomic regions in the narrow genetic pool of temperate japonica. A set of 391 rice accessions were GBS-genotyped yielding-after data editing-57000 polymorphic and informative SNPS, among which 54% were in genic regions. In total, 42 significant genotype-phenotype associations were detected: 21 for plant morphology traits, 11 for grain quality traits, 10 for root architecture traits. The FDR of detected associations ranged from 3 · 10-7 to 0.92 (median: 0.25). In most cases, the significant detected associations co-localised with QTLs and candidate genes controlling the phenotypic variation of single or multiple traits. The most significant associations were those for flag leaf width on chromosome 4 (FDR = 3 · 10-7) and for plant height on chromosome 6 (FDR = 0.011). We demonstrate the effectiveness and resolution of the developed platform for high-throughput phenotyping, genotyping and GWAS in detecting major QTLs for relevant traits in rice. We identified strong associations that may be used for selection in temperate irrigated rice breeding: e.g. associations for flag leaf width, plant height, root volume and length, grain length, grain width and their ratio. Our findings pave the way to successfully exploit the narrow genetic pool of European temperate rice and to pinpoint the most relevant genetic components contributing to the adaptability and high yield of this germplasm. The generated data could be of direct use in genomic-assisted breeding strategies.

Genome-Wide Association Study for Traits Related to Plant and Grain Morphology, and Root Architecture in Temperate Rice Accessions.

Directory of Open Access Journals (Sweden)

Filippo Biscarini

Full Text Available In this study we carried out a genome-wide association analysis for plant and grain morphology and root architecture in a unique panel of temperate rice accessions adapted to European pedo-climatic conditions. This is the first study to assess the association of selected phenotypic traits to specific genomic regions in the narrow genetic pool of temperate japonica. A set of 391 rice accessions were GBS-genotyped yielding-after data editing-57000 polymorphic and informative SNPS, among which 54% were in genic regions.In total, 42 significant genotype-phenotype associations were detected: 21 for plant morphology traits, 11 for grain quality traits, 10 for root architecture traits. The FDR of detected associations ranged from 3 · 10-7 to 0.92 (median: 0.25. In most cases, the significant detected associations co-localised with QTLs and candidate genes controlling the phenotypic variation of single or multiple traits. The most significant associations were those for flag leaf width on chromosome 4 (FDR = 3 · 10-7 and for plant height on chromosome 6 (FDR = 0.011.We demonstrate the effectiveness and resolution of the developed platform for high-throughput phenotyping, genotyping and GWAS in detecting major QTLs for relevant traits in rice. We identified strong associations that may be used for selection in temperate irrigated rice breeding: e.g. associations for flag leaf width, plant height, root volume and length, grain length, grain width and their ratio. Our findings pave the way to successfully exploit the narrow genetic pool of European temperate rice and to pinpoint the most relevant genetic components contributing to the adaptability and high yield of this germplasm. The generated data could be of direct use in genomic-assisted breeding strategies.

The bonobo genome compared with the chimpanzee and human genomes

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Prüfer, Kay; Munch, Kasper; Hellmann, Ines; Akagi, Keiko; Miller, Jason R.; Walenz, Brian; Koren, Sergey; Sutton, Granger; Kodira, Chinnappa; Winer, Roger; Knight, James R.; Mullikin, James C.; Meader, Stephen J.; Ponting, Chris P.; Lunter, Gerton; Higashino, Saneyuki; Hobolth, Asger; Dutheil, Julien; Karakoç, Emre; Alkan, Can; Sajjadian, Saba; Catacchio, Claudia Rita; Ventura, Mario; Marques-Bonet, Tomas; Eichler, Evan E.; André, Claudine; Atencia, Rebeca; Mugisha, Lawrence; Junhold, Jörg; Patterson, Nick; Siebauer, Michael; Good, Jeffrey M.; Fischer, Anne; Ptak, Susan E.; Lachmann, Michael; Symer, David E.; Mailund, Thomas; Schierup, Mikkel H.; Andrés, Aida M.; Kelso, Janet; Pääbo, Svante

2012-01-01

Two African apes are the closest living relatives of humans: the chimpanzee (Pan troglodytes) and the bonobo (Pan paniscus). Although they are similar in many respects, bonobos and chimpanzees differ strikingly in key social and sexual behaviours1–4, and for some of these traits they show more similarity with humans than with each other. Here we report the sequencing and assembly of the bonobo genome to study its evolutionary relationship with the chimpanzee and human genomes. We find that more than three per cent of the human genome is more closely related to either the bonobo or the chimpanzee genome than these are to each other. These regions allow various aspects of the ancestry of the two ape species to be reconstructed. In addition, many of the regions that overlap genes may eventually help us understand the genetic basis of phenotypes that humans share with one of the two apes to the exclusion of the other. PMID:22722832

Phenotypic plasticity, QTL mapping and genomic characterization of bud set in black poplar

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Fabbrini Francesco

2012-04-01

Full Text Available Abstract Background The genetic control of important adaptive traits, such as bud set, is still poorly understood in most forest trees species. Poplar is an ideal model tree to study bud set because of its indeterminate shoot growth. Thus, a full-sib family derived from an intraspecific cross of P. nigra with 162 clonally replicated progeny was used to assess the phenotypic plasticity and genetic variation of bud set in two sites of contrasting environmental conditions. Results Six crucial phenological stages of bud set were scored. Night length appeared to be the most important signal triggering the onset of growth cessation. Nevertheless, the effect of other environmental factors, such as temperature, increased during the process. Moreover, a considerable role of genotype × environment (G × E interaction was found in all phenological stages with the lowest temperature appearing to influence the sensitivity of the most plastic genotypes. Descriptors of growth cessation and bud onset explained the largest part of phenotypic variation of the entire process. Quantitative trait loci (QTL for these traits were detected. For the four selected traits (the onset of growth cessation (date2.5, the transition from shoot to bud (date1.5, the duration of bud formation (subproc1 and bud maturation (subproc2 eight and sixteen QTL were mapped on the maternal and paternal map, respectively. The identified QTL, each one characterized by small or modest effect, highlighted the complex nature of traits involved in bud set process. Comparison between map location of QTL and P. trichocarpa genome sequence allowed the identification of 13 gene models, 67 bud set-related expressional and six functional candidate genes (CGs. These CGs are functionally related to relevant biological processes, environmental sensing, signaling, and cell growth and development. Some strong QTL had no obvious CGs, and hold great promise to identify unknown genes that affect bud set

Genomic and Phenotypic Analyses Reveal the Emergence of an Atypical Salmonella enterica Serovar Senftenberg Variant in China

KAUST Repository

Abd El Ghany, Moataz

2016-05-25

Human infections with Salmonella enterica subspecies enterica serovar Senftenberg are often associated with exposure to poultry flocks, farm environments, or contaminated food. The recent emergence of multidrug-resistant isolates has raised public health concerns. In this study, comparative genomics and phenotypic analysis were used to characterize 14 Salmonella Senftenberg clinical isolates recovered from multiple outbreaks in Shenzhen and Shanghai, China, between 2002 and 2011. Single-nucleotide polymorphism analyses identified two phylogenetically distinct clades of S. Senftenberg, designated SC1 and SC2, harboring variations in Salmonella pathogenicity island 1 (SPI-1) and SPI-2 and exhibiting distinct biochemical and phenotypic signatures. Although the two variants shared the same serotype, the SC2 isolates of sequence type 14 (ST14) harbored intact SPI-1 and -2 and hence were characterized by possessing efficient invasion capabilities. In contrast, the SC1 isolates had structural deletion patterns in both SPI-1 and -2 that correlated with an impaired capacity to invade cultured human cells and also the year of their isolation. These atypical SC1 isolates also lacked the capacity to produce hydrogen sulfide. These findings highlight the emergence of atypical Salmonella Senftenberg variants in China and provide genetic validation that variants lacking SPI-1 and regions of SPI-2, which leads to impaired invasion capacity, can still cause clinical disease. These data have identified an emerging public health concern and highlight the need to strengthen surveillance to detect the prevalence and transmission of nontyphoidal Salmonella species.

Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems.

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Len J Wade

Full Text Available The rapid progress in rice genotyping must be matched by advances in phenotyping. A better understanding of genetic variation in rice for drought response, root traits, and practical methods for studying them are needed. In this study, the OryzaSNP set (20 diverse genotypes that have been genotyped for SNP markers was phenotyped in a range of field and container studies to study the diversity of rice root growth and response to drought. Of the root traits measured across more than 20 root experiments, root dry weight showed the most stable genotypic performance across studies. The environment (E component had the strongest effect on yield and root traits. We identified genomic regions correlated with root dry weight, percent deep roots, maximum root depth, and grain yield based on a correlation analysis with the phenotypes and aus, indica, or japonica introgression regions using the SNP data. Two genomic regions were identified as hot spots in which root traits and grain yield were co-located; on chromosome 1 (39.7-40.7 Mb and on chromosome 8 (20.3-21.9 Mb. Across experiments, the soil type/ growth medium showed more correlations with plant growth than the container dimensions. Although the correlations among studies and genetic co-location of root traits from a range of study systems points to their potential utility to represent responses in field studies, the best correlations were observed when the two setups had some similar properties. Due to the co-location of the identified genomic regions (from introgression block analysis with QTL for a number of previously reported root and drought traits, these regions are good candidates for detailed characterization to contribute to understanding rice improvement for response to drought. This study also highlights the utility of characterizing a small set of 20 genotypes for root growth, drought response, and related genomic regions.

Pulmonary phenotypes associated with genetic variation in telomere-related genes.

Science.gov (United States)

Hoffman, Thijs W; van Moorsel, Coline H M; Borie, Raphael; Crestani, Bruno

2018-05-01

Genomic mutations in telomere-related genes have been recognized as a cause of familial forms of idiopathic pulmonary fibrosis (IPF). However, it has become increasingly clear that telomere syndromes and telomere shortening are associated with various types of pulmonary disease. Additionally, it was found that also single nucleotide polymorphisms (SNPs) in telomere-related genes are risk factors for the development of pulmonary disease. This review focuses on recent updates on pulmonary phenotypes associated with genetic variation in telomere-related genes. Genomic mutations in seven telomere-related genes cause pulmonary disease. Pulmonary phenotypes associated with these mutations range from many forms of pulmonary fibrosis to emphysema and pulmonary vascular disease. Telomere-related mutations account for up to 10% of sporadic IPF, 25% of familial IPF, 10% of connective-tissue disease-associated interstitial lung disease, and 1% of COPD. Mixed disease forms have also been found. Furthermore, SNPs in TERT, TERC, OBFC1, and RTEL1, as well as short telomere length, have been associated with several pulmonary diseases. Treatment of pulmonary disease caused by telomere-related gene variation is currently based on disease diagnosis and not on the underlying cause. Pulmonary phenotypes found in carriers of telomere-related gene mutations and SNPs are primarily pulmonary fibrosis, sometimes emphysema and rarely pulmonary vascular disease. Genotype-phenotype relations are weak, suggesting that environmental factors and genetic background of patients determine disease phenotypes to a large degree. A disease model is presented wherever genomic variation in telomere-related genes cause specific pulmonary disease phenotypes whenever triggered by environmental exposure, comorbidity, or unknown factors.

QTL Analysis and Functional Genomics of Animal Model

DEFF Research Database (Denmark)

Farajzadeh, Leila

, for example, has enabled scientists to examine more complex interactions in connection with studies of properties and diseases. In her PhD project, Leila Farajzadeh integrated different organisational levels in biology, including genotype, phenotype, association studies, transcription profiles and genetic......In recent years, the use of functional genomics and next-generation sequencing technologies has increased the probability of success in studies of complex properties. The integration of large data sets from association studies, DNA resequencing, gene expression profiles and phenotypic data...

Generation of New Genotypic and Phenotypic Features in Artificial and Natural Yeast Hybrids

Directory of Open Access Journals (Sweden)

Walter P. Pfliegler

2014-01-01

Full Text Available Evolution and genome stabilization have mostly been studied on the Saccharomyces hybrids isolated from natural and alcoholic fermentation environments. Genetic and phenotypic properties have usually been compared to the laboratory and reference strains, as the true ancestors of the natural hybrid yeasts are unknown. In this way the exact impact of different parental fractions on the genome organization or metabolic activity of the hybrid yeasts is difficult to resolve completely. In the present work the evolution of geno- and phenotypic properties is studied in the interspecies hybrids created by the cross-breeding of S. cerevisiae with S. uvarum or S. kudriavzevii auxotrophic mutants. We hypothesized that the extent of genomic alterations in S. cerevisiae × S. uvarum and S. cerevisiae × S. kudriavzevii should affect the physiology of their F1 offspring in different ways. Our results, obtained by amplified fragment length polymorphism (AFLP genotyping and karyotyping analyses, showed that both subgenomes of the S. cerevisiae x S. uvarum and of S. cerevisiae × S. kudriavzevii hybrids experienced various modifications. However, the S. cerevisiae × S. kudriavzevii F1 hybrids underwent more severe genomic alterations than the S. cerevisiae × S. uvarum ones. Generation of the new genotypes also influenced the physiological performances of the hybrids and the occurrence of novel phenotypes. Significant differences in carbohydrate utilization and distinct growth dynamics at increasing concentrations of sodium chloride, urea and miconazole were observed within and between the S. cerevisiae × S. uvarum and S. cerevisiae × S. kudriavzevii hybrids. Parental strains also demonstrated different contributions to the final metabolic outcomes of the hybrid yeasts. A comparison of the genotypic properties of the artificial hybrids with several hybrid isolates from the wine-related environments and wastewater demonstrated a greater genetic variability of

Sexual Polyploidization in Medicago sativa L.: Impact on the Phenotype, Gene Transcription, and Genome Methylation.

Science.gov (United States)

Rosellini, Daniele; Ferradini, Nicoletta; Allegrucci, Stefano; Capomaccio, Stefano; Zago, Elisa Debora; Leonetti, Paola; Balech, Bachir; Aversano, Riccardo; Carputo, Domenico; Reale, Lara; Veronesi, Fabio

2016-04-07

Polyploidization as the consequence of 2n gamete formation is a prominent mechanism in plant evolution. Studying its effects on the genome, and on genome expression, has both basic and applied interest. We crossed two diploid (2n = 2x = 16) Medicago sativa plants, a subsp. falcata seed parent, and a coerulea × falcata pollen parent that form a mixture of n and 2n eggs and pollen, respectively. Such a cross produced full-sib diploid and tetraploid (2n = 4x = 32) hybrids, the latter being the result of bilateral sexual polyploidization (BSP). These unique materials allowed us to investigate the effects of BSP, and to separate the effect of intraspecific hybridization from those of polyploidization by comparing 2x with 4x full sib progeny plants. Simple sequence repeat marker segregation demonstrated tetrasomic inheritance for all chromosomes but one, demonstrating that these neotetraploids are true autotetraploids. BSP brought about increased biomass, earlier flowering, higher seed set and weight, and larger leaves with larger cells. Microarray analyses with M. truncatula gene chips showed that several hundred genes, related to diverse metabolic functions, changed their expression level as a consequence of polyploidization. In addition, cytosine methylation increased in 2x, but not in 4x, hybrids. Our results indicate that sexual polyploidization induces significant transcriptional novelty, possibly mediated in part by DNA methylation, and phenotypic novelty that could underpin improved adaptation and reproductive success of tetraploid M. sativa with respect to its diploid progenitor. These polyploidy-induced changes may have promoted the adoption of tetraploid alfalfa in agriculture. Copyright © 2016 Rosellini et al.

Sexual Polyploidization in Medicago sativa L.: Impact on the Phenotype, Gene Transcription, and Genome Methylation

Directory of Open Access Journals (Sweden)

Daniele Rosellini

2016-04-01

Full Text Available Polyploidization as the consequence of 2n gamete formation is a prominent mechanism in plant evolution. Studying its effects on the genome, and on genome expression, has both basic and applied interest. We crossed two diploid (2n = 2x = 16 Medicago sativa plants, a subsp. falcata seed parent, and a coerulea × falcata pollen parent that form a mixture of n and 2n eggs and pollen, respectively. Such a cross produced full-sib diploid and tetraploid (2n = 4x = 32 hybrids, the latter being the result of bilateral sexual polyploidization (BSP. These unique materials allowed us to investigate the effects of BSP, and to separate the effect of intraspecific hybridization from those of polyploidization by comparing 2x with 4x full sib progeny plants. Simple sequence repeat marker segregation demonstrated tetrasomic inheritance for all chromosomes but one, demonstrating that these neotetraploids are true autotetraploids. BSP brought about increased biomass, earlier flowering, higher seed set and weight, and larger leaves with larger cells. Microarray analyses with M. truncatula gene chips showed that several hundred genes, related to diverse metabolic functions, changed their expression level as a consequence of polyploidization. In addition, cytosine methylation increased in 2x, but not in 4x, hybrids. Our results indicate that sexual polyploidization induces significant transcriptional novelty, possibly mediated in part by DNA methylation, and phenotypic novelty that could underpin improved adaptation and reproductive success of tetraploid M. sativa with respect to its diploid progenitor. These polyploidy-induced changes may have promoted the adoption of tetraploid alfalfa in agriculture.

Genome-wide study of the defective sucrose fermenter strain of Vibrio cholerae from the Latin American cholera epidemic.

Directory of Open Access Journals (Sweden)

Daniel Rios Garza

Full Text Available The 7th cholera pandemic reached Latin America in 1991, spreading from Peru to virtually all Latin American countries. During the late epidemic period, a strain that failed to ferment sucrose dominated cholera outbreaks in the Northern Brazilian Amazon region. In order to understand the genomic characteristics and the determinants of this altered sucrose fermenting phenotype, the genome of the strain IEC224 was sequenced. This paper reports a broad genomic study of this strain, showing its correlation with the major epidemic lineage. The potentially mobile genomic regions are shown to possess GC content deviation, and harbor the main V. cholera virulence genes. A novel bioinformatic approach was applied in order to identify the putative functions of hypothetical proteins, and was compared with the automatic annotation by RAST. The genome of a large bacteriophage was found to be integrated to the IEC224's alanine aminopeptidase gene. The presence of this phage is shown to be a common characteristic of the El Tor strains from the Latin American epidemic, as well as its putative ancestor from Angola. The defective sucrose fermenting phenotype is shown to be due to a single nucleotide insertion in the V. cholerae sucrose-specific transportation gene. This frame-shift mutation truncated a membrane protein, altering its structural pore-like conformation. Further, the identification of a common bacteriophage reinforces both the monophyletic and African-Origin hypotheses for the main causative agent of the 1991 Latin America cholera epidemics.

Semantic prioritization of novel causative genomic variants

KAUST Repository

Boudellioua, Imene

2017-04-17

Discriminating the causative disease variant(s) for individuals with inherited or de novo mutations presents one of the main challenges faced by the clinical genetics community today. Computational approaches for variant prioritization include machine learning methods utilizing a large number of features, including molecular information, interaction networks, or phenotypes. Here, we demonstrate the PhenomeNET Variant Predictor (PVP) system that exploits semantic technologies and automated reasoning over genotype-phenotype relations to filter and prioritize variants in whole exome and whole genome sequencing datasets. We demonstrate the performance of PVP in identifying causative variants on a large number of synthetic whole exome and whole genome sequences, covering a wide range of diseases and syndromes. In a retrospective study, we further illustrate the application of PVP for the interpretation of whole exome sequencing data in patients suffering from congenital hypothyroidism. We find that PVP accurately identifies causative variants in whole exome and whole genome sequencing datasets and provides a powerful resource for the discovery of causal variants.

Semantic prioritization of novel causative genomic variants

KAUST Repository

Boudellioua, Imene; Mohamad Razali, Rozaimi; Kulmanov, Maxat; Hashish, Yasmeen; Bajic, Vladimir B.; Goncalves-Serra, Eva; Schoenmakers, Nadia; Gkoutos, Georgios V.; Schofield, Paul N.; Hoehndorf, Robert

2017-01-01

Discriminating the causative disease variant(s) for individuals with inherited or de novo mutations presents one of the main challenges faced by the clinical genetics community today. Computational approaches for variant prioritization include machine learning methods utilizing a large number of features, including molecular information, interaction networks, or phenotypes. Here, we demonstrate the PhenomeNET Variant Predictor (PVP) system that exploits semantic technologies and automated reasoning over genotype-phenotype relations to filter and prioritize variants in whole exome and whole genome sequencing datasets. We demonstrate the performance of PVP in identifying causative variants on a large number of synthetic whole exome and whole genome sequences, covering a wide range of diseases and syndromes. In a retrospective study, we further illustrate the application of PVP for the interpretation of whole exome sequencing data in patients suffering from congenital hypothyroidism. We find that PVP accurately identifies causative variants in whole exome and whole genome sequencing datasets and provides a powerful resource for the discovery of causal variants.

Vagal innervation is required for pulmonary function phenotype in Htr4-/- mice.

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House, John S; Nichols, Cody E; Li, Huiling; Brandenberger, Christina; Virgincar, Rohan S; DeGraff, Laura M; Driehuys, Bastiaan; Zeldin, Darryl C; London, Stephanie J

2017-04-01

Human genome-wide association studies have identified over 50 loci associated with pulmonary function and related phenotypes, yet follow-up studies to determine causal genes or variants are rare. Single nucleotide polymorphisms in serotonin receptor 4 ( HTR4 ) are associated with human pulmonary function in genome-wide association studies and follow-up animal work has demonstrated that Htr4 is causally associated with pulmonary function in mice, although the precise mechanisms were not identified. We sought to elucidate the role of neural innervation and pulmonary architecture in the lung phenotype of Htr4 -/- animals. We report here that the Htr4 -/- phenotype in mouse is dependent on vagal innervation to the lung. Both ex vivo tracheal ring reactivity and in vivo flexiVent pulmonary functional analyses demonstrate that vagotomy abrogates the Htr4 -/- airway hyperresponsiveness phenotype. Hyperpolarized 3 He gas magnetic resonance imaging and stereological assessment of wild-type and Htr4 -/- mice reveal no observable differences in lung volume, inflation characteristics, or pulmonary microarchitecture. Finally, control of breathing experiments reveal substantive differences in baseline breathing characteristics between mice with/without functional HTR4 in breathing frequency, relaxation time, flow rate, minute volume, time of inspiration and expiration and breathing pauses. These results suggest that HTR4's role in pulmonary function likely relates to neural innervation and control of breathing. Copyright © 2017 the American Physiological Society.

Implementation of genomic recursions in single-step genomic best linear unbiased predictor for US Holsteins with a large number of genotyped animals.

Science.gov (United States)

Masuda, Y; Misztal, I; Tsuruta, S; Legarra, A; Aguilar, I; Lourenco, D A L; Fragomeni, B O; Lawlor, T J

2016-03-01

The objectives of this study were to develop and evaluate an efficient implementation in the computation of the inverse of genomic relationship matrix with the recursion algorithm, called the algorithm for proven and young (APY), in single-step genomic BLUP. We validated genomic predictions for young bulls with more than 500,000 genotyped animals in final score for US Holsteins. Phenotypic data included 11,626,576 final scores on 7,093,380 US Holstein cows, and genotypes were available for 569,404 animals. Daughter deviations for young bulls with no classified daughters in 2009, but at least 30 classified daughters in 2014 were computed using all the phenotypic data. Genomic predictions for the same bulls were calculated with single-step genomic BLUP using phenotypes up to 2009. We calculated the inverse of the genomic relationship matrix GAPY(-1) based on a direct inversion of genomic relationship matrix on a small subset of genotyped animals (core animals) and extended that information to noncore animals by recursion. We tested several sets of core animals including 9,406 bulls with at least 1 classified daughter, 9,406 bulls and 1,052 classified dams of bulls, 9,406 bulls and 7,422 classified cows, and random samples of 5,000 to 30,000 animals. Validation reliability was assessed by the coefficient of determination from regression of daughter deviation on genomic predictions for the predicted young bulls. The reliabilities were 0.39 with 5,000 randomly chosen core animals, 0.45 with the 9,406 bulls, and 7,422 cows as core animals, and 0.44 with the remaining sets. With phenotypes truncated in 2009 and the preconditioned conjugate gradient to solve mixed model equations, the number of rounds to convergence for core animals defined by bulls was 1,343; defined by bulls and cows, 2,066; and defined by 10,000 random animals, at most 1,629. With complete phenotype data, the number of rounds decreased to 858, 1,299, and at most 1,092, respectively. Setting up GAPY(-1

Genome-wide association study of handedness excludes simple genetic models

Science.gov (United States)

Armour, J AL; Davison, A; McManus, I C

2014-01-01

Handedness is a human behavioural phenotype that appears to be congenital, and is often assumed to be inherited, but for which the developmental origin and underlying causation(s) have been elusive. Models of the genetic basis of variation in handedness have been proposed that fit different features of the observed resemblance between relatives, but none has been decisively tested or a corresponding causative locus identified. In this study, we applied data from well-characterised individuals studied at the London Twin Research Unit. Analysis of genome-wide SNP data from 3940 twins failed to identify any locus associated with handedness at a genome-wide level of significance. The most straightforward interpretation of our analyses is that they exclude the simplest formulations of the ‘right-shift' model of Annett and the ‘dextral/chance' model of McManus, although more complex modifications of those models are still compatible with our observations. For polygenic effects, our study is inadequately powered to reliably detect alleles with effect sizes corresponding to an odds ratio of 1.2, but should have good power to detect effects at an odds ratio of 2 or more. PMID:24065183

A genome-wide association study of social genetic effects in Landrace pigs.

Science.gov (United States)

Hong, Joon Ki; Jeong, Yong Dae; Cho, Eun Seok; Choi, Tae Jeong; Kim, Yong Min; Cho, Kyu Ho; Lee, Jae Bong; Lim, Hyun Tae; Lee, Deuk Hwan

2018-06-01

The genetic effects of an individual on the phenotypes of its social partners, such as its pen mates, are known as social genetic effects. This study aims to identify the candidate genes for social (pen-mates') average daily gain (ADG) in pigs by using the genome-wide association approach. Social ADG (sADG) was the average ADG of unrelated pen-mates (strangers). We used the phenotype data (16,802 records) after correcting for batch (week), sex, pen, number of strangers (1 to 7 pigs) in the pen, full-sib rate (0% to 80%) within pen, and age at the end of the test. A total of 1,041 pigs from Landrace breeds were genotyped using the Illumina PorcineSNP60 v2 BeadChip panel, which comprised 61,565 single nucleotide polymorphism (SNP) markers. After quality control, 909 individuals and 39,837 markers remained for sADG in genome-wide association study. We detected five new SNPs, all on chromosome 6, which have not been associated with social ADG or other growth traits to date. One SNP was inside the prostaglandin F2α receptor ( PTGFR ) gene, another SNP was located 22 kb upstream of gene interferon-induced protein 44 ( IFI44 ), and the last three SNPs were between 161 kb and 191 kb upstream of the EGF latrophilin and seven transmembrane domain-containing protein 1 ( ELTD1 ) gene. PTGFR, IFI44, and ELTD1 were never associated with social interaction and social genetic effects in any of the previous studies. The identification of several genomic regions, and candidate genes associated with social genetic effects reported here, could contribute to a better understanding of the genetic basis of interaction traits for ADG. In conclusion, we suggest that the PTGFR, IFI44, and ELTD1 may be used as a molecular marker for sADG, although their functional effect was not defined yet. Thus, it will be of interest to execute association studies in those genes.

A DEL phenotype attributed to RHD Exon 9 sequence deletion: slipped-strand mispairing and blood group polymorphisms.

Science.gov (United States)

Lopez, Genghis H; Turner, Robyn M; McGowan, Eunike C; Schoeman, Elizna M; Scott, Stacy A; O'Brien, Helen; Millard, Glenda M; Roulis, Eileen V; Allen, Amanda J; Liew, Yew-Wah; Flower, Robert L; Hyland, Catherine A

2018-03-01

The RhD blood group antigen is extremely polymorphic and the DEL phenotype represents one such class of polymorphisms. The DEL phenotype prevalent in East Asian populations arises from a synonymous substitution defined as RHD*1227A. However, initially, based on genomic and cDNA studies, the genetic basis for a DEL phenotype in Taiwan was attributed to a deletion of RHD Exon 9 that was never verified at the genomic level by any other independent group. Here we investigate the genetic basis for a Caucasian donor with a DEL partial D phenotype and compare the genomic findings to those initial molecular studies. The 3'-region of the RHD gene was amplified by long-range polymerase chain reaction (PCR) for massively parallel sequencing. Primers were designed to encompass a deletion, flanking Exon 9, by standard PCR for Sanger sequencing. Targeted sequencing of exons and flanking introns was also performed. Genomic DNA exhibited a 1012-bp deletion spanning from Intron 8, across Exon 9 into Intron 9. The deletion breakpoints occurred between two 25-bp repeat motifs flanking Exon 9 such that one repeat sequence remained. Deletion mutations bordered by repeat sequences are a hallmark of slipped-strand mispairing (SSM) event. We propose this genetic mechanism generated the germline deletion in the Caucasian donor. Extensive studies show that the RHD*1227A is the most prevalent DEL allele in East Asian populations and may have confounded the initial molecular studies. Review of the literature revealed that the SSM model explains some of the extreme polymorphisms observed in the clinically significant RhD blood group antigen. © 2017 AABB.

Genome-wide association study identifies multiple loci associated with both mammographic density and breast cancer risk

Science.gov (United States)

Lindström, Sara; Thompson, Deborah J.; Paterson, Andrew D.; Li, Jingmei; Gierach, Gretchen L.; Scott, Christopher; Stone, Jennifer; Douglas, Julie A.; dos-Santos-Silva, Isabel; Fernandez-Navarro, Pablo; Verghase, Jajini; Smith, Paula; Brown, Judith; Luben, Robert; Wareham, Nicholas J.; Loos, Ruth J.F.; Heit, John A.; Pankratz, V. Shane; Norman, Aaron; Goode, Ellen L.; Cunningham, Julie M.; deAndrade, Mariza; Vierkant, Robert A.; Czene, Kamila; Fasching, Peter A.; Baglietto, Laura; Southey, Melissa C.; Giles, Graham G.; Shah, Kaanan P.; Chan, Heang-Ping; Helvie, Mark A.; Beck, Andrew H.; Knoblauch, Nicholas W.; Hazra, Aditi; Hunter, David J.; Kraft, Peter; Pollan, Marina; Figueroa, Jonine D.; Couch, Fergus J.; Hopper, John L.; Hall, Per; Easton, Douglas F.; Boyd, Norman F.; Vachon, Celine M.; Tamimi, Rulla M.

2015-01-01

Mammographic density reflects the amount of stromal and epithelial tissues in relation to adipose tissue in the breast and is a strong risk factor for breast cancer. Here we report the results from meta-analysis of genome-wide association studies (GWAS) of three mammographic density phenotypes: dense area, non-dense area and percent density in up to 7,916 women in stage 1 and an additional 10,379 women in stage 2. We identify genome-wide significant (P<5×10−8) loci for dense area (AREG, ESR1, ZNF365, LSP1/TNNT3, IGF1, TMEM184B, SGSM3/MKL1), non-dense area (8p11.23) and percent density (PRDM6, 8p11.23, TMEM184B). Four of these regions are known breast cancer susceptibility loci, and four additional regions were found to be associated with breast cancer (P<0.05) in a large meta-analysis. These results provide further evidence of a shared genetic basis between mammographic density and breast cancer and illustrate the power of studying intermediate quantitative phenotypes to identify putative disease susceptibility loci. PMID:25342443

Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration.

Science.gov (United States)

Thorvaldsdóttir, Helga; Robinson, James T; Mesirov, Jill P

2013-03-01

Data visualization is an essential component of genomic data analysis. However, the size and diversity of the data sets produced by today's sequencing and array-based profiling methods present major challenges to visualization tools. The Integrative Genomics Viewer (IGV) is a high-performance viewer that efficiently handles large heterogeneous data sets, while providing a smooth and intuitive user experience at all levels of genome resolution. A key characteristic of IGV is its focus on the integrative nature of genomic studies, with support for both array-based and next-generation sequencing data, and the integration of clinical and phenotypic data. Although IGV is often used to view genomic data from public sources, its primary emphasis is to support researchers who wish to visualize and explore their own data sets or those from colleagues. To that end, IGV supports flexible loading of local and remote data sets, and is optimized to provide high-performance data visualization and exploration on standard desktop systems. IGV is freely available for download from http://www.broadinstitute.org/igv, under a GNU LGPL open-source license.

COMPUTER APPROACHES TO WHEAT HIGH-THROUGHPUT PHENOTYPING

Directory of Open Access Journals (Sweden)

Afonnikov D.

2012-08-01

Full Text Available The growing need for rapid and accurate approaches for large-scale assessment of phenotypic characters in plants becomes more and more obvious in the studies looking into relationships between genotype and phenotype. This need is due to the advent of high throughput methods for analysis of genomes. Nowadays, any genetic experiment involves data on thousands and dozens of thousands of plants. Traditional ways of assessing most phenotypic characteristics (those with reliance on the eye, the touch, the ruler are little effective on samples of such sizes. Modern approaches seek to take advantage of automated phenotyping, which warrants a much more rapid data acquisition, higher accuracy of the assessment of phenotypic features, measurement of new parameters of these features and exclusion of human subjectivity from the process. Additionally, automation allows measurement data to be rapidly loaded into computer databases, which reduces data processing time.In this work, we present the WheatPGE information system designed to solve the problem of integration of genotypic and phenotypic data and parameters of the environment, as well as to analyze the relationships between the genotype and phenotype in wheat. The system is used to consolidate miscellaneous data on a plant for storing and processing various morphological traits and genotypes of wheat plants as well as data on various environmental factors. The system is available at www.wheatdb.org. Its potential in genetic experiments has been demonstrated in high-throughput phenotyping of wheat leaf pubescence.

RECG maintains plastid and mitochondrial genome stability by suppressing extensive recombination between short dispersed repeats.

Directory of Open Access Journals (Sweden)

Masaki Odahara

2015-03-01

Full Text Available Maintenance of plastid and mitochondrial genome stability is crucial for photosynthesis and respiration, respectively. Recently, we have reported that RECA1 maintains mitochondrial genome stability by suppressing gross rearrangements induced by aberrant recombination between short dispersed repeats in the moss Physcomitrella patens. In this study, we studied a newly identified P. patens homolog of bacterial RecG helicase, RECG, some of which is localized in both plastid and mitochondrial nucleoids. RECG partially complements recG deficiency in Escherichia coli cells. A knockout (KO mutation of RECG caused characteristic phenotypes including growth delay and developmental and mitochondrial defects, which are similar to those of the RECA1 KO mutant. The RECG KO cells showed heterogeneity in these phenotypes. Analyses of RECG KO plants showed that mitochondrial genome was destabilized due to a recombination between 8-79 bp repeats and the pattern of the recombination partly differed from that observed in the RECA1 KO mutants. The mitochondrial DNA (mtDNA instability was greater in severe phenotypic RECG KO cells than that in mild phenotypic ones. This result suggests that mitochondrial genomic instability is responsible for the defective phenotypes of RECG KO plants. Some of the induced recombination caused efficient genomic rearrangements in RECG KO mitochondria. Such loci were sometimes associated with a decrease in the levels of normal mtDNA and significant decrease in the number of transcripts derived from the loci. In addition, the RECG KO mutation caused remarkable plastid abnormalities and induced recombination between short repeats (12-63 bp in the plastid DNA. These results suggest that RECG plays a role in the maintenance of both plastid and mitochondrial genome stability by suppressing aberrant recombination between dispersed short repeats; this role is crucial for plastid and mitochondrial functions.

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.

Rediscovery by Whole Genome Sequencing: Classical Mutations and Genome Polymorphisms in Neurospora crassa

Energy Technology Data Exchange (ETDEWEB)

McCluskey, Kevin; Wiest, Aric E.; Grigoriev, Igor V.; Lipzen, Anna; Martin, Joel; Schackwitz, Wendy; Baker, Scott E.

2011-06-02

Classical forward genetics has been foundational to modern biology, and has been the paradigm for characterizing the role of genes in shaping phenotypes for decades. In recent years, reverse genetics has been used to identify the functions of genes, via the intentional introduction of variation and subsequent evaluation in physiological, molecular, and even population contexts. These approaches are complementary and whole genome analysis serves as a bridge between the two. We report in this article the whole genome sequencing of eighteen classical mutant strains of Neurospora crassa and the putative identification of the mutations associated with corresponding mutant phenotypes. Although some strains carry multiple unique nonsynonymous, nonsense, or frameshift mutations, the combined power of limiting the scope of the search based on genetic markers and of using a comparative analysis among the eighteen genomes provides strong support for the association between mutation and phenotype. For ten of the mutants, the mutant phenotype is recapitulated in classical or gene deletion mutants in Neurospora or other filamentous fungi. From thirteen to 137 nonsense mutations are present in each strain and indel sizes are shown to be highly skewed in gene coding sequence. Significant additional genetic variation was found in the eighteen mutant strains, and this variability defines multiple alleles of many genes. These alleles may be useful in further genetic and molecular analysis of known and yet-to-be-discovered functions and they invite new interpretations of molecular and genetic interactions in classical mutant strains.

Studying the Genetics of Complex Disease With Ancestry-Specific Human Phenotype Networks: The Case of Type 2 Diabetes in East Asian Populations.

Science.gov (United States)

Qiu, Jingya; Moore, Jason H; Darabos, Christian

2016-05-01

Genome-wide association studies (GWAS) have led to the discovery of over 200 single nucleotide polymorphisms (SNPs) associated with type 2 diabetes mellitus (T2DM). Additionally, East Asians develop T2DM at a higher rate, younger age, and lower body mass index than their European ancestry counterparts. The reason behind this occurrence remains elusive. With comprehensive searches through the National Human Genome Research Institute (NHGRI) GWAS catalog literature, we compiled a database of 2,800 ancestry-specific SNPs associated with T2DM and 70 other related traits. Manual data extraction was necessary because the GWAS catalog reports statistics such as odds ratio and P-value, but does not consistently include ancestry information. Currently, many statistics are derived by combining initial and replication samples from study populations of mixed ancestry. Analysis of all-inclusive data can be misleading, as not all SNPs are transferable across diverse populations. We used ancestry data to construct ancestry-specific human phenotype networks (HPN) centered on T2DM. Quantitative and visual analysis of network models reveal the genetic disparities between ancestry groups. Of the 27 phenotypes in the East Asian HPN, six phenotypes were unique to the network, revealing the underlying ancestry-specific nature of some SNPs associated with T2DM. We studied the relationship between T2DM and five phenotypes unique to the East Asian HPN to generate new interaction hypotheses in a clinical context. The genetic differences found in our ancestry-specific HPNs suggest different pathways are involved in the pathogenesis of T2DM among different populations. Our study underlines the importance of ancestry in the development of T2DM and its implications in pharmocogenetics and personalized medicine. © 2016 The Authors. *Genetic Epidemiology Published by Wiley Periodicals, Inc.

A genome-wide search for linkage to asthma phenotypes in the genetics of asthma international network families : evidence for a major susceptibility locus on chromosome 2p

NARCIS (Netherlands)

Pillai, SG; Chiano, MN; White, NJ; Speer, M; Barnes, KC; Carlsen, K; Gerritsen, Jorrit; Helms, P; Lenney, W; Silverman, M; Sly, P; Sundy, J; Tsanakas, J; von Berg, A; Whyte, M; Varsani, S; Skelding, P; Hauser, M; Vance, J; Pericak-Vance, M; Burns, DK; Middleton, LT; Brewster, [No Value; Anderson, WH; Riley, JH

Asthma is a complex disease and the intricate interplay between genetic and environmental factors underlies the overall phenotype of the disease. Families with at least two siblings with asthma were collected from Europe, Australia and the US. A genome scan using a set of 364 families with a panel

Recurrent duplications of 17q12 associated with variable phenotypes

DEFF Research Database (Denmark)

Mitchell, Elyse; Douglas, Andrew; Kjaegaard, Susanne

2015-01-01

The ability to identify the clinical nature of the recurrent duplication of chromosome 17q12 has been limited by its rarity and the diverse range of phenotypes associated with this genomic change. In order to further define the clinical features of affected patients, detailed clinical information......, potentially contributory copy number changes in a subset of patients, including one patient each with 16p11.2 deletion and 15q13.3 deletion. Our data further define and expand the clinical spectrum associated with duplications of 17q12 and provide support for the role of genomic modifiers contributing...... to phenotypic variability....

The ARID1B phenotype: what we have learned so far.

Science.gov (United States)

Santen, Gijs W E; Clayton-Smith, Jill

2014-09-01

Evidence is now accumulating from a number of sequencing studies that ARID1B not only appears to be one of the most frequently mutated intellectual disability (ID) genes, but that the range of phenotypes caused by ARID1B mutations seems to be extremely wide. Thus, it is one of the most interesting ID genes identified so far in the exome sequencing era. In this article, we review the literature surrounding ARID1B and attempt to delineate the ARID1B phenotype. The vast majority of published ARID1B patients have been ascertained through studies of Coffin-Siris syndrome (CSS), which leads to bias when documenting the frequencies of phenotypic features. Additional observations of those individuals ascertained through exome sequencing studies helps in delineation of the broader clinical phenotype. We are currently establishing an ARID1B consortium, aimed at collecting ARID1B patients identified through genome-wide sequencing strategies. We hope that this endeavor will eventually lead to a more comprehensive view of the ARID1B phenotype. © 2014 Wiley Periodicals, Inc.

Bloom syndrome ortholog HIM-6 maintains genomic stability in C. elegans.

Science.gov (United States)

Grabowski, Melissa M; Svrzikapa, Nenad; Tissenbaum, Heidi A

2005-12-01

Bloom syndrome is caused by mutation of the Bloom helicase (BLM), a member of the RecQ helicase family. Loss of BLM function results in genomic instability that causes a high incidence of cancer. It has been demonstrated that BLM is important for maintaining genomic stability by playing a role in DNA recombination and repair; however, the exact function of BLM is not clearly understood. To determine the mechanism by which BLM controls genomic stability in vivo, we examined the phenotypes caused by mutation of the C. elegans BLM helicase ortholog, HIM-6. We find that the loss of HIM-6 leads to genomic instability as evidenced by an increased number of genomic insertions and deletions, which results in visible random mutant phenotypes. In addition to the mutator phenotype, him-6 mutants have a low brood size, a high incidence of males, a shortened life span, and an increased amount of germ line apoptosis. Upon exposure to high temperature, him-6 mutants that are serially passed become sterile demonstrating a mortal germ line phenotype. Our data suggest a model in which loss of HIM-6 results in genomic instability due to an increased number of DNA lesions, which either cannot be repaired and/or are introduced by low fidelity recombination events. The increased level of genomic instability that leads to him-6(ok412) mutants having a shortened life span.

Genome Target Evaluator (GTEvaluator: A workflow exploiting genome dataset to measure the sensitivity and specificity of genetic markers.

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Arnaud Felten

Full Text Available Most of the bacterial typing methods used to discriminate isolates in medical or food safety microbiology are based on genetic markers used as targets in PCR or hybridization experiments. These DNA typing methods are important tools for studying prevalence and epidemiology, for conducting surveillance, investigations and control of biological hazard sources. In that perspective, it is crucial to insure that the chosen genetic markers have the greatest specificity and sensitivity. The wealth of whole-genome sequences available for many bacterial species offers the opportunity to evaluate the performance of these genetic markers. In the present study, we have developed GTEvaluator, a bioinformatics workflow which ranks genetic markers depending on their sensitivity and specificity towards groups of well-defined genomes. GTEvaluator identifies the most performant genetic markers to target individuals among a population. The individuals (i.e. a group of genomes within a collection are defined by any kind of particular phenotypic or biological properties inside a related population (i.e. collection of genomes. The performance of the genetic markers is computed by a distance value which takes into account both sensitivity and specificity. In this study we report two examples of GTEvaluator application. In the first example Bacillus phenotypic markers were evaluated for their capacity to distinguish B. cereus from B. thuringiensis. In the second experiment, GTEvaluator measured the performance of genetic markers dedicated to the molecular serotyping of Salmonella enterica. In one in silico experiment it was possible to test 64 markers onto 134 genomes corresponding to 14 different serotypes.

Genomic growth curves of an outbred pig population

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Fabyano Fonseca e Silva

2013-01-01

Full Text Available In the current post-genomic era, the genetic basis of pig growth can be understood by assessing SNP marker effects and genomic breeding values (GEBV based on estimates of these growth curve parameters as phenotypes. Although various statistical methods, such as random regression (RR-BLUP and Bayesian LASSO (BL, have been applied to genomic selection (GS, none of these has yet been used in a growth curve approach. In this work, we compared the accuracies of RR-BLUP and BL using empirical weight-age data from an outbred F2 (Brazilian Piau X commercial population. The phenotypes were determined by parameter estimates using a nonlinear logistic regression model and the halothane gene was considered as a marker for evaluating the assumptions of the GS methods in relation to the genetic variation explained by each locus. BL yielded more accurate values for all of the phenotypes evaluated and was used to estimate SNP effects and GEBV vectors. The latter allowed the construction of genomic growth curves, which showed substantial genetic discrimination among animals in the final growth phase. The SNP effect estimates allowed identification of the most relevant markers for each phenotype, the positions of which were coincident with reported QTL regions for growth traits.

Genomic prediction in contrast to a genome-wide association study in explaining heritable variation of complex growth traits in breeding populations of Eucalyptus.

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Müller, Bárbara S F; Neves, Leandro G; de Almeida Filho, Janeo E; Resende, Márcio F R; Muñoz, Patricio R; Dos Santos, Paulo E T; Filho, Estefano Paludzyszyn; Kirst, Matias; Grattapaglia, Dario

2017-07-11

The advent of high-throughput genotyping technologies coupled to genomic prediction methods established a new paradigm to integrate genomics and breeding. We carried out whole-genome prediction and contrasted it to a genome-wide association study (GWAS) for growth traits in breeding populations of Eucalyptus benthamii (n =505) and Eucalyptus pellita (n =732). Both species are of increasing commercial interest for the development of germplasm adapted to environmental stresses. Predictive ability reached 0.16 in E. benthamii and 0.44 in E. pellita for diameter growth. Predictive abilities using either Genomic BLUP or different Bayesian methods were similar, suggesting that growth adequately fits the infinitesimal model. Genomic prediction models using ~5000-10,000 SNPs provided predictive abilities equivalent to using all 13,787 and 19,506 SNPs genotyped in the E. benthamii and E. pellita populations, respectively. No difference was detected in predictive ability when different sets of SNPs were utilized, based on position (equidistantly genome-wide, inside genes, linkage disequilibrium pruned or on single chromosomes), as long as the total number of SNPs used was above ~5000. Predictive abilities obtained by removing relatedness between training and validation sets fell near zero for E. benthamii and were halved for E. pellita. These results corroborate the current view that relatedness is the main driver of genomic prediction, although some short-range historical linkage disequilibrium (LD) was likely captured for E. pellita. A GWAS identified only one significant association for volume growth in E. pellita, illustrating the fact that while genome-wide regression is able to account for large proportions of the heritability, very little or none of it is captured into significant associations using GWAS in breeding populations of the size evaluated in this study. This study provides further experimental data supporting positive prospects of using genome-wide data to

Genome-Wide Association Mapping and Genomic Selection for Alfalfa (Medicago sativa) Forage Quality Traits.

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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

Warped linear mixed models for the genetic analysis of transformed phenotypes.

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Fusi, Nicolo; Lippert, Christoph; Lawrence, Neil D; Stegle, Oliver

2014-09-19

Linear mixed models (LMMs) are a powerful and established tool for studying genotype-phenotype relationships. A limitation of the LMM is that the model assumes Gaussian distributed residuals, a requirement that rarely holds in practice. Violations of this assumption can lead to false conclusions and loss in power. To mitigate this problem, it is common practice to pre-process the phenotypic values to make them as Gaussian as possible, for instance by applying logarithmic or other nonlinear transformations. Unfortunately, different phenotypes require different transformations, and choosing an appropriate transformation is challenging and subjective. Here we present an extension of the LMM that estimates an optimal transformation from the observed data. In simulations and applications to real data from human, mouse and yeast, we show that using transformations inferred by our model increases power in genome-wide association studies and increases the accuracy of heritability estimation and phenotype prediction.

Genome-wide patterns of copy number variation in the diversified chicken genomes using next-generation sequencing.

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Yi, Guoqiang; Qu, Lujiang; Liu, Jianfeng; Yan, Yiyuan; Xu, Guiyun; Yang, Ning

2014-11-07

Copy number variation (CNV) is important and widespread in the genome, and is a major cause of disease and phenotypic diversity. Herein, we performed a genome-wide CNV analysis in 12 diversified chicken genomes based on whole genome sequencing. A total of 8,840 CNV regions (CNVRs) covering 98.2 Mb and representing 9.4% of the chicken genome were identified, ranging in size from 1.1 to 268.8 kb with an average of 11.1 kb. Sequencing-based predictions were confirmed at a high validation rate by two independent approaches, including array comparative genomic hybridization (aCGH) and quantitative PCR (qPCR). The Pearson's correlation coefficients between sequencing and aCGH results ranged from 0.435 to 0.755, and qPCR experiments revealed a positive validation rate of 91.71% and a false negative rate of 22.43%. In total, 2,214 (25.0%) predicted CNVRs span 2,216 (36.4%) RefSeq genes associated with specific biological functions. Besides two previously reported copy number variable genes EDN3 and PRLR, we also found some promising genes with potential in phenotypic variation. Two genes, FZD6 and LIMS1, related to disease susceptibility/resistance are covered by CNVRs. The highly duplicated SOCS2 may lead to higher bone mineral density. Entire or partial duplication of some genes like POPDC3 may have great economic importance in poultry breeding. Our results based on extensive genetic diversity provide a more refined chicken CNV map and genome-wide gene copy number estimates, and warrant future CNV association studies for important traits in chickens.

The application of flexible unmanned aerial vehicle remote sensing for field-based crop phenotyping: Current status and perspectives

Science.gov (United States)

Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypi...

Prediction of malting quality traits in barley based on genome-wide marker data to assess the potential of genomic selection.

Science.gov (United States)

Schmidt, Malthe; Kollers, Sonja; Maasberg-Prelle, Anja; Großer, Jörg; Schinkel, Burkhard; Tomerius, Alexandra; Graner, Andreas; Korzun, Viktor

2016-02-01

Genomic prediction of malting quality traits in barley shows the potential of applying genomic selection to improve selection for malting quality and speed up the breeding process. Genomic selection has been applied to various plant species, mostly for yield or yield-related traits such as grain dry matter yield or thousand kernel weight, and improvement of resistances against diseases. Quality traits have not been the main scope of analysis for genomic selection, but have rather been addressed by marker-assisted selection. In this study, the potential to apply genomic selection to twelve malting quality traits in two commercial breeding programs of spring and winter barley (Hordeum vulgare L.) was assessed. Phenotypic means were calculated combining multilocational field trial data from 3 or 4 years, depending on the trait investigated. Three to five locations were available in each of these years. Heritabilities for malting traits ranged between 0.50 and 0.98. Predictive abilities (PA), as derived from cross validation, ranged between 0.14 to 0.58 for spring barley and 0.40-0.80 for winter barley. Small training sets were shown to be sufficient to obtain useful PAs, possibly due to the narrow genetic base in this breeding material. Deployment of genomic selection in malting barley breeding clearly has the potential to reduce cost intensive phenotyping for quality traits, increase selection intensity and to shorten breeding cycles.

Recommendations for using standardised phenotypes in genetic association studies

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Naylor Melissa G

2009-07-01

Full Text Available Abstract Genetic association studies of complex traits often rely on standardised quantitative phenotypes, such as percentage of predicted forced expiratory volume and body mass index to measure an underlying trait of interest (eg lung function, obesity. These phenotypes are appealing because they provide an easy mechanism for comparing subjects, although such standardisations may not be the best way to control for confounders and other covariates. We recommend adjusting raw or standardised phenotypes within the study population via regression. We illustrate through simulation that optimal power in both population- and family-based association tests is attained by using the residuals from within-study adjustment as the complex trait phenotype. An application of family-based association analysis of forced expiratory volume in one second, and obesity in the Childhood Asthma Management Program data, illustrates that power is maintained or increased when adjusted phenotype residuals are used instead of typical standardised quantitative phenotypes.

Genetical Genomics for Evolutionary Studies

NARCIS (Netherlands)

Prins, J.C.P.; Smant, G.; Jansen, R.C.

2012-01-01

Genetical genomics combines acquired high-throughput genomic data with genetic analysis. In this chapter, we discuss the application of genetical genomics for evolutionary studies, where new high-throughput molecular technologies are combined with mapping quantitative trait loci (QTL) on the genome

Genomics: Looking at Life in New Ways

Energy Technology Data Exchange (ETDEWEB)

Adams, Mark D. (Case-Western Reserve University)

2003-10-22

The availability of complete or nearly complete mouse, human, and rat genomes (in addition to those from many other species) has resulted in a series of new and powerful opportunities to apply the technologies and approaches developed for large-scale genome sequencing to the study of disease. New approaches to biological problems are being explored that involve concepts from computer science such as systems theory and modern large scale computing techniques. A recent project at Celera Genomics involved sequencing protein coding regions from several humans and a chimpanzee. Computational models of evolutionary divergence enabled us to identify genes with unique evolutionary signatures. These genes give us some insight into features that may be uniquely human. The laboratory mouse and rat have long been favorite mammalian models of human disease. Integrated approaches to the study of disease that combine genetics, DNA sequence analysis, and careful analysis of phenotype at a molecular level are becoming more common and powerful. In addition, evaluation of the variation inherent in normal populations is now being used to build networks to describe heart function based on the interaction of multiple phenotypes in randomized populations using a factorial design.

A genome-wide association study points out the causal implication of SOX9 in the sex-reversal phenotype in XX pigs.

Science.gov (United States)

Rousseau, Sarah; Iannuccelli, Nathalie; Mercat, Marie-José; Naylies, Claire; Thouly, Jean-Claude; Servin, Bertrand; Milan, Denis; Pailhoux, Eric; Riquet, Juliette

2013-01-01

Among farm animals, pigs are known to show XX sex-reversal. In such cases the individuals are genetically female but exhibit a hermaphroditism, or a male phenotype. While the frequency of this congenital disease is quite low (less than 1%), the economic losses are significant for pig breeders. These losses result from sterility, urogenital infections and the carcasses being downgraded because of the risk of boar taint. It has been clearly demonstrated that the SRY gene is not involved in most cases of sex-reversal in pigs, and that autosomal recessive mutations remain to be discovered. A whole-genome scan analysis was performed in the French Large-White population to identify candidate genes: 38 families comprising the two non-affected parents and 1 to 11 sex-reversed full-sib piglets were genotyped with the PorcineSNP60 BeadChip. A Transmission Disequilibrium Test revealed a highly significant candidate region on SSC12 (most significant p-valueTesco. However, no causal mutations could be identified in either of the two sequenced regions. Further haplotype analyses did not identify a shared homozygous segment between the affected pigs, suggesting either a lack of power due to the SNP properties of the chip, or a second causative locus. Together with information from humans and mice, this study in pigs adds to the field of knowledge, which will lead to characterization of novel molecular mechanisms regulating sexual differentiation and dysregulation in cases of sex reversal.

The Complete Genome of Brucella Suis 019 Provides Insights on Cross-Species Infection

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Yuanzhi Wang

2016-01-01

Full Text Available Brucella species are the most important zoonotic pathogens worldwide and cause considerable harm to humans and animals. In this study, we presented the complete genome of B. suis 019 isolated from sheep (ovine with epididymitis. B. suis 019 has a rough phenotype and can infect sheep, rhesus monkeys and possibly humans. The comparative genome analysis demonstrated that B. suis 019 is closest to the vaccine strain B. suis bv. 1 str. S2. Further analysis associated the rsh gene to the pathogenicity of B. suis 019, and the WbkA gene to the rough phenotype of B. suis 019. The 019 complete genome data was deposited in the GenBank database with ID PRJNA308608.

Multi-source and ontology-based retrieval engine for maize mutant phenotypes

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In the midst of this genomics era, major plant genome databases are collecting massive amounts of heterogeneous information, including sequence data, gene product information, images of mutant phenotypes, etc., as well as textual descriptions of many of these entities. While basic browsing and sear...

Genome-wide resequencing of KRICE_CORE reveals their potential for future breeding, as well as functional and evolutionary studies in the post-genomic era.

Science.gov (United States)

Kim, Tae-Sung; He, Qiang; Kim, Kyu-Won; Yoon, Min-Young; Ra, Won-Hee; Li, Feng Peng; Tong, Wei; Yu, Jie; Oo, Win Htet; Choi, Buung; Heo, Eun-Beom; Yun, Byoung-Kook; Kwon, Soon-Jae; Kwon, Soon-Wook; Cho, Yoo-Hyun; Lee, Chang-Yong; Park, Beom-Seok; Park, Yong-Jin

2016-05-26

Rice germplasm collections continue to grow in number and size around the world. Since maintaining and screening such massive resources remains challenging, it is important to establish practical methods to manage them. A core collection, by definition, refers to a subset of the entire population that preserves the majority of genetic diversity, enhancing the efficiency of germplasm utilization. Here, we report whole-genome resequencing of the 137 rice mini core collection or Korean rice core set (KRICE_CORE) that represents 25,604 rice germplasms deposited in the Korean genebank of the Rural Development Administration (RDA). We implemented the Illumina HiSeq 2000 and 2500 platform to produce short reads and then assembled those with 9.8 depths using Nipponbare as a reference. Comparisons of the sequences with the reference genome yielded more than 15 million (M) single nucleotide polymorphisms (SNPs) and 1.3 M INDELs. Phylogenetic and population analyses using 2,046,529 high-quality SNPs successfully assigned rice accessions to the relevant rice subgroups, suggesting that these SNPs capture evolutionary signatures that have accumulated in rice subpopulations. Furthermore, genome-wide association studies (GWAS) for four exemplary agronomic traits in the KRIC_CORE manifest the utility of KRICE_CORE; that is, identifying previously defined genes or novel genetic factors that potentially regulate important phenotypes. This study provides strong evidence that the size of KRICE_CORE is small but contains high genetic and functional diversity across the genome. Thus, our resequencing results will be useful for future breeding, as well as functional and evolutionary studies, in the post-genomic era.

Harvesting Legume Genomes: Plant Genetic Resources

Science.gov (United States)

Genomics and high through-put phenotyping are ushering in a new era of accessing genetic diversity held in plant genetic resources, the cornerstone of both traditional and genomics-assisted breeding efforts of food legume crops. Acknowledged or not, yield plateaus must be broken given the daunting ...

Genomic prediction in animals and plants: simulation of data, validation, reporting, and benchmarking

NARCIS (Netherlands)

Daetwyler, H.D.; Calus, M.P.L.; Pong-Wong, R.; Los Campos, De G.; Hickey, J.M.

2013-01-01

The genomic prediction of phenotypes and breeding values in animals and plants has developed rapidly into its own research field. Results of genomic prediction studies are often difficult to compare because data simulation varies, real or simulated data are not fully described, and not all relevant

Genome sequence of the olive tree, Olea europaea.

Science.gov (United States)

Cruz, Fernando; Julca, Irene; Gómez-Garrido, Jèssica; Loska, Damian; Marcet-Houben, Marina; Cano, Emilio; Galán, Beatriz; Frias, Leonor; Ribeca, Paolo; Derdak, Sophia; Gut, Marta; Sánchez-Fernández, Manuel; García, Jose Luis; Gut, Ivo G; Vargas, Pablo; Alioto, Tyler S; Gabaldón, Toni

2016-06-27

The Mediterranean olive tree (Olea europaea subsp. europaea) was one of the first trees to be domesticated and is currently of major agricultural importance in the Mediterranean region as the source of olive oil. The molecular bases underlying the phenotypic differences among domesticated cultivars, or between domesticated olive trees and their wild relatives, remain poorly understood. Both wild and cultivated olive trees have 46 chromosomes (2n). A total of 543 Gb of raw DNA sequence from whole genome shotgun sequencing, and a fosmid library containing 155,000 clones from a 1,000+ year-old olive tree (cv. Farga) were generated by Illumina sequencing using different combinations of mate-pair and pair-end libraries. Assembly gave a final genome with a scaffold N50 of 443 kb, and a total length of 1.31 Gb, which represents 95 % of the estimated genome length (1.38 Gb). In addition, the associated fungus Aureobasidium pullulans was partially sequenced. Genome annotation, assisted by RNA sequencing from leaf, root, and fruit tissues at various stages, resulted in 56,349 unique protein coding genes, suggesting recent genomic expansion. Genome completeness, as estimated using the CEGMA pipeline, reached 98.79 %. The assembled draft genome of O. europaea will provide a valuable resource for the study of the evolution and domestication processes of this important tree, and allow determination of the genetic bases of key phenotypic traits. Moreover, it will enhance breeding programs and the formation of new varieties.

Genetic variants influencing phenotypic variance heterogeneity.

Science.gov (United States)

Ek, Weronica E; Rask-Andersen, Mathias; Karlsson, Torgny; Enroth, Stefan; Gyllensten, Ulf; Johansson, Åsa

2018-03-01

Most genetic studies identify genetic variants associated with disease risk or with the mean value of a quantitative trait. More rarely, genetic variants associated with variance heterogeneity are considered. In this study, we have identified such variance single-nucleotide polymorphisms (vSNPs) and examined if these represent biological gene × gene or gene × environment interactions or statistical artifacts caused by multiple linked genetic variants influencing the same phenotype. We have performed a genome-wide study, to identify vSNPs associated with variance heterogeneity in DNA methylation levels. Genotype data from over 10 million single-nucleotide polymorphisms (SNPs), and DNA methylation levels at over 430 000 CpG sites, were analyzed in 729 individuals. We identified vSNPs for 7195 CpG sites (P mean DNA methylation levels. We further showed that variance heterogeneity between genotypes mainly represents additional, often rare, SNPs in linkage disequilibrium (LD) with the respective vSNP and for some vSNPs, multiple low frequency variants co-segregating with one of the vSNP alleles. Therefore, our results suggest that variance heterogeneity of DNA methylation mainly represents phenotypic effects by multiple SNPs, rather than biological interactions. Such effects may also be important for interpreting variance heterogeneity of more complex clinical phenotypes.

Common genetic variation and susceptibility to partial epilepsies: a genome-wide association study.

Science.gov (United States)

Kasperaviciūte, Dalia; Catarino, Claudia B; Heinzen, Erin L; Depondt, Chantal; Cavalleri, Gianpiero L; Caboclo, Luis O; Tate, Sarah K; Jamnadas-Khoda, Jenny; Chinthapalli, Krishna; Clayton, Lisa M S; Shianna, Kevin V; Radtke, Rodney A; Mikati, Mohamad A; Gallentine, William B; Husain, Aatif M; Alhusaini, Saud; Leppert, David; Middleton, Lefkos T; Gibson, Rachel A; Johnson, Michael R; Matthews, Paul M; Hosford, David; Heuser, Kjell; Amos, Leslie; Ortega, Marcos; Zumsteg, Dominik; Wieser, Heinz-Gregor; Steinhoff, Bernhard J; Krämer, Günter; Hansen, Jörg; Dorn, Thomas; Kantanen, Anne-Mari; Gjerstad, Leif; Peuralinna, Terhi; Hernandez, Dena G; Eriksson, Kai J; Kälviäinen, Reetta K; Doherty, Colin P; Wood, Nicholas W; Pandolfo, Massimo; Duncan, John S; Sander, Josemir W; Delanty, Norman; Goldstein, David B; Sisodiya, Sanjay M

2010-07-01

Partial epilepsies have a substantial heritability. However, the actual genetic causes are largely unknown. In contrast to many other common diseases for which genetic association-studies have successfully revealed common variants associated with disease risk, the role of common variation in partial epilepsies has not yet been explored in a well-powered study. We undertook a genome-wide association-study to identify common variants which influence risk for epilepsy shared amongst partial epilepsy syndromes, in 3445 patients and 6935 controls of European ancestry. We did not identify any genome-wide significant association. A few single nucleotide polymorphisms may warrant further investigation. We exclude common genetic variants with effect sizes above a modest 1.3 odds ratio for a single variant as contributors to genetic susceptibility shared across the partial epilepsies. We show that, at best, common genetic variation can only have a modest role in predisposition to the partial epilepsies when considered across syndromes in Europeans. The genetic architecture of the partial epilepsies is likely to be very complex, reflecting genotypic and phenotypic heterogeneity. Larger meta-analyses are required to identify variants of smaller effect sizes (odds ratio<1.3) or syndrome-specific variants. Further, our results suggest research efforts should also be directed towards identifying the multiple rare variants likely to account for at least part of the heritability of the partial epilepsies. Data emerging from genome-wide association-studies will be valuable during the next serious challenge of interpreting all the genetic variation emerging from whole-genome sequencing studies.

Identification of neural outgrowth genes using genome-wide RNAi.

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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

Selection on Optimal Haploid Value Increases Genetic Gain and Preserves More Genetic Diversity Relative to Genomic Selection

OpenAIRE

Daetwyler, Hans D.; Hayden, Matthew J.; Spangenberg, German C.; Hayes, Ben J.

2015-01-01

Doubled haploids are routinely created and phenotypically selected in plant breeding programs to accelerate the breeding cycle. Genomic selection, which makes use of both phenotypes and genotypes, has been shown to further improve genetic gain through prediction of performance before or without phenotypic characterization of novel germplasm. Additional opportunities exist to combine genomic prediction methods with the creation of doubled haploids. Here we propose an extension to genomic selec...

Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation

NARCIS (Netherlands)

N. Kato (Norihiro); M. Loh (Marie); F. Takeuchi (Fumihiko); N. Verweij (Niek); X. Wang (Xu); W. Zhang (Weihua); T. NKelly (Tanika); D. Saleheen; B. Lehne (Benjamin); I.M. Leach (Irene Mateo); A. Drong (Alexander); J. Abbott (James); S. Wahl (Simone); S.-T. Tan (Sian-Tsung); W.R. Scott (William R.); G. Campanella (Gianluca); M. Chadeau-Hyam (Marc); U. Afzal (Uzma); T.S. Ahluwalia (Tarunveer Singh); M.J. Bonder (Marc); P. Chen (Ping); A. Dehghan (Abbas); T.L. Edwards (Todd L.); T. Esko (Tõnu); M.J. Go (Min Jin); S.E. Harris (Sarah); J. Hartiala (Jaana); S. Kasela (Silva); A. Kasturiratne (Anuradhani); C.C. Khor; M.E. Kleber (Marcus); H. Li (Huaixing); Z.Y. Mok (Zuan Yu); M. Nakatochi (Masahiro); N.S. Sapari (Nur Sabrina); R. Saxena (Richa); A.F. Stewart (Alexandre F.); L. Stolk (Lisette); Y. Tabara (Yasuharu); A.L. Teh (Ai Ling); Y. Wu (Ying); J.-Y. Wu (Jer-Yuarn); Y. Zhang (Yi); I. Aits (Imke); A. Da Silva Couto Alves (Alexessander); S. Das (Shikta); R. Dorajoo (Rajkumar); J. CHopewell (Jemma); Y.K. Kim (Yun Kyoung); R. WKoivula (Robert); J. Luan (Jian'An); L.-P. Lyytikäinen (Leo-Pekka); Q. NNguyen (Quang); M.A. Pereira (Mark A); D. Postmus (Douwe); O. TRaitakari (Olli); M. Scannell Bryan (Molly); R.A. Scott (Robert); R. Sorice; V. Tragante (Vinicius); M. Traglia (Michela); J. White (Jon); K. Yamamoto (Ken); Y. Zhang (Yonghong); L.S. Adair (Linda); A. Ahmed (Alauddin); K. Akiyama (Koichi); R. Asif (Rasheed); T. Aung (Tin); I.E. Barroso (Inês); A. Bjonnes (Andrew); T.R. Braun (Timothy R.); H. Cai (Hui); L.-C. Chang (Li-Ching); C.-H. Chen; C-Y. Cheng (Ching-Yu); Y.-S. Chong (Yap-Seng); F.S. Collins (Francis); R. Courtney (Regina); G. Davies (Gail); G. Delgado; L.D. Do (Loi D.); P.A. Doevendans (Pieter); R.T. Gansevoort (Ron); Y. Gao; T.B. Grammer (Tanja B); N. Grarup (Niels); J. Grewal (Jagvir); D. Gu (D.); G. SWander (Gurpreet); A.L. Hartikainen; S.L. Hazen (Stanley); J. He (Jing); C.K. Heng (Chew-Kiat); E.J.A. Hixso (E. James Ames); A. Hofman (Albert); C. Hsu (Chris); W. Huang (Wei); L.L.N. Husemoen (Lise Lotte); J.-Y. Hwang (Joo-Yeon); S. Ichihara (Sahoko); M. Igase (Michiya); M. Isono (Masato); J.M. Justesen (Johanne M.); T. Katsuya (Tomohiro); M. GKibriya (Muhammad); Y.J. Kim; M. Kishimoto (Miyako); W.-P. Koh (Woon-Puay); K. Kohara (Katsuhiko); M. Kumari (Meena); K. Kwek (Kenneth); N.R. Lee (Nanette); J. Lee (Jeannette); J. Liao (Jie); W. Lieb (Wolfgang); D.C. Liewald (David C.); T. Matsubara (Tatsuaki); Y. Matsushita (Yumi); T. Meitinger (Thomas); E. Mihailov (Evelin); L. Milani (Lili); R. Mills (Rebecca); K. Mononen (Kari); M. Müller-Nurasyid (Martina); T. Nabika (Toru); E. Nakashima (Eitaro); H.K. Ng (Hong Kiat); K. Nikus (Kjell); T. Nutile; T. Ohkubo (Takayoshi); K. Ohnaka (Keizo); S. Parish (Sarah); L. Paternoster (Lavinia); H. Peng (Hao); A. Peters (Annette); S. TPham (Son); M.J. Pinidiyapathirage (Mohitha J.); M. Rahman (Mahfuzar); H. Rakugi (Hiromi); O. Rolandsson (Olov); M.A. Rozario (Michelle Ann); D. Ruggiero; C. Sala (Cinzia); R. Sarju (Ralhan); K. Shimokawa (Kazuro); H. Snieder (Harold); T. Sparsø (Thomas); W. Spiering (Wilko); J.M. Starr (John); D.J. Stott (David J.); D. OStram (Daniel); T. Sugiyama (Takao); S. Szymczak (Silke); W.H.W. Tang (W.H. Wilson); L. Tong (Lin); S. Trompet (Stella); V. Turjanmaa (Väinö); H. Ueshima (Hirotsugu); A.G. Uitterlinden (André); S. Umemura (Satoshi); M. Vaarasmaki (Marja); R.M. Dam (Rob Mvan); W.H. van Gilst (Wiek); D.J. van Veldhuisen (Dirk); J. Viikari (Jorma); M. Waldenberger (Melanie); Y. Wang (Yiqin); A. Wang (Aili); R. Wilson (Rory); T.Y. Wong (Tien Yin); Y.-B. Xiang (Yong-Bing); S. Yamaguchi (Shuhei); X. Ye (Xingwang); R. Young (Robin); T.L. Young (Terri); J.-M. Yuan (Jian-Min); X. Zhou (Xueya); F.W. Asselbergs (Folkert); M. Ciullo; R. Clarke (Robert); P. Deloukas (Panagiotis); A. Franke (Andre); W.F. Paul (W. Frank); S. Franks (Steve); Y. Friedlander (Yechiel); M.D. Gross (Myron D.); Z. Guo (Zhirong); T. Hansen (T.); M.-R. Jarvelin (Marjo-Riitta); T. Jørgensen (Torben); J.W. Jukema (Jan Wouter); M. Kähönen (Mika); H. Kajio (Hiroshi); M. Kivimaki (Mika); J.-Y. Lee (Jong-Young); T. Lehtimäki (Terho); A. Linneberg (Allan); T. Miki (Tetsuro); O. Pedersen (Oluf); N.J. Samani (Nilesh); T.I.A. Sørensen (Thorkild); R. Takayanagi (Ryoichi); D. Toniolo (Daniela); H. Ahsan (Habibul); H. Allayee (Hooman); Y.-T. Chen (Yuan-Tsong); J. Danesh (John); I.J. Deary (Ian J.); O.H. Franco (Oscar); L. Franke (Lude); B. THeijman (Bastiaan); J.D. Holbrook (Joanna D.); A.J. Isaacs (Aaron); B.-J. Kim (Bong-Jo); X. Lin (Xu); J. Liu (Jianjun); W. März (Winfried); A. Metspalu (Andres); K.L. Mohlke (Karen); K. Sangher; D. Harambir (Dharambir); X.-O. Shu (Xiao-Ou); J.B.J. van Meurs (Joyce); E.N. Vithana (Eranga); A.R. Wickremasinghe (Ananda); C. Wijmenga (Cisca); B.H.W. Wolffenbuttel (Bruce H.W.); M. Yokota (Mitsuhiro); W. Zheng (Wei); D. Zhu (Dingliang); P. Vineis (Paolo); S.A. Kyrtopoulos (Soterios A.); J.C.S. Kleinjans (Jos C.S.); M.I. McCarthy (Mark); R. Soong (Richie); C. Gieger (Christian); J. Scott (James); Y.Y. Teo (Yik Ying); J. He (Jiang); P. Elliott (Paul); E.S. Tai (Shyong); P. van der Harst (Pim); J.S. Kooner (Jaspal S.); J.C. Chambers (John)

2015-01-01

textabstractWe carried out a trans-ancestry genome-wide association and replication study of blood pressure phenotypes among up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 new loci to be associated with blood pressure (P = 3.9 × 10 -11 to

The humankind genome: from genetic diversity to the origin of human diseases.

Science.gov (United States)

Belizário, Jose E

2013-12-01

Genome-wide association studies have failed to establish common variant risk for the majority of common human diseases. The underlying reasons for this failure are explained by recent studies of resequencing and comparison of over 1200 human genomes and 10 000 exomes, together with the delineation of DNA methylation patterns (epigenome) and full characterization of coding and noncoding RNAs (transcriptome) being transcribed. These studies have provided the most comprehensive catalogues of functional elements and genetic variants that are now available for global integrative analysis and experimental validation in prospective cohort studies. With these datasets, researchers will have unparalleled opportunities for the alignment, mining, and testing of hypotheses for the roles of specific genetic variants, including copy number variations, single nucleotide polymorphisms, and indels as the cause of specific phenotypes and diseases. Through the use of next-generation sequencing technologies for genotyping and standardized ontological annotation to systematically analyze the effects of genomic variation on humans and model organism phenotypes, we will be able to find candidate genes and new clues for disease's etiology and treatment. This article describes essential concepts in genetics and genomic technologies as well as the emerging computational framework to comprehensively search websites and platforms available for the analysis and interpretation of genomic data.

Genomic Prediction and Association Mapping of Curd-Related Traits in Gene Bank Accessions of Cauliflower.

Science.gov (United States)

Thorwarth, Patrick; Yousef, Eltohamy A A; Schmid, Karl J

2018-02-02

Genetic resources are an important source of genetic variation for plant breeding. Genome-wide association studies (GWAS) and genomic prediction greatly facilitate the analysis and utilization of useful genetic diversity for improving complex phenotypic traits in crop plants. We explored the potential of GWAS and genomic prediction for improving curd-related traits in cauliflower ( Brassica oleracea var. botrytis ) by combining 174 randomly selected cauliflower gene bank accessions from two different gene banks. The collection was genotyped with genotyping-by-sequencing (GBS) and phenotyped for six curd-related traits at two locations and three growing seasons. A GWAS analysis based on 120,693 single-nucleotide polymorphisms identified a total of 24 significant associations for curd-related traits. The potential for genomic prediction was assessed with a genomic best linear unbiased prediction model and BayesB. Prediction abilities ranged from 0.10 to 0.66 for different traits and did not differ between prediction methods. Imputation of missing genotypes only slightly improved prediction ability. Our results demonstrate that GWAS and genomic prediction in combination with GBS and phenotyping of highly heritable traits can be used to identify useful quantitative trait loci and genotypes among genetically diverse gene bank material for subsequent utilization as genetic resources in cauliflower breeding. Copyright © 2018 Thorwarth et al.

Genomic Prediction and Association Mapping of Curd-Related Traits in Gene Bank Accessions of Cauliflower

Directory of Open Access Journals (Sweden)

Patrick Thorwarth

2018-02-01

Full Text Available Genetic resources are an important source of genetic variation for plant breeding. Genome-wide association studies (GWAS and genomic prediction greatly facilitate the analysis and utilization of useful genetic diversity for improving complex phenotypic traits in crop plants. We explored the potential of GWAS and genomic prediction for improving curd-related traits in cauliflower (Brassica oleracea var. botrytis by combining 174 randomly selected cauliflower gene bank accessions from two different gene banks. The collection was genotyped with genotyping-by-sequencing (GBS and phenotyped for six curd-related traits at two locations and three growing seasons. A GWAS analysis based on 120,693 single-nucleotide polymorphisms identified a total of 24 significant associations for curd-related traits. The potential for genomic prediction was assessed with a genomic best linear unbiased prediction model and BayesB. Prediction abilities ranged from 0.10 to 0.66 for different traits and did not differ between prediction methods. Imputation of missing genotypes only slightly improved prediction ability. Our results demonstrate that GWAS and genomic prediction in combination with GBS and phenotyping of highly heritable traits can be used to identify useful quantitative trait loci and genotypes among genetically diverse gene bank material for subsequent utilization as genetic resources in cauliflower breeding.

Genome privacy: challenges, technical approaches to mitigate risk, and ethical considerations in the United States

Science.gov (United States)

Wang, Shuang; Jiang, Xiaoqian; Singh, Siddharth; Marmor, Rebecca; Bonomi, Luca; Fox, Dov; Dow, Michelle; Ohno-Machado, Lucila

2016-01-01

Accessing and integrating human genomic data with phenotypes is important for biomedical research. Making genomic data accessible for research purposes, however, must be handled carefully to avoid leakage of sensitive individual information to unauthorized parties and improper use of data. In this article, we focus on data sharing within the scope of data accessibility for research. Current common practices to gain biomedical data access are strictly rule based, without a clear and quantitative measurement of the risk of privacy breaches. In addition, several types of studies require privacy-preserving linkage of genotype and phenotype information across different locations (e.g., genotypes stored in a sequencing facility and phenotypes stored in an electronic health record) to accelerate discoveries. The computer science community has developed a spectrum of techniques for data privacy and confidentiality protection, many of which have yet to be tested on real-world problems. In this article, we discuss clinical, technical, and ethical aspects of genome data privacy and confidentiality in the United States, as well as potential solutions for privacy-preserving genotype–phenotype linkage in biomedical research. PMID:27681358

Genome-wide association study identifies novel locus for neuroticism and shows polygenic association with Major Depressive Disorder

Science.gov (United States)

de Moor, Marleen H.M.; van den Berg, Stéphanie M.; Verweij, Karin J.H.; Krueger, Robert F.; Luciano, Michelle; Vasquez, Alejandro Arias; Matteson, Lindsay K.; Derringer, Jaime; Esko, Tõnu; Amin, Najaf; Gordon, Scott D.; Hansell, Narelle K.; Hart, Amy B.; Seppälä, Ilkka; Huffman, Jennifer E.; Konte, Bettina; Lahti, Jari; Lee, Minyoung; Miller, Mike; Nutile, Teresa; Tanaka, Toshiko; Teumer, Alexander; Viktorin, Alexander; Wedenoja, Juho; Abecasis, Goncalo R.; Adkins, Daniel E.; Agrawal, Arpana; Allik, Jüri; Appel, Katja; Bigdeli, Timothy B.; Busonero, Fabio; Campbell, Harry; Costa, Paul T.; Smith, George Davey; Davies, Gail; de Wit, Harriet; Ding, Jun; Engelhardt, Barbara E.; Eriksson, Johan G.; Fedko, Iryna O.; Ferrucci, Luigi; Franke, Barbara; Giegling, Ina; Grucza, Richard; Hartmann, Annette M.; Heath, Andrew C.; Heinonen, Kati; Henders, Anjali K.; Homuth, Georg; Hottenga, Jouke-Jan; Janzing, Joost; Jokela, Markus; Karlsson, Robert; Kemp, John P.; Kirkpatrick, Matthew G.; Latvala, Antti; Lehtimäki, Terho; Liewald, David C.; Madden, Pamela A.F.; Magri, Chiara; Magnusson, Patrik K.E.; Marten, Jonathan; Maschio, Andrea; Medland, Sarah E.; Mihailov, Evelin; Milaneschi, Yuri; Montgomery, Grant W.; Nauck, Matthias; Ouwens, Klaasjan G.; Palotie, Aarno; Pettersson, Erik; Polasek, Ozren; Qian, Yong; Pulkki-Råback, Laura; Raitakari, Olli T.; Realo, Anu; Rose, Richard J.; Ruggiero, Daniela; Schmidt, Carsten O.; Slutske, Wendy S.; Sorice, Rossella; Starr, John M.; Pourcain, Beate St; Sutin, Angelina R.; Timpson, Nicholas J.; Trochet, Holly; Vermeulen, Sita; Vuoksimaa, Eero; Widen, Elisabeth; Wouda, Jasper; Wright, Margaret J.; Zgaga, Lina; Scotland, Generation; Porteous, David; Minelli, Alessandra; Palmer, Abraham A.; Rujescu, Dan; Ciullo, Marina; Hayward, Caroline; Rudan, Igor; Metspalu, Andres; Kaprio, Jaakko; Deary, Ian J.; Räikkönen, Katri; Wilson, James F.; Keltikangas-Järvinen, Liisa; Bierut, Laura J.; Hettema, John M.; Grabe, Hans J.; van Duijn, Cornelia M.; Evans, David M.; Schlessinger, David; Pedersen, Nancy L.; Terracciano, Antonio; McGue, Matt; Penninx, Brenda W.J.H.; Martin, Nicholas G.; Boomsma, Dorret I.

2015-01-01

Importance Neuroticism is a personality trait that is briefly defined by emotional instability. It is a robust genetic risk factor for Major Depressive Disorder (MDD) and other psychiatric disorders. Hence, neuroticism is an important phenotype for psychiatric genetics. The Genetics of Personality Consortium (GPC) has created a resource for genome-wide association analyses of personality traits in over 63,000 participants (including MDD cases). Objective To identify genetic variants associated with neuroticism by performing a meta-analysis of genome-wide association (GWA) results based on 1000Genomes imputation, to evaluate if common genetic variants as assessed by Single Nucleotide Polymorphisms (SNPs) explain variation in neuroticism by estimating SNP-based heritability, and to examine whether SNPs that predict neuroticism also predict MDD. Setting 30 cohorts with genome-wide genotype, personality and MDD data from the GPC. Participants The study included 63,661 participants from 29 discovery cohorts and 9,786 participants from a replication cohort. Participants came from Europe, the United States or Australia. Main outcome measure(s) Neuroticism scores harmonized across all cohorts by Item Response Theory (IRT) analysis, and clinically assessed MDD case-control status. Results A genome-wide significant SNP was found in the MAGI1 gene (rs35855737; P=9.26 × 10−9 in the discovery meta-analysis, and P=2.38 × 10−8 in the meta-analysis of all 30 cohorts). Common genetic variants explain 15% of the variance in neuroticism. Polygenic scores based on the meta-analysis of neuroticism in 27 of the discovery cohorts significantly predicted neuroticism in 2 independent cohorts. Importantly, polygenic scores also predicted MDD in these cohorts. Conclusions and relevance This study identifies a novel locus for neuroticism. The variant is located in a known gene that has been associated with bipolar disorder and schizophrenia in previous studies. In addition, the study

The characterization of twenty sequenced human genomes.

Directory of Open Access Journals (Sweden)

Kimberly Pelak

2010-09-01

Full Text Available We present the analysis of twenty human genomes to evaluate the prospects for identifying rare functional variants that contribute to a phenotype of interest. We sequenced at high coverage ten "case" genomes from individuals with severe hemophilia A and ten "control" genomes. We summarize the number of genetic variants emerging from a study of this magnitude, and provide a proof of concept for the identification of rare and highly-penetrant functional variants by confirming that the cause of hemophilia A is easily recognizable in this data set. We also show that the number of novel single nucleotide variants (SNVs discovered per genome seems to stabilize at about 144,000 new variants per genome, after the first 15 individuals have been sequenced. Finally, we find that, on average, each genome carries 165 homozygous protein-truncating or stop loss variants in genes representing a diverse set of pathways.

H2DB: a heritability database across multiple species by annotating trait-associated genomic loci.

Science.gov (United States)

Kaminuma, Eli; Fujisawa, Takatomo; Tanizawa, Yasuhiro; Sakamoto, Naoko; Kurata, Nori; Shimizu, Tokurou; Nakamura, Yasukazu

2013-01-01

H2DB (http://tga.nig.ac.jp/h2db/), an annotation database of genetic heritability estimates for humans and other species, has been developed as a knowledge database to connect trait-associated genomic loci. Heritability estimates have been investigated for individual species, particularly in human twin studies and plant/animal breeding studies. However, there appears to be no comprehensive heritability database for both humans and other species. Here, we introduce an annotation database for genetic heritabilities of various species that was annotated by manually curating online public resources in PUBMED abstracts and journal contents. The proposed heritability database contains attribute information for trait descriptions, experimental conditions, trait-associated genomic loci and broad- and narrow-sense heritability specifications. Annotated trait-associated genomic loci, for which most are single-nucleotide polymorphisms derived from genome-wide association studies, may be valuable resources for experimental scientists. In addition, we assigned phenotype ontologies to the annotated traits for the purposes of discussing heritability distributions based on phenotypic classifications.

Multiple-Trait Genomic Selection Methods Increase Genetic Value Prediction Accuracy

Science.gov (United States)

Jia, Yi; Jannink, Jean-Luc

2012-01-01

Genetic correlations between quantitative traits measured in many breeding programs are pervasive. These correlations indicate that measurements of one trait carry information on other traits. Current single-trait (univariate) genomic selection does not take advantage of this information. Multivariate genomic selection on multiple traits could accomplish this but has been little explored and tested in practical breeding programs. In this study, three multivariate linear models (i.e., GBLUP, BayesA, and BayesCπ) were presented and compared to univariate models using simulated and real quantitative traits controlled by different genetic architectures. We also extended BayesA with fixed hyperparameters to a full hierarchical model that estimated hyperparameters and BayesCπ to impute missing phenotypes. We found that optimal marker-effect variance priors depended on the genetic architecture of the trait so that estimating them was beneficial. We showed that the prediction accuracy for a low-heritability trait could be significantly increased by multivariate genomic selection when a correlated high-heritability trait was available. Further, multiple-trait genomic selection had higher prediction accuracy than single-trait genomic selection when phenotypes are not available on all individuals and traits. Additional factors affecting the performance of multiple-trait genomic selection were explored. PMID:23086217

Relationship between Deleterious Variation, Genomic Autozygosity, and Disease Risk: Insights from The 1000 Genomes Project.

Science.gov (United States)

Pemberton, Trevor J; Szpiech, Zachary A

2018-04-05

Genomic regions of autozygosity (ROAs) represent segments of individual genomes that are homozygous for haplotypes inherited identical-by-descent (IBD) from a common ancestor. ROAs are nonuniformly distributed across the genome, and increased ROA levels are a reported risk factor for numerous complex diseases. Previously, we hypothesized that long ROAs are enriched for deleterious homozygotes as a result of young haplotypes with recent deleterious mutations-relatively untouched by purifying selection-being paired IBD as a consequence of recent parental relatedness, a pattern supported by ROA and whole-exome sequence data on 27 individuals. Here, we significantly bolster support for our hypothesis and expand upon our original analyses using ROA and whole-genome sequence data on 2,436 individuals from The 1000 Genomes Project. Considering CADD deleteriousness scores, we reaffirm our previous observation that long ROAs are enriched for damaging homozygotes worldwide. We show that strongly damaging homozygotes experience greater enrichment than weaker damaging homozygotes, while overall enrichment varies appreciably among populations. Mendelian disease genes and those encoding FDA-approved drug targets have significantly increased rates of gain in damaging homozygotes with increasing ROA coverage relative to all other genes. In genes implicated in eight complex phenotypes for which ROA levels have been identified as a risk factor, rates of gain in damaging homozygotes vary across phenotypes and populations but frequently differ significantly from non-disease genes. These findings highlight the potential confounding effects of population background in the assessment of associations between ROA levels and complex disease risk, which might underlie reported inconsistencies in ROA-phenotype associations. Copyright © 2018 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Correlation between phenotypic antibiotic susceptibility and the resistome in Pseudomonas aeruginosa.

Science.gov (United States)

Jaillard, Magali; van Belkum, Alex; Cady, Kyle C; Creely, David; Shortridge, Dee; Blanc, Bernadette; Barbu, E Magda; Dunne, W Michael; Zambardi, Gilles; Enright, Mark; Mugnier, Nathalie; Le Priol, Christophe; Schicklin, Stéphane; Guigon, Ghislaine; Veyrieras, Jean-Baptiste

2017-08-01

Genetic determinants of antibiotic resistance (AR) have been extensively investigated. High-throughput sequencing allows for the assessment of the relationship between genotype and phenotype. A panel of 672 Pseudomonas aeruginosa strains was analysed, including representatives of globally disseminated multidrug-resistant and extensively drug-resistant clones; genomes and multiple antibiograms were available. This panel was annotated for AR gene presence and polymorphism, defining a resistome in which integrons were included. Integrons were present in >70 distinct cassettes, with In5 being the most prevalent. Some cassettes closely associated with clonal complexes, whereas others spread across the phylogenetic diversity, highlighting the importance of horizontal transfer. A resistome-wide association study (RWAS) was performed for clinically relevant antibiotics by correlating the variability in minimum inhibitory concentration (MIC) values with resistome data. Resistome annotation identified 147 loci associated with AR. These loci consisted mainly of acquired genomic elements and intrinsic genes. The RWAS allowed for correct identification of resistance mechanisms for meropenem, amikacin, levofloxacin and cefepime, and added 46 novel mutations. Among these, 29 were variants of the oprD gene associated with variation in meropenem MIC. Using genomic and MIC data, phenotypic AR was successfully correlated with molecular determinants at the whole-genome sequence level. Copyright © 2017 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.

Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation

DEFF Research Database (Denmark)

Kato, Norihiro; Loh, Marie; Takeuchi, Fumihiko

2015-01-01

We carried out a trans-ancestry genome-wide association and replication study of blood pressure phenotypes among up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 new loci to be associated with blood pressure (P = 3.9 × 10(-11) to 5.0 × 10...

Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation

NARCIS (Netherlands)

Kato, Norihiro; Loh, Marie; Takeuchi, Fumihiko; Verweij, Niek; Wang, Xu; Zhang, Weihua; Kelly, Tanika N.; Saleheen, Danish; Lehne, Benjamin; Leach, Irene Mateo; Drong, Alexander W.; Abbott, James; Wahl, Simone; Tan, Sian-Tsung; Scott, William R.; Campanella, Gianluca; Chadeau-Hyam, Marc; Afzal, Uzma; Ahluwalia, Tarunveer S.; Bonder, Marc Jan; Chen, Peng; Dehghan, Abbas; Edwards, Todd L.; Esko, Tonu; Go, Min Jin; Harris, Sarah E.; Hartiala, Jaana; Kasela, Silva; Kasturiratne, Anuradhani; Khor, Chiea-Chuen; Kleber, Marcus E.; Li, Huaixing; Mok, Zuan Yu; Nakatochi, Masahiro; Sapari, Nur Sabrina; Saxena, Richa; Stewart, Alexandre F. R.; Stolk, Lisette; Tabara, Yasuharu; Teh, Ai Ling; Wu, Ying; Wu, Jer-Yuarn; Zhang, Yi; Aits, Imke; Alves, Alexessander Da Silva Couto; Das, Shikta; Dorajoo, Rajkumar; Hopewell, Jemma C.; Kim, Yun Kyoung; Koivula, Robert W.; Luan, Jian'an; Lyytikainen, Leo-Pekka; Nguyen, Quang N.; Pereira, Mark A.; Postmus, Iris; Raitakari, Olli T.; Bryan, Molly Scannell; Scott, Robert A.; Sorice, Rossella; Tragante, Vinicius; Traglia, Michela; White, Jon; Yamamoto, Ken; Zhang, Yonghong; Adair, Linda S.; Ahmed, Alauddin; Akiyama, Koichi; Asif, Rasheed; Aung, Tin; Barroso, Ines; Bjonnes, Andrew; Braun, Timothy R.; Cai, Hui; Chang, Li-Ching; Chen, Chien-Hsiun; Cheng, Ching-Yu; Chong, Yap-Seng; Collins, Rory; Courtney, Regina; Davies, Gail; Delgado, Graciela; Do, Loi D.; Doevendans, Pieter A.; Gansevoort, Ron T.; Gao, Yu-Tang; Grammer, Tanja B.; Grarup, Niels; Grewal, Jagvir; Gu, Dongfeng; Wander, Gurpreet S.; Hartikainen, Anna-Liisa; Hazen, Stanley L.; He, Jing; Heng, Chew-Kiat; Hixson, James E.; Hofman, Albert; Hsu, Chris; Huang, Wei; Husemoen, Lise L. N.; Hwang, Joo-Yeon; Ichihara, Sahoko; Igase, Michiya; Isono, Masato; Justesen, Johanne M.; Katsuy, Tomohiro; Kibriya, Muhammad G.; Kim, Young Jin; Kishimoto, Miyako; Koh, Woon-Puay; Kohara, Katsuhiko; Kumari, Meena; Kwek, Kenneth; Lee, Nanette R.; Lee, Jeannette; Liao, Jiemin; Lieb, Wolfgang; Liewald, David C. M.; Matsubara, Tatsuaki; Matsushita, Yumi; Meitinger, Thomas; Mihailov, Evelin; Milani, Lili; Mills, Rebecca; Mononen, Nina; Mueller-Nurasyid, Martina; Nabika, Toru; Nakashima, Eitaro; Ng, Hong Kiat; Nikus, Kjell; Nutile, Teresa; Ohkubo, Takayoshi; Ohnaka, Keizo; Parish, Sarah; Paternoster, Lavinia; Peng, Hao; Peters, Annette; Pham, Son T.; Pinidiyapathirage, Mohitha J.; Rahman, Mahfuzar; Rakugi, Hiromi; Rolandsson, Olov; Rozario, Michelle Ann; Ruggiero, Daniela; Sala, Cinzia F.; Sarju, Ralhan; Shimokawa, Kazuro; Snieder, Harold; Sparso, Thomas; Spiering, Wilko; Starr, John M.; Stott, David J.; Stram, Daniel O.; Sugiyama, Takao; Szymczak, Silke; Tang, W. H. Wilson; Tong, Lin; Trompet, Stella; Turjanmaa, Vaino; Ueshima, Hirotsugu; Uitterlinden, Andre G.; Umemura, Satoshi; Vaarasmaki, Marja; van Dam, Rob M.; van Gilst, Wiek H.; van Veldhuisen, Dirk J.; Viikari, Jorma S.; Waldenberger, Melanie; Wang, Yiqin; Wang, Aili; Wilson, Rory; Wong, Tien-Yin; Xiang, Yong-Bing; Yamaguchi, Shuhei; Ye, Xingwang; Young, Robin D.; Young, Terri L.; Yuan, Jian-Min; Zhou, Xueya; Asselbergs, Folkert W.; Ciullo, Marina; Clarke, Robert; Deloukas, Panos; Franke, Andre; Franks, Paul W.; Franks, Steve; Friedlander, Yechiel; Gross, Myron D.; Guo, Zhirong; Hansen, Torben; Jarvelin, Marjo-Riitta; Jorgensen, Torben; Jukema, J. Wouter; Kahonen, Mika; Kajio, Hiroshi; Kivimaki, Mika; Lee, Jong-Young; Lehtimaki, Terho; Linneberg, Allan; Miki, Tetsuro; Pedersen, Oluf; Samani, Nilesh J.; Sorensen, Thorkild I. A.; Takayanagi, Ryoichi; Toniolo, Daniela; Ahsan, Habibul; Allayee, Hooman; Chen, Yuan-Tsong; Danesh, John; Deary, Ian J.; Franco, Oscar H.; Franke, Lude; Heijman, Bastiaan T.; Holbrook, Joanna D.; Isaacs, Aaron; Kim, Bong-Jo; Lin, Xu; Liu, Jianjun; Maerz, Winfried; Metspalu, Andres; Mohlke, Karen L.; Sanghera, Dharambir K.; Shu, Xiao-Ou; van Meurs, Joyce B. J.; Vithana, Eranga; Wickremasinghe, Ananda R.; Wijmenga, Cisca; Wolffenbuttel, Bruce H. W.; Yokota, Mitsuhiro; Zheng, Wei; Zhu, Dingliang; Vineis, Paolo; Kyrtopoulos, Soterios A.; Kleinjans, Jos C. S.; McCarthy, Mark I.; Soong, Richie; Gieger, Christian; Scott, James; Teo, Yik-Ying; He, Jiang; Elliott, Paul; Tai, E. Shyong; van der Harst, Pim; Kooner, Jaspal S.; Chambers, John C.

2015-01-01

We carried out a trans-ancestry genome-wide association and replication study of blood pressure phenotypes among up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 new loci to be associated with blood pressure (P = 3.9 x 10(-11) to 5.0 x

A genome wide association study of Plasmodium falciparum susceptibility to 22 antimalarial drugs in Kenya.

Directory of Open Access Journals (Sweden)

Jason P Wendler

Full Text Available Drug resistance remains a chief concern for malaria control. In order to determine the genetic markers of drug resistant parasites, we tested the genome-wide associations (GWA of sequence-based genotypes from 35 Kenyan P. falciparum parasites with the activities of 22 antimalarial drugs.Parasites isolated from children with acute febrile malaria were adapted to culture, and sensitivity was determined by in vitro growth in the presence of anti-malarial drugs. Parasites were genotyped using whole genome sequencing techniques. Associations between 6250 single nucleotide polymorphisms (SNPs and resistance to individual anti-malarial agents were determined, with false discovery rate adjustment for multiple hypothesis testing. We identified expected associations in the pfcrt region with chloroquine (CQ activity, and other novel loci associated with amodiaquine, quinazoline, and quinine activities. Signals for CQ and primaquine (PQ overlap in and around pfcrt, and interestingly the phenotypes are inversely related for these two drugs. We catalog the variation in dhfr, dhps, mdr1, nhe, and crt, including novel SNPs, and confirm the presence of a dhfr-164L quadruple mutant in coastal Kenya. Mutations implicated in sulfadoxine-pyrimethamine resistance are at or near fixation in this sample set.Sequence-based GWA studies are powerful tools for phenotypic association tests. Using this approach on falciparum parasites from coastal Kenya we identified known and previously unreported genes associated with phenotypic resistance to anti-malarial drugs, and observe in high-resolution haplotype visualizations a possible signature of an inverse selective relationship between CQ and PQ.

Genomic and Functional Approaches to Understanding Cancer Aneuploidy.

Science.gov (United States)

Taylor, Alison M; Shih, Juliann; Ha, Gavin; Gao, Galen F; Zhang, Xiaoyang; Berger, Ashton C; Schumacher, Steven E; Wang, Chen; Hu, Hai; Liu, Jianfang; Lazar, Alexander J; Cherniack, Andrew D; Beroukhim, Rameen; Meyerson, Matthew

2018-04-09

Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was anti-correlated with expression of immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss of chromosome arm 3p in squamous cancers. We applied genome engineering to delete 3p in lung cells, causing decreased proliferation rescued in part by chromosome 3 duplication. This study defines genomic and phenotypic correlates of cancer aneuploidy and provides an experimental approach to study chromosome arm aneuploidy. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions1

Science.gov (United States)

Zuñiga, Cristal; Li, Chien-Ting; Zielinski, Daniel C.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Zengler, Karsten

2016-01-01

The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53 949)

Science.gov (United States)

Davies, G; Armstrong, N; Bis, J C; Bressler, J; Chouraki, V; Giddaluru, S; Hofer, E; Ibrahim-Verbaas, C A; Kirin, M; Lahti, J; van der Lee, S J; Le Hellard, S; Liu, T; Marioni, R E; Oldmeadow, C; Postmus, I; Smith, A V; Smith, J A; Thalamuthu, A; Thomson, R; Vitart, V; Wang, J; Yu, L; Zgaga, L; Zhao, W; Boxall, R; Harris, S E; Hill, W D; Liewald, D C; Luciano, M; Adams, H; Ames, D; Amin, N; Amouyel, P; Assareh, A A; Au, R; Becker, J T; Beiser, A; Berr, C; Bertram, L; Boerwinkle, E; Buckley, B M; Campbell, H; Corley, J; De Jager, P L; Dufouil, C; Eriksson, J G; Espeseth, T; Faul, J D; Ford, I; Scotland, Generation; Gottesman, R F; Griswold, M E; Gudnason, V; Harris, T B; Heiss, G; Hofman, A; Holliday, E G; Huffman, J; Kardia, S L R; Kochan, N; Knopman, D S; Kwok, J B; Lambert, J-C; Lee, T; Li, G; Li, S-C; Loitfelder, M; Lopez, O L; Lundervold, A J; Lundqvist, A; Mather, K A; Mirza, S S; Nyberg, L; Oostra, B A; Palotie, A; Papenberg, G; Pattie, A; Petrovic, K; Polasek, O; Psaty, B M; Redmond, P; Reppermund, S; Rotter, J I; Schmidt, H; Schuur, M; Schofield, P W; Scott, R J; Steen, V M; Stott, D J; van Swieten, J C; Taylor, K D; Trollor, J; Trompet, S; Uitterlinden, A G; Weinstein, G; Widen, E; Windham, B G; Jukema, J W; Wright, A F; Wright, M J; Yang, Q; Amieva, H; Attia, J R; Bennett, D A; Brodaty, H; de Craen, A J M; Hayward, C; Ikram, M A; Lindenberger, U; Nilsson, L-G; Porteous, D J; Räikkönen, K; Reinvang, I; Rudan, I; Sachdev, P S; Schmidt, R; Schofield, P R; Srikanth, V; Starr, J M; Turner, S T; Weir, D R; Wilson, J F; van Duijn, C; Launer, L; Fitzpatrick, A L; Seshadri, S; Mosley, T H; Deary, I J

2015-01-01

General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53 949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10−9, MIR2113; rs17522122, P=2.55 × 10−8, AKAP6; rs10119, P=5.67 × 10−9, APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10−6). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ~1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10−17). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer's disease: TOMM40, APOE, ABCG1 and MEF2C. PMID:25644384

Clinical utilization of genomics data produced by the international Pseudomonas aeruginosa consortium

DEFF Research Database (Denmark)

Freschi, Luca; Jeukens, Julie; Kukavica-Ibrulj, Irena

2015-01-01

The International Pseudomonas aeruginosa Consortium is sequencing over 1000 genomes and building an analysis pipeline for the study of Pseudomonas genome evolution, antibiotic resistance and virulence genes. Metadata, including genomic and phenotypic data for each isolate of the collection, are a...... implicated in human and animal infections, understand how patients become infected and how the infection evolves over time as well as identify prognostic markers for better evidence-based decisions on patient care....

High-throughput phenotyping allows for QTL analysis of defense, symbiosis and development-related traits

DEFF Research Database (Denmark)

Hansen, Nina Eberhardtsen

-throughput phenotyping of whole plants. Additionally, a system for automated confocal microscopy aiming at automated detection of infection thread formation as well as detection of lateral root and nodule primordia is being developed. The objective was to use both systems in genome wide association studies and mutant...... the analysis. Additional phenotyping of defense mutants revealed that MLO, which confers susceptibility towards Blumeria graminis in barley, is also a prime candidate for a S. trifoliorum susceptibility gene in Lotus....

Harnessing CRISPR-Cas systems for bacterial genome editing.

Science.gov (United States)

Selle, Kurt; Barrangou, Rodolphe

2015-04-01

Manipulation of genomic sequences facilitates the identification and characterization of key genetic determinants in the investigation of biological processes. Genome editing via clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated (Cas) constitutes a next-generation method for programmable and high-throughput functional genomics. CRISPR-Cas systems are readily reprogrammed to induce sequence-specific DNA breaks at target loci, resulting in fixed mutations via host-dependent DNA repair mechanisms. Although bacterial genome editing is a relatively unexplored and underrepresented application of CRISPR-Cas systems, recent studies provide valuable insights for the widespread future implementation of this technology. This review summarizes recent progress in bacterial genome editing and identifies fundamental genetic and phenotypic outcomes of CRISPR targeting in bacteria, in the context of tool development, genome homeostasis, and DNA repair. Copyright © 2015 Elsevier Ltd. All rights reserved.

Integrating Nonadditive Genomic Relationship Matrices into the Study of Genetic Architecture of Complex Traits.

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Nazarian, Alireza; Gezan, Salvador A

2016-03-01

The study of genetic architecture of complex traits has been dramatically influenced by implementing genome-wide analytical approaches during recent years. Of particular interest are genomic prediction strategies which make use of genomic information for predicting phenotypic responses instead of detecting trait-associated loci. In this work, we present the results of a simulation study to improve our understanding of the statistical properties of estimation of genetic variance components of complex traits, and of additive, dominance, and genetic effects through best linear unbiased prediction methodology. Simulated dense marker information was used to construct genomic additive and dominance matrices, and multiple alternative pedigree- and marker-based models were compared to determine if including a dominance term into the analysis may improve the genetic analysis of complex traits. Our results showed that a model containing a pedigree- or marker-based additive relationship matrix along with a pedigree-based dominance matrix provided the best partitioning of genetic variance into its components, especially when some degree of true dominance effects was expected to exist. Also, we noted that the use of a marker-based additive relationship matrix along with a pedigree-based dominance matrix had the best performance in terms of accuracy of correlations between true and estimated additive, dominance, and genetic effects. © The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Improving accuracy of genomic prediction in Brangus cattle by adding animals with imputed low-density SNP genotypes.

Science.gov (United States)

Lopes, F B; Wu, X-L; Li, H; Xu, J; Perkins, T; Genho, J; Ferretti, R; Tait, R G; Bauck, S; Rosa, G J M

2018-02-01

Reliable genomic prediction of breeding values for quantitative traits requires the availability of sufficient number of animals with genotypes and phenotypes in the training set. As of 31 October 2016, there were 3,797 Brangus animals with genotypes and phenotypes. These Brangus animals were genotyped using different commercial SNP chips. Of them, the largest group consisted of 1,535 animals genotyped by the GGP-LDV4 SNP chip. The remaining 2,262 genotypes were imputed to the SNP content of the GGP-LDV4 chip, so that the number of animals available for training the genomic prediction models was more than doubled. The present study showed that the pooling of animals with both original or imputed 40K SNP genotypes substantially increased genomic prediction accuracies on the ten traits. By supplementing imputed genotypes, the relative gains in genomic prediction accuracies on estimated breeding values (EBV) were from 12.60% to 31.27%, and the relative gain in genomic prediction accuracies on de-regressed EBV was slightly small (i.e. 0.87%-18.75%). The present study also compared the performance of five genomic prediction models and two cross-validation methods. The five genomic models predicted EBV and de-regressed EBV of the ten traits similarly well. Of the two cross-validation methods, leave-one-out cross-validation maximized the number of animals at the stage of training for genomic prediction. Genomic prediction accuracy (GPA) on the ten quantitative traits was validated in 1,106 newly genotyped Brangus animals based on the SNP effects estimated in the previous set of 3,797 Brangus animals, and they were slightly lower than GPA in the original data. The present study was the first to leverage currently available genotype and phenotype resources in order to harness genomic prediction in Brangus beef cattle. © 2018 Blackwell Verlag GmbH.

Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

Science.gov (United States)

Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

2016-09-01

The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. © 2016 American Society of Plant Biologists. All rights reserved.

Improving the baking quality of bread wheat by genomic selection in early generations.

Science.gov (United States)

Michel, Sebastian; Kummer, Christian; Gallee, Martin; Hellinger, Jakob; Ametz, Christian; Akgöl, Batuhan; Epure, Doru; Löschenberger, Franziska; Buerstmayr, Hermann

2018-02-01

Genomic selection shows great promise for pre-selecting lines with superior bread baking quality in early generations, 3 years ahead of labour-intensive, time-consuming, and costly quality analysis. The genetic improvement of baking quality is one of the grand challenges in wheat breeding as the assessment of the associated traits often involves time-consuming, labour-intensive, and costly testing forcing breeders to postpone sophisticated quality tests to the very last phases of variety development. The prospect of genomic selection for complex traits like grain yield has been shown in numerous studies, and might thus be also an interesting method to select for baking quality traits. Hence, we focused in this study on the accuracy of genomic selection for laborious and expensive to phenotype quality traits as well as its selection response in comparison with phenotypic selection. More than 400 genotyped wheat lines were, therefore, phenotyped for protein content, dough viscoelastic and mixing properties related to baking quality in multi-environment trials 2009-2016. The average prediction accuracy across three independent validation populations was r = 0.39 and could be increased to r = 0.47 by modelling major QTL as fixed effects as well as employing multi-trait prediction models, which resulted in an acceptable prediction accuracy for all dough rheological traits (r = 0.38-0.63). Genomic selection can furthermore be applied 2-3 years earlier than direct phenotypic selection, and the estimated selection response was nearly twice as high in comparison with indirect selection by protein content for baking quality related traits. This considerable advantage of genomic selection could accordingly support breeders in their selection decisions and aid in efficiently combining superior baking quality with grain yield in newly developed wheat varieties.

Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies

Directory of Open Access Journals (Sweden)

Qiong Yang

2012-01-01

Full Text Available Multivariate phenotypes are frequently encountered in genetic association studies. The purpose of analyzing multivariate phenotypes usually includes discovery of novel genetic variants of pleiotropy effects, that is, affecting multiple phenotypes, and the ultimate goal of uncovering the underlying genetic mechanism. In recent years, there have been new method development and application of existing statistical methods to such phenotypes. In this paper, we provide a review of the available methods for analyzing association between a single marker and a multivariate phenotype consisting of the same type of components (e.g., all continuous or all categorical or different types of components (e.g., some are continuous and others are categorical. We also reviewed causal inference methods designed to test whether the detected association with the multivariate phenotype is truly pleiotropy or the genetic marker exerts its effects on some phenotypes through affecting the others.

SNPpy--database management for SNP data from genome wide association studies.

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Faheem Mitha

Full Text Available BACKGROUND: We describe SNPpy, a hybrid script database system using the Python SQLAlchemy library coupled with the PostgreSQL database to manage genotype data from Genome-Wide Association Studies (GWAS. This system makes it possible to merge study data with HapMap data and merge across studies for meta-analyses, including data filtering based on the values of phenotype and Single-Nucleotide Polymorphism (SNP data. SNPpy and its dependencies are open source software. RESULTS: The current version of SNPpy offers utility functions to import genotype and annotation data from two commercial platforms. We use these to import data from two GWAS studies and the HapMap Project. We then export these individual datasets to standard data format files that can be imported into statistical software for downstream analyses. CONCLUSIONS: By leveraging the power of relational databases, SNPpy offers integrated management and manipulation of genotype and phenotype data from GWAS studies. The analysis of these studies requires merging across GWAS datasets as well as patient and marker selection. To this end, SNPpy enables the user to filter the data and output the results as standardized GWAS file formats. It does low level and flexible data validation, including validation of patient data. SNPpy is a practical and extensible solution for investigators who seek to deploy central management of their GWAS data.

Partitioning of genomic variance using biological pathways

DEFF Research Database (Denmark)

Edwards, Stefan McKinnon; Janss, Luc; Madsen, Per

and that these variants are enriched for genes that are connected in biological pathways or for likely functional effects on genes. These biological findings provide valuable insight for developing better genomic models. These are statistical models for predicting complex trait phenotypes on the basis of SNP......-data and trait phenotypes and can account for a much larger fraction of the heritable component. A disadvantage is that this “black-box” modelling approach conceals the biological mechanisms underlying the trait. We propose to open the “black-box” by building SNP-set genomic models that evaluate the collective...... action of multiple SNPs in genes, biological pathways or other external findings on the trait phenotype. As proof of concept we have tested the modelling framework on several traits in dairy cattle....

Characterizing visible and invisible cell wall mutant phenotypes

Energy Technology Data Exchange (ETDEWEB)

Carpita, Nicholas C.; McCann, Maureen C.

2015-04-06

About 10% of a plant's genome is devoted to generating the protein machinery to synthesize, remodel, and deconstruct the cell wall. High-throughput genome sequencing technologies have enabled a reasonably complete inventory of wall-related genes that can be assembled into families of common evolutionary origin. Assigning function to each gene family member has been aided immensely by identification of mutants with visible phenotypes or by chemical and spectroscopic analysis of mutants with ‘invisible’ phenotypes of modified cell wall composition and architecture that do not otherwise affect plant growth or development. This review connects the inference of gene function on the basis of deviation from the wild type in genetic functional analyses to insights provided by modern analytical techniques that have brought us ever closer to elucidating the sequence structures of the major polysaccharide components of the plant cell wall.

Whole-genome sequencing analysis of phenotypic heterogeneity and anticipation in Li-Fraumeni cancer predisposition syndrome.

Science.gov (United States)

Ariffin, Hany; Hainaut, Pierre; Puzio-Kuter, Anna; Choong, Soo Sin; Chan, Adelyne Sue Li; Tolkunov, Denis; Rajagopal, Gunaretnam; Kang, Wenfeng; Lim, Leon Li Wen; Krishnan, Shekhar; Chen, Kok-Siong; Achatz, Maria Isabel; Karsa, Mawar; Shamsani, Jannah; Levine, Arnold J; Chan, Chang S

2014-10-28

The Li-Fraumeni syndrome (LFS) and its variant form (LFL) is a familial predisposition to multiple forms of childhood, adolescent, and adult cancers associated with germ-line mutation in the TP53 tumor suppressor gene. Individual disparities in tumor patterns are compounded by acceleration of cancer onset with successive generations. It has been suggested that this apparent anticipation pattern may result from germ-line genomic instability in TP53 mutation carriers, causing increased DNA copy-number variations (CNVs) with successive generations. To address the genetic basis of phenotypic disparities of LFS/LFL, we performed whole-genome sequencing (WGS) of 13 subjects from two generations of an LFS kindred. Neither de novo CNV nor significant difference in total CNV was detected in relation with successive generations or with age at cancer onset. These observations were consistent with an experimental mouse model system showing that trp53 deficiency in the germ line of father or mother did not increase CNV occurrence in the offspring. On the other hand, individual records on 1,771 TP53 mutation carriers from 294 pedigrees were compiled to assess genetic anticipation patterns (International Agency for Research on Cancer TP53 database). No strictly defined anticipation pattern was observed. Rather, in multigeneration families, cancer onset was delayed in older compared with recent generations. These observations support an alternative model for apparent anticipation in which rare variants from noncarrier parents may attenuate constitutive resistance to tumorigenesis in the offspring of TP53 mutation carriers with late cancer onset.

A Genome-Wide Landscape of Retrocopies in Primate Genomes.

Science.gov (United States)

Navarro, Fábio C P; Galante, Pedro A F

2015-07-29

Gene duplication is a key factor contributing to phenotype diversity across and within species. Although the availability of complete genomes has led to the extensive study of genomic duplications, the dynamics and variability of gene duplications mediated by retrotransposition are not well understood. Here, we predict mRNA retrotransposition and use comparative genomics to investigate their origin and variability across primates. Analyzing seven anthropoid primate genomes, we found a similar number of mRNA retrotranspositions (∼7,500 retrocopies) in Catarrhini (Old Word Monkeys, including humans), but a surprising large number of retrocopies (∼10,000) in Platyrrhini (New World Monkeys), which may be a by-product of higher long interspersed nuclear element 1 activity in these genomes. By inferring retrocopy orthology, we dated most of the primate retrocopy origins, and estimated a decrease in the fixation rate in recent primate history, implying a smaller number of species-specific retrocopies. Moreover, using RNA-Seq data, we identified approximately 3,600 expressed retrocopies. As expected, most of these retrocopies are located near or within known genes, present tissue-specific and even species-specific expression patterns, and no expression correlation to their parental genes. Taken together, our results provide further evidence that mRNA retrotransposition is an active mechanism in primate evolution and suggest that retrocopies may not only introduce great genetic variability between lineages but also create a large reservoir of potentially functional new genomic loci in primate genomes. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Integration of curated databases to identify genotype-phenotype associations

Directory of Open Access Journals (Sweden)

Li Jianrong

2006-10-01

Full Text Available Abstract Background The ability to rapidly characterize an unknown microorganism is critical in both responding to infectious disease and biodefense. To do this, we need some way of anticipating an organism's phenotype based on the molecules encoded by its genome. However, the link between molecular composition (i.e. genotype and phenotype for microbes is not obvious. While there have been several studies that address this challenge, none have yet proposed a large-scale method integrating curated biological information. Here we utilize a systematic approach to discover genotype-phenotype associations that combines phenotypic information from a biomedical informatics database, GIDEON, with the molecular information contained in National Center for Biotechnology Information's Clusters of Orthologous Groups database (NCBI COGs. Results Integrating the information in the two databases, we are able to correlate the presence or absence of a given protein in a microbe with its phenotype as measured by certain morphological characteristics or survival in a particular growth media. With a 0.8 correlation score threshold, 66% of the associations found were confirmed by the literature and at a 0.9 correlation threshold, 86% were positively verified. Conclusion Our results suggest possible phenotypic manifestations for proteins biochemically associated with sugar metabolism and electron transport. Moreover, we believe our approach can be extended to linking pathogenic phenotypes with functionally related proteins.

Genomic diversity within the Enterobacter cloacae complex.

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Armand Paauw

Full Text Available BACKGROUND: Isolates of the Enterobacter cloacae complex have been increasingly isolated as nosocomial pathogens, but phenotypic identification of the E. cloacae complex is unreliable and irreproducible. Identification of species based on currently available genotyping tools is already superior to phenotypic identification, but the taxonomy of isolates belonging to this complex is cumbersome. METHODOLOGY/PRINCIPAL FINDINGS: This study shows that multilocus sequence analysis and comparative genomic hybridization based on a mixed genome array is a powerful method for studying species assignment within the E. cloacae complex. The E. cloacae complex is shown to be evolutionarily divided into two clades that are genetically distinct from each other. The younger first clade is genetically more homogenous, contains the Enterobacter hormaechei species and is the most frequently cultured Enterobacter species in hospitals. The second and older clade consists of several (subspecies that are genetically more heterogeneous. Genetic markers were identified that could discriminate between the two clades and cluster 1. CONCLUSIONS/SIGNIFICANCE: Based on genomic differences it is concluded that some previously defined (clonal and heterogenic (subspecies of the E. cloacae complex have to be redefined because of disagreements with known or proposed nomenclature. However, further improved identification of the redefined species will be possible based on novel markers presented here.

Genomic heritabilities and genomic estimated breeding values for methane traits in Angus cattle.

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Hayes, B J; Donoghue, K A; Reich, C M; Mason, B A; Bird-Gardiner, T; Herd, R M; Arthur, P F

2016-03-01

Enteric methane emissions from beef cattle are a significant component of total greenhouse gas emissions from agriculture. The variation between beef cattle in methane emissions is partly genetic, whether measured as methane production, methane yield (methane production/DMI), or residual methane production (observed methane production - expected methane production), with heritabilities ranging from 0.19 to 0.29. This suggests methane emissions could be reduced by selection. Given the high cost of measuring methane production from individual beef cattle, genomic selection is the most feasible approach to achieve this reduction in emissions. We derived genomic EBV (GEBV) for methane traits from a reference set of 747 Angus animals phenotyped for methane traits and genotyped for 630,000 SNP. The accuracy of GEBV was tested in a validation set of 273 Angus animals phenotyped for the same traits. Accuracies of GEBV ranged from 0.29 ± 0.06 for methane yield and 0.35 ± 0.06 for residual methane production. Selection on GEBV using the genomic prediction equations derived here could reduce emissions for Angus cattle by roughly 5% over 10 yr.

Salmon and steelhead genetics and genomics - Epigenetic and genomic variation in salmon and steelhead

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National Oceanic and Atmospheric Administration, Department of Commerce — Conduct analyses of epigenetic and genomic variation in Chinook salmon and steelhead to determine influence on phenotypic expression of life history traits. Genetic,...

The phenotypic manifestations of rare genic CNVs in autism spectrum disorder.

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Merikangas, A K; Segurado, R; Heron, E A; Anney, R J L; Paterson, A D; Cook, E H; Pinto, D; Scherer, S W; Szatmari, P; Gill, M; Corvin, A P; Gallagher, L

2015-11-01

Significant evidence exists for the association between copy number variants (CNVs) and Autism Spectrum Disorder (ASD); however, most of this work has focused solely on the diagnosis of ASD. There is limited understanding of the impact of CNVs on the 'sub-phenotypes' of ASD. The objective of this paper is to evaluate associations between CNVs in differentially brain expressed (DBE) genes or genes previously implicated in ASD/intellectual disability (ASD/ID) and specific sub-phenotypes of ASD. The sample consisted of 1590 cases of European ancestry from the Autism Genome Project (AGP) with a diagnosis of an ASD and at least one rare CNV impacting any gene and a core set of phenotypic measures, including symptom severity, language impairments, seizures, gait disturbances, intelligence quotient (IQ) and adaptive function, as well as paternal and maternal age. Classification analyses using a non-parametric recursive partitioning method (random forests) were employed to define sets of phenotypic characteristics that best classify the CNV-defined groups. There was substantial variation in the classification accuracy of the two sets of genes. The best variables for classification were verbal IQ for the ASD/ID genes, paternal age at birth for the DBE genes and adaptive function for de novo CNVs. CNVs in the ASD/ID list were primarily associated with communication and language domains, whereas CNVs in DBE genes were related to broader manifestations of adaptive function. To our knowledge, this is the first study to examine the associations between sub-phenotypes and CNVs genome-wide in ASD. This work highlights the importance of examining the diverse sub-phenotypic manifestations of CNVs in ASD, including the specific features, comorbid conditions and clinical correlates of ASD that comprise underlying characteristics of the disorder.

TU-CD-BRB-07: Identification of Associations Between Radiologist-Annotated Imaging Features and Genomic Alterations in Breast Invasive Carcinoma, a TCGA Phenotype Research Group Study

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Rao, A; Net, J [University of Miami, Miami, Florida (United States); Brandt, K [Mayo Clinic, Rochester, Minnesota (United States); Huang, E [National Cancer Institute, NIH, Bethesda, MD (United States); Freymann, J; Kirby, J [Leidos Biomedical Research Inc., Frederick, MD (United States); Burnside, E [University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (United States); Morris, E; Sutton, E [Memorial Sloan Kettering Cancer Center, New York, NY (United States); Bonaccio, E [Roswell Park Cancer Institute, Buffalo, NY (United States); Giger, M; Jaffe, C [Univ Chicago, Chicago, IL (United States); Ganott, M; Zuley, M [University of Pittsburgh Medical Center - Magee Womens Hospital, Pittsburgh, Pennsylvania (United States); Le-Petross, H [MD Anderson Cancer Center, Houston, TX (United States); Dogan, B [UT MDACC, Houston, TX (United States); Whitman, G [UTMDACC, Houston, TX (United States)

2015-06-15

Purpose: To determine associations between radiologist-annotated MRI features and genomic measurements in breast invasive carcinoma (BRCA) from the Cancer Genome Atlas (TCGA). Methods: 98 TCGA patients with BRCA were assessed by a panel of radiologists (TCGA Breast Phenotype Research Group) based on a variety of mass and non-mass features according to the Breast Imaging Reporting and Data System (BI-RADS). Batch corrected gene expression data was obtained from the TCGA Data Portal. The Kruskal-Wallis test was used to assess correlations between categorical image features and tumor-derived genomic features (such as gene pathway activity, copy number and mutation characteristics). Image-derived features were also correlated with estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2/neu) status. Multiple hypothesis correction was done using Benjamini-Hochberg FDR. Associations at an FDR of 0.1 were selected for interpretation. Results: ER status was associated with rim enhancement and peritumoral edema. PR status was associated with internal enhancement. Several components of the PI3K/Akt pathway were associated with rim enhancement as well as heterogeneity. In addition, several components of cell cycle regulation and cell division were associated with imaging characteristics.TP53 and GATA3 mutations were associated with lesion size. MRI features associated with TP53 mutation status were rim enhancement and peritumoral edema. Rim enhancement was associated with activity of RB1, PIK3R1, MAP3K1, AKT1,PI3K, and PIK3CA. Margin status was associated with HIF1A/ARNT, Ras/ GTP/PI3K, KRAS, and GADD45A. Axillary lymphadenopathy was associated with RB1 and BCL2L1. Peritumoral edema was associated with Aurora A/GADD45A, BCL2L1, CCNE1, and FOXA1. Heterogeneous internal nonmass enhancement was associated with EGFR, PI3K, AKT1, HF/MET, and EGFR/Erbb4/neuregulin 1. Diffuse nonmass enhancement was associated with HGF/MET/MUC20/SHIP

Comparative Genomic and Functional Analysis of 100 Lactobacillus rhamnosus Strains and Their Comparison with Strain GG

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Pietilä, Taija E.; Järvinen, Hanna M.; Messing, Marcel; Randazzo, Cinzia L.; Paulin, Lars; Laine, Pia; Ritari, Jarmo; Caggia, Cinzia; Lähteinen, Tanja; Brouns, Stan J. J.; Satokari, Reetta; von Ossowski, Ingemar; Reunanen, Justus; Palva, Airi; de Vos, Willem M.

2013-01-01

Lactobacillus rhamnosus is a lactic acid bacterium that is found in a large variety of ecological habitats, including artisanal and industrial dairy products, the oral cavity, intestinal tract or vagina. To gain insights into the genetic complexity and ecological versatility of the species L. rhamnosus, we examined the genomes and phenotypes of 100 L. rhamnosus strains isolated from diverse sources. The genomes of 100 L. rhamnosus strains were mapped onto the L. rhamnosus GG reference genome. These strains were phenotypically characterized for a wide range of metabolic, antagonistic, signalling and functional properties. Phylogenomic analysis showed multiple groupings of the species that could partly be associated with their ecological niches. We identified 17 highly variable regions that encode functions related to lifestyle, i.e. carbohydrate transport and metabolism, production of mucus-binding pili, bile salt resistance, prophages and CRISPR adaptive immunity. Integration of the phenotypic and genomic data revealed that some L. rhamnosus strains possibly resided in multiple niches, illustrating the dynamics of bacterial habitats. The present study showed two distinctive geno-phenotypes in the L. rhamnosus species. The geno-phenotype A suggests an adaptation to stable nutrient-rich niches, i.e. milk-derivative products, reflected by the alteration or loss of biological functions associated with antimicrobial activity spectrum, stress resistance, adaptability and fitness to a distinctive range of habitats. In contrast, the geno-phenotype B displays adequate traits to a variable environment, such as the intestinal tract, in terms of nutrient resources, bacterial population density and host effects. PMID:23966868

Comparative genomic and functional analysis of 100 Lactobacillus rhamnosus strains and their comparison with strain GG.

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François P Douillard

Full Text Available Lactobacillus rhamnosus is a lactic acid bacterium that is found in a large variety of ecological habitats, including artisanal and industrial dairy products, the oral cavity, intestinal tract or vagina. To gain insights into the genetic complexity and ecological versatility of the species L. rhamnosus, we examined the genomes and phenotypes of 100 L. rhamnosus strains isolated from diverse sources. The genomes of 100 L. rhamnosus strains were mapped onto the L. rhamnosus GG reference genome. These strains were phenotypically characterized for a wide range of metabolic, antagonistic, signalling and functional properties. Phylogenomic analysis showed multiple groupings of the species that could partly be associated with their ecological niches. We identified 17 highly variable regions that encode functions related to lifestyle, i.e. carbohydrate transport and metabolism, production of mucus-binding pili, bile salt resistance, prophages and CRISPR adaptive immunity. Integration of the phenotypic and genomic data revealed that some L. rhamnosus strains possibly resided in multiple niches, illustrating the dynamics of bacterial habitats. The present study showed two distinctive geno-phenotypes in the L. rhamnosus species. The geno-phenotype A suggests an adaptation to stable nutrient-rich niches, i.e. milk-derivative products, reflected by the alteration or loss of biological functions associated with antimicrobial activity spectrum, stress resistance, adaptability and fitness to a distinctive range of habitats. In contrast, the geno-phenotype B displays adequate traits to a variable environment, such as the intestinal tract, in terms of nutrient resources, bacterial population density and host effects.

BGD: a database of bat genomes.

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Fang, Jianfei; Wang, Xuan; Mu, Shuo; Zhang, Shuyi; Dong, Dong

2015-01-01

Bats account for ~20% of mammalian species, and are the only mammals with true powered flight. For the sake of their specialized phenotypic traits, many researches have been devoted to examine the evolution of bats. Until now, some whole genome sequences of bats have been assembled and annotated, however, a uniform resource for the annotated bat genomes is still unavailable. To make the extensive data associated with the bat genomes accessible to the general biological communities, we established a Bat Genome Database (BGD). BGD is an open-access, web-available portal that integrates available data of bat genomes and genes. It hosts data from six bat species, including two megabats and four microbats. Users can query the gene annotations using efficient searching engine, and it offers browsable tracks of bat genomes. Furthermore, an easy-to-use phylogenetic analysis tool was also provided to facilitate online phylogeny study of genes. To the best of our knowledge, BGD is the first database of bat genomes. It will extend our understanding of the bat evolution and be advantageous to the bat sequences analysis. BGD is freely available at: http://donglab.ecnu.edu.cn/databases/BatGenome/.

BGD: a database of bat genomes.

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Jianfei Fang

Full Text Available Bats account for ~20% of mammalian species, and are the only mammals with true powered flight. For the sake of their specialized phenotypic traits, many researches have been devoted to examine the evolution of bats. Until now, some whole genome sequences of bats have been assembled and annotated, however, a uniform resource for the annotated bat genomes is still unavailable. To make the extensive data associated with the bat genomes accessible to the general biological communities, we established a Bat Genome Database (BGD. BGD is an open-access, web-available portal that integrates available data of bat genomes and genes. It hosts data from six bat species, including two megabats and four microbats. Users can query the gene annotations using efficient searching engine, and it offers browsable tracks of bat genomes. Furthermore, an easy-to-use phylogenetic analysis tool was also provided to facilitate online phylogeny study of genes. To the best of our knowledge, BGD is the first database of bat genomes. It will extend our understanding of the bat evolution and be advantageous to the bat sequences analysis. BGD is freely available at: http://donglab.ecnu.edu.cn/databases/BatGenome/.

Are we Genomic Mosaics? Variations of the Genome of Somatic Cells can Contribute to Diversify our Phenotypes.

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Astolfi, P A; Salamini, F; Sgaramella, V

2010-09-01

Theoretical and experimental evidences support the hypothesis that the genomes and the epigenomes may be different in the somatic cells of complex organisms. In the genome, the differences range from single base substitutions to chromosome number; in the epigenome, they entail multiple postsynthetic modifications of the chromatin. Somatic genome variations (SGV) may accumulate during development in response both to genetic programs, which may differ from tissue to tissue, and to environmental stimuli, which are often undetected and generally irreproducible. SGV may jeopardize physiological cellular functions, but also create novel coding and regulatory sequences, to be exposed to intraorganismal Darwinian selection. Genomes acknowledged as comparatively poor in genes, such as humans', could thus increase their pristine informational endowment. A better understanding of SGV will contribute to basic issues such as the "nature vs nurture" dualism and the inheritance of acquired characters. On the applied side, they may explain the low yield of cloning via somatic cell nuclear transfer, provide clues to some of the problems associated with transdifferentiation, and interfere with individual DNA analysis. SGV may be unique in the different cells types and in the different developmental stages, and thus explain the several hundred gaps persisting in the human genomes "completed" so far. They may compound the variations associated to our epigenomes and make of each of us an "(epi)genomic" mosaic. An ensuing paradigm is the possibility that a single genome (the ephemeral one assembled at fertilization) has the capacity to generate several different brains in response to different environments.

Tissue-specific functional networks for prioritizing phenotype and disease genes.

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Yuanfang Guan

Full Text Available Integrated analyses of functional genomics data have enormous potential for identifying phenotype-associated genes. Tissue-specificity is an important aspect of many genetic diseases, reflecting the potentially different roles of proteins and pathways in diverse cell lineages. Accounting for tissue specificity in global integration of functional genomics data is challenging, as "functionality" and "functional relationships" are often not resolved for specific tissue types. We address this challenge by generating tissue-specific functional networks, which can effectively represent the diversity of protein function for more accurate identification of phenotype-associated genes in the laboratory mouse. Specifically, we created 107 tissue-specific functional relationship networks through integration of genomic data utilizing knowledge of tissue-specific gene expression patterns. Cross-network comparison revealed significantly changed genes enriched for functions related to specific tissue development. We then utilized these tissue-specific networks to predict genes associated with different phenotypes. Our results demonstrate that prediction performance is significantly improved through using the tissue-specific networks as compared to the global functional network. We used a testis-specific functional relationship network to predict genes associated with male fertility and spermatogenesis phenotypes, and experimentally confirmed one top prediction, Mbyl1. We then focused on a less-common genetic disease, ataxia, and identified candidates uniquely predicted by the cerebellum network, which are supported by both literature and experimental evidence. Our systems-level, tissue-specific scheme advances over traditional global integration and analyses and establishes a prototype to address the tissue-specific effects of genetic perturbations, diseases and drugs.

Genome Stability Maintenance in Naked Mole-Rat.

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Petruseva, I O; Evdokimov, A N; Lavrik, O I

2017-01-01

The naked mole-rat ( Heterocephalus glaber ) is one of the most promising models used to study genome maintenance systems, including the effective repair of damage to DNA. The naked mole-rat is the longest lived rodent species, which is extraordinarily resistant to cancer and has a number of other unique phenotypic traits. For at least 80% of its lifespan, this animal shows no signs of aging or any increased likelihood of death and retains the ability to reproduce. The naked mole-rat draws the heightened attention of researchers who study the molecular basis of lengthy lifespan and cancer resistance. Despite the fact that the naked mole-rat lives under genotoxic stress conditions (oxidative, etc.), the main characteristics of its genome and proteome are a high stability and effective functioning. Replicative senescence in the somatic cells of naked mole-rats is missing, while an additional p53/pRb-dependent mechanism of early contact inhibition has been revealed in its fibroblasts, which controls cell proliferation and its mechanism of arf- dependent aging. The unique traits of phenotypic and molecular adaptations found in the naked mole-rat speak to a high stability and effective functioning of the molecular machinery that counteract damage accumulation in its genome. This review analyzes existing results in the study of the molecular basis of longevity and high cancer resistance in naked mole-rats.

Historical Datasets Support Genomic Selection Models for the Prediction of Cotton Fiber Quality Phenotypes Across Multiple Environments.

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Gapare, Washington; Liu, Shiming; Conaty, Warren; Zhu, Qian-Hao; Gillespie, Vanessa; Llewellyn, Danny; Stiller, Warwick; Wilson, Iain

2018-03-20

Genomic selection (GS) has successfully been used in plant breeding to improve selection efficiency and reduce breeding time and cost. However, there has not been a study to evaluate GS prediction models that may be used for predicting cotton breeding lines across multiple environments. In this study, we evaluated the performance of Bayes Ridge Regression, BayesA, BayesB, BayesC and Reproducing Kernel Hilbert Spaces regression models. We then extended the single-site GS model to accommodate genotype × environment interaction (G×E) in order to assess the merits of multi- over single-environment models in a practical breeding and selection context in cotton, a crop for which this has not previously been evaluated. Our study was based on a population of 215 upland cotton ( Gossypium hirsutum ) breeding lines which were evaluated for fiber length and strength at multiple locations in Australia and genotyped with 13,330 single nucleotide polymorphic (SNP) markers. BayesB, which assumes unique variance for each marker and a proportion of markers to have large effects, while most other markers have zero effect, was the preferred model. GS accuracy for fiber length based on a single-site model varied across sites, ranging from 0.27 to 0.77 (mean = 0.38), while that of fiber strength ranged from 0.19 to 0.58 (mean = 0.35) using randomly selected sub-populations as the training population. Prediction accuracies from the M×E model were higher than those for single-site and across-site models, with an average accuracy of 0.71 and 0.59 for fiber length and strength, respectively. The use of the M×E model could therefore identify which breeding lines have effects that are stable across environments and which ones are responsible for G×E and so reduce the amount of phenotypic screening required in cotton breeding programs to identify adaptable genotypes. Copyright © 2018, G3: Genes, Genomes, Genetics.

Contribution of genome-wide association studies to scientific research: a pragmatic approach to evaluate their impact.

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Vito A G Ricigliano

Full Text Available The factual value of genome-wide association studies (GWAS for the understanding of multifactorial diseases is a matter of intense debate. Practical consequences for the development of more effective therapies do not seem to be around the corner. Here we propose a pragmatic and objective evaluation of how much new biology is arising from these studies, with particular attention to the information that can help prioritize therapeutic targets. We chose multiple sclerosis (MS as a paradigm disease and assumed that, in pre-GWAS candidate-gene studies, the knowledge behind the choice of each gene reflected the understanding of the disease prior to the advent of GWAS. Importantly, this knowledge was based mainly on non-genetic, phenotypic grounds. We performed single-gene and pathway-oriented comparisons of old and new knowledge in MS by confronting an unbiased list of candidate genes in pre-GWAS association studies with those genes exceeding the genome-wide significance threshold in GWAS published from 2007 on. At the single gene level, the majority (94 out of 125 of GWAS-discovered variants had never been contemplated as plausible candidates in pre-GWAS association studies. The 31 genes that were present in both pre- and post-GWAS lists may be of particular interest in that they represent disease-associated variants whose pathogenetic relevance is supported at the phenotypic level (i.e. the phenotypic information that steered their selection as candidate genes in pre-GWAS association studies. As such they represent attractive therapeutic targets. Interestingly, our analysis shows that some of these variants are targets of pharmacologically active compounds, including drugs that are already registered for human use. Compared with the above single-gene analysis, at the pathway level GWAS results appear more coherent with previous knowledge, reinforcing some of the current views on MS pathogenesis and related therapeutic research. This study presents a

Genome-Wide Association Study of Septoria tritici Blotch Resistance in Ethiopian Durum Wheat Landraces

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Yosef G. Kidane

2017-09-01

Full Text Available Septoria tritici blotch (STB is a devastating fungal disease affecting durum and bread wheat cultivation worldwide. The identification, development, and employment of resistant wheat genetic material is the key to overcoming costs and limitations of fungicide treatments. The search for resistance sources in untapped genetic material may speed up the deployment of STB genetic resistance in the field. Ethiopian durum wheat landraces represent a valuable source of such diversity. In this study, 318 Ethiopian durum wheat genotypes, for the most part traditional landraces, were phenotyped for resistance to different aspects of STB infection. Phenology, yield and yield component traits were concurrently measured the collection. Here we describe the distribution of STB resistance traits in modern varieties and in landraces, and the relation existing between STB resistance and other agronomic traits. STB resistance sources were found in landraces as well as in modern varieties tested, suggesting the presence of alleles of breeding relevance. The genetic material was genotyped with more than 16 thousand genome-wide polymorphic markers to describe the linkage disequilibrium and genetic structure existing within the panel of genotypes, and a genome-wide association (GWA study was run to allow the identification of genomic loci involved in STB resistance. High diversity and low genetic structure in the panel allowed high efficiency GWA. The GWA scan detected five major putative QTL for STB resistance, only partially overlapping those already reported in the wheat literature. We report four putative loci for Septoria resistance with no match in previous literature: two highly significant ones on Chr 3A and 5A, and two suggestive ones on Chr 4B and 5B. Markers underlying these QTL explained as much as 10% of the phenotypic variance for disease resistance. We found three cases in which putative QTL for agronomic traits overlapped marker trait association

MSeqDR: A Centralized Knowledge Repository and Bioinformatics Web Resource to Facilitate Genomic Investigations in Mitochondrial Disease.

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Shen, Lishuang; Diroma, Maria Angela; Gonzalez, Michael; Navarro-Gomez, Daniel; Leipzig, Jeremy; Lott, Marie T; van Oven, Mannis; Wallace, Douglas C; Muraresku, Colleen Clarke; Zolkipli-Cunningham, Zarazuela; Chinnery, Patrick F; Attimonelli, Marcella; Zuchner, Stephan; Falk, Marni J; Gai, Xiaowu

2016-06-01

MSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes, genes, and variants. A central Web portal (https://mseqdr.org) integrates community knowledge from expert-curated databases with genomic and phenotype data shared by clinicians and researchers. MSeqDR also functions as a centralized application server for Web-based tools to analyze data across both mitochondrial and nuclear DNA, including investigator-driven whole exome or genome dataset analyses through MSeqDR-Genesis. MSeqDR-GBrowse genome browser supports interactive genomic data exploration and visualization with custom tracks relevant to mtDNA variation and mitochondrial disease. MSeqDR-LSDB is a locus-specific database that currently manages 178 mitochondrial diseases, 1,363 genes associated with mitochondrial biology or disease, and 3,711 pathogenic variants in those genes. MSeqDR Disease Portal allows hierarchical tree-style disease exploration to evaluate their unique descriptions, phenotypes, and causative variants. Automated genomic data submission tools are provided that capture ClinVar compliant variant annotations. PhenoTips will be used for phenotypic data submission on deidentified patients using human phenotype ontology terminology. The development of a dynamic informed patient consent process to guide data access is underway to realize the full potential of these resources. © 2016 WILEY PERIODICALS, INC.

Prediction of maize phenotype based on whole-genome single nucleotide polymorphisms using deep belief networks

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Rachmatia, H.; Kusuma, W. A.; Hasibuan, L. S.

2017-05-01

Selection in plant breeding could be more effective and more efficient if it is based on genomic data. Genomic selection (GS) is a new approach for plant-breeding selection that exploits genomic data through a mechanism called genomic prediction (GP). Most of GP models used linear methods that ignore effects of interaction among genes and effects of higher order nonlinearities. Deep belief network (DBN), one of the architectural in deep learning methods, is able to model data in high level of abstraction that involves nonlinearities effects of the data. This study implemented DBN for developing a GP model utilizing whole-genome Single Nucleotide Polymorphisms (SNPs) as data for training and testing. The case study was a set of traits in maize. The maize dataset was acquisitioned from CIMMYT’s (International Maize and Wheat Improvement Center) Global Maize program. Based on Pearson correlation, DBN is outperformed than other methods, kernel Hilbert space (RKHS) regression, Bayesian LASSO (BL), best linear unbiased predictor (BLUP), in case allegedly non-additive traits. DBN achieves correlation of 0.579 within -1 to 1 range.

Pan-genome and phylogeny of Bacillus cereus sensu lato

OpenAIRE

Bazinet, Adam

2017-01-01

Background: Bacillus cereus sensu lato ( s . l .) is an ecologically diverse bacterial group of medical and agricultural significance. In this study, I use publicly available genomes to characterize the B. cereus s. l. pan-genome and perform the largest phylogenetic and population genetic analyses of this group to date in terms of the number of genes and taxa included. With these fundamental data in hand, I identify genes associated with particular phenotypic traits (i.e., "pan-GWAS" analysis...

Pan-genome and phylogeny of Bacillus cereus sensu lato

OpenAIRE

Bazinet, Adam L.

2017-01-01

Background Bacillus cereus sensu lato (s. l.) is an ecologically diverse bacterial group of medical and agricultural significance. In this study, I use publicly available genomes and novel bioinformatic workflows to characterize the B. cereus s. l. pan-genome and perform the largest phylogenetic and population genetic analyses of this group to date in terms of the number of genes and taxa included. With these fundamental data in hand, I identify genes associated with particular phenotypic tra...

Mining for genotype-phenotype relations in Saccharomyces using partial least squares

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Sæbø Solve

2011-08-01

Full Text Available Abstract Background Multivariate approaches are important due to their versatility and applications in many fields as it provides decisive advantages over univariate analysis in many ways. Genome wide association studies are rapidly emerging, but approaches in hand pay less attention to multivariate relation between genotype and phenotype. We introduce a methodology based on a BLAST approach for extracting information from genomic sequences and Soft- Thresholding Partial Least Squares (ST-PLS for mapping genotype-phenotype relations. Results Applying this methodology to an extensive data set for the model yeast Saccharomyces cerevisiae, we found that the relationship between genotype-phenotype involves surprisingly few genes in the sense that an overwhelmingly large fraction of the phenotypic variation can be explained by variation in less than 1% of the full gene reference set containing 5791 genes. These phenotype influencing genes were evolving 20% faster than non-influential genes and were unevenly distributed over cellular functions, with strong enrichments in functions such as cellular respiration and transposition. These genes were also enriched with known paralogs, stop codon variations and copy number variations, suggesting that such molecular adjustments have had a disproportionate influence on Saccharomyces yeasts recent adaptation to environmental changes in its ecological niche. Conclusions BLAST and PLS based multivariate approach derived results that adhere to the known yeast phylogeny and gene ontology and thus verify that the methodology extracts a set of fast evolving genes that capture the phylogeny of the yeast strains. The approach is worth pursuing, and future investigations should be made to improve the computations of genotype signals as well as variable selection procedure within the PLS framework.

Accuracy of genomic selection in biparental populations of flax (Linum usitatissimum L.

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Frank M. You

2016-08-01

Full Text Available Flax is an important economic crop for seed oil and stem fiber. Phenotyping of traits such as seed yield, seed quality, stem fiber yield, and quality characteristics is expensive and time consuming. Genomic selection (GS refers to a breeding approach aimed at selecting preferred individuals based on genomic estimated breeding values predicted by a statistical model based on the relationship between phenotypes and genome-wide genetic markers. We evaluated the prediction accuracy of GS (rMP and the efficiency of GS relative to phenotypic selection (RE for three GS models: ridge regression best linear unbiased prediction (RR-BLUP, Bayesian LASSO (BL, and Bayesian ridge regression (BRR, for seed yield, oil content, iodine value, linoleic, and linolenic acid content with a full and a common set of genome-wide simple sequence repeat markers in each of three biparental populations. The three GS models generated similar rMP and RE, while BRR displayed a higher coefficient of determination (R2 of the fitted models than did RR-BLUP or BL. The mean rMP and RE varied for traits with different heritabilities and was affected by the genetic variation of the traits in the populations. GS for seed yield generated a mean RE of 1.52 across populations and marker sets, a value significantly superior to that for direct phenotypic selection. Our empirical results provide the first validation of GS in flax and demonstrate that GS could increase genetic gain per unit time for linseed breeding. Further studies for selection of training populations and markers are warranted.

Structural genomics in endocrinology

NARCIS (Netherlands)

Smit, J. W.; Romijn, J. A.

2001-01-01

Traditionally, endocrine research evolved from the phenotypical characterisation of endocrine disorders to the identification of underlying molecular pathophysiology. This approach has been, and still is, extremely successful. The introduction of genomics and proteomics has resulted in a reversal of

Further Improvements to Linear Mixed Models for Genome-Wide Association Studies

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Widmer, Christian; Lippert, Christoph; Weissbrod, Omer; Fusi, Nicolo; Kadie, Carl; Davidson, Robert; Listgarten, Jennifer; Heckerman, David

2014-11-01

We examine improvements to the linear mixed model (LMM) that better correct for population structure and family relatedness in genome-wide association studies (GWAS). LMMs rely on the estimation of a genetic similarity matrix (GSM), which encodes the pairwise similarity between every two individuals in a cohort. These similarities are estimated from single nucleotide polymorphisms (SNPs) or other genetic variants. Traditionally, all available SNPs are used to estimate the GSM. In empirical studies across a wide range of synthetic and real data, we find that modifications to this approach improve GWAS performance as measured by type I error control and power. Specifically, when only population structure is present, a GSM constructed from SNPs that well predict the phenotype in combination with principal components as covariates controls type I error and yields more power than the traditional LMM. In any setting, with or without population structure or family relatedness, a GSM consisting of a mixture of two component GSMs, one constructed from all SNPs and another constructed from SNPs that well predict the phenotype again controls type I error and yields more power than the traditional LMM. Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science.

Mutagenesis and phenotyping resources in zebrafish for studying development and human disease

Science.gov (United States)

Varshney, Gaurav Kumar

2014-01-01

The zebrafish (Danio rerio) is an important model organism for studying development and human disease. The zebrafish has an excellent reference genome and the functions of hundreds of genes have been tested using both forward and reverse genetic approaches. Recent years have seen an increasing number of large-scale mutagenesis projects and the number of mutants or gene knockouts in zebrafish has increased rapidly, including for the first time conditional knockout technologies. In addition, targeted mutagenesis techniques such as zinc finger nucleases, transcription activator-like effector nucleases and clustered regularly interspaced short sequences (CRISPR) or CRISPR-associated (Cas), have all been shown to effectively target zebrafish genes as well as the first reported germline homologous recombination, further expanding the utility and power of zebrafish genetics. Given this explosion of mutagenesis resources, it is now possible to perform systematic, high-throughput phenotype analysis of all zebrafish gene knockouts. PMID:24162064

Genome-wide association study, genomic prediction and marker-assisted selection for seed weight in soybean (Glycine max).

Science.gov (United States)

Zhang, Jiaoping; Song, Qijian; Cregan, Perry B; Jiang, Guo-Liang

2016-01-01

Twenty-two loci for soybean SW and candidate genes conditioning seed development were identified; and prediction accuracies of GS and MAS were estimated through cross-validation and validation with unrelated populations. Soybean (Glycine max) is a major crop for plant protein and oil production, and seed weight (SW) is important for yield and quality in food/vegetable uses of soybean. However, our knowledge of genes controlling SW remains limited. To better understand the molecular mechanism underlying the trait and explore marker-based breeding approaches, we conducted a genome-wide association study in a population of 309 soybean germplasm accessions using 31,045 single nucleotide polymorphisms (SNPs), and estimated the prediction accuracy of genomic selection (GS) and marker-assisted selection (MAS) for SW. Twenty-two loci of minor effect associated with SW were identified, including hotspots on Gm04 and Gm19. The mixed model containing these loci explained 83.4% of phenotypic variation. Candidate genes with Arabidopsis orthologs conditioning SW were also proposed. The prediction accuracies of GS and MAS by cross-validation were 0.75-0.87 and 0.62-0.75, respectively, depending on the number of SNPs used and the size of training population. GS also outperformed MAS when the validation was performed using unrelated panels across a wide range of maturities, with an average prediction accuracy of 0.74 versus 0.53. This study convincingly demonstrated that soybean SW is controlled by numerous minor-effect loci. It greatly enhances our understanding of the genetic basis of SW in soybean and facilitates the identification of genes controlling the trait. It also suggests that GS holds promise for accelerating soybean breeding progress. The results are helpful for genetic improvement and genomic prediction of yield in soybean.

Remembrance of things past retrieved from the Paramecium genome.

Science.gov (United States)

Sperling, Linda

2011-01-01

Paramecium and other ciliates are the only unicellular eukaryotes that separate germinal and somatic functions. A germline micronucleus transmits the genetic information to sexual progeny, while a somatic macronucleus expresses the genetic information during vegetative growth to determine the phenotype. At each sexual generation, a new macronucleus develops from the zygotic nucleus through programmed rearrangements of the germline genome. Paramecium tetraurelia somatic genome sequencing, reviewed here, has provided insight into the organization and evolution of the genome. A series of at least 3 whole genome duplications was detected in the Paramecium lineage and selective pressures that determine the fate of the gene duplicates analyzed. Variability in the somatic DNA was characterized and could be attributed to the genome rearrangement processes. Since, in Paramecium, alternative genome rearrangement patterns can be inherited across sexual generations by homology-dependent epigenetic mechanisms and can affect phenotype, I discuss the possibility that ciliate nuclear dimorphism buffers genetic variation hidden in the germline. Copyright © 2011 Institut Pasteur. Published by Elsevier SAS. All rights reserved.

Shared regulatory sites are abundant in the human genome and shed light on genome evolution and disease pleiotropy.

Science.gov (United States)

Tong, Pin; Monahan, Jack; Prendergast, James G D

2017-03-01

Large-scale gene expression datasets are providing an increasing understanding of the location of cis-eQTLs in the human genome and their role in disease. However, little is currently known regarding the extent of regulatory site-sharing between genes. This is despite it having potentially wide-ranging implications, from the determination of the way in which genetic variants may shape multiple phenotypes to the understanding of the evolution of human gene order. By first identifying the location of non-redundant cis-eQTLs, we show that regulatory site-sharing is a relatively common phenomenon in the human genome, with over 10% of non-redundant regulatory variants linked to the expression of multiple nearby genes. We show that these shared, local regulatory sites are linked to high levels of chromatin looping between the regulatory sites and their associated genes. In addition, these co-regulated gene modules are found to be strongly conserved across mammalian species, suggesting that shared regulatory sites have played an important role in shaping human gene order. The association of these shared cis-eQTLs with multiple genes means they also appear to be unusually important in understanding the genetics of human phenotypes and pleiotropy, with shared regulatory sites more often linked to multiple human phenotypes than other regulatory variants. This study shows that regulatory site-sharing is likely an underappreciated aspect of gene regulation and has important implications for the understanding of various biological phenomena, including how the two and three dimensional structures of the genome have been shaped and the potential causes of disease pleiotropy outside coding regions.

Distinct genetic architectures for phenotype means and plasticities in Zea mays.

Science.gov (United States)

Kusmec, Aaron; Srinivasan, Srikant; Nettleton, Dan; Schnable, Patrick S

2017-09-01

Phenotypic plasticity describes the phenotypic variation of a trait when a genotype is exposed to different environments. Understanding the genetic control of phenotypic plasticity in crops such as maize is of paramount importance for maintaining and increasing yields in a world experiencing climate change. Here, we report the results of genome-wide association analyses of multiple phenotypes and two measures of phenotypic plasticity in a maize nested association mapping (US-NAM) population grown in multiple environments and genotyped with ~2.5 million single-nucleotide polymorphisms. We show that across all traits the candidate genes for mean phenotype values and plasticity measures form structurally and functionally distinct groups. Such independent genetic control suggests that breeders will be able to select semi-independently for mean phenotype values and plasticity, thereby generating varieties with both high mean phenotype values and levels of plasticity that are appropriate for the target performance environments.

Impact of selective genotyping in the training population on accuracy and bias of genomic selection.

Science.gov (United States)

Zhao, Yusheng; Gowda, Manje; Longin, Friedrich H; Würschum, Tobias; Ranc, Nicolas; Reif, Jochen C

2012-08-01

Estimating marker effects based on routinely generated phenotypic data of breeding programs is a cost-effective strategy to implement genomic selection. Truncation selection in breeding populations, however, could have a strong impact on the accuracy to predict genomic breeding values. The main objective of our study was to investigate the influence of phenotypic selection on the accuracy and bias of genomic selection. We used experimental data of 788 testcross progenies from an elite maize breeding program. The testcross progenies were evaluated in unreplicated field trials in ten environments and fingerprinted with 857 SNP markers. Random regression best linear unbiased prediction method was used in combination with fivefold cross-validation based on genotypic sampling. We observed a substantial loss in the accuracy to predict genomic breeding values in unidirectional selected populations. In contrast, estimating marker effects based on bidirectional selected populations led to only a marginal decrease in the prediction accuracy of genomic breeding values. We concluded that bidirectional selection is a valuable approach to efficiently implement genomic selection in applied plant breeding programs.

DeepPVP: phenotype-based prioritization of causative variants using deep learning

KAUST Repository

Boudellioua, Imene

2018-05-02

Background: Prioritization of variants in personal genomic data is a major challenge. Recently, computational methods that rely on comparing phenotype similarity have shown to be useful to identify causative variants. In these methods, pathogenicity prediction is combined with a semantic similarity measure to prioritize not only variants that are likely to be dysfunctional but those that are likely involved in the pathogenesis of a patient\\'s phenotype. Results: We have developed DeepPVP, a variant prioritization method that combined automated inference with deep neural networks to identify the likely causative variants in whole exome or whole genome sequence data. We demonstrate that DeepPVP performs significantly better than existing methods, including phenotype-based methods that use similar features. DeepPVP is freely available at https://github.com/bio-ontology-research-group/phenomenet-vp Conclusions: DeepPVP further improves on existing variant prioritization methods both in terms of speed as well as accuracy.

Comprehensive genomic characterization of campylobacter genus reveals some underlying mechanisms for its genomic diversification.

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Yizhuang Zhou

Full Text Available Campylobacter species.are phenotypically diverse in many aspects including host habitats and pathogenicities, which demands comprehensive characterization of the entire Campylobacter genus to study their underlying genetic diversification. Up to now, 34 Campylobacter strains have been sequenced and published in public databases, providing good opportunity to systemically analyze their genomic diversities. In this study, we first conducted genomic characterization, which includes genome-wide alignments, pan-genome analysis, and phylogenetic identification, to depict the genetic diversity of Campylobacter genus. Afterward, we improved the tetranucleotide usage pattern-based naïve Bayesian classifier to identify the abnormal composition fragments (ACFs, fragments with significantly different tetranucleotide frequency profiles from its genomic tetranucleotide frequency profiles including horizontal gene transfers (HGTs to explore the mechanisms for the genetic diversity of this organism. Finally, we analyzed the HGTs transferred via bacteriophage transductions. To our knowledge, this study is the first to use single nucleotide polymorphism information to construct liable microevolution phylogeny of 21 Campylobacter jejuni strains. Combined with the phylogeny of all the collected Campylobacter species based on genome-wide core gene information, comprehensive phylogenetic inference of all 34 Campylobacter organisms was determined. It was found that C. jejuni harbors a high fraction of ACFs possibly through intraspecies recombination, whereas other Campylobacter members possess numerous ACFs possibly via intragenus recombination. Furthermore, some Campylobacter strains have undergone significant ancient viral integration during their evolution process. The improved method is a powerful tool for bacterial genomic analysis. Moreover, the findings would provide useful information for future research on Campylobacter genus.

Use of genomic recursions and algorithm for proven and young animals for single-step genomic BLUP analyses--a simulation study.

Science.gov (United States)

Fragomeni, B O; Lourenco, D A L; Tsuruta, S; Masuda, Y; Aguilar, I; Misztal, I

2015-10-01

The purpose of this study was to examine accuracy of genomic selection via single-step genomic BLUP (ssGBLUP) when the direct inverse of the genomic relationship matrix (G) is replaced by an approximation of G(-1) based on recursions for young genotyped animals conditioned on a subset of proven animals, termed algorithm for proven and young animals (APY). With the efficient implementation, this algorithm has a cubic cost with proven animals and linear with young animals. Ten duplicate data sets mimicking a dairy cattle population were simulated. In a first scenario, genomic information for 20k genotyped bulls, divided in 7k proven and 13k young bulls, was generated for each replicate. In a second scenario, 5k genotyped cows with phenotypes were included in the analysis as young animals. Accuracies (average for the 10 replicates) in regular EBV were 0.72 and 0.34 for proven and young animals, respectively. When genomic information was included, they increased to 0.75 and 0.50. No differences between genomic EBV (GEBV) obtained with the regular G(-1) and the approximated G(-1) via the recursive method were observed. In the second scenario, accuracies in GEBV (0.76, 0.51 and 0.59 for proven bulls, young males and young females, respectively) were also higher than those in EBV (0.72, 0.35 and 0.49). Again, no differences between GEBV with regular G(-1) and with recursions were observed. With the recursive algorithm, the number of iterations to achieve convergence was reduced from 227 to 206 in the first scenario and from 232 to 209 in the second scenario. Cows can be treated as young animals in APY without reducing the accuracy. The proposed algorithm can be implemented to reduce computing costs and to overcome current limitations on the number of genotyped animals in the ssGBLUP method. © 2015 Blackwell Verlag GmbH.

Sex Differences in Genetic Architecture of Complex Phenotypes?

NARCIS (Netherlands)

Vink, J.M.; Bartels, M.; van Beijsterveldt, C.E.M.; van Dongen, J.; van Beek, J.H.D.A.; Distel, M.A.; de Moor, M.H.M.; Smit, D.J.A.; Minica, C.C.; Ligthart, R.S.L.; Geels, L.M.; Abdellaoui, A.; Middeldorp, C.M.; Hottenga, J.J.; Willemsen, G.; de Geus, E.J.C.; Boomsma, D.I.

2012-01-01

We examined sex differences in familial resemblance for a broad range of behavioral, psychiatric and health related phenotypes (122 complex traits) in children and adults. There is a renewed interest in the importance of genotype by sex interaction in, for example, genome-wide association (GWA)

Gene copy number variation throughout the Plasmodium falciparum genome

Directory of Open Access Journals (Sweden)

Stewart Lindsay B

2009-08-01

Full Text Available Abstract Background Gene copy number variation (CNV is responsible for several important phenotypes of the malaria parasite Plasmodium falciparum, including drug resistance, loss of infected erythrocyte cytoadherence and alteration of receptor usage for erythrocyte invasion. Despite the known effects of CNV, little is known about its extent throughout the genome. Results We performed a whole-genome survey of CNV genes in P. falciparum using comparative genome hybridisation of a diverse set of 16 laboratory culture-adapted isolates to a custom designed high density Affymetrix GeneChip array. Overall, 186 genes showed hybridisation signals consistent with deletion or amplification in one or more isolate. There is a strong association of CNV with gene length, genomic location, and low orthology to genes in other Plasmodium species. Sub-telomeric regions of all chromosomes are strongly associated with CNV genes independent from members of previously described multigene families. However, ~40% of CNV genes were located in more central regions of the chromosomes. Among the previously undescribed CNV genes, several that are of potential phenotypic relevance are identified. Conclusion CNV represents a major form of genetic variation within the P. falciparum genome; the distribution of gene features indicates the involvement of highly non-random mutational and selective processes. Additional studies should be directed at examining CNV in natural parasite populations to extend conclusions to clinical settings.

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.

A genome-wide association study points out the causal implication of SOX9 in the sex-reversal phenotype in XX pigs.

Directory of Open Access Journals (Sweden)

Sarah Rousseau

Full Text Available Among farm animals, pigs are known to show XX sex-reversal. In such cases the individuals are genetically female but exhibit a hermaphroditism, or a male phenotype. While the frequency of this congenital disease is quite low (less than 1%, the economic losses are significant for pig breeders. These losses result from sterility, urogenital infections and the carcasses being downgraded because of the risk of boar taint. It has been clearly demonstrated that the SRY gene is not involved in most cases of sex-reversal in pigs, and that autosomal recessive mutations remain to be discovered. A whole-genome scan analysis was performed in the French Large-White population to identify candidate genes: 38 families comprising the two non-affected parents and 1 to 11 sex-reversed full-sib piglets were genotyped with the PorcineSNP60 BeadChip. A Transmission Disequilibrium Test revealed a highly significant candidate region on SSC12 (most significant p-value<4.65.10(-10 containing the SOX9 gene. SOX9, one of the master genes involved in testis differentiation, was sequenced together with one of its main regulatory region Tesco. However, no causal mutations could be identified in either of the two sequenced regions. Further haplotype analyses did not identify a shared homozygous segment between the affected pigs, suggesting either a lack of power due to the SNP properties of the chip, or a second causative locus. Together with information from humans and mice, this study in pigs adds to the field of knowledge, which will lead to characterization of novel molecular mechanisms regulating sexual differentiation and dysregulation in cases of sex reversal.

Phenotypic H-Antigen Typing by Mass Spectrometry Combined with Genetic Typing of H Antigens, O Antigens, and Toxins by Whole-Genome Sequencing Enhances Identification of Escherichia coli Isolates.

Science.gov (United States)

Cheng, Keding; Chui, Huixia; Domish, Larissa; Sloan, Angela; Hernandez, Drexler; McCorrister, Stuart; Robinson, Alyssia; Walker, Matthew; Peterson, Lorea A M; Majcher, Miles; Ratnam, Sam; Haldane, David J M; Bekal, Sadjia; Wylie, John; Chui, Linda; Tyler, Shaun; Xu, Bianli; Reimer, Aleisha; Nadon, Celine; Knox, J David; Wang, Gehua

2016-08-01

Mass spectrometry-based phenotypic H-antigen typing (MS-H) combined with whole-genome-sequencing-based genetic identification of H antigens, O antigens, and toxins (WGS-HOT) was used to type 60 clinical Escherichia coli isolates, 43 of which were previously identified as nonmotile, H type undetermined, or O rough by serotyping or having shown discordant MS-H and serotyping results. Whole-genome sequencing confirmed that MS-H was able to provide more accurate data regarding H antigen expression than serotyping. Further, enhanced and more confident O antigen identification resulted from gene cluster based typing in combination with conventional typing based on the gene pair comprising wzx and wzy and that comprising wzm and wzt The O antigen was identified in 94.6% of the isolates when the two genetic O typing approaches (gene pair and gene cluster) were used in conjunction, in comparison to 78.6% when the gene pair database was used alone. In addition, 98.2% of the isolates showed the existence of genes for various toxins and/or virulence factors, among which verotoxins (Shiga toxin 1 and/or Shiga toxin 2) were 100% concordant with conventional PCR based testing results. With more applications of mass spectrometry and whole-genome sequencing in clinical microbiology laboratories, this combined phenotypic and genetic typing platform (MS-H plus WGS-HOT) should be ideal for pathogenic E. coli typing. Copyright © 2016 Cheng et al.

Genomic phenotyping by barcode sequencing broadly distinguishes between alkylating agents, oxidizing agents, and non-genotoxic agents, and reveals a role for aromatic amino acids in cellular recovery after quinone exposure.

Science.gov (United States)

Svensson, J Peter; Quirós Pesudo, Laia; McRee, Siobhan K; Adeleye, Yeyejide; Carmichael, Paul; Samson, Leona D

2013-01-01

Toxicity screening of compounds provides a means to identify compounds harmful for human health and the environment. Here, we further develop the technique of genomic phenotyping to improve throughput while maintaining specificity. We exposed cells to eight different compounds that rely on different modes of action: four genotoxic alkylating (methyl methanesulfonate (MMS), N-Methyl-N-nitrosourea (MNU), N,N'-bis(2-chloroethyl)-N-nitroso-urea (BCNU), N-ethylnitrosourea (ENU)), two oxidizing (2-methylnaphthalene-1,4-dione (menadione, MEN), benzene-1,4-diol (hydroquinone, HYQ)), and two non-genotoxic (methyl carbamate (MC) and dimethyl sulfoxide (DMSO)) compounds. A library of S. cerevisiae 4,852 deletion strains, each identifiable by a unique genetic 'barcode', were grown in competition; at different time points the ratio between the strains was assessed by quantitative high throughput 'barcode' sequencing. The method was validated by comparison to previous genomic phenotyping studies and 90% of the strains identified as MMS-sensitive here were also identified as MMS-sensitive in a much lower throughput solid agar screen. The data provide profiles of proteins and pathways needed for recovery after both genotoxic and non-genotoxic compounds. In addition, a novel role for aromatic amino acids in the recovery after treatment with oxidizing agents was suggested. The role of aromatic acids was further validated; the quinone subgroup of oxidizing agents were extremely toxic in cells where tryptophan biosynthesis was compromised.

Robust and sensitive analysis of mouse knockout phenotypes.

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Natasha A Karp

Full Text Available A significant challenge of in-vivo studies is the identification of phenotypes with a method that is robust and reliable. The challenge arises from practical issues that lead to experimental designs which are not ideal. Breeding issues, particularly in the presence of fertility or fecundity problems, frequently lead to data being collected in multiple batches. This problem is acute in high throughput phenotyping programs. In addition, in a high throughput environment operational issues lead to controls not being measured on the same day as knockouts. We highlight how application of traditional methods, such as a Student's t-Test or a 2-way ANOVA, in these situations give flawed results and should not be used. We explore the use of mixed models using worked examples from Sanger Mouse Genome Project focusing on Dual-Energy X-Ray Absorptiometry data for the analysis of mouse knockout data and compare to a reference range approach. We show that mixed model analysis is more sensitive and less prone to artefacts allowing the discovery of subtle quantitative phenotypes essential for correlating a gene's function to human disease. We demonstrate how a mixed model approach has the additional advantage of being able to include covariates, such as body weight, to separate effect of genotype from these covariates. This is a particular issue in knockout studies, where body weight is a common phenotype and will enhance the precision of assigning phenotypes and the subsequent selection of lines for secondary phenotyping. The use of mixed models with in-vivo studies has value not only in improving the quality and sensitivity of the data analysis but also ethically as a method suitable for small batches which reduces the breeding burden of a colony. This will reduce the use of animals, increase throughput, and decrease cost whilst improving the quality and depth of knowledge gained.

A genome-wide association study identifies five loci influencing facial morphology in Europeans.

Directory of Open Access Journals (Sweden)

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.

A Genome-Wide Association Study Identifies Five Loci Influencing Facial Morphology in Europeans

Science.gov (United States)

Liu, Fan; van der Lijn, Fedde; Schurmann, Claudia; Zhu, Gu; Chakravarty, M. Mallar; Hysi, Pirro G.; Wollstein, Andreas; Lao, Oscar; de Bruijne, Marleen; Ikram, M. Arfan; van der Lugt, Aad; Rivadeneira, Fernando; Uitterlinden, André G.; Hofman, Albert; Niessen, Wiro J.; Homuth, Georg; de Zubicaray, Greig; McMahon, Katie L.; Thompson, Paul M.; Daboul, Amro; Puls, Ralf; Hegenscheid, Katrin; Bevan, Liisa; Pausova, Zdenka; Medland, Sarah E.; Montgomery, Grant W.; Wright, Margaret J.; Wicking, Carol; Boehringer, Stefan; Spector, Timothy D.; Paus, Tomáš; Martin, Nicholas G.; Biffar, Reiner; Kayser, Manfred

2012-01-01

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. PMID:23028347

[Ethical considerations in genomic cohort study].

Science.gov (United States)

Choi, Eun Kyung; Kim, Ock-Joo

2007-03-01

During the last decade, genomic cohort study has been developed in many countries by linking health data and genetic data in stored samples. Genomic cohort study is expected to find key genetic components that contribute to common diseases, thereby promising great advance in genome medicine. While many countries endeavor to build biobank systems, biobank-based genome research has raised important ethical concerns including genetic privacy, confidentiality, discrimination, and informed consent. Informed consent for biobank poses an important question: whether true informed consent is possible in population-based genomic cohort research where the nature of future studies is unforeseeable when consent is obtained. Due to the sensitive character of genetic information, protecting privacy and keeping confidentiality become important topics. To minimize ethical problems and achieve scientific goals to its maximum degree, each country strives to build population-based genomic cohort research project, by organizing public consultation, trying public and expert consensus in research, and providing safeguards to protect privacy and confidentiality.

Chemical rationale for selection of isolates for genome sequencing

DEFF Research Database (Denmark)

Rank, Christian; Larsen, Thomas Ostenfeld; Frisvad, Jens Christian

The advances in gene sequencing will in the near future enable researchers to affordably acquire the full genomes of handpicked isolates. We here present a method to evaluate the chemical potential of an entire species and select representatives for genome sequencing. The selection criteria for new...... strains to be sequenced can be manifold, but for studying the functional phenotype, using a metabolome based approach offers a cheap and rapid assessment of critical strains to cover the chemical diversity. We have applied this methodology on the complex A. flavus/A. oryzae group. Though these two species...... are in principal identical, they represent two different phenotypes. This is clearly presented through a correspondence analysis of selected extrolites, in which the subtle chemical differences are visually dispersed. The results points to a handful of strains, which, if sequenced, will likely enhance our...

Genomic Prediction of Seed Quality Traits Using Advanced Barley Breeding Lines

Science.gov (United States)

Nielsen, Nanna Hellum; Jahoor, Ahmed; Jensen, Jens Due; Orabi, Jihad; Cericola, Fabio; Edriss, Vahid; Jensen, Just

2016-01-01

Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines) are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families. PMID:27783639

Genomic Prediction of Seed Quality Traits Using Advanced Barley Breeding Lines.

Directory of Open Access Journals (Sweden)

Nanna Hellum Nielsen

Full Text Available Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families.

Genomic prediction of traits related to canine hip dysplasia

Directory of Open Access Journals (Sweden)

Enrique eSanchez-Molano

2015-03-01

Full Text Available Increased concern for the welfare of pedigree dogs has led to development of selection programs against inherited diseases. An example is canine hip dysplasia (CHD, which has a moderate heritability and a high prevalence in some large-sized breeds. To date, selection using phenotypes has led to only modest improvement, and alternative strategies such as genomic selection may prove more effective. The primary aims of this study were to compare the performance of pedigree- and genomic-based breeding against CHD in the UK Labrador retriever population and to evaluate the performance of different genomic selection methods. A sample of 1179 Labrador Retrievers evaluated for CHD according to the UK scoring method (hip score, HS was genotyped with the Illumina CanineHD BeadChip. Twelve functions of HS and its component traits were analyzed using different statistical methods (GBLUP, Bayes C and Single-Step methods, and results were compared with a pedigree-based approach (BLUP using cross-validation. Genomic methods resulted in similar or higher accuracies than pedigree-based methods with training sets of 944 individuals for all but the untransformed HS, suggesting that genomic selection is an effective strategy. GBLUP and Bayes C gave similar prediction accuracies for HS and related traits, indicating a polygenic architecture. This conclusion was also supported by the low accuracies obtained in additional GBLUP analyses performed using only the SNPs with highest test statistics, also indicating that marker-assisted selection would not be as effective as genomic selection. A Single-Step method that combines genomic and pedigree information also showed higher accuracy than GBLUP and Bayes C for the log-transformed HS, which is currently used for pedigree based evaluations in UK. In conclusion, genomic selection is a promising alternative to pedigree-based selection against CHD, requiring more phenotypes with genomic data to improve further the accuracy

Evolutionary genomics and population structure of Entamoeba histolytica

Directory of Open Access Journals (Sweden)

Koushik Das

2014-11-01

Full Text Available Amoebiasis caused by the gastrointestinal parasite Entamoeba histolytica has diverse disease outcomes. Study of genome and evolution of this fascinating parasite will help us to understand the basis of its virulence and explain why, when and how it causes diseases. In this review, we have summarized current knowledge regarding evolutionary genomics of E. histolytica and discussed their association with parasite phenotypes and its differential pathogenic behavior. How genetic diversity reveals parasite population structure has also been discussed. Queries concerning their evolution and population structure which were required to be addressed have also been highlighted. This significantly large amount of genomic data will improve our knowledge about this pathogenic species of Entamoeba.

Understanding mammalian genetic systems: the challenge of phenotyping in the mouse.

Directory of Open Access Journals (Sweden)

Steve D M Brown

2006-08-01

Full Text Available Understanding mammalian genetic systems is predicated on the determination of the relationship between genetic variation and phenotype. Several international programmes are under way to deliver mutations in every gene in the mouse genome. The challenge for mouse geneticists is to develop approaches that will provide comprehensive phenotype datasets for these mouse mutant libraries. Several factors are critical to success in this endeavour. It will be important to catalogue assay and environment and where possible to adopt standardised procedures for phenotyping tests along with common environmental conditions to ensure comparable datasets of phenotypes. Moreover, the scale of the task underlines the need to invest in technological development improving both the speed and cost of phenotyping platforms. In addition, it will be necessary to develop new informatics standards that capture the phenotype assay as well as other factors, genetic and environmental, that impinge upon phenotype outcome.

The genomic analysis of lactic acidosis and acidosis response in human cancers.

Directory of Open Access Journals (Sweden)

Julia Ling-Yu Chen

2008-12-01

Full Text Available The tumor microenvironment has a significant impact on tumor development. Two important determinants in this environment are hypoxia and lactic acidosis. Although lactic acidosis has long been recognized as an important factor in cancer, relatively little is known about how cells respond to lactic acidosis and how that response relates to cancer phenotypes. We develop genome-scale gene expression studies to dissect transcriptional responses of primary human mammary epithelial cells to lactic acidosis and hypoxia in vitro and to explore how they are linked to clinical tumor phenotypes in vivo. The resulting experimental signatures of responses to lactic acidosis and hypoxia are evaluated in a heterogeneous set of breast cancer datasets. A strong lactic acidosis response signature identifies a subgroup of low-risk breast cancer patients having distinct metabolic profiles suggestive of a preference for aerobic respiration. The association of lactic acidosis response with good survival outcomes may relate to the role of lactic acidosis in directing energy generation toward aerobic respiration and utilization of other energy sources via inhibition of glycolysis. This "inhibition of glycolysis" phenotype in tumors is likely caused by the repression of glycolysis gene expression and Akt inhibition. Our study presents a genomic evaluation of the prognostic information of a lactic acidosis response independent of the hypoxic response. Our results identify causal roles of lactic acidosis in metabolic reprogramming, and the direct functional consequence of lactic acidosis pathway activity on cellular responses and tumor development. The study also demonstrates the utility of genomic analysis that maps expression-based findings from in vitro experiments to human samples to assess links to in vivo clinical phenotypes.

From risk genes to psychiatric phenotypes - Studies of fibroblast growth factor-related and genome-wide genetic variants in humans and mice

NARCIS (Netherlands)

Terwisscha van Scheltinga, A.F.

2013-01-01

Schizophrenia is a severe mental disorder with a high heritability. This thesis describes studies on the association between genetic variants and phenotypes related to schizophrenia, such as brain volume and IQ, in order to learn about which processes are affected by schizophrenia-associated genetic

The Genome of the Basidiomycetous Yeast and Human Pathogen Cryptococcus neoformans

Science.gov (United States)

Loftus, Brendan J.; Fung, Eula; Roncaglia, Paola; Rowley, Don; Amedeo, Paolo; Bruno, Dan; Vamathevan, Jessica; Miranda, Molly; Anderson, Iain J.; Fraser, James A.; Allen, Jonathan E.; Bosdet, Ian E.; Brent, Michael R.; Chiu, Readman; Doering, Tamara L.; Donlin, Maureen J.; D’Souza, Cletus A.; Fox, Deborah S.; Grinberg, Viktoriya; Fu, Jianmin; Fukushima, Marilyn; Haas, Brian J.; Huang, James C.; Janbon, Guilhem; Jones, Steven J. M.; Koo, Hean L.; Krzywinski, Martin I.; Kwon-Chung, June K.; Lengeler, Klaus B.; Maiti, Rama; Marra, Marco A.; Marra, Robert E.; Mathewson, Carrie A.; Mitchell, Thomas G.; Pertea, Mihaela; Riggs, Florenta R.; Salzberg, Steven L.; Schein, Jacqueline E.; Shvartsbeyn, Alla; Shin, Heesun; Shumway, Martin; Specht, Charles A.; Suh, Bernard B.; Tenney, Aaron; Utterback, Terry R.; Wickes, Brian L.; Wortman, Jennifer R.; Wye, Natasja H.; Kronstad, James W.; Lodge, Jennifer K.; Heitman, Joseph; Davis, Ronald W.; Fraser, Claire M.; Hyman, Richard W.

2012-01-01

Cryptococcus neoformans is a basidiomycetous yeast ubiquitous in the environment, a model for fungal pathogenesis, and an opportunistic human pathogen of global importance. We have sequenced its ~20-megabase genome, which contains ~6500 intron-rich gene structures and encodes a transcriptome abundant in alternatively spliced and antisense messages. The genome is rich in transposons, many of which cluster at candidate centromeric regions. The presence of these transposons may drive karyotype instability and phenotypic variation. C. neoformans encodes unique genes that may contribute to its unusual virulence properties, and comparison of two phenotypically distinct strains reveals variation in gene content in addition to sequence polymorphisms between the genomes. PMID:15653466

MSeqDR: A Centralized Knowledge Repository and Bioinformatics Web Resource to Facilitate Genomic Investigations in Mitochondrial Disease

OpenAIRE

Shen, Lishuang; Diroma, Maria Angela; Gonzalez, Michael; Navarro-Gomez, Daniel; Leipzig, Jeremy; Lott, Marie T.; Oven, Mannis; Wallace, D.C.; Muraresku, Colleen Clarke; Zolkipli-Cunningham, Zarazuela; Chinnery, Patrick; Attimonelli, Marcella; Zuchner, Stephan; Falk, Marni J.; Gai, Xiaowu

2016-01-01

textabstractMSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes, genes, and variants. A central Web portal (https://mseqdr.org) integrates community knowledge from expert-curated databases with genomic and phenotype data shared by clinicians and researchers. MSeqDR ...

Intraclonal genome diversity of Pseudomonas aeruginosa clones CHA and TB

Science.gov (United States)

2013-01-01

Background Adaptation of Pseudomonas aeruginosa to different living conditions is accompanied by microevolution resulting in genomic diversity between strains of the same clonal lineage. In order to detect the impact of colonized habitats on P. aeruginosa microevolution we determined the genomic diversity between the highly virulent cystic fibrosis (CF) isolate CHA and two temporally and geographically unrelated clonal variants. The outcome was compared with the intraclonal genome diversity between three more closely related isolates of another clonal complex. Results The three clone CHA isolates differed in their core genome in several dozen strain specific nucleotide exchanges and small deletions from each other. Loss of function mutations and non-conservative amino acid replacements affected several habitat- and lifestyle-associated traits, for example, the key regulator GacS of the switch between acute and chronic disease phenotypes was disrupted in strain CHA. Intraclonal genome diversity manifested in an individual composition of the respective accessory genome whereby the highest number of accessory DNA elements was observed for isolate PT22 from a polluted aquatic habitat. Little intraclonal diversity was observed between three spatiotemporally related outbreak isolates of clone TB. Although phenotypically different, only a few individual SNPs and deletions were detected in the clone TB isolates. Their accessory genome mainly differed in prophage-like DNA elements taken up by one of the strains. Conclusions The higher geographical and temporal distance of the clone CHA isolates was associated with an increased intraclonal genome diversity compared to the more closely related clone TB isolates derived from a common source demonstrating the impact of habitat adaptation on the microevolution of P. aeruginosa. However, even short-term habitat differentiation can cause major phenotypic diversification driven by single genomic variation events and uptake of phage

Urban Evolutionary Ecology and the Potential Benefits of Implementing Genomics.

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Schell, Christopher J

2018-02-14

Urban habitats are quickly becoming exceptional models to address adaptation under rapid environmental change, given the expansive temporal and spatial scales with which anthropogenic landscape conversion occurs. Urban ecologists in the last 10-15 years have done an extraordinary job of highlighting phenotypic patterns that correspond with urban living, as well as delineating urban population structure using traditional genetic markers. The underpinning genetic mechanisms that govern those phenotypic patterns, however, are less well established. Moreover, the power of traditional molecular studies is constrained by the number of markers being evaluated, which limits the potential to assess fine-scale population structure potentially common in urban areas. With the recent proliferation of low-cost, high-throughput sequencing methods, we can begin to address an emerging question in urban ecology: are species adapted to local optima within cities or are they expressing latent phenotypic plasticity? Here, I provide a comprehensive review of previous urban ecological studies, with special focus on the molecular ecology and phenotypic adjustments documented in urban terrestrial and amphibious fauna. I subsequently pinpoint areas in the literature that could benefit from a genomic investigation and briefly discuss the suitability of specific techniques in addressing eco-evolutionary questions within urban ecology. Though many challenges exist with implementing genomics into urban ecology, such studies provide an exceptional opportunity to advance our understanding of eco-evolutionary processes in metropolitan areas. © The American Genetic Association 2018. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Functional validation of candidate genes detected by genomic feature models

DEFF Research Database (Denmark)

Rohde, Palle Duun; Østergaard, Solveig; Kristensen, Torsten Nygaard

2018-01-01

Understanding the genetic underpinnings of complex traits requires knowledge of the genetic variants that contribute to phenotypic variability. Reliable statistical approaches are needed to obtain such knowledge. In genome-wide association studies, variants are tested for association with trait...... then functionally assessed whether the identified candidate genes affected locomotor activity by reducing gene expression using RNA interference. In five of the seven candidate genes tested, reduced gene expression altered the phenotype. The ranking of genes within the predictive GO term was highly correlated...

Combining genomic and proteomic approaches for epigenetics research

Science.gov (United States)

Han, Yumiao; Garcia, Benjamin A

2014-01-01

Epigenetics is the study of changes in gene expression or cellular phenotype that do not change the DNA sequence. In this review, current methods, both genomic and proteomic, associated with epigenetics research are discussed. Among them, chromatin immunoprecipitation (ChIP) followed by sequencing and other ChIP-based techniques are powerful techniques for genome-wide profiling of DNA-binding proteins, histone post-translational modifications or nucleosome positions. However, mass spectrometry-based proteomics is increasingly being used in functional biological studies and has proved to be an indispensable tool to characterize histone modifications, as well as DNA–protein and protein–protein interactions. With the development of genomic and proteomic approaches, combination of ChIP and mass spectrometry has the potential to expand our knowledge of epigenetics research to a higher level. PMID:23895656

Analysis Of Segmental Duplications In The Pig Genome Based On Next-Generation Sequencing

DEFF Research Database (Denmark)

Fadista, João; Bendixen, Christian

Segmental duplications are >1kb segments of duplicated DNA present in a genome with high sequence identity (>90%). They are associated with genomic rearrangements and provide a significant source of gene and genome evolution within mammalian genomes. Although segmental duplications have been...... extensively studied in other organisms, its analysis in pig has been hampered by the lack of a complete pig genome assembly. By measuring the depth of coverage of Illumina whole-genome shotgun sequencing reads of the Tabasco animal aligned to the latest pig genome assembly (Sus scrofa 10 – based also...... and their associated copy number alterations, focusing on the global organization of these segments and their possible functional significance in porcine phenotypes. This work provides insights into mammalian genome evolution and generates a valuable resource for porcine genomics research...

Genomics and fish adaptation

Directory of Open Access Journals (Sweden)

Agostinho Antunes

2015-12-01

Full Text Available The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of varied fish species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

GUESS-ing polygenic associations with multiple phenotypes using a GPU-based evolutionary stochastic search algorithm.

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Leonardo Bottolo

Full Text Available Genome-wide association studies (GWAS yielded significant advances in defining the genetic architecture of complex traits and disease. Still, a major hurdle of GWAS is narrowing down multiple genetic associations to a few causal variants for functional studies. This becomes critical in multi-phenotype GWAS where detection and interpretability of complex SNP(s-trait(s associations are complicated by complex Linkage Disequilibrium patterns between SNPs and correlation between traits. Here we propose a computationally efficient algorithm (GUESS to explore complex genetic-association models and maximize genetic variant detection. We integrated our algorithm with a new Bayesian strategy for multi-phenotype analysis to identify the specific contribution of each SNP to different trait combinations and study genetic regulation of lipid metabolism in the Gutenberg Health Study (GHS. Despite the relatively small size of GHS (n  =  3,175, when compared with the largest published meta-GWAS (n > 100,000, GUESS recovered most of the major associations and was better at refining multi-trait associations than alternative methods. Amongst the new findings provided by GUESS, we revealed a strong association of SORT1 with TG-APOB and LIPC with TG-HDL phenotypic groups, which were overlooked in the larger meta-GWAS and not revealed by competing approaches, associations that we replicated in two independent cohorts. Moreover, we demonstrated the increased power of GUESS over alternative multi-phenotype approaches, both Bayesian and non-Bayesian, in a simulation study that mimics real-case scenarios. We showed that our parallel implementation based on Graphics Processing Units outperforms alternative multi-phenotype methods. Beyond multivariate modelling of multi-phenotypes, our Bayesian model employs a flexible hierarchical prior structure for genetic effects that adapts to any correlation structure of the predictors and increases the power to identify

Toward the use of genomics to study microevolutionary change in bacteria.

LENUS (Irish Health Repository)

Falush, Daniel

2009-10-01

Bacteria evolve rapidly in response to the environment they encounter. Some environmental changes are experienced numerous times by bacteria from the same population, providing an opportunity to dissect the genetic basis of adaptive evolution. Here I discuss two examples in which the patterns of rapid change provide insight into medically important bacterial phenotypes, namely immune escape by Neisseria meningitidis and host specificity of Campylobacter jejuni. Genomic analysis of populations of bacteria from these species holds great promise but requires appropriate concepts and statistical tools.

Toward the use of genomics to study microevolutionary change in bacteria.

Directory of Open Access Journals (Sweden)

Daniel Falush

2009-10-01

Full Text Available Bacteria evolve rapidly in response to the environment they encounter. Some environmental changes are experienced numerous times by bacteria from the same population, providing an opportunity to dissect the genetic basis of adaptive evolution. Here I discuss two examples in which the patterns of rapid change provide insight into medically important bacterial phenotypes, namely immune escape by Neisseria meningitidis and host specificity of Campylobacter jejuni. Genomic analysis of populations of bacteria from these species holds great promise but requires appropriate concepts and statistical tools.

Genetic and Computational Approaches for Studying Plant Development and Abiotic Stress Responses Using Image-Based Phenotyping

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Campbell, M. T.; Walia, H.; Grondin, A.; Knecht, A.

2017-12-01

The development of abiotic stress tolerant crops (i.e. drought, salinity, or heat stress) requires the discovery of DNA sequence variants associated with stress tolerance-related traits. However, many traits underlying adaptation to abiotic stress involve a suite of physiological pathways that may be induced at different times throughout the duration of stress. Conventional single-point phenotyping approaches fail to fully capture these temporal responses, and thus downstream genetic analysis may only identify a subset of the genetic variants that are important for adaptation to sub-optimal environments. Although genomic resources for crops have advanced tremendously, the collection of phenotypic data for morphological and physiological traits is laborious and remains a significant bottleneck in bridging the phenotype-genotype gap. In recent years, the availability of automated, image-based phenotyping platforms has provided researchers with an opportunity to collect morphological and physiological traits non-destructively in a highly controlled environment. Moreover, these platforms allow abiotic stress responses to be recorded throughout the duration of the experiment, and have facilitated the use of function-valued traits for genetic analyses in major crops. We will present our approaches for addressing abiotic stress tolerance in cereals. This talk will focus on novel open-source software to process and extract biological meaningful data from images generated from these phenomics platforms. In addition, we will discuss the statistical approaches to model longitudinal phenotypes and dissect the genetic basis of dynamic responses to these abiotic stresses throughout development.

Genome size evolution in Ontario ferns (Polypodiidae): evolutionary correlations with cell size, spore size, and habitat type and an absence of genome downsizing.

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Henry, Thomas A; Bainard, Jillian D; Newmaster, Steven G

2014-10-01

Genome size is known to correlate with a number of traits in angiosperms, but less is known about the phenotypic correlates of genome size in ferns. We explored genome size variation in relation to a suite of morphological and ecological traits in ferns. Thirty-six fern taxa were collected from wild populations in Ontario, Canada. 2C DNA content was measured using flow cytometry. We tested for genome downsizing following polyploidy using a phylogenetic comparative analysis to explore the correlation between 1Cx DNA content and ploidy. There was no compelling evidence for the occurrence of widespread genome downsizing during the evolution of Ontario ferns. The relationship between genome size and 11 morphological and ecological traits was explored using a phylogenetic principal component regression analysis. Genome size was found to be significantly associated with cell size, spore size, spore type, and habitat type. These results are timely as past and recent studies have found conflicting support for the association between ploidy/genome size and spore size in fern polyploid complexes; this study represents the first comparative analysis of the trend across a broad taxonomic group of ferns.

Linkage analysis using co-phenotypes in the BRIGHT study reveals novel potential susceptibility loci for hypertension.

Science.gov (United States)

Wallace, Chris; Xue, Ming-Zhan; Newhouse, Stephen J; Marcano, Ana Carolina B; Onipinla, Abiodun K; Burke, Beverley; Gungadoo, Johannie; Dobson, Richard J; Brown, Morris; Connell, John M; Dominiczak, Anna; Lathrop, G Mark; Webster, John; Farrall, Martin; Mein, Charles; Samani, Nilesh J; Caulfield, Mark J; Clayton, David G; Munroe, Patricia B

2006-08-01

Identification of the genetic influences on human essential hypertension and other complex diseases has proved difficult, partly because of genetic heterogeneity. In many complex-trait resources, additional phenotypic data have been collected, allowing comorbid intermediary phenotypes to be used to characterize more genetically homogeneous subsets. The traditional approach to analyzing covariate-defined subsets has typically depended on researchers' previous expectations for definition of a comorbid subset and leads to smaller data sets, with a concomitant attrition in power. An alternative is to test for dependence between genetic sharing and covariates across the entire data set. This approach offers the advantage of exploiting the full data set and could be widely applied to complex-trait genome scans. However, existing maximum-likelihood methods can be prohibitively computationally expensive, especially since permutation is often required to determine significance. We developed a less computationally intensive score test and applied it to biometric and biochemical covariate data, from 2,044 sibling pairs with severe hypertension, collected by the British Genetics of Hypertension (BRIGHT) study. We found genomewide-significant evidence for linkage with hypertension and several related covariates. The strongest signals were with leaner-body-mass measures on chromosome 20q (maximum LOD = 4.24) and with parameters of renal function on chromosome 5p (maximum LOD = 3.71). After correction for the multiple traits and genetic locations studied, our global genomewide P value was .046. This is the first identity-by-descent regression analysis of hypertension to our knowledge, and it demonstrates the value of this approach for the incorporation of additional phenotypic information in genetic studies of complex traits.

The tiger genome and comparative analysis with lion and snow leopard genomes.

Science.gov (United States)

Cho, Yun Sung; Hu, Li; Hou, Haolong; Lee, Hang; Xu, Jiaohui; Kwon, Soowhan; Oh, Sukhun; Kim, Hak-Min; Jho, Sungwoong; Kim, Sangsoo; Shin, Young-Ah; Kim, Byung Chul; Kim, Hyunmin; Kim, Chang-Uk; Luo, Shu-Jin; Johnson, Warren E; Koepfli, Klaus-Peter; Schmidt-Küntzel, Anne; Turner, Jason A; Marker, Laurie; Harper, Cindy; Miller, Susan M; Jacobs, Wilhelm; Bertola, Laura D; Kim, Tae Hyung; Lee, Sunghoon; Zhou, Qian; Jung, Hyun-Ju; Xu, Xiao; Gadhvi, Priyvrat; Xu, Pengwei; Xiong, Yingqi; Luo, Yadan; Pan, Shengkai; Gou, Caiyun; Chu, Xiuhui; Zhang, Jilin; Liu, Sanyang; He, Jing; Chen, Ying; Yang, Linfeng; Yang, Yulan; He, Jiaju; Liu, Sha; Wang, Junyi; Kim, Chul Hong; Kwak, Hwanjong; Kim, Jong-Soo; Hwang, Seungwoo; Ko, Junsu; Kim, Chang-Bae; Kim, Sangtae; Bayarlkhagva, Damdin; Paek, Woon Kee; Kim, Seong-Jin; O'Brien, Stephen J; Wang, Jun; Bhak, Jong

2013-01-01

Tigers and their close relatives (Panthera) are some of the world's most endangered species. Here we report the de novo assembly of an Amur tiger whole-genome sequence as well as the genomic sequences of a white Bengal tiger, African lion, white African lion and snow leopard. Through comparative genetic analyses of these genomes, we find genetic signatures that may reflect molecular adaptations consistent with the big cats' hypercarnivorous diet and muscle strength. We report a snow leopard-specific genetic determinant in EGLN1 (Met39>Lys39), which is likely to be associated with adaptation to high altitude. We also detect a TYR260G>A mutation likely responsible for the white lion coat colour. Tiger and cat genomes show similar repeat composition and an appreciably conserved synteny. Genomic data from the five big cats provide an invaluable resource for resolving easily identifiable phenotypes evident in very close, but distinct, species.

The tiger genome and comparative analysis with lion and snow leopard genomes

Science.gov (United States)

Cho, Yun Sung; Hu, Li; Hou, Haolong; Lee, Hang; Xu, Jiaohui; Kwon, Soowhan; Oh, Sukhun; Kim, Hak-Min; Jho, Sungwoong; Kim, Sangsoo; Shin, Young-Ah; Kim, Byung Chul; Kim, Hyunmin; Kim, Chang-uk; Luo, Shu-Jin; Johnson, Warren E.; Koepfli, Klaus-Peter; Schmidt-Küntzel, Anne; Turner, Jason A.; Marker, Laurie; Harper, Cindy; Miller, Susan M.; Jacobs, Wilhelm; Bertola, Laura D.; Kim, Tae Hyung; Lee, Sunghoon; Zhou, Qian; Jung, Hyun-Ju; Xu, Xiao; Gadhvi, Priyvrat; Xu, Pengwei; Xiong, Yingqi; Luo, Yadan; Pan, Shengkai; Gou, Caiyun; Chu, Xiuhui; Zhang, Jilin; Liu, Sanyang; He, Jing; Chen, Ying; Yang, Linfeng; Yang, Yulan; He, Jiaju; Liu, Sha; Wang, Junyi; Kim, Chul Hong; Kwak, Hwanjong; Kim, Jong-Soo; Hwang, Seungwoo; Ko, Junsu; Kim, Chang-Bae; Kim, Sangtae; Bayarlkhagva, Damdin; Paek, Woon Kee; Kim, Seong-Jin; O’Brien, Stephen J.; Wang, Jun; Bhak, Jong

2013-01-01

Tigers and their close relatives (Panthera) are some of the world’s most endangered species. Here we report the de novo assembly of an Amur tiger whole-genome sequence as well as the genomic sequences of a white Bengal tiger, African lion, white African lion and snow leopard. Through comparative genetic analyses of these genomes, we find genetic signatures that may reflect molecular adaptations consistent with the big cats’ hypercarnivorous diet and muscle strength. We report a snow leopard-specific genetic determinant in EGLN1 (Met39>Lys39), which is likely to be associated with adaptation to high altitude. We also detect a TYR260G>A mutation likely responsible for the white lion coat colour. Tiger and cat genomes show similar repeat composition and an appreciably conserved synteny. Genomic data from the five big cats provide an invaluable resource for resolving easily identifiable phenotypes evident in very close, but distinct, species. PMID:24045858

Using trajectory analyses to refine phenotype for genetic association: conduct problems and the serotonin transporter (5HTTLPR).

Science.gov (United States)

Sakai, Joseph T; Boardman, Jason D; Gelhorn, Heather L; Smolen, Andrew; Corley, Robin P; Huizinga, David; Menard, Scott; Hewitt, John K; Stallings, Michael C

2010-10-01

Conduct disorder is a serious, relatively common disorder of childhood and adolescence. Findings from genetic association studies searching for genetic determinants of the liability toward such behaviors have been inconsistent. One possible explanation for differential results is that most studies define phenotype from a single assessment; for many adolescents conduct problems decrease in severity over time, whereas for others such behaviors persist. Therefore, longitudinal datasets offer the opportunity to refine phenotype. We used Caucasians that were first assessed during adolescence from the National Youth Survey Family Study. Nine waves of data were used to create latent growth trajectories and test for associations between trajectory class and 5HTTLPR genotype. For the full sample, 5HTTLPR was not associated with conduct problem phenotypes. However, the short (s) allele was associated with chronic conduct problems in females; a nominally significant sex by 5HTTLPR genotype interaction was noted. Longitudinal studies provide unique opportunities for phenotypic refinement and such techniques, with large samples, may be useful for phenotypic definition with other study designs, such as whole genome association studies.

Glioblastoma-infiltrated innate immune cells resemble M0 macrophage phenotype

Science.gov (United States)

Gabrusiewicz, Konrad; Rodriguez, Benjamin; Wei, Jun; Hashimoto, Yuuri; Healy, Luke M.; Maiti, Sourindra N.; Wang, Qianghu; Elakkad, Ahmed; Liebelt, Brandon D.; Yaghi, Nasser K.; Ezhilarasan, Ravesanker; Huang, Neal; Weinberg, Jeffrey S.; Prabhu, Sujit S.; Rao, Ganesh; Sawaya, Raymond; Langford, Lauren A.; Bruner, Janet M.; Fuller, Gregory N.; Bar-Or, Amit; Li, Wei; Colen, Rivka R.; Curran, Michael A.; Bhat, Krishna P.; Antel, Jack P.; Cooper, Laurence J.; Sulman, Erik P.; Heimberger, Amy B.

2016-01-01

Glioblastomas are highly infiltrated by diverse immune cells, including microglia, macrophages, and myeloid-derived suppressor cells (MDSCs). Understanding the mechanisms by which glioblastoma-associated myeloid cells (GAMs) undergo metamorphosis into tumor-supportive cells, characterizing the heterogeneity of immune cell phenotypes within glioblastoma subtypes, and discovering new targets can help the design of new efficient immunotherapies. In this study, we performed a comprehensive battery of immune phenotyping, whole-genome microarray analysis, and microRNA expression profiling of GAMs with matched blood monocytes, healthy donor monocytes, normal brain microglia, nonpolarized M0 macrophages, and polarized M1, M2a, M2c macrophages. Glioblastoma patients had an elevated number of monocytes relative to healthy donors. Among CD11b+ cells, microglia and MDSCs constituted a higher percentage of GAMs than did macrophages. GAM profiling using flow cytometry studies revealed a continuum between the M1- and M2-like phenotype. Contrary to current dogma, GAMs exhibited distinct immunological functions, with the former aligned close to nonpolarized M0 macrophages. PMID:26973881

Whole-Genome Sequence Analysis of Antimicrobial Resistance Genes in Streptococcus uberis and Streptococcus dysgalactiae Isolates from Canadian Dairy Herds

Directory of Open Access Journals (Sweden)

Julián Reyes Vélez

2017-05-01

Full Text Available The objectives of this study are to determine the occurrence of antimicrobial resistance (AMR genes using whole-genome sequence (WGS of Streptococcus uberis (S. uberis and Streptococcus dysgalactiae (S. dysgalactiae isolates, recovered from dairy cows in the Canadian Maritime Provinces. A secondary objective included the exploration of the association between phenotypic AMR and the genomic characteristics (genome size, guanine–cytosine content, and occurrence of unique gene sequences. Initially, 91 isolates were sequenced, and of these isolates, 89 were assembled. Furthermore, 16 isolates were excluded due to larger than expected genomic sizes (>2.3 bp × 1,000 bp. In the final analysis, 73 were used with complete WGS and minimum inhibitory concentration records, which were part of the previous phenotypic AMR study, representing 18 dairy herds from the Maritime region of Canada (1. A total of 23 unique AMR gene sequences were found in the bacterial genomes, with a mean number of 8.1 (minimum: 5; maximum: 13 per genome. Overall, there were 10 AMR genes [ANT(6, TEM-127, TEM-163, TEM-89, TEM-95, Linb, Lnub, Ermb, Ermc, and TetS] present only in S. uberis genomes and 2 genes unique (EF-TU and TEM-71 to the S. dysgalactiae genomes; 11 AMR genes [APH(3′, TEM-1, TEM-136, TEM-157, TEM-47, TetM, bl2b, gyrA, parE, phoP, and rpoB] were found in both bacterial species. Two-way tabulations showed association between the phenotypic susceptibility to lincosamides and the presence of linB (P = 0.002 and lnuB (P < 0.001 genes and the between the presence of tetM (P = 0.015 and tetS (P = 0.064 genes and phenotypic resistance to tetracyclines only for the S. uberis isolates. The logistic model showed that the odds of resistance (to any of the phenotypically tested antimicrobials was 4.35 times higher when there were >11 AMR genes present in the genome, compared with <7 AMR genes (P < 0.001. The odds of resistance was lower for S

Statistical power and utility of meta-analysis methods for cross-phenotype genome-wide association studies.

Science.gov (United States)

Zhu, Zhaozhong; Anttila, Verneri; Smoller, Jordan W; Lee, Phil H

2018-01-01

Advances in recent genome wide association studies (GWAS) suggest that pleiotropic effects on human complex traits are widespread. A number of classic and recent meta-analysis methods have been used to identify genetic loci with pleiotropic effects, but the overall performance of these methods is not well understood. In this work, we use extensive simulations and case studies of GWAS datasets to investigate the power and type-I error rates of ten meta-analysis methods. We specifically focus on three conditions commonly encountered in the studies of multiple traits: (1) extensive heterogeneity of genetic effects; (2) characterization of trait-specific association; and (3) inflated correlation of GWAS due to overlapping samples. Although the statistical power is highly variable under distinct study conditions, we found the superior power of several methods under diverse heterogeneity. In particular, classic fixed-effects model showed surprisingly good performance when a variant is associated with more than a half of study traits. As the number of traits with null effects increases, ASSET performed the best along with competitive specificity and sensitivity. With opposite directional effects, CPASSOC featured the first-rate power. However, caution is advised when using CPASSOC for studying genetically correlated traits with overlapping samples. We conclude with a discussion of unresolved issues and directions for future research.

Integrated Genome-Based Studies of Shewanella Ecophysiology

Energy Technology Data Exchange (ETDEWEB)

Andrei L. Osterman, Ph.D.

2012-12-17

Integration of bioinformatics and experimental techniques was applied to mapping and characterization of the key components (pathways, enzymes, transporters, regulators) of the core metabolic machinery in Shewanella oneidensis and related species with main focus was on metabolic and regulatory pathways involved in utilization of various carbon and energy sources. Among the main accomplishments reflected in ten joint publications with other participants of Shewanella Federation are: (i) A systems-level reconstruction of carbohydrate utilization pathways in the genus of Shewanella (19 species). This analysis yielded reconstruction of 18 sugar utilization pathways including 10 novel pathway variants and prediction of > 60 novel protein families of enzymes, transporters and regulators involved in these pathways. Selected functional predictions were verified by focused biochemical and genetic experiments. Observed growth phenotypes were consistent with bioinformatic predictions providing strong validation of the technology and (ii) Global genomic reconstruction of transcriptional regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors, 8 riboswitches and 6 translational attenuators. Of those, 45 regulons were inferred directly from the genome context analysis, whereas others were propagated from previously characterized regulons in other species. Selected regulatory predictions were experimentally tested. Integration of this analysis with microarray data revealed overall consistency and provided additional layer of interactions between regulons. All the results were captured in the new database RegPrecise, which is a joint development with the LBNL team. A more detailed analysis of the individual subsystems, pathways and regulons in Shewanella spp included bioinfiormatics-based prediction and experimental characterization of: (i) N-Acetylglucosamine catabolic pathway; (ii)Lactate utilization machinery; (iii) Novel Nrt

Genome-Wide Association Mapping of Flowering and Ripening Periods in Apple

Directory of Open Access Journals (Sweden)

Jorge Urrestarazu

2017-11-01

Full Text Available Deciphering the genetic control of flowering and ripening periods in apple is essential for breeding cultivars adapted to their growing environments. We implemented a large Genome-Wide Association Study (GWAS at the European level using an association panel of 1,168 different apple genotypes distributed over six locations and phenotyped for these phenological traits. The panel was genotyped at a high-density of SNPs using the Axiom®Apple 480 K SNP array. We ran GWAS with a multi-locus mixed model (MLMM, which handles the putatively confounding effect of significant SNPs elsewhere on the genome. Genomic regions were further investigated to reveal candidate genes responsible for the phenotypic variation. At the whole population level, GWAS retained two SNPs as cofactors on chromosome 9 for flowering period, and six for ripening period (four on chromosome 3, one on chromosome 10 and one on chromosome 16 which, together accounted for 8.9 and 17.2% of the phenotypic variance, respectively. For both traits, SNPs in weak linkage disequilibrium were detected nearby, thus suggesting the existence of allelic heterogeneity. The geographic origins and relationships of apple cultivars accounted for large parts of the phenotypic variation. Variation in genotypic frequency of the SNPs associated with the two traits was connected to the geographic origin of the genotypes (grouped as North+East, West and South Europe, and indicated differential selection in different growing environments. Genes encoding transcription factors containing either NAC or MADS domains were identified as major candidates within the small confidence intervals computed for the associated genomic regions. A strong microsynteny between apple and peach was revealed in all the four confidence interval regions. This study shows how association genetics can unravel the genetic control of important horticultural traits in apple, as well as reduce the confidence intervals of the associated

Genetic and phenotypic intra-species variation in Candida albicans.

Science.gov (United States)

Hirakawa, Matthew P; Martinez, Diego A; Sakthikumar, Sharadha; Anderson, Matthew Z; Berlin, Aaron; Gujja, Sharvari; Zeng, Qiandong; Zisson, Ethan; Wang, Joshua M; Greenberg, Joshua M; Berman, Judith; Bennett, Richard J; Cuomo, Christina A

2015-03-01

Candida albicans is a commensal fungus of the human gastrointestinal tract and a prevalent opportunistic pathogen. To examine diversity within this species, extensive genomic and phenotypic analyses were performed on 21 clinical C. albicans isolates. Genomic variation was evident in the form of polymorphisms, copy number variations, chromosomal inversions, subtelomeric hypervariation, loss of heterozygosity (LOH), and whole or partial chromosome aneuploidies. All 21 strains were diploid, although karyotypic changes were present in eight of the 21 isolates, with multiple strains being trisomic for Chromosome 4 or Chromosome 7. Aneuploid strains exhibited a general fitness defect relative to euploid strains when grown under replete conditions. All strains were also heterozygous, yet multiple, distinct LOH tracts were present in each isolate. Higher overall levels of genome heterozygosity correlated with faster growth rates, consistent with increased overall fitness. Genes with the highest rates of amino acid substitutions included many cell wall proteins, implicating fast evolving changes in cell adhesion and host interactions. One clinical isolate, P94015, presented several striking properties including a novel cellular phenotype, an inability to filament, drug resistance, and decreased virulence. Several of these properties were shown to be due to a homozygous nonsense mutation in the EFG1 gene. Furthermore, loss of EFG1 function resulted in increased fitness of P94015 in a commensal model of infection. Our analysis therefore reveals intra-species genetic and phenotypic differences in C. albicans and delineates a natural mutation that alters the balance between commensalism and pathogenicity. © 2015 Hirakawa et al.; Published by Cold Spring Harbor Laboratory Press.

Phenotypic and genomic responses to titanium dioxide and cerium oxide nanoparticles in Arabidopsis germinants

Science.gov (United States)

The effects of exposure to two nanoparticles (NPs) -titanium dioxide (nano-titania) and cerium oxide (nano-ceria) at 500 mg NPs L-1 on gene expression and growth in Arabidopsis thaliana germinants were studied using microarrays and phenotype studies. After 12 days post treatment,...

A survey of single nucleotide polymorphisms identified from whole-genome sequencing and their functional effect in the porcine genome.

Science.gov (United States)

Keel, B N; Nonneman, D J; Rohrer, G A

2017-08-01

Genetic variants detected from sequence have been used to successfully identify causal variants and map complex traits in several organisms. High and moderate impact variants, those expected to alter or disrupt the protein coded by a gene and those that regulate protein production, likely have a more significant effect on phenotypic variation than do other types of genetic variants. Hence, a comprehensive list of these functional variants would be of considerable interest in swine genomic studies, particularly those targeting fertility and production traits. Whole-genome sequence was obtained from 72 of the founders of an intensely phenotyped experimental swine herd at the U.S. Meat Animal Research Center (USMARC). These animals included all 24 of the founding boars (12 Duroc and 12 Landrace) and 48 Yorkshire-Landrace composite sows. Sequence reads were mapped to the Sscrofa10.2 genome build, resulting in a mean of 6.1 fold (×) coverage per genome. A total of 22 342 915 high confidence SNPs were identified from the sequenced genomes. These included 21 million previously reported SNPs and 79% of the 62 163 SNPs on the PorcineSNP60 BeadChip assay. Variation was detected in the coding sequence or untranslated regions (UTRs) of 87.8% of the genes in the porcine genome: loss-of-function variants were predicted in 504 genes, 10 202 genes contained nonsynonymous variants, 10 773 had variation in UTRs and 13 010 genes contained synonymous variants. Approximately 139 000 SNPs were classified as loss-of-function, nonsynonymous or regulatory, which suggests that over 99% of the variation detected in our pigs could potentially be ignored, allowing us to focus on a much smaller number of functional SNPs during future analyses. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Analysis of Genome-Scale Data

OpenAIRE

Kemmeren, P.P.C.W.

2005-01-01

The genetic material of every cell in an organism is stored inside DNA in the form of genes, which together form the genome. The information stored in the DNA is translated to RNA and subsequently to proteins, which form complex biological systems. The availability of whole genome sequences has given rise to the parallel development of other high-throughput approaches such as determining mRNA expression level changes, gene-deletion phenotypes, chromosomal location of DNA binding proteins, cel...

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.