Genome wide study of maternal and parent-of-origin effects on the etiology of orofacial clefts

Science.gov (United States)

Shi, Min; Murray, Jeffrey C; Marazita, Mary L; Munger, Ronald G; Ruczinski, Ingo; Hetmanski, Jacqueline B; Wu, Tao; Murray, Tanda; Redett, Richard J; Wilcox, Allen J; Lie, Rolv T; Jabs, Ethylin Wang; Wu-Chou, Yah Huei; Chen, Philip K; Wang, Hong; Ye, Xiaoqian; Yeow, Vincent; Chong, Samuel S; Shi, Bing; Christensen, Kaare; Scott, Alan F; Patel, Poorav; Cheah, Felicia; Beaty, Terri H

2013-01-01

We performed a genome wide association analysis of maternally-mediated genetic effects and parent-of-origin effects on risk of orofacial clefting using over 2,000 case-parent triads collected through an international cleft consortium. We used log-linear regression models to test individual SNPs. For SNPs with a p-value <10−5 for maternal genotypic effects, we also applied a haplotype-based method, TRIMM, to extract potential information from clusters of correlated SNPs. None of the SNPs were significant at the genome wide level. Our results suggest neither maternal genome nor parent of origin effects play major roles in the etiology of orofacial clefting in our sample. This finding is consistent with previous genetic studies and recent population-based cohort studies in Norway and Denmark, which showed no apparent difference between mother-to-offspring and father-to-offspring recurrence of clefting. We, however, cannot completely rule out maternal genome or parent of origin effects as risk factors because very small effects might not be detectable with our sample size, they may influence risk through interactions with environmental exposures or may act through a more complex network of interacting genes. Thus the most promising SNPs identified by this study may still be worth further investigation. PMID:22419666

Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci

DEFF Research Database (Denmark)

Børglum, A D; Demontis, D; Grove, J

2014-01-01

Genetic and environmental components as well as their interaction contribute to the risk of schizophrenia, making it highly relevant to include environmental factors in genetic studies of schizophrenia. This study comprises genome-wide association (GWA) and follow-up analyses of all individuals...... born in Denmark since 1981 and diagnosed with schizophrenia as well as controls from the same birth cohort. Furthermore, we present the first genome-wide interaction survey of single nucleotide polymorphisms (SNPs) and maternal cytomegalovirus (CMV) infection. The GWA analysis included 888 cases...... was found for rs7902091 (P(SNP × CMV)=7.3 × 10(-7)) in CTNNA3, a gene not previously implicated in schizophrenia, stressing the importance of including environmental factors in genetic studies....

An R package "VariABEL" for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity

Directory of Open Access Journals (Sweden)

Struchalin Maksim V

2012-01-01

Full Text Available Abstract Background Hundreds of new loci have been discovered by genome-wide association studies of human traits. These studies mostly focused on associations between single locus and a trait. Interactions between genes and between genes and environmental factors are of interest as they can improve our understanding of the genetic background underlying complex traits. Genome-wide testing of complex genetic models is a computationally demanding task. Moreover, testing of such models leads to multiple comparison problems that reduce the probability of new findings. Assuming that the genetic model underlying a complex trait can include hundreds of genes and environmental factors, testing of these models in genome-wide association studies represent substantial difficulties. We and Pare with colleagues (2010 developed a method allowing to overcome such difficulties. The method is based on the fact that loci which are involved in interactions can show genotypic variance heterogeneity of a trait. Genome-wide testing of such heterogeneity can be a fast scanning approach which can point to the interacting genetic variants. Results In this work we present a new method, SVLM, allowing for variance heterogeneity analysis of imputed genetic variation. Type I error and power of this test are investigated and contracted with these of the Levene's test. We also present an R package, VariABEL, implementing existing and newly developed tests. Conclusions Variance heterogeneity analysis is a promising method for detection of potentially interacting loci. New method and software package developed in this work will facilitate such analysis in genome-wide context.

No evidence for genome-wide interactions on plasma fibrinogen by smoking, alcohol consumption and body mass index: results from meta-analyses of 80,607 subjects.

Directory of Open Access Journals (Sweden)

Jens Baumert

Full Text Available Plasma fibrinogen is an acute phase protein playing an important role in the blood coagulation cascade having strong associations with smoking, alcohol consumption and body mass index (BMI. Genome-wide association studies (GWAS have identified a variety of gene regions associated with elevated plasma fibrinogen concentrations. However, little is yet known about how associations between environmental factors and fibrinogen might be modified by genetic variation. Therefore, we conducted large-scale meta-analyses of genome-wide interaction studies to identify possible interactions of genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentration. The present study included 80,607 subjects of European ancestry from 22 studies. Genome-wide interaction analyses were performed separately in each study for about 2.6 million single nucleotide polymorphisms (SNPs across the 22 autosomal chromosomes. For each SNP and risk factor, we performed a linear regression under an additive genetic model including an interaction term between SNP and risk factor. Interaction estimates were meta-analysed using a fixed-effects model. No genome-wide significant interaction with smoking status, alcohol consumption or BMI was observed in the meta-analyses. The most suggestive interaction was found for smoking and rs10519203, located in the LOC123688 region on chromosome 15, with a p value of 6.2 × 10(-8. This large genome-wide interaction study including 80,607 participants found no strong evidence of interaction between genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentrations. Further studies are needed to yield deeper insight in the interplay between environmental factors and gene variants on the regulation of fibrinogen concentrations.

Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics

NARCIS (Netherlands)

Lundby, Alicia; Rossin, Elizabeth J.; Steffensen, Annette B.; Acha, Moshe Ray; Newton-Cheh, Christopher; Pfeufer, Arne; Lyneh, Stacey N.; Olesen, Soren-Peter; Brunak, Soren; Ellinor, Patrick T.; Jukema, J. Wouter; Trompet, Stella; Ford, Ian; Macfarlane, Peter W.; Krijthe, Bouwe P.; Hofman, Albert; Uitterlinden, Andre G.; Stricker, Bruno H.; Nathoe, Hendrik M.; Spiering, Wilko; Daly, Mark J.; Asselbergs, Ikea W.; van der Harst, Pim; Milan, David J.; de Bakker, Paul I. W.; Lage, Kasper; Olsen, Jesper V.

Genome-wide association studies (GWAS) have identified thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes

Genome-wide analysis of E. coli cell-gene interactions.

Science.gov (United States)

Cardinale, S; Cambray, G

2017-11-23

The pursuit of standardization and reliability in synthetic biology has achieved, in recent years, a number of advances in the design of more predictable genetic parts for biological circuits. However, even with the development of high-throughput screening methods and whole-cell models, it is still not possible to predict reliably how a synthetic genetic construct interacts with all cellular endogenous systems. This study presents a genome-wide analysis of how the expression of synthetic genes is affected by systematic perturbations of cellular functions. We found that most perturbations modulate expression indirectly through an effect on cell size, putting forward the existence of a generic Size-Expression interaction in the model prokaryote Escherichia coli. The Size-Expression interaction was quantified by inserting a dual fluorescent reporter gene construct into each of the 3822 single-gene deletion strains comprised in the KEIO collection. Cellular size was measured for single cells via flow cytometry. Regression analyses were used to discriminate between expression-specific and gene-specific effects. Functions of the deleted genes broadly mapped onto three systems with distinct primary influence on the Size-Expression map. Perturbations in the Division and Biosynthesis (DB) system led to a large-cell and high-expression phenotype. In contrast, disruptions of the Membrane and Motility (MM) system caused small-cell and low-expression phenotypes. The Energy, Protein synthesis and Ribosome (EPR) system was predominantly associated with smaller cells and positive feedback on ribosome function. Feedback between cell growth and gene expression is widespread across cell systems. Even though most gene disruptions proximally affect one component of the Size-Expression interaction, the effect therefore ultimately propagates to both. More specifically, we describe the dual impact of growth on cell size and gene expression through cell division and ribosomal content

A genome-wide screen for interactions reveals a new locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol.

Directory of Open Access Journals (Sweden)

Ida Surakka

2011-10-01

Full Text Available Recent genome-wide association (GWA studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA data from 18 population-based cohorts with European ancestry (maximum N = 32,225. We collected 8 further cohorts (N = 17,102 for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR on total cholesterol (TC with a combined P-value of 4.79×10(-9. There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.

A novel test for gene-ancestry interactions in genome-wide association data.

Directory of Open Access Journals (Sweden)

Joanna L Davies

Full Text Available Genome-wide association study (GWAS data on a disease are increasingly available from multiple related populations. In this scenario, meta-analyses can improve power to detect homogeneous genetic associations, but if there exist ancestry-specific effects, via interactions on genetic background or with a causal effect that co-varies with genetic background, then these will typically be obscured. To address this issue, we have developed a robust statistical method for detecting susceptibility gene-ancestry interactions in multi-cohort GWAS based on closely-related populations. We use the leading principal components of the empirical genotype matrix to cluster individuals into "ancestry groups" and then look for evidence of heterogeneous genetic associations with disease or other trait across these clusters. Robustness is improved when there are multiple cohorts, as the signal from true gene-ancestry interactions can then be distinguished from gene-collection artefacts by comparing the observed interaction effect sizes in collection groups relative to ancestry groups. When applied to colorectal cancer, we identified a missense polymorphism in iron-absorption gene CYBRD1 that associated with disease in individuals of English, but not Scottish, ancestry. The association replicated in two additional, independently-collected data sets. Our method can be used to detect associations between genetic variants and disease that have been obscured by population genetic heterogeneity. It can be readily extended to the identification of genetic interactions on other covariates such as measured environmental exposures. We envisage our methodology being of particular interest to researchers with existing GWAS data, as ancestry groups can be easily defined and thus tested for interactions.

A Genome-Wide Screen for Interactions Reveals a New Locus on 4p15 Modifying the Effect of Waist-to-Hip Ratio on Total Cholesterol

DEFF Research Database (Denmark)

Surakka, I.; Isaacs, A.; Karssen, L. C.

2011-01-01

Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain similar to 25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened......, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79 x 10(-9). There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes...

Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent

DEFF Research Database (Denmark)

Smith, Caren E; Follis, Jack L; Dashti, Hassan S

2018-01-01

SCOPE: Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption. METHODS AND RESULTS: A genome-wide interaction study to discover genetic variants that account for variati...

Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci

NARCIS (Netherlands)

A.D. Børglum; D. Demontis; J. Grove (Jakob); J. Pallesen (J.); M.V. Hollegaard (Mads V); C.B. Pedersen (C.); A. Hedemand (A.); M. Mattheisen (Manuel); A.G. Uitterlinden (André); M. Nyegaard (M.); T.F. Orntoft (Torben); C. Wiuf (Carsten); M. Didriksen (Michael); M. Nordentoft (M.); M.M. Nö then (M.); M. Rietschel (Marcella); R.A. Ophoff (Roel); S. Cichon (Sven); R.H. Yolken (Robert); D.M. Hougaard (David); P.B. Mortensen; O. Mors

2014-01-01

textabstractGenetic and environmental components as well as their interaction contribute to the risk of schizophrenia, making it highly relevant to include environmental factors in genetic studies of schizophrenia. This study comprises genome-wide association (GWA) and follow-up analyses of all

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

Directory of Open Access Journals (Sweden)

Elisabeth M van Leeuwen

Full Text Available Genome-wide association studies (GWAS have revealed 74 single nucleotide polymorphisms (SNPs associated with high-density lipoprotein cholesterol (HDL blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS cohort I (RS-I using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III, we were able to filter 181 interaction terms with a p-value<1 · 10-8 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30,011 when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098 and rs12442098 in SPATA8 (ENSG00000185594 being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS.

Genome-wide joint meta-analysis of SNP and SNP-by-smoking interaction identifies novel loci for pulmonary function.

Directory of Open Access Journals (Sweden)

Dana B Hancock

Full Text Available Genome-wide association studies have identified numerous genetic loci for spirometic measures of pulmonary function, forced expiratory volume in one second (FEV(1, and its ratio to forced vital capacity (FEV(1/FVC. Given that cigarette smoking adversely affects pulmonary function, we conducted genome-wide joint meta-analyses (JMA of single nucleotide polymorphism (SNP and SNP-by-smoking (ever-smoking or pack-years associations on FEV(1 and FEV(1/FVC across 19 studies (total N = 50,047. We identified three novel loci not previously associated with pulmonary function. SNPs in or near DNER (smallest P(JMA = 5.00×10(-11, HLA-DQB1 and HLA-DQA2 (smallest P(JMA = 4.35×10(-9, and KCNJ2 and SOX9 (smallest P(JMA = 1.28×10(-8 were associated with FEV(1/FVC or FEV(1 in meta-analysis models including SNP main effects, smoking main effects, and SNP-by-smoking (ever-smoking or pack-years interaction. The HLA region has been widely implicated for autoimmune and lung phenotypes, unlike the other novel loci, which have not been widely implicated. We evaluated DNER, KCNJ2, and SOX9 and found them to be expressed in human lung tissue. DNER and SOX9 further showed evidence of differential expression in human airway epithelium in smokers compared to non-smokers. Our findings demonstrated that joint testing of SNP and SNP-by-environment interaction identified novel loci associated with complex traits that are missed when considering only the genetic main effects.

Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics

DEFF Research Database (Denmark)

Lundby, Alicia; Rossin, Elizabeth J.; Steffensen, Annette B.

2014-01-01

Genome-wide association studies (GWAS) have identified thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes...... involved in the Mendelian disorder long QT syndrome (LOTS). We integrated the LOTS network with GWAS loci from the corresponding common complex trait, QT-interval variation, to identify candidate genes that were subsequently confirmed in Xenopus laevis oocytes and zebrafish. We used the LOTS protein...... network to filter weak GWAS signals by identifying single-nucleotide polymorphisms (SNPs) in proximity to genes in the network supported by strong proteomic evidence. Three SNPs passing this filter reached genome-wide significance after replication genotyping. Overall, we present a general strategy...

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.

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.

Gene interactions in the DNA damage-response pathway identified by genome-wide RNA-interference analysis of synthetic lethality

NARCIS (Netherlands)

van Haaften, Gijs; Vastenhouw, Nadine L; Nollen, Ellen A A; Plasterk, Ronald H A; Tijsterman, Marcel

2004-01-01

Here, we describe a systematic search for synthetic gene interactions in a multicellular organism, the nematode Caenorhabditis elegans. We established a high-throughput method to determine synthetic gene interactions by genome-wide RNA interference and identified genes that are required to protect

Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci.

Science.gov (United States)

Børglum, A D; Demontis, D; Grove, J; Pallesen, J; Hollegaard, M V; Pedersen, C B; Hedemand, A; Mattheisen, M; Uitterlinden, A; Nyegaard, M; Ørntoft, T; Wiuf, C; Didriksen, M; Nordentoft, M; Nöthen, M M; Rietschel, M; Ophoff, R A; Cichon, S; Yolken, R H; Hougaard, D M; Mortensen, P B; Mors, O

2014-03-01

Genetic and environmental components as well as their interaction contribute to the risk of schizophrenia, making it highly relevant to include environmental factors in genetic studies of schizophrenia. This study comprises genome-wide association (GWA) and follow-up analyses of all individuals born in Denmark since 1981 and diagnosed with schizophrenia as well as controls from the same birth cohort. Furthermore, we present the first genome-wide interaction survey of single nucleotide polymorphisms (SNPs) and maternal cytomegalovirus (CMV) infection. The GWA analysis included 888 cases and 882 controls, and the follow-up investigation of the top GWA results was performed in independent Danish (1396 cases and 1803 controls) and German-Dutch (1169 cases, 3714 controls) samples. The SNPs most strongly associated in the single-marker analysis of the combined Danish samples were rs4757144 in ARNTL (P=3.78 × 10(-6)) and rs8057927 in CDH13 (P=1.39 × 10(-5)). Both genes have previously been linked to schizophrenia or other psychiatric disorders. The strongest associated SNP in the combined analysis, including Danish and German-Dutch samples, was rs12922317 in RUNDC2A (P=9.04 × 10(-7)). A region-based analysis summarizing independent signals in segments of 100 kb identified a new region-based genome-wide significant locus overlapping the gene ZEB1 (P=7.0 × 10(-7)). This signal was replicated in the follow-up analysis (P=2.3 × 10(-2)). Significant interaction with maternal CMV infection was found for rs7902091 (P(SNP × CMV)=7.3 × 10(-7)) in CTNNA3, a gene not previously implicated in schizophrenia, stressing the importance of including environmental factors in genetic studies.

Network Graph Analysis of Gene-Gene Interactions in Genome-Wide Association Study Data

Directory of Open Access Journals (Sweden)

Sungyoung Lee

2012-12-01

Full Text Available Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs. For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR is one of the powerful and efficient methods for detecting high-order gene-gene (GxG interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI. Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

Network graph analysis of gene-gene interactions in genome-wide association study data.

Science.gov (United States)

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

2012-12-01

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

Does parental expressed emotion moderate genetic effects in ADHD? An exploration using a genome wide association scan

NARCIS (Netherlands)

Sonuga-Barke, E.; Lasky-Su, J.; Neale, B.; Oades, R.D.; Chen, W.; Franke, B.; Buitelaar, J.K.; Banaschewski, T.; Ebstein, R.; Gill, M.; Anney, R.J.; Miranda, A.; Mulas, F.; Roeyers, H.; Rothenberger, A.; Sergeant, J.A.; Steinhausen, H.C.; Thompson, M.; Asherson, P.; Faraone, S.V.

2008-01-01

Studies of gene x environment (G x E) interaction in ADHD have previously focused on known risk genes for ADHD and environmentally mediated biological risk. Here we use G x E analysis in the context of a genome-wide association scan to identify novel genes whose effects on ADHD symptoms and comorbid

Does parental expressed emotion moderate genetic effects in ADHD? An exploration using a genome wide association scan.

NARCIS (Netherlands)

Sonuga-Barke, E.J.S.; Lasky-Su, J.; Neale, B.; Oades, R.D.; Chen, W.; Franke, B.; Buitelaar, J.K.; Banaschewski, T.; Ebstein, R.P.; Gill, M.; Anney, R.; Miranda, A.; Mulas, F.; Roeyers, H.; Rothenberger, A.; Sergeant, J.A.; Steinhausen, H.C.; Thompson, M.; Asherson, P.; Faraone, S.V.

2008-01-01

Studies of gene x environment (G x E) interaction in ADHD have previously focused on known risk genes for ADHD and environmentally mediated biological risk. Here we use G x E analysis in the context of a genome-wide association scan to identify novel genes whose effects on ADHD symptoms and comorbid

BPhyOG: An interactive server for genome-wide inference of bacterial phylogenies based on overlapping genes

Directory of Open Access Journals (Sweden)

Lin Kui

2007-07-01

Full Text Available Abstract Background Overlapping genes (OGs in bacterial genomes are pairs of adjacent genes of which the coding sequences overlap partly or entirely. With the rapid accumulation of sequence data, many OGs in bacterial genomes have now been identified. Indeed, these might prove a consistent feature across all microbial genomes. Our previous work suggests that OGs can be considered as robust markers at the whole genome level for the construction of phylogenies. An online, interactive web server for inferring phylogenies is needed for biologists to analyze phylogenetic relationships among a set of bacterial genomes of interest. Description BPhyOG is an online interactive server for reconstructing the phylogenies of completely sequenced bacterial genomes on the basis of their shared overlapping genes. It provides two tree-reconstruction methods: Neighbor Joining (NJ and Unweighted Pair-Group Method using Arithmetic averages (UPGMA. Users can apply the desired method to generate phylogenetic trees, which are based on an evolutionary distance matrix for the selected genomes. The distance between two genomes is defined by the normalized number of their shared OG pairs. BPhyOG also allows users to browse the OGs that were used to infer the phylogenetic relationships. It provides detailed annotation for each OG pair and the features of the component genes through hyperlinks. Users can also retrieve each of the homologous OG pairs that have been determined among 177 genomes. It is a useful tool for analyzing the tree of life and overlapping genes from a genomic standpoint. Conclusion BPhyOG is a useful interactive web server for genome-wide inference of any potential evolutionary relationship among the genomes selected by users. It currently includes 177 completely sequenced bacterial genomes containing 79,855 OG pairs, the annotation and homologous OG pairs of which are integrated comprehensively. The reliability of phylogenies complemented by

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

Directory of Open Access Journals (Sweden)

Wenchao Zhang

2016-05-01

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

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

Science.gov (United States)

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

2016-05-01

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

Investigation of Maternal Genotype Effects in Autism by Genome-Wide Association

Science.gov (United States)

Yuan, Han; Dougherty, Joseph D.

2014-01-01

Lay Abstract Autism spectrum disorders (ASDs) are pervasive developmental disorders which have both a genetic and environmental component. One source of the environmental component is the in utero (prenatal) environment. The maternal genome can potentially contribute to the risk of autism in children by altering this prenatal environment. In this study, the possibility of maternal genotype effects was explored by looking for common variants (single nucleotide polymorphisms, or SNPs) in the maternal genome associated with increased risk of autism in children. We performed a case/control genome-wide association study (GWAS) using mothers of probands as cases and either fathers of probands or normal females as controls, using two collections of families with autism. We did not identify any SNP that reached significance and thus a common variant of large effect is unlikely. However, there was evidence for the possibility of a large number of alleles each carrying a small effect. This suggested that if there is a contribution to autism risk through common-variant maternal genetic effects, it may be the result of multiple loci of small effects. We did not investigate rare variants in this study. Scientific Abstract Like most psychiatric disorders, autism spectrum disorders have both a genetic and an environmental component. While previous studies have clearly demonstrated the contribution of in utero (prenatal) environment on autism risk, most of them focused on transient environmental factors. Based on a recent sibling study, we hypothesized that environmental factors could also come from the maternal genome, which would result in persistent effects across siblings. In this study, the possibility of maternal genotype effects was examined by looking for common variants (single nucleotide polymorphisms, or SNPs) in the maternal genome associated with increased risk of autism in children. A case/control genome-wide association study (GWAS) was performed using mothers of

A Genome-Wide Screen for Interactions Reveals a New Locus on 4p15 Modifying the Effect of Waist-to-Hip Ratio on Total Cholesterol

NARCIS (Netherlands)

Surakka, I.; Isaacs, A.; Karssen, L.C.; Laurila, P.P.P.; Middelberg, R.P.S.; Tikkanen, E.; Ried, J.S.; Lamina, C.; Mangino, M.; Igl, W.; Hottenga, J.J.; Lagou, V.; van der Harst, P.; Mateo Leach, I.; Esko, T.; Kutalik, Z.; Wainwright, N.W.; Struchalin, M.V.; Sarin, A.P.; Kangas, A.J.; Viikari, J.S.; Perola, M.; Rantanen, T.; Petersen, A.K.; Soininen, P.; Johansson, Å.; Soranzo, N.; Heath, A.C.; Papamarkou, T.; Prokopenko, I.; Tönjes, A.; Kronenberg, F.; Döring, A.; Rivadeneira, F.; Montgomery, GW; Whitfield, J.B.; Kähönen, M.; Lehtimäki, T.; Freimer, N.B.; Willemsen, G.; de Geus, E.J.C.; Palotie, A.; Sandhu, M.S.; Waterworth, D.; Metspalu, A.; Stumvoll, M.; Uitterlinden, A.G.; Navis, G.; Wijmenga, C.; Wolffenbuttel, B.H.R.; Taskinen, M.R.; Ala-Korpela, M.; Kaprio, J.; Kyvik, K.O.; Boomsma, D.I.; Pedersen, N.L.; Gyllensten, U.; Wilson, J.F.; Rudan, I.; Campbell, H.; Pramstaller, P.P.; Spector, T.D.; Witteman, J.C.M.; Eriksson, J.G.; Salomaa, V.; Oostra, B.A.; Raitakari, O.T.; Wichmann, H.E.; Gieger, C.; Järvelin, M.J.; Martin, N.G.; Hofman, A.; McCarthy, M.I.; Peltonen, L.; van Duijn, C.M.; Aulchenko, Y.S.; Ripatti, S.

2011-01-01

Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ~25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants

A genome-wide screen for interactions reveals a new locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol

NARCIS (Netherlands)

I. Surakka (Ida); A.J. Isaacs (Aaron); L.C. Karssen (Lennart); P.-P.P. Laurila; R.P.S. Middelberg (Rita); E. Tikkanen (Emmi); J.S. Ried (Janina); C. Lamina (Claudia); M. Mangino (Massimo); W. Igl (Wilmar); J.J. Hottenga (Jouke Jan); V. Lagou (Vasiliki); P. van der Harst (Pim); I.M. Leach (Irene Mateo); T. Esko (Tõnu); Z. Kutalik (Zoltán); N.W. Wainwright (Nicholas); M.V. Struchalin (Maksim); A.-P. Sarin; A.J. Kangas (Antti); J. Viikari (Jorma); M. Perola (Markus); T. Rantanen (Taina); A.K. Petersen; P. Soininen (Pasi); A. Johansson (Åsa); N. Soranzo (Nicole); A.C. Heath (Andrew); T. Papamarkou (Theodore); I. Prokopenko (Inga); A. Tönjes (Anke); F. Kronenberg (Florian); A. Döring (Angela); F. Rivadeneira Ramirez (Fernando); G.W. Montgomery (Grant); J.B. Whitfield (John); M. Kähönen (Mika); T. Lehtimäki (Terho); N.B. Freimer (Nelson); G.A.H.M. Willemsen (Gonneke); E.J.C. de Geus (Eco); A. Palotie (Aarno); M.S. Sandhu (Manj); D. Waterworth (Dawn); A. Metspalu (Andres); M. Stumvoll (Michael); A.G. Uitterlinden (André); A. Jula (Antti); G. Navis (Gerjan); C. Wijmenga (Cisca); B.H.R. Wolffenbuttel (Bruce); M.-R. Taskinen; M. Ala-Korpela (Mika); J. Kaprio (Jaakko); K.O. Kyvik (Kirsten Ohm); D.I. Boomsma (Dorret); N.L. Pedersen (Nancy); U. Gyllensten (Ulf); J.F. Wilson (James); I. Rudan (Igor); H. Campbell (Harry); P.P. Pramstaller (Peter Paul); T.D. Spector (Timothy); J.C.M. Witteman (Jacqueline); J.G. Eriksson (Johan); V. Salomaa (Veikko); B.A. Oostra (Ben); O. Raitakari (Olli); H.E. Wichmann (Heinz Erich); C. Gieger (Christian); M.R. Järvelin; N.G. Martin (Nicholas); A. Hofman (Albert); M.I. McCarthy (Mark); Y.S. Aulchenko (Yurii); L. Peltonen (Leena Johanna); P. Tikka-Kleemola (Päivi); S. Ripatti (Samuli)

2011-01-01

textabstractRecent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ~25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for

Genome-wide pharmacogenomic study of citalopram-induced side effects in STAR*D.

Science.gov (United States)

Adkins, D E; Clark, S L; Åberg, K; Hettema, J M; Bukszár, J; McClay, J L; Souza, R P; van den Oord, E J C G

2012-07-03

Affecting about 1 in 12 Americans annually, depression is a leading cause of the global disease burden. While a range of effective antidepressants are now available, failure and relapse rates remain substantial, with intolerable side effect burden the most commonly cited reason for discontinuation. Thus, understanding individual differences in susceptibility to antidepressant therapy side effects will be essential to optimize depression treatment. Here we perform genome-wide association studies (GWAS) to identify genetic variation influencing susceptibility to citalopram-induced side effects. The analysis sample consisted of 1762 depression patients, successfully genotyped for 421K single-nucleotide polymorphisms (SNPs), from the Sequenced Treatment Alternatives to Relieve Depression (STAR(*)D) study. Outcomes included five indicators of citalopram side effects: general side effect burden, overall tolerability, sexual side effects, dizziness and vision/hearing side effects. Two SNPs met our genome-wide significance criterion (qeffects of citalopram on vision/hearing side effects (P=3.27 × 10(-8), q=0.026). The second genome-wide significant finding, representing a haplotype spanning ∼30 kb and eight genotyped SNPs in a gene desert on chromosome 13, was associated with general side effect burden (P=3.22 × 10(-7), q=0.096). Suggestive findings were also found for SNPs at LAMA1, AOX2P, EGFLAM, FHIT and RTP2. Although our findings require replication and functional validation, this study demonstrates the potential of GWAS to discover genes and pathways that potentially mediate adverse effects of antidepressant medications.

A Genome-Wide Screen for Interactions Reveals a New Locus on 4p15 Modifying the Effect of Waist-to-Hip Ratio on Total Cholesterol

NARCIS (Netherlands)

Surakka, Ida; Isaacs, Aaron; Karssen, Lennart C.; Laurila, Pirkka-Pekka P.; Middelberg, Rita P. S.; Tikkanen, Emmi; Ried, Janina S.; Lamina, Claudia; Mangino, Massimo; Igl, Wilmar; Hottenga, Jouke-Jan; Lagou, Vasiliki; van der Harst, Pim; Mateo Leach, Irene; Esko, Tonu; Kutalik, Zoltan; Wainwright, Nicholas W.; Struchalin, Maksim V.; Sarin, Antti-Pekka; Kangas, Antti J.; Viikari, Jorma S.; Perola, Markus; Rantanen, Taina; Petersen, Ann-Kristin; Soininen, Pasi; Johansson, Asa; Soranzo, Nicole; Heath, Andrew C.; Papamarkou, Theodore; Prokopenko, Inga; Toenjes, Anke; Kronenberg, Florian; Doering, Angela; Rivadeneira, Fernando; Montgomery, Grant W.; Whitfield, John B.; Kahonen, Mika; Lehtimaki, Terho; Freimer, Nelson B.; Willemsen, Gonneke; de Geus, Eco J. C.; Palotie, Aarno; Sandhu, Manj S.; Waterworth, Dawn M.; Metspalu, Andres; Stumvoll, Michael; Uitterlinden, Andre G.; Navis, Gerjan; Wijmenga, Cisca; Wolffenbuttel, Bruce H. R.

2011-01-01

Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain similar to 25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for

DMS-Seq for In Vivo Genome-wide Mapping of Protein-DNA Interactions and Nucleosome Centers.

Science.gov (United States)

Umeyama, Taichi; Ito, Takashi

2017-10-03

Protein-DNA interactions provide the basis for chromatin structure and gene regulation. Comprehensive identification of protein-occupied sites is thus vital to an in-depth understanding of genome function. Dimethyl sulfate (DMS) is a chemical probe that has long been used to detect footprints of DNA-bound proteins in vitro and in vivo. Here, we describe a genomic footprinting method, dimethyl sulfate sequencing (DMS-seq), which exploits the cell-permeable nature of DMS to obviate the need for nuclear isolation. This feature makes DMS-seq simple in practice and removes the potential risk of protein re-localization during nuclear isolation. DMS-seq successfully detects transcription factors bound to cis-regulatory elements and non-canonical chromatin particles in nucleosome-free regions. Furthermore, an unexpected preference of DMS confers on DMS-seq a unique potential to directly detect nucleosome centers without using genetic manipulation. We expect that DMS-seq will serve as a characteristic method for genome-wide interrogation of in vivo protein-DNA interactions. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

4C-ker: A Method to Reproducibly Identify Genome-Wide Interactions Captured by 4C-Seq Experiments.

Science.gov (United States)

Raviram, Ramya; Rocha, Pedro P; Müller, Christian L; Miraldi, Emily R; Badri, Sana; Fu, Yi; Swanzey, Emily; Proudhon, Charlotte; Snetkova, Valentina; Bonneau, Richard; Skok, Jane A

2016-03-01

4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or "bait") that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes.

4C-ker: A Method to Reproducibly Identify Genome-Wide Interactions Captured by 4C-Seq Experiments.

Directory of Open Access Journals (Sweden)

Ramya Raviram

2016-03-01

Full Text Available 4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or "bait" that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes.

Evidence for gene-environment interaction in a genome wide study of nonsyndromic cleft palate

DEFF Research Database (Denmark)

Beaty, Terri H; Ruczinski, Ingo; Murray, Jeffrey C

2011-01-01

Nonsyndromic cleft palate (CP) is a common birth defect with a complex and heterogeneous etiology involving both genetic and environmental risk factors. We conducted a genome-wide association study (GWAS) using 550 case-parent trios, ascertained through a CP case collected in an international...... consortium. Family-based association tests of single nucleotide polymorphisms (SNP) and three common maternal exposures (maternal smoking, alcohol consumption, and multivitamin supplementation) were used in a combined 2 df test for gene (G) and gene-environment (G × E) interaction simultaneously, plus...... multiple SNPs associated with higher risk of CP in the presence of maternal smoking. Additional evidence of reduced risk due to G × E interaction in the presence of multivitamin supplementation was observed for SNPs in BAALC on chr. 8. These results emphasize the need to consider G × E interaction when...

GBOOST: a GPU-based tool for detecting gene-gene interactions in genome-wide case control studies.

Science.gov (United States)

Yung, Ling Sing; Yang, Can; Wan, Xiang; Yu, Weichuan

2011-05-01

Collecting millions of genetic variations is feasible with the advanced genotyping technology. With a huge amount of genetic variations data in hand, developing efficient algorithms to carry out the gene-gene interaction analysis in a timely manner has become one of the key problems in genome-wide association studies (GWAS). Boolean operation-based screening and testing (BOOST), a recent work in GWAS, completes gene-gene interaction analysis in 2.5 days on a desktop computer. Compared with central processing units (CPUs), graphic processing units (GPUs) are highly parallel hardware and provide massive computing resources. We are, therefore, motivated to use GPUs to further speed up the analysis of gene-gene interactions. We implement the BOOST method based on a GPU framework and name it GBOOST. GBOOST achieves a 40-fold speedup compared with BOOST. It completes the analysis of Wellcome Trust Case Control Consortium Type 2 Diabetes (WTCCC T2D) genome data within 1.34 h on a desktop computer equipped with Nvidia GeForce GTX 285 display card. GBOOST code is available at http://bioinformatics.ust.hk/BOOST.html#GBOOST.

bNEAT: a Bayesian network method for detecting epistatic interactions in genome-wide association studies

Directory of Open Access Journals (Sweden)

Chen Xue-wen

2011-07-01

Full Text Available Abstract Background Detecting epistatic interactions plays a significant role in improving pathogenesis, prevention, diagnosis and treatment of complex human diseases. A recent study in automatic detection of epistatic interactions shows that Markov Blanket-based methods are capable of finding genetic variants strongly associated with common diseases and reducing false positives when the number of instances is large. Unfortunately, a typical dataset from genome-wide association studies consists of very limited number of examples, where current methods including Markov Blanket-based method may perform poorly. Results To address small sample problems, we propose a Bayesian network-based approach (bNEAT to detect epistatic interactions. The proposed method also employs a Branch-and-Bound technique for learning. We apply the proposed method to simulated datasets based on four disease models and a real dataset. Experimental results show that our method outperforms Markov Blanket-based methods and other commonly-used methods, especially when the number of samples is small. Conclusions Our results show bNEAT can obtain a strong power regardless of the number of samples and is especially suitable for detecting epistatic interactions with slight or no marginal effects. The merits of the proposed approach lie in two aspects: a suitable score for Bayesian network structure learning that can reflect higher-order epistatic interactions and a heuristic Bayesian network structure learning method.

Genome-Wide Host-Pathogen Interaction Unveiled by Transcriptomic Response of Diamondback Moth to Fungal Infection.

Directory of Open Access Journals (Sweden)

Zhen-Jian Chu

Full Text Available Genome-wide insight into insect pest response to the infection of Beauveria bassiana (fungal insect pathogen is critical for genetic improvement of fungal insecticides but has been poorly explored. We constructed three pairs of transcriptomes of Plutella xylostella larvae at 24, 36 and 48 hours post treatment of infection (hptI and of control (hptC for insight into the host-pathogen interaction at genomic level. There were 2143, 3200 and 2967 host genes differentially expressed at 24, 36 and 48 hptI/hptC respectively. These infection-responsive genes (~15% of the host genome were enriched in various immune processes, such as complement and coagulation cascades, protein digestion and absorption, and drug metabolism-cytochrome P450. Fungal penetration into cuticle and host defense reaction began at 24 hptI, followed by most intensive host immune response at 36 hptI and attenuated immunity at 48 hptI. Contrastingly, 44% of fungal genes were differentially expressed in the infection course and enriched in several biological processes, such as antioxidant activity, peroxidase activity and proteolysis. There were 1636 fungal genes co-expressed during 24-48 hptI, including 116 encoding putative secretion proteins. Our results provide novel insights into the insect-pathogen interaction and help to probe molecular mechanisms involved in the fungal infection to the global pest.

GWAMA: software for genome-wide association meta-analysis

Directory of Open Access Journals (Sweden)

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.

Genome-Wide Detection and Analysis of Multifunctional Genes

Science.gov (United States)

Pritykin, Yuri; Ghersi, Dario; Singh, Mona

2015-01-01

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

Does parental expressed emotion moderate genetic effects in ADHD? An exploration using a genome wide association scan

OpenAIRE

Sonuga-Barke, E.; Lasky-Su, J.; Neale, B.; Oades, R.D.; Chen, W.; Franke, B.; Buitelaar, J.K.; Banaschewski, T.; Ebstein, R.; Gill, M.; Anney, R.J.; Miranda, A.; Mulas, F.; Roeyers, H.; Rothenberger, A.

2008-01-01

Studies of gene x environment (G x E) interaction in ADHD have previously focused on known risk genes for ADHD and environmentally mediated biological risk. Here we use G x E analysis in the context of a genome-wide association scan to identify novel genes whose effects on ADHD symptoms and comorbid conduct disorder are moderated by high maternal expressed emotion (EE). SNPs (600,000) were genotyped in 958 ADHD proband-parent trios. After applying data cleaning procedures we examined 429,981 ...

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

DEFF Research Database (Denmark)

Vrieze, S. I.; Iacono, W. G.; McGue, M.

2012-01-01

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...

Transcription facilitated genome-wide recruitment of topoisomerase I and DNA gyrase.

Science.gov (United States)

Ahmed, Wareed; Sala, Claudia; Hegde, Shubhada R; Jha, Rajiv Kumar; Cole, Stewart T; Nagaraja, Valakunja

2017-05-01

Movement of the transcription machinery along a template alters DNA topology resulting in the accumulation of supercoils in DNA. The positive supercoils generated ahead of transcribing RNA polymerase (RNAP) and the negative supercoils accumulating behind impose severe topological constraints impeding transcription process. Previous studies have implied the role of topoisomerases in the removal of torsional stress and the maintenance of template topology but the in vivo interaction of functionally distinct topoisomerases with heterogeneous chromosomal territories is not deciphered. Moreover, how the transcription-induced supercoils influence the genome-wide recruitment of DNA topoisomerases remains to be explored in bacteria. Using ChIP-Seq, we show the genome-wide occupancy profile of both topoisomerase I and DNA gyrase in conjunction with RNAP in Mycobacterium tuberculosis taking advantage of minimal topoisomerase representation in the organism. The study unveils the first in vivo genome-wide interaction of both the topoisomerases with the genomic regions and establishes that transcription-induced supercoils govern their recruitment at genomic sites. Distribution profiles revealed co-localization of RNAP and the two topoisomerases on the active transcriptional units (TUs). At a given locus, topoisomerase I and DNA gyrase were localized behind and ahead of RNAP, respectively, correlating with the twin-supercoiled domains generated. The recruitment of topoisomerases was higher at the genomic loci with higher transcriptional activity and/or at regions under high torsional stress compared to silent genomic loci. Importantly, the occupancy of DNA gyrase, sole type II topoisomerase in Mtb, near the Ter domain of the Mtb chromosome validates its function as a decatenase.

Prospecting sugarcane resistance to Sugarcane yellow leaf virus by genome-wide association.

Science.gov (United States)

Debibakas, S; Rocher, S; Garsmeur, O; Toubi, L; Roques, D; D'Hont, A; Hoarau, J-Y; Daugrois, J H

2014-08-01

Using GWAS approaches, we detected independent resistant markers in sugarcane towards a vectored virus disease. Based on comparative genomics, several candidate genes potentially involved in virus/aphid/plant interactions were pinpointed. Yellow leaf of sugarcane is an emerging viral disease whose causal agent is a Polerovirus, the Sugarcane yellow leaf virus (SCYLV) transmitted by aphids. To identify quantitative trait loci controlling resistance to yellow leaf which are of direct relevance for breeding, we undertook a genome-wide association study (GWAS) on a sugarcane cultivar panel (n = 189) representative of current breeding germplasm. This panel was fingerprinted with 3,949 polymorphic markers (DArT and AFLP). The panel was phenotyped for SCYLV infection in leaves and stalks in two trials for two crop cycles, under natural disease pressure prevalent in Guadeloupe. Mixed linear models including co-factors representing population structure fixed effects and pairwise kinship random effects provided an efficient control of the risk of inflated type-I error at a genome-wide level. Six independent markers were significantly detected in association with SCYLV resistance phenotype. These markers explained individually between 9 and 14 % of the disease variation of the cultivar panel. Their frequency in the panel was relatively low (8-20 %). Among them, two markers were detected repeatedly across the GWAS exercises based on the different disease resistance parameters. These two markers could be blasted on Sorghum bicolor genome and candidate genes potentially involved in plant-aphid or plant-virus interactions were localized in the vicinity of sorghum homologs of sugarcane markers. Our results illustrate the potential of GWAS approaches to prospect among sugarcane germplasm for accessions likely bearing resistance alleles of significant effect useful in breeding programs.

The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

Directory of Open Access Journals (Sweden)

Thomas W Winkler

2015-10-01

Full Text Available Genome-wide association studies (GWAS have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI, a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE, sex-specific effects (G x SEX or age-specific effects that differed between men and women (G x AGE x SEX. For BMI, we identified 15 loci (11 previously established for main effects, four novel that showed significant (FDR<5% age-specific effects, of which 11 had larger effects in younger (<50y than in older adults (≥50y. No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.

Genome-wide analysis of protein-protein interactions and involvement of viral proteins in SARS-CoV replication.

Directory of Open Access Journals (Sweden)

Ji'an Pan

Full Text Available Analyses of viral protein-protein interactions are an important step to understand viral protein functions and their underlying molecular mechanisms. In this study, we adopted a mammalian two-hybrid system to screen the genome-wide intraviral protein-protein interactions of SARS coronavirus (SARS-CoV and therefrom revealed a number of novel interactions which could be partly confirmed by in vitro biochemical assays. Three pairs of the interactions identified were detected in both directions: non-structural protein (nsp 10 and nsp14, nsp10 and nsp16, and nsp7 and nsp8. The interactions between the multifunctional nsp10 and nsp14 or nsp16, which are the unique proteins found in the members of Nidovirales with large RNA genomes including coronaviruses and toroviruses, may have important implication for the mechanisms of replication/transcription complex assembly and functions of these viruses. Using a SARS-CoV replicon expressing a luciferase reporter under the control of a transcription regulating sequence, it has been shown that several viral proteins (N, X and SUD domains of nsp3, and nsp12 provided in trans stimulated the replicon reporter activity, indicating that these proteins may regulate coronavirus replication and transcription. Collectively, our findings provide a basis and platform for further characterization of the functions and mechanisms of coronavirus proteins.

A Pooled Genome-Wide Association Study of Asperger Syndrome.

Directory of Open Access Journals (Sweden)

Varun Warrier

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

Detection of gene-environment interaction in pedigree data using genome-wide genotypes

NARCIS (Netherlands)

Nivard, Michel G.; Middeldorp, Christel M.; Lubke, Gitta; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Boomsma, Dorret I.; Dolan, Conor V.

2016-01-01

Heritability may be estimated using phenotypic data collected in relatives or in distantly related individuals using genome-wide single nucleotide polymorphism (SNP) data. We combined these approaches by re-parameterizing the model proposed by Zaitlen et al and extended this model to include

HIV Genome-Wide Protein Associations: a Review of 30 Years of Research

Science.gov (United States)

2016-01-01

SUMMARY The HIV genome encodes a small number of viral proteins (i.e., 16), invariably establishing cooperative associations among HIV proteins and between HIV and host proteins, to invade host cells and hijack their internal machineries. As a known example, the HIV envelope glycoprotein GP120 is closely associated with GP41 for viral entry. From a genome-wide perspective, a hypothesis can be worked out to determine whether 16 HIV proteins could develop 120 possible pairwise associations either by physical interactions or by functional associations mediated via HIV or host molecules. Here, we present the first systematic review of experimental evidence on HIV genome-wide protein associations using a large body of publications accumulated over the past 3 decades. Of 120 possible pairwise associations between 16 HIV proteins, at least 34 physical interactions and 17 functional associations have been identified. To achieve efficient viral replication and infection, HIV protein associations play essential roles (e.g., cleavage, inhibition, and activation) during the HIV life cycle. In either a dispensable or an indispensable manner, each HIV protein collaborates with another viral protein to accomplish specific activities that precisely take place at the proper stages of the HIV life cycle. In addition, HIV genome-wide protein associations have an impact on anti-HIV inhibitors due to the extensive cross talk between drug-inhibited proteins and other HIV proteins. Overall, this study presents for the first time a comprehensive overview of HIV genome-wide protein associations, highlighting meticulous collaborations between all viral proteins during the HIV life cycle. PMID:27357278

Spatial organization of the budding yeast genome in the cell nucleus and identification of specific chromatin interactions from multi-chromosome constrained chromatin model.

Science.gov (United States)

Gürsoy, Gamze; Xu, Yun; Liang, Jie

2017-07-01

Nuclear landmarks and biochemical factors play important roles in the organization of the yeast genome. The interaction pattern of budding yeast as measured from genome-wide 3C studies are largely recapitulated by model polymer genomes subject to landmark constraints. However, the origin of inter-chromosomal interactions, specific roles of individual landmarks, and the roles of biochemical factors in yeast genome organization remain unclear. Here we describe a multi-chromosome constrained self-avoiding chromatin model (mC-SAC) to gain understanding of the budding yeast genome organization. With significantly improved sampling of genome structures, both intra- and inter-chromosomal interaction patterns from genome-wide 3C studies are accurately captured in our model at higher resolution than previous studies. We show that nuclear confinement is a key determinant of the intra-chromosomal interactions, and centromere tethering is responsible for the inter-chromosomal interactions. In addition, important genomic elements such as fragile sites and tRNA genes are found to be clustered spatially, largely due to centromere tethering. We uncovered previously unknown interactions that were not captured by genome-wide 3C studies, which are found to be enriched with tRNA genes, RNAPIII and TFIIS binding. Moreover, we identified specific high-frequency genome-wide 3C interactions that are unaccounted for by polymer effects under landmark constraints. These interactions are enriched with important genes and likely play biological roles.

Genome-wide occupancy profile of mediator and the Srb8-11 module reveals interactions with coding regions

DEFF Research Database (Denmark)

Zhu, Xuefeng; Wirén, Marianna; Sinha, Indranil

2006-01-01

Mediator exists in a free form containing the Med12, Med13, CDK8, and CycC subunits (the Srb8-11 module) and a smaller form, which lacks these four subunits and associates with RNA polymerase II (Pol II), forming a holoenzyme. We use chromatin immunoprecipitation (ChIP) and DNA microarrays...... to investigate genome-wide localization of Mediator and the Srb8-11 module in fission yeast. Mediator and the Srb8-11 module display similar binding patterns, and interactions with promoters and upstream activating sequences correlate with increased transcription activity. Unexpectedly, Mediator also interacts...... with the downstream coding region of many genes. These interactions display a negative bias for positions closer to the 5' ends of open reading frames (ORFs) and appear functionally important, because downregulation of transcription in a temperature-sensitive med17 mutant strain correlates with increased Mediator...

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

Science.gov (United States)

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

Off-target effects of psychoactive drugs revealed by genome-wide assays in yeast.

Directory of Open Access Journals (Sweden)

Elke Ericson

2008-08-01

Full Text Available To better understand off-target effects of widely prescribed psychoactive drugs, we performed a comprehensive series of chemogenomic screens using the budding yeast Saccharomyces cerevisiae as a model system. Because the known human targets of these drugs do not exist in yeast, we could employ the yeast gene deletion collections and parallel fitness profiling to explore potential off-target effects in a genome-wide manner. Among 214 tested, documented psychoactive drugs, we identified 81 compounds that inhibited wild-type yeast growth and were thus selected for genome-wide fitness profiling. Many of these drugs had a propensity to affect multiple cellular functions. The sensitivity profiles of half of the analyzed drugs were enriched for core cellular processes such as secretion, protein folding, RNA processing, and chromatin structure. Interestingly, fluoxetine (Prozac interfered with establishment of cell polarity, cyproheptadine (Periactin targeted essential genes with chromatin-remodeling roles, while paroxetine (Paxil interfered with essential RNA metabolism genes, suggesting potential secondary drug targets. We also found that the more recently developed atypical antipsychotic clozapine (Clozaril had no fewer off-target effects in yeast than the typical antipsychotics haloperidol (Haldol and pimozide (Orap. Our results suggest that model organism pharmacogenetic studies provide a rational foundation for understanding the off-target effects of clinically important psychoactive agents and suggest a rational means both for devising compound derivatives with fewer side effects and for tailoring drug treatment to individual patient genotypes.

Assessment of gene-by-sex interaction effect on bone mineral density

DEFF Research Database (Denmark)

Liu, Ching-Ti; Estrada, Karol; Yerges-Armstrong, Laura M

2012-01-01

Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and ......Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome...

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

Directory of Open Access Journals (Sweden)

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.

Effects of in ovo electroporation on endogenous gene expression: genome-wide analysis

Directory of Open Access Journals (Sweden)

Chambers David

2011-04-01

Full Text Available Abstract Background In ovo electroporation is a widely used technique to study gene function in developmental biology. Despite the widespread acceptance of this technique, no genome-wide analysis of the effects of in ovo electroporation, principally the current applied across the tissue and exogenous vector DNA introduced, on endogenous gene expression has been undertaken. Here, the effects of electric current and expression of a GFP-containing construct, via electroporation into the midbrain of Hamburger-Hamilton stage 10 chicken embryos, are analysed by microarray. Results Both current alone and in combination with exogenous DNA expression have a small but reproducible effect on endogenous gene expression, changing the expression of the genes represented on the array by less than 0.1% (current and less than 0.5% (current + DNA, respectively. The subset of genes regulated by electric current and exogenous DNA span a disparate set of cellular functions. However, no genes involved in the regional identity were affected. In sharp contrast to this, electroporation of a known transcription factor, Dmrt5, caused a much greater change in gene expression. Conclusions These findings represent the first systematic genome-wide analysis of the effects of in ovo electroporation on gene expression during embryonic development. The analysis reveals that this process has minimal impact on the genetic basis of cell fate specification. Thus, the study demonstrates the validity of the in ovo electroporation technique to study gene function and expression during development. Furthermore, the data presented here can be used as a resource to refine the set of transcriptional responders in future in ovo electroporation studies of specific gene function.

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

Directory of Open Access Journals (Sweden)

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.

Using a higher criticism statistic to detect modest effects in a genome-wide study of rheumatoid arthritis

Science.gov (United States)

2009-01-01

In high-dimensional studies such as genome-wide association studies, the correction for multiple testing in order to control total type I error results in decreased power to detect modest effects. We present a new analytical approach based on the higher criticism statistic that allows identification of the presence of modest effects. We apply our method to the genome-wide study of rheumatoid arthritis provided in the Genetic Analysis Workshop 16 Problem 1 data set. There is evidence for unknown bias in this study that could be explained by the presence of undetected modest effects. We compared the asymptotic and empirical thresholds for the higher criticism statistic. Using the asymptotic threshold we detected the presence of modest effects genome-wide. We also detected modest effects using 90th percentile of the empirical null distribution as a threshold; however, there is no such evidence when the 95th and 99th percentiles were used. While the higher criticism method suggests that there is some evidence for modest effects, interpreting individual single-nucleotide polymorphisms with significant higher criticism statistics is of undermined value. The goal of higher criticism is to alert the researcher that genetic effects remain to be discovered and to promote the use of more targeted and powerful studies to detect the remaining effects. PMID:20018032

Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

Directory of Open Access Journals (Sweden)

Ueki Masao

2012-05-01

Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.

Protein Interaction-Based Genome-Wide Analysis of Incident Coronary Heart Disease

DEFF Research Database (Denmark)

Jensen, Majken Karoline; Pers, Tune Hannes; Dworzynski, Piotr

2011-01-01

in genes associated with risk of coronary heart disease (CHD). Methods and Results-Genome-wide association analyses of approximately approximate to 700 000 single-nucleotide polymorphisms in 899 incident CHD cases and 1823 age-and sex-matched controls within the Nurses' Health and the Health Professionals...... complex. Conclusions-The integration of a GWA study with PPI data successfully identifies a set of candidate susceptibility genes for incident CHD that would have been missed in single-marker GWA analysis. (Circ Cardiovasc Genet. 2011; 4:549-556.)...

iLOCi: a SNP interaction prioritization technique for detecting epistasis in genome-wide association studies

Directory of Open Access Journals (Sweden)

Piriyapongsa Jittima

2012-12-01

Full Text Available Abstract Background Genome-wide association studies (GWAS do not provide a full account of the heritability of genetic diseases since gene-gene interactions, also known as epistasis are not considered in single locus GWAS. To address this problem, a considerable number of methods have been developed for identifying disease-associated gene-gene interactions. However, these methods typically fail to identify interacting markers explaining more of the disease heritability over single locus GWAS, since many of the interactions significant for disease are obscured by uninformative marker interactions e.g., linkage disequilibrium (LD. Results In this study, we present a novel SNP interaction prioritization algorithm, named iLOCi (Interacting Loci. This algorithm accounts for marker dependencies separately in case and control groups. Disease-associated interactions are then prioritized according to a novel ranking score calculated from the difference in marker dependencies for every possible pair between case and control groups. The analysis of a typical GWAS dataset can be completed in less than a day on a standard workstation with parallel processing capability. The proposed framework was validated using simulated data and applied to real GWAS datasets using the Wellcome Trust Case Control Consortium (WTCCC data. The results from simulated data showed the ability of iLOCi to identify various types of gene-gene interactions, especially for high-order interaction. From the WTCCC data, we found that among the top ranked interacting SNP pairs, several mapped to genes previously known to be associated with disease, and interestingly, other previously unreported genes with biologically related roles. Conclusion iLOCi is a powerful tool for uncovering true disease interacting markers and thus can provide a more complete understanding of the genetic basis underlying complex disease. The program is available for download at http://www4a.biotec.or.th/GI/tools/iloci.

Exploring relationships between host genome and microbiome: new insights from genome-wide association studies.

Directory of Open Access Journals (Sweden)

Muslihudeen Abdul-Razaq Abdul-Aziz

2016-10-01

Full Text Available As our understanding of the human microbiome expands, impacts on health and disease continue to be revealed. Alterations in the microbiome can result in dysbiosis, which has now been linked to subsequent autoimmune and metabolic diseases, highlighting the need to identify factors that shape the microbiome. Research has identified that the composition and functions of the human microbiome can be influenced by diet, age, gender, and environment. More recently, studies have explored how human genetic variation may also influence the microbiome. Here, we review several recent analytical advances in this new research area, including those that use genome-wide association studies to examine host genome-microbiome interactions, while controlling for the influence of other factors. We find that current research is limited by small sample sizes, lack of cohort replication, and insufficient confirmatory mechanistic studies. In addition, we discuss the importance of understanding long-term interactions between the host genome and microbiome, as well as the potential impacts of disrupting this relationship, and explore new research avenues that may provide information about the co-evolutionary history of humans and their microorganisms.

Genome-Wide Gene-Environment Study Identifies Glutamate Receptor Gene GRIN2A as a Parkinson's Disease Modifier Gene via Interaction with Coffee

Science.gov (United States)

Hamza, Taye H.; Chen, Honglei; Hill-Burns, Erin M.; Rhodes, Shannon L.; Montimurro, Jennifer; Kay, Denise M.; Tenesa, Albert; Kusel, Victoria I.; Sheehan, Patricia; Eaaswarkhanth, Muthukrishnan; Yearout, Dora; Samii, Ali; Roberts, John W.; Agarwal, Pinky; Bordelon, Yvette; Park, Yikyung; Wang, Liyong; Gao, Jianjun; Vance, Jeffery M.; Kendler, Kenneth S.; Bacanu, Silviu-Alin; Scott, William K.; Ritz, Beate; Nutt, John; Factor, Stewart A.; Zabetian, Cyrus P.; Payami, Haydeh

2011-01-01

Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P2df = 10−6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10−7) but not in light coffee-drinkers. The a priori Replication hypothesis that “Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers” was confirmed: ORReplication = 0.59, PReplication = 10−3; ORPooled = 0.51, PPooled = 7×10−8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10−3), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10−13). Imputation revealed a block of SNPs that achieved P2dfcoffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify genes that

Genome-wide gene-environment study identifies glutamate receptor gene GRIN2A as a Parkinson's disease modifier gene via interaction with coffee.

Science.gov (United States)

Hamza, Taye H; Chen, Honglei; Hill-Burns, Erin M; Rhodes, Shannon L; Montimurro, Jennifer; Kay, Denise M; Tenesa, Albert; Kusel, Victoria I; Sheehan, Patricia; Eaaswarkhanth, Muthukrishnan; Yearout, Dora; Samii, Ali; Roberts, John W; Agarwal, Pinky; Bordelon, Yvette; Park, Yikyung; Wang, Liyong; Gao, Jianjun; Vance, Jeffery M; Kendler, Kenneth S; Bacanu, Silviu-Alin; Scott, William K; Ritz, Beate; Nutt, John; Factor, Stewart A; Zabetian, Cyrus P; Payami, Haydeh

2011-08-01

Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P(2df) = 10(-6), GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10(-7)) but not in light coffee-drinkers. The a priori Replication hypothesis that "Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers" was confirmed: OR(Replication) = 0.59, P(Replication) = 10(-3); OR(Pooled) = 0.51, P(Pooled) = 7×10(-8). Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10(-3)), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10(-13)). Imputation revealed a block of SNPs that achieved P(2df)coffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify

Vitamin D receptor signaling and its therapeutic implications: Genome-wide and structural view.

Science.gov (United States)

Carlberg, Carsten; Molnár, Ferdinand

2015-05-01

Vitamin D3 is one of the few natural compounds that has, via its metabolite 1α,25-dihydroxyvitamin D3 (1,25(OH)2D3) and the transcription factor vitamin D receptor (VDR), a direct effect on gene regulation. For efficiently applying the therapeutic and disease-preventing potential of 1,25(OH)2D3 and its synthetic analogs, the key steps in vitamin D signaling need to be understood. These are the different types of molecular interactions with the VDR, such as (i) the complex formation of VDR with genomic DNA, (ii) the interaction of VDR with its partner transcription factors, (iii) the binding of 1,25(OH)2D3 or its synthetic analogs within the ligand-binding pocket of the VDR, and (iv) the resulting conformational change on the surface of the VDR leading to a change of the protein-protein interaction profile of the receptor with other proteins. This review will present the latest genome-wide insight into vitamin D signaling, and will discuss its therapeutic implications.

Gaussian covariance graph models accounting for correlated marker effects in genome-wide prediction.

Science.gov (United States)

Martínez, C A; Khare, K; Rahman, S; Elzo, M A

2017-10-01

Several statistical models used in genome-wide prediction assume uncorrelated marker allele substitution effects, but it is known that these effects may be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high-dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated data sets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies, which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multi-allelic loci case is straightforward. © 2017 Blackwell Verlag GmbH.

Adiponectin Concentrations: A Genome-wide Association Study

Science.gov (United States)

Jee, Sun Ha; Sull, Jae Woong; Lee, Jong-Eun; Shin, Chol; Park, Jongkeun; Kimm, Heejin; Cho, Eun-Young; Shin, Eun-Soon; Yun, Ji Eun; Park, Ji Wan; Kim, Sang Yeun; Lee, Sun Ju; Jee, Eun Jung; Baik, Inkyung; Kao, Linda; Yoon, Sungjoo Kim; Jang, Yangsoo; Beaty, Terri H.

2010-01-01

Adiponectin is associated with obesity and insulin resistance. To date, there has been no genome-wide association study (GWAS) of adiponectin levels in Asians. Here we present a GWAS of a cohort of Korean volunteers. A total of 4,001 subjects were genotyped by using a genome-wide marker panel in a two-stage design (979 subjects initially and 3,022 in a second stage). Another 2,304 subjects were used for follow-up replication studies with selected markers. In the discovery phase, the top SNP associated with mean log adiponectin was rs3865188 in CDH13 on chromosome 16 (p = 1.69 × 10−15 in the initial sample, p = 6.58 × 10−39 in the second genome-wide sample, and p = 2.12 × 10−32 in the replication sample). The meta-analysis p value for rs3865188 in all 6,305 individuals was 2.82 × 10−83. The association of rs3865188 with high-molecular-weight adiponectin (p = 7.36 × 10−58) was even stronger in the third sample. A reporter assay that evaluated the effects of a CDH13 promoter SNP in complete linkage disequilibrium with rs3865188 revealed that the major allele increased expression 2.2-fold. This study clearly shows that genetic variants in CDH13 influence adiponectin levels in Korean adults. PMID:20887962

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

Directory of Open Access Journals (Sweden)

Christopher Y Park

2010-11-01

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

Investigation of common, low-frequency and rare genome-wide variation in anorexia nervosa

Science.gov (United States)

Huckins, L M; Hatzikotoulas, K; Southam, L; Thornton, L M; Steinberg, J; Aguilera-McKay, F; Treasure, J; Schmidt, U; Gunasinghe, C; Romero, A; Curtis, C; Rhodes, D; Moens, J; Kalsi, G; Dempster, D; Leung, R; Keohane, A; Burghardt, R; Ehrlich, S; Hebebrand, J; Hinney, A; Ludolph, A; Walton, E; Deloukas, P; Hofman, A; Palotie, A; Palta, P; van Rooij, F J A; Stirrups, K; Adan, R; Boni, C; Cone, R; Dedoussis, G; van Furth, E; Gonidakis, F; Gorwood, P; Hudson, J; Kaprio, J; Kas, M; Keski-Rahonen, A; Kiezebrink, K; Knudsen, G-P; Slof-Op 't Landt, M C T; Maj, M; Monteleone, A M; Monteleone, P; Raevuori, A H; Reichborn-Kjennerud, T; Tozzi, F; Tsitsika, A; van Elburg, A; Adan, R A H; Alfredsson, L; Ando, T; Andreassen, O A; Aschauer, H; Baker, J H; Barrett, J C; Bencko, V; Bergen, A W; Berrettini, W H; Birgegard, A; Boni, C; Boraska Perica, V; Brandt, H; Breen, G; Bulik, C M; Carlberg, L; Cassina, M; Cichon, S; Clementi, M; Cohen-Woods, S; Coleman, J; Cone, R D; Courtet, P; Crawford, S; Crow, S; Crowley, J; Danner, U N; Davis, O S P; de Zwaan, M; Dedoussis, G; Degortes, D; DeSocio, J E; Dick, D M; Dikeos, D; Dina, C; Ding, B; Dmitrzak-Weglarz, M; Docampo, E; Duncan, L; Egberts, K; Ehrlich, S; Escaramís, G; Esko, T; Espeseth, T; Estivill, X; Favaro, A; Fernández-Aranda, F; Fichter, M M; Finan, C; Fischer, K; Floyd, J A B; Foretova, L; Forzan, M; Franklin, C S; Gallinger, S; Gambaro, G; Gaspar, H A; Giegling, I; Gonidakis, F; Gorwood, P; Gratacos, M; Guillaume, S; Guo, Y; Hakonarson, H; Halmi, K A; Hatzikotoulas, K; Hauser, J; Hebebrand, J; Helder, S; Herms, S; Herpertz-Dahlmann, B; Herzog, W; Hilliard, C E; Hinney, A; Hübel, C; Huckins, L M; Hudson, J I; Huemer, J; Inoko, H; Janout, V; Jiménez-Murcia, S; Johnson, C; Julià, A; Juréus, A; Kalsi, G; Kaminska, D; Kaplan, A S; Kaprio, J; Karhunen, L; Karwautz, A; Kas, M J H; Kaye, W; Kennedy, J L; Keski-Rahkonen, A; Kiezebrink, K; Klareskog, L; Klump, K L; Knudsen, G P S; Koeleman, B P C; Koubek, D; La Via, M C; Landén, M; Le Hellard, S; Levitan, R D; Li, D; Lichtenstein, P; Lilenfeld, L; Lissowska, J; Lundervold, A; Magistretti, P; Maj, M; Mannik, K; Marsal, S; Martin, N; Mattingsdal, M; McDevitt, S; McGuffin, P; Merl, E; Metspalu, A; Meulenbelt, I; Micali, N; Mitchell, J; Mitchell, K; Monteleone, P; Monteleone, A M; Mortensen, P; Munn-Chernoff, M A; Navratilova, M; Nilsson, I; Norring, C; Ntalla, I; Ophoff, R A; O'Toole, J K; Palotie, A; Pante, J; Papezova, H; Pinto, D; Rabionet, R; Raevuori, A; Rajewski, A; Ramoz, N; Rayner, N W; Reichborn-Kjennerud, T; Ripatti, S; Roberts, M; Rotondo, A; Rujescu, D; Rybakowski, F; Santonastaso, P; Scherag, A; Scherer, S W; Schmidt, U; Schork, N J; Schosser, A; Slachtova, L; Sladek, R; Slagboom, P E; Slof-Op 't Landt, M C T; Slopien, A; Soranzo, N; Southam, L; Steen, V M; Strengman, E; Strober, M; Sullivan, P F; Szatkiewicz, J P; Szeszenia-Dabrowska, N; Tachmazidou, I; Tenconi, E; Thornton, L M; Tortorella, A; Tozzi, F; Treasure, J; Tsitsika, A; Tziouvas, K; van Elburg, A A; van Furth, E F; Wagner, G; Walton, E; Watson, H; Wichmann, H-E; Widen, E; Woodside, D B; Yanovski, J; Yao, S; Yilmaz, Z; Zeggini, E; Zerwas, S; Zipfel, S; Collier, D A; Sullivan, P F; Breen, G; Bulik, C M; Zeggini, E

2018-01-01

Anorexia nervosa (AN) is a complex neuropsychiatric disorder presenting with dangerously low body weight, and a deep and persistent fear of gaining weight. To date, only one genome-wide significant locus associated with AN has been identified. We performed an exome-chip based genome-wide association studies (GWAS) in 2158 cases from nine populations of European origin and 15 485 ancestrally matched controls. Unlike previous studies, this GWAS also probed association in low-frequency and rare variants. Sixteen independent variants were taken forward for in silico and de novo replication (11 common and 5 rare). No findings reached genome-wide significance. Two notable common variants were identified: rs10791286, an intronic variant in OPCML (P=9.89 × 10−6), and rs7700147, an intergenic variant (P=2.93 × 10−5). No low-frequency variant associations were identified at genome-wide significance, although the study was well-powered to detect low-frequency variants with large effect sizes, suggesting that there may be no AN loci in this genomic search space with large effect sizes. PMID:29155802

The Glyphosate-Based Herbicide Roundup Does not Elevate Genome-Wide Mutagenesis of Escherichia coli.

Science.gov (United States)

Tincher, Clayton; Long, Hongan; Behringer, Megan; Walker, Noah; Lynch, Michael

2017-10-05

Mutations induced by pollutants may promote pathogen evolution, for example by accelerating mutations conferring antibiotic resistance. Generally, evaluating the genome-wide mutagenic effects of long-term sublethal pollutant exposure at single-nucleotide resolution is extremely difficult. To overcome this technical barrier, we use the mutation accumulation/whole-genome sequencing (MA/WGS) method as a mutagenicity test, to quantitatively evaluate genome-wide mutagenesis of Escherichia coli after long-term exposure to a wide gradient of the glyphosate-based herbicide (GBH) Roundup Concentrate Plus. The genome-wide mutation rate decreases as GBH concentration increases, suggesting that even long-term GBH exposure does not compromise the genome stability of bacteria. Copyright © 2017 Tincher et al.

A genome-wide association study of seed protein and oil content in soybean.

Science.gov (United States)

Hwang, Eun-Young; Song, Qijian; Jia, Gaofeng; Specht, James E; Hyten, David L; Costa, Jose; Cregan, Perry B

2014-01-02

Association analysis is an alternative to conventional family-based methods to detect the location of gene(s) or quantitative trait loci (QTL) and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Seed protein and oil concentration are quantitative traits which are determined by the interaction among many genes with small to moderate genetic effects and their interaction with the environment. In this study, a genome-wide association study (GWAS) was performed to identify quantitative trait loci (QTL) controlling seed protein and oil concentration in 298 soybean germplasm accessions exhibiting a wide range of seed protein and oil content. A total of 55,159 single nucleotide polymorphisms (SNPs) were genotyped using various methods including Illumina Infinium and GoldenGate assays and 31,954 markers with minor allele frequency >0.10 were used to estimate linkage disequilibrium (LD) in heterochromatic and euchromatic regions. In euchromatic regions, the mean LD (r2) rapidly declined to 0.2 within 360 Kbp, whereas the mean LD declined to 0.2 at 9,600 Kbp in heterochromatic regions. The GWAS results identified 40 SNPs in 17 different genomic regions significantly associated with seed protein. Of these, the five SNPs with the highest associations and seven adjacent SNPs were located in the 27.6-30.0 Mbp region of Gm20. A major seed protein QTL has been previously mapped to the same location and potential candidate genes have recently been identified in this region. The GWAS results also detected 25 SNPs in 13 different genomic regions associated with seed oil. Of these markers, seven SNPs had a significant association with both protein and oil. This research indicated that GWAS not only identified most of the previously reported QTL controlling seed protein and oil, but also resulted in narrower genomic regions than the regions reported as containing these QTL. The narrower GWAS-defined genome regions will allow more precise

Genome-wide DNA polymorphism analyses using VariScan

Directory of Open Access Journals (Sweden)

Vilella Albert J

2006-09-01

Full Text Available Abstract Background DNA sequence polymorphisms analysis can provide valuable information on the evolutionary forces shaping nucleotide variation, and provides an insight into the functional significance of genomic regions. The recent ongoing genome projects will radically improve our capabilities to detect specific genomic regions shaped by natural selection. Current available methods and software, however, are unsatisfactory for such genome-wide analysis. Results We have developed methods for the analysis of DNA sequence polymorphisms at the genome-wide scale. These methods, which have been tested on a coalescent-simulated and actual data files from mouse and human, have been implemented in the VariScan software package version 2.0. Additionally, we have also incorporated a graphical-user interface. The main features of this software are: i exhaustive population-genetic analyses including those based on the coalescent theory; ii analysis adapted to the shallow data generated by the high-throughput genome projects; iii use of genome annotations to conduct a comprehensive analyses separately for different functional regions; iv identification of relevant genomic regions by the sliding-window and wavelet-multiresolution approaches; v visualization of the results integrated with current genome annotations in commonly available genome browsers. Conclusion VariScan is a powerful and flexible suite of software for the analysis of DNA polymorphisms. The current version implements new algorithms, methods, and capabilities, providing an important tool for an exhaustive exploratory analysis of genome-wide DNA polymorphism data.

Parent-of-origin effects in autism identified through genome-wide linkage analysis of 16,000 SNPs.

Directory of Open Access Journals (Sweden)

Delphine Fradin

2010-09-01

Full Text Available Autism is a common heritable neurodevelopmental disorder with complex etiology. Several genome-wide linkage and association scans have been carried out to identify regions harboring genes related to autism or autism spectrum disorders, with mixed results. Given the overlap in autism features with genetic abnormalities known to be associated with imprinting, one possible reason for lack of consistency would be the influence of parent-of-origin effects that may mask the ability to detect linkage and association.We have performed a genome-wide linkage scan that accounts for potential parent-of-origin effects using 16,311 SNPs among families from the Autism Genetic Resource Exchange (AGRE and the National Institute of Mental Health (NIMH autism repository. We report parametric (GH, Genehunter and allele-sharing linkage (Aspex results using a broad spectrum disorder case definition. Paternal-origin genome-wide statistically significant linkage was observed on chromosomes 4 (LOD(GH = 3.79, empirical p<0.005 and LOD(Aspex = 2.96, p = 0.008, 15 (LOD(GH = 3.09, empirical p<0.005 and LOD(Aspex = 3.62, empirical p = 0.003 and 20 (LOD(GH = 3.36, empirical p<0.005 and LOD(Aspex = 3.38, empirical p = 0.006.These regions may harbor imprinted sites associated with the development of autism and offer fruitful domains for molecular investigation into the role of epigenetic mechanisms in autism.

Genome-wide association study for the interaction between BMR and BMI in obese Korean women including overweight.

Science.gov (United States)

Lee, Myoungsook; Kwon, Dae Young; Kim, Myung-Sunny; Choi, Chong Ran; Park, Mi-Young; Kim, Ae-Jung

2016-02-01

This is the first study to identify common genetic factors associated with the basal metabolic rate (BMR) and body mass index (BMI) in obese Korean women including overweight. This will be a basic study for future research of obese gene-BMR interaction. The experimental design was 2 by 2 with variables of BMR and BMI. A genome-wide association study (GWAS) of single nucleotide polymorphisms (SNPs) was conducted in the overweight and obesity (BMI > 23 kg/m(2)) compared to the normality, and in women with low BMR (BMR. A total of 140 SNPs reached formal genome-wide statistical significance in this study (P BMR (rs10786764; P = 8.0 × 10(-7), rs1040675; 2.3 × 10(-6)) and BMI (rs10786764; P = 2.5 × 10(-5), rs10786764; 6.57 × 10(-5)). The other genes related to BMI (HSD52, TMA16, MARCH1, NRG1, NRXN3, and STK4) yielded P BMR and BMI, including NRG3, OR8U8, BCL2L2-PABPN1, PABPN1, and SLC22A17 were identified in obese Korean women (P BMR- and BMI-related genes using GWAS. Although most of these newly established loci were not previously associated with obesity, they may provide new insights into body weight regulation. Our findings of five common genes associated with BMR and BMI in Koreans will serve as a reference for replication and validation of future studies on the metabolic rate.

Genome-Wide Approaches to Drosophila Heart Development

Directory of Open Access Journals (Sweden)

Manfred Frasch

2016-05-01

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

Genome-wide Association Study of Personality Traits in the Long Life Family Study

Directory of Open Access Journals (Sweden)

Harold T Bae

2013-05-01

Full Text Available Personality traits have been shown to be associated with longevity and healthy aging. In order to discover novel genetic modifiers associated with personality traits as related with longevity, we performed a genome-wide association study (GWAS on personality factors assessed by NEO-FFI in individuals enrolled in the Long Life Family Study (LLFS, a study of 583 families (N up to 4595 with clustering for longevity in the United States and Denmark. Three SNPs, in almost perfect LD, associated with agreeableness reached genome-wide significance (p<10-8 and replicated in an additional sample of 1279 LLFS subjects, although one (rs9650241 failed to replicate and the other two were not available in two independent replication cohorts, the Baltimore Longitudinal Study of Aging and the New England Centenarian Study. Based on 10,000,000 permutations, the empirical p-value of 2X10-7 was observed for the genome-wide significant SNPs. Seventeen SNPs that reached marginal statistical significance in the two previous GWASs (p-value < 10-4 and 10-5, were also marginally significantly associated in this study (p-value < 0.05, although none of the associations passed the Bonferroni correction. In addition, we tested age-by-SNP interactions and found some significant associations. Since scores of personality traits in LLFS subjects change in the oldest ages, and genetic factors outweigh environmental factors to achieve extreme ages, these age-by-SNP interactions could be a proxy for complex gene-gene interactions affecting personality traits and longevity.

Genome-wide gene-environment study identifies glutamate receptor gene GRIN2A as a Parkinson's disease modifier gene via interaction with coffee.

Directory of Open Access Journals (Sweden)

Taye H Hamza

2011-08-01

Full Text Available Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD. We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC, and we performed a genome-wide association and interaction study (GWAIS, testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P(2df = 10(-6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10(-7 but not in light coffee-drinkers. The a priori Replication hypothesis that "Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers" was confirmed: OR(Replication = 0.59, P(Replication = 10(-3; OR(Pooled = 0.51, P(Pooled = 7×10(-8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10(-3, whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10(-13. Imputation revealed a block of SNPs that achieved P(2df<5×10(-8 in GWAIS, and OR = 0.41, P = 3×10(-8 in heavy coffee-drinkers. This study is proof of

Genome wide study of maternal and parent-of-origin effects on the etiology of orofacial clefts

DEFF Research Database (Denmark)

Shi, Min; Murray, Jeff; Marazita, Mary L

2012-01-01

We performed a genome wide association analysis of maternally-mediated genetic effects and parent-of-origin (POO) effects on risk of orofacial clefting (OC) using over 2,000 case-parent triads collected through an international cleft consortium. We used log-linear regression models to test indivi...... individual SNPs. For SNPs with a P-value...

Modifiers of notch transcriptional activity identified by genome-wide RNAi

Directory of Open Access Journals (Sweden)

Firnhaber Christopher B

2010-10-01

Full Text Available Abstract Background The Notch signaling pathway regulates a diverse array of developmental processes, and aberrant Notch signaling can lead to diseases, including cancer. To obtain a more comprehensive understanding of the genetic network that integrates into Notch signaling, we performed a genome-wide RNAi screen in Drosophila cell culture to identify genes that modify Notch-dependent transcription. Results Employing complementary data analyses, we found 399 putative modifiers: 189 promoting and 210 antagonizing Notch activated transcription. These modifiers included several known Notch interactors, validating the robustness of the assay. Many novel modifiers were also identified, covering a range of cellular localizations from the extracellular matrix to the nucleus, as well as a large number of proteins with unknown function. Chromatin-modifying proteins represent a major class of genes identified, including histone deacetylase and demethylase complex components and other chromatin modifying, remodeling and replacement factors. A protein-protein interaction map of the Notch-dependent transcription modifiers revealed that a large number of the identified proteins interact physically with these core chromatin components. Conclusions The genome-wide RNAi screen identified many genes that can modulate Notch transcriptional output. A protein interaction map of the identified genes highlighted a network of chromatin-modifying enzymes and remodelers that regulate Notch transcription. Our results open new avenues to explore the mechanisms of Notch signal regulation and the integration of this pathway into diverse cellular processes.

Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations.

Science.gov (United States)

Ji, Yuan; Schaid, Daniel J; Desta, Zeruesenay; Kubo, Michiaki; Batzler, Anthony J; Snyder, Karen; Mushiroda, Taisei; Kamatani, Naoyuki; Ogburn, Evan; Hall-Flavin, Daniel; Flockhart, David; Nakamura, Yusuke; Mrazek, David A; Weinshilboum, Richard M

2014-08-01

Citalopram (CT) and escitalopram (S-CT) are among the most widely prescribed selective serotonin reuptake inhibitors used to treat major depressive disorder (MDD). We applied a genome-wide association study to identify genetic factors that contribute to variation in plasma concentrations of CT or S-CT and their metabolites in MDD patients treated with CT or S-CT. Our genome-wide association study was performed using samples from 435 MDD patients. Linear mixed models were used to account for within-subject correlations of longitudinal measures of plasma drug/metabolite concentrations (4 and 8 weeks after the initiation of drug therapy), and single-nucleotide polymorphisms (SNPs) were modelled as additive allelic effects. Genome-wide significant associations were observed for S-CT concentration with SNPs in or near the CYP2C19 gene on chromosome 10 (rs1074145, P = 4.1 × 10(-9) ) and with S-didesmethylcitalopram concentration for SNPs near the CYP2D6 locus on chromosome 22 (rs1065852, P = 2.0 × 10(-16) ), supporting the important role of these cytochrome P450 (CYP) enzymes in biotransformation of citalopram. After adjustment for the effect of CYP2C19 functional alleles, the analyses also identified novel loci that will require future replication and functional validation. In vitro and in vivo studies have suggested that the biotransformation of CT to monodesmethylcitalopram and didesmethylcitalopram is mediated by CYP isozymes. The results of our genome-wide association study performed in MDD patients treated with CT or S-CT have confirmed those observations but also identified novel genomic loci that might play a role in variation in plasma levels of CT or its metabolites during the treatment of MDD patients with these selective serotonin reuptake inhibitors. © 2014 The British Pharmacological Society.

Genome-wide association study of multiplex schizophrenia pedigrees

DEFF Research Database (Denmark)

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

2012-01-01

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

Genome-Wide Mutagenesis in Borrelia burgdorferi.

Science.gov (United States)

Lin, Tao; Gao, Lihui

2018-01-01

Signature-tagged mutagenesis (STM) is a functional genomics approach to identify bacterial virulence determinants and virulence factors by simultaneously screening multiple mutants in a single host animal, and has been utilized extensively for the study of bacterial pathogenesis, host-pathogen interactions, and spirochete and tick biology. The signature-tagged transposon mutagenesis has been developed to investigate virulence determinants and pathogenesis of Borrelia burgdorferi. Mutants in genes important in virulence are identified by negative selection in which the mutants fail to colonize or disseminate in the animal host and tick vector. STM procedure combined with Luminex Flex ® Map™ technology and next-generation sequencing (e.g., Tn-seq) are the powerful high-throughput tools for the determination of Borrelia burgdorferi virulence determinants. The assessment of multiple tissue sites and two DNA resources at two different time points using Luminex Flex ® Map™ technology provides a robust data set. B. burgdorferi transposon mutant screening indicates that a high proportion of genes are the novel virulence determinants that are required for mouse and tick infection. In this protocol, an effective signature-tagged Himar1-based transposon suicide vector was developed and used to generate a sequence-defined library of nearly 4800 mutants in the infectious B. burgdorferi B31 clone. In STM, signature-tagged suicide vectors are constructed by inserting unique DNA sequences (tags) into the transposable elements. The signature-tagged transposon mutants are generated when transposon suicide vectors are transformed into an infectious B. burgdorferi clone, and the transposable element is transposed into the 5'-TA-3' sequence in the B. burgdorferi genome with the signature tag. The transposon library is created and consists of many sub-libraries, each sub-library has several hundreds of mutants with same tags. A group of mice or ticks are infected with a mixed

Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity

DEFF Research Database (Denmark)

Thorleifsson, Gudmar; Walters, G Bragi; Gudbjartsson, Daniel F

2009-01-01

Obesity results from the interaction of genetic and environmental factors. To search for sequence variants that affect variation in two common measures of obesity, weight and body mass index (BMI), both of which are highly heritable, we performed a genome-wide association (GWA) study with 305......,846 SNPs typed in 25,344 Icelandic, 2,998 Dutch, 1,890 European Americans and 1,160 African American subjects and combined the results with previously published results from the Diabetes Genetics Initiative (DGI) on 3,024 Scandinavians. We selected 43 variants in 19 regions for follow-up in 5,586 Danish...... individuals and compared the results to a genome-wide study on obesity-related traits from the GIANT consortium. In total, 29 variants, some correlated, in 11 chromosomal regions reached a genome-wide significance threshold of P

Genome-wide nucleosome map and cytosine methylation levels of an ancient human genome

DEFF Research Database (Denmark)

Pedersen, Jakob Skou; Valen, Eivind; Velazquez, Amhed Missael Vargas

2014-01-01

Epigenetic information is available from contemporary organisms, but is difficult to track back in evolutionary time. Here, we show that genome-wide epigenetic information can be gathered directly from next-generation sequence reads of DNA isolated from ancient remains. Using the genome sequence...... data generated from hair shafts of a 4000-yr-old Paleo-Eskimo belonging to the Saqqaq culture, we generate the first ancient nucleosome map coupled with a genome-wide survey of cytosine methylation levels. The validity of both nucleosome map and methylation levels were confirmed by the recovery...

Impact of the genome wide supported NRGN gene on anterior cingulate morphology in schizophrenia.

Directory of Open Access Journals (Sweden)

Kazutaka Ohi

Full Text Available BACKGROUND: The rs12807809 single-nucleotide polymorphism in NRGN is a genetic risk variant with genome-wide significance for schizophrenia. The frequency of the T allele of rs12807809 is higher in individuals with schizophrenia than in those without the disorder. Reduced immunoreactivity of NRGN, which is expressed exclusively in the brain, has been observed in Brodmann areas (BA 9 and 32 of the prefrontal cortex in postmortem brains from patients with schizophrenia compared with those in controls. METHODS: Genotype effects of rs12807809 were investigated on gray matter (GM and white matter (WM volumes using magnetic resonance imaging (MRI with a voxel-based morphometry (VBM technique in a sample of 99 Japanese patients with schizophrenia and 263 healthy controls. RESULTS: Although significant genotype-diagnosis interaction either on GM or WM volume was not observed, there was a trend of genotype-diagnosis interaction on GM volume in the left anterior cingulate cortex (ACC. Thus, the effects of NRGN genotype on GM volume of patients with schizophrenia and healthy controls were separately investigated. In patients with schizophrenia, carriers of the risk T allele had a smaller GM volume in the left ACC (BA32 than did carriers of the non-risk C allele. Significant genotype effect on other regions of the GM or WM was not observed for either the patients or controls. CONCLUSIONS: Our findings suggest that the genome-wide associated genetic risk variant in the NRGN gene may be related to a small GM volume in the ACC in the left hemisphere in patients with schizophrenia.

Identification of novel type 1 diabetes candidate genes by integrating genome-wide association data, protein-protein interactions, and human pancreatic islet gene expression

DEFF Research Database (Denmark)

Bergholdt, Regine; Brorsson, Caroline; Palleja, Albert

2012-01-01

Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated with dis......-cells. Our results provide novel insight to the mechanisms behind type 1 diabetes pathogenesis and, thus, may provide the basis for the design of novel treatment strategies.......Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated...... with disease, and they do not typically inform the broader context in which the disease genes operate. Here, we integrated type 1 diabetes GWAS data with protein-protein interactions to construct biological networks of relevance for disease. A total of 17 networks were identified. To prioritize...

Adiponectin Concentrations: A Genome-wide Association Study

OpenAIRE

Jee, Sun Ha; Sull, Jae Woong; Lee, Jong-Eun; Shin, Chol; Park, Jongkeun; Kimm, Heejin; Cho, Eun-Young; Shin, Eun-Soon; Yun, Ji Eun; Park, Ji Wan; Kim, Sang Yeun; Lee, Sun Ju; Jee, Eun Jung; Baik, Inkyung; Kao, Linda

2010-01-01

Adiponectin is associated with obesity and insulin resistance. To date, there has been no genome-wide association study (GWAS) of adiponectin levels in Asians. Here we present a GWAS of a cohort of Korean volunteers. A total of 4,001 subjects were genotyped by using a genome-wide marker panel in a two-stage design (979 subjects initially and 3,022 in a second stage). Another 2,304 subjects were used for follow-up replication studies with selected markers. In the discovery phase, the top SNP a...

A genome-wide association study of resistance to HIV infection in highly exposed uninfected individuals with hemophilia A

Science.gov (United States)

Lane, Jérôme; McLaren, Paul J.; Dorrell, Lucy; Shianna, Kevin V.; Stemke, Amanda; Pelak, Kimberly; Moore, Stephen; Oldenburg, Johannes; Alvarez-Roman, Maria Teresa; Angelillo-Scherrer, Anne; Boehlen, Francoise; Bolton-Maggs, Paula H.B.; Brand, Brigit; Brown, Deborah; Chiang, Elaine; Cid-Haro, Ana Rosa; Clotet, Bonaventura; Collins, Peter; Colombo, Sara; Dalmau, Judith; Fogarty, Patrick; Giangrande, Paul; Gringeri, Alessandro; Iyer, Rathi; Katsarou, Olga; Kempton, Christine; Kuriakose, Philip; Lin, Judith; Makris, Mike; Manco-Johnson, Marilyn; Tsakiris, Dimitrios A.; Martinez-Picado, Javier; Mauser-Bunschoten, Evelien; Neff, Anne; Oka, Shinichi; Oyesiku, Lara; Parra, Rafael; Peter-Salonen, Kristiina; Powell, Jerry; Recht, Michael; Shapiro, Amy; Stine, Kimo; Talks, Katherine; Telenti, Amalio; Wilde, Jonathan; Yee, Thynn Thynn; Wolinsky, Steven M.; Martinson, Jeremy; Hussain, Shehnaz K.; Bream, Jay H.; Jacobson, Lisa P.; Carrington, Mary; Goedert, James J.; Haynes, Barton F.; McMichael, Andrew J.; Goldstein, David B.; Fellay, Jacques

2013-01-01

Human genetic variation contributes to differences in susceptibility to HIV-1 infection. To search for novel host resistance factors, we performed a genome-wide association study (GWAS) in hemophilia patients highly exposed to potentially contaminated factor VIII infusions. Individuals with hemophilia A and a documented history of factor VIII infusions before the introduction of viral inactivation procedures (1979–1984) were recruited from 36 hemophilia treatment centers (HTCs), and their genome-wide genetic variants were compared with those from matched HIV-infected individuals. Homozygous carriers of known CCR5 resistance mutations were excluded. Single nucleotide polymorphisms (SNPs) and inferred copy number variants (CNVs) were tested using logistic regression. In addition, we performed a pathway enrichment analysis, a heritability analysis, and a search for epistatic interactions with CCR5 Δ32 heterozygosity. A total of 560 HIV-uninfected cases were recruited: 36 (6.4%) were homozygous for CCR5 Δ32 or m303. After quality control and SNP imputation, we tested 1 081 435 SNPs and 3686 CNVs for association with HIV-1 serostatus in 431 cases and 765 HIV-infected controls. No SNP or CNV reached genome-wide significance. The additional analyses did not reveal any strong genetic effect. Highly exposed, yet uninfected hemophiliacs form an ideal study group to investigate host resistance factors. Using a genome-wide approach, we did not detect any significant associations between SNPs and HIV-1 susceptibility, indicating that common genetic variants of major effect are unlikely to explain the observed resistance phenotype in this population. PMID:23372042

A genome-wide meta-analysis of genetic variants associated with allergic rhinitis and grass sensitization and their interaction with birth order.

Science.gov (United States)

Ramasamy, Adaikalavan; Curjuric, Ivan; Coin, Lachlan J; Kumar, Ashish; McArdle, Wendy L; Imboden, Medea; Leynaert, Benedicte; Kogevinas, Manolis; Schmid-Grendelmeier, Peter; Pekkanen, Juha; Wjst, Matthias; Bircher, Andreas J; Sovio, Ulla; Rochat, Thierry; Hartikainen, Anna-Liisa; Balding, David J; Jarvelin, Marjo-Riitta; Probst-Hensch, Nicole; Strachan, David P; Jarvis, Deborah L

2011-11-01

Hay fever or seasonal allergic rhinitis (AR) is a chronic disorder associated with IgE sensitization to grass. The underlying genetic variants have not been studied comprehensively. There is overwhelming evidence that those who have older siblings have less AR, although the mechanism for this remains unclear. We sought to identify common genetic variant associations with prevalent AR and grass sensitization using existing genome-wide association study (GWAS) data and to determine whether genetic variants modify the protective effect of older siblings. Approximately 2.2 million genotyped or imputed single nucleotide polymorphisms were investigated in 4 large European adult cohorts for AR (3,933 self-reported cases vs 8,965 control subjects) and grass sensitization (2,315 cases vs 10,032 control subjects). Three loci reached genome-wide significance for either phenotype. The HLA variant rs7775228, which cis-regulates HLA-DRB4, was strongly associated with grass sensitization and weakly with AR (P(grass) = 1.6 × 10(-9); P(AR) = 8.0 × 10(-3)). Variants in a locus near chromosome 11 open reading frame 30 (C11orf30) and leucine-rich repeat containing 32 (LRRC32), which was previously associated with atopic dermatitis and eczema, were also strongly associated with both phenotypes (rs2155219; P(grass) = 9.4 × 10(-9); P(AR) = 3.8 × 10(-8)). The third genome-wide significant variant was rs17513503 (P(grass) = 1.2 × 10(-8); PAR = 7.4 × 10(-7)) which was located near transmembrane protein 232 (TMEM232) and solute carrier family 25, member 46 (SLC25A46). Twelve further loci with suggestive associations were also identified. Using a candidate gene approach, where we considered variants within 164 genes previously thought to be important, we found variants in 3 further genes that may be of interest: thymic stromal lymphopoietin (TSLP), Toll-like receptor 6 (TLR6) and nucleotide-binding oligomerization domain containing 1 (NOD1/CARD4). We found no evidence for variants

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

Directory of Open Access Journals (Sweden)

Wesley K Thompson

2015-12-01

Full Text Available Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local false discovery rate, and power for discovery of a specified proportion of phenotypic variance explained from additive effects of loci surpassing a given significance threshold. We also examine the crucial issue of the impact of linkage disequilibrium (LD on effect sizes and parameter estimates, both analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn's disease (CD and the other for schizophrenia (SZ. A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While capturing the general behavior of the data, this mixture model underestimates the tails of the CD effect size distribution. We discuss the

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

Science.gov (United States)

Thompson, Wesley K; Wang, Yunpeng; Schork, Andrew J; Witoelar, Aree; Zuber, Verena; Xu, Shujing; Werge, Thomas; Holland, Dominic; Andreassen, Ole A; Dale, Anders M

2015-12-01

Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS) test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local false discovery rate, and power for discovery of a specified proportion of phenotypic variance explained from additive effects of loci surpassing a given significance threshold. We also examine the crucial issue of the impact of linkage disequilibrium (LD) on effect sizes and parameter estimates, both analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn's disease (CD) and the other for schizophrenia (SZ). A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While capturing the general behavior of the data, this mixture model underestimates the tails of the CD effect size distribution. We discuss the implications of

Genome-wide identification of direct HBx genomic targets

KAUST Repository

Guerrieri, Francesca

2017-02-17

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

Controversy and debate on clinical genomics sequencing-paper 2: clinical genome-wide sequencing: don't throw out the baby with the bathwater!

Science.gov (United States)

Adam, Shelin; Friedman, Jan M

2017-12-01

Genome-wide (exome or whole genome) sequencing with appropriate genetic counseling should be considered for any patient with a suspected Mendelian disease that has not been identified by conventional testing. Clinical genome-wide sequencing provides a powerful and effective means of identifying specific genetic causes of serious disease and improving clinical care. Copyright © 2017 Elsevier Inc. All rights reserved.

Meta-analysis of 32 genome-wide linkage studies of schizophrenia

Science.gov (United States)

Ng, MYM; Levinson, DF; Faraone, SV; Suarez, BK; DeLisi, LE; Arinami, T; Riley, B; Paunio, T; Pulver, AE; Irmansyah; Holmans, PA; Escamilla, M; Wildenauer, DB; Williams, NM; Laurent, C; Mowry, BJ; Brzustowicz, LM; Maziade, M; Sklar, P; Garver, DL; Abecasis, GR; Lerer, B; Fallin, MD; Gurling, HMD; Gejman, PV; Lindholm, E; Moises, HW; Byerley, W; Wijsman, EM; Forabosco, P; Tsuang, MT; Hwu, H-G; Okazaki, Y; Kendler, KS; Wormley, B; Fanous, A; Walsh, D; O’Neill, FA; Peltonen, L; Nestadt, G; Lasseter, VK; Liang, KY; Papadimitriou, GM; Dikeos, DG; Schwab, SG; Owen, MJ; O’Donovan, MC; Norton, N; Hare, E; Raventos, H; Nicolini, H; Albus, M; Maier, W; Nimgaonkar, VL; Terenius, L; Mallet, J; Jay, M; Godard, S; Nertney, D; Alexander, M; Crowe, RR; Silverman, JM; Bassett, AS; Roy, M-A; Mérette, C; Pato, CN; Pato, MT; Roos, J Louw; Kohn, Y; Amann-Zalcenstein, D; Kalsi, G; McQuillin, A; Curtis, D; Brynjolfson, J; Sigmundsson, T; Petursson, H; Sanders, AR; Duan, J; Jazin, E; Myles-Worsley, M; Karayiorgou, M; Lewis, CM

2009-01-01

A genome scan meta-analysis (GSMA) was carried out on 32 independent genome-wide linkage scan analyses that included 3255 pedigrees with 7413 genotyped cases affected with schizophrenia (SCZ) or related disorders. The primary GSMA divided the autosomes into 120 bins, rank-ordered the bins within each study according to the most positive linkage result in each bin, summed these ranks (weighted for study size) for each bin across studies and determined the empirical probability of a given summed rank (PSR) by simulation. Suggestive evidence for linkage was observed in two single bins, on chromosomes 5q (142-168 Mb) and 2q (103-134 Mb). Genome-wide evidence for linkage was detected on chromosome 2q (119-152 Mb) when bin boundaries were shifted to the middle of the previous bins. The primary analysis met empirical criteria for ‘aggregate’ genome-wide significance, indicating that some or all of 10 bins are likely to contain loci linked to SCZ, including regions of chromosomes 1, 2q, 3q, 4q, 5q, 8p and 10q. In a secondary analysis of 22 studies of European-ancestry samples, suggestive evidence for linkage was observed on chromosome 8p (16-33 Mb). Although the newer genome-wide association methodology has greater power to detect weak associations to single common DNA sequence variants, linkage analysis can detect diverse genetic effects that segregate in families, including multiple rare variants within one locus or several weakly associated loci in the same region. Therefore, the regions supported by this meta-analysis deserve close attention in future studies. PMID:19349958

Genome-wide expressions in autologous eutopic and ectopic endometrium of fertile women with endometriosis

OpenAIRE

Khan, Meraj A; Sengupta, Jayasree; Mittal, Suneeta; Ghosh, Debabrata

2012-01-01

Abstract Background In order to obtain a lead of the pathophysiology of endometriosis, genome-wide expressional analyses of eutopic and ectopic endometrium have earlier been reported, however, the effects of stages of severity and phases of menstrual cycle on expressional profiles have not been examined. The effect of genetic heterogeneity and fertility history on transcriptional activity was also not considered. In the present study, a genome-wide expression analysis of autologous, paired eu...

The properties of genome conformation and spatial gene interaction and regulation networks of normal and malignant human cell types.

Directory of Open Access Journals (Sweden)

Zheng Wang

Full Text Available The spatial conformation of a genome plays an important role in the long-range regulation of genome-wide gene expression and methylation, but has not been extensively studied due to lack of genome conformation data. The recently developed chromosome conformation capturing techniques such as the Hi-C method empowered by next generation sequencing can generate unbiased, large-scale, high-resolution chromosomal interaction (contact data, providing an unprecedented opportunity to investigate the spatial structure of a genome and its applications in gene regulation, genomics, epigenetics, and cell biology. In this work, we conducted a comprehensive, large-scale computational analysis of this new stream of genome conformation data generated for three different human leukemia cells or cell lines by the Hi-C technique. We developed and applied a set of bioinformatics methods to reliably generate spatial chromosomal contacts from high-throughput sequencing data and to effectively use them to study the properties of the genome structures in one-dimension (1D and two-dimension (2D. Our analysis demonstrates that Hi-C data can be effectively applied to study tissue-specific genome conformation, chromosome-chromosome interaction, chromosomal translocations, and spatial gene-gene interaction and regulation in a three-dimensional genome of primary tumor cells. Particularly, for the first time, we constructed genome-scale spatial gene-gene interaction network, transcription factor binding site (TFBS - TFBS interaction network, and TFBS-gene interaction network from chromosomal contact information. Remarkably, all these networks possess the properties of scale-free modular networks.

Genome-wide screening identifies a KCNIP1 copy number variant as a genetic predictor for atrial fibrillation

Science.gov (United States)

Tsai, Chia-Ti; Hsieh, Chia-Shan; Chang, Sheng-Nan; Chuang, Eric Y.; Ueng, Kwo-Chang; Tsai, Chin-Feng; Lin, Tsung-Hsien; Wu, Cho-Kai; Lee, Jen-Kuang; Lin, Lian-Yu; Wang, Yi-Chih; Yu, Chih-Chieh; Lai, Ling-Ping; Tseng, Chuen-Den; Hwang, Juey-Jen; Chiang, Fu-Tien; Lin, Jiunn-Lee

2016-01-01

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. Previous genome-wide association studies had identified single-nucleotide polymorphisms in several genomic regions to be associated with AF. In human genome, copy number variations (CNVs) are known to contribute to disease susceptibility. Using a genome-wide multistage approach to identify AF susceptibility CNVs, we here show a common 4,470-bp diallelic CNV in the first intron of potassium interacting channel 1 gene (KCNIP1) is strongly associated with AF in Taiwanese populations (odds ratio=2.27 for insertion allele; P=6.23 × 10−24). KCNIP1 insertion is associated with higher KCNIP1 mRNA expression. KCNIP1-encoded protein potassium interacting channel 1 (KCHIP1) is physically associated with potassium Kv channels and modulates atrial transient outward current in cardiac myocytes. Overexpression of KCNIP1 results in inducible AF in zebrafish. In conclusions, a common CNV in KCNIP1 gene is a genetic predictor of AF risk possibly pointing to a functional pathway. PMID:26831368

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

Directory of Open Access Journals (Sweden)

Ding Jiandong

2012-06-01

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

Genome-wide mapping of DNA strand breaks.

Directory of Open Access Journals (Sweden)

Frédéric Leduc

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

Genome-Wide Association Meta-Analyses to Identify Common Genetic Variants Associated with Hallux Valgus in Caucasian and African Americans

Science.gov (United States)

Hsu, Yi-Hsiang; Liu, Youfang; Hannan, Marian T.; Maixner, William; Smith, Shad B.; Diatchenko, Luda; Golightly, Yvonne M.; Menz, Hylton B.; Kraus, Virginia B.; Doherty, Michael; Wilson, A.G.; Jordan, Joanne M.

2016-01-01

Objective Hallux valgus (HV) affects ~36% of Caucasian adults. Although considered highly heritable, the underlying genetic determinants are unclear. We conducted the first genome-wide association study (GWAS) aimed to identify genetic variants associated with HV. Methods HV was assessed in 3 Caucasian cohorts (n=2,263, n=915, and n=1,231 participants, respectively). In each cohort, a GWAS was conducted using 2.5M imputed single nucleotide polymorphisms (SNPs). Mixed-effect regression with the additive genetic model adjusted for age, sex, weight and within-family correlations was used for both sex-specific and combined analyses. To combine GWAS results across cohorts, fixed-effect inverse-variance meta-analyses were used. Following meta-analyses, top-associated findings were also examined in an African American cohort (n=327). Results The proportion of HV variance explained by genome-wide genotyped SNPs was 50% in men and 48% in women. A higher proportion of genetic determinants of HV was sex-specific. The most significantly associated SNP in men was rs9675316 located on chr17q23-a24 near the AXIN2 gene (p=5.46×10−7); the most significantly associated SNP in women was rs7996797 located on chr13q14.1-q14.2 near the ESD gene (p=7.21×10−7). Genome-wide significant SNP-by-sex interaction was found for SNP rs1563374 located on chr11p15.1 near the MRGPRX3 gene (interaction p-value =4.1×10−9). The association signals diminished when combining men and women. Conclusion Findings suggest that the potential pathophysiological mechanisms of HV are complex and strongly underlined by sex-specific interactions. The identified genetic variants imply contribution of biological pathways observed in osteoarthritis as well as new pathways, influencing skeletal development and inflammation. PMID:26337638

Behavior of QQ-plots and genomic control in studies of gene-environment interaction.

Directory of Open Access Journals (Sweden)

Arend Voorman

2011-05-01

Full Text Available Genome-wide association studies of gene-environment interaction (GxE GWAS are becoming popular. As with main effects GWAS, quantile-quantile plots (QQ-plots and Genomic Control are being used to assess and correct for population substructure. However, in G x E work these approaches can be seriously misleading, as we illustrate; QQ-plots may give strong indications of substructure when absolutely none is present. Using simulation and theory, we show how and why spurious QQ-plot inflation occurs in G x E GWAS, and how this differs from main-effects analyses. We also explain how simple adjustments to standard regression-based methods used in G x E GWAS can alleviate this problem.

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

Science.gov (United States)

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

Quality control and conduct of genome-wide association meta-analyses

DEFF Research Database (Denmark)

Winkler, Thomas W; Day, Felix R; Croteau-Chonka, Damien C

2014-01-01

Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for (i) organizational aspects of GWAMAs, and for (ii) QC...

Genome-wide association study of pathological gambling.

Science.gov (United States)

Lang, M; Leménager, T; Streit, F; Fauth-Bühler, M; Frank, J; Juraeva, D; Witt, S H; Degenhardt, F; Hofmann, A; Heilmann-Heimbach, S; Kiefer, F; Brors, B; Grabe, H-J; John, U; Bischof, A; Bischof, G; Völker, U; Homuth, G; Beutel, M; Lind, P A; Medland, S E; Slutske, W S; Martin, N G; Völzke, H; Nöthen, M M; Meyer, C; Rumpf, H-J; Wurst, F M; Rietschel, M; Mann, K F

2016-08-01

Pathological gambling is a behavioural addiction with negative economic, social, and psychological consequences. Identification of contributing genes and pathways may improve understanding of aetiology and facilitate therapy and prevention. Here, we report the first genome-wide association study of pathological gambling. Our aims were to identify pathways involved in pathological gambling, and examine whether there is a genetic overlap between pathological gambling and alcohol dependence. Four hundred and forty-five individuals with a diagnosis of pathological gambling according to the Diagnostic and Statistical Manual of Mental Disorders were recruited in Germany, and 986 controls were drawn from a German general population sample. A genome-wide association study of pathological gambling comprising single marker, gene-based, and pathway analyses, was performed. Polygenic risk scores were generated using data from a German genome-wide association study of alcohol dependence. No genome-wide significant association with pathological gambling was found for single markers or genes. Pathways for Huntington's disease (P-value=6.63×10(-3)); 5'-adenosine monophosphate-activated protein kinase signalling (P-value=9.57×10(-3)); and apoptosis (P-value=1.75×10(-2)) were significant. Polygenic risk score analysis of the alcohol dependence dataset yielded a one-sided nominal significant P-value in subjects with pathological gambling, irrespective of comorbid alcohol dependence status. The present results accord with previous quantitative formal genetic studies which showed genetic overlap between non-substance- and substance-related addictions. Furthermore, pathway analysis suggests shared pathology between Huntington's disease and pathological gambling. This finding is consistent with previous imaging studies. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Genomic Selection for Drought Tolerance Using Genome-Wide SNPs in Maize

Directory of Open Access Journals (Sweden)

Thirunavukkarasu Nepolean

2017-04-01

Full Text Available Traditional breeding strategies for selecting superior genotypes depending on phenotypic traits have proven to be of limited success, as this direct selection is hindered by low heritability, genetic interactions such as epistasis, environmental-genotype interactions, and polygenic effects. With the advent of new genomic tools, breeders have paved a way for selecting superior breeds. Genomic selection (GS has emerged as one of the most important approaches for predicting genotype performance. Here, we tested the breeding values of 240 maize subtropical lines phenotyped for drought at different environments using 29,619 cured SNPs. Prediction accuracies of seven genomic selection models (ridge regression, LASSO, elastic net, random forest, reproducing kernel Hilbert space, Bayes A and Bayes B were tested for their agronomic traits. Though prediction accuracies of Bayes B, Bayes A and RKHS were comparable, Bayes B outperformed the other models by predicting highest Pearson correlation coefficient in all three environments. From Bayes B, a set of the top 1053 significant SNPs with higher marker effects was selected across all datasets to validate the genes and QTLs. Out of these 1053 SNPs, 77 SNPs associated with 10 drought-responsive transcription factors. These transcription factors were associated with different physiological and molecular functions (stomatal closure, root development, hormonal signaling and photosynthesis. Of several models, Bayes B has been shown to have the highest level of prediction accuracy for our data sets. Our experiments also highlighted several SNPs based on their performance and relative importance to drought tolerance. The result of our experiments is important for the selection of superior genotypes and candidate genes for breeding drought-tolerant maize hybrids.

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

DEFF Research Database (Denmark)

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

2011-01-01

steatosis, a non-invasive measure of NAFLD, in large population based samples. Using variance components methods, we show that CT hepatic steatosis is heritable (~26%-27%) in family-based Amish, Family Heart, and Framingham Heart Studies (n¿=¿880 to 3,070). By carrying out a fixed-effects meta......-analysis of genome-wide association (GWA) results between CT hepatic steatosis and ~2.4 million imputed or genotyped SNPs in 7,176 individuals from the Old Order Amish, Age, Gene/Environment Susceptibility-Reykjavik study (AGES), Family Heart, and Framingham Heart Studies, we identify variants associated at genome......Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic...

Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

Science.gov (United States)

Nguyen, Thanh-Tung; Huang, Joshua; Wu, Qingyao; Nguyen, Thuy; Li, Mark

2015-01-01

Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large portion of SNPs in the data is irrelevant to the disease. Advanced machine learning methods have been successfully used in Genome-wide association studies (GWAS) for identification of genetic variants that have relatively big effects in some common, complex diseases. Among them, the most successful one is Random Forests (RF). Despite of performing well in terms of prediction accuracy in some data sets with moderate size, RF still suffers from working in GWAS for selecting informative SNPs and building accurate prediction models. In this paper, we propose to use a new two-stage quality-based sampling method in random forests, named ts-RF, for SNP subspace selection for GWAS. The method first applies p-value assessment to find a cut-off point that separates informative and irrelevant SNPs in two groups. The informative SNPs group is further divided into two sub-groups: highly informative and weak informative SNPs. When sampling the SNP subspace for building trees for the forest, only those SNPs from the two sub-groups are taken into account. The feature subspaces always contain highly informative SNPs when used to split a node at a tree. This approach enables one to generate more accurate trees with a lower prediction error, meanwhile possibly avoiding overfitting. It allows one to detect interactions of multiple SNPs with the diseases, and to reduce the dimensionality and the amount of Genome-wide association data needed for learning the RF model. Extensive experiments on two genome-wide SNP data sets (Parkinson case-control data comprised of 408,803 SNPs and Alzheimer case-control data comprised of 380,157 SNPs) and 10 gene data sets have demonstrated that the proposed model significantly reduced prediction errors and outperformed

Genome-wide association study of clinical dimensions of schizophrenia

DEFF Research Database (Denmark)

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

2012-01-01

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

GWIS: Genome-Wide Inferred Statistics for Functions of Multiple Phenotypes

NARCIS (Netherlands)

Nieuwboer, H.A.; Pool, R.; Dolan, C.V.; Boomsma, D.I.; Nivard, M.G.

2016-01-01

Here we present a method of genome-wide inferred study (GWIS) that provides an approximation of genome-wide association study (GWAS) summary statistics for a variable that is a function of phenotypes for which GWAS summary statistics, phenotypic means, and covariances are available. A GWIS can be

REVIEW: Genome-wide findings in schizophrenia and the role of gene-environment interplay.

Science.gov (United States)

Van Winkel, Ruud; Esquivel, Gabriel; Kenis, Gunter; Wichers, Marieke; Collip, Dina; Peerbooms, Odette; Rutten, Bart; Myin-Germeys, Inez; Van Os, Jim

2010-10-01

The recent advent of genome-wide mass-marker technology has resulted in renewed optimism to unravel the genetic architecture of psychotic disorders. Genome-wide association studies have identified a number of common polymorphisms robustly associated with schizophrenia, in ZNF804A, transcription factor 4, major histocompatibility complex, and neurogranin. In addition, copy number variants (CNVs) in 1q21.1, 2p16.3, 15q11.2, 15q13.3, 16p11.2, and 22q11.2 were convincingly implicated in schizophrenia risk. Furthermore, these studies have suggested considerable genetic overlap with bipolar disorder (particularly for common polymorphisms) and neurodevelopmental disorders such as autism (particularly for CNVs). The influence of these risk variants on relevant intermediate phenotypes needs further study. In addition, there is a need for etiological models of psychosis integrating genetic risk with environmental factors associated with the disorder, focusing specifically on environmental impact on gene expression (epigenetics) and convergence of genes and environment on common biological pathways bringing about larger effects than those of genes or environment in isolation (gene-environment interaction). Collaborative efforts that bring together expertise in statistics, genetics, epidemiology, experimental psychiatry, brain imaging, and clinical psychiatry will be required to succeed in this challenging task. © 2010 Blackwell Publishing Ltd.

Network Biomarkers of Bladder Cancer Based on a Genome-Wide Genetic and Epigenetic Network Derived from Next-Generation Sequencing Data.

Science.gov (United States)

Li, Cheng-Wei; Chen, Bor-Sen

2016-01-01

Epigenetic and microRNA (miRNA) regulation are associated with carcinogenesis and the development of cancer. By using the available omics data, including those from next-generation sequencing (NGS), genome-wide methylation profiling, candidate integrated genetic and epigenetic network (IGEN) analysis, and drug response genome-wide microarray analysis, we constructed an IGEN system based on three coupling regression models that characterize protein-protein interaction networks (PPINs), gene regulatory networks (GRNs), miRNA regulatory networks (MRNs), and epigenetic regulatory networks (ERNs). By applying system identification method and principal genome-wide network projection (PGNP) to IGEN analysis, we identified the core network biomarkers to investigate bladder carcinogenic mechanisms and design multiple drug combinations for treating bladder cancer with minimal side-effects. The progression of DNA repair and cell proliferation in stage 1 bladder cancer ultimately results not only in the derepression of miR-200a and miR-200b but also in the regulation of the TNF pathway to metastasis-related genes or proteins, cell proliferation, and DNA repair in stage 4 bladder cancer. We designed a multiple drug combination comprising gefitinib, estradiol, yohimbine, and fulvestrant for treating stage 1 bladder cancer with minimal side-effects, and another multiple drug combination comprising gefitinib, estradiol, chlorpromazine, and LY294002 for treating stage 4 bladder cancer with minimal side-effects.

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.

Survey of protein–DNA interactions in Aspergillus oryzae on a genomic scale

Science.gov (United States)

Wang, Chao; Lv, Yangyong; Wang, Bin; Yin, Chao; Lin, Ying; Pan, Li

2015-01-01

The genome-scale delineation of in vivo protein–DNA interactions is key to understanding genome function. Only ∼5% of transcription factors (TFs) in the Aspergillus genus have been identified using traditional methods. Although the Aspergillus oryzae genome contains >600 TFs, knowledge of the in vivo genome-wide TF-binding sites (TFBSs) in aspergilli remains limited because of the lack of high-quality antibodies. We investigated the landscape of in vivo protein–DNA interactions across the A. oryzae genome through coupling the DNase I digestion of intact nuclei with massively parallel sequencing and the analysis of cleavage patterns in protein–DNA interactions at single-nucleotide resolution. The resulting map identified overrepresented de novo TF-binding motifs from genomic footprints, and provided the detailed chromatin remodeling patterns and the distribution of digital footprints near transcription start sites. The TFBSs of 19 known Aspergillus TFs were also identified based on DNase I digestion data surrounding potential binding sites in conjunction with TF binding specificity information. We observed that the cleavage patterns of TFBSs were dependent on the orientation of TF motifs and independent of strand orientation, consistent with the DNA shape features of binding motifs with flanking sequences. PMID:25883143

Novel Genes Affecting the Interaction between the Cabbage Whitefly and Arabidopsis Uncovered by Genome-Wide Association Mapping.

Directory of Open Access Journals (Sweden)

Colette Broekgaarden

Full Text Available Plants have evolved a variety of ways to defend themselves against biotic attackers. This has resulted in the presence of substantial variation in defense mechanisms among plants, even within a species. Genome-wide association (GWA mapping is a useful tool to study the genetic architecture of traits, but has so far only had limited exploitation in studies of plant defense. Here, we study the genetic architecture of defense against the phloem-feeding insect cabbage whitefly (Aleyrodes proletella in Arabidopsis thaliana. We determined whitefly performance, i.e. the survival and reproduction of whitefly females, on 360 worldwide selected natural accessions and subsequently performed GWA mapping using 214,051 SNPs. Substantial variation for whitefly adult survival and oviposition rate (number of eggs laid per female per day was observed between the accessions. We identified 39 candidate SNPs for either whitefly adult survival or oviposition rate, all with relatively small effects, underpinning the complex architecture of defense traits. Among the corresponding candidate genes, i.e. genes in linkage disequilibrium (LD with candidate SNPs, none have previously been identified as a gene playing a role in the interaction between plants and phloem-feeding insects. Whitefly performance on knock-out mutants of a number of candidate genes was significantly affected, validating the potential of GWA mapping for novel gene discovery in plant-insect interactions. Our results show that GWA analysis is a very useful tool to gain insight into the genetic architecture of plant defense against herbivorous insects, i.e. we identified and validated several genes affecting whitefly performance that have not previously been related to plant defense against herbivorous insects.

A Genome-Wide Breast Cancer Scan in African Americans

Science.gov (United States)

2010-06-01

SNPs from the African American breast cancer scan to COGs , a European collaborative study which is has designed a SNP array with that will be genotyped...Award Number: W81XWH-08-1-0383 TITLE: A Genome-wide Breast Cancer Scan in African Americans PRINCIPAL INVESTIGATOR: Christopher A...SUBTITLE A Genome-wide Breast Cancer Scan in African Americans 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-08-1-0383 5c. PROGRAM

Detection of gene–environment interaction in pedigree data using genome-wide genotypes

Science.gov (United States)

Nivard, Michel G; Middeldorp, Christel M; Lubke, Gitta; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Boomsma, Dorret I; Dolan, Conor V

2016-01-01

Heritability may be estimated using phenotypic data collected in relatives or in distantly related individuals using genome-wide single nucleotide polymorphism (SNP) data. We combined these approaches by re-parameterizing the model proposed by Zaitlen et al and extended this model to include moderation of (total and SNP-based) genetic and environmental variance components by a measured moderator. By means of data simulation, we demonstrated that the type 1 error rates of the proposed test are correct and parameter estimates are accurate. As an application, we considered the moderation by age or year of birth of variance components associated with body mass index (BMI), height, attention problems (AP), and symptoms of anxiety and depression. The genetic variance of BMI was found to increase with age, but the environmental variance displayed a greater increase with age, resulting in a proportional decrease of the heritability of BMI. Environmental variance of height increased with year of birth. The environmental variance of AP increased with age. These results illustrate the assessment of moderation of environmental and genetic effects, when estimating heritability from combined SNP and family data. The assessment of moderation of genetic and environmental variance will enhance our understanding of the genetic architecture of complex traits. PMID:27436263

Informing the Design of Direct-to-Consumer Interactive Personal Genomics Reports.

Science.gov (United States)

Shaer, Orit; Nov, Oded; Okerlund, Johanna; Balestra, Martina; Stowell, Elizabeth; Ascher, Laura; Bi, Joanna; Schlenker, Claire; Ball, Madeleine

2015-06-12

In recent years, people who sought direct-to-consumer genetic testing services have been increasingly confronted with an unprecedented amount of personal genomic information, which influences their decisions, emotional state, and well-being. However, these users of direct-to-consumer genetic services, who vary in their education and interests, frequently have little relevant experience or tools for understanding, reasoning about, and interacting with their personal genomic data. Online interactive techniques can play a central role in making personal genomic data useful for these users. We sought to (1) identify the needs of diverse users as they make sense of their personal genomic data, (2) consequently develop effective interactive visualizations of genomic trait data to address these users' needs, and (3) evaluate the effectiveness of the developed visualizations in facilitating comprehension. The first two user studies, conducted with 63 volunteers in the Personal Genome Project and with 36 personal genomic users who participated in a design workshop, respectively, employed surveys and interviews to identify the needs and expectations of diverse users. Building on the two initial studies, the third study was conducted with 730 Amazon Mechanical Turk users and employed a controlled experimental design to examine the effectiveness of different design interventions on user comprehension. The first two studies identified searching, comparing, sharing, and organizing data as fundamental to users' understanding of personal genomic data. The third study demonstrated that interactive and visual design interventions could improve the understandability of personal genomic reports for consumers. In particular, results showed that a new interactive bubble chart visualization designed for the study resulted in the highest comprehension scores, as well as the highest perceived comprehension scores. These scores were significantly higher than scores received using the

Genome-wide association studies and resting heart rate

DEFF Research Database (Denmark)

Oskari Kilpeläinen, Tuomas

2016-01-01

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

Ensembl Genomes 2013: scaling up access to genome-wide data.

Science.gov (United States)

Kersey, Paul Julian; Allen, James E; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Hughes, Daniel Seth Toney; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Langridge, Nicholas; McDowall, Mark D; Maheswari, Uma; Maslen, Gareth; Nuhn, Michael; Ong, Chuang Kee; Paulini, Michael; Pedro, Helder; Toneva, Iliana; Tuli, Mary Ann; Walts, Brandon; Williams, Gareth; Wilson, Derek; Youens-Clark, Ken; Monaco, Marcela K; Stein, Joshua; Wei, Xuehong; Ware, Doreen; Bolser, Daniel M; Howe, Kevin Lee; Kulesha, Eugene; Lawson, Daniel; Staines, Daniel Michael

2014-01-01

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species. The project exploits and extends technologies for genome annotation, analysis and dissemination, developed in the context of the vertebrate-focused Ensembl project, and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. This article provides an update to the previous publications about the resource, with a focus on recent developments. These include the addition of important new genomes (and related data sets) including crop plants, vectors of human disease and eukaryotic pathogens. In addition, the resource has scaled up its representation of bacterial genomes, and now includes the genomes of over 9000 bacteria. Specific extensions to the web and programmatic interfaces have been developed to support users in navigating these large data sets. Looking forward, analytic tools to allow targeted selection of data for visualization and download are likely to become increasingly important in future as the number of available genomes increases within all domains of life, and some of the challenges faced in representing bacterial data are likely to become commonplace for eukaryotes in future.

Pervasive, Genome-Wide Transcription in the Organelle Genomes of Diverse Plastid-Bearing Protists

Directory of Open Access Journals (Sweden)

Matheus Sanitá Lima

2017-11-01

Full Text Available Organelle genomes are among the most sequenced kinds of chromosome. This is largely because they are small and widely used in molecular studies, but also because next-generation sequencing technologies made sequencing easier, faster, and cheaper. However, studies of organelle RNA have not kept pace with those of DNA, despite huge amounts of freely available eukaryotic RNA-sequencing (RNA-seq data. Little is known about organelle transcription in nonmodel species, and most of the available eukaryotic RNA-seq data have not been mined for organelle transcripts. Here, we use publicly available RNA-seq experiments to investigate organelle transcription in 30 diverse plastid-bearing protists with varying organelle genomic architectures. Mapping RNA-seq data to organelle genomes revealed pervasive, genome-wide transcription, regardless of the taxonomic grouping, gene organization, or noncoding content. For every species analyzed, transcripts covered ≥85% of the mitochondrial and/or plastid genomes (all of which were ≤105 kb, indicating that most of the organelle DNA—coding and noncoding—is transcriptionally active. These results follow earlier studies of model species showing that organellar transcription is coupled and ubiquitous across the genome, requiring significant downstream processing of polycistronic transcripts. Our findings suggest that noncoding organelle DNA can be transcriptionally active, raising questions about the underlying function of these transcripts and underscoring the utility of publicly available RNA-seq data for recovering complete genome sequences. If pervasive transcription is also found in bigger organelle genomes (>105 kb and across a broader range of eukaryotes, this could indicate that noncoding organelle RNAs are regulating fundamental processes within eukaryotic cells.

Genome-Wide Association Uncovers Shared Genetic Effects Among Personality Traits and Mood States

NARCIS (Netherlands)

Luciano, Michelle; Huffman, Jennifer E.; Arias-Vásquez, Alejandro; Vinkhuyzen, Anna A. E.; Middeldorp, Christel M.; Giegling, Ina; Payton, Antony; Davies, Gail; Zgaga, Lina; Janzing, Joost; Ke, Xiayi; Galesloot, Tessel; Hartmann, Annette M.; Ollier, William; Tenesa, Albert; Hayward, Caroline; Verhagen, Maaike; Montgomery, Grant W.; Hottenga, Jouke-Jan; Konte, Bettina; Starr, John M.; Vitart, Veronique; Vos, Pieter E.; Madden, Pamela A. F.; Willemsen, Gonneke; Konnerth, Heike; Horan, Michael A.; Porteous, David J.; Campbell, Harry; Vermeulen, Sita H.; Heath, Andrew C.; Wright, Alan; Polasek, Ozren; Kovacevic, Sanja B.; Hastie, Nicholas D.; Franke, Barbara; Boomsma, Dorret I.; Martin, Nicholas G.; Rujescu, Dan; Wilson, James F.; Buitelaar, Jan; Pendleton, Neil; Rudan, Igor; Deary, Ian J.

2012-01-01

Measures of personality and psychological distress are correlated and exhibit genetic covariance. We conducted univariate genome-wide SNP (similar to 2.5 million) and gene-based association analyses of these traits and examined the overlap in results across traits, including a prediction analysis of

Genome-wide association study identifies five new schizophrenia loci.

LENUS (Irish Health Repository)

Ripke, Stephan

2011-10-01

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

Genome-wide association analysis accounting for environmental factors through propensity-score matching: application to stressful live events in major depressive disorder.

Science.gov (United States)

Power, Robert A; Cohen-Woods, Sarah; Ng, Mandy Y; Butler, Amy W; Craddock, Nick; Korszun, Ania; Jones, Lisa; Jones, Ian; Gill, Michael; Rice, John P; Maier, Wolfgang; Zobel, Astrid; Mors, Ole; Placentino, Anna; Rietschel, Marcella; Aitchison, Katherine J; Tozzi, Federica; Muglia, Pierandrea; Breen, Gerome; Farmer, Anne E; McGuffin, Peter; Lewis, Cathryn M; Uher, Rudolf

2013-09-01

Stressful life events are an established trigger for depression and may contribute to the heterogeneity within genome-wide association analyses. With depression cases showing an excess of exposure to stressful events compared to controls, there is difficulty in distinguishing between "true" cases and a "normal" response to a stressful environment. This potential contamination of cases, and that from genetically at risk controls that have not yet experienced environmental triggers for onset, may reduce the power of studies to detect causal variants. In the RADIANT sample of 3,690 European individuals, we used propensity score matching to pair cases and controls on exposure to stressful life events. In 805 case-control pairs matched on stressful life event, we tested the influence of 457,670 common genetic variants on the propensity to depression under comparable level of adversity with a sign test. While this analysis produced no significant findings after genome-wide correction for multiple testing, we outline a novel methodology and perspective for providing environmental context in genetic studies. We recommend contextualizing depression by incorporating environmental exposure into genome-wide analyses as a complementary approach to testing gene-environment interactions. Possible explanations for negative findings include a lack of statistical power due to small sample size and conditional effects, resulting from the low rate of adequate matching. Our findings underscore the importance of collecting information on environmental risk factors in studies of depression and other complex phenotypes, so that sufficient sample sizes are available to investigate their effect in genome-wide association analysis. Copyright © 2013 Wiley Periodicals, Inc.

FGWAS: Functional genome wide association analysis.

Science.gov (United States)

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.

High performance computing enabling exhaustive analysis of higher order single nucleotide polymorphism interaction in Genome Wide Association Studies.

Science.gov (United States)

Goudey, Benjamin; Abedini, Mani; Hopper, John L; Inouye, Michael; Makalic, Enes; Schmidt, Daniel F; Wagner, John; Zhou, Zeyu; Zobel, Justin; Reumann, Matthias

2015-01-01

Genome-wide association studies (GWAS) are a common approach for systematic discovery of single nucleotide polymorphisms (SNPs) which are associated with a given disease. Univariate analysis approaches commonly employed may miss important SNP associations that only appear through multivariate analysis in complex diseases. However, multivariate SNP analysis is currently limited by its inherent computational complexity. In this work, we present a computational framework that harnesses supercomputers. Based on our results, we estimate a three-way interaction analysis on 1.1 million SNP GWAS data requiring over 5.8 years on the full "Avoca" IBM Blue Gene/Q installation at the Victorian Life Sciences Computation Initiative. This is hundreds of times faster than estimates for other CPU based methods and four times faster than runtimes estimated for GPU methods, indicating how the improvement in the level of hardware applied to interaction analysis may alter the types of analysis that can be performed. Furthermore, the same analysis would take under 3 months on the currently largest IBM Blue Gene/Q supercomputer "Sequoia" at the Lawrence Livermore National Laboratory assuming linear scaling is maintained as our results suggest. Given that the implementation used in this study can be further optimised, this runtime means it is becoming feasible to carry out exhaustive analysis of higher order interaction studies on large modern GWAS.

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

Revisiting the classification of curtoviruses based on genome-wide pairwise identity

KAUST Repository

Varsani, Arvind; Martin, Darren Patrick; Navas-Castillo, Jesú s; Moriones, Enrique; Herná ndez-Zepeda, Cecilia; Idris, Ali; Murilo Zerbini, F.; Brown, Judith K.

2014-01-01

Members of the genus Curtovirus (family Geminiviridae) are important pathogens of many wild and cultivated plant species. Until recently, relatively few full curtovirus genomes have been characterised. However, with the 19 full genome sequences now available in public databases, we revisit the proposed curtovirus species and strain classification criteria. Using pairwise identities coupled with phylogenetic evidence, revised species and strain demarcation guidelines have been instituted. Specifically, we have established 77% genome-wide pairwise identity as a species demarcation threshold and 94% genome-wide pairwise identity as a strain demarcation threshold. Hence, whereas curtovirus sequences with >77% genome-wide pairwise identity would be classified as belonging to the same species, those sharing >94% identity would be classified as belonging to the same strain. We provide step-by-step guidelines to facilitate the classification of newly discovered curtovirus full genome sequences and a set of defined criteria for naming new species and strains. The revision yields three curtovirus species: Beet curly top virus (BCTV), Spinach severe surly top virus (SpSCTV) and Horseradish curly top virus (HrCTV). © 2014 Springer-Verlag Wien.

Revisiting the classification of curtoviruses based on genome-wide pairwise identity

KAUST Repository

Varsani, Arvind

2014-01-25

Members of the genus Curtovirus (family Geminiviridae) are important pathogens of many wild and cultivated plant species. Until recently, relatively few full curtovirus genomes have been characterised. However, with the 19 full genome sequences now available in public databases, we revisit the proposed curtovirus species and strain classification criteria. Using pairwise identities coupled with phylogenetic evidence, revised species and strain demarcation guidelines have been instituted. Specifically, we have established 77% genome-wide pairwise identity as a species demarcation threshold and 94% genome-wide pairwise identity as a strain demarcation threshold. Hence, whereas curtovirus sequences with >77% genome-wide pairwise identity would be classified as belonging to the same species, those sharing >94% identity would be classified as belonging to the same strain. We provide step-by-step guidelines to facilitate the classification of newly discovered curtovirus full genome sequences and a set of defined criteria for naming new species and strains. The revision yields three curtovirus species: Beet curly top virus (BCTV), Spinach severe surly top virus (SpSCTV) and Horseradish curly top virus (HrCTV). © 2014 Springer-Verlag Wien.

Pervasive, Genome-Wide Transcription in the Organelle Genomes of Diverse Plastid-Bearing Protists.

Science.gov (United States)

Sanitá Lima, Matheus; Smith, David Roy

2017-11-06

Organelle genomes are among the most sequenced kinds of chromosome. This is largely because they are small and widely used in molecular studies, but also because next-generation sequencing technologies made sequencing easier, faster, and cheaper. However, studies of organelle RNA have not kept pace with those of DNA, despite huge amounts of freely available eukaryotic RNA-sequencing (RNA-seq) data. Little is known about organelle transcription in nonmodel species, and most of the available eukaryotic RNA-seq data have not been mined for organelle transcripts. Here, we use publicly available RNA-seq experiments to investigate organelle transcription in 30 diverse plastid-bearing protists with varying organelle genomic architectures. Mapping RNA-seq data to organelle genomes revealed pervasive, genome-wide transcription, regardless of the taxonomic grouping, gene organization, or noncoding content. For every species analyzed, transcripts covered ≥85% of the mitochondrial and/or plastid genomes (all of which were ≤105 kb), indicating that most of the organelle DNA-coding and noncoding-is transcriptionally active. These results follow earlier studies of model species showing that organellar transcription is coupled and ubiquitous across the genome, requiring significant downstream processing of polycistronic transcripts. Our findings suggest that noncoding organelle DNA can be transcriptionally active, raising questions about the underlying function of these transcripts and underscoring the utility of publicly available RNA-seq data for recovering complete genome sequences. If pervasive transcription is also found in bigger organelle genomes (>105 kb) and across a broader range of eukaryotes, this could indicate that noncoding organelle RNAs are regulating fundamental processes within eukaryotic cells. Copyright © 2017 Sanitá Lima and Smith.

Genome-Wide Association Study of Intelligence: Additive Effects of Novel Brain Expressed Genes

Science.gov (United States)

Loo, Sandra K.; Shtir, Corina; Doyle, Alysa E.; Mick, Eric; McGough, James J.; McCracken, James; Biederman, Joseph; Smalley, Susan L.; Cantor, Rita M.; Faraone, Stephen V.; Nelson, Stanley F.

2012-01-01

Objective: The purpose of the present study was to identify common genetic variants that are associated with human intelligence or general cognitive ability. Method: We performed a genome-wide association analysis with a dense set of 1 million single-nucleotide polymorphisms (SNPs) and quantitative intelligence scores within an ancestrally…

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 ...

Optimization and quality control of genome-wide Hi-C library preparation.

Science.gov (United States)

Zhang, Xiang-Yuan; He, Chao; Ye, Bing-Yu; Xie, De-Jian; Shi, Ming-Lei; Zhang, Yan; Shen, Wen-Long; Li, Ping; Zhao, Zhi-Hu

2017-09-20

Highest-throughput chromosome conformation capture (Hi-C) is one of the key assays for genome- wide chromatin interaction studies. It is a time-consuming process that involves many steps and many different kinds of reagents, consumables, and equipments. At present, the reproducibility is unsatisfactory. By optimizing the key steps of the Hi-C experiment, such as crosslinking, pretreatment of digestion, inactivation of restriction enzyme, and in situ ligation etc., we established a robust Hi-C procedure and prepared two biological replicates of Hi-C libraries from the GM12878 cells. After preliminary quality control by Sanger sequencing, the two replicates were high-throughput sequenced. The bioinformatics analysis of the raw sequencing data revealed the mapping-ability and pair-mate rate of the raw data were around 90% and 72%, respectively. Additionally, after removal of self-circular ligations and dangling-end products, more than 96% of the valid pairs were reached. Genome-wide interactome profiling shows clear topological associated domains (TADs), which is consistent with previous reports. Further correlation analysis showed that the two biological replicates strongly correlate with each other in terms of both bin coverage and all bin pairs. All these results indicated that the optimized Hi-C procedure is robust and stable, which will be very helpful for the wide applications of the Hi-C assay.

Genome-wide association study of smoking initiation and current smoking

DEFF Research Database (Denmark)

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

2009-01-01

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

A genome-wide association study of aging.

Science.gov (United States)

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

2011-11-01

Human longevity and healthy aging show moderate heritability (20%-50%). We conducted a meta-analysis of genome-wide association studies from 9 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium for 2 outcomes: (1) all-cause mortality, and (2) survival free of major disease or death. No single nucleotide polymorphism (SNP) was a genome-wide significant predictor of either outcome (p < 5 × 10(-8)). We found 14 independent SNPs that predicted risk of death, and 8 SNPs that predicted event-free survival (p < 10(-5)). These SNPs are in or near genes that are highly expressed in the brain (HECW2, HIP1, BIN2, GRIA1), genes involved in neural development and function (KCNQ4, LMO4, GRIA1, NETO1) and autophagy (ATG4C), and genes that are associated with risk of various diseases including cancer and Alzheimer's disease. In addition to considerable overlap between the traits, pathway and network analysis corroborated these findings. These findings indicate that variation in genes involved in neurological processes may be an important factor in regulating aging free of major disease and achieving longevity. Copyright © 2011 Elsevier Inc. All rights reserved.

Gigwa-Genotype investigator for genome-wide analyses.

Science.gov (United States)

Sempéré, Guilhem; Philippe, Florian; Dereeper, Alexis; Ruiz, Manuel; Sarah, Gautier; Larmande, Pierre

2016-06-06

Exploring the structure of genomes and analyzing their evolution is essential to understanding the ecological adaptation of organisms. However, with the large amounts of data being produced by next-generation sequencing, computational challenges arise in terms of storage, search, sharing, analysis and visualization. This is particularly true with regards to studies of genomic variation, which are currently lacking scalable and user-friendly data exploration solutions. Here we present Gigwa, a web-based tool that provides an easy and intuitive way to explore large amounts of genotyping data by filtering it not only on the basis of variant features, including functional annotations, but also on genotype patterns. The data storage relies on MongoDB, which offers good scalability properties. Gigwa can handle multiple databases and may be deployed in either single- or multi-user mode. In addition, it provides a wide range of popular export formats. The Gigwa application is suitable for managing large amounts of genomic variation data. Its user-friendly web interface makes such processing widely accessible. It can either be simply deployed on a workstation or be used to provide a shared data portal for a given community of researchers.

Comprehensive evaluation of genome-wide 5-hydroxymethylcytosine profiling approaches in human DNA.

Science.gov (United States)

Skvortsova, Ksenia; Zotenko, Elena; Luu, Phuc-Loi; Gould, Cathryn M; Nair, Shalima S; Clark, Susan J; Stirzaker, Clare

2017-01-01

The discovery that 5-methylcytosine (5mC) can be oxidized to 5-hydroxymethylcytosine (5hmC) by the ten-eleven translocation (TET) proteins has prompted wide interest in the potential role of 5hmC in reshaping the mammalian DNA methylation landscape. The gold-standard bisulphite conversion technologies to study DNA methylation do not distinguish between 5mC and 5hmC. However, new approaches to mapping 5hmC genome-wide have advanced rapidly, although it is unclear how the different methods compare in accurately calling 5hmC. In this study, we provide a comparative analysis on brain DNA using three 5hmC genome-wide approaches, namely whole-genome bisulphite/oxidative bisulphite sequencing (WG Bis/OxBis-seq), Infinium HumanMethylation450 BeadChip arrays coupled with oxidative bisulphite (HM450K Bis/OxBis) and antibody-based immunoprecipitation and sequencing of hydroxymethylated DNA (hMeDIP-seq). We also perform loci-specific TET-assisted bisulphite sequencing (TAB-seq) for validation of candidate regions. We show that whole-genome single-base resolution approaches are advantaged in providing precise 5hmC values but require high sequencing depth to accurately measure 5hmC, as this modification is commonly in low abundance in mammalian cells. HM450K arrays coupled with oxidative bisulphite provide a cost-effective representation of 5hmC distribution, at CpG sites with 5hmC levels >~10%. However, 5hmC analysis is restricted to the genomic location of the probes, which is an important consideration as 5hmC modification is commonly enriched at enhancer elements. Finally, we show that the widely used hMeDIP-seq method provides an efficient genome-wide profile of 5hmC and shows high correlation with WG Bis/OxBis-seq 5hmC distribution in brain DNA. However, in cell line DNA with low levels of 5hmC, hMeDIP-seq-enriched regions are not detected by WG Bis/OxBis or HM450K, either suggesting misinterpretation of 5hmC calls by hMeDIP or lack of sensitivity of the latter methods. We

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

Directory of Open Access Journals (Sweden)

Down Thomas A

2010-09-01

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

Genome-wide identification of significant aberrations in cancer genome.

Science.gov (United States)

Yuan, Xiguo; Yu, Guoqiang; Hou, Xuchu; Shih, Ie-Ming; Clarke, Robert; Zhang, Junying; Hoffman, Eric P; Wang, Roger R; Zhang, Zhen; Wang, Yue

2012-07-27

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

LD Score regression distinguishes confounding from polygenicity in genome-wide association studies

DEFF Research Database (Denmark)

Bulik-Sullivan, Brendan K.; Loh, Po-Ru; Finucane, Hilary K.

2015-01-01

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from...

GenoGAM: genome-wide generalized additive models for ChIP-Seq analysis.

Science.gov (United States)

Stricker, Georg; Engelhardt, Alexander; Schulz, Daniel; Schmid, Matthias; Tresch, Achim; Gagneur, Julien

2017-08-01

Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is a widely used approach to study protein-DNA interactions. Often, the quantities of interest are the differential occupancies relative to controls, between genetic backgrounds, treatments, or combinations thereof. Current methods for differential occupancy of ChIP-Seq data rely however on binning or sliding window techniques, for which the choice of the window and bin sizes are subjective. Here, we present GenoGAM (Genome-wide Generalized Additive Model), which brings the well-established and flexible generalized additive models framework to genomic applications using a data parallelism strategy. We model ChIP-Seq read count frequencies as products of smooth functions along chromosomes. Smoothing parameters are objectively estimated from the data by cross-validation, eliminating ad hoc binning and windowing needed by current approaches. GenoGAM provides base-level and region-level significance testing for full factorial designs. Application to a ChIP-Seq dataset in yeast showed increased sensitivity over existing differential occupancy methods while controlling for type I error rate. By analyzing a set of DNA methylation data and illustrating an extension to a peak caller, we further demonstrate the potential of GenoGAM as a generic statistical modeling tool for genome-wide assays. Software is available from Bioconductor: https://www.bioconductor.org/packages/release/bioc/html/GenoGAM.html . gagneur@in.tum.de. Supplementary information is available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Genomics for public health improvement: relevant international ethical and policy issues around genome-wide association studies and biobanks.

Science.gov (United States)

Pang, T

2013-01-01

Genome-wide association studies and biobanks are at the forefront of genomics research and possess unprecedented potential to improve public health. However, for public health genomics to ultimately fulfill its potential, technological and scientific advances alone are insufficient. Scientists, ethicists, policy makers, and regulators must work closely together with research participants and communities in order to craft an equitable and just ethical framework, and a sustainable environment for effective policies. Such a framework should be a 'hybrid' form which balances equity and solidarity with entrepreneurship and scientific advances. A good balance between research and policy on one hand, and privacy, protection and trust on the other is the key for public health improvement based on advances in genomics science. Copyright © 2013 S. Karger AG, Basel.

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

Science.gov (United States)

Yu, Xijiang; Meuwissen, Theo H E

2011-11-01

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

Genome-wide association study of Tourette's syndrome

NARCIS (Netherlands)

Scharf, J. M.; Yu, D.; Mathews, C. A.; Neale, B. M.; Stewart, S. E.; Fagerness, J. A.; Evans, P.; Gamazon, E.; Edlund, C. K.; Service, S. K.; Tikhomirov, A.; Osiecki, L.; Illmann, C.; Pluzhnikov, A.; Konkashbaev, A.; Davis, L. K.; Han, B.; Crane, J.; Moorjani, P.; Crenshaw, A. T.; Parkin, M. A.; Reus, V. I.; Lowe, T. L.; Rangel-Lugo, M.; Chouinard, S.; Dion, Y.; Girard, S.; Cath, D. C.; Smit, J. H.; King, R. A.; Fernandez, T. V.; Leckman, J. F.; Kidd, K. K.; Kidd, J. R.; Pakstis, A. J.; State, M. W.; Herrera, L. D.; Romero, R.; Fournier, E.; Sandor, P.; Barr, C. L.; Phan, N.; Gross-Tsur, V.; Benarroch, F.; Pollak, Y.; Budman, C. L.; Bruun, R. D.; Erenberg, G.; Naarden, A. L.; Hoekstra, P. J.

2013-01-01

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

Statistical power of model selection strategies for genome-wide association studies.

Directory of Open Access Journals (Sweden)

Zheyang Wu

2009-07-01

Full Text Available Genome-wide association studies (GWAS aim to identify genetic variants related to diseases by examining the associations between phenotypes and hundreds of thousands of genotyped markers. Because many genes are potentially involved in common diseases and a large number of markers are analyzed, it is crucial to devise an effective strategy to identify truly associated variants that have individual and/or interactive effects, while controlling false positives at the desired level. Although a number of model selection methods have been proposed in the literature, including marginal search, exhaustive search, and forward search, their relative performance has only been evaluated through limited simulations due to the lack of an analytical approach to calculating the power of these methods. This article develops a novel statistical approach for power calculation, derives accurate formulas for the power of different model selection strategies, and then uses the formulas to evaluate and compare these strategies in genetic model spaces. In contrast to previous studies, our theoretical framework allows for random genotypes, correlations among test statistics, and a false-positive control based on GWAS practice. After the accuracy of our analytical results is validated through simulations, they are utilized to systematically evaluate and compare the performance of these strategies in a wide class of genetic models. For a specific genetic model, our results clearly reveal how different factors, such as effect size, allele frequency, and interaction, jointly affect the statistical power of each strategy. An example is provided for the application of our approach to empirical research. The statistical approach used in our derivations is general and can be employed to address the model selection problems in other random predictor settings. We have developed an R package markerSearchPower to implement our formulas, which can be downloaded from the

High-resolution genetic map for understanding the effect of genome-wide recombination rate on nucleotide diversity in watermelon.

Science.gov (United States)

Reddy, Umesh K; Nimmakayala, Padma; Levi, Amnon; Abburi, Venkata Lakshmi; Saminathan, Thangasamy; Tomason, Yan R; Vajja, Gopinath; Reddy, Rishi; Abburi, Lavanya; Wehner, Todd C; Ronin, Yefim; Karol, Abraham

2014-09-15

We used genotyping by sequencing to identify a set of 10,480 single nucleotide polymorphism (SNP) markers for constructing a high-resolution genetic map of 1096 cM for watermelon. We assessed the genome-wide variation in recombination rate (GWRR) across the map and found an association between GWRR and genome-wide nucleotide diversity. Collinearity between the map and the genome-wide reference sequence for watermelon was studied to identify inconsistency and chromosome rearrangements. We assessed genome-wide nucleotide diversity, linkage disequilibrium (LD), and selective sweep for wild, semi-wild, and domesticated accessions of Citrullus lanatus var. lanatus to track signals of domestication. Principal component analysis combined with chromosome-wide phylogenetic study based on 1563 SNPs obtained after LD pruning with minor allele frequency of 0.05 resolved the differences between semi-wild and wild accessions as well as relationships among worldwide sweet watermelon. Population structure analysis revealed predominant ancestries for wild, semi-wild, and domesticated watermelons as well as admixture of various ancestries that were important for domestication. Sliding window analysis of Tajima's D across various chromosomes was used to resolve selective sweep. LD decay was estimated for various chromosomes. We identified a strong selective sweep on chromosome 3 consisting of important genes that might have had a role in sweet watermelon domestication. Copyright © 2014 Reddy et al.

Genome-wide linkage analysis for human longevity

DEFF Research Database (Denmark)

Beekman, Marian; Blanché, Hélène; Perola, Markus

2013-01-01

Clear evidence exists for heritability of human longevity, and much interest is focused on identifying genes associated with longer lives. To identify such longevity alleles, we performed the largest genome-wide linkage scan thus far reported. Linkage analyses included 2118 nonagenarian Caucasian...

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

Science.gov (United States)

Biazzi, Elisa; Nazzicari, Nelson; Pecetti, Luciano; Brummer, E Charles; Palmonari, Alberto; Tava, Aldo; Annicchiarico, Paolo

2017-01-01

Genetic progress for forage quality has been poor in alfalfa (Medicago sativa L.), the most-grown forage legume worldwide. This study aimed at exploring opportunities for marker-assisted selection (MAS) and genomic selection of forage quality traits based on breeding values of parent plants. Some 154 genotypes from a broadly-based reference population were genotyped by genotyping-by-sequencing (GBS), and phenotyped for leaf-to-stem ratio, leaf and stem contents of protein, neutral detergent fiber (NDF) and acid detergent lignin (ADL), and leaf and stem NDF digestibility after 24 hours (NDFD), of their dense-planted half-sib progenies in three growing conditions (summer harvest, full irrigation; summer harvest, suspended irrigation; autumn harvest). Trait-marker analyses were performed on progeny values averaged over conditions, owing to modest germplasm × condition interaction. Genomic selection exploited 11,450 polymorphic SNP markers, whereas a subset of 8,494 M. truncatula-aligned markers were used for a genome-wide association study (GWAS). GWAS confirmed the polygenic control of quality traits and, in agreement with phenotypic correlations, indicated substantially different genetic control of a given trait in stems and leaves. It detected several SNPs in different annotated genes that were highly linked to stem protein content. Also, it identified a small genomic region on chromosome 8 with high concentration of annotated genes associated with leaf ADL, including one gene probably involved in the lignin pathway. Three genomic selection models, i.e., Ridge-regression BLUP, Bayes B and Bayesian Lasso, displayed similar prediction accuracy, whereas SVR-lin was less accurate. Accuracy values were moderate (0.3-0.4) for stem NDFD and leaf protein content, modest for leaf ADL and NDFD, and low to very low for the other traits. Along with previous results for the same germplasm set, this study indicates that GBS data can be exploited to improve both quality traits

Genome-wide comparative analysis of four Indian Drosophila species.

Science.gov (United States)

Mohanty, Sujata; Khanna, Radhika

2017-12-01

Comparative analysis of multiple genomes of closely or distantly related Drosophila species undoubtedly creates excitement among evolutionary biologists in exploring the genomic changes with an ecology and evolutionary perspective. We present herewith the de novo assembled whole genome sequences of four Drosophila species, D. bipectinata, D. takahashii, D. biarmipes and D. nasuta of Indian origin using Next Generation Sequencing technology on an Illumina platform along with their detailed assembly statistics. The comparative genomics analysis, e.g. gene predictions and annotations, functional and orthogroup analysis of coding sequences and genome wide SNP distribution were performed. The whole genome of Zaprionus indianus of Indian origin published earlier by us and the genome sequences of previously sequenced 12 Drosophila species available in the NCBI database were included in the analysis. The present work is a part of our ongoing genomics project of Indian Drosophila species.

Genome-wide association studies (GWAS) of adiposity

DEFF Research Database (Denmark)

Oskari Kilpeläinen, Tuomas; Ingelsson, Erik

2016-01-01

Adiposity is strongly heritable and one of the leading risk factors for type 2 diabetes, cardiovascular disease, cancer, and premature death. In the past 8 years, genome-wide association studies (GWAS) have greatly increased our understanding of the genes and biological pathways that regulate...

Meta-analysis of Genome-Wide Association Studies for Extraversion

DEFF Research Database (Denmark)

van den Berg, Stéphanie M; de Moor, Marleen H M; Verweij, K. J. H.

2016-01-01

small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found...... at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero...

Genome-wide investigation reveals high evolutionary rates in annual model plants.

Science.gov (United States)

Yue, Jia-Xing; Li, Jinpeng; Wang, Dan; Araki, Hitoshi; Tian, Dacheng; Yang, Sihai

2010-11-09

Rates of molecular evolution vary widely among species. While significant deviations from molecular clock have been found in many taxa, effects of life histories on molecular evolution are not fully understood. In plants, annual/perennial life history traits have long been suspected to influence the evolutionary rates at the molecular level. To date, however, the number of genes investigated on this subject is limited and the conclusions are mixed. To evaluate the possible heterogeneity in evolutionary rates between annual and perennial plants at the genomic level, we investigated 85 nuclear housekeeping genes, 10 non-housekeeping families, and 34 chloroplast genes using the genomic data from model plants including Arabidopsis thaliana and Medicago truncatula for annuals and grape (Vitis vinifera) and popular (Populus trichocarpa) for perennials. According to the cross-comparisons among the four species, 74-82% of the nuclear genes and 71-97% of the chloroplast genes suggested higher rates of molecular evolution in the two annuals than those in the two perennials. The significant heterogeneity in evolutionary rate between annuals and perennials was consistently found both in nonsynonymous sites and synonymous sites. While a linear correlation of evolutionary rates in orthologous genes between species was observed in nonsynonymous sites, the correlation was weak or invisible in synonymous sites. This tendency was clearer in nuclear genes than in chloroplast genes, in which the overall evolutionary rate was small. The slope of the regression line was consistently lower than unity, further confirming the higher evolutionary rate in annuals at the genomic level. The higher evolutionary rate in annuals than in perennials appears to be a universal phenomenon both in nuclear and chloroplast genomes in the four dicot model plants we investigated. Therefore, such heterogeneity in evolutionary rate should result from factors that have genome-wide influence, most likely those

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....

An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

DEFF Research Database (Denmark)

Scott, Robert A; Scott, Laura J; Mägi, Reedik

2017-01-01

To characterise type 2 diabetes (T2D) associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D cases and 132,532 controls of European ancestry after imputation using the 1000 Genomes multi-ethnic reference panel. Promi...... secretion, and in adipocytes, monocytes and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology....

Genome-wide Association Study for Calving Traits in Danish and Swedish Holstein Cattle

DEFF Research Database (Denmark)

Sahana, Goutam; Guldbrandtsen, Bernt; Lund, Mogens Sandø

2011-01-01

A total of 22 quantitative trait loci (QTL) were detected on 19 chromosomes for direct and maternal calving traits in cattle using a genome-wide association study. Calving performance is affected by the genotypes of both the calf (direct effect) and dam (maternal effect). To identify the QTL cont...

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.

NSD1 mutations generate a genome-wide DNA methylation signature.

LENUS (Irish Health Repository)

Choufani, S

2015-12-22

Sotos syndrome (SS) represents an important human model system for the study of epigenetic regulation; it is an overgrowth\\/intellectual disability syndrome caused by mutations in a histone methyltransferase, NSD1. As layered epigenetic modifications are often interdependent, we propose that pathogenic NSD1 mutations have a genome-wide impact on the most stable epigenetic mark, DNA methylation (DNAm). By interrogating DNAm in SS patients, we identify a genome-wide, highly significant NSD1(+\\/-)-specific signature that differentiates pathogenic NSD1 mutations from controls, benign NSD1 variants and the clinically overlapping Weaver syndrome. Validation studies of independent cohorts of SS and controls assigned 100% of these samples correctly. This highly specific and sensitive NSD1(+\\/-) signature encompasses genes that function in cellular morphogenesis and neuronal differentiation, reflecting cardinal features of the SS phenotype. The identification of SS-specific genome-wide DNAm alterations will facilitate both the elucidation of the molecular pathophysiology of SS and the development of improved diagnostic testing.

Genome-wide identification of significant aberrations in cancer genome

Directory of Open Access Journals (Sweden)

Yuan Xiguo

2012-07-01

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

Meta-analysis and genome-wide interpretation of genetic susceptibility to drug addiction

Science.gov (United States)

2011-01-01

Background Classical genetic studies provide strong evidence for heritable contributions to susceptibility to developing dependence on addictive substances. Candidate gene and genome-wide association studies (GWAS) have sought genes, chromosomal regions and allelic variants likely to contribute to susceptibility to drug addiction. Results Here, we performed a meta-analysis of addiction candidate gene association studies and GWAS to investigate possible functional mechanisms associated with addiction susceptibility. From meta-data retrieved from 212 publications on candidate gene association studies and 5 GWAS reports, we linked a total of 843 haplotypes to addiction susceptibility. We mapped the SNPs in these haplotypes to functional and regulatory elements in the genome and estimated the magnitude of the contributions of different molecular mechanisms to their effects on addiction susceptibility. In addition to SNPs in coding regions, these data suggest that haplotypes in gene regulatory regions may also contribute to addiction susceptibility. When we compared the lists of genes identified by association studies and those identified by molecular biological studies of drug-regulated genes, we observed significantly higher participation in the same gene interaction networks than expected by chance, despite little overlap between the two gene lists. Conclusions These results appear to offer new insights into the genetic factors underlying drug addiction. PMID:21999673

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

DEFF Research Database (Denmark)

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

2015-01-01

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

Genome-wide divergence, haplotype distribution and population demographic histories for Gossypium hirsutum and Gossypium barbadense as revealed by genome-anchored SNPs

Science.gov (United States)

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

A human genome-wide loss-of-function screen identifies effective chikungunya antiviral drugs.

Science.gov (United States)

Karlas, Alexander; Berre, Stefano; Couderc, Thérèse; Varjak, Margus; Braun, Peter; Meyer, Michael; Gangneux, Nicolas; Karo-Astover, Liis; Weege, Friderike; Raftery, Martin; Schönrich, Günther; Klemm, Uwe; Wurzlbauer, Anne; Bracher, Franz; Merits, Andres; Meyer, Thomas F; Lecuit, Marc

2016-05-12

Chikungunya virus (CHIKV) is a globally spreading alphavirus against which there is no commercially available vaccine or therapy. Here we use a genome-wide siRNA screen to identify 156 proviral and 41 antiviral host factors affecting CHIKV replication. We analyse the cellular pathways in which human proviral genes are involved and identify druggable targets. Twenty-one small-molecule inhibitors, some of which are FDA approved, targeting six proviral factors or pathways, have high antiviral activity in vitro, with low toxicity. Three identified inhibitors have prophylactic antiviral effects in mouse models of chikungunya infection. Two of them, the calmodulin inhibitor pimozide and the fatty acid synthesis inhibitor TOFA, have a therapeutic effect in vivo when combined. These results demonstrate the value of loss-of-function screening and pathway analysis for the rational identification of small molecules with therapeutic potential and pave the way for the development of new, host-directed, antiviral agents.

Genome-wide association study of Tourette Syndrome

Science.gov (United States)

Scharf, Jeremiah M.; Yu, Dongmei; Mathews, Carol A.; Neale, Benjamin M.; Stewart, S. Evelyn; Fagerness, Jesen A; Evans, Patrick; Gamazon, Eric; Edlund, Christopher K.; Service, Susan; Tikhomirov, Anna; Osiecki, Lisa; Illmann, Cornelia; Pluzhnikov, Anna; Konkashbaev, Anuar; Davis, Lea K; Han, Buhm; Crane, Jacquelyn; Moorjani, Priya; Crenshaw, Andrew T.; Parkin, Melissa A.; Reus, Victor I.; Lowe, Thomas L.; Rangel-Lugo, Martha; Chouinard, Sylvain; Dion, Yves; Girard, Simon; Cath, Danielle C; Smit, Jan H; King, Robert A.; Fernandez, Thomas; Leckman, James F.; Kidd, Kenneth K.; Kidd, Judith R.; Pakstis, Andrew J.; State, Matthew; Herrera, Luis Diego; Romero, Roxana; Fournier, Eduardo; Sandor, Paul; Barr, Cathy L; Phan, Nam; Gross-Tsur, Varda; Benarroch, Fortu; Pollak, Yehuda; Budman, Cathy L.; Bruun, Ruth D.; Erenberg, Gerald; Naarden, Allan L; Lee, Paul C; Weiss, Nicholas; Kremeyer, Barbara; Berrío, Gabriel Bedoya; Campbell, Desmond; Silgado, Julio C. Cardona; Ochoa, William Cornejo; Restrepo, Sandra C. Mesa; Muller, Heike; Duarte, Ana V. Valencia; Lyon, Gholson J; Leppert, Mark; Morgan, Jubel; Weiss, Robert; Grados, Marco A.; Anderson, Kelley; Davarya, Sarah; Singer, Harvey; Walkup, John; Jankovic, Joseph; Tischfield, Jay A.; Heiman, Gary A.; Gilbert, Donald L.; Hoekstra, Pieter J.; Robertson, Mary M.; Kurlan, Roger; Liu, Chunyu; Gibbs, J. Raphael; Singleton, Andrew; Hardy, John; Strengman, Eric; Ophoff, Roel; Wagner, Michael; Moessner, Rainald; Mirel, Daniel B.; Posthuma, Danielle; Sabatti, Chiara; Eskin, Eleazar; Conti, David V.; Knowles, James A.; Ruiz-Linares, Andres; Rouleau, Guy A.; Purcell, Shaun; Heutink, Peter; Oostra, Ben A.; McMahon, William; Freimer, Nelson; Cox, Nancy J.; Pauls, David L.

2012-01-01

Tourette Syndrome (TS) is a developmental disorder that has one of the highest familial recurrence rates among neuropsychiatric diseases with complex inheritance. However, the identification of definitive TS susceptibility genes remains elusive. Here, we report the first genome-wide association study (GWAS) of TS in 1285 cases and 4964 ancestry-matched controls of European ancestry, including two European-derived population isolates, Ashkenazi Jews from North America and Israel, and French Canadians from Quebec, Canada. In a primary meta-analysis of GWAS data from these European ancestry samples, no markers achieved a genome-wide threshold of significance (p<5 × 10−8); the top signal was found in rs7868992 on chromosome 9q32 within COL27A1 (p=1.85 × 10−6). A secondary analysis including an additional 211 cases and 285 controls from two closely-related Latin-American population isolates from the Central Valley of Costa Rica and Antioquia, Colombia also identified rs7868992 as the top signal (p=3.6 × 10−7 for the combined sample of 1496 cases and 5249 controls following imputation with 1000 Genomes data). This study lays the groundwork for the eventual identification of common TS susceptibility variants in larger cohorts and helps to provide a more complete understanding of the full genetic architecture of this disorder. PMID:22889924

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

Directory of Open Access Journals (Sweden)

Jolly Emmitt R

2005-11-01

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

A Genome-Wide Methylation Study of Severe Vitamin D Deficiency in African American Adolescents

NARCIS (Netherlands)

Zhu, Haidong; Wang, Xiaoling; Shi, Huidong; Su, Shaoyong; Harshfield, Gregory A.; Gutin, Bernard; Snieder, Harold; Dong, Yanbin

Objectives To test the hypothesis that changes in DNA methylation are involved in vitamin D deficiency-related immune cell regulation using an unbiased genome-wide approach combined with a genomic and epigenomic integrative approach. Study design We performed a genome-wide methylation scan using the

Genome-wide association study of the four-constitution medicine.

Science.gov (United States)

Yin, Chang Shik; Park, Hi Joon; Chung, Joo-Ho; Lee, Hye-Jung; Lee, Byung-Cheol

2009-12-01

Four-constitution medicine (FCM), also known as Sasang constitutional medicine, and the heritage of the long history of individualized acupuncture medicine tradition, is one of the holistic and traditional systems of constitution to appraise and categorize individual differences into four major types. This study first reports a genome-wide association study on FCM, to explore the genetic basis of FCM and facilitate the integration of FCM with conventional individual differences research. Healthy individuals of the Korean population were classified into the four constitutional types (FCTs). A total of 353,202 single nucleotide polymorphisms (SNPs) were typed using whole genome amplified samples, and six-way comparison of FCM types provided lists of significantly differential SNPs. In one-to-one FCT comparisons, 15,944 SNPs were significantly differential, and 5 SNPs were commonly significant in all of the three comparisons. In one-to-two FCT comparisons, 22,616 SNPs were significantly differential, and 20 SNPs were commonly significant in all of the three comparison groups. This study presents the association between genome-wide SNP profiles and the categorization of the FCM, and it could further provide a starting point of genome-based identification and research of the constitutions of FCM.

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.

A genome-wide association study of atopic dermatitis identifies loci with overlapping effects on asthma and psoriasis.

Science.gov (United States)

Weidinger, Stephan; Willis-Owen, Saffron A G; Kamatani, Yoichiro; Baurecht, Hansjörg; Morar, Nilesh; Liang, Liming; Edser, Pauline; Street, Teresa; Rodriguez, Elke; O'Regan, Grainne M; Beattie, Paula; Fölster-Holst, Regina; Franke, Andre; Novak, Natalija; Fahy, Caoimhe M; Winge, Mårten C G; Kabesch, Michael; Illig, Thomas; Heath, Simon; Söderhäll, Cilla; Melén, Erik; Pershagen, Göran; Kere, Juha; Bradley, Maria; Lieden, Agne; Nordenskjold, Magnus; Harper, John I; McLean, W H Irwin; Brown, Sara J; Cookson, William O C; Lathrop, G Mark; Irvine, Alan D; Moffatt, Miriam F

2013-12-01

Atopic dermatitis (AD) is the most common dermatological disease of childhood. Many children with AD have asthma and AD shares regions of genetic linkage with psoriasis, another chronic inflammatory skin disease. We present here a genome-wide association study (GWAS) of childhood-onset AD in 1563 European cases with known asthma status and 4054 European controls. Using Illumina genotyping followed by imputation, we generated 268 034 consensus genotypes and in excess of 2 million single nucleotide polymorphisms (SNPs) for analysis. Association signals were assessed for replication in a second panel of 2286 European cases and 3160 European controls. Four loci achieved genome-wide significance for AD and replicated consistently across all cohorts. These included the epidermal differentiation complex (EDC) on chromosome 1, the genomic region proximal to LRRC32 on chromosome 11, the RAD50/IL13 locus on chromosome 5 and the major histocompatibility complex (MHC) on chromosome 6; reflecting action of classical HLA alleles. We observed variation in the contribution towards co-morbid asthma for these regions of association. We further explored the genetic relationship between AD, asthma and psoriasis by examining previously identified susceptibility SNPs for these diseases. We found considerable overlap between AD and psoriasis together with variable coincidence between allergic rhinitis (AR) and asthma. Our results indicate that the pathogenesis of AD incorporates immune and epidermal barrier defects with combinations of specific and overlapping effects at individual loci.

Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology

DEFF Research Database (Denmark)

Rossin, Elizabeth J.; Hansen, Kasper Lage; Raychaudhuri, Soumya

2011-01-01

Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these r......Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed...... in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein-protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more...... that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non...

Data analysis in the post-genome-wide association study era

Directory of Open Access Journals (Sweden)

Qiao-Ling Wang

2016-12-01

Full Text Available Since the first report of a genome-wide association study (GWAS on human age-related macular degeneration, GWAS has successfully been used to discover genetic variants for a variety of complex human diseases and/or traits, and thousands of associated loci have been identified. However, the underlying mechanisms for these loci remain largely unknown. To make these GWAS findings more useful, it is necessary to perform in-depth data mining. The data analysis in the post-GWAS era will include the following aspects: fine-mapping of susceptibility regions to identify susceptibility genes for elucidating the biological mechanism of action; joint analysis of susceptibility genes in different diseases; integration of GWAS, transcriptome, and epigenetic data to analyze expression and methylation quantitative trait loci at the whole-genome level, and find single-nucleotide polymorphisms that influence gene expression and DNA methylation; genome-wide association analysis of disease-related DNA copy number variations. Applying these strategies and methods will serve to strengthen GWAS data to enhance the utility and significance of GWAS in improving understanding of the genetics of complex diseases or traits and translate these findings for clinical applications. Keywords: Genome-wide association study, Data mining, Integrative data analysis, Polymorphism, Copy number variation

Genome-wide selection signatures in Pinzgau cattle

Directory of Open Access Journals (Sweden)

Radovan Kasarda

2015-08-01

Full Text Available The aim of this study was to identify the evidence of recent selection based on estimation of the integrated Haplotype Score (iHS, population differentiation index (FST and characterize affected regions near QTL associated with traits under strong selection in Pinzgau cattle. In total 21 Austrian and 19 Slovak purebreed bulls genotyped with Illumina bovineHD and  bovineSNP50 BeadChip were used to identify genomic regions under selection. Only autosomal loci with call rate higher than 90%, minor allele frequency higher than 0.01 and Hardy-Weinberg equlibrium limit of 0.001 were included in the subsequent analyses of selection sweeps presence. The final dataset was consisted from 30538 SNPs with 81.86 kb average adjacent SNPs spacing. The iHS score were averaged into non-overlapping 500 kb segments across the genome. The FST values were also plotted against genome position based on sliding windows approach and averaged over 8 consecutive SNPs. Based on integrated Haplotype Score evaluation only 7 regions with iHS score higher than 1.7 was found. The average iHS score observed for each adjacent syntenic regions indicated slight effect of recent selection in analysed group of Pinzgau bulls. The level of genetic differentiation between Austrian and Slovak bulls estimated based on FST index was low. Only 24% of FST values calculated for each SNP was greather than 0.01. By using sliding windows approach was found that 5% of analysed windows had higher value than 0.01. Our results indicated use of similar selection scheme in breeding programs of Slovak and Austrian Pinzgau bulls. The evidence for genome-wide association between signatures of selection and regions affecting complex traits such as milk production was insignificant, because the loci in segments identified as affected by selection were very distant from each other. Identification of genomic regions that may be under pressure of selection for phenotypic traits to better understanding of the

Signatures of selection in the Iberian honey bee: a genome wide approach using single nucleotide polymorphisms (SNPs)

OpenAIRE

Chavez-Galarza, Julio; Johnston, J. Spencer; Azevedo, João; Muñoz, Irene; De la Rúa, Pilar; Patton, John C.; Pinto, M. Alice

2011-01-01

Dissecting genome-wide (expansions, contractions, admixture) from genome-specific effects (selection) is a goal of central importance in evolutionary biology because it leads to more robust inferences of demographic history and to identification of adaptive divergence. The publication of the honey bee genome and the development of high-density SNPs genotyping, provide us with powerful tools, allowing us to identify signatures of selection in the honey bee genome. These signatur...

Chapter 10: Mining genome-wide genetic markers.

Directory of Open Access Journals (Sweden)

Xiang Zhang

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

Genome-wide deficiency screen for the genomic regions responsible for heat resistance in Drosophila melanogaster

Directory of Open Access Journals (Sweden)

Teramura Kouhei

2011-06-01

Full Text Available Abstract Background Temperature adaptation is one of the most important determinants of distribution and population size of organisms in nature. Recently, quantitative trait loci (QTL mapping and gene expression profiling approaches have been used for detecting candidate genes for heat resistance. However, the resolution of QTL mapping is not high enough to examine the individual effects of various genes in each QTL. Heat stress-responsive genes, characterized by gene expression profiling studies, are not necessarily responsible for heat resistance. Some of these genes may be regulated in association with the heat stress response of other genes. Results To evaluate which heat-responsive genes are potential candidates for heat resistance with higher resolution than previous QTL mapping studies, we performed genome-wide deficiency screen for QTL for heat resistance. We screened 439 isogenic deficiency strains from the DrosDel project, covering 65.6% of the Drosophila melanogaster genome in order to map QTL for thermal resistance. As a result, we found 19 QTL for heat resistance, including 3 novel QTL outside the QTL found in previous studies. Conclusion The QTL found in this study encompassed 19 heat-responsive genes found in the previous gene expression profiling studies, suggesting that they were strong candidates for heat resistance. This result provides new insights into the genetic architecture of heat resistance. It also emphasizes the advantages of genome-wide deficiency screen using isogenic deficiency libraries.

Genome-wide association analyses of expression phenotypes.

Science.gov (United States)

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.

Genome-wide analysis of tandem repeats in plants and green algae

Science.gov (United States)

Zhixin Zhao; Cheng Guo; Sreeskandarajan Sutharzan; Pei Li; Craig Echt; Jie Zhang; Chun Liang

2014-01-01

Tandem repeats (TRs) extensively exist in the genomes of prokaryotes and eukaryotes. Based on the sequenced genomes and gene annotations of 31 plant and algal species in Phytozome version 8.0 (http://www.phytozome.net/), we examined TRs in a genome-wide scale, characterized their distributions and motif features, and explored their putative biological functions. Among...

AID/APOBEC cytosine deaminase induces genome-wide kataegis

Directory of Open Access Journals (Sweden)

Lada Artem G

2012-12-01

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

Epigenomics of Total Acute Sleep Deprivation in Relation to Genome-Wide DNA Methylation Profiles and RNA Expression

OpenAIRE

Nilsson, Emil K.; Bostr?m, Adrian E.; Mwinyi, Jessica; Schi?th, Helgi B.

2016-01-01

Abstract Despite an established link between sleep deprivation and epigenetic processes in humans, it remains unclear to what extent sleep deprivation modulates DNA methylation. We performed a within-subject randomized blinded study with 16 healthy subjects to examine the effect of one night of total sleep deprivation (TSD) on the genome-wide methylation profile in blood compared with that in normal sleep. Genome-wide differences in methylation between both conditions were assessed by applyin...

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

Science.gov (United States)

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

2000-12-15

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

Genome-wide survey of allele-specific splicing in humans

Directory of Open Access Journals (Sweden)

Scheffler Konrad

2008-06-01

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

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

Science.gov (United States)

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A.; Burgueño, Juan; Pérez-Rodríguez, Paulino; de los Campos, Gustavo

2016-01-01

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects (u) that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model (u) plus an extra component, f, that captures random effects between environments that were not captured by the random effects u. We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u and f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u. PMID:27793970

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

Directory of Open Access Journals (Sweden)

Jaime Cuevas

2017-01-01

Full Text Available The phenomenon of genotype × environment (G × E interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects ( u that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP and Gaussian (Gaussian kernel, GK. The other model has the same genetic component as the first model ( u plus an extra component, f, that captures random effects between environments that were not captured by the random effects u . We used five CIMMYT data sets (one maize and four wheat that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u   and   f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u .

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Sebastian Weiterer

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

Genome-Wide Prediction of the Performance of Three-Way Hybrids in Barley

Directory of Open Access Journals (Sweden)

Zuo Li

2017-03-01

Full Text Available Predicting the grain yield performance of three-way hybrids is challenging. Three-way crosses are relevant for hybrid breeding in barley ( L. and maize ( L. adapted to East Africa. The main goal of our study was to implement and evaluate genome-wide prediction approaches of the performance of three-way hybrids using data of single-cross hybrids for a scenario in which parental lines of the three-way hybrids originate from three genetically distinct subpopulations. We extended the ridge regression best linear unbiased prediction (RRBLUP and devised a genomic selection model allowing for subpopulation-specific marker effects (GSA-RRBLUP: general and subpopulation-specific additive RRBLUP. Using an empirical barley data set, we showed that applying GSA-RRBLUP tripled the prediction ability of three-way hybrids from 0.095 to 0.308 compared with RRBLUP, modeling one additive effect for all three subpopulations. The experimental findings were further substantiated with computer simulations. Our results emphasize the potential of GSA-RRBLUP to improve genome-wide hybrid prediction of three-way hybrids for scenarios of genetically diverse parental populations. Because of the advantages of the GSA-RRBLUP model in dealing with hybrids from different parental populations, it may also be a promising approach to boost the prediction ability for hybrid breeding programs based on genetically diverse heterotic groups.

Genome-wide single nucleotide polymorphisms (SNPs) for a model invasive ascidian Botryllus schlosseri.

Science.gov (United States)

Gao, Yangchun; Li, Shiguo; Zhan, Aibin

2018-04-01

Invasive species cause huge damages to ecology, environment and economy globally. The comprehensive understanding of invasion mechanisms, particularly genetic bases of micro-evolutionary processes responsible for invasion success, is essential for reducing potential damages caused by invasive species. The golden star tunicate, Botryllus schlosseri, has become a model species in invasion biology, mainly owing to its high invasiveness nature and small well-sequenced genome. However, the genome-wide genetic markers have not been well developed in this highly invasive species, thus limiting the comprehensive understanding of genetic mechanisms of invasion success. Using restriction site-associated DNA (RAD) tag sequencing, here we developed a high-quality resource of 14,119 out of 158,821 SNPs for B. schlosseri. These SNPs were relatively evenly distributed at each chromosome. SNP annotations showed that the majority of SNPs (63.20%) were located at intergenic regions, and 21.51% and 14.58% were located at introns and exons, respectively. In addition, the potential use of the developed SNPs for population genomics studies was primarily assessed, such as the estimate of observed heterozygosity (H O ), expected heterozygosity (H E ), nucleotide diversity (π), Wright's inbreeding coefficient (F IS ) and effective population size (Ne). Our developed SNP resource would provide future studies the genome-wide genetic markers for genetic and genomic investigations, such as genetic bases of micro-evolutionary processes responsible for invasion success.

Genome-wide assessment in Escherichia coli reveals time-dependent nanotoxicity paradigms.

Science.gov (United States)

Reyes, Vincent C; Li, Minghua; Hoek, Eric M V; Mahendra, Shaily; Damoiseaux, Robert

2012-11-27

The use of engineered nanomaterials (eNM) in consumer and industrial products is increasing exponentially. Our ability to rapidly assess their potential effects on human and environmental health is limited by our understanding of nanomediated toxicity. High-throughput screening (HTS) enables the investigation of nanomediated toxicity on a genome-wide level, thus uncovering their novel mechanisms and paradigms. Herein, we investigate the toxicity of zinc-containing nanomaterials (Zn-eNMs) using a time-resolved HTS methodology in an arrayed Escherichia coli genome-wide knockout (KO) library. The library was screened against nanoscale zerovalent zinc (nZn), nanoscale zinc oxide (nZnO), and zinc chloride (ZnCl(2)) salt as reference. Through sequential screening over 24 h, our method identified 173 sensitive clones from diverse biological pathways, which fell into two general groups: early and late responders. The overlap between these groups was small. Our results suggest that bacterial toxicity mechanisms change from pathways related to general metabolic function, transport, signaling, and metal ion homeostasis to membrane synthesis pathways over time. While all zinc sources shared pathways relating to membrane damage and metal ion homeostasis, Zn-eNMs and ZnCl(2) displayed differences in their sensitivity profiles. For example, ZnCl(2) and nZnO elicited unique responses in pathways related to two-component signaling and monosaccharide biosynthesis, respectively. Single isolated measurements, such as MIC or IC(50), are inadequate, and time-resolved approaches utilizing genome-wide assays are therefore needed to capture this crucial dimension and illuminate the dynamic interplay at the nano-bio interface.

Genome-wide dissection of hybrid sterility in Drosophila confirms a polygenic threshold architecture.

Science.gov (United States)

Morán, Tomás; Fontdevila, Antonio

2014-01-01

To date, different studies about the genetic basis of hybrid male sterility (HMS), a postzygotic reproductive barrier thoroughly investigated using Drosophila species, have demonstrated that no single major gene can produce hybrid sterility without the cooperation of several genetic factors. Early work using hybrids between Drosophila koepferae (Dk) and Drosophila buzzatii (Db) was consistent with the idea that HMS requires the cooperation of several genetic factors, supporting a polygenic threshold (PT) model. Here we present a genome-wide mapping strategy to test the PT model, analyzing serially backcrossed fertile and sterile males in which the Dk genome was introgressed into the Db background. We identified 32 Dk-specific markers significantly associated with hybrid sterility. Our results demonstrate 1) a strong correlation between the number of segregated sterility markers and males' degree of sterility, 2) the exchangeability among markers, 3) their tendency to cluster into low-recombining chromosomal regions, and 4) the requirement for a minimum number (threshold) of markers to elicit sterility. Although our findings do not contradict a role for occasional major hybrid-sterility genes, they conform more to the view that HMS primarily evolves by the cumulative action of many interacting genes of minor effect in a complex PT architecture.

StereoGene: rapid estimation of genome-wide correlation of continuous or interval feature data.

Science.gov (United States)

Stavrovskaya, Elena D; Niranjan, Tejasvi; Fertig, Elana J; Wheelan, Sarah J; Favorov, Alexander V; Mironov, Andrey A

2017-10-15

Genomics features with similar genome-wide distributions are generally hypothesized to be functionally related, for example, colocalization of histones and transcription start sites indicate chromatin regulation of transcription factor activity. Therefore, statistical algorithms to perform spatial, genome-wide correlation among genomic features are required. Here, we propose a method, StereoGene, that rapidly estimates genome-wide correlation among pairs of genomic features. These features may represent high-throughput data mapped to reference genome or sets of genomic annotations in that reference genome. StereoGene enables correlation of continuous data directly, avoiding the data binarization and subsequent data loss. Correlations are computed among neighboring genomic positions using kernel correlation. Representing the correlation as a function of the genome position, StereoGene outputs the local correlation track as part of the analysis. StereoGene also accounts for confounders such as input DNA by partial correlation. We apply our method to numerous comparisons of ChIP-Seq datasets from the Human Epigenome Atlas and FANTOM CAGE to demonstrate its wide applicability. We observe the changes in the correlation between epigenomic features across developmental trajectories of several tissue types consistent with known biology and find a novel spatial correlation of CAGE clusters with donor splice sites and with poly(A) sites. These analyses provide examples for the broad applicability of StereoGene for regulatory genomics. The StereoGene C ++ source code, program documentation, Galaxy integration scripts and examples are available from the project homepage http://stereogene.bioinf.fbb.msu.ru/. favorov@sensi.org. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

A genome-wide search for genes involved in type 2 diabetes in a recently genetically isolated population from the Netherlands

NARCIS (Netherlands)

Y.S. Aulchenko (Yurii); N. Vaessen (Norbert); P. Heutink (Peter); J. Pullen (Jan); P.J.L.M. Snijders (Pieter); A. Hofman (Albert); L.A. Sandkuijl (Lodewijk); J.J. Houwing-Duistermaat (Jeanine); S. Bennett (Simon); B.A. Oostra (Ben); C.M. van Duijn (Cornelia); M. Edwards (Mark)

2003-01-01

textabstractMultiple genes, interacting with the environment, contribute to the susceptibility to type 2 diabetes. We performed a genome-wide search to localize type 2 diabetes susceptibility genes in a recently genetically isolated population in the Netherlands. We identified 79 nuclear families

Increased prediction accuracy in wheat breeding trials using a marker × environment interaction genomic selection model.

Science.gov (United States)

Lopez-Cruz, Marco; Crossa, Jose; Bonnett, David; Dreisigacker, Susanne; Poland, Jesse; Jannink, Jean-Luc; Singh, Ravi P; Autrique, Enrique; de los Campos, Gustavo

2015-02-06

Genomic selection (GS) models use genome-wide genetic information to predict genetic values of candidates of selection. Originally, these models were developed without considering genotype × environment interaction(G×E). Several authors have proposed extensions of the single-environment GS model that accommodate G×E using either covariance functions or environmental covariates. In this study, we model G×E using a marker × environment interaction (M×E) GS model; the approach is conceptually simple and can be implemented with existing GS software. We discuss how the model can be implemented by using an explicit regression of phenotypes on markers or using co-variance structures (a genomic best linear unbiased prediction-type model). We used the M×E model to analyze three CIMMYT wheat data sets (W1, W2, and W3), where more than 1000 lines were genotyped using genotyping-by-sequencing and evaluated at CIMMYT's research station in Ciudad Obregon, Mexico, under simulated environmental conditions that covered different irrigation levels, sowing dates and planting systems. We compared the M×E model with a stratified (i.e., within-environment) analysis and with a standard (across-environment) GS model that assumes that effects are constant across environments (i.e., ignoring G×E). The prediction accuracy of the M×E model was substantially greater of that of an across-environment analysis that ignores G×E. Depending on the prediction problem, the M×E model had either similar or greater levels of prediction accuracy than the stratified analyses. The M×E model decomposes marker effects and genomic values into components that are stable across environments (main effects) and others that are environment-specific (interactions). Therefore, in principle, the interaction model could shed light over which variants have effects that are stable across environments and which ones are responsible for G×E. The data set and the scripts required to reproduce the analysis are

Genome-wide association study of anthropometric traits and evidence of interactions with age and study year in Filipino women.

Science.gov (United States)

Croteau-Chonka, Damien C; Marvelle, Amanda F; Lange, Ethan M; Lee, Nanette R; Adair, Linda S; Lange, Leslie A; Mohlke, Karen L

2011-05-01

Increased values of multiple adiposity-related anthropometric traits are important risk factors for many common complex diseases. We performed a genome-wide association (GWA) study for four quantitative traits related to body size and adiposity (BMI, weight, waist circumference, and height) in a cohort of 1,792 adult Filipino women from the Cebu Longitudinal Health and Nutrition Survey (CLHNS). This is the first GWA study of anthropometric traits in Filipinos, a population experiencing a rapid transition into a more obesogenic environment. In addition to identifying suggestive evidence of additional single-nucleotide polymorphism (SNP) association signals (P Filipinos and provide further insight into the effects of BDNF, FTO, and MC4R on BMI.

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

DEFF Research Database (Denmark)

Justice, Anne E; Winkler, Thomas W; Feitosa, Mary F

2017-01-01

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87......% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent...... direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting...

Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs

NARCIS (Netherlands)

Lee, S.H.; Ripke, S.; Neale, B.; Faraone, S.V.; Purcell, S.M.; Perlis, R.H.; Mowry, B. J.; Thapar, A.; Goddard, M.E.; Witte, J.S.; Absher, D.; Agartz, I.; Akil, H.; Amin, F.; Andreassen, O.A.; Anjorin, A.; Anney, R.; Anttila, V.; Arking, D.E.; Asherson, P.; Azevedo, M.H.; Backlund, L.; Badner, J.A.; Bailey, A.J.; Banaschewski, T.; Barchas, J.D.; Barnes, M.R.; Barrett, T.B.; Bass, N.; Battaglia, A.; Bauer, M.; Bayés, M.; Bellivier, F.; Bergen, S.E.; Berrettini, W.; Betancur, C.; Bettecken, T.; Biederman, J; Binder, E.B.; Black, D.W.; Blackwood, D.H.; Bloss, C.S.; Boehnke, M.; Boomsma, D.I.; Breen, G.; Breuer, R.; Bruggeman, R.; Cormican, P.; Buccola, N.G.; Buitelaar, J.K.; Bunney, W.E.; Buxbaum, J.D.; Byerley, W. F.; Byrne, E.M.; Caesar, S.; Cahn, W.; Cantor, R.M.; Casas, M.; Chakravarti, A.; Chambert, K.; Choudhury, K.; Cichon, S.; Cloninger, C. R.; Collier, D.A.; Cook, E.H.; Coon, H.; Corman, B.; Corvin, A.; Coryell, W.H.; Craig, D.W.; Craig, I.W.; Crosbie, J.; Cuccaro, M.L.; Curtis, D.; Czamara, D.; Datta, S.; Dawson, G.; Day, R.; de Geus, E.J.C.; Degenhardt, F.; Djurovic, S.; Donohoe, G.; Doyle, A.E.; Duan, J.; Dudbridge, F.; Duketis, E.; Ebstein, R.P.; Edenberg, H.J.; Elia, J.; Ennis, S.; Etain, B.; Fanous, A.; Farmer, A.E.; Ferrier, I.N.; Flickinger, M.; Fombonne, E.; Foroud, T.; Frank, J.; Franke, B.; Fraser, C.; Freedman, R.; Freimer, N.B.; Freitag, C.; Friedl, M.; Frisén, L.; Gallagher, L.; Gejman, P.V.; Georgieva, L.; Gershon, E.S.; Geschwind, D.H.; Giegling, I.; Gill, M.; Gordon, S.D.; Gordon-Smith, K.; Green, E.K.; Greenwood, T.A.; Grice, D.E.; Gross, M.; Grozeva, D.; Guan, W.; Gurling, H.; de Haan, L.; Haines, J.L.; Hakonarson, H.; Hallmayer, J.; Hamilton, S.P.; Hamshere, M.L.; Hansen, T.F.; Hartmann, A.M.; Hautzinger, M.; Heath, A.C.; Henders, A.K.; Herms, S.; Hickie, I.B.; Hipolito, M.; Hoefels, S.; Holmans, P.A.; Holsboer, F.; Hoogendijk, W.J.G.; Hottenga, J.J.; Hultman, C. M.; Hus, V.; Ingason, A.; Ising, M.; Jamain, S.; Jones, E.G.; Jones, I.; Jones, L.; Tzeng, J.Y.; Kähler, A.K.; Kahn, R.S.; Kandaswamy, R.; Keller, M.C.; Kennedy, J.L.; Kenny, E.; Kent, L.; Kim, Y.; Kirov, G. K.; Klauck, S.M.; Klei, L.; Knowles, J.A.; Kohli, M.A.; Koller, D.L.; Konte, B.; Korszun, A.; Krabbendam, L.; Krasucki, R.; Kuntsi, J.; Kwan, P.; Landén, M.; Langstrom, N.; Lathrop, M.; Lawrence, J.; Lawson, W.B.; Leboyer, M.; Ledbetter, D.H.; Lee, P.H.; Lencz, T.; Lesch, K.P.; Levinson, D.F.; Lewis, C.M.; Li, J.; Lichtenstein, P.; Lieberman, J. A.; Lin, D.Y.; Linszen, D.H.; Liu, C.; Lohoff, F.W.; Loo, S.K.; Lord, C.; Lowe, J.K.; Lucae, S.; MacIntyre, D.J.; Madden, P.A.F.; Maestrini, E.; Magnusson, P.K.E.; Mahon, P.B.; Maier, W.; Malhotra, A.K.; Mane, S.M.; Martin, C.L.; Martin, N.G.; Mattheisen, M.; Matthews, K.; Mattingsdal, M.; McCarroll, S.A.; McGhee, K.A.; McGough, J.J.; McGrath, P.J.; McGuffin, P.; McInnis, M.G.; McIntosh, A.; McKinney, R.; McLean, A.W.; McMahon, F.J.; McMahon, W.M.; McQuillin, A.; Medeiros, H.; Medland, S.E.; Meier, S.; Melle, I.; Meng, F.; Meyer, J.; Middeldorp, C.M.; Middleton, L.; Milanova, V.; Miranda, A.; Monaco, A.P.; Montgomery, G.W.; Moran, J.L.; Moreno-De Luca, D.; Morken, G.; Morris, D.W.; Morrow, E.M.; Moskvina, V.; Muglia, P.; Mühleisen, T.W.; Muir, W.J.; Müller-Myhsok, B.; Murtha, M.; Myers, R.M.; Myin-Germeys, I.; Neale, M.C.; Nelson, S.F.; Nievergelt, C.M.; Nikolov, I.; Nimgaonkar, V.L.; Nolen, W.A.; Nöthen, M.M.; Nurnberger, J.I.; Nwulia, E.A.; Nyholt, DR; O'Dushlaine, C.; Oades, R.D.; Olincy, A.; Oliveira, G.; Olsen, L.; Ophoff, R.A.; Osby, U.; Owen, M.J.; Palotie, A.; Parr, J.R.; Paterson, A.D.; Pato, C.N.; Pato, M.T.; Penninx, B.W.J.H.; Pergadia, M.L.; Pericak-Vance, M.A.; Pickard, B.S.; Pimm, J.; Piven, J.; Posthuma, D.; Potash, J.B.; Poustka, F.; Propping, P.; Puri, V.; Quested, D.; Quinn, E.M.; Ramos-Quiroga, J.A.; Rasmussen, H.B.; Raychaudhuri, S.; Rehnström, K.; Reif, A.; Ribasés, M.; Rice, J.P.; Rietschel, M.; Roeder, K.; Roeyers, H.; Rossin, L.; Rothenberger, A.; Rouleau, G.; Ruderfer, D.; Rujescu, D.; Sanders, A.R.; Sanders, S.J.; Santangelo, S.; Sergeant, J.A.; Schachar, R.; Schalling, M.; Schatzberg, A.F.; Scheftner, W.A.; Schellenberg, G.D.; Scherer, S.W.; Schork, N.J.; Schulze, T.G.; Schumacher, J.; Schwarz, M.; Scolnick, E.; Scott, L.J.; Shi, J.; Shilling, P.D.; Shyn, S.I.; Silverman, J.M.; Slager, S.L.; Smalley, S.L.; Smit, J.H.; Smith, E.N.; Sonuga-Barke, E.J.; St Clair, D.; State, M.; Steffens, M; Steinhausen, H.C.; Strauss, J.; Strohmaier, J.; Stroup, T.S.; Sutcliffe, J.; Szatmari, P.; Szelinger, S.; Thirumalai, S.; Thompson, R.C.; Todorov, A.A.; Tozzi, F.; Treutlein, J.; Uhr, M.; van den Oord, E.J.C.G.; Grootheest, G.; van Os, J.; Vicente, A.; Vieland, V.; Vincent, J.B.; Visscher, P.M.; Walsh, C.A.; Wassink, T.H.; Watson, S.J.; Weissman, M.M.; Werge, T.; Wienker, T.F.; Wijsman, E.M.; Willemsen, G.; Williams, N.; Willsey, A.J.; Witt, S.H.; Xu, W.; Young, A.H.; Yu, T.W.; Zammit, S.; Zandi, P.P.; Zhang, P.; Zitman, F.G.; Zöllner, S.; Devlin, B.; Kelsoe, J.; Sklar, P.; Daly, M.J.; O'Donovan, M.C.; Craddock, N.; Sullivan, P.F.; Smoller, J.W.; Kendler, K.S.; Wray, N.R.

2013-01-01

Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases

Genome-wide discovered psychosis-risk gene ZNF804A impacts on white matter microstructure in health, schizophrenia and bipolar disorder

Directory of Open Access Journals (Sweden)

Emma-Jane Mallas

2016-02-01

Full Text Available Background. Schizophrenia (SZ and bipolar disorder (BD have both been associated with reduced microstructural white matter integrity using, as a proxy, fractional anisotropy (FA detected using diffusion tensor imaging (DTI. Genetic susceptibility for both illnesses has also been positively correlated in recent genome-wide association studies with allele A (adenine of single nucleotide polymorphism (SNP rs1344706 of the ZNF804A gene. However, little is known about how the genomic linkage disequilibrium region tagged by this SNP impacts on the brain to increase risk for psychosis. This study aimed to assess the impact of this risk variant on FA in patients with SZ, in those with BD and in healthy controls. Methods. 230 individuals were genotyped for the rs1344706 SNP and underwent DTI. We used tract-based spatial statistics (TBSS followed by an analysis of variance, with threshold-free cluster enhancement (TFCE, to assess underlying effects of genotype, diagnosis and their interaction, on FA. Results. As predicted, statistically significant reductions in FA across a widely distributed brain network (p < 0.05, TFCE-corrected were positively associated both with a diagnosis of SZ or BD and with the double (homozygous presence of the ZNF804A rs1344706 risk variant (A. The main effect of genotype was medium (d = 0.48 in a 44,054-voxel cluster and the effect in the SZ group alone was large (d = 1.01 in a 51,260-voxel cluster, with no significant effects in BD or controls, in isolation. No areas under a significant diagnosis by genotype interaction were found. Discussion. We provide the first evidence in a predominantly Caucasian clinical sample, of an association between ZNF804A rs1344706 A-homozygosity and reduced FA, both irrespective of diagnosis and particularly in SZ (in overlapping brain areas. This suggests that the previously observed involvement of this genomic region in psychosis susceptibility, and in impaired functional connectivity, may be

A Two-Stage Penalized Logistic Regression Approach to Case-Control Genome-Wide Association Studies

Directory of Open Access Journals (Sweden)

Jingyuan Zhao

2012-01-01

Full Text Available We propose a two-stage penalized logistic regression approach to case-control genome-wide association studies. This approach consists of a screening stage and a selection stage. In the screening stage, main-effect and interaction-effect features are screened by using L1-penalized logistic like-lihoods. In the selection stage, the retained features are ranked by the logistic likelihood with the smoothly clipped absolute deviation (SCAD penalty (Fan and Li, 2001 and Jeffrey’s Prior penalty (Firth, 1993, a sequence of nested candidate models are formed, and the models are assessed by a family of extended Bayesian information criteria (J. Chen and Z. Chen, 2008. The proposed approach is applied to the analysis of the prostate cancer data of the Cancer Genetic Markers of Susceptibility (CGEMS project in the National Cancer Institute, USA. Simulation studies are carried out to compare the approach with the pair-wise multiple testing approach (Marchini et al. 2005 and the LASSO-patternsearch algorithm (Shi et al. 2007.

A genome-wide association study of heparin-induced thrombocytopenia using an electronic medical record

DEFF Research Database (Denmark)

Karnes, Jason H; Cronin, Robert M; Rollin, Jerome

2015-01-01

Heparin-induced thrombocytopenia (HIT) is an unpredictable, potentially catastrophic adverse effect of heparin treatment resulting from an immune response to platelet factor 4 (PF4)/heparin complexes. No genome-wide evaluations have been performed to identify potential genetic influences on HIT. ...

Genome-Wide Association Study Identifies Four Loci Associated with Eruption of Permanent Teeth

Science.gov (United States)

Zhang, Hao; Shaffer, John R.; Hansen, Thomas; Esserlind, Ann-Louise; Boyd, Heather A.; Nohr, Ellen A.; Timpson, Nicholas J.; Fatemifar, Ghazaleh; Paternoster, Lavinia; Evans, David M.; Weyant, Robert J.; Levy, Steven M.; Lathrop, Mark; Smith, George Davey; Murray, Jeffrey C.; Olesen, Jes; Werge, Thomas; Marazita, Mary L.; Sørensen, Thorkild I. A.; Melbye, Mads

2011-01-01

The sequence and timing of permanent tooth eruption is thought to be highly heritable and can have important implications for the risk of malocclusion, crowding, and periodontal disease. We conducted a genome-wide association study of number of permanent teeth erupted between age 6 and 14 years, analyzed as age-adjusted standard deviation score averaged over multiple time points, based on childhood records for 5,104 women from the Danish National Birth Cohort. Four loci showed association at Peruption and were also known to influence height and breast cancer, respectively. The two other loci pointed to genomic regions without any previous significant genome-wide association study results. The intronic SNP rs7924176 in ADK could be linked to gene expression in monocytes. The combined effect of the four genetic variants was most pronounced between age 10 and 12 years, where children with 6 to 8 delayed tooth eruption alleles had on average 3.5 (95% confidence interval: 2.9–4.1) fewer permanent teeth than children with 0 or 1 of these alleles. PMID:21931568

Detecting DNA double-stranded breaks in mammalian genomes by linear amplification-mediated high-throughput genome-wide translocation sequencing.

Science.gov (United States)

Hu, Jiazhi; Meyers, Robin M; Dong, Junchao; Panchakshari, Rohit A; Alt, Frederick W; Frock, Richard L

2016-05-01

Unbiased, high-throughput assays for detecting and quantifying DNA double-stranded breaks (DSBs) across the genome in mammalian cells will facilitate basic studies of the mechanisms that generate and repair endogenous DSBs. They will also enable more applied studies, such as those to evaluate the on- and off-target activities of engineered nucleases. Here we describe a linear amplification-mediated high-throughput genome-wide sequencing (LAM-HTGTS) method for the detection of genome-wide 'prey' DSBs via their translocation in cultured mammalian cells to a fixed 'bait' DSB. Bait-prey junctions are cloned directly from isolated genomic DNA using LAM-PCR and unidirectionally ligated to bridge adapters; subsequent PCR steps amplify the single-stranded DNA junction library in preparation for Illumina Miseq paired-end sequencing. A custom bioinformatics pipeline identifies prey sequences that contribute to junctions and maps them across the genome. LAM-HTGTS differs from related approaches because it detects a wide range of broken end structures with nucleotide-level resolution. Familiarity with nucleic acid methods and next-generation sequencing analysis is necessary for library generation and data interpretation. LAM-HTGTS assays are sensitive, reproducible, relatively inexpensive, scalable and straightforward to implement with a turnaround time of <1 week.

Cloud-based interactive analytics for terabytes of genomic variants data.

Science.gov (United States)

Pan, Cuiping; McInnes, Gregory; Deflaux, Nicole; Snyder, Michael; Bingham, Jonathan; Datta, Somalee; Tsao, Philip S

2017-12-01

Large scale genomic sequencing is now widely used to decipher questions in diverse realms such as biological function, human diseases, evolution, ecosystems, and agriculture. With the quantity and diversity these data harbor, a robust and scalable data handling and analysis solution is desired. We present interactive analytics using a cloud-based columnar database built on Dremel to perform information compression, comprehensive quality controls, and biological information retrieval in large volumes of genomic data. We demonstrate such Big Data computing paradigms can provide orders of magnitude faster turnaround for common genomic analyses, transforming long-running batch jobs submitted via a Linux shell into questions that can be asked from a web browser in seconds. Using this method, we assessed a study population of 475 deeply sequenced human genomes for genomic call rate, genotype and allele frequency distribution, variant density across the genome, and pharmacogenomic information. Our analysis framework is implemented in Google Cloud Platform and BigQuery. Codes are available at https://github.com/StanfordBioinformatics/mvp_aaa_codelabs. cuiping@stanford.edu or ptsao@stanford.edu. Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2017. This work is written by US Government employees and are in the public domain in the US.

Genome-wide methylation study of diploid and triploid brown trout (Salmo trutta L.).

Science.gov (United States)

Covelo-Soto, L; Leunda, P M; Pérez-Figueroa, A; Morán, P

2015-06-01

The induction of triploidization in fish is a very common practice in aquaculture. Although triploidization has been applied successfully in many salmonid species, little is known about the epigenetic mechanisms implicated in the maintenance of the normal functions of the new polyploid genome. By means of methylation-sensitive amplified polymorphism (MSAP) techniques, genome-wide methylation changes associated with triploidization were assessed in DNA samples obtained from diploid and triploid siblings of brown trout (Salmo trutta). Simple comparative body measurements showed that the triploid trout used in the study were statistically bigger, however, not heavier than their diploid counterparts. The statistical analysis of the MSAP data showed no significant differences between diploid and triploid brown trout in respect to brain, gill, heart, liver, kidney or muscle samples. Nonetheless, local analysis pointed to the possibility of differences in connection with concrete loci. This is the first study that has investigated DNA methylation alterations associated with triploidization in brown trout. Our results set the basis for new studies to be undertaken and provide a new approach concerning triploidization effects of the salmonid genome while also contributing to the better understanding of the genome-wide methylation processes. © 2015 Stichting International Foundation for Animal Genetics.

Genetics of Genome-Wide Recombination Rate Evolution in Mice from an Isolated Island.

Science.gov (United States)

Wang, Richard J; Payseur, Bret A

2017-08-01

Recombination rate is a heritable quantitative trait that evolves despite the fundamentally conserved role that recombination plays in meiosis. Differences in recombination rate can alter the landscape of the genome and the genetic diversity of populations. Yet our understanding of the genetic basis of recombination rate evolution in nature remains limited. We used wild house mice ( Mus musculus domesticus ) from Gough Island (GI), which diverged recently from their mainland counterparts, to characterize the genetics of recombination rate evolution. We quantified genome-wide autosomal recombination rates by immunofluorescence cytology in spermatocytes from 240 F 2 males generated from intercrosses between GI-derived mice and the wild-derived inbred strain WSB/EiJ. We identified four quantitative trait loci (QTL) responsible for inter-F 2 variation in this trait, the strongest of which had effects that opposed the direction of the parental trait differences. Candidate genes and mutations for these QTL were identified by overlapping the detected intervals with whole-genome sequencing data and publicly available transcriptomic profiles from spermatocytes. Combined with existing studies, our findings suggest that genome-wide recombination rate divergence is not directional and its evolution within and between subspecies proceeds from distinct genetic loci. Copyright © 2017 by the Genetics Society of America.

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models.

Science.gov (United States)

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A; Burgueño, Juan; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo

2017-01-05

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects [Formula: see text] that can be assessed by the Kronecker product of variance-covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model [Formula: see text] plus an extra component, F: , that captures random effects between environments that were not captured by the random effects [Formula: see text] We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with [Formula: see text] over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect [Formula: see text]. Copyright © 2017 Cuevas et al.

Genome-wide approaches towards identification of susceptibility genes in complex diseases

NARCIS (Netherlands)

Franke, L.H.

2008-01-01

Throughout the human genome millions of places exist where humans differ gentically. The aim of this PhD thesis was to systematically assess this genetic variation and its biological consequences in a genome-wide way, through the utilization of DNA oligonucleotide arrays that assess hundres of

Genome-wide Association Analysis of Kernel Weight in Hard Winter Wheat

Science.gov (United States)

Wheat kernel weight is an important and heritable component of wheat grain yield and a key predictor of flour extraction. Genome-wide association analysis was conducted to identify genomic regions associated with kernel weight and kernel weight environmental response in 8 trials of 299 hard winter ...

Infrastructure for genomic interactions: Bioconductor classes for Hi-C, ChIA-PET and related experiments [version 1; referees: 2 approved

Directory of Open Access Journals (Sweden)

Aaron T. L. Lun

2016-05-01

Full Text Available The study of genomic interactions has been greatly facilitated by techniques such as chromatin conformation capture with high-throughput sequencing (Hi-C. These genome-wide experiments generate large amounts of data that require careful analysis to obtain useful biological conclusions. However, development of the appropriate software tools is hindered by the lack of basic infrastructure to represent and manipulate genomic interaction data. Here, we present the InteractionSet package that provides classes to represent genomic interactions and store their associated experimental data, along with the methods required for low-level manipulation and processing of those classes. The InteractionSet package exploits existing infrastructure in the open-source Bioconductor project, while in turn being used by Bioconductor packages designed for higher-level analyses. For new packages, use of the functionality in InteractionSet will simplify development, allow access to more features and improve interoperability between packages.

Infrastructure for genomic interactions: Bioconductor classes for Hi-C, ChIA-PET and related experiments [version 2; referees: 2 approved

Directory of Open Access Journals (Sweden)

Aaron T. L. Lun

2016-06-01

Full Text Available The study of genomic interactions has been greatly facilitated by techniques such as chromatin conformation capture with high-throughput sequencing (Hi-C. These genome-wide experiments generate large amounts of data that require careful analysis to obtain useful biological conclusions. However, development of the appropriate software tools is hindered by the lack of basic infrastructure to represent and manipulate genomic interaction data. Here, we present the InteractionSet package that provides classes to represent genomic interactions and store their associated experimental data, along with the methods required for low-level manipulation and processing of those classes. The InteractionSet package exploits existing infrastructure in the open-source Bioconductor project, while in turn being used by Bioconductor packages designed for higher-level analyses. For new packages, use of the functionality in InteractionSet will simplify development, allow access to more features and improve interoperability between packages.

Genome-wide association study of response to cognitive–behavioural therapy in children with anxiety disorders

Science.gov (United States)

Coleman, Jonathan R. I.; Lester, Kathryn J.; Keers, Robert; Roberts, Susanna; Curtis, Charles; Arendt, Kristian; Bögels, Susan; Cooper, Peter; Creswell, Cathy; Dalgleish, Tim; Hartman, Catharina A.; Heiervang, Einar R.; Hötzel, Katrin; Hudson, Jennifer L.; In-Albon, Tina; Lavallee, Kristen; Lyneham, Heidi J.; Marin, Carla E.; Meiser-Stedman, Richard; Morris, Talia; Nauta, Maaike H.; Rapee, Ronald M.; Schneider, Silvia; Schneider, Sophie C.; Silverman, Wendy K.; Thastum, Mikael; Thirlwall, Kerstin; Waite, Polly; Wergeland, Gro Janne; Breen, Gerome; Eley, Thalia C.

2016-01-01

Background Anxiety disorders are common, and cognitive–behavioural therapy (CBT) is a first-line treatment. Candidate gene studies have suggested a genetic basis to treatment response, but findings have been inconsistent. Aims To perform the first genome-wide association study (GWAS) of psychological treatment response in children with anxiety disorders (n = 980). Method Presence and severity of anxiety was assessed using semi-structured interview at baseline, on completion of treatment (post-treatment), and 3 to 12 months after treatment completion (follow-up). DNA was genotyped using the Illumina Human Core Exome-12v1.0 array. Linear mixed models were used to test associations between genetic variants and response (change in symptom severity) immediately post-treatment and at 6-month follow-up. Results No variants passed a genome-wide significance threshold (P = 5 × 10−8) in either analysis. Four variants met criteria for suggestive significance (P<5 × 10−6) in association with response post-treatment, and three variants in the 6-month follow-up analysis. Conclusions This is the first genome-wide therapygenetic study. It suggests no common variants of very high effect underlie response to CBT. Future investigations should maximise power to detect single-variant and polygenic effects by using larger, more homogeneous cohorts. PMID:26989097

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

Science.gov (United States)

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.

Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study

DEFF Research Database (Denmark)

de Vries, Paul S; Sabater-Lleal, Maria; Chasman, Daniel I

2017-01-01

An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In...

Regulatory network construction in Arabidopsis by using genome-wide gene expression quantitative trait loci

NARCIS (Netherlands)

Keurentjes, Joost J.B.; Fu, Jingyuan; Terpstra, Inez R.; Garcia, Juan M.; Ackerveken, Guido van den; Snoek, L. Basten; Peeters, Anton J.M.; Vreugdenhil, Dick; Koornneef, Maarten; Jansen, Ritsert C.

2007-01-01

Accessions of a plant species can show considerable genetic differences that are analyzed effectively by using recombinant inbred line (RIL) populations. Here we describe the results of genome-wide expression variation analysis in an RIL population of Arabidopsis thaliana. For many genes, variation

A mega-analysis of genome-wide association studies for major depressive disorder.

Science.gov (United States)

Ripke, Stephan; Wray, Naomi R; Lewis, Cathryn M; Hamilton, Steven P; Weissman, Myrna M; Breen, Gerome; Byrne, Enda M; Blackwood, Douglas H R; Boomsma, Dorret I; Cichon, Sven; Heath, Andrew C; Holsboer, Florian; Lucae, Susanne; Madden, Pamela A F; Martin, Nicholas G; McGuffin, Peter; Muglia, Pierandrea; Noethen, Markus M; Penninx, Brenda P; Pergadia, Michele L; Potash, James B; Rietschel, Marcella; Lin, Danyu; Müller-Myhsok, Bertram; Shi, Jianxin; Steinberg, Stacy; Grabe, Hans J; Lichtenstein, Paul; Magnusson, Patrik; Perlis, Roy H; Preisig, Martin; Smoller, Jordan W; Stefansson, Kari; Uher, Rudolf; Kutalik, Zoltan; Tansey, Katherine E; Teumer, Alexander; Viktorin, Alexander; Barnes, Michael R; Bettecken, Thomas; Binder, Elisabeth B; Breuer, René; Castro, Victor M; Churchill, Susanne E; Coryell, William H; Craddock, Nick; Craig, Ian W; Czamara, Darina; De Geus, Eco J; Degenhardt, Franziska; Farmer, Anne E; Fava, Maurizio; Frank, Josef; Gainer, Vivian S; Gallagher, Patience J; Gordon, Scott D; Goryachev, Sergey; Gross, Magdalena; Guipponi, Michel; Henders, Anjali K; Herms, Stefan; Hickie, Ian B; Hoefels, Susanne; Hoogendijk, Witte; Hottenga, Jouke Jan; Iosifescu, Dan V; Ising, Marcus; Jones, Ian; Jones, Lisa; Jung-Ying, Tzeng; Knowles, James A; Kohane, Isaac S; Kohli, Martin A; Korszun, Ania; Landen, Mikael; Lawson, William B; Lewis, Glyn; Macintyre, Donald; Maier, Wolfgang; Mattheisen, Manuel; McGrath, Patrick J; McIntosh, Andrew; McLean, Alan; Middeldorp, Christel M; Middleton, Lefkos; Montgomery, Grant M; Murphy, Shawn N; Nauck, Matthias; Nolen, Willem A; Nyholt, Dale R; O'Donovan, Michael; Oskarsson, Högni; Pedersen, Nancy; Scheftner, William A; Schulz, Andrea; Schulze, Thomas G; Shyn, Stanley I; Sigurdsson, Engilbert; Slager, Susan L; Smit, Johannes H; Stefansson, Hreinn; Steffens, Michael; Thorgeirsson, Thorgeir; Tozzi, Federica; Treutlein, Jens; Uhr, Manfred; van den Oord, Edwin J C G; Van Grootheest, Gerard; Völzke, Henry; Weilburg, Jeffrey B; Willemsen, Gonneke; Zitman, Frans G; Neale, Benjamin; Daly, Mark; Levinson, Douglas F; Sullivan, Patrick F

2013-04-01

Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 × 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 × 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.

Genome-wide association studies in an isolated founder population from the Pacific Island of Kosrae.

Directory of Open Access Journals (Sweden)

Jennifer K Lowe

2009-02-01

Full Text Available It has been argued that the limited genetic diversity and reduced allelic heterogeneity observed in isolated founder populations facilitates discovery of loci contributing to both Mendelian and complex disease. A strong founder effect, severe isolation, and substantial inbreeding have dramatically reduced genetic diversity in natives from the island of Kosrae, Federated States of Micronesia, who exhibit a high prevalence of obesity and other metabolic disorders. We hypothesized that genetic drift and possibly natural selection on Kosrae might have increased the frequency of previously rare genetic variants with relatively large effects, making these alleles readily detectable in genome-wide association analysis. However, mapping in large, inbred cohorts introduces analytic challenges, as extensive relatedness between subjects violates the assumptions of independence upon which traditional association test statistics are based. We performed genome-wide association analysis for 15 quantitative traits in 2,906 members of the Kosrae population, using novel approaches to manage the extreme relatedness in the sample. As positive controls, we observe association to known loci for plasma cholesterol, triglycerides, and C-reactive protein and to a compelling candidate loci for thyroid stimulating hormone and fasting plasma glucose. We show that our study is well powered to detect common alleles explaining >/=5% phenotypic variance. However, no such large effects were observed with genome-wide significance, arguing that even in such a severely inbred population, common alleles typically have modest effects. Finally, we show that a majority of common variants discovered in Caucasians have indistinguishable effect sizes on Kosrae, despite the major differences in population genetics and environment.

The influence of age and sex on genetic associations with adult body size and shape: a large-scale genome-wide interaction study

OpenAIRE

Winkler, Thomas W.; Heid, Iris M.; Gorski, Mathias

2015-01-01

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age-and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of Eur...

Genome-wide analysis of disease progression in age-related macular degeneration.

Science.gov (United States)

Yan, Qi; Ding, Ying; Liu, Yi; Sun, Tao; Fritsche, Lars G; Clemons, Traci; Ratnapriya, Rinki; Klein, Michael L; Cook, Richard J; Liu, Yu; Fan, Ruzong; Wei, Lai; Abecasis, Gonçalo R; Swaroop, Anand; Chew, Emily Y; Weeks, Daniel E; Chen, Wei

2018-03-01

Family- and population-based genetic studies have successfully identified multiple disease-susceptibility loci for Age-related macular degeneration (AMD), one of the first batch and most successful examples of genome-wide association study. However, most genetic studies to date have focused on case-control studies of late AMD (choroidal neovascularization or geographic atrophy). The genetic influences on disease progression are largely unexplored. We assembled unique resources to perform a genome-wide bivariate time-to-event analysis to test for association of time-to-late-AMD with ∼9 million variants on 2721 Caucasians from a large multi-center randomized clinical trial, the Age-Related Eye Disease Study. To our knowledge, this is the first genome-wide association study of disease progression (bivariate survival outcome) in AMD genetic studies, thus providing novel insights to AMD genetics. We used a robust Cox proportional hazards model to appropriately account for between-eye correlation when analyzing the progression time in the two eyes of each participant. We identified four previously reported susceptibility loci showing genome-wide significant association with AMD progression: ARMS2-HTRA1 (P = 8.1 × 10-43), CFH (P = 3.5 × 10-37), C2-CFB-SKIV2L (P = 8.1 × 10-10) and C3 (P = 1.2 × 10-9). Furthermore, we detected association of rs58978565 near TNR (P = 2.3 × 10-8), rs28368872 near ATF7IP2 (P = 2.9 × 10-8) and rs142450006 near MMP9 (P = 0.0006) with progression to choroidal neovascularization but not geographic atrophy. Secondary analysis limited to 34 reported risk variants revealed that LIPC and CTRB2-CTRB1 were also associated with AMD progression (P < 0.0015). Our genome-wide analysis thus expands the genetics in both development and progression of AMD and should assist in early identification of high risk individuals.

A "candidate-interactome" aggregate analysis of genome-wide association data in multiple sclerosis

DEFF Research Database (Denmark)

Mechelli, Rosella; Umeton, Renato; Policano, Claudia

2013-01-01

of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge......, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate...... immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated...

Polygenic analysis of genome-wide SNP data identifies common variants on allergic rhinitis

DEFF Research Database (Denmark)

Mohammadnejad, Afsaneh; Brasch-Andersen, Charlotte; Haagerup, Annette

Background: Allergic Rhinitis (AR) is a complex disorder that affects many people around the world. There is a high genetic contribution to the development of the AR, as twins and family studies have estimated heritability of more than 33%. Due to the complex nature of the disease, single SNP...... analysis has limited power in identifying the genetic variations for AR. We combined genome-wide association analysis (GWAS) with polygenic risk score (PRS) in exploring the genetic basis underlying the disease. Methods: We collected clinical data on 631 Danish subjects with AR cases consisting of 434...... sibling pairs and unrelated individuals and control subjects of 197 unrelated individuals. SNP genotyping was done by Affymetrix Genome-Wide Human SNP Array 5.0. SNP imputation was performed using "IMPUTE2". Using additive effect model, GWAS was conducted in discovery sample, the genotypes...

Nanobody®-based chromatin immunoprecipitation/micro-array analysis for genome-wide identification of transcription factor DNA binding sites

Science.gov (United States)

Nguyen-Duc, Trong; Peeters, Eveline; Muyldermans, Serge; Charlier, Daniel; Hassanzadeh-Ghassabeh, Gholamreza

2013-01-01

Nanobodies® are single-domain antibody fragments derived from camelid heavy-chain antibodies. Because of their small size, straightforward production in Escherichia coli, easy tailoring, high affinity, specificity, stability and solubility, nanobodies® have been exploited in various biotechnological applications. A major challenge in the post-genomics and post-proteomics era is the identification of regulatory networks involving nucleic acid–protein and protein–protein interactions. Here, we apply a nanobody® in chromatin immunoprecipitation followed by DNA microarray hybridization (ChIP-chip) for genome-wide identification of DNA–protein interactions. The Lrp-like regulator Ss-LrpB, arguably one of the best-studied specific transcription factors of the hyperthermophilic archaeon Sulfolobus solfataricus, was chosen for this proof-of-principle nanobody®-assisted ChIP. Three distinct Ss-LrpB-specific nanobodies®, each interacting with a different epitope, were generated for ChIP. Genome-wide ChIP-chip with one of these nanobodies® identified the well-established Ss-LrpB binding sites and revealed several unknown target sequences. Furthermore, these ChIP-chip profiles revealed auxiliary operator sites in the open reading frame of Ss-lrpB. Our work introduces nanobodies® as a novel class of affinity reagents for ChIP. Taking into account the unique characteristics of nanobodies®, in particular, their short generation time, nanobody®-based ChIP is expected to further streamline ChIP-chip and ChIP-Seq experiments, especially in organisms with no (or limited) possibility of genetic manipulation. PMID:23275538

Genome-Wide Association Study of Short-Acting beta(2)-Agonists A Novel Genome-Wide Significant Locus on Chromosome 2 near ASB3

NARCIS (Netherlands)

Israel, Elliot; Lasky-Su, Jessica; Markezich, Amy; Damask, Amy; Szefler, Stanley J.; Schuemann, Brooke; Klanderman, Barbara; Sylvia, Jody; Kazani, Shamsah; Wu, Rongling; Martinez, Fernando; Boushey, Homer A.; Chinchilli, Vernon M.; Mauger, Dave; Weiss, Scott T.; Tantisira, Kelan G.; de Zeeuw, Dick; Navis, Gerjan J.

2015-01-01

Rationale: [beta(2)-Agonists are the most common form of treatment of asthma, but there is significant variability in response to these medications. A significant proportion of this responsiveness may be heritable. Objectives: To investigate whether a genome-wide association study (GWAS) could

Genome-wide identification of coding and non-coding conserved sequence tags in human and mouse genomes

Directory of Open Access Journals (Sweden)

Maggi Giorgio P

2008-06-01

Full Text Available Abstract Background The accurate detection of genes and the identification of functional regions is still an open issue in the annotation of genomic sequences. This problem affects new genomes but also those of very well studied organisms such as human and mouse where, despite the great efforts, the inventory of genes and regulatory regions is far from complete. Comparative genomics is an effective approach to address this problem. Unfortunately it is limited by the computational requirements needed to perform genome-wide comparisons and by the problem of discriminating between conserved coding and non-coding sequences. This discrimination is often based (thus dependent on the availability of annotated proteins. Results In this paper we present the results of a comprehensive comparison of human and mouse genomes performed with a new high throughput grid-based system which allows the rapid detection of conserved sequences and accurate assessment of their coding potential. By detecting clusters of coding conserved sequences the system is also suitable to accurately identify potential gene loci. Following this analysis we created a collection of human-mouse conserved sequence tags and carefully compared our results to reliable annotations in order to benchmark the reliability of our classifications. Strikingly we were able to detect several potential gene loci supported by EST sequences but not corresponding to as yet annotated genes. Conclusion Here we present a new system which allows comprehensive comparison of genomes to detect conserved coding and non-coding sequences and the identification of potential gene loci. Our system does not require the availability of any annotated sequence thus is suitable for the analysis of new or poorly annotated genomes.

Genome-wide association study of classical Hodgkin lymphoma identifies key regulators of disease susceptibility

NARCIS (Netherlands)

Sud, A. (Amit); Thomsen, H. (Hauke); Law, P.J. (Philip J.); A. Försti (Asta); Filho, M.I.D.S. (Miguel Inacio Da Silva); Holroyd, A. (Amy); P. Broderick (Peter); Orlando, G. (Giulia); Lenive, O. (Oleg); Wright, L. (Lauren); R. Cooke (Rosie); D.F. Easton (Douglas); P.D.P. Pharoah (Paul); A.M. Dunning (Alison); J. Peto (Julian); F. Canzian (Federico); Eeles, R. (Rosalind); Z. Kote-Jarai; K.R. Muir (K.); Pashayan, N. (Nora); B.E. Henderson (Brian); C.A. Haiman (Christopher); S. Benlloch (Sara); F.R. Schumacher (Fredrick R); Olama, A.A.A. (Ali Amin Al); S.I. Berndt (Sonja); G. Conti (Giario); F. Wiklund (Fredrik); S.J. Chanock (Stephen); Stevens, V.L. (Victoria L.); C.M. Tangen (Catherine M.); Batra, J. (Jyotsna); Clements, J. (Judith); H. Grönberg (Henrik); Schleutker, J. (Johanna); D. Albanes (Demetrius); Weinstein, S. (Stephanie); K. Wolk (Kerstin); West, C. (Catharine); Mucci, L. (Lorelei); Cancel-Tassin, G. (Géraldine); Koutros, S. (Stella); Sorensen, K.D. (Karina Dalsgaard); L. Maehle; D. Neal (David); S.P.L. Travis (Simon); Hamilton, R.J. (Robert J.); S.A. Ingles (Sue); B.S. Rosenstein (Barry S.); Lu, Y.-J. (Yong-Jie); Giles, G.G. (Graham G.); A. Kibel (Adam); Vega, A. (Ana); M. Kogevinas (Manolis); Penney, K.L. (Kathryn L.); Park, J.Y. (Jong Y.); Stanford, J.L. (Janet L.); C. Cybulski (Cezary); B.G. Nordestgaard (Børge); Brenner, H. (Hermann); Maier, C. (Christiane); Kim, J. (Jeri); E.M. John (Esther); P.J. Teixeira; Neuhausen, S.L. (Susan L.); De Ruyck, K. (Kim); Razack, A. (Azad); Newcomb, L.F. (Lisa F.); Lessel, D. (Davor); Kaneva, R. (Radka); N. Usmani (Nawaid); F. Claessens; Townsend, P.A. (Paul A.); Dominguez, M.G. (Manuela Gago); Roobol, M.J. (Monique J.); F. Menegaux (Florence); P. Hoffmann (Per); M.M. Nöthen (Markus); K.-H. JöCkel (Karl-Heinz); Strandmann, E.P.V. (Elke Pogge Von); Lightfoot, T. (Tracy); Kane, E. (Eleanor); Roman, E. (Eve); Lake, A. (Annette); Montgomery, D. (Dorothy); Jarrett, R.F. (Ruth F.); A.J. Swerdlow (Anthony ); A. Engert (Andreas); N. Orr (Nick); K. Hemminki (Kari); Houlston, R.S. (Richard S.)

2017-01-01

textabstractSeveral susceptibility loci for classical Hodgkin lymphoma have been reported. However, much of the heritable risk is unknown. Here, we perform a meta-analysis of two existing genome-wide association studies, a new genome-wide association study, and replication totalling 5,314 cases and

Genome-wide identification of breed-informative single-nucleotide ...

African Journals Online (AJOL)

This is because the SNPs on BovineSNP50 and GGP-80K assays were ascertained as being common in European taurine breeds. Lower MAF and SNP informativeness observed in this study limits the application of these assays in breed assignment, and could have other implications for genome-wide studies in South ...

Effects of short-term high-fat overfeeding on genome-wide DNA methylation in the skeletal muscle of healthy young men

DEFF Research Database (Denmark)

Jacobsen, S C; Brøns, Charlotte; Bork-Jensen, Jette

2012-01-01

Energy-dense diets that are high in fat are associated with a risk of metabolic diseases. The underlying molecular mechanisms could involve epigenetics, as recent data show altered DNA methylation of putative type 2 diabetes candidate genes in response to high-fat diets. We examined the effect...... of a short-term high-fat overfeeding (HFO) diet on genome-wide DNA methylation patterns in human skeletal muscle....

Genome-wide detection of selection and other evolutionary forces

DEFF Research Database (Denmark)

Xu, Zhuofei; Zhou, Rui

2015-01-01

As is well known, pathogenic microbes evolve rapidly to escape from the host immune system and antibiotics. Genetic variations among microbial populations occur frequently during the long-term pathogen–host evolutionary arms race, and individual mutation beneficial for the fitness can be fixed...... to scan genome-wide alignments for evidence of positive Darwinian selection, recombination, and other evolutionary forces operating on the coding regions. In this chapter, we describe an integrative analysis pipeline and its application to tracking featured evolutionary trajectories on the genome...

Updates on genome-wide association findings in eating disorders and future application to precision medicine.

Science.gov (United States)

Breithaupt, Lauren; Hubel, Christopher; Bulik, Cynthia M

2018-02-22

Heterogeneity, frequent diagnostic fluctuation across presentations, and global concerns with the absence of effective treatments all encourage science that moves the field toward individualized or precision medicine in eating disorders. We review recent advances in psychiatric genetics focusing on genome-wide association studies (GWAS) in eating disorders and enumerate the prospects and challenges of a genomics-driven approach towards personalized intervention. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Genome-wide methylation analysis identifies genes silenced in non-seminoma cell lines.

Science.gov (United States)

Noor, Dzul Azri Mohamed; Jeyapalan, Jennie N; Alhazmi, Safiah; Carr, Matthew; Squibb, Benjamin; Wallace, Claire; Tan, Christopher; Cusack, Martin; Hughes, Jaime; Reader, Tom; Shipley, Janet; Sheer, Denise; Scotting, Paul J

2016-01-01

Silencing of genes by DNA methylation is a common phenomenon in many types of cancer. However, the genome-wide effect of DNA methylation on gene expression has been analysed in relatively few cancers. Germ cell tumours (GCTs) are a complex group of malignancies. They are unique in developing from a pluripotent progenitor cell. Previous analyses have suggested that non-seminomas exhibit much higher levels of DNA methylation than seminomas. The genomic targets that are methylated, the extent to which this results in gene silencing and the identity of the silenced genes most likely to play a role in the tumours' biology have not yet been established. In this study, genome-wide methylation and expression analysis of GCT cell lines was combined with gene expression data from primary tumours to address this question. Genome methylation was analysed using the Illumina infinium HumanMethylome450 bead chip system and gene expression was analysed using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Regulation by methylation was confirmed by demethylation using 5-aza-2-deoxycytidine and reverse transcription-quantitative PCR. Large differences in the level of methylation of the CpG islands of individual genes between tumour cell lines correlated well with differential gene expression. Treatment of non-seminoma cells with 5-aza-2-deoxycytidine verified that methylation of all genes tested played a role in their silencing in yolk sac tumour cells and many of these genes were also differentially expressed in primary tumours. Genes silenced by methylation in the various GCT cell lines were identified. Several pluripotency-associated genes were identified as a major functional group of silenced genes.

Combining Genome-Wide Information with a Functional Structural Plant Model to Simulate 1-Year-Old Apple Tree Architecture.

Science.gov (United States)

Migault, Vincent; Pallas, Benoît; Costes, Evelyne

2016-01-01

In crops, optimizing target traits in breeding programs can be fostered by selecting appropriate combinations of architectural traits which determine light interception and carbon acquisition. In apple tree, architectural traits were observed to be under genetic control. However, architectural traits also result from many organogenetic and morphological processes interacting with the environment. The present study aimed at combining a FSPM built for apple tree, MAppleT, with genetic determinisms of architectural traits, previously described in a bi-parental population. We focused on parameters related to organogenesis (phyllochron and immediate branching) and morphogenesis processes (internode length and leaf area) during the first year of tree growth. Two independent datasets collected in 2004 and 2007 on 116 genotypes, issued from a 'Starkrimson' × 'Granny Smith' cross, were used. The phyllochron was estimated as a function of thermal time and sylleptic branching was modeled subsequently depending on phyllochron. From a genetic map built with SNPs, marker effects were estimated on four MAppleT parameters with rrBLUP, using 2007 data. These effects were then considered in MAppleT to simulate tree development in the two climatic conditions. The genome wide prediction model gave consistent estimations of parameter values with correlation coefficients between observed values and estimated values from SNP markers ranging from 0.79 to 0.96. However, the accuracy of the prediction model following cross validation schemas was lower. Three integrative traits (the number of leaves, trunk length, and number of sylleptic laterals) were considered for validating MAppleT simulations. In 2007 climatic conditions, simulated values were close to observations, highlighting the correct simulation of genetic variability. However, in 2004 conditions which were not used for model calibration, the simulations differed from observations. This study demonstrates the possibility of

Genome-wide association study of classical Hodgkin lymphoma identifies key regulators of disease susceptibility

DEFF Research Database (Denmark)

Sud, Amit; Thomsen, Hauke; Law, Philip J.

2017-01-01

Several susceptibility loci for classical Hodgkin lymphoma have been reported. However, much of the heritable risk is unknown. Here, we perform a meta-analysis of two existing genome-wide association studies, a new genome-wide association study, and replication totalling 5,314 cases and 16,749 co...

Genome-wide population-based association study of extremely overweight young adults--the GOYA study

DEFF Research Database (Denmark)

Paternoster, Lavinia; Evans, David M; Nohr, Ellen Aagaard

2011-01-01

Thirty-two common variants associated with body mass index (BMI) have been identified in genome-wide association studies, explaining ∼1.45% of BMI variation in general population cohorts. We performed a genome-wide association study in a sample of young adults enriched for extremely overweight...

Targeting 160 candidate genes for blood pressure regulation with a genome-wide genotyping array.

Directory of Open Access Journals (Sweden)

Siim Sõber

2009-06-01

Full Text Available The outcome of Genome-Wide Association Studies (GWAS has challenged the field of blood pressure (BP genetics as previous candidate genes have not been among the top loci in these scans. We used Affymetrix 500K genotyping data of KORA S3 cohort (n = 1,644; Southern-Germany to address (i SNP coverage in 160 BP candidate genes; (ii the evidence for associations with BP traits in genome-wide and replication data, and haplotype analysis. In total, 160 gene regions (genic region+/-10 kb covered 2,411 SNPs across 11.4 Mb. Marker densities in genes varied from 0 (n = 11 to 0.6 SNPs/kb. On average 52.5% of the HAPMAP SNPs per gene were captured. No evidence for association with BP was obtained for 1,449 tested SNPs. Considerable associations (P50% of HAPMAP SNPs were tagged. In general, genes with higher marker density (>0.2 SNPs/kb revealed a better chance to reach close to significance associations. Although, none of the detected P-values remained significant after Bonferroni correction (P<0.05/2319, P<2.15 x 10(-5, the strength of some detected associations was close to this level: rs10889553 (LEPR and systolic BP (SBP (P = 4.5 x 10(-5 as well as rs10954174 (LEP and diastolic BP (DBP (P = 5.20 x 10(-5. In total, 12 markers in 7 genes (ADRA2A, LEP, LEPR, PTGER3, SLC2A1, SLC4A2, SLC8A1 revealed considerable association (P<10(-3 either with SBP, DBP, and/or hypertension (HYP. None of these were confirmed in replication samples (KORA S4, HYPEST, BRIGHT. However, supportive evidence for the association of rs10889553 (LEPR and rs11195419 (ADRA2A with BP was obtained in meta-analysis across samples stratified either by body mass index, smoking or alcohol consumption. Haplotype analysis highlighted LEPR and PTGER3. In conclusion, the lack of associations in BP candidate genes may be attributed to inadequate marker coverage on the genome-wide arrays, small phenotypic effects of the loci and/or complex interaction with life-style and metabolic parameters.

Assessing Predictive Properties of Genome-Wide Selection in Soybeans

Directory of Open Access Journals (Sweden)

Alencar Xavier

2016-08-01

Full Text Available Many economically important traits in plant breeding have low heritability or are difficult to measure. For these traits, genomic selection has attractive features and may boost genetic gains. Our goal was to evaluate alternative scenarios to implement genomic selection for yield components in soybean (Glycine max L. merr. We used a nested association panel with cross validation to evaluate the impacts of training population size, genotyping density, and prediction model on the accuracy of genomic prediction. Our results indicate that training population size was the factor most relevant to improvement in genome-wide prediction, with greatest improvement observed in training sets up to 2000 individuals. We discuss assumptions that influence the choice of the prediction model. Although alternative models had minor impacts on prediction accuracy, the most robust prediction model was the combination of reproducing kernel Hilbert space regression and BayesB. Higher genotyping density marginally improved accuracy. Our study finds that breeding programs seeking efficient genomic selection in soybeans would best allocate resources by investing in a representative training set.

Assessing Predictive Properties of Genome-Wide Selection in Soybeans.

Science.gov (United States)

Xavier, Alencar; Muir, William M; Rainey, Katy Martin

2016-08-09

Many economically important traits in plant breeding have low heritability or are difficult to measure. For these traits, genomic selection has attractive features and may boost genetic gains. Our goal was to evaluate alternative scenarios to implement genomic selection for yield components in soybean (Glycine max L. merr). We used a nested association panel with cross validation to evaluate the impacts of training population size, genotyping density, and prediction model on the accuracy of genomic prediction. Our results indicate that training population size was the factor most relevant to improvement in genome-wide prediction, with greatest improvement observed in training sets up to 2000 individuals. We discuss assumptions that influence the choice of the prediction model. Although alternative models had minor impacts on prediction accuracy, the most robust prediction model was the combination of reproducing kernel Hilbert space regression and BayesB. Higher genotyping density marginally improved accuracy. Our study finds that breeding programs seeking efficient genomic selection in soybeans would best allocate resources by investing in a representative training set. Copyright © 2016 Xavie et al.

Comparative Genomics and Disorder Prediction Identify Biologically Relevant SH3 Protein Interactions.

Directory of Open Access Journals (Sweden)

2005-08-01

Full Text Available Protein interaction networks are an important part of the post-genomic effort to integrate a part-list view of the cell into system-level understanding. Using a set of 11 yeast genomes we show that combining comparative genomics and secondary structure information greatly increases consensus-based prediction of SH3 targets. Benchmarking of our method against positive and negative standards gave 83% accuracy with 26% coverage. The concept of an optimal divergence time for effective comparative genomics studies was analyzed, demonstrating that genomes of species that diverged very recently from Saccharomyces cerevisiae(S. mikatae, S. bayanus, and S. paradoxus, or a long time ago (Neurospora crassa and Schizosaccharomyces pombe, contain less information for accurate prediction of SH3 targets than species within the optimal divergence time proposed. We also show here that intrinsically disordered SH3 domain targets are more probable sites of interaction than equivalent sites within ordered regions. Our findings highlight several novel S. cerevisiae SH3 protein interactions, the value of selection of optimal divergence times in comparative genomics studies, and the importance of intrinsic disorder for protein interactions. Based on our results we propose novel roles for the S. cerevisiae proteins Abp1p in endocytosis and Hse1p in endosome protein sorting.

Comparative genomics and disorder prediction identify biologically relevant SH3 protein interactions.

Directory of Open Access Journals (Sweden)

Pedro Beltrao

2005-08-01

Full Text Available Protein interaction networks are an important part of the post-genomic effort to integrate a part-list view of the cell into system-level understanding. Using a set of 11 yeast genomes we show that combining comparative genomics and secondary structure information greatly increases consensus-based prediction of SH3 targets. Benchmarking of our method against positive and negative standards gave 83% accuracy with 26% coverage. The concept of an optimal divergence time for effective comparative genomics studies was analyzed, demonstrating that genomes of species that diverged very recently from Saccharomyces cerevisiae(S. mikatae, S. bayanus, and S. paradoxus, or a long time ago (Neurospora crassa and Schizosaccharomyces pombe, contain less information for accurate prediction of SH3 targets than species within the optimal divergence time proposed. We also show here that intrinsically disordered SH3 domain targets are more probable sites of interaction than equivalent sites within ordered regions. Our findings highlight several novel S. cerevisiae SH3 protein interactions, the value of selection of optimal divergence times in comparative genomics studies, and the importance of intrinsic disorder for protein interactions. Based on our results we propose novel roles for the S. cerevisiae proteins Abp1p in endocytosis and Hse1p in endosome protein sorting.

Genome-wide association study of prostate cancer-specific survival

DEFF Research Database (Denmark)

Szulkin, Robert; Karlsson, Robert; Whitington, Thomas

2015-01-01

BACKGROUND: Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical. METHODS: We performed a genome-wide survival analysis of cause-specific death in 24,...

Genome-Wide Association Study of Antiphospholipid Antibodies

Directory of Open Access Journals (Sweden)

M. Ilyas Kamboh

2013-01-01

Full Text Available Background. The persistent presence of antiphospholipid antibodies (APA may lead to the development of primary or secondary antiphospholipid syndrome. Although the genetic basis of APA has been suggested, the identity of the underlying genes is largely unknown. In this study, we have performed a genome-wide association study (GWAS in an effort to identify susceptibility loci/genes for three main APA: anticardiolipin antibodies (ACL, lupus anticoagulant (LAC, and anti-β2 glycoprotein I antibodies (anti-β2GPI. Methods. DNA samples were genotyped using the Affymetrix 6.0 array containing 906,600 single-nucleotide polymorphisms (SNPs. Association of SNPs with the antibody status (positive/negative was tested using logistic regression under the additive model. Results. We have identified a number of suggestive novel loci with Pgenome-wide significance, many of the suggestive loci are potential candidates for the production of APA. We have replicated the previously reported associations of HLA genes and APOH with APA but these were not the top loci. Conclusions. We have identified a number of suggestive novel loci for APA that will stimulate follow-up studies in independent and larger samples to replicate our findings.

Genome-wide estimates of coancestry and inbreeding in a closed herd of ancient Iberian pigs.

Directory of Open Access Journals (Sweden)

María Saura

Full Text Available Maintaining genetic variation and controlling the increase in inbreeding are crucial requirements in animal conservation programs. The most widely accepted strategy for achieving these objectives is to maximize the effective population size by minimizing the global coancestry obtained from a particular pedigree. However, for most natural or captive populations genealogical information is absent. In this situation, microsatellites have been traditionally the markers of choice to characterize genetic variation, and several estimators of genealogical coefficients have been developed using marker data, with unsatisfactory results. The development of high-throughput genotyping techniques states the necessity of reviewing the paradigm that genealogical coancestry is the best parameter for measuring genetic diversity. In this study, the Illumina PorcineSNP60 BeadChip was used to obtain genome-wide estimates of rates of coancestry and inbreeding and effective population size for an ancient strain of Iberian pigs that is now in serious danger of extinction and for which very accurate genealogical information is available (the Guadyerbas strain. Genome-wide estimates were compared with those obtained from microsatellite and from pedigree data. Estimates of coancestry and inbreeding computed from the SNP chip were strongly correlated with genealogical estimates and these correlations were substantially higher than those between microsatellite and genealogical coefficients. Also, molecular coancestry computed from SNP information was a better predictor of genealogical coancestry than coancestry computed from microsatellites. Rates of change in coancestry and inbreeding and effective population size estimated from molecular data were very similar to those estimated from genealogical data. However, estimates of effective population size obtained from changes in coancestry or inbreeding differed. Our results indicate that genome-wide information represents a

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

Science.gov (United States)

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.

Hematopoietic transcriptional mechanisms: from locus-specific to genome-wide vantage points.

Science.gov (United States)

DeVilbiss, Andrew W; Sanalkumar, Rajendran; Johnson, Kirby D; Keles, Sunduz; Bresnick, Emery H

2014-08-01

Hematopoiesis is an exquisitely regulated process in which stem cells in the developing embryo and the adult generate progenitor cells that give rise to all blood lineages. Master regulatory transcription factors control hematopoiesis by integrating signals from the microenvironment and dynamically establishing and maintaining genetic networks. One of the most rudimentary aspects of cell type-specific transcription factor function, how they occupy a highly restricted cohort of cis-elements in chromatin, remains poorly understood. Transformative technologic advances involving the coupling of next-generation DNA sequencing technology with the chromatin immunoprecipitation assay (ChIP-seq) have enabled genome-wide mapping of factor occupancy patterns. However, formidable problems remain; notably, ChIP-seq analysis yields hundreds to thousands of chromatin sites occupied by a given transcription factor, and only a fraction of the sites appear to be endowed with critical, non-redundant function. It has become en vogue to map transcription factor occupancy patterns genome-wide, while using powerful statistical tools to establish correlations to inform biology and mechanisms. With the advent of revolutionary genome editing technologies, one can now reach beyond correlations to conduct definitive hypothesis testing. This review focuses on key discoveries that have emerged during the path from single loci to genome-wide analyses, specifically in the context of hematopoietic transcriptional mechanisms. Copyright © 2014 ISEH - International Society for Experimental Hematology. Published by Elsevier Inc. All rights reserved.

DNA Breaks and End Resection Measured Genome-wide by End Sequencing.

Science.gov (United States)

Canela, Andres; Sridharan, Sriram; Sciascia, Nicholas; Tubbs, Anthony; Meltzer, Paul; Sleckman, Barry P; Nussenzweig, André

2016-09-01

DNA double-strand breaks (DSBs) arise during physiological transcription, DNA replication, and antigen receptor diversification. Mistargeting or misprocessing of DSBs can result in pathological structural variation and mutation. Here we describe a sensitive method (END-seq) to monitor DNA end resection and DSBs genome-wide at base-pair resolution in vivo. We utilized END-seq to determine the frequency and spectrum of restriction-enzyme-, zinc-finger-nuclease-, and RAG-induced DSBs. Beyond sequence preference, chromatin features dictate the repertoire of these genome-modifying enzymes. END-seq can detect at least one DSB per cell among 10,000 cells not harboring DSBs, and we estimate that up to one out of 60 cells contains off-target RAG cleavage. In addition to site-specific cleavage, we detect DSBs distributed over extended regions during immunoglobulin class-switch recombination. Thus, END-seq provides a snapshot of DNA ends genome-wide, which can be utilized for understanding genome-editing specificities and the influence of chromatin on DSB pathway choice. Published by Elsevier Inc.

Genome-wide prediction of cis-regulatory regions using supervised deep learning methods.

Science.gov (United States)

Li, Yifeng; Shi, Wenqiang; Wasserman, Wyeth W

2018-05-31

In the human genome, 98% of DNA sequences are non-protein-coding regions that were previously disregarded as junk DNA. In fact, non-coding regions host a variety of cis-regulatory regions which precisely control the expression of genes. Thus, Identifying active cis-regulatory regions in the human genome is critical for understanding gene regulation and assessing the impact of genetic variation on phenotype. The developments of high-throughput sequencing and machine learning technologies make it possible to predict cis-regulatory regions genome wide. Based on rich data resources such as the Encyclopedia of DNA Elements (ENCODE) and the Functional Annotation of the Mammalian Genome (FANTOM) projects, we introduce DECRES based on supervised deep learning approaches for the identification of enhancer and promoter regions in the human genome. Due to their ability to discover patterns in large and complex data, the introduction of deep learning methods enables a significant advance in our knowledge of the genomic locations of cis-regulatory regions. Using models for well-characterized cell lines, we identify key experimental features that contribute to the predictive performance. Applying DECRES, we delineate locations of 300,000 candidate enhancers genome wide (6.8% of the genome, of which 40,000 are supported by bidirectional transcription data), and 26,000 candidate promoters (0.6% of the genome). The predicted annotations of cis-regulatory regions will provide broad utility for genome interpretation from functional genomics to clinical applications. The DECRES model demonstrates potentials of deep learning technologies when combined with high-throughput sequencing data, and inspires the development of other advanced neural network models for further improvement of genome annotations.

Meta-analysis for genome-wide association studies using case-control design: application and practice.

Science.gov (United States)

Shim, Sungryul; Kim, Jiyoung; Jung, Wonguen; Shin, In-Soo; Bae, Jong-Myon

2016-01-01

This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA). The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy-Weinberg equilibrium (HWE) in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The 'genhwcci' and 'metan' commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the 'metareg' command of STATA should be conducted to evaluate related factors of heterogeneities.

Use of genome-wide association studies for cancer research and drug repositioning.

Directory of Open Access Journals (Sweden)

Jizhun Zhang

Full Text Available Although genome-wide association studies have identified many risk loci associated with colorectal cancer, the molecular basis of these associations are still unclear. We aimed to infer biological insights and highlight candidate genes of interest within GWAS risk loci. We used an in silico pipeline based on functional annotation, quantitative trait loci mapping of cis-acting gene, PubMed text-mining, protein-protein interaction studies, genetic overlaps with cancer somatic mutations and knockout mouse phenotypes, and functional enrichment analysis to prioritize the candidate genes at the colorectal cancer risk loci. Based on these analyses, we observed that these genes were the targets of approved therapies for colorectal cancer, and suggested that drugs approved for other indications may be repurposed for the treatment of colorectal cancer. This study highlights the use of publicly available data as a cost effective solution to derive biological insights, and provides an empirical evidence that the molecular basis of colorectal cancer can provide important leads for the discovery of new drugs.

Genome wide analysis of drug-induced torsades de pointes: lack of common variants with large effect sizes.

Directory of Open Access Journals (Sweden)

Elijah R Behr

Full Text Available Marked prolongation of the QT interval on the electrocardiogram associated with the polymorphic ventricular tachycardia Torsades de Pointes is a serious adverse event during treatment with antiarrhythmic drugs and other culprit medications, and is a common cause for drug relabeling and withdrawal. Although clinical risk factors have been identified, the syndrome remains unpredictable in an individual patient. Here we used genome-wide association analysis to search for common predisposing genetic variants. Cases of drug-induced Torsades de Pointes (diTdP, treatment tolerant controls, and general population controls were ascertained across multiple sites using common definitions, and genotyped on the Illumina 610k or 1M-Duo BeadChips. Principal Components Analysis was used to select 216 Northwestern European diTdP cases and 771 ancestry-matched controls, including treatment-tolerant and general population subjects. With these sample sizes, there is 80% power to detect a variant at genome-wide significance with minor allele frequency of 10% and conferring an odds ratio of ≥2.7. Tests of association were carried out for each single nucleotide polymorphism (SNP by logistic regression adjusting for gender and population structure. No SNP reached genome wide-significance; the variant with the lowest P value was rs2276314, a non-synonymous coding variant in C18orf21 (p  =  3×10(-7, odds ratio = 2, 95% confidence intervals: 1.5-2.6. The haplotype formed by rs2276314 and a second SNP, rs767531, was significantly more frequent in controls than cases (p  =  3×10(-9. Expanding the number of controls and a gene-based analysis did not yield significant associations. This study argues that common genomic variants do not contribute importantly to risk for drug-induced Torsades de Pointes across multiple drugs.

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 .

CMS: a web-based system for visualization and analysis of genome-wide methylation data of human cancers.

Science.gov (United States)

Gu, Fei; Doderer, Mark S; Huang, Yi-Wen; Roa, Juan C; Goodfellow, Paul J; Kizer, E Lynette; Huang, Tim H M; Chen, Yidong

2013-01-01

DNA methylation of promoter CpG islands is associated with gene suppression, and its unique genome-wide profiles have been linked to tumor progression. Coupled with high-throughput sequencing technologies, it can now efficiently determine genome-wide methylation profiles in cancer cells. Also, experimental and computational technologies make it possible to find the functional relationship between cancer-specific methylation patterns and their clinicopathological parameters. Cancer methylome system (CMS) is a web-based database application designed for the visualization, comparison and statistical analysis of human cancer-specific DNA methylation. Methylation intensities were obtained from MBDCap-sequencing, pre-processed and stored in the database. 191 patient samples (169 tumor and 22 normal specimen) and 41 breast cancer cell-lines are deposited in the database, comprising about 6.6 billion uniquely mapped sequence reads. This provides comprehensive and genome-wide epigenetic portraits of human breast cancer and endometrial cancer to date. Two views are proposed for users to better understand methylation structure at the genomic level or systemic methylation alteration at the gene level. In addition, a variety of annotation tracks are provided to cover genomic information. CMS includes important analytic functions for interpretation of methylation data, such as the detection of differentially methylated regions, statistical calculation of global methylation intensities, multiple gene sets of biologically significant categories, interactivity with UCSC via custom-track data. We also present examples of discoveries utilizing the framework. CMS provides visualization and analytic functions for cancer methylome datasets. A comprehensive collection of datasets, a variety of embedded analytic functions and extensive applications with biological and translational significance make this system powerful and unique in cancer methylation research. CMS is freely accessible

Genome-wide analysis of the human Alu Yb-lineage

Directory of Open Access Journals (Sweden)

Carter Anthony B

2004-03-01

Full Text Available Abstract The Alu Yb-lineage is a 'young' primarily human-specific group of short interspersed element (SINE subfamilies that have integrated throughout the human genome. In this study, we have computationally screened the draft sequence of the human genome for Alu Yb-lineage subfamily members present on autosomal chromosomes. A total of 1,733 Yb Alu subfamily members have integrated into human autosomes. The average ages of Yb-lineage subfamilies, Yb7, Yb8 and Yb9, are estimated as 4.81, 2.39 and 2.32 million years, respectively. In order to determine the contribution of the Alu Yb-lineage to human genomic diversity, 1,202 loci were analysed using polymerase chain reaction (PCR-based assays, which amplify the genomic regions containing individual Yb-lineage subfamily members. Approximately 20 per cent of the Yb-lineage Alu elements are polymorphic for insertion presence/absence in the human genome. Fewer than 0.5 per cent of the Yb loci also demonstrate insertions at orthologous positions in non-human primate genomes. Genomic sequencing of these unusual loci demonstrates that each of the orthologous loci from non-human primate genomes contains older Y, Sg and Sx Alu family members that have been altered, through various mechanisms, into Yb8 sequences. These data suggest that Alu Yb-lineage subfamily members are largely restricted to the human genome. The high copy number, level of insertion polymorphism and estimated age indicate that members of the Alu Yb elements will be useful in a wide range of genetic analyses.

Genome-wide association of lipid-lowering response to statins in combined study populations.

Directory of Open Access Journals (Sweden)

Mathew J Barber

2010-03-01

Full Text Available Statins effectively lower total and plasma LDL-cholesterol, but the magnitude of decrease varies among individuals. To identify single nucleotide polymorphisms (SNPs contributing to this variation, we performed a combined analysis of genome-wide association (GWA results from three trials of statin efficacy.Bayesian and standard frequentist association analyses were performed on untreated and statin-mediated changes in LDL-cholesterol, total cholesterol, HDL-cholesterol, and triglyceride on a total of 3932 subjects using data from three studies: Cholesterol and Pharmacogenetics (40 mg/day simvastatin, 6 weeks, Pravastatin/Inflammation CRP Evaluation (40 mg/day pravastatin, 24 weeks, and Treating to New Targets (10 mg/day atorvastatin, 8 weeks. Genotype imputation was used to maximize genomic coverage and to combine information across studies. Phenotypes were normalized within each study to account for systematic differences among studies, and fixed-effects combined analysis of the combined sample were performed to detect consistent effects across studies. Two SNP associations were assessed as having posterior probability greater than 50%, indicating that they were more likely than not to be genuinely associated with statin-mediated lipid response. SNP rs8014194, located within the CLMN gene on chromosome 14, was strongly associated with statin-mediated change in total cholesterol with an 84% probability by Bayesian analysis, and a p-value exceeding conventional levels of genome-wide significance by frequentist analysis (P = 1.8 x 10(-8. This SNP was less significantly associated with change in LDL-cholesterol (posterior probability = 0.16, P = 4.0 x 10(-6. Bayesian analysis also assigned a 51% probability that rs4420638, located in APOC1 and near APOE, was associated with change in LDL-cholesterol.Using combined GWA analysis from three clinical trials involving nearly 4,000 individuals treated with simvastatin, pravastatin, or atorvastatin, we

A novel genome-information content-based statistic for genome-wide association analysis designed for next-generation sequencing data.

Science.gov (United States)

Luo, Li; Zhu, Yun; Xiong, Momiao

2012-06-01

The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T(2), collapsing method, multivariate and collapsing (CMC) method, individual χ(2) test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets.

Genome-wide association study of young-onset hypertension in the Han Chinese population of Taiwan.

Directory of Open Access Journals (Sweden)

Hsin-Chou Yang

Full Text Available Young-onset hypertension has a stronger genetic component than late-onset counterpart; thus, the identification of genes related to its susceptibility is a critical issue for the prevention and management of this disease. We carried out a two-stage association scan to map young-onset hypertension susceptibility genes. The first-stage analysis, a genome-wide association study, analyzed 175 matched case-control pairs; the second-stage analysis, a confirmatory association study, verified the results at the first stage based on a total of 1,008 patients and 1,008 controls. Single-locus association tests, multilocus association tests and pair-wise gene-gene interaction tests were performed to identify young-onset hypertension susceptibility genes. After considering stringent adjustments of multiple testing, gene annotation and single-nucleotide polymorphism (SNP quality, four SNPs from two SNP triplets with strong association signals (-log(10(p>7 and 13 SNPs from 8 interactive SNP pairs with strong interactive signals (-log(10(p>8 were carefully re-examined. The confirmatory study verified the association for a SNP quartet 219 kb and 495 kb downstream of LOC344371 (a hypothetical gene and RASGRP3 on chromosome 2p22.3, respectively. The latter has been implicated in the abnormal vascular responsiveness to endothelin-1 and angiotensin II in diabetic-hypertensive rats. Intrinsic synergy involving IMPG1 on chromosome 6q14.2-q15 was also verified. IMPG1 encodes interphotoreceptor matrix proteoglycan 1 which has cation binding capacity. The genes are novel hypertension targets identified in this first genome-wide hypertension association study of the Han Chinese population.

Genome-wide association study of Arabidopsis thaliana leaf microbial community.

Science.gov (United States)

Horton, Matthew W; Bodenhausen, Natacha; Beilsmith, Kathleen; Meng, Dazhe; Muegge, Brian D; Subramanian, Sathish; Vetter, M Madlen; Vilhjálmsson, Bjarni J; Nordborg, Magnus; Gordon, Jeffrey I; Bergelson, Joy

2014-11-10

Identifying the factors that influence the outcome of host-microbial interactions is critical to protecting biodiversity, minimizing agricultural losses and improving human health. A few genes that determine symbiosis or resistance to infectious disease have been identified in model species, but a comprehensive examination of how a host genotype influences the structure of its microbial community is lacking. Here we report the results of a field experiment with the model plant Arabidopsis thaliana to identify the fungi and bacteria that colonize its leaves and the host loci that influence the microbe numbers. The composition of this community differs among accessions of A. thaliana. Genome-wide association studies (GWAS) suggest that plant loci responsible for defense and cell wall integrity affect variation in this community. Furthermore, species richness in the bacterial community is shaped by host genetic variation, notably at loci that also influence the reproduction of viruses, trichome branching and morphogenesis.

Efficient genome-wide genotyping strategies and data integration in crop plants.

Science.gov (United States)

Torkamaneh, Davoud; Boyle, Brian; Belzile, François

2018-03-01

Next-generation sequencing (NGS) has revolutionized plant and animal research by providing powerful genotyping methods. This review describes and discusses the advantages, challenges and, most importantly, solutions to facilitate data processing, the handling of missing data, and cross-platform data integration. Next-generation sequencing technologies provide powerful and flexible genotyping methods to plant breeders and researchers. These methods offer a wide range of applications from genome-wide analysis to routine screening with a high level of accuracy and reproducibility. Furthermore, they provide a straightforward workflow to identify, validate, and screen genetic variants in a short time with a low cost. NGS-based genotyping methods include whole-genome re-sequencing, SNP arrays, and reduced representation sequencing, which are widely applied in crops. The main challenges facing breeders and geneticists today is how to choose an appropriate genotyping method and how to integrate genotyping data sets obtained from various sources. Here, we review and discuss the advantages and challenges of several NGS methods for genome-wide genetic marker development and genotyping in crop plants. We also discuss how imputation methods can be used to both fill in missing data in genotypic data sets and to integrate data sets obtained using different genotyping tools. It is our hope that this synthetic view of genotyping methods will help geneticists and breeders to integrate these NGS-based methods in crop plant breeding and research.

Pooled genome wide association detects association upstream of FCRL3 with Graves' disease.

Science.gov (United States)

Khong, Jwu Jin; Burdon, Kathryn P; Lu, Yi; Laurie, Kate; Leonardos, Lefta; Baird, Paul N; Sahebjada, Srujana; Walsh, John P; Gajdatsy, Adam; Ebeling, Peter R; Hamblin, Peter Shane; Wong, Rosemary; Forehan, Simon P; Fourlanos, Spiros; Roberts, Anthony P; Doogue, Matthew; Selva, Dinesh; Montgomery, Grant W; Macgregor, Stuart; Craig, Jamie E

2016-11-18

Graves' disease is an autoimmune thyroid disease of complex inheritance. Multiple genetic susceptibility loci are thought to be involved in Graves' disease and it is therefore likely that these can be identified by genome wide association studies. This study aimed to determine if a genome wide association study, using a pooling methodology, could detect genomic loci associated with Graves' disease. Nineteen of the top ranking single nucleotide polymorphisms including HLA-DQA1 and C6orf10, were clustered within the Major Histo-compatibility Complex region on chromosome 6p21, with rs1613056 reaching genome wide significance (p = 5 × 10 -8 ). Technical validation of top ranking non-Major Histo-compatablity complex single nucleotide polymorphisms with individual genotyping in the discovery cohort revealed four single nucleotide polymorphisms with p ≤ 10 -4 . Rs17676303 on chromosome 1q23.1, located upstream of FCRL3, showed evidence of association with Graves' disease across the discovery, replication and combined cohorts. A second single nucleotide polymorphism rs9644119 downstream of DPYSL2 showed some evidence of association supported by finding in the replication cohort that warrants further study. Pooled genome wide association study identified a genetic variant upstream of FCRL3 as a susceptibility locus for Graves' disease in addition to those identified in the Major Histo-compatibility Complex. A second locus downstream of DPYSL2 is potentially a novel genetic variant in Graves' disease that requires further confirmation.

Genome-Wide Gene Set Analysis for Identification of Pathways Associated with Alcohol Dependence

Science.gov (United States)

Biernacka, Joanna M.; Geske, Jennifer; Jenkins, Gregory D.; Colby, Colin; Rider, David N.; Karpyak, Victor M.; Choi, Doo-Sup; Fridley, Brooke L.

2013-01-01

It is believed that multiple genetic variants with small individual effects contribute to the risk of alcohol dependence. Such polygenic effects are difficult to detect in genome-wide association studies that test for association of the phenotype with each single nucleotide polymorphism (SNP) individually. To overcome this challenge, gene set analysis (GSA) methods that jointly test for the effects of pre-defined groups of genes have been proposed. Rather than testing for association between the phenotype and individual SNPs, these analyses evaluate the global evidence of association with a set of related genes enabling the identification of cellular or molecular pathways or biological processes that play a role in development of the disease. It is hoped that by aggregating the evidence of association for all available SNPs in a group of related genes, these approaches will have enhanced power to detect genetic associations with complex traits. We performed GSA using data from a genome-wide study of 1165 alcohol dependent cases and 1379 controls from the Study of Addiction: Genetics and Environment (SAGE), for all 200 pathways listed in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results demonstrated a potential role of the “Synthesis and Degradation of Ketone Bodies” pathway. Our results also support the potential involvement of the “Neuroactive Ligand Receptor Interaction” pathway, which has previously been implicated in addictive disorders. These findings demonstrate the utility of GSA in the study of complex disease, and suggest specific directions for further research into the genetic architecture of alcohol dependence. PMID:22717047

Meta-analysis of genome-wide association studies for personality

NARCIS (Netherlands)

M.H.M. de Moor; P.T. Costa Jr; A. Terracciano; R.F. Krueger; E.J.C. de Geus (Eco); T. Toshiko; B.W.J.H. Penninx (Brenda); T. Esko; P.A.F. Madden (Pamela); J. Derringer; N. Amin (Najaf); G.A.H.M. Willemsen (Gonneke); J.J. Hottenga (Jouke Jan); M.A. Distel (Marijn); M. Uda (Manuela); S. Sanna (Serena); P. Spinhoven; C.A. Hartman; P.F. Sullivan (Patrick); A. Realo; J. Allik; A.C. Heath; M.L. Pergadia; P. Lin; R. Grucza; T. Nutile; M. Ciullo; D. Rujescu (Dan); I. Giegling (Ina); B. Konte; E. Widen (Elisabeth); D.L. Cousminer (Diana); J.G. Eriksson; A. Palotie; L. Peltonen; M. Luciano (Michelle); A. Tenesa (Albert); G. Davies; L.M. Lopez; N.K. Hansell (Narelle); S.E. Medland (Sarah Elizabeth); L. Ferrucci; D. Schlessinger; G.W. Montgomery; M.J. Wright (Margaret); Y.S. Aulchenko (Yurii); A.C.J.W. Janssens (Cécile); B.A. Oostra (Ben); A. Metspalu (Andres); I.J. Deary; K. Räikkönen (Katri); L.J. Bierut (Laura); N.G. Martin; C.M. van Duijn (Cornelia); D.I. Boomsma (Dorret); G.R. Abecasis (Gonçalo); A. Agrawal (Arpana)

2012-01-01

textabstractPersonality can be thought of as a set of characteristics that influence people's thoughts, feelings and behavior across a variety of settings. Variation in personality is predictive of many outcomes in life, including mental health. Here we report on a meta-analysis of genome-wide

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.

A genome-wide investigation of SNPs and CNVs in schizophrenia.

Directory of Open Access Journals (Sweden)

Anna C Need

2009-02-01

Full Text Available We report a genome-wide assessment of single nucleotide polymorphisms (SNPs and copy number variants (CNVs in schizophrenia. We investigated SNPs using 871 patients and 863 controls, following up the top hits in four independent cohorts comprising 1,460 patients and 12,995 controls, all of European origin. We found no genome-wide significant associations, nor could we provide support for any previously reported candidate gene or genome-wide associations. We went on to examine CNVs using a subset of 1,013 cases and 1,084 controls of European ancestry, and a further set of 60 cases and 64 controls of African ancestry. We found that eight cases and zero controls carried deletions greater than 2 Mb, of which two, at 8p22 and 16p13.11-p12.4, are newly reported here. A further evaluation of 1,378 controls identified no deletions greater than 2 Mb, suggesting a high prior probability of disease involvement when such deletions are observed in cases. We also provide further evidence for some smaller, previously reported, schizophrenia-associated CNVs, such as those in NRXN1 and APBA2. We could not provide strong support for the hypothesis that schizophrenia patients have a significantly greater "load" of large (>100 kb, rare CNVs, nor could we find common CNVs that associate with schizophrenia. Finally, we did not provide support for the suggestion that schizophrenia-associated CNVs may preferentially disrupt genes in neurodevelopmental pathways. Collectively, these analyses provide the first integrated study of SNPs and CNVs in schizophrenia and support the emerging view that rare deleterious variants may be more important in schizophrenia predisposition than common polymorphisms. While our analyses do not suggest that implicated CNVs impinge on particular key pathways, we do support the contribution of specific genomic regions in schizophrenia, presumably due to recurrent mutation. On balance, these data suggest that very few schizophrenia patients

A scored human protein-protein interaction network to catalyze genomic interpretation

DEFF Research Database (Denmark)

Li, Taibo; Wernersson, Rasmus; Hansen, Rasmus B

2017-01-01

Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap,......Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (In...

Genome-wide association studies of obesity and metabolic syndrome.

Science.gov (United States)

Fall, Tove; Ingelsson, Erik

2014-01-25

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

The causal effect of red blood cell folate on genome-wide methylation in cord blood: a Mendelian randomization approach.

Science.gov (United States)

Binder, Alexandra M; Michels, Karin B

2013-12-04

Investigation of the biological mechanism by which folate acts to affect fetal development can inform appraisal of expected benefits and risk management. This research is ethically imperative given the ubiquity of folic acid fortified products in the US. Considering that folate is an essential component in the one-carbon metabolism pathway that provides methyl groups for DNA methylation, epigenetic modifications provide a putative molecular mechanism mediating the effect of folic acid supplementation on neonatal and pediatric outcomes. In this study we use a Mendelian Randomization Unnecessary approach to assess the effect of red blood cell (RBC) folate on genome-wide DNA methylation in cord blood. Site-specific CpG methylation within the proximal promoter regions of approximately 14,500 genes was analyzed using the Illumina Infinium Human Methylation27 Bead Chip for 50 infants from the Epigenetic Birth Cohort at Brigham and Women's Hospital in Boston. Using methylenetetrahydrofolate reductase genotype as the instrument, the Mendelian Randomization approach identified 7 CpG loci with a significant (mostly positive) association between RBC folate and methylation level. Among the genes in closest proximity to this significant subset of CpG loci, several enriched biologic processes were involved in nucleic acid transport and metabolic processing. Compared to the standard ordinary least squares regression method, our estimates were demonstrated to be more robust to unmeasured confounding. To the authors' knowledge, this is the largest genome-wide analysis of the effects of folate on methylation pattern, and the first to employ Mendelian Randomization to assess the effects of an exposure on epigenetic modifications. These results can help guide future analyses of the causal effects of periconceptional folate levels on candidate pathways.

Microbial genome-wide association studies: lessons from human GWAS.

Science.gov (United States)

Power, Robert A; Parkhill, Julian; de Oliveira, Tulio

2017-01-01

The reduced costs of sequencing have led to whole-genome sequences for a large number of microorganisms, enabling the application of microbial genome-wide association studies (GWAS). Given the successes of human GWAS in understanding disease aetiology and identifying potential drug targets, microbial GWAS are likely to further advance our understanding of infectious diseases. These advances include insights into pressing global health problems, such as antibiotic resistance and disease transmission. In this Review, we outline the methodologies of GWAS, the current state of the field of microbial GWAS, and how lessons from human GWAS can direct the future of the field.

Meta-analysis for genome-wide association studies using case-control design: application and practice

Directory of Open Access Journals (Sweden)

Sungryul Shim

2016-12-01

Full Text Available This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA. The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy–Weinberg equilibrium (HWE in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The ‘genhwcci’ and ‘metan’ commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the ‘metareg’ command of STATA should be conducted to evaluate related factors of heterogeneities.

A genome-wide association study of cognitive function in Chinese adult twins

DEFF Research Database (Denmark)

Xu, Chunsheng; Zhang, Dongfeng; Wu, Yili

2017-01-01

Multiple loci or genes have been identified using genome-wide association studies mainly in western countries but with inconsistent results. No similar studies have been conducted in the world's largest and rapidly aging Chinese population. The paper aimed to identify the specific genetic variants....... Gene-based analysis was performed on VEGAS2. The statistically significant genes were then subject to gene set enrichment analysis to further identify the specific biological pathways associated with cognitive function. No SNPs reached genome-wide significance although there were 13 SNPs of suggestive...

Advances in genome-wide RNAi cellular screens: a case study using the Drosophila JAK/STAT pathway

Science.gov (United States)

2012-01-01

Background Genome-scale RNA-interference (RNAi) screens are becoming ever more common gene discovery tools. However, whilst every screen identifies interacting genes, less attention has been given to how factors such as library design and post-screening bioinformatics may be effecting the data generated. Results Here we present a new genome-wide RNAi screen of the Drosophila JAK/STAT signalling pathway undertaken in the Sheffield RNAi Screening Facility (SRSF). This screen was carried out using a second-generation, computationally optimised dsRNA library and analysed using current methods and bioinformatic tools. To examine advances in RNAi screening technology, we compare this screen to a biologically very similar screen undertaken in 2005 with a first-generation library. Both screens used the same cell line, reporters and experimental design, with the SRSF screen identifying 42 putative regulators of JAK/STAT signalling, 22 of which verified in a secondary screen and 16 verified with an independent probe design. Following reanalysis of the original screen data, comparisons of the two gene lists allows us to make estimates of false discovery rates in the SRSF data and to conduct an assessment of off-target effects (OTEs) associated with both libraries. We discuss the differences and similarities between the resulting data sets and examine the relative improvements in gene discovery protocols. Conclusions Our work represents one of the first direct comparisons between first- and second-generation libraries and shows that modern library designs together with methodological advances have had a significant influence on genome-scale RNAi screens. PMID:23006893

An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

NARCIS (Netherlands)

Scott, Robert A; Scott, Laura J; Mägi, Reedik; Marullo, Letizia; Gaulton, Kyle J; Kaakinen, Marika; Pervjakova, Natalia; Pers, Tune H; Johnson, Andrew D; Eicher, John D; Jackson, Anne U; Ferreira, Teresa; Lee, Yeji; Ma, Clement; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Qi, Lu; Van Zuydam, Natalie R; Mahajan, Anubha; Chen, Han; Almgren, Peter; Voight, Ben F; Grallert, Harald; Müller-Nurasyid, Martina; Ried, Janina S; Rayner, William N; Robertson, Neil; Karssen, Lennart C; van Leeuwen, Elisabeth M; Willems, Sara M; Fuchsberger, Christian; Kwan, Phoenix; Teslovich, Tanya M; Chanda, Pritam; Li, Man; Lu, Yingchang; Dina, Christian; Thuillier, Dorothee; Yengo, Loic; Jiang, Longda; Sparso, Thomas; Kestler, Hans A; Chheda, Himanshu; Eisele, Lewin; Gustafsson, Stefan; Frånberg, Mattias; Strawbridge, Rona J; Benediktsson, Rafn; Hreidarsson, Astradur B; Kong, Augustine; Sigurðsson, Gunnar; Kerrison, Nicola D; Luan, Jian'an; Liang, Liming; Meitinger, Thomas; Roden, Michael; Thorand, Barbara; Esko, Tõnu; Mihailov, Evelin; Fox, Caroline; Liu, Ching-Ti; Rybin, Denis; Isomaa, Bo; Lyssenko, Valeriya; Tuomi, Tiinamaija; Couper, David J; Pankow, James S; Grarup, Niels; Have, Christian T; Jørgensen, Marit E; Jørgensen, Torben; Linneberg, Allan; Cornelis, Marilyn C; van Dam, Rob M; Hunter, David J; Kraft, Peter; Sun, Qi; Edkins, Sarah; Owen, Katharine R; Perry, John Rb; Wood, Andrew R; Zeggini, Eleftheria; Tajes-Fernandes, Juan; Abecasis, Goncalo R; Bonnycastle, Lori L; Chines, Peter S; Stringham, Heather M; Koistinen, Heikki A; Kinnunen, Leena; Sennblad, Bengt; Mühleisen, Thomas W; Nöthen, Markus M; Pechlivanis, Sonali; Baldassarre, Damiano; Gertow, Karl; Humphries, Steve E; Tremoli, Elena; Klopp, Norman; Meyer, Julia; Steinbach, Gerald; Wennauer, Roman; Eriksson, Johan G; Mӓnnistö, Satu; Peltonen, Leena; Tikkanen, Emmi; Charpentier, Guillaume; Eury, Elodie; Lobbens, Stéphane; Gigante, Bruna; Leander, Karin; McLeod, Olga; Bottinger, Erwin P; Gottesman, Omri; Ruderfer, Douglas; Blüher, Matthias; Kovacs, Peter; Tonjes, Anke; Maruthur, Nisa M; Scapoli, Chiara; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne; de Faire, Ulf; Hamsten, Anders; Stumvoll, Michael; Deloukas, Panagiotis; Donnelly, Peter J; Frayling, Timothy M; Hattersley, Andrew T; Ripatti, Samuli; Salomaa, Veikko; Pedersen, Nancy L; Boehm, Bernhard O; Bergman, Richard N; Collins, Francis S; Mohlke, Karen L; Tuomilehto, Jaakko; Hansen, Torben; Pedersen, Oluf; Barroso, Inês; Lannfelt, Lars; Ingelsson, Erik; Lind, Lars; Lindgren, Cecilia M; Cauchi, Stephane; Froguel, Philippe; Loos, Ruth Jf; Balkau, Beverley; Boeing, Heiner; Franks, Paul W; Gurrea, Aurelio Barricarte; Palli, Domenico; van der Schouw, Yvonne T; Altshuler, David; Groop, Leif C; Langenberg, Claudia; Wareham, Nicholas J; Sijbrands, Eric; van Duijn, Cornelia M; Florez, Jose C; Meigs, James B; Boerwinkle, Eric; Gieger, Christian; Strauch, Konstantin; Metspalu, Andres; Morris, Andrew D; Palmer, Colin Na; Hu, Frank B; Thorsteinsdottir, Unnur; Stefansson, Kari; Dupuis, Josée; Morris, Andrew P; Boehnke, Michael; McCarthy, Mark I; Prokopenko, Inga

2017-01-01

To characterise type 2 diabetes (T2D) associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D cases and 132,532 controls of European ancestry after imputation using the 1000 Genomes multi-ethnic reference panel.

Genome scan for nonadditive heterotic trait loci reveals mainly underdominant effects in Saccharomyces cerevisiae.

Science.gov (United States)

Laiba, Efrat; Glikaite, Ilana; Levy, Yael; Pasternak, Zohar; Fridman, Eyal

2016-04-01

The overdominant model of heterosis explains the superior phenotype of hybrids by synergistic allelic interaction within heterozygous loci. To map such genetic variation in yeast, we used a population doubling time dataset of Saccharomyces cerevisiae 16 × 16 diallel and searched for major contributing heterotic trait loci (HTL). Heterosis was observed for the majority of hybrids, as they surpassed their best parent growth rate. However, most of the local heterozygous loci identified by genome scan were surprisingly underdominant, i.e., reduced growth. We speculated that in these loci adverse effects on growth resulted from incompatible allelic interactions. To test this assumption, we eliminated these allelic interactions by creating hybrids with local hemizygosity for the underdominant HTLs, as well as for control random loci. Growth of hybrids was indeed elevated for most hemizygous to HTL genes but not for control genes, hence validating the results of our genome scan. Assessing the consequences of local heterozygosity by reciprocal hemizygosity and allele replacement assays revealed the influence of genetic background on the underdominant effects of HTLs. Overall, this genome-wide study on a multi-parental hybrid population provides a strong argument against single gene overdominance as a major contributor to heterosis, and favors the dominance complementation model.

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

Directory of Open Access Journals (Sweden)

Chen Jiun-Ching

2007-05-01

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

A review of genome-wide approaches to study the genetic basis for spermatogenic defects.

Science.gov (United States)

Aston, Kenneth I; Conrad, Donald F

2013-01-01

Rapidly advancing tools for genetic analysis on a genome-wide scale have been instrumental in identifying the genetic bases for many complex diseases. About half of male infertility cases are of unknown etiology in spite of tremendous efforts to characterize the genetic basis for the disorder. Advancing our understanding of the genetic basis for male infertility will require the application of established and emerging genomic tools. This chapter introduces many of the tools available for genetic studies on a genome-wide scale along with principles of study design and data analysis.

Genome-Wide Divergence in the West-African Malaria Vector Anopheles melas

Directory of Open Access Journals (Sweden)

Kevin C. Deitz

2016-09-01

Full Text Available Anopheles melas is a member of the recently diverged An. gambiae species complex, a model for speciation studies, and is a locally important malaria vector along the West-African coast where it breeds in brackish water. A recent population genetic study of An. melas revealed species-level genetic differentiation between three population clusters. An. melas West extends from The Gambia to the village of Tiko, Cameroon. The other mainland cluster, An. melas South, extends from the southern Cameroonian village of Ipono to Angola. Bioko Island, Equatorial Guinea An. melas populations are genetically isolated from mainland populations. To examine how genetic differentiation between these An. melas forms is distributed across their genomes, we conducted a genome-wide analysis of genetic differentiation and selection using whole genome sequencing data of pooled individuals (Pool-seq from a representative population of each cluster. The An. melas forms exhibit high levels of genetic differentiation throughout their genomes, including the presence of numerous fixed differences between clusters. Although the level of divergence between the clusters is on a par with that of other species within the An. gambiae complex, patterns of genome-wide divergence and diversity do not provide evidence for the presence of pre- and/or postmating isolating mechanisms in the form of speciation islands. These results are consistent with an allopatric divergence process with little or no introgression.

Systematic Search for Gene-Gene Interaction Effect on Prostate Cancer Risk

Science.gov (United States)

2013-07-01

Systematic Search for Gene-Gene Interaction 5a. CONTRACT NUMBER Effect on Prostate Cancer Risk 5b. GRANT NUMBER W81XWH-09-1-0488 5c. PROGRAM...Supported by this grant ) 1. Tao S, Wang Z, Feng J, Hsu FC, Jin G, Kin ST, Zhang Z, Gronberg H, Zheng, SL, Isaacs WB, XU J, Sun J. A Genome-Wide Search for...order interactions among estrogen- metabolism genes in sporadic breast cancer. Am J Hum Genet, 69, 138-47. 48. Marchini, J., Donnelly, P. and Cardon

Genome-wide diet-gene interaction analyses for risk of colorectal cancer.

Directory of Open Access Journals (Sweden)

Jane C Figueiredo

2014-04-01

Full Text Available Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet interactions, as well as our recently developed Cocktail method that involves a screening step based on marginal associations and gene-diet correlations and a testing step for multiplicative interactions, while correcting for multiple testing using weighted hypothesis testing. Per quartile increment in the intake of red and processed meat were associated with statistically significant increased risks of colorectal cancer and vegetable, fruit and fiber intake with lower risks. From the case-control analysis, we detected a significant interaction between rs4143094 (10p14/near GATA3 and processed meat consumption (OR = 1.17; p = 8.7E-09, which was consistently observed across studies (p heterogeneity = 0.78. The risk of colorectal cancer associated with processed meat was increased among individuals with the rs4143094-TG and -TT genotypes (OR = 1.20 and OR = 1.39, respectively and null among those with the GG genotype (OR = 1.03. Our results identify a novel gene-diet interaction with processed meat for colorectal cancer, highlighting that diet may modify the effect of genetic variants on disease risk, which may have important implications for prevention.

Genome-wide Meta-analysis on the Sense of Smell Among US Older Adults.

Science.gov (United States)

Dong, Jing; Yang, Jingyun; Tranah, Greg; Franceschini, Nora; Parimi, Neeta; Alkorta-Aranburu, Gorka; Xu, Zongli; Alonso, Alvaro; Cummings, Steven R; Fornage, Myriam; Huang, Xuemei; Kritchevsky, Stephen; Liu, Yongmei; London, Stephanie; Niu, Liang; Wilson, Robert S; De Jager, Philip L; Yu, Lei; Singleton, Andrew B; Harris, Tamara; Mosley, Thomas H; Pinto, Jayant M; Bennett, David A; Chen, Honglei

2015-11-01

Olfactory dysfunction is common among older adults and affects their safety, nutrition, quality of life, and mortality. More importantly, the decreased sense of smell is an early symptom of neurodegenerative diseases such as Parkinson disease (PD) and Alzheimer disease. However, the genetic determinants for the sense of smell have been poorly investigated. We here performed the first genome-wide meta-analysis on the sense of smell among 6252 US older adults of European descent from the Atherosclerosis Risk in Communities (ARIC) study, the Health, Aging, and Body Composition (Health ABC) study, and the Religious Orders Study and the Rush Memory and Aging Project (ROS/MAP). Genome-wide association study analysis was performed first by individual cohorts and then meta-analyzed using fixed-effect models with inverse variance weights. Although no SNPs reached genome-wide statistical significance, we identified 13 loci with suggestive evidence for an association with the sense of smell (Pmeta < 1 × 10). Of these, 2 SNPs at chromosome 17q21.31 (rs199443 in NSF, P = 3.02 × 10; and rs2732614 in KIAA1267-LRRC37A, P = 6.65 × 10) exhibited cis effects on the expression of microtubule-associated protein tau (MAPT, 17q21.31) in 447 frontal-cortex samples obtained postmortem and profiled by RNA-seq (P < 1 × 10). Gene-based and pathway-enrichment analyses further implicated MAPT in regulating the sense of smell in older adults. Similar results were obtained after excluding participants who reported a physician-diagnosed PD or use of PD medications. In conclusion, we provide preliminary evidence that the MAPT locus may play a role in regulating the sense of smell in older adults and therefore offer a potential genetic link between poor sense of smell and major neurodegenerative diseases.

Genome-wide DNA methylation patterns and transcription analysis in sheep muscle.

Directory of Open Access Journals (Sweden)

Christine Couldrey

Full Text Available DNA methylation plays a central role in regulating many aspects of growth and development in mammals through regulating gene expression. The development of next generation sequencing technologies have paved the way for genome-wide, high resolution analysis of DNA methylation landscapes using methodology known as reduced representation bisulfite sequencing (RRBS. While RRBS has proven to be effective in understanding DNA methylation landscapes in humans, mice, and rats, to date, few studies have utilised this powerful method for investigating DNA methylation in agricultural animals. Here we describe the utilisation of RRBS to investigate DNA methylation in sheep Longissimus dorsi muscles. RRBS analysis of ∼1% of the genome from Longissimus dorsi muscles provided data of suitably high precision and accuracy for DNA methylation analysis, at all levels of resolution from genome-wide to individual nucleotides. Combining RRBS data with mRNAseq data allowed the sheep Longissimus dorsi muscle methylome to be compared with methylomes from other species. While some species differences were identified, many similarities were observed between DNA methylation patterns in sheep and other more commonly studied species. The RRBS data presented here highlights the complexity of epigenetic regulation of genes. However, the similarities observed across species are promising, in that knowledge gained from epigenetic studies in human and mice may be applied, with caution, to agricultural species. The ability to accurately measure DNA methylation in agricultural animals will contribute an additional layer of information to the genetic analyses currently being used to maximise production gains in these species.

Genome-wide association genetics of an adaptive trait in lodgepole pine.

Science.gov (United States)

Parchman, Thomas L; Gompert, Zachariah; Mudge, Joann; Schilkey, Faye D; Benkman, Craig W; Buerkle, C Alex

2012-06-01

Pine cones that remain closed and retain seeds until fire causes the cones to open (cone serotiny) represent a key adaptive trait in a variety of pine species. In lodgepole pine, there is substantial geographical variation in serotiny across the Rocky Mountain region. This variation in serotiny has evolved as a result of geographically divergent selection, with consequences that extend to forest communities and ecosystems. An understanding of the genetic architecture of this trait is of interest owing to the wide-reaching ecological consequences of serotiny and also because of the repeated evolution of the trait across the genus. Here, we present and utilize an inexpensive and time-effective method for generating population genomic data. The method uses restriction enzymes and PCR amplification to generate a library of fragments that can be sequenced with a high level of multiplexing. We obtained data for more than 95,000 single nucleotide polymorphisms across 98 serotinous and nonserotinous lodgepole pines from three populations. We used a Bayesian generalized linear model (GLM) to test for an association between genotypic variation at these loci and serotiny. The probability of serotiny varied by genotype at 11 loci, and the association between genotype and serotiny at these loci was consistent in each of the three populations of pines. Genetic variation across these 11 loci explained 50% of the phenotypic variation in serotiny. Our results provide a first genome-wide association map of serotiny in pines and demonstrate an inexpensive and efficient method for generating population genomic data. © 2012 Blackwell Publishing Ltd.

Genome-wide association study of antisocial personality disorder.

Science.gov (United States)

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

2016-09-06

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

Genome-wide association study of antisocial personality disorder

Science.gov (United States)

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

2016-01-01

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

Investigating Drought Tolerance in Chickpea Using Genome-Wide Association Mapping and Genomic Selection Based on Whole-Genome Resequencing Data.

Science.gov (United States)

Li, Yongle; Ruperao, Pradeep; Batley, Jacqueline; Edwards, David; Khan, Tanveer; Colmer, Timothy D; Pang, Jiayin; Siddique, Kadambot H M; Sutton, Tim

2018-01-01

Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought tolerant varieties. Using a whole-genome resequencing approach, we sequenced 132 chickpea varieties and advanced breeding lines and found more than 144,000 single nucleotide polymorphisms (SNPs). We measured 13 yield and yield-related traits in three drought-prone environments of Western Australia. The genotypic effects were significant for all traits, and many traits showed highly significant correlations, ranging from 0.83 between grain yield and biomass to -0.67 between seed weight and seed emergence rate. To identify candidate genes, the SNP and trait data were incorporated into the SUPER genome-wide association study (GWAS) model, a modified version of the linear mixed model. We found that several SNPs from auxin-related genes, including auxin efflux carrier protein (PIN3), p-glycoprotein, and nodulin MtN21/EamA-like transporter, were significantly associated with yield and yield-related traits under drought-prone environments. We identified four genetic regions containing SNPs significantly associated with several different traits, which was an indication of pleiotropic effects. We also investigated the possibility of incorporating the GWAS results into a genomic selection (GS) model, which is another approach to deal with complex traits. Compared to using all SNPs, application of the GS model using subsets of SNPs significantly associated with the traits under investigation increased the prediction accuracies of three yield and yield-related traits by more than twofold. This has important implication for implementing GS in plant breeding programs.

Genome-wide association study identifies five new schizophrenia loci

NARCIS (Netherlands)

Ripke, S.; Sanders, A. R.; Kendler, K. S.; Levinson, D. F.; Sklar, P.; Holmans, P. A.; Lin, D. Y.; Duan, J.; Ophoff, R. A.; Andreassen, O. A.; Scolnick, E.; Cichon, S.; St Clair, D.; Corvin, A.; Gurling, H.; Werge, T.; Rujescu, D.; Blackwood, D. H.; Pato, C. N.; Malhotra, A. K.; Purcell, S.; Dudbridge, F.; Neale, B. M.; Rossin, L.; Visscher, P. M.; Posthuma, D.; Ruderfer, D. M.; Fanous, A.; Stefansson, H.; Steinberg, S.; Mowry, B. J.; Golimbet, V.; de Hert, M.; Jonsson, E. G.; Bitter, I.; Pietilainen, O. P.; Collier, D. A.; Tosato, S.; Agartz, I.; Albus, M.; Alexander, M.; Amdur, R. L.; Amin, F.; Bass, N.; Bergen, S. E.; Black, D. W.; Borglum, A. D.; Brown, M. A.; Bruggeman, R.; Buccola, N. G.; Byerley, W. F.; Cahn, W.; Cantor, R. M.; Carr, V. J.; Catts, S. V.; Choudhury, K.; Cloninger, C. R.; Cormican, P.; Craddock, N.; Danoy, P. A.; Datta, S.; de Haan, L.; Demontis, D.; Dikeos, D.; Djurovic, S.; Donnely, P.; Donohoe, G.; Duong, L.; Dwyer, S.; Fink-Jensen, A.; Freedman, R.; Freimer, N. B.; Friedl, M.; Georgieva, L.; Giegling, I.; Gill, M.; Glenthoj, B.; Godard, S.; Hamshere, M.; Hansen, M.; Hartmann, A. M.; Henskens, F. A.; Hougaard, D. M.; Hultman, C. M.; Ingason, A.; Jablensky, A. V.; Jakobsen, K. D.; Jay, M.; Jurgens, G.; Kahn, R. S.; Keller, M. C.; Kenis, G.; Kenny, E.; Kim, Y.; Kirov, G. K.; Konnerth, H.; Konte, B.; Krabbendam, L.; Krasucki, R.; Lasseter, V. K.; Laurent, C.; Lawrence, J.; Lencz, T.; Lerer, F. B.; Liang, K. Y.; Lichtenstein, P.; Lieberman, J. A.; Linszen, D. H.; Lonnqvist, J.; Loughland, C. M.; Maclean, A. W.; Maher, B. S.; Maier, W.; Mallet, J.; Malloy, P.; Mattheisen, M.; Mattingsdal, M.; McGhee, K. A.; McGrath, J. J.; McIntosh, A.; McLean, D. E.; McQuillin, A.; Melle, I.; Michie, P. T.; Milanova, V.; Morris, D. W.; Mors, O.; Mortensen, P. B.; Moskvina, V.; Muglia, P.; Myin-Germeys, I.; Nertney, D. A.; Nestadt, G.; Nielsen, J.; Nikolov, I.; Nordentoft, M.; Norton, N.; Nothen, M. M.; O'Dushlaine, C. T.; Olincy, A.; Olsen, L.; O'Neill, F. A.; Orntoft, T. F.; Owen, M. J.; Pantelis, C.; Papadimitriou, G.; Pato, M. T.; Peltonen, L.; Petursson, H.; Pickard, B.; Pimm, J.; Pulver, A. E.; Puri, V.; Quested, D.; Quinn, E. M.; Rasmussen, H. B.; Rethelyi, J. M.; Ribble, R.; Rietschel, M.; Riley, B. P.; Ruggeri, M.; Schall, U.; Schulze, T. G.; Schwab, S. G.; Scott, R. J.; Shi, J.; Sigurdsson, E.; Silvermann, J. M.; Spencer, C. C.; Stefansson, K.; Strange, A.; Strengman, E.; Stroup, T. S.; Suvisaari, J.; Terenius, L.; Thirumalai, S.; Thygesen, J. H.; Timm, S.; Toncheva, D.; van den Oord, E.; van Os, J.; van Winkel, R.; Veldink, J.; Walsh, D.; Wang, A. G.; Wiersma, D.; Wildenauer, D. B.; Williams, H. J.; Williams, N. M.; Wormley, B.; Zammit, S.; Sullivan, P. F.; O'Donovan, M. C.; Daly, M. J.; Gejman, P. V.

2011-01-01

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

Genome-environment interactions and prospective technology assessment: evolution from pharmacogenomics to nutrigenomics and ecogenomics.

Science.gov (United States)

Ozdemir, Vural; Motulsky, Arno G; Kolker, Eugene; Godard, Béatrice

2009-02-01

The relationships between food, nutrition science, and health outcomes have been mapped over the past century. Genomic variation among individuals and populations is a new factor that enriches and challenges our understanding of these complex relationships. Hence, the confluence of nutritional science and genomics-nutrigenomics--was the focus of the OMICS: A Journal of Integrative Biology in December 2008 (Part 1). The 2009 Special Issue (Part 2) concludes the analysis of nutrigenomics research and innovations. Together, these two issues expand the scope and depth of critical scholarship in nutrigenomics, in keeping with an integrated multidisciplinary analysis across the bioscience, omics technology, social, ethical, intellectual property and policy dimensions. Historically, the field of pharmacogenetics provided the first examples of specifically identifiable gene variants predisposing to unexpected responses to drugs since the 1950s. Brewer coined the term ecogenetics in 1971 to broaden the concept of gene-environment interactions from drugs and nutrition to include environmental agents in general. In the mid-1990s, introduction of high-throughput technologies led to the terms pharmacogenomics, nutrigenomics and ecogenomics to describe, respectively, the contribution of genomic variability to differential responses to drugs, food, and environment defined in the broadest sense. The distinctions, if any, between these newer fields (e.g., nutrigenomics) and their predecessors (e.g., nutrigenetics) remain to be delineated. For nutrigenomics, its reliance on genome-wide analyses may lead to detection of new biological mechanisms governing host response to food. Recognizing "genome-environment interactions" as the conceptual thread that connects and runs through pharmacogenomics, nutrigenomics, and ecogenomics may contribute toward anticipatory governance and prospective real-time analysis of these omics fields. Such real-time analysis of omics technologies and

Comparison of genome-wide selection strategies to identify furfural tolerance genes in Escherichia coli.

Science.gov (United States)

Glebes, Tirzah Y; Sandoval, Nicholas R; Gillis, Jacob H; Gill, Ryan T

2015-01-01

Engineering both feedstock and product tolerance is important for transitioning towards next-generation biofuels derived from renewable sources. Tolerance to chemical inhibitors typically results in complex phenotypes, for which multiple genetic changes must often be made to confer tolerance. Here, we performed a genome-wide search for furfural-tolerant alleles using the TRackable Multiplex Recombineering (TRMR) method (Warner et al. (2010), Nature Biotechnology), which uses chromosomally integrated mutations directed towards increased or decreased expression of virtually every gene in Escherichia coli. We employed various growth selection strategies to assess the role of selection design towards growth enrichments. We also compared genes with increased fitness from our TRMR selection to those from a previously reported genome-wide identification study of furfural tolerance genes using a plasmid-based genomic library approach (Glebes et al. (2014) PLOS ONE). In several cases, growth improvements were observed for the chromosomally integrated promoter/RBS mutations but not for the plasmid-based overexpression constructs. Through this assessment, four novel tolerance genes, ahpC, yhjH, rna, and dicA, were identified and confirmed for their effect on improving growth in the presence of furfural. © 2014 Wiley Periodicals, Inc.

Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

DEFF Research Database (Denmark)

Zillikens, M Carola; Demissie, Serkalem; Hsu, Yi-Hsiang

2017-01-01

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorpt...... a meta-analysis of genome-wide association studies for whole body lean body mass and find five novel genetic loci to be significantly associated.......-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p 

Non-replication study of a genome-wide association study for hypertension and blood pressure in African Americans

Directory of Open Access Journals (Sweden)

Kidambi Srividya

2012-04-01

Full Text Available Abstract Background A recent genome wide association study in 1017 African Americans identified several single nucleotide polymorphisms that reached genome-wide significance for systolic blood pressure. We attempted to replicate these findings in an independent sample of 2474 unrelated African Americans in the Milwaukee metropolitan area; 53% were women and 47% were hypertensives. Methods We evaluated sixteen top associated SNPs from the above genome wide association study for hypertension as a binary trait or blood pressure as a continuous trait. In addition, we evaluated eight single nucleotide polymorphisms located in two genes (STK-39 and CDH-13 found to be associated with systolic and diastolic blood pressures by other genome wide association studies in European and Amish populations. TaqMan MGB-based chemistry with fluorescent probes was used for genotyping. We had an adequate sample size (80% power to detect an effect size of 1.2-2.0 for all the single nucleotide polymorphisms for hypertension as a binary trait, and 1% variance in blood pressure as a continuous trait. Quantitative trait analyses were performed both by excluding and also by including subjects on anti-hypertensive therapy (after adjustments were made for anti-hypertensive medications. Results For all 24 SNPs, no statistically significant differences were noted in the minor allele frequencies between cases and controls. One SNP (rs2146204 showed borderline association (p = 0.006 with hypertension status using recessive model and systolic blood pressure (p = 0.02, but was not significant after adjusting for multiple comparisons. In quantitative trait analyses, among normotensives only, rs12748299 was associated with SBP (p = 0.002. In addition, several nominally significant associations were noted with SBP and DBP among normotensives but none were statistically significant. Conclusions This study highlights the importance of replication to confirm the validity of genome wide

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

Directory of Open Access Journals (Sweden)

Sungkyoung Choi

2016-12-01

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

Genomic consequences of selection and genome-wide association mapping in soybean.

Science.gov (United States)

Wen, Zixiang; Boyse, John F; Song, Qijian; Cregan, Perry B; Wang, Dechun

2015-09-03

Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits. To this end, two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms (SNPs), and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio (XP-CLR) method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies (GWAS) were conducted on 7 selection traits targeted in soybean breeding (grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content) and 2 non-selection traits (pubescence and flower color). Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified. These findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.

GST-PRIME: an algorithm for genome-wide primer design.

Science.gov (United States)

Leister, Dario; Varotto, Claudio

2007-01-01

The profiling of mRNA expression based on DNA arrays has become a powerful tool to study genome-wide transcription of genes in a number of organisms. GST-PRIME is a software package created to facilitate large-scale primer design for the amplification of probes to be immobilized on arrays for transcriptome analyses, even though it can be also applied in low-throughput approaches. GST-PRIME allows highly efficient, direct amplification of gene-sequence tags (GSTs) from genomic DNA (gDNA), starting from annotated genome or transcript sequences. GST-PRIME provides a customer-friendly platform for automatic primer design, and despite the relative simplicity of the algorithm, experimental tests in the model plant species Arabidopsis thaliana confirmed the reliability of the software. This chapter describes the algorithm used for primer design, its input and output files, and the installation of the standalone package and its use.

Viral dark matter and virus–host interactions resolved from publicly available microbial genomes

Science.gov (United States)

Roux, Simon; Hallam, Steven J; Woyke, Tanja; Sullivan, Matthew B

2015-01-01

The ecological importance of viruses is now widely recognized, yet our limited knowledge of viral sequence space and virus–host interactions precludes accurate prediction of their roles and impacts. In this study, we mined publicly available bacterial and archaeal genomic data sets to identify 12,498 high-confidence viral genomes linked to their microbial hosts. These data augment public data sets 10-fold, provide first viral sequences for 13 new bacterial phyla including ecologically abundant phyla, and help taxonomically identify 7–38% of ‘unknown’ sequence space in viromes. Genome- and network-based classification was largely consistent with accepted viral taxonomy and suggested that (i) 264 new viral genera were identified (doubling known genera) and (ii) cross-taxon genomic recombination is limited. Further analyses provided empirical data on extrachromosomal prophages and coinfection prevalences, as well as evaluation of in silico virus–host linkage predictions. Together these findings illustrate the value of mining viral signal from microbial genomes. DOI: http://dx.doi.org/10.7554/eLife.08490.001 PMID:26200428

Single-cell Hi-C for genome-wide detection of chromatin interactions that occur simultaneously in a single cell.

Science.gov (United States)

Nagano, Takashi; Lubling, Yaniv; Yaffe, Eitan; Wingett, Steven W; Dean, Wendy; Tanay, Amos; Fraser, Peter

2015-12-01

Hi-C is a powerful method that provides pairwise information on genomic regions in spatial proximity in the nucleus. Hi-C requires millions of cells as input and, as genome organization varies from cell to cell, a limitation of Hi-C is that it only provides a population average of genome conformations. We developed single-cell Hi-C to create snapshots of thousands of chromatin interactions that occur simultaneously in a single cell. To adapt Hi-C to single-cell analysis, we modified the protocol to include in-nucleus ligation. This enables the isolation of single nuclei carrying Hi-C-ligated DNA into separate tubes, followed by reversal of cross-links, capture of biotinylated ligation junctions on streptavidin-coated magnetic beads and PCR amplification of single-cell Hi-C libraries. The entire laboratory protocol can be carried out in 1 week, and although we have demonstrated its use in mouse T helper (TH1) cells, it should be applicable to any cell type or species for which standard Hi-C has been successful. We also developed an analysis pipeline to filter noise and assess the quality of data sets in a few hours. Although the interactome maps produced by single-cell Hi-C are sparse, the data provide useful information to understand cellular variability in nuclear genome organization and chromosome structure. Standard wet and dry laboratory skills in molecular biology and computational analysis are required.

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

Science.gov (United States)

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

2016-08-01

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

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits.

Science.gov (United States)

Justice, Anne E; Winkler, Thomas W; Feitosa, Mary F; Graff, Misa; Fisher, Virginia A; Young, Kristin; Barata, Llilda; Deng, Xuan; Czajkowski, Jacek; Hadley, David; Ngwa, Julius S; Ahluwalia, Tarunveer S; Chu, Audrey Y; Heard-Costa, Nancy L; Lim, Elise; Perez, Jeremiah; Eicher, John D; Kutalik, Zoltán; Xue, Luting; Mahajan, Anubha; Renström, Frida; Wu, Joseph; Qi, Qibin; Ahmad, Shafqat; Alfred, Tamuno; Amin, Najaf; Bielak, Lawrence F; Bonnefond, Amelie; Bragg, Jennifer; Cadby, Gemma; Chittani, Martina; Coggeshall, Scott; Corre, Tanguy; Direk, Nese; Eriksson, Joel; Fischer, Krista; Gorski, Mathias; Neergaard Harder, Marie; Horikoshi, Momoko; Huang, Tao; Huffman, Jennifer E; Jackson, Anne U; Justesen, Johanne Marie; Kanoni, Stavroula; Kinnunen, Leena; Kleber, Marcus E; Komulainen, Pirjo; Kumari, Meena; Lim, Unhee; Luan, Jian'an; Lyytikäinen, Leo-Pekka; Mangino, Massimo; Manichaikul, Ani; Marten, Jonathan; Middelberg, Rita P S; Müller-Nurasyid, Martina; Navarro, Pau; Pérusse, Louis; Pervjakova, Natalia; Sarti, Cinzia; Smith, Albert Vernon; Smith, Jennifer A; Stančáková, Alena; Strawbridge, Rona J; Stringham, Heather M; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W; van der Most, Peter J; Van Vliet-Ostaptchouk, Jana V; Vedantam, Sailaja L; Verweij, Niek; Vink, Jacqueline M; Vitart, Veronique; Wu, Ying; Yengo, Loic; Zhang, Weihua; Hua Zhao, Jing; Zimmermann, Martina E; Zubair, Niha; Abecasis, Gonçalo R; Adair, Linda S; Afaq, Saima; Afzal, Uzma; Bakker, Stephan J L; Bartz, Traci M; Beilby, John; Bergman, Richard N; Bergmann, Sven; Biffar, Reiner; Blangero, John; Boerwinkle, Eric; Bonnycastle, Lori L; Bottinger, Erwin; Braga, Daniele; Buckley, Brendan M; Buyske, Steve; Campbell, Harry; Chambers, John C; Collins, Francis S; Curran, Joanne E; de Borst, Gert J; de Craen, Anton J M; de Geus, Eco J C; Dedoussis, George; Delgado, Graciela E; den Ruijter, Hester M; Eiriksdottir, Gudny; Eriksson, Anna L; Esko, Tõnu; Faul, Jessica D; Ford, Ian; Forrester, Terrence; Gertow, Karl; Gigante, Bruna; Glorioso, Nicola; Gong, Jian; Grallert, Harald; Grammer, Tanja B; Grarup, Niels; Haitjema, Saskia; Hallmans, Göran; Hamsten, Anders; Hansen, Torben; Harris, Tamara B; Hartman, Catharina A; Hassinen, Maija; Hastie, Nicholas D; Heath, Andrew C; Hernandez, Dena; Hindorff, Lucia; Hocking, Lynne J; Hollensted, Mette; Holmen, Oddgeir L; Homuth, Georg; Jan Hottenga, Jouke; Huang, Jie; Hung, Joseph; Hutri-Kähönen, Nina; Ingelsson, Erik; James, Alan L; Jansson, John-Olov; Jarvelin, Marjo-Riitta; Jhun, Min A; Jørgensen, Marit E; Juonala, Markus; Kähönen, Mika; Karlsson, Magnus; Koistinen, Heikki A; Kolcic, Ivana; Kolovou, Genovefa; Kooperberg, Charles; Krämer, Bernhard K; Kuusisto, Johanna; Kvaløy, Kirsti; Lakka, Timo A; Langenberg, Claudia; Launer, Lenore J; Leander, Karin; Lee, Nanette R; Lind, Lars; Lindgren, Cecilia M; Linneberg, Allan; Lobbens, Stephane; Loh, Marie; Lorentzon, Mattias; Luben, Robert; Lubke, Gitta; Ludolph-Donislawski, Anja; Lupoli, Sara; Madden, Pamela A F; Männikkö, Reija; Marques-Vidal, Pedro; Martin, Nicholas G; McKenzie, Colin A; McKnight, Barbara; Mellström, Dan; Menni, Cristina; Montgomery, Grant W; Musk, Aw Bill; Narisu, Narisu; Nauck, Matthias; Nolte, Ilja M; Oldehinkel, Albertine J; Olden, Matthias; Ong, Ken K; Padmanabhan, Sandosh; Peyser, Patricia A; Pisinger, Charlotta; Porteous, David J; Raitakari, Olli T; Rankinen, Tuomo; Rao, D C; Rasmussen-Torvik, Laura J; Rawal, Rajesh; Rice, Treva; Ridker, Paul M; Rose, Lynda M; Bien, Stephanie A; Rudan, Igor; Sanna, Serena; Sarzynski, Mark A; Sattar, Naveed; Savonen, Kai; Schlessinger, David; Scholtens, Salome; Schurmann, Claudia; Scott, Robert A; Sennblad, Bengt; Siemelink, Marten A; Silbernagel, Günther; Slagboom, P Eline; Snieder, Harold; Staessen, Jan A; Stott, David J; Swertz, Morris A; Swift, Amy J; Taylor, Kent D; Tayo, Bamidele O; Thorand, Barbara; Thuillier, Dorothee; Tuomilehto, Jaakko; Uitterlinden, Andre G; Vandenput, Liesbeth; Vohl, Marie-Claude; Völzke, Henry; Vonk, Judith M; Waeber, Gérard; Waldenberger, Melanie; Westendorp, R G J; Wild, Sarah; Willemsen, Gonneke; Wolffenbuttel, Bruce H R; Wong, Andrew; Wright, Alan F; Zhao, Wei; Zillikens, M Carola; Baldassarre, Damiano; Balkau, Beverley; Bandinelli, Stefania; Böger, Carsten A; Boomsma, Dorret I; Bouchard, Claude; Bruinenberg, Marcel; Chasman, Daniel I; Chen, Yii-DerIda; Chines, Peter S; Cooper, Richard S; Cucca, Francesco; Cusi, Daniele; Faire, Ulf de; Ferrucci, Luigi; Franks, Paul W; Froguel, Philippe; Gordon-Larsen, Penny; Grabe, Hans-Jörgen; Gudnason, Vilmundur; Haiman, Christopher A; Hayward, Caroline; Hveem, Kristian; Johnson, Andrew D; Wouter Jukema, J; Kardia, Sharon L R; Kivimaki, Mika; Kooner, Jaspal S; Kuh, Diana; Laakso, Markku; Lehtimäki, Terho; Marchand, Loic Le; März, Winfried; McCarthy, Mark I; Metspalu, Andres; Morris, Andrew P; Ohlsson, Claes; Palmer, Lyle J; Pasterkamp, Gerard; Pedersen, Oluf; Peters, Annette; Peters, Ulrike; Polasek, Ozren; Psaty, Bruce M; Qi, Lu; Rauramaa, Rainer; Smith, Blair H; Sørensen, Thorkild I A; Strauch, Konstantin; Tiemeier, Henning; Tremoli, Elena; van der Harst, Pim; Vestergaard, Henrik; Vollenweider, Peter; Wareham, Nicholas J; Weir, David R; Whitfield, John B; Wilson, James F; Tyrrell, Jessica; Frayling, Timothy M; Barroso, Inês; Boehnke, Michael; Deloukas, Panagiotis; Fox, Caroline S; Hirschhorn, Joel N; Hunter, David J; Spector, Tim D; Strachan, David P; van Duijn, Cornelia M; Heid, Iris M; Mohlke, Karen L; Marchini, Jonathan; Loos, Ruth J F; Kilpeläinen, Tuomas O; Liu, Ching-Ti; Borecki, Ingrid B; North, Kari E; Cupples, L Adrienne

2017-04-26

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

Genome-Wide Requirements for Resistance to Functionally Distinct DNA-Damaging Agents.

Directory of Open Access Journals (Sweden)

2005-08-01

Full Text Available The mechanistic and therapeutic differences in the cellular response to DNA-damaging compounds are not completely understood, despite intense study. To expand our knowledge of DNA damage, we assayed the effects of 12 closely related DNA-damaging agents on the complete pool of ~4,700 barcoded homozygous deletion strains of Saccharomyces cerevisiae. In our protocol, deletion strains are pooled together and grown competitively in the presence of compound. Relative strain sensitivity is determined by hybridization of PCR-amplified barcodes to an oligonucleotide array carrying the barcode complements. These screens identified genes in well-characterized DNA-damage-response pathways as well as genes whose role in the DNA-damage response had not been previously established. High-throughput individual growth analysis was used to independently confirm microarray results. Each compound produced a unique genome-wide profile. Analysis of these data allowed us to determine the relative importance of DNA-repair modules for resistance to each of the 12 profiled compounds. Clustering the data for 12 distinct compounds uncovered both known and novel functional interactions that comprise the DNA-damage response and allowed us to define the genetic determinants required for repair of interstrand cross-links. Further genetic analysis allowed determination of epistasis for one of these functional groups.

Genome-wide meta-analysis of cerebral white matter hyperintensities in patients with stroke

NARCIS (Netherlands)

Traylor, M.; Zhang, C.R.; Adib-Samii, P.; Devan, W.J.; Parsons, O.E.; Lanfranconi, S.; Gregory, S.; Cloonan, L.; Falcone, G.J.; Radmanesh, F.; Fitzpatrick, K.; Kanakis, A.; Barrick, T.R.; Moynihan, B.; Lewis, C.M.; Boncoraglio, G.B.; Lemmens, R.; Thijs, V.; Sudlow, C.; Wardlaw, J.; Rothwell, P.M.; Meschia, J.F.; Worrall, B.B.; Levi, C.; Bevan, S.; Furie, K.L.; Dichgans, M.; Rosand, J.; Markus, H.S.; Rost, N.; Klijn, C.J.M.; et al.,

2016-01-01

OBJECTIVE: For 3,670 stroke patients from the United Kingdom, United States, Australia, Belgium, and Italy, we performed a genome-wide meta-analysis of white matter hyperintensity volumes (WMHV) on data imputed to the 1000 Genomes reference dataset to provide insights into disease mechanisms.

Genome-wide association study of serum selenium concentrations

DEFF Research Database (Denmark)

Gong, Jian; Hsu, Li; Harrison, Tabitha

2013-01-01

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

Genome-Wide Fine-Scale Recombination Rate Variation in Drosophila melanogaster

Science.gov (United States)

Song, Yun S.

2012-01-01

Estimating fine-scale recombination maps of Drosophila from population genomic data is a challenging problem, in particular because of the high background recombination rate. In this paper, a new computational method is developed to address this challenge. Through an extensive simulation study, it is demonstrated that the method allows more accurate inference, and exhibits greater robustness to the effects of natural selection and noise, compared to a well-used previous method developed for studying fine-scale recombination rate variation in the human genome. As an application, a genome-wide analysis of genetic variation data is performed for two Drosophila melanogaster populations, one from North America (Raleigh, USA) and the other from Africa (Gikongoro, Rwanda). It is shown that fine-scale recombination rate variation is widespread throughout the D. melanogaster genome, across all chromosomes and in both populations. At the fine-scale, a conservative, systematic search for evidence of recombination hotspots suggests the existence of a handful of putative hotspots each with at least a tenfold increase in intensity over the background rate. A wavelet analysis is carried out to compare the estimated recombination maps in the two populations and to quantify the extent to which recombination rates are conserved. In general, similarity is observed at very broad scales, but substantial differences are seen at fine scales. The average recombination rate of the X chromosome appears to be higher than that of the autosomes in both populations, and this pattern is much more pronounced in the African population than the North American population. The correlation between various genomic features—including recombination rates, diversity, divergence, GC content, gene content, and sequence quality—is examined using the wavelet analysis, and it is shown that the most notable difference between D. melanogaster and humans is in the correlation between recombination and

A PLSPM-Based Test Statistic for Detecting Gene-Gene Co-Association in Genome-Wide Association Study with Case-Control Design

Science.gov (United States)

Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong

2013-01-01

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods. PMID:23620809

Harnessing Omics Big Data in Nine Vertebrate Species by Genome-Wide Prioritization of Sequence Variants with the Highest Predicted Deleterious Effect on Protein Function.

Science.gov (United States)

Rozman, Vita; Kunej, Tanja

2018-05-10

Harnessing the genomics big data requires innovation in how we extract and interpret biologically relevant variants. Currently, there is no established catalog of prioritized missense variants associated with deleterious protein function phenotypes. We report in this study, to the best of our knowledge, the first genome-wide prioritization of sequence variants with the most deleterious effect on protein function (potentially deleterious variants [pDelVars]) in nine vertebrate species: human, cattle, horse, sheep, pig, dog, rat, mouse, and zebrafish. The analysis was conducted using the Ensembl/BioMart tool. Genes comprising pDelVars in the highest number of examined species were identified using a Python script. Multiple genomic alignments of the selected genes were built to identify interspecies orthologous potentially deleterious variants, which we defined as the "ortho-pDelVars." Genome-wide prioritization revealed that in humans, 0.12% of the known variants are predicted to be deleterious. In seven out of nine examined vertebrate species, the genes encoding the multiple PDZ domain crumbs cell polarity complex component (MPDZ) and the transforming acidic coiled-coil containing protein 2 (TACC2) comprise pDelVars. Five interspecies ortho-pDelVars were identified in three genes. These findings offer new ways to harness genomics big data by facilitating the identification of functional polymorphisms in humans and animal models and thus provide a future basis for optimization of protocols for whole genome prioritization of pDelVars and screening of orthologous sequence variants. The approach presented here can inform various postgenomic applications such as personalized medicine and multiomics study of health interventions (iatromics).

Genome-wide analysis identifies 12 loci influencing human reproductive behavior

Science.gov (United States)

Barban, Nicola; Jansen, Rick; de Vlaming, Ronald; Vaez, Ahmad; Mandemakers, Jornt J.; Tropf, Felix C.; Shen, Xia; Wilson, James F.; Chasman, Daniel I.; Nolte, Ilja M.; Tragante, Vinicius; van der Laan, Sander W.; Perry, John R. B.; Kong, Augustine; Ahluwalia, Tarunveer; Albrecht, Eva; Yerges-Armstrong, Laura; Atzmon, Gil; Auro, Kirsi; Ayers, Kristin; Bakshi, Andrew; Ben-Avraham, Danny; Berger, Klaus; Bergman, Aviv; Bertram, Lars; Bielak, Lawrence F.; Bjornsdottir, Gyda; Bonder, Marc Jan; Broer, Linda; Bui, Minh; Barbieri, Caterina; Cavadino, Alana; Chavarro, Jorge E; Turman, Constance; Concas, Maria Pina; Cordell, Heather J.; Davies, Gail; Eibich, Peter; Eriksson, Nicholas; Esko, Tõnu; Eriksson, Joel; Falahi, Fahimeh; Felix, Janine F.; Fontana, Mark Alan; Franke, Lude; Gandin, Ilaria; Gaskins, Audrey J.; Gieger, Christian; Gunderson, Erica P.; Guo, Xiuqing; Hayward, Caroline; He, Chunyan; Hofer, Edith; Huang, Hongyan; Joshi, Peter K.; Kanoni, Stavroula; Karlsson, Robert; Kiechl, Stefan; Kifley, Annette; Kluttig, Alexander; Kraft, Peter; Lagou, Vasiliki; Lecoeur, Cecile; Lahti, Jari; Li-Gao, Ruifang; Lind, Penelope A.; Liu, Tian; Makalic, Enes; Mamasoula, Crysovalanto; Matteson, Lindsay; Mbarek, Hamdi; McArdle, Patrick F.; McMahon, George; Meddens, S. Fleur W.; Mihailov, Evelin; Miller, Mike; Missmer, Stacey A.; Monnereau, Claire; van der Most, Peter J.; Myhre, Ronny; Nalls, Mike A.; Nutile, Teresa; Panagiota, Kalafati Ioanna; Porcu, Eleonora; Prokopenko, Inga; Rajan, Kumar B.; Rich-Edwards, Janet; Rietveld, Cornelius A.; Robino, Antonietta; Rose, Lynda M.; Rueedi, Rico; Ryan, Kathy; Saba, Yasaman; Schmidt, Daniel; Smith, Jennifer A.; Stolk, Lisette; Streeten, Elizabeth; Tonjes, Anke; Thorleifsson, Gudmar; Ulivi, Sheila; Wedenoja, Juho; Wellmann, Juergen; Willeit, Peter; Yao, Jie; Yengo, Loic; Zhao, Jing Hua; Zhao, Wei; Zhernakova, Daria V.; Amin, Najaf; Andrews, Howard; Balkau, Beverley; Barzilai, Nir; Bergmann, Sven; Biino, Ginevra; Bisgaard, Hans; Bønnelykke, Klaus; Boomsma, Dorret I.; Buring, Julie E.; Campbell, Harry; Cappellani, Stefania; Ciullo, Marina; Cox, Simon R.; Cucca, Francesco; Daniela, Toniolo; Davey-Smith, George; Deary, Ian J.; Dedoussis, George; Deloukas, Panos; van Duijn, Cornelia M.; de Geus, Eco JC.; Eriksson, Johan G.; Evans, Denis A.; Faul, Jessica D.; Felicita, Sala Cinzia; Froguel, Philippe; Gasparini, Paolo; Girotto, Giorgia; Grabe, Hans-Jörgen; Greiser, Karin Halina; Groenen, Patrick J.F.; de Haan, Hugoline G.; Haerting, Johannes; Harris, Tamara B.; Heath, Andrew C.; Heikkilä, Kauko; Hofman, Albert; Homuth, Georg; Holliday, Elizabeth G; Hopper, John; Hypponen, Elina; Jacobsson, Bo; Jaddoe, Vincent W. V.; Johannesson, Magnus; Jugessur, Astanand; Kähönen, Mika; Kajantie, Eero; Kardia, Sharon L.R.; Keavney, Bernard; Kolcic, Ivana; Koponen, Päivikki; Kovacs, Peter; Kronenberg, Florian; Kutalik, Zoltan; La Bianca, Martina; Lachance, Genevieve; Iacono, William; Lai, Sandra; Lehtimäki, Terho; Liewald, David C; Lindgren, Cecilia; Liu, Yongmei; Luben, Robert; Lucht, Michael; Luoto, Riitta; Magnus, Per; Magnusson, Patrik K.E.; Martin, Nicholas G.; McGue, Matt; McQuillan, Ruth; Medland, Sarah E.; Meisinger, Christa; Mellström, Dan; Metspalu, Andres; Michela, Traglia; Milani, Lili; Mitchell, Paul; Montgomery, Grant W.; Mook-Kanamori, Dennis; de Mutsert, Renée; Nohr, Ellen A; Ohlsson, Claes; Olsen, Jørn; Ong, Ken K.; Paternoster, Lavinia; Pattie, Alison; Penninx, Brenda WJH; Perola, Markus; Peyser, Patricia A.; Pirastu, Mario; Polasek, Ozren; Power, Chris; Kaprio, Jaakko; Raffel, Leslie J.; Räikkönen, Katri; Raitakari, Olli; Ridker, Paul M.; Ring, Susan M.; Roll, Kathryn; Rudan, Igor; Ruggiero, Daniela; Rujescu, Dan; Salomaa, Veikko; Schlessinger, David; Schmidt, Helena; Schmidt, Reinhold; Schupf, Nicole; Smit, Johannes; Sorice, Rossella; Spector, Tim D.; Starr, John M.; Stöckl, Doris; Strauch, Konstantin; Stumvoll, Michael; Swertz, Morris A.; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tönjes, Anke; Tung, Joyce Y.; Uitterlinden, André G.; Vaccargiu, Simona; Viikari, Jorma; Vitart, Veronique; Völzke, Henry; Vollenweider, Peter; Vuckovic, Dragana; Waage, Johannes; Wagner, Gert G.; Wang, Jie Jin; Wareham, Nicholas J.; Weir, David R.; Willemsen, Gonneke; Willeit, Johann; Wright, Alan F.; Zondervan, Krina T.; Stefansson, Kari; Krueger, Robert F.; Lee, James J.; Benjamin, Daniel J.; Cesarini, David; Koellinger, Philipp D.; den Hoed, Marcel; Snieder, Harold; Mills, Melinda C.

2017-01-01

The genetic architecture of human reproductive behavior – age at first birth (AFB) and number of children ever born (NEB) – has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified and the underlying mechanisms of AFB and NEB are poorly understood. We report the largest genome-wide association study to date of both sexes including 251,151 individuals for AFB and 343,072 for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study, and four additional loci in a gene-based effort. These loci harbor genes that are likely to play a role – either directly or by affecting non-local gene expression – in human reproduction and infertility, thereby increasing our understanding of these complex traits. PMID:27798627

Genetics of Obesity Traits: A Bivariate Genome-Wide Association Analysis

DEFF Research Database (Denmark)

Wu, Yili; Duan, Haiping; Tian, Xiaocao

2018-01-01

Previous genome-wide association studies on anthropometric measurements have identified more than 100 related loci, but only a small portion of heritability in obesity was explained. Here we present a bivariate twin study to look for the genetic variants associated with body mass index and waist......-hip ratio, and to explore the obesity-related pathways in Northern Han Chinese. Cholesky decompositionmodel for 242monozygotic and 140 dizygotic twin pairs indicated a moderate genetic correlation (r = 0.53, 95%CI: 0.42–0.64) between body mass index and waist-hip ratio. Bivariate genome-wide association.......05. Expression quantitative trait loci analysis identified rs2242044 as a significant cis-eQTL in both the normal adipose-subcutaneous (P = 1.7 × 10−9) and adipose-visceral (P = 4.4 × 10−15) tissue. These findings may provide an important entry point to unravel genetic pleiotropy in obesity traits....

Neuropsychological effects of the CSMD1 genome-wide associated schizophrenia risk variant rs10503253.

LENUS (Irish Health Repository)

Donohoe, G

2013-03-01

The single-nucleotide polymorphism (SNP) rs10503253, located within the CUB and Sushi multiple domains-1 (CSMD1) gene on 8p23.2, was recently identified as genome-wide significant for schizophrenia (SZ), but is of unknown function. We investigated the neurocognitive effects of this CSMD1 variant in vivo in patients and healthy participants using behavioral and imaging measures of brain structure and function. We compared carriers and non-carriers of the risk \\'A\\' allele on measures of neuropsychological performance typically impaired in SZ (general cognitive ability, episodic and working memory and attentional control) in independent samples of Irish patients (n = 387) and controls (n = 171) and German patients (205) and controls (n = 533). Across these groups, the risk \\'A\\' allele at CSMD1 was associated with deleterious effects across a number of neurocognitive phenotypes. Specifically, the risk allele was associated with poorer performance on neuropsychological measures of general cognitive ability and memory function but not attentional control. These effects, while significant, were subtle, and varied between samples. Consistent with previous evidence suggesting that CSMD1 may be involved in brain mechanisms related to memory and learning, these data appear to reflect the deleterious effects of the identified \\'A\\' risk allele on neurocognitive function, possibly as part of the mechanism by which CSMD1 is associated with SZ risk.

Identification of neural outgrowth genes using genome-wide RNAi.

Directory of Open Access Journals (Sweden)

Katharine J Sepp

2008-07-01

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

DNA immunoprecipitation semiconductor sequencing (DIP-SC-seq) as a rapid method to generate genome wide epigenetic signatures

OpenAIRE

Thomson, John P.; Fawkes, Angie; Ottaviano, Raffaele; Hunter, Jennifer M.; Shukla, Ruchi; Mjoseng, Heidi K.; Clark, Richard; Coutts, Audrey; Murphy, Lee; Meehan, Richard R.

2015-01-01

Modification of DNA resulting in 5-methylcytosine (5 mC) or 5-hydroxymethylcytosine (5hmC) has been shown to influence the local chromatin environment and affect transcription. Although recent advances in next generation sequencing technology allow researchers to map epigenetic modifications across the genome, such experiments are often time-consuming and cost prohibitive. Here we present a rapid and cost effective method of generating genome wide DNA modification maps utilising commercially ...

Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers.

Directory of Open Access Journals (Sweden)

Guosheng Su

Full Text Available Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1 a simple additive genetic model (MA, 2 a model including both additive and additive by additive epistatic genetic effects (MAE, 3 a model including both additive and dominance genetic effects (MAD, and 4 a full model including all three genetic components (MAED. Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions.

Genome-wide association scan for variants associated with early-onset prostate cancer.

Directory of Open Access Journals (Sweden)

Ethan M Lange

Full Text Available Prostate cancer is the most common non-skin cancer and the second leading cause of cancer related mortality for men in the United States. There is strong empirical and epidemiological evidence supporting a stronger role of genetics in early-onset prostate cancer. We performed a genome-wide association scan for early-onset prostate cancer. Novel aspects of this study include the focus on early-onset disease (defined as men with prostate cancer diagnosed before age 56 years and use of publically available control genotype data from previous genome-wide association studies. We found genome-wide significant (p<5×10(-8 evidence for variants at 8q24 and 11p15 and strong supportive evidence for a number of previously reported loci. We found little evidence for individual or systematic inflated association findings resulting from using public controls, demonstrating the utility of using public control data in large-scale genetic association studies of common variants. Taken together, these results demonstrate the importance of established common genetic variants for early-onset prostate cancer and the power of including early-onset prostate cancer cases in genetic association studies.

A Probabilistic Genome-Wide Gene Reading Frame Sequence Model

DEFF Research Database (Denmark)

Have, Christian Theil; Mørk, Søren

We introduce a new type of probabilistic sequence model, that model the sequential composition of reading frames of genes in a genome. Our approach extends gene finders with a model of the sequential composition of genes at the genome-level -- effectively producing a sequential genome annotation...... as output. The model can be used to obtain the most probable genome annotation based on a combination of i: a gene finder score of each gene candidate and ii: the sequence of the reading frames of gene candidates through a genome. The model --- as well as a higher order variant --- is developed and tested...... and are evaluated by the effect on prediction performance. Since bacterial gene finding to a large extent is a solved problem it forms an ideal proving ground for evaluating the explicit modeling of larger scale gene sequence composition of genomes. We conclude that the sequential composition of gene reading frames...

Investigating Drought Tolerance in Chickpea Using Genome-Wide Association Mapping and Genomic Selection Based on Whole-Genome Resequencing Data

Directory of Open Access Journals (Sweden)

Yongle Li

2018-02-01

Full Text Available Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought tolerant varieties. Using a whole-genome resequencing approach, we sequenced 132 chickpea varieties and advanced breeding lines and found more than 144,000 single nucleotide polymorphisms (SNPs. We measured 13 yield and yield-related traits in three drought-prone environments of Western Australia. The genotypic effects were significant for all traits, and many traits showed highly significant correlations, ranging from 0.83 between grain yield and biomass to -0.67 between seed weight and seed emergence rate. To identify candidate genes, the SNP and trait data were incorporated into the SUPER genome-wide association study (GWAS model, a modified version of the linear mixed model. We found that several SNPs from auxin-related genes, including auxin efflux carrier protein (PIN3, p-glycoprotein, and nodulin MtN21/EamA-like transporter, were significantly associated with yield and yield-related traits under drought-prone environments. We identified four genetic regions containing SNPs significantly associated with several different traits, which was an indication of pleiotropic effects. We also investigated the possibility of incorporating the GWAS results into a genomic selection (GS model, which is another approach to deal with complex traits. Compared to using all SNPs, application of the GS model using subsets of SNPs significantly associated with the traits under investigation increased the prediction accuracies of three yield and yield-related traits by more than twofold. This has important implication for implementing GS in plant breeding programs.

A genome-wide association study identifies protein quantitative trait loci (pQTLs.

Directory of Open Access Journals (Sweden)

David Melzer

2008-05-01

Full Text Available There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts - cis effects, and elsewhere in the genome - trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8x10(-57, CCL4L1 (p = 3.9x10(-21, IL18 (p = 6.8x10(-13, LPA (p = 4.4x10(-10, GGT1 (p = 1.5x10(-7, SHBG (p = 3.1x10(-7, CRP (p = 6.4x10(-6 and IL1RN (p = 7.3x10(-6 genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R, altered secretion rates of different sized proteins (LPA, variation in gene copy number (CCL4L1 and altered transcription (GGT1. We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha levels (p = 6.8x10(-40, but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis

Genome-Wide Association Study Reveals Greater Polygenic Loading for Schizophrenia in Cases With a Family History of Illness

Science.gov (United States)

Bigdeli, Tim B.; Ripke, Stephan; Bacanu, Silviu-Alin; Lee, Sang Hong; Wray, Naomi R.; Gejman, Pablo V.; Rietschel, Marcella; Cichon, Sven; St Clair, David; Corvin, Aiden; Kirov, George; McQuillin, Andrew; Gurling, Hugh; Rujescu, Dan; Andreassen, Ole A.; Werge, Thomas; Blackwood, Douglas H.R.; Pato, Carlos N.; Pato, Michele T.; Malhotra, Anil K.; O’Donovan, Michael C.; Kendler, Kenneth S.; Fanous, Ayman H.

2018-01-01

Genome-wide association studies (GWAS) of schizophrenia have yielded more than 100 common susceptibility variants, and strongly support a substantial polygenic contribution of a large number of small allelic effects. It has been hypothesized that familial schizophrenia is largely a consequence of inherited rather than environmental factors. We investigated the extent to which familiality of schizophrenia is associated with enrichment for common risk variants detectable in a large GWAS. We analyzed single nucleotide polymorphism (SNP) data for cases reporting a family history of psychotic illness (N = 978), cases reporting no such family history (N = 4,503), and unscreened controls (N = 8,285) from the Psychiatric Genomics Consortium (PGC1) study of schizophrenia. We used a multinomial logistic regression approach with model-fitting to detect allelic effects specific to either family history subgroup. We also considered a polygenic model, in which we tested whether family history positive subjects carried more schizophrenia risk alleles than family history negative subjects, on average. Several individual SNPs attained suggestive but not genome-wide significant association with either family history subgroup. Comparison of genome-wide polygenic risk scores based on GWAS summary statistics indicated a significant enrichment for SNP effects among family history positive compared to family history negative cases (Nagelkerke’s R2 = 0.0021; P = 0.00331; P-value threshold history positive compared to family history negative cases (0.32 and 0.22, respectively; P = 0.031).We found suggestive evidence of allelic effects detectable in large GWAS of schizophrenia that might be specific to particular family history subgroups. However, consideration of a polygenic risk score indicated a significant enrichment among family history positive cases for common allelic effects. Familial illness might, therefore, represent a more heritable form of schizophrenia, as suggested by

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

Directory of Open Access Journals (Sweden)

Flores Kevin

2012-09-01

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

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

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

2012-03-01

Successful reverse engineering of mutants that have been obtained by nontargeted strain improvement has long presented a major challenge in yeast biotechnology. This paper reviews the use of genome-wide approaches for analysis of Saccharomyces cerevisiae strains originating from evolutionary engineering or random mutagenesis. On the basis of an evaluation of the strengths and weaknesses of different methods, we conclude that for the initial identification of relevant genetic changes, whole genome sequencing is superior to other analytical techniques, such as transcriptome, metabolome, proteome, or array-based genome analysis. Key advantages of this technique over gene expression analysis include the independency of genome sequences on experimental context and the possibility to directly and precisely reproduce the identified changes in naive strains. The predictive value of genome-wide analysis of strains with industrially relevant characteristics can be further improved by classical genetics or simultaneous analysis of strains derived from parallel, independent strain improvement lineages. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

TEGS-CN: A Statistical Method for Pathway Analysis of Genome-wide Copy Number Profile.

Science.gov (United States)

Huang, Yen-Tsung; Hsu, Thomas; Christiani, David C

2014-01-01

The effects of copy number alterations make up a significant part of the tumor genome profile, but pathway analyses of these alterations are still not well established. We proposed a novel method to analyze multiple copy numbers of genes within a pathway, termed Test for the Effect of a Gene Set with Copy Number data (TEGS-CN). TEGS-CN was adapted from TEGS, a method that we previously developed for gene expression data using a variance component score test. With additional development, we extend the method to analyze DNA copy number data, accounting for different sizes and thus various numbers of copy number probes in genes. The test statistic follows a mixture of X (2) distributions that can be obtained using permutation with scaled X (2) approximation. We conducted simulation studies to evaluate the size and the power of TEGS-CN and to compare its performance with TEGS. We analyzed a genome-wide copy number data from 264 patients of non-small-cell lung cancer. With the Molecular Signatures Database (MSigDB) pathway database, the genome-wide copy number data can be classified into 1814 biological pathways or gene sets. We investigated associations of the copy number profile of the 1814 gene sets with pack-years of cigarette smoking. Our analysis revealed five pathways with significant P values after Bonferroni adjustment (number data, and causal mechanisms of the five pathways require further study.

A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance

DEFF Research Database (Denmark)

Manning, Alisa K; Hivert, Marie-France; Scott, Robert A

2012-01-01

pathways might be uncovered by accounting for differences in body mass index (BMI) and potential interactions between BMI and genetic variants. We applied a joint meta-analysis approach to test associations with fasting insulin and glucose on a genome-wide scale. We present six previously unknown loci...... associated with fasting insulin at P triglyceride and lower high-density lipoprotein (HDL) cholesterol levels, suggesting a role for these loci...

Efficient genome-wide association in biobanks using topic modeling identifies multiple novel disease loci.

Science.gov (United States)

McCoy, Thomas H; Castro, Victor M; Snapper, Leslie A; Hart, Kamber L; Perlis, Roy H

2017-08-31

Biobanks and national registries represent a powerful tool for genomic discovery, but rely on diagnostic codes that may be unreliable and fail to capture the relationship between related diagnoses. We developed an efficient means of conducting genome-wide association studies using combinations of diagnostic codes from electronic health records (EHR) for 10845 participants in a biobanking program at two large academic medical centers. Specifically, we applied latent Dirichilet allocation to fit 50 disease topics based on diagnostic codes, then conducted genome-wide common-variant association for each topic. In sensitivity analysis, these results were contrasted with those obtained from traditional single-diagnosis phenome-wide association analysis, as well as those in which only a subset of diagnostic codes are included per topic. In meta-analysis across three biobank cohorts, we identified 23 disease-associated loci with p<1e-15, including previously associated autoimmune disease loci. In all cases, observed significant associations were of greater magnitude than for single phenome-wide diagnostic codes, and incorporation of less strongly-loading diagnostic codes enhanced association. This strategy provides a more efficient means of phenome-wide association in biobanks with coded clinical data.

A genome-wide association study implicates the APOE locus in nonpathological cognitive ageing.

Science.gov (United States)

Davies, G; Harris, S E; Reynolds, C A; Payton, A; Knight, H M; Liewald, D C; Lopez, L M; Luciano, M; Gow, A J; Corley, J; Henderson, R; Murray, C; Pattie, A; Fox, H C; Redmond, P; Lutz, M W; Chiba-Falek, O; Linnertz, C; Saith, S; Haggarty, P; McNeill, G; Ke, X; Ollier, W; Horan, M; Roses, A D; Ponting, C P; Porteous, D J; Tenesa, A; Pickles, A; Starr, J M; Whalley, L J; Pedersen, N L; Pendleton, N; Visscher, P M; Deary, I J

2014-01-01

Cognitive decline is a feared aspect of growing old. It is a major contributor to lower quality of life and loss of independence in old age. We investigated the genetic contribution to individual differences in nonpathological cognitive ageing in five cohorts of older adults. We undertook a genome-wide association analysis using 549 692 single-nucleotide polymorphisms (SNPs) in 3511 unrelated adults in the Cognitive Ageing Genetics in England and Scotland (CAGES) project. These individuals have detailed longitudinal cognitive data from which phenotypes measuring each individual's cognitive changes were constructed. One SNP--rs2075650, located in TOMM40 (translocase of the outer mitochondrial membrane 40 homolog)--had a genome-wide significant association with cognitive ageing (P=2.5 × 10(-8)). This result was replicated in a meta-analysis of three independent Swedish cohorts (P=2.41 × 10(-6)). An Apolipoprotein E (APOE) haplotype (adjacent to TOMM40), previously associated with cognitive ageing, had a significant effect on cognitive ageing in the CAGES sample (P=2.18 × 10(-8); females, P=1.66 × 10(-11); males, P=0.01). Fine SNP mapping of the TOMM40/APOE region identified both APOE (rs429358; P=3.66 × 10(-11)) and TOMM40 (rs11556505; P=2.45 × 10(-8)) as loci that were associated with cognitive ageing. Imputation and conditional analyses in the discovery and replication cohorts strongly suggest that this effect is due to APOE (rs429358). Functional genomic analysis indicated that SNPs in the TOMM40/APOE region have a functional, regulatory non-protein-coding effect. The APOE region is significantly associated with nonpathological cognitive ageing. The identity and mechanism of one or multiple causal variants remain unclear.

Genome mining of Streptomyces scabrisporus NF3 reveals symbiotic features including genes related to plant interactions

Science.gov (United States)

Rodríguez-Luna, Stefany Daniela; Cruz Vázquez, Angélica Patricia; Jiménez Suárez, Verónica; Rodríguez-Sanoja, Romina; Alvarez-Buylla, Elena R.; Sánchez, Sergio

2018-01-01

Endophytic bacteria are wide-spread and associated with plant physiological benefits, yet their genomes and secondary metabolites remain largely unidentified. In this study, we explored the genome of the endophyte Streptomyces scabrisporus NF3 for discovery of potential novel molecules as well as genes and metabolites involved in host interactions. The complete genomes of seven Streptomyces and three other more distantly related bacteria were used to define the functional landscape of this unique microbe. The S. scabrisporus NF3 genome is larger than the average Streptomyces genome and not structured for an obligate endosymbiotic lifestyle; this and the fact that can grow in R2YE media implies that it could include a soil-living stage. The genome displays an enrichment of genes associated with amino acid production, protein secretion, secondary metabolite and antioxidants production and xenobiotic degradation, indicating that S. scabrisporus NF3 could contribute to the metabolic enrichment of soil microbial communities and of its hosts. Importantly, besides its metabolic advantages, the genome showed evidence for differential functional specificity and diversification of plant interaction molecules, including genes for the production of plant hormones, stress resistance molecules, chitinases, antibiotics and siderophores. Given the diversity of S. scabrisporus mechanisms for host upkeep, we propose that these strategies were necessary for its adaptation to plant hosts and to face changes in environmental conditions. PMID:29447216

Genome mining of Streptomyces scabrisporus NF3 reveals symbiotic features including genes related to plant interactions.

Directory of Open Access Journals (Sweden)

Corina Diana Ceapă

Full Text Available Endophytic bacteria are wide-spread and associated with plant physiological benefits, yet their genomes and secondary metabolites remain largely unidentified. In this study, we explored the genome of the endophyte Streptomyces scabrisporus NF3 for discovery of potential novel molecules as well as genes and metabolites involved in host interactions. The complete genomes of seven Streptomyces and three other more distantly related bacteria were used to define the functional landscape of this unique microbe. The S. scabrisporus NF3 genome is larger than the average Streptomyces genome and not structured for an obligate endosymbiotic lifestyle; this and the fact that can grow in R2YE media implies that it could include a soil-living stage. The genome displays an enrichment of genes associated with amino acid production, protein secretion, secondary metabolite and antioxidants production and xenobiotic degradation, indicating that S. scabrisporus NF3 could contribute to the metabolic enrichment of soil microbial communities and of its hosts. Importantly, besides its metabolic advantages, the genome showed evidence for differential functional specificity and diversification of plant interaction molecules, including genes for the production of plant hormones, stress resistance molecules, chitinases, antibiotics and siderophores. Given the diversity of S. scabrisporus mechanisms for host upkeep, we propose that these strategies were necessary for its adaptation to plant hosts and to face changes in environmental conditions.

Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network and pathway analyses

DEFF Research Database (Denmark)

Kogelman, Lisette; Pant, Sameer Dinkar; Fredholm, Merete

2014-01-01

.g. metabolic processes. WISH networks based on genotypic correlations allowed further identification of various gene ontology terms and pathways related to obesity and related traits, which were not identified by the GWA study. In conclusion, this is the first study to develop a (genetic) obesity index...... investigations focusing on single genetic variants have achieved limited success, and the importance of including genetic interactions is becoming evident. Here, the aim was to perform an integrative genomic analysis in an F2 pig resource population that was constructed with an aim to maximize genetic variation...... of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA) analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation...

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.

Directory of Open Access Journals (Sweden)

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.

Genome-wide meta-analysis identifies new susceptibility loci for migraine

NARCIS (Netherlands)

Anttila, Verneri; Winsvold, Bendik S.; Gormley, Padhraig; Kurth, Tobias; Bettella, Francesco; McMahon, George; Kallela, Mikko; Malik, Rainer; de Vries, Boukje; Terwindt, Gisela; Medland, Sarah E.; Todt, Unda; McArdle, Wendy L.; Quaye, Lydia; Koiranen, Markku; Ikram, M. Arfan; Lehtimaki, Terho; Stam, Anine H.; Ligthart, Lannie; Wedenoja, Juho; Dunham, Ian; Neale, Benjamin M.; Palta, Priit; Hamalainen, Eija; Schuerks, Markus; Rose, Lynda M.; Buring, Julie E.; Ridker, Paul M.; Steinberg, Stacy; Stefansson, Hreinn; Jakobsson, Finnbogi; Lawlor, Debbie A.; Evans, David M.; Ring, Susan M.; Farkkila, Markus; Artto, Ville; Kaunisto, Mari A.; Freilinger, Tobias; Schoenen, Jean; Frants, Rune R.; Pelzer, Nadine; Weller, Claudia M.; Zielman, Ronald; Heath, Andrew C.; Madden, Pamela A. F.; Montgomery, Grant W.; Martin, Nicholas G.; Borck, Guntram; Goebel, Hartmut; Heinze, Axel

Migraine is the most common brain disorder, affecting approximately 14% of the adult population, but its molecular mechanisms are poorly understood. We report the results of a meta-analysis across 29 genome-wide association studies, including a total of 23,285 individuals with migraine (cases) and

Genome-wide meta-analysis identifies new susceptibility loci for migraine

NARCIS (Netherlands)

Anttila, V.; Winsvold, B.S.; Gormley, P.; Kurth, T.; Bettella, F.; McMahon, G.; Kallela, M.; Malik, R.; de Vries, B.; Terwindt, G.; Medland, S.E.; Todt, U.; McArdle, W.L.; Quaye, L.; Koiranen, M.; Ikram, M.A.; Lehtimäki, T.; Stam, A.H.; Ligthart, R.S.L.; Wedenoja, J.; Dunham, I.; Neale, B. M.; Palta, P.; Hamalainen, E.; Schürks, M.; Rose, L.M.; Buring, J.E.; Ridker, P.M.; Steinberg, S.; Stefansson, H.; Jakobsson, F.; Lawlor, D.A.; Evans, D.M.; Ring, S.M.; Färkkilä, M.; Artto, V.; Kaunisto, M.A.; Freilinger, T.; Schoenen, J.; Frants, R.R.; Pelzer, N.; Weller, C.M.; Zielman, R.; Heath, A.C.; Madden, P.A.F.; Montgomery, G.W.; Martin, N.G.; Borck, G.; Göbel, H.; Heinze, A.; Heinze-Kuhn, K.; Williams, F.M.; Hartikainen, A.-L.; Pouta, A.; van den Ende, J..; Uitterlinden, A.G.; Hofman, A.; Amin, N.; Hottenga, J.J.; Vink, J.M.; Heikkilä, K.; Alexander, M.; Muller-Myhsok, B.; Schreiber, S; Meitinger, T.; Wichmann, H. E.; Aromaa, A.; Eriksson, J.G.; Traynor, B.J.; Trabzuni, D.; Rossin, E.; Lage, K.; Jacobs, S.B.; Gibbs, J.R.; Birney, E.; Kaprio, J.; Penninx, B.W.J.H.; Boomsma, D.I.; van Duijn, C.M.; Raitakari, O.; Jarvelin, M.-R.; Zwart, J.A.; Cherkas, L.; Strachan, D.P.; Kubisch, C.; Ferrari, M.D.; van den Maagdenberg, A.M.J.M.; Dichgans, M.; Wessman, M.; Smith, G.D.; Stefansson, K.; Daly, M.J.; Nyholt, DR; Chasman, D.I.; Palotie, A.

2013-01-01

Migraine is the most common brain disorder, affecting approximately 14% of the adult population, but its molecular mechanisms are poorly understood. We report the results of a meta-analysis across 29 genome-wide association studies, including a total of 23,285 individuals with migraine (cases) and

Genome-wide meta-analysis identifies new susceptibility loci for migraine

DEFF Research Database (Denmark)

Anttila, Verneri; Winsvold, Bendik S; Gormley, Padhraig

2013-01-01

Migraine is the most common brain disorder, affecting approximately 14% of the adult population, but its molecular mechanisms are poorly understood. We report the results of a meta-analysis across 29 genome-wide association studies, including a total of 23,285 individuals with migraine (cases) an...

Meta-analysis of genome-wide association studies of HDL cholesterol response to statins

DEFF Research Database (Denmark)

Postmus, Iris; Warren, Helen R; Trompet, Stella

2016-01-01

BACKGROUND: In addition to lowering low density lipoprotein cholesterol (LDL-C), statin therapy also raises high density lipoprotein cholesterol (HDL-C) levels. Inter-individual variation in HDL-C response to statins may be partially explained by genetic variation. METHODS AND RESULTS: We performed...... a meta-analysis of genome-wide association studies (GWAS) to identify variants with an effect on statin-induced high density lipoprotein cholesterol (HDL-C) changes. The 123 most promising signals with p

RTEL1 is a replisome-associated helicase that promotes telomere and genome-wide replication.

Science.gov (United States)

Vannier, Jean-Baptiste; Sandhu, Sumit; Petalcorin, Mark I R; Wu, Xiaoli; Nabi, Zinnatun; Ding, Hao; Boulton, Simon J

2013-10-11

Regulator of telomere length 1 (RTEL1) is an essential DNA helicase that disassembles telomere loops (T loops) and suppresses telomere fragility to maintain the integrity of chromosome ends. We established that RTEL1 also associates with the replisome through binding to proliferating cell nuclear antigen (PCNA). Mouse cells disrupted for the RTEL1-PCNA interaction (PIP mutant) exhibited accelerated senescence, replication fork instability, reduced replication fork extension rates, and increased origin usage. Although T-loop disassembly at telomeres was unaffected in the mutant cells, telomere replication was compromised, leading to fragile sites at telomeres. RTEL1-PIP mutant mice were viable, but loss of the RTEL1-PCNA interaction accelerated the onset of tumorigenesis in p53-deficient mice. We propose that RTEL1 plays a critical role in both telomere and genome-wide replication, which is crucial for genetic stability and tumor avoidance.

Plastome-Genome Interactions Affect Plastid Transmission in Oenothera

Science.gov (United States)

Chiu, W. L.; Sears, B. B.

1993-01-01

Plastids of Oenothera, the evening primrose, can be transmitted to the progeny from both parents. In a constant nuclear background, the frequency of biparental plastid transmission is determined by the types of plastid genomes (plastomes) involved in the crosses. In this study, the impact of nuclear genomes on plastid inheritance was analyzed. In general, the transmission efficiency of each plastome correlated strongly with its compatibility with the nuclear genome of the progeny, suggesting that plastome-genome interactions can influence plastid transmission by affecting the efficiency of plastid multiplication after fertilization. Lower frequencies of plastid transmission from the paternal side were observed when the pollen had poor vigor due to an incompatible plastome-genome combination, indicating that plastome-genome interactions may also affect the input of plastids at fertilization. Parental traits that affect the process of fertilization can also have an impact on plastid transmission. Crosses using maternal parents with long styles or pollen with relatively low growth capacity resulted in reduced frequencies of paternal plastid transmission. These observations suggest that degeneration of pollen plastids may occur as the time interval between pollination and fertilization is lengthened. PMID:8462856

Genome-wide significant locus for Research Diagnostic Criteria Schizoaffective Disorder Bipolar type.

Science.gov (United States)

Green, Elaine K; Di Florio, Arianna; Forty, Liz; Gordon-Smith, Katherine; Grozeva, Detelina; Fraser, Christine; Richards, Alexander L; Moran, Jennifer L; Purcell, Shaun; Sklar, Pamela; Kirov, George; Owen, Michael J; O'Donovan, Michael C; Craddock, Nick; Jones, Lisa; Jones, Ian R

2017-12-01

Studies have suggested that Research Diagnostic Criteria for Schizoaffective Disorder Bipolar type (RDC-SABP) might identify a more genetically homogenous subgroup of bipolar disorder. Aiming to identify loci associated with RDC-SABP, we have performed a replication study using independent RDC-SABP cases (n = 144) and controls (n = 6,559), focusing on the 10 loci that reached a p-value bipolar disorder sample. Combining the WTCCC and replication datasets by meta-analysis (combined RDC-SABP, n = 423, controls, n = 9,494), we observed genome-wide significant association at one SNP, rs2352974, located within the intron of the gene TRAIP on chromosome 3p21.31 (p-value, 4.37 × 10 -8 ). This locus did not reach genome-wide significance in bipolar disorder or schizophrenia large Psychiatric Genomic Consortium datasets, suggesting that it may represent a relatively specific genetic risk for the bipolar subtype of schizoaffective disorder. © 2017 Wiley Periodicals, Inc.

A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance

Science.gov (United States)

Manning, Alisa K.; Hivert, Marie-France; Scott, Robert A.; Grimsby, Jonna L.; Bouatia-Naji, Nabila; Chen, Han; Rybin, Denis; Liu, Ching-Ti; Bielak, Lawrence F.; Prokopenko, Inga; Amin, Najaf; Barnes, Daniel; Cadby, Gemma; Hottenga, Jouke-Jan; Ingelsson, Erik; Jackson, Anne U.; Johnson, Toby; Kanoni, Stavroula; Ladenvall, Claes; Lagou, Vasiliki; Lahti, Jari; Lecoeur, Cecile; Liu, Yongmei; Martinez-Larrad, Maria Teresa; Montasser, May E.; Navarro, Pau; Perry, John R. B.; Rasmussen-Torvik, Laura J.; Salo, Perttu; Sattar, Naveed; Shungin, Dmitry; Strawbridge, Rona J.; Tanaka, Toshiko; van Duijn, Cornelia M.; An, Ping; de Andrade, Mariza; Andrews, Jeanette S.; Aspelund, Thor; Atalay, Mustafa; Aulchenko, Yurii; Balkau, Beverley; Bandinelli, Stefania; Beckmann, Jacques S.; Beilby, John P.; Bellis, Claire; Bergman, Richard N.; Blangero, John; Boban, Mladen; Boehnke, Michael; Boerwinkle, Eric; Bonnycastle, Lori L.; Boomsma, Dorret I.; Borecki, Ingrid B.; Böttcher, Yvonne; Bouchard, Claude; Brunner, Eric; Budimir, Danijela; Campbell, Harry; Carlson, Olga; Chines, Peter S.; Clarke, Robert; Collins, Francis S.; Corbatón-Anchuelo, Arturo; Couper, David; de Faire, Ulf; Dedoussis, George V; Deloukas, Panos; Dimitriou, Maria; Egan, Josephine M; Eiriksdottir, Gudny; Erdos, Michael R.; Eriksson, Johan G.; Eury, Elodie; Ferrucci, Luigi; Ford, Ian; Forouhi, Nita G.; Fox, Caroline S; Franzosi, Maria Grazia; Franks, Paul W; Frayling, Timothy M; Froguel, Philippe; Galan, Pilar; de Geus, Eco; Gigante, Bruna; Glazer, Nicole L.; Goel, Anuj; Groop, Leif; Gudnason, Vilmundur; Hallmans, Göran; Hamsten, Anders; Hansson, Ola; Harris, Tamara B.; Hayward, Caroline; Heath, Simon; Hercberg, Serge; Hicks, Andrew A.; Hingorani, Aroon; Hofman, Albert; Hui, Jennie; Hung, Joseph; Jarvelin, Marjo Riitta; Jhun, Min A.; Johnson, Paul C.D.; Jukema, J Wouter; Jula, Antti; Kao, W.H.; Kaprio, Jaakko; Kardia, Sharon L. R.; Keinanen-Kiukaanniemi, Sirkka; Kivimaki, Mika; Kolcic, Ivana; Kovacs, Peter; Kumari, Meena; Kuusisto, Johanna; Kyvik, Kirsten Ohm; Laakso, Markku; Lakka, Timo; Lannfelt, Lars; Lathrop, G Mark; Launer, Lenore J.; Leander, Karin; Li, Guo; Lind, Lars; Lindstrom, Jaana; Lobbens, Stéphane; Loos, Ruth J. F.; Luan, Jian’an; Lyssenko, Valeriya; Mägi, Reedik; Magnusson, Patrik K. E.; Marmot, Michael; Meneton, Pierre; Mohlke, Karen L.; Mooser, Vincent; Morken, Mario A.; Miljkovic, Iva; Narisu, Narisu; O’Connell, Jeff; Ong, Ken K.; Oostra, Ben A.; Palmer, Lyle J.; Palotie, Aarno; Pankow, James S.; Peden, John F.; Pedersen, Nancy L.; Pehlic, Marina; Peltonen, Leena; Penninx, Brenda; Pericic, Marijana; Perola, Markus; Perusse, Louis; Peyser, Patricia A; Polasek, Ozren; Pramstaller, Peter P.; Province, Michael A.; Räikkönen, Katri; Rauramaa, Rainer; Rehnberg, Emil; Rice, Ken; Rotter, Jerome I.; Rudan, Igor; Ruokonen, Aimo; Saaristo, Timo; Sabater-Lleal, Maria; Salomaa, Veikko; Savage, David B.; Saxena, Richa; Schwarz, Peter; Seedorf, Udo; Sennblad, Bengt; Serrano-Rios, Manuel; Shuldiner, Alan R.; Sijbrands, Eric J.G.; Siscovick, David S.; Smit, Johannes H.; Small, Kerrin S.; Smith, Nicholas L.; Smith, Albert Vernon; Stančáková, Alena; Stirrups, Kathleen; Stumvoll, Michael; Sun, Yan V.; Swift, Amy J.; Tönjes, Anke; Tuomilehto, Jaakko; Trompet, Stella; Uitterlinden, Andre G.; Uusitupa, Matti; Vikström, Max; Vitart, Veronique; Vohl, Marie-Claude; Voight, Benjamin F.; Vollenweider, Peter; Waeber, Gerard; Waterworth, Dawn M; Watkins, Hugh; Wheeler, Eleanor; Widen, Elisabeth; Wild, Sarah H.; Willems, Sara M.; Willemsen, Gonneke; Wilson, James F.; Witteman, Jacqueline C.M.; Wright, Alan F.; Yaghootkar, Hanieh; Zelenika, Diana; Zemunik, Tatijana; Zgaga, Lina; Wareham, Nicholas J.; McCarthy, Mark I.; Barroso, Ines; Watanabe, Richard M.; Florez, Jose C.; Dupuis, Josée; Meigs, James B.; Langenberg, Claudia

2013-01-01

Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and beta-cell dysfunction, but contributed little to our understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways may be uncovered by accounting for differences in body mass index (BMI) and potential interaction between BMI and genetic variants. We applied a novel joint meta-analytical approach to test associations with fasting insulin (FI) and glucose (FG) on a genome-wide scale. We present six previously unknown FI loci at P<5×10−8 in combined discovery and follow-up analyses of 52 studies comprising up to 96,496non-diabetic individuals. Risk variants were associated with higher triglyceride and lower HDL cholesterol levels, suggestive of a role for these FI loci in insulin resistance pathways. The localization of these additional loci will aid further characterization of the role of insulin resistance in T2D pathophysiology. PMID:22581228

The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study

NARCIS (Netherlands)

T.W. Winkler (Thomas W.); A.E. Justice (Anne); M.J. Graff (Maud J.L.); Barata, L. (Llilda); M.F. Feitosa (Mary Furlan); Chu, S. (Su); J. Czajkowski (Jacek); T. Esko (Tõnu); M. Fall (Magnus); T.O. Kilpeläinen (Tuomas); Y. Lu (Yingchang); R. Mägi (Reedik); E. Mihailov (Evelin); T.H. Pers (Tune); Rüeger, S. (Sina); A. Teumer (Alexander); G.B. Ehret (Georg); T. Ferreira (Teresa); N.L. Heard-Costa (Nancy); J. Karjalainen (Juha); V. Lagou (Vasiliki); A. Mahajan (Anubha); Neinast, M.D. (Michael D.); I. Prokopenko (Inga); J. Simino (Jeannette); T.M. Teslovich (Tanya M.); R. Jansen; H.J. Westra (Harm-Jan); C.C. White (Charles); D. Absher (Devin); T.S. Ahluwalia (Tarunveer Singh); S. Ahmad (Shafqat); E. Albrecht (Eva); A.C. Alves (Alexessander Couto); Bragg-Gresham, J.L. (Jennifer L.); A.J. de Craen (Anton); J.C. Bis (Joshua); A. Bonnefond (Amélie); G. Boucher (Gabrielle); G. Cadby (Gemma); Y.-C. Cheng (Yu-Ching); Chiang, C.W. (Charleston W K); G. Delgado; A. Demirkan (Ayşe); N. Dueker (Nicole); N. Eklund (Niina); G. Eiriksdottir (Gudny); J. Eriksson (Joel); B. Feenstra (Bjarke); K. Fischer (Krista); F. Frau (Francesca); T.E. Galesloot (Tessel); F. Geller (Frank); A. Goel (Anuj); M. Gorski (Mathias); T.B. Grammer (Tanja); S. Gustafsson (Stefan); Haitjema, S. (Saskia); J.J. Hottenga (Jouke Jan); J.E. Huffman (Jennifer); A.U. Jackson (Anne); K.B. Jacobs (Kevin); A. Johansson (Åsa); M. Kaakinen (Marika); M.E. Kleber (Marcus); J. Lahti (Jari); I.M. Leach (Irene Mateo); Lehne, B. (Benjamin); Liu, Y. (Youfang); K.S. Lo; M. Lorentzon (Mattias); J. Luan (Jian'An); P.A. Madden (Pamela); M. Mangino (Massimo); B. McKnight (Barbara); Medina-Gomez, C. (Carolina); K.L. Monda (Keri); M.E. Montasser (May E.); G. Müller (Gabriele); M. Müller-Nurasyid (Martina); I.M. Nolte (Ilja); Panoutsopoulou, K. (Kalliope); L. Pascoe (Laura); L. Paternoster (Lavinia); N.W. Rayner (Nigel William); F. Renström (Frida); Rizzi, F. (Federica); L.M. Rose (Lynda); Ryan, K.A. (Kathy A.); P. Salo (Perttu); S. Sanna (Serena); H. Scharnagl (Hubert); Shi, J. (Jianxin); A.V. Smith (Albert Vernon); L. Southam (Lorraine); A. Stancáková (Alena); V. Steinthorsdottir (Valgerdur); R.J. Strawbridge (Rona); Sung, Y.J. (Yun Ju); I. Tachmazidou (Ioanna); T. Tanaka (Toshiko); G. Thorleifsson (Gudmar); S. Trompet (Stella); N. Pervjakova (Natalia); J.P. Tyrer (Jonathan); L. Vandenput (Liesbeth); S.W. Van Der Laan (Sander W.); N. van der Velde (Nathalie); J. van Setten (Jessica); J.V. van Vliet-Ostaptchouk (Jana); N. Verweij (Niek); E. Vlachopoulou (Efthymia); L. Waite (Lindsay); S.R. Wang (Sophie); Z. Wang (Zhaoming); S.H. Wild (Sarah); C. Willenborg (Christina); J.F. Wilson (James); A. Wong (Andrew); Yang, J. (Jian); L. Yengo (Loic); L.M. Yerges-Armstrong (Laura); Yu, L. (Lei); W. Zhang (Weihua); Zhao, J.H. (Jing Hua); E.A. Andersson (Ehm Astrid); S.J.L. Bakker (Stephan); D. Baldassarre (Damiano); Banasik, K. (Karina); Barcella, M. (Matteo); Barlassina, C. (Cristina); C. Bellis (Claire); P. Benaglio (Paola); J. Blangero (John); M. Blüher (Matthias); Bonnet, F. (Fabrice); L.L. Bonnycastle (Lori); H.A. Boyd (Heather); M. Bruinenberg (M.); Buchman, A.S. (Aron S.); H. Campbell (Harry); Y.D. Chen (Y.); P.S. Chines (Peter); S. Claudi-Boehm (Simone); J.W. Cole (John W.); F.S. Collins (Francis); E.J.C. de Geus (Eco); L.C.P.G.M. de Groot (Lisette); M. Dimitriou (Maria); J. Duan (Jubao); S. Enroth (Stefan); E. Eury (Elodie); A.-E. Farmaki (Aliki-Eleni); N.G. Forouhi (Nita); N. Friedrich (Nele); P.V. Gejman (Pablo); B. Gigante (Bruna); N. Glorioso (Nicola); A. Go (Attie); R.F. Gottesman (Rebecca); J. Gräßler (Jürgen); H. Grallert (Harald); N. Grarup (Niels); Gu, Y.-M. (Yu-Mei); L. Broer (Linda); A.C. Ham (Annelies); T. Hansen (T.); T.B. Harris (Tamara); C.A. Hartman (Catharina A.); Hassinen, M. (Maija); N. Hastie (Nick); A.T. Hattersley (Andrew); A.C. Heath (Andrew); A.K. Henders (Anjali); D.G. Hernandez (Dena); H.L. Hillege (Hans); O.L. Holmen (Oddgeir); G.K. Hovingh (Kees); J. Hui (Jennie); Husemoen, L.L. (Lise L.); Hutri-Kähönen, N. (Nina); P.G. Hysi (Pirro); T. Illig (Thomas); P.L. de Jager (Philip); S. Jalilzadeh (Shapour); T. Jorgensen (Torben); J.W. Jukema (Jan Wouter); Juonala, M. (Markus); S. Kanoni (Stavroula); M. Karaleftheri (Maria); K.T. Khaw; L. Kinnunen (Leena); T. Kittner (Thomas); W. Koenig (Wolfgang); I. Kolcic (Ivana); P. Kovacs (Peter); Krarup, N.T. (Nikolaj T.); W. Kratzer (Wolfgang); Krüger, J. (Janine); Kuh, D. (Diana); M. Kumari (Meena); T. Kyriakou (Theodosios); C. Langenberg (Claudia); L. Lannfelt (Lars); C. Lanzani (Chiara); V. Lotay (Vaneet); L.J. Launer (Lenore); K. Leander (Karin); J. Lindström (Jaana); A. Linneberg (Allan); Liu, Y.-P. (Yan-Ping); S. Lobbens (Stéphane); R.N. Luben (Robert); V. Lyssenko (Valeriya); S. Männistö (Satu); P.K. Magnusson (Patrik); W.L. McArdle (Wendy); C. Menni (Cristina); S. Merger (Sigrun); L. Milani (Lili); Montgomery, G.W. (Grant W.); A.P. Morris (Andrew); N. Narisu (Narisu); M. Nelis (Mari); K.K. Ong (Ken); A. Palotie (Aarno); L. Perusse (Louis); I. Pichler (Irene); M.G. Pilia (Maria Grazia); A. Pouta (Anneli); Rheinberger, M. (Myriam); Ribel-Madsen, R. (Rasmus); Richards, M. (Marcus); K.M. Rice (Kenneth); T.K. Rice (Treva K.); C. Rivolta (Carlo); V. Salomaa (Veikko); A.R. Sanders (Alan); M.A. Sarzynski (Mark A.); S. Scholtens (Salome); R.A. Scott (Robert); W.R. Scott (William R.); S. Sebert (Sylvain); S. Sengupta (Sebanti); B. Sennblad (Bengt); T. Seufferlein (Thomas); A. Silveira (Angela); P.E. Slagboom (Eline); J.H. Smit (Jan); T. Sparsø (Thomas); K. Stirrups (Kathy); R.P. Stolk (Ronald); H.M. Stringham (Heather); Swertz, M.A. (Morris A.); A.J. Swift (Amy); A.C. Syvänen; S.-T. Tan (Sian-Tsung); B. Thorand (Barbara); A. Tönjes (Anke); Tremblay, A. (Angelo); E. Tsafantakis (Emmanouil); P.J. van der Most (Peter); U. Völker (Uwe); M.-C. Vohl (Marie-Claude); J.M. Vonk (Judith); M. Waldenberger (Melanie); Walker, R.W. (Ryan W.); R. Wennauer (Roman); E. Widen; G.A.H.M. Willemsen (Gonneke); T. Wilsgaard (Tom); A.F. Wright (Alan); M.C. Zillikens (Carola); S. Van Dijk (Suzanne); N.M. van Schoor (Natasja); F.W. Asselbergs (Folkert); P.I.W. de Bakker (Paul); J.S. Beckmann (Jacques); J.P. Beilby (John); D.A. Bennett (David A.); R.N. Bergman (Richard); S.M. Bergmann (Sven); C.A. Böger (Carsten); B.O. Boehm (Bernhard); E.A. Boerwinkle (Eric); D.I. Boomsma (Dorret); S.R. Bornstein (Stefan); E.P. Bottinger (Erwin); C. Bouchard (Claude); J.C. Chambers (John); S.J. Chanock (Stephen); D.I. Chasman (Daniel); F. Cucca (Francesco); D. Cusi (Daniele); G.V. Dedoussis (George); J. Erdmann (Jeanette); K. Hagen (Knut); D. Evans; U. de Faire (Ulf); M. Farrall (Martin); L. Ferrucci (Luigi); I. Ford (Ian); L. Franke (Lude); P.W. Franks (Paul); P. Froguel (Philippe); R.T. Gansevoort (Ron); C. Gieger (Christian); H. Grönberg (Henrik); V. Gudnason (Vilmundur); U. Gyllensten (Ulf); P. Hall (Per); A. Hamsten (Anders); P. van der Harst (Pim); C. Hayward (Caroline); M. Heliovaara (Markku); C. Hengstenberg (Christian); A.A. Hicks (Andrew); A. Hingorani (Aroon); A. Hofman (Albert); Hu, F. (Frank); H.V. Huikuri (Heikki); K. Hveem (Kristian); A. James (Alan); Jordan, J.M. (Joanne M.); A. Jula (Antti); M. Kähönen (Mika); E. Kajantie (Eero); S. Kathiresan (Sekar); L.A.L.M. Kiemeney (Bart); M. Kivimaki (Mika); P. Knekt; H. Koistinen (Heikki); J.S. Kooner (Jaspal S.); S. Koskinen (Seppo); J. Kuusisto (Johanna); W. Maerz (Winfried); N.G. Martin (Nicholas); M. Laakso (Markku); T.A. Lakka (Timo); T. Lehtimäki (Terho); G. Lettre (Guillaume); D.F. Levinson (Douglas); W.H.L. Kao (Wen); M.L. Lokki; Mäntyselkä, P. (Pekka); M. Melbye (Mads); A. Metspalu (Andres); B.D. Mitchell (Braxton); F.L. Moll (Frans); J.C. Murray (Jeffrey); A.W. Musk (Arthur); M.S. Nieminen (Markku); I. Njølstad (Inger); C. Ohlsson (Claes); A.J. Oldehinkel (Albertine); B.A. Oostra (Ben); C. Palmer (Cameron); J.S. Pankow (James); G. Pasterkamp (Gerard); N.L. Pedersen (Nancy); O. Pedersen (Oluf); B.W.J.H. Penninx (Brenda); M. Perola (Markus); A. Peters (Annette); O. Polasek (Ozren); P.P. Pramstaller (Peter Paul); Psaty, B.M. (Bruce M.); Qi, L. (Lu); T. Quertermous (Thomas); Raitakari, O.T. (Olli T.); T. Rankinen (Tuomo); R. Rauramaa (Rainer); P.M. Ridker (Paul); J.D. Rioux (John); F. Rivadeneira Ramirez (Fernando); J.I. Rotter (Jerome I.); I. Rudan (Igor); H.M. den Ruijter (Hester ); J. Saltevo (Juha); N. Sattar (Naveed); Schunkert, H. (Heribert); P.E.H. Schwarz (Peter); A.R. Shuldiner (Alan); J. Sinisalo (Juha); H. Snieder (Harold); T.I.A. Sørensen (Thorkild); T.D. Spector (Timothy); Staessen, J.A. (Jan A.); Stefania, B. (Bandinelli); U. Thorsteinsdottir (Unnur); M. Stumvoll (Michael); J.-C. Tardif (Jean-Claude); E. Tremoli (Elena); J. Tuomilehto (Jaakko); A.G. Uitterlinden (André); M. Uusitupa (Matti); A.L.M. Verbeek; S.H.H.M. Vermeulen (Sita); J. Viikari (Jorma); Vitart, V. (Veronique); H. Völzke (Henry); P. Vollenweider (Peter); G. Waeber (Gérard); M. Walker (Mark); H. Wallaschofski (Henri); N.J. Wareham (Nick); H. Watkins (Hugh); E. Zeggini (Eleftheria); A. Chakravarti (Aravinda); Clegg, D.J. (Deborah J.); L.A. Cupples (Adrienne); P. Gordon-Larsen (Penny); C.E. Jaquish (Cashell); D.C. Rao (Dabeeru C.); Abecasis, G.R. (Goncalo R.); T.L. Assimes (Themistocles); I.E. Barroso (Inês); S.I. Berndt (Sonja); M. Boehnke (Michael); P. Deloukas (Panagiotis); C.S. Fox (Caroline); L. Groop (Leif); D. Hunter (David); E. Ingelsson (Erik); R.C. Kaplan (Robert); McCarthy, M.I. (Mark I.); K.L. Mohlke (Karen); J.R. O´Connell; Schlessinger, D. (David); D.P. Strachan (David); J-A. Zwart (John-Anker); C.M. van Duijn (Cornelia); J.N. Hirschhorn (Joel); C.M. Lindgren (Cecilia M.); I.M. Heid (Iris); K.E. North (Kari); I.B. Borecki (Ingrid); Z. Kutalik (Zoltán); R.J.F. Loos (Ruth)

2015-01-01

textabstractGenome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ

Genome-wide association study reveals greater polygenic loading for schizophrenia in cases with a family history of illness

DEFF Research Database (Denmark)

Bigdeli, Tim B.; Ripke, Stephan; Bacanu, Silviu-Alin

2016-01-01

Genome-wide association studies (GWAS) of schizophrenia have yielded more than 100 common susceptibility variants, and strongly support a substantial polygenic contribution of a large number of small allelic effects. It has been hypothesized that familial schizophrenia is largely a consequence...... of inherited rather than environmental factors. We investigated the extent to which familiality of schizophrenia is associated with enrichment for common risk variants detectable in a large GWAS. We analyzed single nucleotide polymorphism (SNP) data for cases reporting a family history of psychotic illness (N...... history subgroup. Comparison of genome-wide polygenic risk scores based on GWAS summary statistics indicated a significant enrichment for SNP effects among family history positive compared to family history negative cases (Nagelkerke's R2=0.0021; P=0.00331; P-value threshold

Genome-wide haplotype analysis of cis expression quantitative trait loci in monocytes.

Directory of Open Access Journals (Sweden)

Sophie Garnier

Full Text Available In order to assess whether gene expression variability could be influenced by several SNPs acting in cis, either through additive or more complex haplotype effects, a systematic genome-wide search for cis haplotype expression quantitative trait loci (eQTL was conducted in a sample of 758 individuals, part of the Cardiogenics Transcriptomic Study, for which genome-wide monocyte expression and GWAS data were available. 19,805 RNA probes were assessed for cis haplotypic regulation through investigation of ~2,1 × 10(9 haplotypic combinations. 2,650 probes demonstrated haplotypic p-values >10(4-fold smaller than the best single SNP p-value. Replication of significant haplotype effects were tested for 412 probes for which SNPs (or proxies that defined the detected haplotypes were available in the Gutenberg Health Study composed of 1,374 individuals. At the Bonferroni correction level of 1.2 × 10(-4 (~0.05/412, 193 haplotypic signals replicated. 1000 G imputation was then conducted, and 105 haplotypic signals still remained more informative than imputed SNPs. In-depth analysis of these 105 cis eQTL revealed that at 76 loci genetic associations were compatible with additive effects of several SNPs, while for the 29 remaining regions data could be compatible with a more complex haplotypic pattern. As 24 of the 105 cis eQTL have previously been reported to be disease-associated loci, this work highlights the need for conducting haplotype-based and 1000 G imputed cis eQTL analysis before commencing functional studies at disease-associated loci.

Genome-wide analysis of multi- and extensively drug-resistant Mycobacterium tuberculosis

KAUST Repository

Coll, Francesc; Phelan, Jody; Hill-Cawthorne, Grant A.; Nair, Mridul; Mallard, Kim; Ali, Shahjahan; Abdallah, Abdallah; Alghamdi, Saad; Alsomali, Mona; Ahmed, Abdallah O.; Portelli, Stephanie; Oppong, Yaa; Alves, Adriana; Bessa, Theolis Barbosa; Campino, Susana; Caws, Maxine; Chatterjee, Anirvan; Crampin, Amelia C.; Dheda, Keertan; Furnham, Nicholas; Glynn, Judith R.; Grandjean, Louis; Minh Ha, Dang; Hasan, Rumina; Hasan, Zahra; Hibberd, Martin L.; Joloba, Moses; Jones-Ló pez, Edward C.; Matsumoto, Tomoshige; Miranda, Anabela; Moore, David J.; Mocillo, Nora; Panaiotov, Stefan; Parkhill, Julian; Penha, Carlos; Perdigã o, Joã o; Portugal, Isabel; Rchiad, ‍ Zineb; Robledo, Jaime; Sheen, Patricia; Shesha, Nashwa Talaat; Sirgel, Frik A.; Sola, Christophe; Oliveira Sousa, Erivelton; Streicher, Elizabeth M.; Helden, Paul Van; Viveiros, Miguel; Warren, Robert M.; McNerney, Ruth; Pain, Arnab; Clark, Taane G.

2018-01-01

To characterize the genetic determinants of resistance to antituberculosis drugs, we performed a genome-wide association study (GWAS) of 6,465 Mycobacterium tuberculosis clinical isolates from more than 30 countries. A GWAS approach within a mixed

Genome-wide association study identifies new prostate cancer susceptibility loci

DEFF Research Database (Denmark)

Schumacher, Fredrick R.; Berndt, Sonja I.; Siddiq, Afshan

2011-01-01

Prostate cancer (PrCa) is the most common non-skin cancer diagnosed among males in developed countries and the second leading cause of cancer mortality, yet little is known regarding its etiology and factors that influence clinical outcome. Genome-wide association studies (GWAS) of PrCa have iden...

Connecting the dots, genome-wide association studies in substance use

NARCIS (Netherlands)

Nivard, M.G.; Verweij, K.J.H.; Minica, C.C.; Treur, J.L.; Vink, J.M.; Boomsma, D.I.

2016-01-01

The recent genome-wide association (GWA) meta-analysis of lifetime cannabis use by the International Cannabis Consortium marks a milestone in the study of the genetics of cannabis use. Similar milestones for the genetics of substance use were the GWA meta-analyses of four smoking related traits, of

Genome-wide identification of SAUR genes in watermelon (Citrullus lanatus).

Science.gov (United States)

Zhang, Na; Huang, Xing; Bao, Yaning; Wang, Bo; Zeng, Hongxia; Cheng, Weishun; Tang, Mi; Li, Yuhua; Ren, Jian; Sun, Yuhong

2017-07-01

The early auxin responsive SAUR family is an important gene family in auxin signal transduction. We here present the first report of a genome-wide identification of SAUR genes in watermelon genome. We successfully identified 65 ClaSAURs and provide a genomic framework for future study on these genes. Phylogenetic result revealed a Cucurbitaceae-specific SAUR subfamily and contribute to understanding of the evolutionary pattern of SAUR genes in plants. Quantitative RT-PCR analysis demonstrates the existed expression of 11 randomly selected SAUR genes in watermelon tissues. ClaSAUR36 was highly expressed in fruit, for which further study might bring a new prospective for watermelon fruit development. Moreover, correlation analysis revealed the similar expression profiles of SAUR genes between watermelon and Arabidopsis during shoot organogenesis. This work gives us a new support for the conserved auxin machinery in plants.

Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis.

Science.gov (United States)

Cho, Seoae; Kim, Haseong; Oh, Sohee; Kim, Kyunga; Park, Taesung

2009-12-15

The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.

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

Science.gov (United States)

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

A Genome-Wide mQTL Analysis in Human Adipose Tissue Identifies Genetic Variants Associated with DNA Methylation, Gene Expression and Metabolic Traits

DEFF Research Database (Denmark)

Volkov, Petr; Olsson, Anders H; Gillberg, Linn

2016-01-01

Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men, w...... and epigenetic variation in both cis and trans positions influencing gene expression in adipose tissue and in vivo (dys)metabolic traits associated with the development of obesity and diabetes.......Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men......, where 592,794 single nucleotide polymorphisms (SNPs) were related to DNA methylation of 477,891 CpG sites, covering 99% of RefSeq genes. SNPs in significant mQTLs were further related to gene expression in adipose tissue and obesity related traits. We found 101,911 SNP-CpG pairs (mQTLs) in cis and 5...

Impacts of Genome-Wide Analyses on Our Understanding of Human Herpesvirus Diversity and Evolution.

Science.gov (United States)

Renner, Daniel W; Szpara, Moriah L

2018-01-01

Until fairly recently, genome-wide evolutionary dynamics and within-host diversity were more commonly examined in the context of small viruses than in the context of large double-stranded DNA viruses such as herpesviruses. The high mutation rates and more compact genomes of RNA viruses have inspired the investigation of population dynamics for these species, and recent data now suggest that herpesviruses might also be considered candidates for population modeling. High-throughput sequencing (HTS) and bioinformatics have expanded our understanding of herpesviruses through genome-wide comparisons of sequence diversity, recombination, allele frequency, and selective pressures. Here we discuss recent data on the mechanisms that generate herpesvirus genomic diversity and underlie the evolution of these virus families. We focus on human herpesviruses, with key insights drawn from veterinary herpesviruses and other large DNA virus families. We consider the impacts of cell culture on herpesvirus genomes and how to accurately describe the viral populations under study. The need for a strong foundation of high-quality genomes is also discussed, since it underlies all secondary genomic analyses such as RNA sequencing (RNA-Seq), chromatin immunoprecipitation, and ribosome profiling. Areas where we foresee future progress, such as the linking of viral genetic differences to phenotypic or clinical outcomes, are highlighted as well. Copyright © 2017 Renner and Szpara.

Impacts of Genome-Wide Analyses on Our Understanding of Human Herpesvirus Diversity and Evolution

Science.gov (United States)

Renner, Daniel W.

2017-01-01

ABSTRACT Until fairly recently, genome-wide evolutionary dynamics and within-host diversity were more commonly examined in the context of small viruses than in the context of large double-stranded DNA viruses such as herpesviruses. The high mutation rates and more compact genomes of RNA viruses have inspired the investigation of population dynamics for these species, and recent data now suggest that herpesviruses might also be considered candidates for population modeling. High-throughput sequencing (HTS) and bioinformatics have expanded our understanding of herpesviruses through genome-wide comparisons of sequence diversity, recombination, allele frequency, and selective pressures. Here we discuss recent data on the mechanisms that generate herpesvirus genomic diversity and underlie the evolution of these virus families. We focus on human herpesviruses, with key insights drawn from veterinary herpesviruses and other large DNA virus families. We consider the impacts of cell culture on herpesvirus genomes and how to accurately describe the viral populations under study. The need for a strong foundation of high-quality genomes is also discussed, since it underlies all secondary genomic analyses such as RNA sequencing (RNA-Seq), chromatin immunoprecipitation, and ribosome profiling. Areas where we foresee future progress, such as the linking of viral genetic differences to phenotypic or clinical outcomes, are highlighted as well. PMID:29046445

Genome-wide variation in recombination rate in Eucalyptus.

Science.gov (United States)

Gion, Jean-Marc; Hudson, Corey J; Lesur, Isabelle; Vaillancourt, René E; Potts, Brad M; Freeman, Jules S

2016-08-09

Meiotic recombination is a fundamental evolutionary process. It not only generates diversity, but influences the efficacy of natural selection and genome evolution. There can be significant heterogeneity in recombination rates within and between species, however this variation is not well understood outside of a few model taxa, particularly in forest trees. Eucalypts are forest trees of global economic importance, and dominate many Australian ecosystems. We studied recombination rate in Eucalyptus globulus using genetic linkage maps constructed in 10 unrelated individuals, and markers anchored to the Eucalyptus reference genome. This experimental design provided the replication to study whether recombination rate varied between individuals and chromosomes, and allowed us to study the genomic attributes and population genetic parameters correlated with this variation. Recombination rate varied significantly between individuals (range = 2.71 to 3.51 centimorgans/megabase [cM/Mb]), but was not significantly influenced by sex or cross type (F1 vs. F2). Significant differences in recombination rate between chromosomes were also evident (range = 1.98 to 3.81 cM/Mb), beyond those which were due to variation in chromosome size. Variation in chromosomal recombination rate was significantly correlated with gene density (r = 0.94), GC content (r = 0.90), and the number of tandem duplicated genes (r = -0.72) per chromosome. Notably, chromosome level recombination rate was also negatively correlated with the average genetic diversity across six species from an independent set of samples (r = -0.75). The correlations with genomic attributes are consistent with findings in other taxa, however, the direction of the correlation between diversity and recombination rate is opposite to that commonly observed. We argue this is likely to reflect the interaction of selection and specific genome architecture of Eucalyptus. Interestingly, the differences amongst

Genome-Wide Progesterone Receptor Binding: Cell Type-Specific and Shared Mechanisms in T47D Breast Cancer Cells and Primary Leiomyoma Cells

Science.gov (United States)

Huang, Lei; Owen, Jonas K.; Xie, Anna; Navarro, Antonia; Monsivais, Diana; Coon V, John S.; Kim, J. Julie; Dai, Yang; Bulun, Serdar E.

2012-01-01

Background Progesterone, via its nuclear receptor (PR), exerts an overall tumorigenic effect on both uterine fibroid (leiomyoma) and breast cancer tissues, whereas the antiprogestin RU486 inhibits growth of these tissues through an unknown mechanism. Here, we determined the interaction between common or cell-specific genome-wide binding sites of PR and mRNA expression in RU486-treated uterine leiomyoma and breast cancer cells. Principal Findings ChIP-sequencing revealed 31,457 and 7,034 PR-binding sites in breast cancer and uterine leiomyoma cells, respectively; 1,035 sites overlapped in both cell types. Based on the chromatin-PR interaction in both cell types, we statistically refined the consensus progesterone response element to G•ACA• • •TGT•C. We identified two striking differences between uterine leiomyoma and breast cancer cells. First, the cis-regulatory elements for HSF, TEF-1, and C/EBPα and β were statistically enriched at genomic RU486/PR-targets in uterine leiomyoma, whereas E2F, FOXO1, FOXA1, and FOXF sites were preferentially enriched in breast cancer cells. Second, 51.5% of RU486-regulated genes in breast cancer cells but only 6.6% of RU486-regulated genes in uterine leiomyoma cells contained a PR-binding site within 5 kb from their transcription start sites (TSSs), whereas 75.4% of RU486-regulated genes contained a PR-binding site farther than 50 kb from their TSSs in uterine leiomyoma cells. RU486 regulated only seven mRNAs in both cell types. Among these, adipophilin (PLIN2), a pro-differentiation gene, was induced via RU486 and PR via the same regulatory region in both cell types. Conclusions Our studies have identified molecular components in a RU486/PR-controlled gene network involved in the regulation of cell growth, cell migration, and extracellular matrix function. Tissue-specific and common patterns of genome-wide PR binding and gene regulation may determine the therapeutic effects of antiprogestins in uterine fibroids and

Genome-wide mapping of autonomous promoter activity in human cells.

Science.gov (United States)

van Arensbergen, Joris; FitzPatrick, Vincent D; de Haas, Marcel; Pagie, Ludo; Sluimer, Jasper; Bussemaker, Harmen J; van Steensel, Bas

2017-02-01

Previous methods to systematically characterize sequence-intrinsic activity of promoters have been limited by relatively low throughput and the length of the sequences that could be tested. Here we present 'survey of regulatory elements' (SuRE), a method that assays more than 10 8 DNA fragments, each 0.2-2 kb in size, for their ability to drive transcription autonomously. In SuRE, a plasmid library of random genomic fragments upstream of a 20-bp barcode is constructed, and decoded by paired-end sequencing. This library is used to transfect cells, and barcodes in transcribed RNA are quantified by high-throughput sequencing. When applied to the human genome, we achieve 55-fold genome coverage, allowing us to map autonomous promoter activity genome-wide in K562 cells. By computational modeling we delineate subregions within promoters that are relevant for their activity. We show that antisense promoter transcription is generally dependent on the sense core promoter sequences, and that most enhancers and several families of repetitive elements act as autonomous transcription initiation sites.

Genome-Wide Association Study of the Genetic Determinants of Emphysema Distribution.

Science.gov (United States)

Boueiz, Adel; Lutz, Sharon M; Cho, Michael H; Hersh, Craig P; Bowler, Russell P; Washko, George R; Halper-Stromberg, Eitan; Bakke, Per; Gulsvik, Amund; Laird, Nan M; Beaty, Terri H; Coxson, Harvey O; Crapo, James D; Silverman, Edwin K; Castaldi, Peter J; DeMeo, Dawn L

2017-03-15

Emphysema has considerable variability in the severity and distribution of parenchymal destruction throughout the lungs. Upper lobe-predominant emphysema has emerged as an important predictor of response to lung volume reduction surgery. Yet, aside from alpha-1 antitrypsin deficiency, the genetic determinants of emphysema distribution remain largely unknown. To identify the genetic influences of emphysema distribution in non-alpha-1 antitrypsin-deficient smokers. A total of 11,532 subjects with complete genotype and computed tomography densitometry data in the COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]; non-Hispanic white and African American), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints), and GenKOLS (Genetics of Chronic Obstructive Lung Disease) studies were analyzed. Two computed tomography scan emphysema distribution measures (difference between upper-third and lower-third emphysema; ratio of upper-third to lower-third emphysema) were tested for genetic associations in all study subjects. Separate analyses in each study population were followed by a fixed effect metaanalysis. Single-nucleotide polymorphism-, gene-, and pathway-based approaches were used. In silico functional evaluation was also performed. We identified five loci associated with emphysema distribution at genome-wide significance. These loci included two previously reported associations with COPD susceptibility (4q31 near HHIP and 15q25 near CHRNA5) and three new associations near SOWAHB, TRAPPC9, and KIAA1462. Gene set analysis and in silico functional evaluation revealed pathways and cell types that may potentially contribute to the pathogenesis of emphysema distribution. This multicohort genome-wide association study identified new genomic loci associated with differential emphysematous destruction throughout the lungs. These findings may point to new biologic pathways on which to expand diagnostic and therapeutic

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

Science.gov (United States)

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

Generation of meiomaps of genome-wide recombination and chromosome segregation in human oocytes

DEFF Research Database (Denmark)

Ottolini, Christian S; Capalbo, Antonio; Newnham, Louise

2016-01-01

We have developed a protocol for the generation of genome-wide maps (meiomaps) of recombination and chromosome segregation for the three products of human female meiosis: the first and second polar bodies (PB1 and PB2) and the corresponding oocyte. PB1 is biopsied and the oocyte is artificially......-nucleotide polymorphisms (SNPs) genome-wide by microarray. Informative maternal heterozygous SNPs are phased using a haploid PB2 or oocyte as a reference. A simple algorithm is then used to identify the maternal haplotypes for each chromosome, in all of the products of meiosis for each oocyte. This allows mapping...

Genetic link between family socioeconomic status and children's educational achievement estimated from genome-wide SNPs.

Science.gov (United States)

Krapohl, E; Plomin, R

2016-03-01

One of the best predictors of children's educational achievement is their family's socioeconomic status (SES), but the degree to which this association is genetically mediated remains unclear. For 3000 UK-representative unrelated children we found that genome-wide single-nucleotide polymorphisms could explain a third of the variance of scores on an age-16 UK national examination of educational achievement and half of the correlation between their scores and family SES. Moreover, genome-wide polygenic scores based on a previously published genome-wide association meta-analysis of total number of years in education accounted for ~3.0% variance in educational achievement and ~2.5% in family SES. This study provides the first molecular evidence for substantial genetic influence on differences in children's educational achievement and its association with family SES.

Genome-wide microsatellite characterization and marker development in the sequenced Brassica crop species.

Science.gov (United States)

Shi, Jiaqin; Huang, Shunmou; Zhan, Jiepeng; Yu, Jingyin; Wang, Xinfa; Hua, Wei; Liu, Shengyi; Liu, Guihua; Wang, Hanzhong

2014-02-01

Although much research has been conducted, the pattern of microsatellite distribution has remained ambiguous, and the development/utilization of microsatellite markers has still been limited/inefficient in Brassica, due to the lack of genome sequences. In view of this, we conducted genome-wide microsatellite characterization and marker development in three recently sequenced Brassica crops: Brassica rapa, Brassica oleracea and Brassica napus. The analysed microsatellite characteristics of these Brassica species were highly similar or almost identical, which suggests that the pattern of microsatellite distribution is likely conservative in Brassica. The genomic distribution of microsatellites was highly non-uniform and positively or negatively correlated with genes or transposable elements, respectively. Of the total of 115 869, 185 662 and 356 522 simple sequence repeat (SSR) markers developed with high frequencies (408.2, 343.8 and 356.2 per Mb or one every 2.45, 2.91 and 2.81 kb, respectively), most represented new SSR markers, the majority had determined physical positions, and a large number were genic or putative single-locus SSR markers. We also constructed a comprehensive database for the newly developed SSR markers, which was integrated with public Brassica SSR markers and annotated genome components. The genome-wide SSR markers developed in this study provide a useful tool to extend the annotated genome resources of sequenced Brassica species to genetic study/breeding in different Brassica species.

Genome-Wide Meta-Analysis of Longitudinal Alcohol Consumption Across Youth and Early Adulthood.

Science.gov (United States)

Adkins, Daniel E; Clark, Shaunna L; Copeland, William E; Kennedy, Martin; Conway, Kevin; Angold, Adrian; Maes, Hermine; Liu, Youfang; Kumar, Gaurav; Erkanli, Alaattin; Patkar, Ashwin A; Silberg, Judy; Brown, Tyson H; Fergusson, David M; Horwood, L John; Eaves, Lindon; van den Oord, Edwin J C G; Sullivan, Patrick F; Costello, E J

2015-08-01

The public health burden of alcohol is unevenly distributed across the life course, with levels of use, abuse, and dependence increasing across adolescence and peaking in early adulthood. Here, we leverage this temporal patterning to search for common genetic variants predicting developmental trajectories of alcohol consumption. Comparable psychiatric evaluations measuring alcohol consumption were collected in three longitudinal community samples (N=2,126, obs=12,166). Consumption-repeated measurements spanning adolescence and early adulthood were analyzed using linear mixed models, estimating individual consumption trajectories, which were then tested for association with Illumina 660W-Quad genotype data (866,099 SNPs after imputation and QC). Association results were combined across samples using standard meta-analysis methods. Four meta-analysis associations satisfied our pre-determined genome-wide significance criterion (FDR<0.1) and six others met our 'suggestive' criterion (FDR<0.2). Genome-wide significant associations were highly biological plausible, including associations within GABA transporter 1, SLC6A1 (solute carrier family 6, member 1), and exonic hits in LOC100129340 (mitofusin-1-like). Pathway analyses elaborated single marker results, indicating significant enriched associations to intuitive biological mechanisms, including neurotransmission, xenobiotic pharmacodynamics, and nuclear hormone receptors (NHR). These findings underscore the value of combining longitudinal behavioral data and genome-wide genotype information in order to study developmental patterns and improve statistical power in genomic studies.

Genome-wide association for sensitivity to chronic oxidative stress in Drosophila melanogaster.

Directory of Open Access Journals (Sweden)

Katherine W Jordan

Full Text Available Reactive oxygen species (ROS are a common byproduct of mitochondrial energy metabolism, and can also be induced by exogenous sources, including UV light, radiation, and environmental toxins. ROS generation is essential for maintaining homeostasis by triggering cellular signaling pathways and host defense mechanisms. However, an imbalance of ROS induces oxidative stress and cellular death and is associated with human disease, including age-related locomotor impairment. To identify genes affecting sensitivity and resistance to ROS-induced locomotor decline, we assessed locomotion of aged flies of the sequenced, wild-derived lines from the Drosophila melanogaster Genetics Reference Panel on standard medium and following chronic exposure to medium supplemented with 3 mM menadione sodium bisulfite (MSB. We found substantial genetic variation in sensitivity to oxidative stress with respect to locomotor phenotypes. We performed genome-wide association analyses to identify candidate genes associated with variation in sensitivity to ROS-induced decline in locomotor performance, and confirmed the effects for 13 of 16 mutations tested in these candidate genes. Candidate genes associated with variation in sensitivity to MSB-induced oxidative stress form networks of genes involved in neural development, immunity, and signal transduction. Many of these genes have human orthologs, highlighting the utility of genome-wide association in Drosophila for studying complex human disease.

A genome-wide approach to children's aggressive behavior: The EAGLE consortium

NARCIS (Netherlands)

Pappa, I.; St Pourcain, B.; Benke, K.S.; Cavadino, A.; Hakulinen, C.; Nivard, M.G.; Nolte, I.M.; Tiesler, C.M.T.; Bakermans-Kranenburg, M.J.; Davies, G.E.; Evans, D.M.; Geoffroy, M.C.; Grallert, H.; Blokhuis, M.M.; Hudziak, J.J.; Kemp, J.P.; Keltikangas-Järvinen, L.; McMahon, G.; Mileva-Seitz, V.R.; Motazedi, E.; Power, C.; Raitakari, O.T.; Ring, S.M.; Rivadeneira, F.; Rodriguez, A.; Scheet, P.; Seppälä, I.; Snieder, H.; Standl, M.; Thiering, E.; Timpson, N.J.; Veenstra, R.; Velders, F.P.; Whitehouse, A.J.O.; Davey Smith, G.; Heinrich, J.; Hypponen, E.; Lehtimäki, T.; Middeldorp, C.M.; Oldehinkel, A.J.; Pennell, C.E.; Boomsma, D.I.; Tiemeier, H.

2016-01-01

Individual differences in aggressive behavior emerge in early childhood and predict persisting behavioral problems and disorders. Studies of antisocial and severe aggression in adulthood indicate substantial underlying biology. However, little attention has been given to genome-wide approaches of

SOAPsplice: genome-wide ab initio detection of splice junctions from RNA-Seq data

Directory of Open Access Journals (Sweden)

Songbo eHuang

2011-07-01

Full Text Available RNA-Seq, a method using next generation sequencing technologies to sequence the transcriptome, facilitates genome-wide analysis of splice junction sites. In this paper, we introduce SOAPsplice, a robust tool to detect splice junctions using RNA-Seq data without using any information of known splice junctions. SOAPsplice uses a novel two-step approach consisting of first identifying as many reasonable splice junction candidates as possible, and then, filtering the false positives with two effective filtering strategies. In both simulated and real datasets, SOAPsplice is able to detect many reliable splice junctions with low false positive rate. The improvement gained by SOAPsplice, when compared to other existing tools, becomes more obvious when the depth of sequencing is low. SOAPsplice is freely available at http://soap.genomics.org.cn/soapsplice.html.

Interactive or static reports to guide clinical interpretation of cancer genomics.

Science.gov (United States)

Gray, Stacy W; Gagan, Jeffrey; Cerami, Ethan; Cronin, Angel M; Uno, Hajime; Oliver, Nelly; Lowenstein, Carol; Lederman, Ruth; Revette, Anna; Suarez, Aaron; Lee, Charlotte; Bryan, Jordan; Sholl, Lynette; Van Allen, Eliezer M

2018-05-01

Misinterpretation of complex genomic data presents a major challenge in the implementation of precision oncology. We sought to determine whether interactive genomic reports with embedded clinician education and optimized data visualization improved genomic data interpretation. We conducted a randomized, vignette-based survey study to determine whether exposure to interactive reports for a somatic gene panel, as compared to static reports, improves physicians' genomic comprehension and report-related satisfaction (overall scores calculated across 3 vignettes, range 0-18 and 1-4, respectively, higher score corresponding with improved endpoints). One hundred and five physicians at a tertiary cancer center participated (29% participation rate): 67% medical, 20% pediatric, 7% radiation, and 7% surgical oncology; 37% female. Prior to viewing the case-based vignettes, 34% of the physicians reported difficulty making treatment recommendations based on the standard static report. After vignette/report exposure, physicians' overall comprehension scores did not differ by report type (mean score: interactive 11.6 vs static 10.5, difference = 1.1, 95% CI, -0.3, 2.5, P = .13). However, physicians exposed to the interactive report were more likely to correctly assess sequencing quality (P < .001) and understand when reports needed to be interpreted with caution (eg, low tumor purity; P = .02). Overall satisfaction scores were higher in the interactive group (mean score 2.5 vs 2.1, difference = 0.4, 95% CI, 0.2-0.7, P = .001). Interactive genomic reports may improve physicians' ability to accurately assess genomic data and increase report-related satisfaction. Additional research in users' genomic needs and efforts to integrate interactive reports into electronic health records may facilitate the implementation of precision oncology.

Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption

NARCIS (Netherlands)

M. Cornelis (Marilyn); E.M. Byrne; T. Esko (Tõnu); M.A. Nalls (Michael); A. Ganna (Andrea); N.P. Paynter (Nina); K.L. Monda (Keri); N. Amin (Najaf); K. Fischer (Krista); F. Renström (Frida); J.S. Ngwa; V. Huikari (Ville); A. Cavadino (Alana); I.M. Nolte (Ilja M.); A. Teumer (Alexander); K. Yu; P. Marques-Vidal; R. Rawal; A. Manichaikul (Ani); M.K. Wojczynski (Mary ); J.M. Vink; J.H. Zhao (Jing Hua); G. Burlutsky (George); J. Lahti (Jari); V. Mikkilä (Vera); R.N. Lemaitre (Rozenn ); J. Eriksson; S. Musani (Solomon); T. Tanaka; F. Geller (Frank); J. Luan; J. Hui; R. Mägi (Reedik); M. Dimitriou (Maria); M. Garcia (Melissa); W.-K. Ho; M.J. Wright (Margaret); L.M. Rose (Lynda M.); P.K.E. Magnusson (Patrik K. E.); N.L. Pedersen (Nancy L.); D.J. Couper (David); B.A. Oostra (Ben); A. Hofman (Albert); M.A. Ikram (Arfan); H.W. Tiemeier (Henning); A.G. Uitterlinden (André); F.J.A. van Rooij (Frank); I. Barroso; I. Johansson (Ingegerd); L. Xue (Luting); M. Kaakinen (Marika); L. Milani (Lili); C. Power (Christine); H. Snieder (Harold); R.P. Stolk; S.E. Baumeister (Sebastian); R. Biffar; F. Gu; F. Bastardot (Francois); Z. Kutalik; D.R. Jacobs (David); N.G. Forouhi (Nita G.); E. Mihailov (Evelin); L. Lind (Lars); C. Lindgren; K. Michaëlsson; A.P. Morris (Andrew); M.K. Jensen (Majken K.); K.T. Khaw; R.N. Luben (Robert); J.J. Wang; S. Männistö (Satu); M.-M. Perälä; M. Kähönen (Mika); T. Lehtimäki (Terho); J. Viikari (Jorma); D. Mozaffarian; K. Mukamal (Kenneth); B.M. Psaty (Bruce); A. Döring; A.C. Heath (Andrew C.); G.W. Montgomery (Grant W.); N. Dahmen (N.); T. Carithers; K.L. Tucker; L. Ferrucci (Luigi); H.A. Boyd; M. Melbye (Mads); J.L. Treur; D. Mellström (Dan); J.J. Hottenga (Jouke Jan); I. Prokopenko (Inga); A. Tönjes (Anke); P. Deloukas (Panagiotis); S. Kanoni (Stavroula); M. Lorentzon (Mattias); D.K. Houston; Y. Liu; J. Danesh (John); A. Rasheed; M.A. Mason; A.B. Zonderman; L. Franke (Lude); B.S. Kristal; J. Karjalainen (Juha); D.R. Reed; H.-J. Westra; M.K. Evans; D. Saleheen; T.B. Harris (Tamara); G.V. Dedoussis (George V.); G.C. Curhan (Gary); M. Stumvoll (Michael); J. Beilby (John); L.R. Pasquale; B. Feenstra; S. Bandinelli; J.M. Ordovas; A.T. Chan; U. Peters (Ulrike); C. Ohlsson (Claes); C. Gieger (Christian); N.G. Martin (Nicholas); M. Waldenberger (Melanie); D.S. Siscovick (David); O. Raitakari (Olli); J.G. Eriksson (Johan G.); P. Mitchell (Paul); D. Hunter (David); P. Kraft (Peter); E.B. Rimm (Eric B.); D.I. Boomsma (Dorret); I.B. Borecki (Ingrid); R.J.F. Loos (Ruth); N.J. Wareham (Nick); P.K. Vollenweider (Peter K.); N. Caporaso; H.J. Grabe (Hans Jörgen); M.L. Neuhouser (Marian L.); B.H.R. Wolffenbuttel (Bruce H. R.); F.B. Hu (Frank); E. Hypponen (Elina); M.-R. Jarvelin (Marjo-Riitta); L.A. Cupples (Adrienne); P.W. Franks; P.M. Ridker (Paul); C.M. van Duijn (Cornelia); G. Heiss (Gerardo); A. Metspalu (Andres); K.E. North (Kari); E. Ingelsson (Erik); J.A. Nettleton; R.M. van Dam (Rob); D.I. Chasman (Daniel)

2015-01-01

textabstractCoffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day)

Clinical, polysomnographic and genome-wide association analyses of narcolepsy with cataplexy

DEFF Research Database (Denmark)

Luca, Gianina; Haba-Rubio, José; Dauvilliers, Yves

2013-01-01

diagnosed according to International Classification of Sleep Disorders-2. Demographic and clinical characteristics, polysomnography and multiple sleep latency test data, hypocretin-1 levels, and genome-wide genotypes were available. We found a significantly lower age at sleepiness onset (men versus women...

Case-control genome-wide association study of attention-deficit/hyperactivity disorder.

NARCIS (Netherlands)

Neale, B.M.; Medland, S.; Ripke, S.; Anney, R.J.; Asherson, P.; Buitelaar, J.K.; Franke, B.; Gill, M.; Kent, L.; Holmans, P.; Middleton, F.; Thapar, A.; Lesch, K.P.; Faraone, S.V.; Daly, M.; Nguyen, T.T.; Schafer, H.; Steinhausen, H.C.; Reif, A.; Renner, T.J.; Romanos, M.; Romanos, J.; Warnke, A.; Walitza, S.; Freitag, C.; Meyer, J.; Palmason, H.; Rothenberger, A.; Hawi, Z.; Sergeant, J.A.; Roeyers, H.; Mick, E.; Biederman, J.

2010-01-01

OBJECTIVE: Although twin and family studies have shown attention-deficit/hyperactivity disorder (ADHD) to be highly heritable, genetic variants influencing the trait at a genome-wide significant level have yet to be identified. Thus additional genomewide association studies (GWAS) are needed.

Genome-wide single-generation signatures of local selection in the panmictic European eel

DEFF Research Database (Denmark)

Pujolar, J. M.; Jacobsen, M. W.; Als, Thomas Damm

2014-01-01

Next-generation sequencing and the collection of genome-wide data allow identifying adaptive variation and footprints of directional selection. Using a large SNP data set from 259 RAD-sequenced European eel individuals (glass eels) from eight locations between 34 and 64oN, we examined the patterns...... of genome-wide genetic diversity across locations. We tested for local selection by searching for increased population differentiation using FST-based outlier tests and by testing for significant associations between allele frequencies and environmental variables. The overall low genetic differentiation...... with single-generation signatures of spatially varying selection acting on glass eels. After screening 50 354 SNPs, a total of 754 potentially locally selected SNPs were identified. Candidate genes for local selection constituted a wide array of functions, including calcium signalling, neuroactive ligand...

Genome-wide identification and characterization of WRKY gene family in peanut

Directory of Open Access Journals (Sweden)

Hui eSong

2016-04-01

Full Text Available WRKY, an important transcription factor family, is widely distributed in the plant kingdom. Many reports focused on analysis of phylogenetic relationship and biological function of WRKY protein at the whole genome level in different plant species. However, little is known about WRKY proteins in the genome of Arachis species and their response to salicylic acid (SA and jasmonic acid (JA treatment. In this study, we identified 77 and 75 WRKY proteins from the two wild ancestral diploid genomes of cultivated tetraploid peanut, Arachis duranensis and Arachis ipaënsis, using bioinformatics approaches. Most peanut WRKY coding genes were located on A. duranensis chromosome A6 and A. ipaënsis chromosome B3, while the least number of WRKY genes was found in chromosome 9. The WRKY orthologous gene pairs in A. duranensis and A. ipaënsis chromosomes were highly syntenic. Our analysis indicated that segmental duplication events played a major role in AdWRKY and AiWRKY genes, and strong purifying selection was observed in gene duplication pairs. Furthermore, we translate the knowledge gained from the genome-wide analysis result of wild ancestral peanut to cultivated peanut to reveal that gene activities of specific cultivated peanut WRKY gene were changed due to SA and JA treatment. Peanut WRKY7, 8 and 13 genes were down-regulated, whereas WRKY1 and 12 genes were up-regulated with SA and JA treatment. These results could provide valuable information for peanut improvement.

Genome-Wide Identification and Characterization of WRKY Gene Family in Peanut.

Science.gov (United States)

Song, Hui; Wang, Pengfei; Lin, Jer-Young; Zhao, Chuanzhi; Bi, Yuping; Wang, Xingjun

2016-01-01

WRKY, an important transcription factor family, is widely distributed in the plant kingdom. Many reports focused on analysis of phylogenetic relationship and biological function of WRKY protein at the whole genome level in different plant species. However, little is known about WRKY proteins in the genome of Arachis species and their response to salicylic acid (SA) and jasmonic acid (JA) treatment. In this study, we identified 77 and 75 WRKY proteins from the two wild ancestral diploid genomes of cultivated tetraploid peanut, Arachis duranensis and Arachis ipaënsis, using bioinformatics approaches. Most peanut WRKY coding genes were located on A. duranensis chromosome A6 and A. ipaënsis chromosome B3, while the least number of WRKY genes was found in chromosome 9. The WRKY orthologous gene pairs in A. duranensis and A. ipaënsis chromosomes were highly syntenic. Our analysis indicated that segmental duplication events played a major role in AdWRKY and AiWRKY genes, and strong purifying selection was observed in gene duplication pairs. Furthermore, we translate the knowledge gained from the genome-wide analysis result of wild ancestral peanut to cultivated peanut to reveal that gene activities of specific cultivated peanut WRKY gene were changed due to SA and JA treatment. Peanut WRKY7, 8 and 13 genes were down-regulated, whereas WRKY1 and 12 genes were up-regulated with SA and JA treatment. These results could provide valuable information for peanut improvement.

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies

Science.gov (United States)

Manitz, Juliane; Burger, Patricia; Amos, Christopher I.; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility. PMID:28785300

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.

Science.gov (United States)

Friedrichs, Stefanie; Manitz, Juliane; Burger, Patricia; Amos, Christopher I; Risch, Angela; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike; Hofner, Benjamin

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility.

Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption

NARCIS (Netherlands)

Cornelis, M. C.; Byrne, E. M.; Esko, T.; Nalls, M. A.; Ganna, A.; Paynter, N.; Monda, K. L.; Amin, N.; Fischer, K.; Renstrom, F.; Ngwa, J. S.; Huikari, V.; Cavadino, A.; Nolte, I. M.; Teumer, A.; Yu, K.; Marques-Vidal, P.; Rawal, R.; Manichaikul, A.; Wojczynski, M. K.; Vink, J. M.; Zhao, J. H.; Burlutsky, G.; Lahti, J.; Mikkila, V.; Lemaitre, R. N.; Eriksson, J.; Musani, S. K.; Tanaka, T.; Geller, F.; Luan, J.; Hui, J.; Maegi, R.; Dimitriou, M.; Garcia, M. E.; Ho, W-K; Wright, M. J.; Rose, L. M.; Magnusson, P. K. E.; Pedersen, N. L.; Couper, D.; Oostra, B. A.; Hofman, A.; Ikram, M. A.; Tiemeier, H. W.; Uitterlinden, A. G.; van Rooij, F. J. A.; Barroso, I.; Johansson, I.; Xue, L.; Kaakinen, M.; Milani, L.; Power, C.; Snieder, H.; Stolk, R. P.; Baumeister, S. E.; Biffar, R.; Gu, F.; Bastardot, F.; Kutalik, Z.; Jacobs, D. R.; Forouhi, N. G.; Mihailov, E.; Lind, L.; Lindgren, C.; Michaelsson, K.; Morris, A.; Jensen, M.; Khaw, K-T; Luben, R. N.; Wang, J. J.; Mannisto, S.; Perala, M-M; Kahonen, M.; Lehtimaki, T.; Viikari, J.; Mozaffarian, D.; Mukamal, K.; Psaty, B. M.; Doering, A.; Heath, A. C.; Montgomery, G. W.; Dahmen, N.; Carithers, T.; Tucker, K. L.; Ferrucci, L.; Boyd, H. A.; Melbye, M.; Treur, J. L.; Mellstrom, D.; Hottenga, J. J.; Prokopenko, I.; Toenjes, A.; Deloukas, P.; Kanoni, S.; Lorentzon, M.; Houston, D. K.; Liu, Y.; Danesh, J.; Rasheed, A.; Mason, M. A.; Zonderman, A. B.; Franke, L.; Kristal, B. S.; Karjalainen, J.; Reed, D. R.; Westra, H-J; Evans, M. K.; Saleheen, D.; Harris, T. B.; Dedoussis, G.; Curhan, G.; Stumvoll, M.; Beilby, J.; Pasquale, L. R.; Feenstra, B.; Bandinelli, S.; Ordovas, J. M.; Chan, A. T.; Peters, U.; Ohlsson, C.; Gieger, C.; Martin, N. G.; Waldenberger, M.; Siscovick, D. S.; Raitakari, O.; Eriksson, J. G.; Mitchell, P.; Hunter, D. J.; Kraft, P.; Rimm, E. B.; Boomsma, D. I.; Borecki, I. B.; Loos, R. J. F.; Wareham, N. J.; Vollenweider, P.; Caporaso, N.; Grabe, H. J.; Neuhouser, M. L.; Wolffenbuttel, B. H. R.; Hu, F. B.; Hyppoenen, E.; Jarvelin, M-R; Cupples, L. A.; Franks, P. W.; Ridker, P. M.; van Duijn, C. M.; Heiss, G.; Metspalu, A.; North, K. E.; Ingelsson, E.; Nettleton, J. A.; van Dam, R. M.; Chasman, D. I.

Coffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to

Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption

NARCIS (Netherlands)

Cornelis, M. C.; Byrne, E. M.; Esko, T.; Nalls, M. A.; Ganna, A.; Paynter, N.; Monda, K. L.; Amin, N.; Fischer, K.; Renstrom, F.; Ngwa, J. S.; Huikari, V.; Cavadino, A.; Nolte, I. M.; Teumer, A.; Yu, K.; Marques-Vidal, P.; Rawal, R.; Manichaikul, A.; Wojczynski, M. K.; Vink, J. M.; Zhao, J. H.; Burlutsky, G.; Lahti, J.; Mikkilä, V.; Lemaitre, R. N.; Eriksson, J.; Musani, S. K.; Tanaka, T.; Geller, F.; Luan, J.; Hui, J.; Mägi, R.; Dimitriou, M.; Garcia, M. E.; Ho, W.-K.; Wright, M. J.; Rose, L. M.; Magnusson, P. K. E.; Pedersen, N. L.; Couper, D.; Oostra, B. A.; Hofman, A.; Ikram, M. A.; Tiemeier, H. W.; Uitterlinden, A. G.; van Rooij, F. J. A.; Barroso, I.; Johansson, I.; Xue, L.; Kaakinen, M.; Milani, L.; Power, C.; Snieder, H.; Stolk, R. P.; Baumeister, S. E.; Biffar, R.; Gu, F.; Bastardot, F.; Kutalik, Z.; Jacobs, D. R.; Forouhi, N. G.; Mihailov, E.; Lind, L.; Lindgren, C.; Michaëlsson, K.; Morris, A.; Jensen, M.; Khaw, K.-T.; Luben, R. N.; Wang, J. J.; Männistö, S.; Perälä, M.-M.; Kähönen, M.; Lehtimäki, T.; Viikari, J.; Mozaffarian, D.; Mukamal, K.; Psaty, B. M.; Döring, A.; Heath, A. C.; Montgomery, G. W.; Dahmen, N.; Carithers, T.; Tucker, K. L.; Ferrucci, L.; Boyd, H. A.; Melbye, M.; Treur, J. L.; Mellström, D.; Hottenga, J. J.; Prokopenko, I.; Tönjes, A.; Deloukas, P.; Kanoni, S.; Lorentzon, M.; Houston, D. K.; Liu, Y.; Danesh, J.; Rasheed, A.; Mason, M. A.; Zonderman, A. B.; Franke, L.; Kristal, B. S.; Karjalainen, J.; Reed, D. R.; Westra, H.-J.; Evans, M. K.; Saleheen, D.; Harris, T. B.; Dedoussis, G.; Curhan, G.; Stumvoll, M.; Beilby, J.; Pasquale, L. R.; Feenstra, B.; Bandinelli, S.; Ordovas, J. M.; Chan, A. T.; Peters, U.; Ohlsson, C.; Gieger, C.; Martin, N. G.; Waldenberger, M.; Siscovick, D. S.; Raitakari, O.; Eriksson, J. G.; Mitchell, P.; Hunter, D. J.; Kraft, P.; Rimm, E. B.; Boomsma, D. I.; Borecki, I. B.; Loos, R. J. F.; Wareham, N. J.; Vollenweider, P.; Caporaso, N.; Grabe, H. J.; Neuhouser, M. L.; Wolffenbuttel, B. H. R.; Hu, F. B.; Hyppönen, E.; Järvelin, M.-R.; Cupples, L. A.; Franks, P. W.; Ridker, P. M.; van Duijn, C. M.; Heiss, G.; Metspalu, A.; North, K. E.; Ingelsson, E.; Nettleton, J. A.; van Dam, R. M.; Chasman, D. I.; Nalls, Michael A.; Plagnol, Vincent; Hernandez, Dena G.; Sharma, Manu; Sheerin, Una-Marie; Saad, Mohamad; Simón-Sánchez, Javier; Schulte, Claudia; Lesage, Suzanne; Sveinbjörnsdóttir, Sigurlaug; Arepalli, Sampath; Barker, Roger; Ben-Shlomo, Yoav; Berendse, Henk W.; Berg, Daniela; Bhatia, Kailash; de Bie, Rob M. A.; Biffi, Alessandro; Bloem, Bas; Bochdanovits, Zoltan; Bonin, Michael; Bras, M.; Brockmann, Kathrin; Brooks, Janet; Burn, David J.; Charlesworth, Gavin; Chen, Honglei; Chinnery, Patrick F.; Chong, Sean; Clarke, Carl E.; Cookson, Mark R.; Cooper, J. Mark; Corvol, Jean Christophe; Counsell, Carl; Damier, Philippe; Dartigues, Jean-François; Deloukas, Panos; Deuschl, Günther; Dexter, David T.; van Dijk, Karin D.; Dillman, Allissa; Durif, Frank; Dürr, Alexandra; Edkins, Sarah; Evans, Jonathan R.; Foltynie, Thomas; Dong, Jing; Gardner, Michelle; Gibbs, J. Raphael; Goate, Alison; Gray, Emma; Guerreiro, Rita; Harris, Clare; van Hilten, Jacobus J.; Hofman, Albert; Hollenbeck, Albert; Holton, Janice; Hu, Michele; Huang, Xuemei; Hershey, Milton S.; Wurster, Isabel; Mätzler, Walter; Hudson, Gavin; Hunt, Sarah E.; Huttenlocher, Johanna; Illig, Thomas; München, Helmholtz Zentrum; Jónsson, Pálmi V.; Lambert, Jean-Charles; Langford, Cordelia; Lees, Andrew; Lichtner, Peter; Limousin, Patricia; Lopez, Grisel; Lorenz, Delia; McNeill, Alisdair; Moorby, Catriona; Moore, Matthew; Morris, Huw R.; Morrison, Karen E.; O' Sullivan, Sean S.; Pearson, Justin; Perlmutter, Joel S.; Pétursson, Hjörvar; Pollak, Pierre; Potter, Simon; Ravina, Bernard; Revesz, Tamas; Riess, Olaf; Rivadeneira, Fernando; Rizzu, Patrizia; Ryten, Mina; Sawcer, Stephen; Schapira, Anthony; Scheffer, Hans; Shaw, Karen; Sidransky, Ellen; Smith, Colin; Spencer, Chris C. A.; Stefánsson, Hreinn; Bettella, Francesco; Stockton, Joanna D.; Strange, Amy; Talbot, Kevin; Tanner, M.; Tashakkori-Ghanbaria, Avazeh; Tison, François; Trabzuni, Daniah; Traynor, Bryan J.; Uitterlinden, André G.; Velseboer, Daan; Vidailhet, Marie; Walker, Robert; van de Warrenburg, Bart; Wickremaratchi, Mirdhu; Williams, Nigel; Williams-Gray, Caroline H.; Winder-Rhodes, Sophie; Stefánsson, Kári; Martinez, Maria; Sabatier, Paul; Wood, Nicholas W.; Hardy, John; Heutink, Peter; Brice, Alexis; Gasser, Thomas; Singleton, Andrew B.; Singleton, Andrew; Cookson, Mark; Hernandez, Dena; Nalls, Michael; Zonderman, Alan; Ferrucci, Luigi; Johnson, Robert; Longo, Dan; O'Brien, Richard; Traynor, Bryan; Troncoso, Juan; van der Brug, Marcel; Zielke, Ronald; Weale, Michael; Ramasamy, Adaikalavan; Box, P. O.

2015-01-01

Coffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to

Genome-wide profiling of the PIWI-interacting RNA-mRNA regulatory networks in epithelial ovarian cancers.

Science.gov (United States)

Singh, Garima; Roy, Jyoti; Rout, Pratiti; Mallick, Bibekanand

2018-01-01

PIWI-interacting (piRNAs), ~23-36 nucleotide-long small non-coding RNAs (sncRNAs), earlier believed to be germline-specific, have now been identified in somatic cells, including cancer cells. These sncRNAs impact critical biological processes by fine-tuning gene expression at post-transcriptional and epigenetic levels. The expression of piRNAs in ovarian cancer, the most lethal gynecologic cancer is largely uncharted. In this study, we investigated the expression of PIWILs by qRT-PCR and western blotting and then identified piRNA transcriptomes in tissues of normal ovary and two most prevalent epithelial ovarian cancer subtypes, serous and endometrioid by small RNA sequencing. We detected 219, 256 and 234 piRNAs in normal ovary, endometrioid and serous ovarian cancer samples respectively. We observed piRNAs are encoded from various genomic regions, among which introns harbor the majority of them. Surprisingly, piRNAs originated from different genomic contexts showed the varied level of conservations across vertebrates. The functional analysis of predicted targets of differentially expressed piRNAs revealed these could modulate key processes and pathways involved in ovarian oncogenesis. Our study provides the first comprehensive piRNA landscape in these samples and a useful resource for further functional studies to decipher new mechanistic views of piRNA-mediated gene regulatory networks affecting ovarian oncogenesis. The RNA-seq data is submitted to GEO database (GSE83794).

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 =

Genome wide predictions of miRNA regulation by transcription factors.

Science.gov (United States)

Ruffalo, Matthew; Bar-Joseph, Ziv

2016-09-01

Reconstructing regulatory networks from expression and interaction data is a major goal of systems biology. While much work has focused on trying to experimentally and computationally determine the set of transcription-factors (TFs) and microRNAs (miRNAs) that regulate genes in these networks, relatively little work has focused on inferring the regulation of miRNAs by TFs. Such regulation can play an important role in several biological processes including development and disease. The main challenge for predicting such interactions is the very small positive training set currently available. Another challenge is the fact that a large fraction of miRNAs are encoded within genes making it hard to determine the specific way in which they are regulated. To enable genome wide predictions of TF-miRNA interactions, we extended semi-supervised machine-learning approaches to integrate a large set of different types of data including sequence, expression, ChIP-seq and epigenetic data. As we show, the methods we develop achieve good performance on both a labeled test set, and when analyzing general co-expression networks. We next analyze mRNA and miRNA cancer expression data, demonstrating the advantage of using the predicted set of interactions for identifying more coherent and relevant modules, genes, and miRNAs. The complete set of predictions is available on the supporting website and can be used by any method that combines miRNAs, genes, and TFs. Code and full set of predictions are available from the supporting website: http://cs.cmu.edu/~mruffalo/tf-mirna/ zivbj@cs.cmu.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Three invariant Hi-C interaction patterns: Applications to genome assembly.

Science.gov (United States)

Oddes, Sivan; Zelig, Aviv; Kaplan, Noam

2018-06-01

Assembly of reference-quality genomes from next-generation sequencing data is a key challenge in genomics. Recently, we and others have shown that Hi-C data can be used to address several outstanding challenges in the field of genome assembly. This principle has since been developed in academia and industry, and has been used in the assembly of several major genomes. In this paper, we explore the central principles underlying Hi-C-based assembly approaches, by quantitatively defining and characterizing three invariant Hi-C interaction patterns on which these approaches can build: Intrachromosomal interaction enrichment, distance-dependent interaction decay and local interaction smoothness. Specifically, we evaluate to what degree each invariant pattern holds on a single locus level in different species, cell types and Hi-C map resolutions. We find that these patterns are generally consistent across species and cell types but are affected by sequencing depth, and that matrix balancing improves consistency of loci with all three invariant patterns. Finally, we overview current Hi-C-based assembly approaches in light of these invariant patterns and demonstrate how local interaction smoothness can be used to easily detect scaffolding errors in extremely sparse Hi-C maps. We suggest that simultaneously considering all three invariant patterns may lead to better Hi-C-based genome assembly methods. Copyright © 2018 Elsevier Inc. All rights reserved.

Genome-wide association study of proneness to anger.

Directory of Open Access Journals (Sweden)

Eric Mick

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

Unraveling the genetic etiology of adult antisocial behavior: a genome-wide association study.

Directory of Open Access Journals (Sweden)

Jorim J Tielbeek

Full Text Available Crime poses a major burden for society. The heterogeneous nature of criminal behavior makes it difficult to unravel its causes. Relatively little research has been conducted on the genetic influences of criminal behavior. The few twin and adoption studies that have been undertaken suggest that about half of the variance in antisocial behavior can be explained by genetic factors. In order to identify the specific common genetic variants underlying this behavior, we conduct the first genome-wide association study (GWAS on adult antisocial behavior. Our sample comprised a community sample of 4816 individuals who had completed a self-report questionnaire. No genetic polymorphisms reached genome-wide significance for association with adult antisocial behavior. In addition, none of the traditional candidate genes can be confirmed in our study. While not genome-wide significant, the gene with the strongest association (p-value = 8.7×10(-5 was DYRK1A, a gene previously related to abnormal brain development and mental retardation. Future studies should use larger, more homogeneous samples to disentangle the etiology of antisocial behavior. Biosocial criminological research allows a more empirically grounded understanding of criminal behavior, which could ultimately inform and improve current treatment strategies.

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

Science.gov (United States)

2011-09-01

SNP Array v2. A ‘proof-of-concept’ advanced data mining algorithm for unsupervised analysis of genome-wide association study (GWAS) dataset was... Opal F AUS Yes U141 Peggs F AUS Yes U142 Taxi F AUS Yes U143 Riso MI MAL Yes U144 Szarik MI GSD Yes U145 Astor MI MAL Yes U146 Roy MC MAL Yes... mining of genetic studies in general, and especially GWAS. As a proof-of-concept, a classification analysis of the WG SNP typing dataset of a

Genome-wide association analysis of thirty one production, health, reproduction and body conformation traits in contemporary U.S. Holstein cows

Directory of Open Access Journals (Sweden)

Van Tassell Curtis P

2011-08-01

Full Text Available Abstract Background Genome-wide association analysis is a powerful tool for annotating phenotypic effects on the genome and knowledge of genes and chromosomal regions associated with dairy phenotypes is useful for genome and gene-based selection. Here, we report results of a genome-wide analysis of predicted transmitting ability (PTA of 31 production, health, reproduction and body conformation traits in contemporary Holstein cows. Results Genome-wide association analysis identified a number of candidate genes and chromosome regions associated with 31 dairy traits in contemporary U.S. Holstein cows. Highly significant genes and chromosome regions include: BTA13's GNAS region for milk, fat and protein yields; BTA7's INSR region and BTAX's LOC520057 and GRIA3 for daughter pregnancy rate, somatic cell score and productive life; BTA2's LRP1B for somatic cell score; BTA14's DGAT1-NIBP region for fat percentage; BTA1's FKBP2 for protein yields and percentage, BTA26's MGMT and BTA6's PDGFRA for protein percentage; BTA18's 53.9-58.7 Mb region for service-sire and daughter calving ease and service-sire stillbirth; BTA18's PGLYRP1-IGFL1 region for a large number of traits; BTA18's LOC787057 for service-sire stillbirth and daughter calving ease; BTA15's CD82, BTA23's DST and the MOCS1-LRFN2 region for daughter stillbirth; and BTAX's LOC520057 and GRIA3 for daughter pregnancy rate. For body conformation traits, BTA11, BTAX, BTA10, BTA5, and BTA26 had the largest concentrations of SNP effects, and PHKA2 of BTAX and REN of BTA16 had the most significant effects for body size traits. For body shape traits, BTAX, BTA19 and BTA3 were most significant. Udder traits were affected by BTA16, BTA22, BTAX, BTA2, BTA10, BTA11, BTA20, BTA22 and BTA25, teat traits were affected by BTA6, BTA7, BTA9, BTA16, BTA11, BTA26 and BTA17, and feet/legs traits were affected by BTA11, BTA13, BTA18, BTA20, and BTA26. Conclusions Genome-wide association analysis identified a number of

Genome-wide association study for ovarian cancer susceptibility using pooled DNA.

NARCIS (Netherlands)

Lu, Y.; Chen, X.; Beesley, J.; Johnatty, S.E.; Defazio, A.; Lambrechts, S.; Lambrechts, D.; Despierre, E.; Vergotes, I.; Chang-Claude, J.; Hein, R.; Nickels, S.; Wang-Gohrke, S.; Dork, T.; Durst, M.; Antonenkova, N.; Bogdanova, N.; Goodman, M.T.; Lurie, G.; Wilkens, L.R.; Carney, M.E.; Butzow, R.; Nevanlinna, H.; Heikkinen, T.; Leminen, A.; Kiemeney, L.A.L.M.; Massuger, L.F.A.G.; Altena, A.M. van; Aben, K.K.H.; Kjaer, S.K.; Hogdall, E.; Jensen, A.; Brooks-Wilson, A.; Le, N.; Cook, L.; Earp, M.; Kelemen, L.; Easton, D.; Pharoah, P.; Song, H.; Tyrer, J.; Ramus, S.; Menon, U.; Gentry-Maharaj, A.; Gayther, S.A.; Bandera, E.V.; Olson, S.H.; Orlow, I.; Rodriguez-Rodriguez, L.; MacGregor, S.; Chenevix-Trench, G.

2012-01-01

Recent Genome-Wide Association Studies (GWAS) have identified four low-penetrance ovarian cancer susceptibility loci. We hypothesized that further moderate- or low-penetrance variants exist among the subset of single-nucleotide polymorphisms (SNPs) not well tagged by the genotyping arrays used in

Genome-wide identification, functional and evolutionary analysis of terpene synthases in pineapple.

Science.gov (United States)

Chen, Xiaoe; Yang, Wei; Zhang, Liqin; Wu, Xianmiao; Cheng, Tian; Li, Guanglin

2017-10-01

Terpene synthases (TPSs) are vital for the biosynthesis of active terpenoids, which have important physiological, ecological and medicinal value. Although terpenoids have been reported in pineapple (Ananas comosus), genome-wide investigations of the TPS genes responsible for pineapple terpenoid synthesis are still lacking. By integrating pineapple genome and proteome data, twenty-one putative terpene synthase genes were found in pineapple and divided into five subfamilies. Tandem duplication is the cause of TPS gene family duplication. Furthermore, functional differentiation between each TPS subfamily may have occurred for several reasons. Sixty-two key amino acid sites were identified as being type-II functionally divergence between TPS-a and TPS-c subfamily. Finally, coevolution analysis indicated that multiple amino acid residues are involved in coevolutionary processes. In addition, the enzyme activity of two TPSs were tested. This genome-wide identification, functional and evolutionary analysis of pineapple TPS genes provide a new insight into understanding the roles of TPS family and lay the basis for further characterizing the function and evolution of TPS gene family. Copyright © 2017 Elsevier Ltd. All rights reserved.

A genome-wide association study in chronic obstructive pulmonary disease (COPD: identification of two major susceptibility loci.

Directory of Open Access Journals (Sweden)

Sreekumar G Pillai

2009-03-01

Full Text Available There is considerable variability in the susceptibility of smokers to develop chronic obstructive pulmonary disease (COPD. The only known genetic risk factor is severe deficiency of alpha(1-antitrypsin, which is present in 1-2% of individuals with COPD. We conducted a genome-wide association study (GWAS in a homogenous case-control cohort from Bergen, Norway (823 COPD cases and 810 smoking controls and evaluated the top 100 single nucleotide polymorphisms (SNPs in the family-based International COPD Genetics Network (ICGN; 1891 Caucasian individuals from 606 pedigrees study. The polymorphisms that showed replication were further evaluated in 389 subjects from the US National Emphysema Treatment Trial (NETT and 472 controls from the Normative Aging Study (NAS and then in a fourth cohort of 949 individuals from 127 extended pedigrees from the Boston Early-Onset COPD population. Logistic regression models with adjustments of covariates were used to analyze the case-control populations. Family-based association analyses were conducted for a diagnosis of COPD and lung function in the family populations. Two SNPs at the alpha-nicotinic acetylcholine receptor (CHRNA 3/5 locus were identified in the genome-wide association study. They showed unambiguous replication in the ICGN family-based analysis and in the NETT case-control analysis with combined p-values of 1.48 x 10(-10, (rs8034191 and 5.74 x 10(-10 (rs1051730. Furthermore, these SNPs were significantly associated with lung function in both the ICGN and Boston Early-Onset COPD populations. The C allele of the rs8034191 SNP was estimated to have a population attributable risk for COPD of 12.2%. The association of hedgehog interacting protein (HHIP locus on chromosome 4 was also consistently replicated, but did not reach genome-wide significance levels. Genome-wide significant association of the HHIP locus with lung function was identified in the Framingham Heart study (Wilk et al., companion article

Quantification and genome-wide mapping of DNA double-strand breaks.

Science.gov (United States)

Grégoire, Marie-Chantal; Massonneau, Julien; Leduc, Frédéric; Arguin, Mélina; Brazeau, Marc-André; Boissonneault, Guylain

2016-12-01

DNA double-strand breaks (DSBs) represent a major threat to the genetic integrity of the cell. Knowing both their genome-wide distribution and number is important for a better assessment of genotoxicity at a molecular level. Available methods may have underestimated the extent of DSBs as they are based on markers specific to those undergoing active repair or may not be adapted for the large diversity of naturally occurring DNA ends. We have established conditions for an efficient first step of DNA nick and gap repair (NGR) allowing specific determination of DSBs by end labeling with terminal transferase. We used DNA extracted from HeLa cells harboring an I-SceI cassette to induce a targeted nick or DSB and demonstrated by immunocapture of 3'-OH that a prior step of NGR allows specific determination of loci-specific or genome wide DSBs. This method can be applied to the global determination of DSBs using radioactive end labeling and can find several applications aimed at understanding the distribution and kinetics of DSBs formation and repair. Copyright © 2016 Elsevier B.V. All rights reserved.

Trends in genome-wide and region-specific genetic diversity in the Dutch-Flemish Holstein-Friesian breeding program from 1986 to 2015.

Science.gov (United States)

Doekes, Harmen P; Veerkamp, Roel F; Bijma, Piter; Hiemstra, Sipke J; Windig, Jack J

2018-04-11

In recent decades, Holstein-Friesian (HF) selection schemes have undergone profound changes, including the introduction of optimal contribution selection (OCS; around 2000), a major shift in breeding goal composition (around 2000) and the implementation of genomic selection (GS; around 2010). These changes are expected to have influenced genetic diversity trends. Our aim was to evaluate genome-wide and region-specific diversity in HF artificial insemination (AI) bulls in the Dutch-Flemish breeding program from 1986 to 2015. Pedigree and genotype data (~ 75.5 k) of 6280 AI-bulls were used to estimate rates of genome-wide inbreeding and kinship and corresponding effective population sizes. Region-specific inbreeding trends were evaluated using regions of homozygosity (ROH). Changes in observed allele frequencies were compared to those expected under pure drift to identify putative regions under selection. We also investigated the direction of changes in allele frequency over time. Effective population size estimates for the 1986-2015 period ranged from 69 to 102. Two major breakpoints were observed in genome-wide inbreeding and kinship trends. Around 2000, inbreeding and kinship levels temporarily dropped. From 2010 onwards, they steeply increased, with pedigree-based, ROH-based and marker-based inbreeding rates as high as 1.8, 2.1 and 2.8% per generation, respectively. Accumulation of inbreeding varied substantially across the genome. A considerable fraction of markers showed changes in allele frequency that were greater than expected under pure drift. Putative selected regions harboured many quantitative trait loci (QTL) associated to a wide range of traits. In consecutive 5-year periods, allele frequencies changed more often in the same direction than in opposite directions, except when comparing the 1996-2000 and 2001-2005 periods. Genome-wide and region-specific diversity trends reflect major changes in the Dutch-Flemish HF breeding program. Introduction of

Genome-wide association studies in asthma: progress and pitfalls

Directory of Open Access Journals (Sweden)

March ME

2015-01-01

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

Genome-wide associations of gene expression variation in humans.

Directory of Open Access Journals (Sweden)

Barbara E Stranger

2005-12-01

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

Genome-Wide Associations of Gene Expression Variation in Humans.

Directory of Open Access Journals (Sweden)

2005-12-01

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

A genome-wide scan for common alleles affecting risk for autism.

LENUS (Irish Health Repository)

Anney, Richard

2010-10-15

Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10(-8). When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner\\'s curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10(-8) threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C.

A genome-wide scan for common alleles affecting risk for autism.

Science.gov (United States)

Anney, Richard; Klei, Lambertus; Pinto, Dalila; Regan, Regina; Conroy, Judith; Magalhaes, Tiago R; Correia, Catarina; Abrahams, Brett S; Sykes, Nuala; Pagnamenta, Alistair T; Almeida, Joana; Bacchelli, Elena; Bailey, Anthony J; Baird, Gillian; Battaglia, Agatino; Berney, Tom; Bolshakova, Nadia; Bölte, Sven; Bolton, Patrick F; Bourgeron, Thomas; Brennan, Sean; Brian, Jessica; Carson, Andrew R; Casallo, Guillermo; Casey, Jillian; Chu, Su H; Cochrane, Lynne; Corsello, Christina; Crawford, Emily L; Crossett, Andrew; Dawson, Geraldine; de Jonge, Maretha; Delorme, Richard; Drmic, Irene; Duketis, Eftichia; Duque, Frederico; Estes, Annette; Farrar, Penny; Fernandez, Bridget A; Folstein, Susan E; Fombonne, Eric; Freitag, Christine M; Gilbert, John; Gillberg, Christopher; Glessner, Joseph T; Goldberg, Jeremy; Green, Jonathan; Guter, Stephen J; Hakonarson, Hakon; Heron, Elizabeth A; Hill, Matthew; Holt, Richard; Howe, Jennifer L; Hughes, Gillian; Hus, Vanessa; Igliozzi, Roberta; Kim, Cecilia; Klauck, Sabine M; Kolevzon, Alexander; Korvatska, Olena; Kustanovich, Vlad; Lajonchere, Clara M; Lamb, Janine A; Laskawiec, Magdalena; Leboyer, Marion; Le Couteur, Ann; Leventhal, Bennett L; Lionel, Anath C; Liu, Xiao-Qing; Lord, Catherine; Lotspeich, Linda; Lund, Sabata C; Maestrini, Elena; Mahoney, William; Mantoulan, Carine; Marshall, Christian R; McConachie, Helen; McDougle, Christopher J; McGrath, Jane; McMahon, William M; Melhem, Nadine M; Merikangas, Alison; Migita, Ohsuke; Minshew, Nancy J; Mirza, Ghazala K; Munson, Jeff; Nelson, Stanley F; Noakes, Carolyn; Noor, Abdul; Nygren, Gudrun; Oliveira, Guiomar; Papanikolaou, Katerina; Parr, Jeremy R; Parrini, Barbara; Paton, Tara; Pickles, Andrew; Piven, Joseph; Posey, David J; Poustka, Annemarie; Poustka, Fritz; Prasad, Aparna; Ragoussis, Jiannis; Renshaw, Katy; Rickaby, Jessica; Roberts, Wendy; Roeder, Kathryn; Roge, Bernadette; Rutter, Michael L; Bierut, Laura J; Rice, John P; Salt, Jeff; Sansom, Katherine; Sato, Daisuke; Segurado, Ricardo; Senman, Lili; Shah, Naisha; Sheffield, Val C; Soorya, Latha; Sousa, Inês; Stoppioni, Vera; Strawbridge, Christina; Tancredi, Raffaella; Tansey, Katherine; Thiruvahindrapduram, Bhooma; Thompson, Ann P; Thomson, Susanne; Tryfon, Ana; Tsiantis, John; Van Engeland, Herman; Vincent, John B; Volkmar, Fred; Wallace, Simon; Wang, Kai; Wang, Zhouzhi; Wassink, Thomas H; Wing, Kirsty; Wittemeyer, Kerstin; Wood, Shawn; Yaspan, Brian L; Zurawiecki, Danielle; Zwaigenbaum, Lonnie; Betancur, Catalina; Buxbaum, Joseph D; Cantor, Rita M; Cook, Edwin H; Coon, Hilary; Cuccaro, Michael L; Gallagher, Louise; Geschwind, Daniel H; Gill, Michael; Haines, Jonathan L; Miller, Judith; Monaco, Anthony P; Nurnberger, John I; Paterson, Andrew D; Pericak-Vance, Margaret A; Schellenberg, Gerard D; Scherer, Stephen W; Sutcliffe, James S; Szatmari, Peter; Vicente, Astrid M; Vieland, Veronica J; Wijsman, Ellen M; Devlin, Bernie; Ennis, Sean; Hallmayer, Joachim

2010-10-15

Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10(-8). When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10(-8) threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C.

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

Directory of Open Access Journals (Sweden)

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

Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson's disease

NARCIS (Netherlands)

Nalls, Mike A.; Pankratz, Nathan; Lill, Christina M.; Do, Chuong B.; Hernandez, Dena G.; Saad, Mohamad; DeStefano, Anita L.; Kara, Eleanna; Bras, Jose; Sharma, Manu; Schulte, Claudia; Keller, Margaux F.; Arepalli, Sampath; Letson, Christopher; Edsall, Connor; Stefansson, Hreinn; Liu, Xinmin; Pliner, Hannah; Lee, Joseph H.; Cheng, Rong; Ikram, M. Arfan; Ioannidis, John P. A.; Hadjigeorgiou, Georgios M.; Bis, Joshua C.; Martinez, Maria; Perlmutter, Joel S.; Goate, Alison; Marder, Karen; Fiske, Brian; Sutherland, Margaret; Xiromerisiou, Georgia; Myers, Richard H.; Clark, Lorraine N.; Stefansson, Kari; Hardy, John A.; Heutink, Peter; Chen, Honglei; Wood, Nicholas W.; Houlden, Henry; Payami, Haydeh; Brice, Alexis; Scott, William K.; Gasser, Thomas; Bertram, Lars; Eriksson, Nicholas; Foroud, Tatiana; Singleton, Andrew B.; Plagnol, Vincent; Sheerin, Una-Marie; Simón-Sánchez, Javier; Lesage, Suzanne; Sveinbjörnsdóttir, Sigurlaug; Barker, Roger; Ben-Shlomo, Yoav; Berendse, Henk W.; Berg, Daniela; Bhatia, Kailash; de Bie, Rob M. A.; Biffi, Alessandro; Bloem, Bas; Bochdanovits, Zoltan; Bonin, Michael; Bras, Jose M.; Brockmann, Kathrin; Brooks, Janet; Burn, David J.; Charlesworth, Gavin; Chinnery, Patrick F.; Chong, Sean; Clarke, Carl E.; Cookson, Mark R.; Cooper, J. Mark; Corvol, Jean Christophe; Counsell, Carl; Damier, Philippe; Dartigues, Jean-François; Deloukas, Panos; Deuschl, Günther; Dexter, David T.; van Dijk, Karin D.; Dillman, Allissa; Durif, Frank; Dürr, Alexandra; Edkins, Sarah; Evans, Jonathan R.; Foltynie, Thomas; Dong, Jing; Gardner, Michelle; Gibbs, J. Raphael; Gray, Emma; Guerreiro, Rita; Harris, Clare; van Hilten, Jacobus J.; Hofman, Albert; Hollenbeck, Albert; Holton, Janice; Hu, Michele; Huang, Xuemei; Wurster, Isabel; Mätzler, Walter; Hudson, Gavin; Hunt, Sarah E.; Huttenlocher, Johanna; Illig, Thomas; Jónsson, Pálmi V.; Lambert, Jean-Charles; Langford, Cordelia; Lees, Andrew; Lichtner, Peter; Limousin, Patricia; Lopez, Grisel; Lorenz, Delia; McNeill, Alisdair; Moorby, Catriona; Moore, Matthew; Morris, Huw R.; Morrison, Karen E.; Mudanohwo, Ese; O'Sullivan, Sean S.; Pearson, Justin; Pétursson, Hjörvar; Pollak, Pierre; Post, Bart; Potter, Simon; Ravina, Bernard; Revesz, Tamas; Riess, Olaf; Rivadeneira, Fernando; Rizzu, Patrizia; Ryten, Mina; Sawcer, Stephen; Schapira, Anthony; Scheffer, Hans; Shaw, Karen; Shoulson, Ira; Sidransky, Ellen; Smith, Colin; Spencer, Chris C. A.; Stefánsson, Hreinn; Bettella, Francesco; Stockton, Joanna D.; Strange, Amy; Talbot, Kevin; Tanner, Carlie M.; Tashakkori-Ghanbaria, Avazeh; Tison, François; Trabzuni, Daniah; Traynor, Bryan J.; Uitterlinden, André G.; Velseboer, Daan; Vidailhet, Marie; Walker, Robert; van de Warrenburg, Bart; Wickremaratchi, Mirdhu; Williams, Nigel; Williams-Gray, Caroline H.; Winder-Rhodes, Sophie; Stefánsson, Kári; Hardy, John; Factor, S.; Higgins, D.; Evans, S.; Shill, H.; Stacy, M.; Danielson, J.; Marlor, L.; Williamson, K.; Jankovic, J.; Hunter, C.; Simon, D.; Ryan, P.; Scollins, L.; Saunders-Pullman, R.; Boyar, K.; Costan-Toth, C.; Ohmann, E.; Sudarsky, L.; Joubert, C.; Friedman, J.; Chou, K.; Fernandez, H.; Lannon, M.; Galvez-Jimenez, N.; Podichetty, A.; Thompson, K.; Lewitt, P.; Deangelis, M.; O'Brien, C.; Seeberger, L.; Dingmann, C.; Judd, D.; Marder, K.; Fraser, J.; Harris, J.; Bertoni, J.; Peterson, C.; Rezak, M.; Medalle, G.; Chouinard, S.; Panisset, M.; Hall, J.; Poiffaut, H.; Calabrese, V.; Roberge, P.; Wojcieszek, J.; Belden, J.; Jennings, D.; Marek, K.; Mendick, S.; Reich, S.; Dunlop, B.; Jog, M.; Horn, C.; Uitti, R.; Turk, M.; Ajax, T.; Mannetter, J.; Sethi, K.; Carpenter, J.; Dill, B.; Hatch, L.; Ligon, K.; Narayan, S.; Blindauer, K.; Abou-Samra, K.; Petit, J.; Elmer, L.; Aiken, E.; Davis, K.; Schell, C.; Wilson, S.; Velickovic, M.; Koller, W.; Phipps, S.; Feigin, A.; Gordon, M.; Hamann, J.; Licari, E.; Marotta-Kollarus, M.; Shannon, B.; Winnick, R.; Simuni, T.; Videnovic, A.; Kaczmarek, A.; Williams, K.; Wolff, M.; Rao, J.; Cook, M.; Fernandez, M.; Kostyk, S.; Hubble, J.; Campbell, A.; Reider, C.; Seward, A.; Camicioli, R.; Carter, J.; Nutt, J.; Andrews, P.; Morehouse, S.; Stone, C.; Mendis, T.; Grimes, D.; Alcorn-Costa, C.; Gray, P.; Haas, K.; Vendette, J.; Sutton, J.; Hutchinson, B.; Young, J.; Rajput, A.; Klassen, L.; Shirley, T.; Manyam, B.; Simpson, P.; Whetteckey, J.; Wulbrecht, B.; Truong, D.; Pathak, M.; Frei, K.; Luong, N.; Tra, T.; Tran, A.; Vo, J.; Lang, A.; Kleiner- Fisman, G.; Nieves, A.; Johnston, L.; So, J.; Podskalny, G.; Giffin, L.; Atchison, P.; Allen, C.; Martin, W.; Wieler, M.; Suchowersky, O.; Furtado, S.; Klimek, M.; Hermanowicz, N.; Niswonger, S.; Shults, C.; Fontaine, D.; Aminoff, M.; Christine, C.; Diminno, M.; Hevezi, J.; Dalvi, A.; Kang, U.; Richman, J.; Uy, S.; Sahay, A.; Gartner, M.; Schwieterman, D.; Hall, D.; Leehey, M.; Culver, S.; Derian, T.; Demarcaida, T.; Thurlow, S.; Rodnitzky, R.; Dobson, J.; Lyons, K.; Pahwa, R.; Gales, T.; Thomas, S.; Shulman, L.; Weiner, W.; Dustin, K.; Singer, C.; Zelaya, L.; Tuite, P.; Hagen, V.; Rolandelli, S.; Schacherer, R.; Kosowicz, J.; Gordon, P.; Werner, J.; Serrano, C.; Roque, S.; Kurlan, R.; Berry, D.; Gardiner, I.; Hauser, R.; Sanchez-Ramos, J.; Zesiewicz, T.; Delgado, H.; Price, K.; Rodriguez, P.; Wolfrath, S.; Pfeiffer, R.; Davis, L.; Pfeiffer, B.; Dewey, R.; Hayward, B.; Johnson, A.; Meacham, M.; Estes, B.; Walker, F.; Hunt, V.; O'Neill, C.; Racette, B.; Swisher, L.; Dijamco, Cheri; Conley, Emily Drabant; Dorfman, Elizabeth; Tung, Joyce Y.; Hinds, David A.; Mountain, Joanna L.; Wojcicki, Anne; Lew, M.; Klein, C.; Golbe, L.; Growdon, J.; Wooten, G. F.; Watts, R.; Guttman, M.; Goldwurm, S.; Saint-Hilaire, M. H.; Baker, K.; Litvan, I.; Nicholson, G.; Nance, M.; Drasby, E.; Isaacson, S.; Burn, D.; Pramstaller, P.; Al-hinti, J.; Moller, A.; Sherman, S.; Roxburgh, R.; Slevin, J.; Perlmutter, J.; Mark, M. H.; Huggins, N.; Pezzoli, G.; Massood, T.; Itin, I.; Corbett, A.; Chinnery, P.; Ostergaard, K.; Snow, B.; Cambi, F.; Kay, D.; Samii, A.; Agarwal, P.; Roberts, J. W.; Higgins, D. S.; Molho, Eric; Rosen, Ami; Montimurro, J.; Martinez, E.; Griffith, A.; Kusel, V.; Yearout, D.; Zabetian, C.; Clark, L. N.; Liu, X.; Lee, J. H.; Taub, R. Cheng; Louis, E. D.; Cote, L. J.; Waters, C.; Ford, B.; Fahn, S.; Vance, Jeffery M.; Beecham, Gary W.; Martin, Eden R.; Nuytemans, Karen; Pericak-Vance, Margaret A.; Haines, Jonathan L.; DeStefano, Anita; Seshadri, Sudha; Choi, Seung Hoan; Frank, Samuel; Psaty, Bruce M.; Rice, Kenneth; Longstreth, W. T.; Ton, Thanh G. N.; Jain, Samay; van Duijn, Cornelia M.; Verlinden, Vincent J.; Koudstaal, Peter J.; Singleton, Andrew; Cookson, Mark; Hernandez, Dena; Nalls, Michael; Zonderman, Alan; Ferrucci, Luigi; Johnson, Robert; Longo, Dan; O'Brien, Richard; Traynor, Bryan; Troncoso, Juan; van der Brug, Marcel; Zielke, Ronald; Weale, Michael; Ramasamy, Adaikalavan; Dardiotis, Efthimios; Tsimourtou, Vana; Spanaki, Cleanthe; Plaitakis, Andreas; Bozi, Maria; Stefanis, Leonidas; Vassilatis, Dimitris; Koutsis, Georgios; Panas, Marios; Lunnon, Katie; Lupton, Michelle; Powell, John; Parkkinen, Laura; Ansorge, Olaf

2014-01-01

We conducted a meta-analysis of Parkinson's disease genome-wide association studies using a common set of 7,893,274 variants across 13,708 cases and 95,282 controls. Twenty-six loci were identified as having genome-wide significant association; these and 6 additional previously reported loci were

Genome-wide association study identifies six new loci influencing pulse pressure and mean arterial pressure

Science.gov (United States)

Wain, Louise V; Verwoert, Germaine C; O’Reilly, Paul F; Shi, Gang; Johnson, Toby; Johnson, Andrew D; Bochud, Murielle; Rice, Kenneth M; Henneman, Peter; Smith, Albert V; Ehret, Georg B; Amin, Najaf; Larson, Martin G; Mooser, Vincent; Hadley, David; Dörr, Marcus; Bis, Joshua C; Aspelund, Thor; Esko, Tõnu; Janssens, A Cecile JW; Zhao, Jing Hua; Heath, Simon; Laan, Maris; Fu, Jingyuan; Pistis, Giorgio; Luan, Jian’an; Arora, Pankaj; Lucas, Gavin; Pirastu, Nicola; Pichler, Irene; Jackson, Anne U; Webster, Rebecca J; Zhang, Feng; Peden, John F; Schmidt, Helena; Tanaka, Toshiko; Campbell, Harry; Igl, Wilmar; Milaneschi, Yuri; Hotteng, Jouke-Jan; Vitart, Veronique; Chasman, Daniel I; Trompet, Stella; Bragg-Gresham, Jennifer L; Alizadeh, Behrooz Z; Chambers, John C; Guo, Xiuqing; Lehtimäki, Terho; Kühnel, Brigitte; Lopez, Lorna M; Polašek, Ozren; Boban, Mladen; Nelson, Christopher P; Morrison, Alanna C; Pihur, Vasyl; Ganesh, Santhi K; Hofman, Albert; Kundu, Suman; Mattace-Raso, Francesco US; Rivadeneira, Fernando; Sijbrands, Eric JG; Uitterlinden, Andre G; Hwang, Shih-Jen; Vasan, Ramachandran S; Wang, Thomas J; Bergmann, Sven; Vollenweider, Peter; Waeber, Gérard; Laitinen, Jaana; Pouta, Anneli; Zitting, Paavo; McArdle, Wendy L; Kroemer, Heyo K; Völker, Uwe; Völzke, Henry; Glazer, Nicole L; Taylor, Kent D; Harris, Tamara B; Alavere, Helene; Haller, Toomas; Keis, Aime; Tammesoo, Mari-Liis; Aulchenko, Yurii; Barroso, Inês; Khaw, Kay-Tee; Galan, Pilar; Hercberg, Serge; Lathrop, Mark; Eyheramendy, Susana; Org, Elin; Sõber, Siim; Lu, Xiaowen; Nolte, Ilja M; Penninx, Brenda W; Corre, Tanguy; Masciullo, Corrado; Sala, Cinzia; Groop, Leif; Voight, Benjamin F; Melander, Olle; O’Donnell, Christopher J; Salomaa, Veikko; d’Adamo, Adamo Pio; Fabretto, Antonella; Faletra, Flavio; Ulivi, Sheila; Del Greco, M Fabiola; Facheris, Maurizio; Collins, Francis S; Bergman, Richard N; Beilby, John P; Hung, Joseph; Musk, A William; Mangino, Massimo; Shin, So-Youn; Soranzo, Nicole; Watkins, Hugh; Goel, Anuj; Hamsten, Anders; Gider, Pierre; Loitfelder, Marisa; Zeginigg, Marion; Hernandez, Dena; Najjar, Samer S; Navarro, Pau; Wild, Sarah H; Corsi, Anna Maria; Singleton, Andrew; de Geus, Eco JC; Willemsen, Gonneke; Parker, Alex N; Rose, Lynda M; Buckley, Brendan; Stott, David; Orru, Marco; Uda, Manuela; van der Klauw, Melanie M; Zhang, Weihua; Li, Xinzhong; Scott, James; Chen, Yii-Der Ida; Burke, Gregory L; Kähönen, Mika; Viikari, Jorma; Döring, Angela; Meitinger, Thomas; Davies, Gail; Starr, John M; Emilsson, Valur; Plump, Andrew; Lindeman, Jan H; ’t Hoen, Peter AC; König, Inke R; Felix, Janine F; Clarke, Robert; Hopewell, Jemma C; Ongen, Halit; Breteler, Monique; Debette, Stéphanie; DeStefano, Anita L; Fornage, Myriam; Mitchell, Gary F; Smith, Nicholas L; Holm, Hilma; Stefansson, Kari; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Samani, Nilesh J; Preuss, Michael; Rudan, Igor; Hayward, Caroline; Deary, Ian J; Wichmann, H-Erich; Raitakari, Olli T; Palmas, Walter; Kooner, Jaspal S; Stolk, Ronald P; Jukema, J Wouter; Wright, Alan F; Boomsma, Dorret I; Bandinelli, Stefania; Gyllensten, Ulf B; Wilson, James F; Ferrucci, Luigi; Schmidt, Reinhold; Farrall, Martin; Spector, Tim D; Palmer, Lyle J; Tuomilehto, Jaakko; Pfeufer, Arne; Gasparini, Paolo; Siscovick, David; Altshuler, David; Loos, Ruth JF; Toniolo, Daniela; Snieder, Harold; Gieger, Christian; Meneton, Pierre; Wareham, Nicholas J; Oostra, Ben A; Metspalu, Andres; Launer, Lenore; Rettig, Rainer; Strachan, David P; Beckmann, Jacques S; Witteman, Jacqueline CM; Erdmann, Jeanette; van Dijk, Ko Willems; Boerwinkle, Eric; Boehnke, Michael; Ridker, Paul M; Jarvelin, Marjo-Riitta; Chakravarti, Aravinda; Abecasis, Goncalo R; Gudnason, Vilmundur; Newton-Cheh, Christopher; Levy, Daniel; Munroe, Patricia B; Psaty, Bruce M; Caulfield, Mark J; Rao, Dabeeru C

2012-01-01

Numerous genetic loci influence systolic blood pressure (SBP) and diastolic blood pressure (DBP) in Europeans 1-3. We now report genome-wide association studies of pulse pressure (PP) and mean arterial pressure (MAP). In discovery (N=74,064) and follow-up studies (N=48,607), we identified at genome-wide significance (P= 2.7×10-8 to P=2.3×10-13) four novel PP loci (at 4q12 near CHIC2/PDGFRAI, 7q22.3 near PIK3CG, 8q24.12 in NOV, 11q24.3 near ADAMTS-8), two novel MAP loci (3p21.31 in MAP4, 10q25.3 near ADRB1) and one locus associated with both traits (2q24.3 near FIGN) which has recently been associated with SBP in east Asians. For three of the novel PP signals, the estimated effect for SBP was opposite to that for DBP, in contrast to the majority of common SBP- and DBP-associated variants which show concordant effects on both traits. These findings indicate novel genetic mechanisms underlying blood pressure variation, including pathways that may differentially influence SBP and DBP. PMID:21909110

Genome-wide expressions in autologous eutopic and ectopic endometrium of fertile women with endometriosis

Directory of Open Access Journals (Sweden)

Khan Meraj A

2012-09-01

Full Text Available Abstract Background In order to obtain a lead of the pathophysiology of endometriosis, genome-wide expressional analyses of eutopic and ectopic endometrium have earlier been reported, however, the effects of stages of severity and phases of menstrual cycle on expressional profiles have not been examined. The effect of genetic heterogeneity and fertility history on transcriptional activity was also not considered. In the present study, a genome-wide expression analysis of autologous, paired eutopic and ectopic endometrial samples obtained from fertile women (n = 18 suffering from moderate (stage 3; n = 8 or severe (stage 4; n = 10 ovarian endometriosis during proliferative (n = 13 and secretory (n = 5 phases of menstrual cycle was performed. Methods Individual pure RNA samples were subjected to Agilent’s Whole Human Genome 44K microarray experiments. Microarray data were validated (P  Results Higher clustering effect of pairing (cluster distance, cd = 0.1 in samples from same individuals on expressional arrays among eutopic and ectopic samples was observed as compared to that of clinical stages of severity (cd = 0.5 and phases of menstrual cycle (cd = 0.6. Post hoc analysis revealed anomaly in the expressional profiles of several genes associated with immunological, neuracrine and endocrine functions and gynecological cancers however with no overt oncogenic potential in endometriotic tissue. Dys-regulation of three (CLOCK, ESR1, and MYC major transcription factors appeared to be significant causative factors in the pathogenesis of ovarian endometriosis. A novel cohort of twenty-eight (28 genes representing potential marker for ovarian endometriosis in fertile women was discovered. Conclusions Dysfunctional expression of immuno-neuro-endocrine behaviour in endometrium appeared critical to endometriosis. Although no overt oncogenic potential was evident, several genes associated with gynecological cancers were

Genome-wide signatures of 'rearrangement hotspots' within segmental duplications in humans.

Directory of Open Access Journals (Sweden)

Mohammed Uddin

Full Text Available The primary objective of this study was to create a genome-wide high resolution map (i.e., >100 bp of 'rearrangement hotspots' which can facilitate the identification of regions capable of mediating de novo deletions or duplications in humans. A hierarchical method was employed to fragment segmental duplications (SDs into multiple smaller SD units. Combining an end space free pairwise alignment algorithm with a 'seed and extend' approach, we have exhaustively searched 409 million alignments to detect complex structural rearrangements within the reference-guided assembly of the NA18507 human genome (18× coverage, including the previously identified novel 4.8 Mb sequence from de novo assembly within this genome. We have identified 1,963 rearrangement hotspots within SDs which encompass 166 genes and display an enrichment of duplicated gene nucleotide variants (DNVs. These regions are correlated with increased non-allelic homologous recombination (NAHR event frequency which presumably represents the origin of copy number variations (CNVs and pathogenic duplications/deletions. Analysis revealed that 20% of the detected hotspots are clustered within the proximal and distal SD breakpoints flanked by the pathogenic deletions/duplications that have been mapped for 24 NAHR-mediated genomic disorders. FISH Validation of selected complex regions revealed 94% concordance with in silico localization of the highly homologous derivatives. Other results from this study indicate that intra-chromosomal recombination is enhanced in genic compared with agenic duplicated regions, and that gene desert regions comprising SDs may represent reservoirs for creation of novel genes. The generation of genome-wide signatures of 'rearrangement hotspots', which likely serve as templates for NAHR, may provide a powerful approach towards understanding the underlying mutational mechanism(s for development of constitutional and acquired diseases.

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

Genome-wide association analysis identifies three new breast cancer susceptibility loci

DEFF Research Database (Denmark)

Ghoussaini, Maya; Fletcher, Olivia; Michailidou, Kyriaki

2012-01-01

Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ∼8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies (GWAS...

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

NARCIS (Netherlands)

A. Okbay (Aysu); J.P. Beauchamp (Jonathan); Fontana, M.A. (Mark Alan); J.J. Lee (James J.); T.H. Pers (Tune); Rietveld, C.A. (Cornelius A.); P. Turley (Patrick); Chen, G.-B. (Guo-Bo); V. Emilsson (Valur); Meddens, S.F.W. (S. Fleur W.); Oskarsson, S. (Sven); Pickrell, J.K. (Joseph K.); Thom, K. (Kevin); Timshel, P. (Pascal); R. de Vlaming (Ronald); A. Abdellaoui (Abdel); T.S. Ahluwalia (Tarunveer Singh); J. Bacelis (Jonas); C. Baumbach (Clemens); Bjornsdottir, G. (Gyda); J.H. Brandsma (Johan); Pina Concas, M. (Maria); J. Derringer; Furlotte, N.A. (Nicholas A.); T.E. Galesloot (Tessel); S. Girotto; Gupta, R. (Richa); L.M. Hall (Leanne M.); S.E. Harris (Sarah); E. Hofer; Horikoshi, M. (Momoko); J.E. Huffman (Jennifer E.); Kaasik, K. (Kadri); I.-P. Kalafati (Ioanna-Panagiota); R. Karlsson (Robert); A. Kong (Augustine); J. Lahti (Jari); S.J. van der Lee (Sven); Deleeuw, C. (Christiaan); P.A. Lind (Penelope); Lindgren, K.-O. (Karl-Oskar); Liu, T. (Tian); M. Mangino (Massimo); J. Marten (Jonathan); E. Mihailov (Evelin); M. Miller (Mike); P.J. van der Most (Peter); C. Oldmeadow (Christopher); A. Payton (Antony); N. Pervjakova (Natalia); W.J. Peyrot (Wouter ); Qian, Y. (Yong); O. Raitakari (Olli); Rueedi, R. (Rico); Salvi, E. (Erika); Schmidt, B. (Börge); Schraut, K.E. (Katharina E.); Shi, J. (Jianxin); A.V. Smith (Albert Vernon); R.A. Poot (Raymond); B. St Pourcain (Beate); A. Teumer (Alexander); G. Thorleifsson (Gudmar); N. Verweij (Niek); D. Vuckovic (Dragana); Wellmann, J. (Juergen); H.J. Westra (Harm-Jan); Yang, J. (Jingyun); Zhao, W. (Wei); Zhu, Z. (Zhihong); B.Z. Alizadeh (Behrooz); N. Amin (Najaf); Bakshi, A. (Andrew); S.E. Baumeister (Sebastian); G. Biino (Ginevra); K. Bønnelykke (Klaus); P.A. Boyle (Patricia); H. Campbell (Harry); Cappuccio, F.P. (Francesco P.); G. Davies (Gail); J.E. de Neve (Jan-Emmanuel); P. Deloukas (Panagiotis); I. Demuth (Ilja); Ding, J. (Jun); Eibich, P. (Peter); Eisele, L. (Lewin); N. Eklund (Niina); D.M. Evans (David); J.D. Faul (Jessica D.); M.F. Feitosa (Mary Furlan); A.J. Forstner (Andreas); I. Gandin (Ilaria); Gunnarsson, B. (Bjarni); B.V. Halldorsson (Bjarni); T.B. Harris (Tamara); E.G. Holliday (Elizabeth); A.C. Heath (Andrew C.); L.J. Hocking; G. Homuth (Georg); M. Horan (Mike); J.J. Hottenga (Jouke Jan); P.L. de Jager (Philip); P.K. Joshi (Peter); A. Juqessur (Astanand); M. Kaakinen (Marika); M. Kähönen (Mika); S. Kanoni (Stavroula); Keltigangas-Järvinen, L. (Liisa); L.A.L.M. Kiemeney (Bart); I. Kolcic (Ivana); Koskinen, S. (Seppo); A. Kraja (Aldi); Kroh, M. (Martin); Z. Kutalik (Zoltán); A. Latvala (Antti); L.J. Launer (Lenore); Lebreton, M.P. (Maël P.); D.F. Levinson (Douglas F.); P. Lichtenstein (Paul); P. Lichtner (Peter); D.C. Liewald (David C.); A. Loukola (Anu); P.A. Madden (Pamela); R. Mägi (Reedik); Mäki-Opas, T. (Tomi); R.E. Marioni (Riccardo); P. Marques-Vidal; Meddens, G.A. (Gerardus A.); G. Mcmahon (George); C. Meisinger (Christa); T. Meitinger (Thomas); Milaneschi, Y. (Yusplitri); L. Milani (Lili); G.W. Montgomery (Grant); R. Myhre (Ronny); C.P. Nelson (Christopher P.); D.R. Nyholt (Dale); W.E.R. Ollier (William); A. Palotie (Aarno); L. Paternoster (Lavinia); N.L. Pedersen (Nancy); K. Petrovic (Katja); D.J. Porteous (David J.); K. Räikkönen (Katri); Ring, S.M. (Susan M.); A. Robino (Antonietta); O. Rostapshova (Olga); I. Rudan (Igor); A. Rustichini (Aldo); V. Salomaa (Veikko); Sanders, A.R. (Alan R.); A.-P. Sarin; R. Schmidt (Reinhold); R.J. Scott (Rodney); B.H. Smith (Blair); J.A. Smith (Jennifer A); J.A. Staessen (Jan); E. Steinhagen-Thiessen (Elisabeth); K. Strauch (Konstantin); A. Terracciano; M.D. Tobin (Martin); S. Ulivi (Shelia); S. Vaccargiu (Simona); L. Quaye (Lydia); F.J.A. van Rooij (Frank); C. Venturini (Cristina); A.A.E. Vinkhuyzen (Anna A.); U. Völker (Uwe); Völzke, H. (Henry); J.M. Vonk (Judith); D. Vozzi (Diego); J. Waage (Johannes); E.B. Ware (Erin B.); G.A.H.M. Willemsen (Gonneke); J. Attia (John); D.A. Bennett (David A.); Berger, K. (Klaus); L. Bertram (Lars); H. Bisgaard (Hans); D.I. Boomsma (Dorret); I.B. Borecki (Ingrid); U. Bültmann (Ute); C.F. Chabris (Christopher F.); F. Cucca (Francesco); D. Cusi (Daniele); I.J. Deary (Ian J.); G.V. Dedoussis (George); C.M. van Duijn (Cornelia); K. Hagen (Knut); B. Franke (Barbara); L. Franke (Lude); P. Gasparini (Paolo); P.V. Gejman (Pablo); C. Gieger (Christian); H.J. Grabe (Hans Jörgen); J. Gratten (Jacob); P.J.F. Groenen (Patrick); V. Gudnason (Vilmundur); P. van der Harst (Pim); C. Hayward (Caroline); D.A. Hinds (David A.); W. Hoffmann (Wolfgang); E. Hypponen (Elina); W.G. Iacono (William); B. Jacobsson (Bo); M.-R. Jarvelin (Marjo-Riitta); K.-H. JöCkel (Karl-Heinz); J. Kaprio (Jaakko); S.L.R. Kardia (Sharon); T. Lehtimäki (Terho); Lehrer, S.F. (Steven F.); P.K. Magnusson (Patrik); N.G. Martin (Nicholas); M. McGue (Matt); A. Metspalu (Andres); N. Pendleton (Neil); B.W.J.H. Penninx (Brenda); M. Perola (Markus); N. Pirastu (Nicola); M. Pirastu (Mario); O. Polasek (Ozren); D. Posthuma (Danielle); C. Power (Christopher); M.A. Province (Mike); N.J. Samani (Nilesh); Schlessinger, D. (David); R. Schmidt (Reinhold); T.I.A. Sørensen (Thorkild); T.D. Spector (Timothy); J-A. Zwart (John-Anker); U. Thorsteinsdottir (Unnur); A.R. Thurik (Roy); Timpson, N.J. (Nicholas J.); H.W. Tiemeier (Henning); J.Y. Tung (Joyce Y.); A.G. Uitterlinden (André); Vitart, V. (Veronique); P. Vollenweider (Peter); D.R. Weir (David); J.F. Wilson (James F.); A.F. Wright (Alan); Conley, D.C. (Dalton C.); R.F. Krueger; G.D. Smith; Hofman, A. (Albert); D. Laibson (David); S.E. Medland (Sarah Elizabeth); M.N. Meyer (Michelle N.); J. Yang (Joanna); M. Johannesson (Magnus); P.M. Visscher (Peter); T. Esko (Tõnu); Ph.D. Koellinger (Philipp); D. Cesarini (David); D.J. Benjamin (Daniel J.)

2016-01-01

textabstractEducational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that

Genome-wide identification of structural variants in genes encoding drug targets

DEFF Research Database (Denmark)

Rasmussen, Henrik Berg; Dahmcke, Christina Mackeprang

2012-01-01

The objective of the present study was to identify structural variants of drug target-encoding genes on a genome-wide scale. We also aimed at identifying drugs that are potentially amenable for individualization of treatments based on knowledge about structural variation in the genes encoding...

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

NARCIS (Netherlands)

Okbay, A.; Beauchamp, J.; Fontana, M.A.; Lee, J.J.; Pers, T.H.; Rietveld, C.A.; Turley, P.; Chen, G.B.; Emilsson, V.; Meddens, S.F.W.; de Vlaming, R.; Abdellaoui, A.; Peyrot, W.; Vinkhuyzen, A.A.E.; Hottenga, J.J.; Willemsen, G.; Boomsma, D.I.; Penninx, B.W.J.H.; Laibson, D.; Medland, S.E.; Meyer, M.N.; Yang, J.; Johannesson, M.; Visscher, P.M.; Esko, T.; Koellinger, P.D.; Cesarini, D.; Benjamin, D.J.

2016-01-01

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our

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

NARCIS (Netherlands)

Okbay, Aysu; Beauchamp, Jonathan P.; Fontana, Mark Alan; Lee, James J.; Pers, Tune H.; Rietveld, Cornelius A.; Turley, Patrick; Chen, Guo-Bo; Emilsson, Valur; Meddens, S. Fleur W.; Oskarsson, Sven; Pickrell, Joseph K.; Thom, Kevin; Timshel, Pascal; de Vlaming, Ronald; Abdellaoui, Abdel; Ahluwalia, Tarunveer S.; Bacelis, Jonas; Baumbach, Clemens; Bjornsdottir, Gyda; Brandsma, Johannes H.; Concas, Maria Pina; Derringer, Jaime; Furlotte, Nicholas A.; Galesloot, Tessel E.; Girotto, Giorgia; Gupta, Richa; Hall, Leanne M.; Harris, Sarah E.; Hofer, Edith; Horikoshi, Momoko; Huffman, Jennifer E.; Kaasik, Kadri; Kalafati, Ioanna P.; Karlsson, Robert; Kong, Augustine; Lahti, Jari; van der Lee, Sven J.; de Leeuw, Christiaan; Lind, Penelope A.; Lindgren, Karl-Oskar; Liu, Tian; van der Most, Peter J.; Verweij, Niek; Alizadeh, Behrooz Z.; Vonk, Judith M.; Bultmann, Ute; Franke, Lude; van der Harst, Pim; Penninx, Brenda W. J. H.

2016-01-01

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals(1). Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends

Genome-Wide Comparative Gene Family Classification

Science.gov (United States)

Frech, Christian; Chen, Nansheng

2010-01-01

Correct classification of genes into gene families is important for understanding gene function and evolution. Although gene families of many species have been resolved both computationally and experimentally with high accuracy, gene family classification in most newly sequenced genomes has not been done with the same high standard. This project has been designed to develop a strategy to effectively and accurately classify gene families across genomes. We first examine and compare the performance of computer programs developed for automated gene family classification. We demonstrate that some programs, including the hierarchical average-linkage clustering algorithm MC-UPGMA and the popular Markov clustering algorithm TRIBE-MCL, can reconstruct manual curation of gene families accurately. However, their performance is highly sensitive to parameter setting, i.e. different gene families require different program parameters for correct resolution. To circumvent the problem of parameterization, we have developed a comparative strategy for gene family classification. This strategy takes advantage of existing curated gene families of reference species to find suitable parameters for classifying genes in related genomes. To demonstrate the effectiveness of this novel strategy, we use TRIBE-MCL to classify chemosensory and ABC transporter gene families in C. elegans and its four sister species. We conclude that fully automated programs can establish biologically accurate gene families if parameterized accordingly. Comparative gene family classification finds optimal parameters automatically, thus allowing rapid insights into gene families of newly sequenced species. PMID:20976221

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

Directory of Open Access Journals (Sweden)

Shefali S Verma

2014-12-01

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

ChIP on SNP-chip for genome-wide analysis of human histone H4 hyperacetylation

Directory of Open Access Journals (Sweden)

Porter Christopher J

2007-09-01

Full Text Available Abstract Background SNP microarrays are designed to genotype Single Nucleotide Polymorphisms (SNPs. These microarrays report hybridization of DNA fragments and therefore can be used for the purpose of detecting genomic fragments. Results Here, we demonstrate that a SNP microarray can be effectively used in this way to perform chromatin immunoprecipitation (ChIP on chip as an alternative to tiling microarrays. We illustrate this novel application by mapping whole genome histone H4 hyperacetylation in human myoblasts and myotubes. We detect clusters of hyperacetylated histone H4, often spanning across up to 300 kilobases of genomic sequence. Using complementary genome-wide analyses of gene expression by DNA microarray we demonstrate that these clusters of hyperacetylated histone H4 tend to be associated with expressed genes. Conclusion The use of a SNP array for a ChIP-on-chip application (ChIP on SNP-chip will be of great value to laboratories whose interest is the determination of general rules regarding the relationship of specific chromatin modifications to transcriptional status throughout the genome and to examine the asymmetric modification of chromatin at heterozygous loci.

Comparative genomic characterization of three Streptococcus parauberis strains in fish pathogen, as assessed by wide-genome analyses.

Directory of Open Access Journals (Sweden)

Seong-Won Nho

Full Text Available Streptococcus parauberis, which is the main causative agent of streptococcosis among olive flounder (Paralichthys olivaceus in northeast Asia, can be distinctly divided into two groups (type I and type II by an agglutination test. Here, the whole genome sequences of two Japanese strains (KRS-02083 and KRS-02109 were determined and compared with the previously determined genome of a Korean strain (KCTC 11537. The genomes of S. parauberis are intermediate in size and have lower GC contents than those of other streptococci. We annotated 2,236 and 2,048 genes in KRS-02083 and KRS-02109, respectively. Our results revealed that the three S. parauberis strains contain different genomic insertions and deletions. In particular, the genomes of Korean and Japanese strains encode different factors for sugar utilization; the former encodes the phosphotransferase system (PTS for sorbose, whereas the latter encodes proteins for lactose hydrolysis, respectively. And the KRS-02109 strain, specifically, was the type II strain found to be able to resist phage infection through the clustered regularly interspaced short palindromic repeats (CRISPR/Cas system and which might contribute valuably to serologically distribution. Thus, our genome-wide association study shows that polymorphisms can affect pathogen responses, providing insight into biological/biochemical pathways and phylogenetic diversity.

An Open Access Database of Genome-wide Association Results

Directory of Open Access Journals (Sweden)

Johnson Andrew D

2009-01-01

Full Text Available Abstract Background The number of genome-wide association studies (GWAS is growing rapidly leading to the discovery and replication of many new disease loci. Combining results from multiple GWAS datasets may potentially strengthen previous conclusions and suggest new disease loci, pathways or pleiotropic genes. However, no database or centralized resource currently exists that contains anywhere near the full scope of GWAS results. Methods We collected available results from 118 GWAS articles into a database of 56,411 significant SNP-phenotype associations and accompanying information, making this database freely available here. In doing so, we met and describe here a number of challenges to creating an open access database of GWAS results. Through preliminary analyses and characterization of available GWAS, we demonstrate the potential to gain new insights by querying a database across GWAS. Results Using a genomic bin-based density analysis to search for highly associated regions of the genome, positive control loci (e.g., MHC loci were detected with high sensitivity. Likewise, an analysis of highly repeated SNPs across GWAS identified replicated loci (e.g., APOE, LPL. At the same time we identified novel, highly suggestive loci for a variety of traits that did not meet genome-wide significant thresholds in prior analyses, in some cases with strong support from the primary medical genetics literature (SLC16A7, CSMD1, OAS1, suggesting these genes merit further study. Additional adjustment for linkage disequilibrium within most regions with a high density of GWAS associations did not materially alter our findings. Having a centralized database with standardized gene annotation also allowed us to examine the representation of functional gene categories (gene ontologies containing one or more associations among top GWAS results. Genes relating to cell adhesion functions were highly over-represented among significant associations (p -14, a finding

Genome-wide maps of alkylation damage, repair, and mutagenesis in yeast reveal mechanisms of mutational heterogeneity.

Science.gov (United States)

Mao, Peng; Brown, Alexander J; Malc, Ewa P; Mieczkowski, Piotr A; Smerdon, Michael J; Roberts, Steven A; Wyrick, John J

2017-10-01

DNA base damage is an important contributor to genome instability, but how the formation and repair of these lesions is affected by the genomic landscape and contributes to mutagenesis is unknown. Here, we describe genome-wide maps of DNA base damage, repair, and mutagenesis at single nucleotide resolution in yeast treated with the alkylating agent methyl methanesulfonate (MMS). Analysis of these maps revealed that base excision repair (BER) of alkylation damage is significantly modulated by chromatin, with faster repair in nucleosome-depleted regions, and slower repair and higher mutation density within strongly positioned nucleosomes. Both the translational and rotational settings of lesions within nucleosomes significantly influence BER efficiency; moreover, this effect is asymmetric relative to the nucleosome dyad axis and is regulated by histone modifications. Our data also indicate that MMS-induced mutations at adenine nucleotides are significantly enriched on the nontranscribed strand (NTS) of yeast genes, particularly in BER-deficient strains, due to higher damage formation on the NTS and transcription-coupled repair of the transcribed strand (TS). These findings reveal the influence of chromatin on repair and mutagenesis of base lesions on a genome-wide scale and suggest a novel mechanism for transcription-associated mutation asymmetry, which is frequently observed in human cancers. © 2017 Mao et al.; Published by Cold Spring Harbor Laboratory Press.

Research Guidelines in the Era of Large-scale Collaborations: An Analysis of Genome-wide Association Study Consortia

Science.gov (United States)

Austin, Melissa A.; Hair, Marilyn S.; Fullerton, Stephanie M.

2012-01-01

Scientific research has shifted from studies conducted by single investigators to the creation of large consortia. Genetic epidemiologists, for example, now collaborate extensively for genome-wide association studies (GWAS). The effect has been a stream of confirmed disease-gene associations. However, effects on human subjects oversight, data-sharing, publication and authorship practices, research organization and productivity, and intellectual property remain to be examined. The aim of this analysis was to identify all research consortia that had published the results of a GWAS analysis since 2005, characterize them, determine which have publicly accessible guidelines for research practices, and summarize the policies in these guidelines. A review of the National Human Genome Research Institute’s Catalog of Published Genome-Wide Association Studies identified 55 GWAS consortia as of April 1, 2011. These consortia were comprised of individual investigators, research centers, studies, or other consortia and studied 48 different diseases or traits. Only 14 (25%) were found to have publicly accessible research guidelines on consortia websites. The available guidelines provide information on organization, governance, and research protocols; half address institutional review board approval. Details of publication, authorship, data-sharing, and intellectual property vary considerably. Wider access to consortia guidelines is needed to establish appropriate research standards with broad applicability to emerging forms of large-scale collaboration. PMID:22491085

Assumption-free estimation of heritability from genome-wide identity-by-descent sharing between full siblings.

Directory of Open Access Journals (Sweden)

2006-03-01

Full Text Available The study of continuously varying, quantitative traits is important in evolutionary biology, agriculture, and medicine. Variation in such traits is attributable to many, possibly interacting, genes whose expression may be sensitive to the environment, which makes their dissection into underlying causative factors difficult. An important population parameter for quantitative traits is heritability, the proportion of total variance that is due to genetic factors. Response to artificial and natural selection and the degree of resemblance between relatives are all a function of this parameter. Following the classic paper by R. A. Fisher in 1918, the estimation of additive and dominance genetic variance and heritability in populations is based upon the expected proportion of genes shared between different types of relatives, and explicit, often controversial and untestable models of genetic and non-genetic causes of family resemblance. With genome-wide coverage of genetic markers it is now possible to estimate such parameters solely within families using the actual degree of identity-by-descent sharing between relatives. Using genome scans on 4,401 quasi-independent sib pairs of which 3,375 pairs had phenotypes, we estimated the heritability of height from empirical genome-wide identity-by-descent sharing, which varied from 0.374 to 0.617 (mean 0.498, standard deviation 0.036. The variance in identity-by-descent sharing per chromosome and per genome was consistent with theory. The maximum likelihood estimate of the heritability for height was 0.80 with no evidence for non-genetic causes of sib resemblance, consistent with results from independent twin and family studies but using an entirely separate source of information. Our application shows that it is feasible to estimate genetic variance solely from within-family segregation and provides an independent validation of previously untestable assumptions. Given sufficient data, our new paradigm will

Genome-wide DNA Methylation Profiling of Cell-Free Serum DNA in Esophageal Adenocarcinoma and Barrett Esophagus

Directory of Open Access Journals (Sweden)

Rihong Zhai

2012-01-01

Full Text Available Aberrant DNA methylation (DNAm is a feature of most types of cancers. Genome-wide DNAm profiling has been performed successfully on tumor tissue DNA samples. However, the invasive procedure limits the utility of tumor tissue for epidemiological studies. While recent data indicate that cell-free circulating DNAm (cfDNAm profiles reflect DNAm status in corresponding tumor tissues, no studies have examined the association of cfDNAm with cancer or precursors on a genome-wide scale. The objective of this pilot study was to evaluate the putative significance of genome-wide cfDNAm profiles in esophageal adenocarcinoma (EA and Barrett esophagus (BE, EA precursor. We performed genome-wide DNAm profiling in EA tissue DNA (n = 8 and matched serum DNA (n = 8, in serum DNA of BE (n = 10, and in healthy controls (n = 10 using the Infinium HumanMethylation27 BeadChip that covers 27,578 CpG loci in 14,495 genes. We found that cfDNAm profiles were highly correlated to DNAm profiles in matched tumor tissue DNA (r = 0.92 in patients with EA. We selected the most differentially methylated loci to perform hierarchical clustering analysis. We found that 911 loci can discriminate perfectly between EA and control samples, 554 loci can separate EA from BE samples, and 46 loci can distinguish BE from control samples. These results suggest that genome-wide cfDNAm profiles are highly consistent with DNAm profiles detected in corresponding tumor tissues. Differential cfDNAm profiling may be a useful approach for the noninvasive screening of EA and EA premalignant lesions.

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)

D-GENIES: dot plot large genomes in an interactive, efficient and simple way.

Science.gov (United States)

Cabanettes, Floréal; Klopp, Christophe

2018-01-01

Dot plots are widely used to quickly compare sequence sets. They provide a synthetic similarity overview, highlighting repetitions, breaks and inversions. Different tools have been developed to easily generated genomic alignment dot plots, but they are often limited in the input sequence size. D-GENIES is a standalone and web application performing large genome alignments using minimap2 software package and generating interactive dot plots. It enables users to sort query sequences along the reference, zoom in the plot and download several image, alignment or sequence files. D-GENIES is an easy-to-install, open-source software package (GPL) developed in Python and JavaScript. The source code is available at https://github.com/genotoul-bioinfo/dgenies and it can be tested at http://dgenies.toulouse.inra.fr/.

Genome-wide meta-analysis of myopia and hyperopia provides evidence for replication of 11 loci.

Directory of Open Access Journals (Sweden)

Claire L Simpson

Full Text Available Refractive error (RE is a complex, multifactorial disorder characterized by a mismatch between the optical power of the eye and its axial length that causes object images to be focused off the retina. The two major subtypes of RE are myopia (nearsightedness and hyperopia (farsightedness, which represent opposite ends of the distribution of the quantitative measure of spherical refraction. We performed a fixed effects meta-analysis of genome-wide association results of myopia and hyperopia from 9 studies of European-derived populations: AREDS, KORA, FES, OGP-Talana, MESA, RSI, RSII, RSIII and ERF. One genome-wide significant region was observed for myopia, corresponding to a previously identified myopia locus on 8q12 (p = 1.25×10(-8, which has been reported by Kiefer et al. as significantly associated with myopia age at onset and Verhoeven et al. as significantly associated to mean spherical-equivalent (MSE refractive error. We observed two genome-wide significant associations with hyperopia. These regions overlapped with loci on 15q14 (minimum p value = 9.11×10(-11 and 8q12 (minimum p value 1.82×10(-11 previously reported for MSE and myopia age at onset. We also used an intermarker linkage- disequilibrium-based method for calculating the effective number of tests in targeted regional replication analyses. We analyzed myopia (which represents the closest phenotype in our data to the one used by Kiefer et al. and showed replication of 10 additional loci associated with myopia previously reported by Kiefer et al. This is the first replication of these loci using myopia as the trait under analysis. "Replication-level" association was also seen between hyperopia and 12 of Kiefer et al.'s published loci. For the loci that show evidence of association to both myopia and hyperopia, the estimated effect of the risk alleles were in opposite directions for the two traits. This suggests that these loci are important contributors to variation of

Genome-wide Analysis of Gene Regulation

DEFF Research Database (Denmark)

Chen, Yun

to protein: through epigenetic modifications, transcription regulators or post-transcriptional controls. The following papers concern several layers of gene regulation with questions answered by different HTS approaches. Genome-wide screening of epigenetic changes by ChIP-seq allowed us to study both spatial...... and temporal alterations of histone modifications (Papers I and II). Coupling the data with machine learning approaches, we established a prediction framework to assess the most informative histone marks as well as their most influential nucleosome positions in predicting the promoter usages. (Papers I...... they regulated or if the sites had global elevated usage rates by multiple TFs. Using RNA-seq, 5’end-seq in combination with depletion of 5’exonuclease as well as nonsensemediated decay (NMD) factors, we systematically analyzed NMD substrates as well as their degradation intermediates in human cells (Paper V...

Genome-Wide DNA Methylation Profiles of Phlegm-Dampness Constitution

Directory of Open Access Journals (Sweden)

Haiqiang Yao

2018-03-01

Full Text Available Background/Aims: Metabolic diseases are leading health concerns in today’s global society. In traditional Chinese medicine (TCM, one body type studied is the phlegm-dampness constitution (PC, which predisposes individuals to complex metabolic disorders. Genomic studies have revealed the potential metabolic disorders and the molecular features of PC. The role of epigenetics in the regulation of PC, however, is unknown. Methods: We analyzed a genome-wide DNA methylation in 12 volunteers using Illumina Infinium Human Methylation450 BeadChip on peripheral blood mononuclear cells (PBMCs. Eight volunteers had PC and 4 had balanced constitutions. Results: Methylation data indicated a genome-scale hyper-methylation pattern in PC. We located 288 differentially methylated probes (DMPs. A total of 256 genes were mapped, and some of these were metabolic-related. SQSTM1, DLGAP2 and DAB1 indicated diabetes mellitus; HOXC4 and SMPD3, obesity; and GRWD1 and ATP10A, insulin resistance. According to Ingenuity Pathway Analysis (IPA, differentially methylated genes were abundant in multiple metabolic pathways. Conclusion: Our results suggest the potential risk for metabolic disorders in individuals with PC. We also explain the clinical characteristics of PC with DNA methylation features.

Genome-wide association analysis identifies 13 new risk loci for schizophrenia

NARCIS (Netherlands)

Ripke, S.; O'Dushlaine, C.; Chambert, K.; Moran, J.L.; Kähler, A.K.; Akterin, S.; Bergen, S.E.; Collins, A.L.; Crowley, J.J.; Fromer, M.; Kim, Y.; Lee, S.H.; Magnusson, P.K.; Sanchez, N.; Stahl, E.A.; Williams, S.; Wray, N.R.; Xia, K.; Bettella, F.; Borglum, A. D.; Bulik-Sullivan, B.K.; Cormican, P.; Craddock, N.; de Leeuw, C.A.; Durmishi, N.; Gill, M.; Golimbet, V.; Hamshere, M.L.; Holmans, P.; Hougaard, D. M.; Kendler, K.S.; Lin, K.; Morris, D. W.; Mors, O.; Mortensen, P.B.; Neale, B. M.; O'Neill, F. A.; Owen, M.J.; Milovancevic, M.P.; Posthuma, D.; Powell, J.; Richards, A.L.; Riley, B.P.; Ruderfer, D.; Rujescu, D.; Sigurdsson, E.; Silagadze, T.; Smit, A.B.; Stefansson, H.; Steinberg, S.; Suvisaari, J.; Tosato, S.; Verhage, M.; Walters, T.J.; Levinson, D.F.; Gejman, P.V.; Laurent, C.; Mowry, B. J.; O'Donovan, M.C.; Pulver, A. E.; Schwab, S.G.; Wildenauer, D. B.; Dudbridge, F.; Shi, J.; Albus, M.; Alexander, M.; Campion, D.; Cohen, D.; Dikeos, D.; Duan, J.; Eichhammer, P.; Godard, S.; Hansen, M.; Lerer, F.B.; Liang, K.Y.; Maier, W.; Mallet, J.; Nertney, D. A.; Nestadt, G.; Norton, N.; O'Neill, F.A.; Papadimitriou, G.N.; Ribble, R.; Sanders, A.R.; Silverman, J.M.; Wormley, B.; Arranz, M.J.; Bakker, S.; Bender, S.; Bramon, E.; Collier, D.; Crespo-Facorro, B.; Hall, J.; Iyegbe, C.; Jablensky, A.; Kahn, R.S.; Kalaydjieva, L.; Lawrie, S.M.; Lewis, C.M.; Linszen, D.H.; Mata, I.; McIntosh, A.; Murray, R.M.; Ophoff, R.A.; van Os, J.; Walshe, M.; Weisbrod, M.; Wiersma, D.; Donnely, P.; Barasso, I.; Blackwell, J.M.; Brown, M.A.; Casas, J.P.; Corvin, A.P.; Deloukas, P.; Duncanson, A.; Jankowski, J.; Markus, H.S.; Mathew, C.G.; Palmer, C.N.; Plomin, R.; Rautanen, A.; Sawcer, S.J.; Trembath, R.C.; Viswanathan, A.C.; Wood, N.W.; Spencer, C. C.; Band, G.; Bellenguez, C.; Freeman, C.; Hellenthal, G.; Giannoulatou, E.; Pirinen, M.; Pearson, R.D.; Strange, A.; Su, Z.; Vukcevic, D.; Langford, C.; Hunt, S.E.; Edkins, S.; Gwilliam, R.; Blackburn, H.; Bumpstead, S.; Dronov, S.; Gillman, M.; Gray, E.; Hammond, N.; Jayakumar, A.; McCann, O.T.; Liddle, J.; Potter, S.C.; Ravindrarajah, R.; Ricketts, M.; Tashakkori-Ghanbaria, A.; Waller, M.J.; Weston, P.; Widaa, S.; Whittaker, P.; Barrroso, I.; McCarthy, M.I.; Spencer, C.C.; Stefansson, K.; Scolnick, E.; Purcell, S.; McCarroll, S.A.; Sklar, P.; Hultman, C. M.; Sullivan, P.F.

2013-01-01

Schizophrenia is an idiopathic mental disorder with a heritable component and a substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases and 6,243 controls) followed by meta-Analysis with

Genome-wide association study identifies multiple susceptibility loci for multiple myeloma

DEFF Research Database (Denmark)

Mitchell, Jonathan S; Li, Ni; Weinhold, Niels

2016-01-01

Multiple myeloma (MM) is a plasma cell malignancy with a significant heritable basis. Genome-wide association studies have transformed our understanding of MM predisposition, but individual studies have had limited power to discover risk loci. Here we perform a meta-analysis of these GWAS, add a ...

Genome-wide association analysis identifies 13 new risk loci for schizophrenia

NARCIS (Netherlands)

Ripke, Stephan; O'Dushlaine, Colm; Chambert, Kimberly; Moran, Jennifer L.; Kähler, Anna K.; Akterin, Susanne; Bergen, Sarah E.; Collins, Ann L.; Crowley, James J.; Fromer, Menachem; Kim, Yunjung; Lee, Sang Hong; Magnusson, Patrik K. E.; Sanchez, Nick; Stahl, Eli A.; Williams, Stephanie; Wray, Naomi R.; Xia, Kai; Bettella, Francesco; Borglum, Anders D.; Bulik-Sullivan, Brendan K.; Cormican, Paul; Craddock, Nick; de Leeuw, Christiaan; Durmishi, Naser; Gill, Michael; Golimbet, Vera; Hamshere, Marian L.; Holmans, Peter; Hougaard, David M.; Kendler, Kenneth S.; Lin, Kuang; Morris, Derek W.; Mors, Ole; Mortensen, Preben B.; Neale, Benjamin M.; O'Neill, Francis A.; Owen, Michael J.; Milovancevic, Milica Pejovic; Posthuma, Danielle; Powell, John; Richards, Alexander L.; Riley, Brien P.; Ruderfer, Douglas; Rujescu, Dan; Sigurdsson, Engilbert; Silagadze, Teimuraz; Smit, August B.; Stefansson, Hreinn; Steinberg, Stacy; Suvisaari, Jaana; Tosato, Sarah; Verhage, Matthijs; Walters, James T.; Levinson, Douglas F.; Gejman, Pablo V.; Laurent, Claudine; Mowry, Bryan J.; O'Donovan, Michael C.; Pulver, Ann E.; Schwab, Sibylle G.; Wildenauer, Dieter B.; Dudbridge, Frank; Shi, Jianxin; Albus, Margot; Alexander, Madeline; Campion, Dominique; Cohen, David; Dikeos, Dimitris; Duan, Jubao; Eichhammer, Peter; Godard, Stephanie; Hansen, Mark; Lerer, F. Bernard; Liang, Kung-Yee; Maier, Wolfgang; Mallet, Jacques; Nertney, Deborah A.; Nestadt, Gerald; Norton, Nadine; Papadimitriou, George N.; Ribble, Robert; Sanders, Alan R.; Silverman, Jeremy M.; Walsh, Dermot; Williams, Nigel M.; Wormley, Brandon; Arranz, Maria J.; Bakker, Steven; Bender, Stephan; Bramon, Elvira; Collier, David; Crespo-Facorro, Benedicto; Hall, Jeremy; Iyegbe, Conrad; Jablensky, Assen; Kahn, Rene S.; Kalaydjieva, Luba; Lawrie, Stephen; Lewis, Cathryn M.; Linszen, Don H.; Mata, Ignacio; McIntosh, Andrew; Murray, Robin M.; Ophoff, Roel A.; van Os, Jim; Walshe, Muriel; Weisbrod, Matthias; Wiersma, Durk; Donnelly, Peter; Barroso, Ines; Blackwell, Jenefer M.; Brown, Matthew A.; Casas, Juan P.; Corvin, Aiden P.; Deloukas, Panos; Duncanson, Audrey; Jankowski, Janusz; Markus, Hugh S.; Mathew, Christopher G.; Palmer, Colin N. A.; Plomin, Robert; Rautanen, Anna; Sawcer, Stephen J.; Trembath, Richard C.; Viswanathan, Ananth C.; Wood, Nicholas W.; Spencer, Chris C. A.; Band, Gavin; Bellenguez, Céline; Freeman, Colin; Hellenthal, Garrett; Giannoulatou, Eleni; Pirinen, Matti; Pearson, Richard D.; Strange, Amy; Su, Zhan; Vukcevic, Damjan; Langford, Cordelia; Hunt, Sarah E.; Edkins, Sarah; Gwilliam, Rhian; Blackburn, Hannah; Bumpstead, Suzannah J.; Dronov, Serge; Gillman, Matthew; Gray, Emma; Hammond, Naomi; Jayakumar, Alagurevathi; McCann, Owen T.; Liddle, Jennifer; Potter, Simon C.; Ravindrarajah, Radhi; Ricketts, Michelle; Tashakkori-Ghanbaria, Avazeh; Waller, Matthew J.; Weston, Paul; Widaa, Sara; Whittaker, Pamela; McCarthy, Mark I.; Stefansson, Kari; Scolnick, Edward; Purcell, Shaun; McCarroll, Steven A.; Sklar, Pamela; Hultman, Christina M.; Sullivan, Patrick F.

2013-01-01

Schizophrenia is an idiopathic mental disorder with a heritable component and a substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases and 6,243 controls) followed by meta-analysis with

Genome-wide association analysis of symbiotic nitrogen fixation in common bean

Science.gov (United States)

A genome-wide association study (GWAS) was conducted to explore the genetic basis of variation for symbiotic nitrogen fixation (SNF) and related traits in the Andean diversity panel (ADP) comprised of 259 common bean (Phaseolus vulgaris) genotypes. The ADP was evaluated for SNF and related traits in...

In vivo genome-wide profiling of RNA secondary structure reveals novel regulatory features.

Science.gov (United States)

Ding, Yiliang; Tang, Yin; Kwok, Chun Kit; Zhang, Yu; Bevilacqua, Philip C; Assmann, Sarah M

2014-01-30

RNA structure has critical roles in processes ranging from ligand sensing to the regulation of translation, polyadenylation and splicing. However, a lack of genome-wide in vivo RNA structural data has limited our understanding of how RNA structure regulates gene expression in living cells. Here we present a high-throughput, genome-wide in vivo RNA structure probing method, structure-seq, in which dimethyl sulphate methylation of unprotected adenines and cytosines is identified by next-generation sequencing. Application of this method to Arabidopsis thaliana seedlings yielded the first in vivo genome-wide RNA structure map at nucleotide resolution for any organism, with quantitative structural information across more than 10,000 transcripts. Our analysis reveals a three-nucleotide periodic repeat pattern in the structure of coding regions, as well as a less-structured region immediately upstream of the start codon, and shows that these features are strongly correlated with translation efficiency. We also find patterns of strong and weak secondary structure at sites of alternative polyadenylation, as well as strong secondary structure at 5' splice sites that correlates with unspliced events. Notably, in vivo structures of messenger RNAs annotated for stress responses are poorly predicted in silico, whereas mRNA structures of genes related to cell function maintenance are well predicted. Global comparison of several structural features between these two categories shows that the mRNAs associated with stress responses tend to have more single-strandedness, longer maximal loop length and higher free energy per nucleotide, features that may allow these RNAs to undergo conformational changes in response to environmental conditions. Structure-seq allows the RNA structurome and its biological roles to be interrogated on a genome-wide scale and should be applicable to any organism.

Genome-wide association identifies OBFC1 as a locus involved in human leukocyte telomere biology.

Science.gov (United States)

Levy, Daniel; Neuhausen, Susan L; Hunt, Steven C; Kimura, Masayuki; Hwang, Shih-Jen; Chen, Wei; Bis, Joshua C; Fitzpatrick, Annette L; Smith, Erin; Johnson, Andrew D; Gardner, Jeffrey P; Srinivasan, Sathanur R; Schork, Nicholas; Rotter, Jerome I; Herbig, Utz; Psaty, Bruce M; Sastrasinh, Malinee; Murray, Sarah S; Vasan, Ramachandran S; Province, Michael A; Glazer, Nicole L; Lu, Xiaobin; Cao, Xiaojian; Kronmal, Richard; Mangino, Massimo; Soranzo, Nicole; Spector, Tim D; Berenson, Gerald S; Aviv, Abraham

2010-05-18

Telomeres are engaged in a host of cellular functions, and their length is regulated by multiple genes. Telomere shortening, in the course of somatic cell replication, ultimately leads to replicative senescence. In humans, rare mutations in genes that regulate telomere length have been identified in monogenic diseases such as dyskeratosis congenita and idiopathic pulmonary fibrosis, which are associated with shortened leukocyte telomere length (LTL) and increased risk for aplastic anemia. Shortened LTL is observed in a host of aging-related complex genetic diseases and is associated with diminished survival in the elderly. We report results of a genome-wide association study of LTL in a consortium of four observational studies (n = 3,417 participants with LTL and genome-wide genotyping). SNPs in the regions of the oligonucleotide/oligosaccharide-binding folds containing one gene (OBFC1; rs4387287; P = 3.9 x 10(-9)) and chemokine (C-X-C motif) receptor 4 gene (CXCR4; rs4452212; P = 2.9 x 10(-8)) were associated with LTL at a genome-wide significance level (P a gene associated with LTL (P = 1.1 x 10(-5)). The identification of OBFC1 through genome-wide association as a locus for interindividual variation in LTL in the general population advances the understanding of telomere biology in humans and may provide insights into aging-related disorders linked to altered LTL dynamics.

Genome-wide transcriptional reprogramming under drought stress

KAUST Repository

Chen, Hao

2012-01-01

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

Genetic Variance Partitioning and Genome-Wide Prediction with Allele Dosage Information in Autotetraploid Potato.

Science.gov (United States)

Endelman, Jeffrey B; Carley, Cari A Schmitz; Bethke, Paul C; Coombs, Joseph J; Clough, Mark E; da Silva, Washington L; De Jong, Walter S; Douches, David S; Frederick, Curtis M; Haynes, Kathleen G; Holm, David G; Miller, J Creighton; Muñoz, Patricio R; Navarro, Felix M; Novy, Richard G; Palta, Jiwan P; Porter, Gregory A; Rak, Kyle T; Sathuvalli, Vidyasagar R; Thompson, Asunta L; Yencho, G Craig

2018-05-01

As one of the world's most important food crops, the potato ( Solanum tuberosum L.) has spurred innovation in autotetraploid genetics, including in the use of SNP arrays to determine allele dosage at thousands of markers. By combining genotype and pedigree information with phenotype data for economically important traits, the objectives of this study were to (1) partition the genetic variance into additive vs. nonadditive components, and (2) determine the accuracy of genome-wide prediction. Between 2012 and 2017, a training population of 571 clones was evaluated for total yield, specific gravity, and chip fry color. Genomic covariance matrices for additive ( G ), digenic dominant ( D ), and additive × additive epistatic ( G # G ) effects were calculated using 3895 markers, and the numerator relationship matrix ( A ) was calculated from a 13-generation pedigree. Based on model fit and prediction accuracy, mixed model analysis with G was superior to A for yield and fry color but not specific gravity. The amount of additive genetic variance captured by markers was 20% of the total genetic variance for specific gravity, compared to 45% for yield and fry color. Within the training population, including nonadditive effects improved accuracy and/or bias for all three traits when predicting total genotypic value. When six F 1 populations were used for validation, prediction accuracy ranged from 0.06 to 0.63 and was consistently lower (0.13 on average) without allele dosage information. We conclude that genome-wide prediction is feasible in potato and that it will improve selection for breeding value given the substantial amount of nonadditive genetic variance in elite germplasm. Copyright © 2018 by the Genetics Society of America.

Genome-wide association study of susceptibility loci for breast cancer in Sardinian population.

Science.gov (United States)

Palomba, Grazia; Loi, Angela; Porcu, Eleonora; Cossu, Antonio; Zara, Ilenia; Budroni, Mario; Dei, Mariano; Lai, Sandra; Mulas, Antonella; Olmeo, Nina; Ionta, Maria Teresa; Atzori, Francesco; Cuccuru, Gianmauro; Pitzalis, Maristella; Zoledziewska, Magdalena; Olla, Nazario; Lovicu, Mario; Pisano, Marina; Abecasis, Gonçalo R; Uda, Manuela; Tanda, Francesco; Michailidou, Kyriaki; Easton, Douglas F; Chanock, Stephen J; Hoover, Robert N; Hunter, David J; Schlessinger, David; Sanna, Serena; Crisponi, Laura; Palmieri, Giuseppe

2015-05-10

Despite progress in identifying genes associated with breast cancer, many more risk loci exist. Genome-wide association analyses in genetically-homogeneous populations, such as that of Sardinia (Italy), could represent an additional approach to detect low penetrance alleles. We performed a genome-wide association study comparing 1431 Sardinian patients with non-familial, BRCA1/2-mutation-negative breast cancer to 2171 healthy Sardinian blood donors. DNA was genotyped using GeneChip Human Mapping 500 K Arrays or Genome-Wide Human SNP Arrays 6.0. To increase genomic coverage, genotypes of additional SNPs were imputed using data from HapMap Phase II. After quality control filtering of genotype data, 1367 cases (9 men) and 1658 controls (1156 men) were analyzed on a total of 2,067,645 SNPs. Overall, 33 genomic regions (67 candidate SNPs) were associated with breast cancer risk at the p <  0(-6) level. Twenty of these regions contained defined genes, including one already associated with breast cancer risk: TOX3. With a lower threshold for preliminary significance to p < 10(-5), we identified 11 additional SNPs in FGFR2, a well-established breast cancer-associated gene. Ten candidate SNPs were selected, excluding those already associated with breast cancer, for technical validation as well as replication in 1668 samples from the same population. Only SNP rs345299, located in intron 1 of VAV3, remained suggestively associated (p-value, 1.16 x 10(-5)), but it did not associate with breast cancer risk in pooled data from two large, mixed-population cohorts. This study indicated the role of TOX3 and FGFR2 as breast cancer susceptibility genes in BRCA1/2-wild-type breast cancer patients from Sardinian population.

Genome-wide association study of susceptibility loci for breast cancer in Sardinian population

International Nuclear Information System (INIS)

Palomba, Grazia; Loi, Angela; Porcu, Eleonora; Cossu, Antonio; Zara, Ilenia

2015-01-01

Despite progress in identifying genes associated with breast cancer, many more risk loci exist. Genome-wide association analyses in genetically-homogeneous populations, such as that of Sardinia (Italy), could represent an additional approach to detect low penetrance alleles. We performed a genome-wide association study comparing 1431 Sardinian patients with non-familial, BRCA1/2-mutation-negative breast cancer to 2171 healthy Sardinian blood donors. DNA was genotyped using GeneChip Human Mapping 500 K Arrays or Genome-Wide Human SNP Arrays 6.0. To increase genomic coverage, genotypes of additional SNPs were imputed using data from HapMap Phase II. After quality control filtering of genotype data, 1367 cases (9 men) and 1658 controls (1156 men) were analyzed on a total of 2,067,645 SNPs. Overall, 33 genomic regions (67 candidate SNPs) were associated with breast cancer risk at the p < 10 −6 level. Twenty of these regions contained defined genes, including one already associated with breast cancer risk: TOX3. With a lower threshold for preliminary significance to p < 10 −5 , we identified 11 additional SNPs in FGFR2, a well-established breast cancer-associated gene. Ten candidate SNPs were selected, excluding those already associated with breast cancer, for technical validation as well as replication in 1668 samples from the same population. Only SNP rs345299, located in intron 1 of VAV3, remained suggestively associated (p-value, 1.16x10 −5 ), but it did not associate with breast cancer risk in pooled data from two large, mixed-population cohorts. This study indicated the role of TOX3 and FGFR2 as breast cancer susceptibility genes in BRCA1/2-wild-type breast cancer patients from Sardinian population. The online version of this article (doi:10.1186/s12885-015-1392-9) contains supplementary material, which is available to authorized users

Genomic Analysis of Genotype-by-Social Environment Interaction for Drosophila melanogaster Aggressive Behavior.

Science.gov (United States)

Rohde, Palle Duun; Gaertner, Bryn; Ward, Kirsty; Sørensen, Peter; Mackay, Trudy F C

2017-08-01

Human psychiatric disorders such as schizophrenia, bipolar disorder, and attention-deficit/hyperactivity disorder often include adverse behaviors including increased aggressiveness. Individuals with psychiatric disorders often exhibit social withdrawal, which can further increase the probability of conducting a violent act. Here, we used the inbred, sequenced lines of the Drosophila Genetic Reference Panel (DGRP) to investigate the genetic basis of variation in male aggressive behavior for flies reared in a socialized and socially isolated environment. We identified genetic variation for aggressive behavior, as well as significant genotype-by-social environmental interaction (GSEI); i.e. , variation among DGRP genotypes in the degree to which social isolation affected aggression. We performed genome-wide association (GWA) analyses to identify genetic variants associated with aggression within each environment. We used genomic prediction to partition genetic variants into gene ontology (GO) terms and constituent genes, and identified GO terms and genes with high prediction accuracies in both social environments and for GSEI. The top predictive GO terms significantly increased the proportion of variance explained, compared to prediction models based on all segregating variants. We performed genomic prediction across environments, and identified genes in common between the social environments that turned out to be enriched for genome-wide associated variants. A large proportion of the associated genes have previously been associated with aggressive behavior in Drosophila and mice. Further, many of these genes have human orthologs that have been associated with neurological disorders, indicating partially shared genetic mechanisms underlying aggression in animal models and human psychiatric disorders. Copyright © 2017 by the Genetics Society of America.

Genome-wide engineering of an infectious clone of herpes simplex virus type 1 using synthetic genomics assembly methods.

Science.gov (United States)

Oldfield, Lauren M; Grzesik, Peter; Voorhies, Alexander A; Alperovich, Nina; MacMath, Derek; Najera, Claudia D; Chandra, Diya Sabrina; Prasad, Sanjana; Noskov, Vladimir N; Montague, Michael G; Friedman, Robert M; Desai, Prashant J; Vashee, Sanjay

2017-10-17

Here, we present a transformational approach to genome engineering of herpes simplex virus type 1 (HSV-1), which has a large DNA genome, using synthetic genomics tools. We believe this method will enable more rapid and complex modifications of HSV-1 and other large DNA viruses than previous technologies, facilitating many useful applications. Yeast transformation-associated recombination was used to clone 11 fragments comprising the HSV-1 strain KOS 152 kb genome. Using overlapping sequences between the adjacent pieces, we assembled the fragments into a complete virus genome in yeast, transferred it into an Escherichia coli host, and reconstituted infectious virus following transfection into mammalian cells. The virus derived from this yeast-assembled genome, KOS YA , replicated with kinetics similar to wild-type virus. We demonstrated the utility of this modular assembly technology by making numerous modifications to a single gene, making changes to two genes at the same time and, finally, generating individual and combinatorial deletions to a set of five conserved genes that encode virion structural proteins. While the ability to perform genome-wide editing through assembly methods in large DNA virus genomes raises dual-use concerns, we believe the incremental risks are outweighed by potential benefits. These include enhanced functional studies, generation of oncolytic virus vectors, development of delivery platforms of genes for vaccines or therapy, as well as more rapid development of countermeasures against potential biothreats.

Genephony: a knowledge management tool for genome-wide research

Directory of Open Access Journals (Sweden)

Riva Alberto

2009-09-01

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

Analysis of the Pantoea ananatis pan-genome reveals factors underlying its ability to colonize and interact with plant, insect and vertebrate hosts.

Science.gov (United States)

De Maayer, Pieter; Chan, Wai Yin; Rubagotti, Enrico; Venter, Stephanus N; Toth, Ian K; Birch, Paul R J; Coutinho, Teresa A

2014-05-27

Pantoea ananatis is found in a wide range of natural environments, including water, soil, as part of the epi- and endophytic flora of various plant hosts, and in the insect gut. Some strains have proven effective as biological control agents and plant-growth promoters, while other strains have been implicated in diseases of a broad range of plant hosts and humans. By analysing the pan-genome of eight sequenced P. ananatis strains isolated from different sources we identified factors potentially underlying its ability to colonize and interact with hosts in both the plant and animal Kingdoms. The pan-genome of the eight compared P. ananatis strains consisted of a core genome comprised of 3,876 protein coding sequences (CDSs) and a sizeable accessory genome consisting of 1,690 CDSs. We estimate that ~106 unique CDSs would be added to the pan-genome with each additional P. ananatis genome sequenced in the future. The accessory fraction is derived mainly from integrated prophages and codes mostly for proteins of unknown function. Comparison of the translated CDSs on the P. ananatis pan-genome with the proteins encoded on all sequenced bacterial genomes currently available revealed that P. ananatis carries a number of CDSs with orthologs restricted to bacteria associated with distinct hosts, namely plant-, animal- and insect-associated bacteria. These CDSs encode proteins with putative roles in transport and metabolism of carbohydrate and amino acid substrates, adherence to host tissues, protection against plant and animal defense mechanisms and the biosynthesis of potential pathogenicity determinants including insecticidal peptides, phytotoxins and type VI secretion system effectors. P. ananatis has an 'open' pan-genome typical of bacterial species that colonize several different environments. The pan-genome incorporates a large number of genes encoding proteins that may enable P. ananatis to colonize, persist in and potentially cause disease symptoms in a wide range of

Meta-analysis of five genome-wide association studies identifies multiple new loci associated with testicular germ cell tumor

DEFF Research Database (Denmark)

Wang, Zhaoming; McGlynn, Katherine A.; Rajpert-De Meyts, Ewa

2017-01-01

The international Testicular Cancer Consortium (TECAC) combined five published genome-wide association studies of testicular germ cell tumor (TGCT; 3,558 cases and 13,970 controls) to identify new susceptibility loci. We conducted a fixed-effects meta-analysis, including, to our knowledge, the fi...

Sex-stratified Genome-wide Association Studies Including 270000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits

NARCIS (Netherlands)

Randall, J.C.; Winkler, T.W.; Kutalik, Z.; Berndt, S.I.; Jackson, A.U.; Monda, K.L.; Kilpeläinen, T.O.; Esko, T.; Mägi, R.; Li, S.; Workalemahu, T.; Feitosa, M.F.; Croteau-Chonka, D.C.; Day, F.R.; Fall, T.; Ferreira, T.; Gustafsson, S.; Locke, A.E.; Mathieson, I.; Scherag, A.; Vedantam, S.; Wood, A.R.; Liang, L.; Steinthorsdottir, V.; Thorleifsson, G.; Dermitzakis, E.T.; Dimas, A.S.; Karpe, F.; Min, J.L.; Nicholson, G.; Clegg, D.J.; Person, T.; Krohn, J.P.; Bauer, S.; Buechler, C.; Eisinger, K.; Bonnefond, A.; Froguel, P.; Hottenga, J.J.; Prokopenko, I.; Waite, L.L.; Harris, T.B.; Smith, A.V.; Shuldiner, A.R.; McArdle, W.L.; Caulfield, M.J.; Munroe, P.B.; Grönberg, H.; Chen, Y.D.; Li, G.; Beckmann, J.S.; Johnson, T.; Thorsteinsdottir, U.; Teder-Laving, M.; Khaw, K.T.; Wareham, N.J.; Zhao, J.H.; Amin, N.; Oostra, B.A.; Kraja, A.T.; Province, M.A.; Cupples, L.A.; Heard-Costa, N.L.; Kaprio, J.; Ripatti, S.; Surakka, I.; Collins, F.S.; Saramies, J.; Tuomilehto, J.; Jula, A.; Salomaa, V.; Erdmann, J.; Hengstenberg, C.; Loley, C.; Schunkert, H.; Lamina, C.; Wichmann, H.E.; Albrecht, E.; Gieger, C.; Hicks, A.A.; Johansson, A.; Pramstaller, P.P.; Kathiresan, S.; Speliotes, E.K.; Penninx, B.W.J.H.; Hartikainen, A.L.; Järvelin, M.R.; Gyllensten, U.; Boomsma, D.I.; Campbell, H.; Wilson, J.F.; Chanock, S.J.; Farrall, M.; Goel, A.; Medina-Gomez, C.; Rivadeneira, F.; Estrada, K.; Uitterlinden, A.G.; Hofman, A.; Zillikens, M.C.; den Heijer, M.; Kiemeney, L.A.; Maschio, A.; Hall, P.; Tyrer, J.; Teumer, A.; Völzke, H.; Kovacs, P.; Tönjes, A.; Mangino, M.; Spector, T.D.; Hayward, C.; Rudan, I.; Hall, A.S.; Samani, N.J.; Attwood, A.P.; Sambrook, J.G.; Hung, J.; Palmer, L.J.; Lokki, M.L.; Sinisalo, J.; Boucher, G.; Huikuri, H.V.; Lorentzon, M.; Ohlsson, C.; Eklund, N.; Eriksson, J.G.; Barlassina, C.; Rivolta, C.; Nolte, I.M.; Snieder, H.; van der Klauw, M.M.; van Vliet-Ostaptchouk, J.V.; Gejman, P.V.; Shi, J.; Jacobs, K.B.; Wang, Z.; Bakker, S.J.; Mateo Leach, I.; Navis, G.; van der Harst, P.; Martin, N.G.; Medland, S.E.; Montgomery, G.W.; Yang, J.; Chasman, D.I.; Ridker, P.M.; Rose, L.M.; Lehtimäki, T.; Raitakari, O.; Absher, D.; Iribarren, C.; Basart, H.; Hovingh, K.G.; Hyppönen, E.; Power, C.; Anderson, D.; Beilby, J.P.; Hui, J.; Jolley, J.; Sager, H.; Bornstein, S.R.; Schwarz, P.E.; Kristiansson, K.; Perola, M.; Lindström, J.; Swift, A.J.; Uusitupa, M.; Atalay, M.; Lakka, T.A.; Rauramaa, R.; Bolton, J.L.; Fowkes, G.; Fraser, R.M.; Price, J.F.; Fischer, K.; Krjuta Kov, K.; Metspalu, A.; Mihailov, E.; Langenberg, C.; Luan, J.; Ong, K.K.; Chines, P.S.; Keinanen-Kiukaanniemie, S.; Saaristo, T.E.; Edkins, S.; Franks, P.W.; Hallmans, G.; Shungin, D.; Morris, A.D.; Palmer, C.N.A.; Erbel, R.; Moebus, S.; Nöthen, M.M.; Pechlivanis, S.; Hveem, K.; Narisu, N.; Hamsten, A.; Humphries, S.E.; Strawbridge, R.J.; Tremoli, E.; Grallert, H.; Thorand, B.; Illig, T.; Koenig, W.; Müller-Nurasyid, M.; Peters, A.; Boehm, B.O.; Kleber, M.E.; März, W.; Winkelmann, B.R.; Kuusisto, J.; Laakso, M.; Arveiler, D.; Cesana, G.; Kuulasmaa, K.; Virtamo, J.; Yarnell, J.W.; Kuh, D; Wong, A.; Lind, L.; de Faire, U.; Gigante, B.; Magnusson, P.K.E.; Pedersen, N.L.; Dedoussis, G.; Dimitriou, M.; Kolovou, G.; Kanoni, S.; Stirrups, K.; Bonnycastle, L.L.; Njolstad, I.; Wilsgaard, T.; Ganna, A.; Rehnberg, E.; Hingorani, A.D.; Kivimaki, M.; Kumari, M.; Assimes, T.L.; Barroso, I.; Boehnke, M.; Borecki, I.B.; Deloukas, P.; Fox, C.S.; Frayling, T.M.; Groop, L.C.; Haritunians, T.; Hunter, D.; Ingelsson, E.; Kaplan, R.; Mohlke, K.L.; O'Connell, J.R.; Schlessinger, D.; Strachan, D.P.; Stefansson, K.; van Duijn, C.M.; Abecasis, G.R.; McCarthy, M.I.; Hirschhorn, J.N.; Qi, L.; Loos, R.J.; Lindgren, C.M.; North, K.E.; Heid, I.M.

2013-01-01

Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723

Genome-wide association of body fat distribution in African ancestry populations suggests new loci.

Directory of Open Access Journals (Sweden)

Ching-Ti Liu

Full Text Available Central obesity, measured by waist circumference (WC or waist-hip ratio (WHR, is a marker of body fat distribution. Although obesity disproportionately affects minority populations, few studies have conducted genome-wide association study (GWAS of fat distribution among those of predominantly African ancestry (AA. We performed GWAS of WC and WHR, adjusted and unadjusted for BMI, in up to 33,591 and 27,350 AA individuals, respectively. We identified loci associated with fat distribution in AA individuals using meta-analyses of GWA results for WC and WHR (stage 1. Overall, 25 SNPs with single genomic control (GC-corrected p-values<5.0 × 10(-6 were followed-up (stage 2 in AA with WC and with WHR. Additionally, we interrogated genomic regions of previously identified European ancestry (EA WHR loci among AA. In joint analysis of association results including both Stage 1 and 2 cohorts, 2 SNPs demonstrated association, rs2075064 at LHX2, p = 2.24×10(-8 for WC-adjusted-for-BMI, and rs6931262 at RREB1, p = 2.48×10(-8 for WHR-adjusted-for-BMI. However, neither signal was genome-wide significant after double GC-correction (LHX2: p = 6.5 × 10(-8; RREB1: p = 5.7 × 10(-8. Six of fourteen previously reported loci for waist in EA populations were significant (p<0.05 divided by the number of independent SNPs within the region in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN. Further, we observed associations with metabolic traits: rs13389219 at GRB14 associated with HDL-cholesterol, triglycerides, and fasting insulin, and rs13060013 at ADAMTS9 with HDL-cholesterol and fasting insulin. Finally, we observed nominal evidence for sexual dimorphism, with stronger results in AA women at the GRB14 locus (p for interaction = 0.02. In conclusion, we identified two suggestive loci associated with fat distribution in AA populations in addition to confirming 6 loci previously identified in populations of EA. These findings reinforce the concept

Genome-wide DNA methylation analysis of pseudohypoparathyroidism patients with GNAS imprinting defects.

Science.gov (United States)

Rochtus, Anne; Martin-Trujillo, Alejandro; Izzi, Benedetta; Elli, Francesca; Garin, Intza; Linglart, Agnes; Mantovani, Giovanna; Perez de Nanclares, Guiomar; Thiele, Suzanne; Decallonne, Brigitte; Van Geet, Chris; Monk, David; Freson, Kathleen

2016-01-01

Pseudohypoparathyroidism (PHP) is caused by (epi)genetic defects in the imprinted GNAS cluster. Current classification of PHP patients is hampered by clinical and molecular diagnostic overlaps. The European Consortium for the study of PHP designed a genome-wide methylation study to improve molecular diagnosis. The HumanMethylation 450K BeadChip was used to analyze genome-wide methylation in 24 PHP patients with parathyroid hormone resistance and 20 age- and gender-matched controls. Patients were previously diagnosed with GNAS-specific differentially methylated regions (DMRs) and include 6 patients with known STX16 deletion (PHP(Δstx16)) and 18 without deletion (PHP(neg)). The array demonstrated that PHP patients do not show DNA methylation differences at the whole-genome level. Unsupervised clustering of GNAS-specific DMRs divides PHP(Δstx16) versus PHP(neg) patients. Interestingly, in contrast to the notion that all PHP patients share methylation defects in the A/B DMR while only PHP(Δstx16) patients have normal NESP, GNAS-AS1 and XL methylation, we found a novel DMR (named GNAS-AS2) in the GNAS-AS1 region that is significantly different in both PHP(Δstx16) and PHP(neg), as validated by Sequenom EpiTYPER in a larger PHP cohort. The analysis of 58 DMRs revealed that 8/18 PHP(neg) and 1/6 PHP(Δstx16) patients have multi-locus methylation defects. Validation was performed for FANCC and SVOPL DMRs. This is the first genome-wide methylation study for PHP patients that confirmed that GNAS is the most significant DMR, and the presence of STX16 deletion divides PHP patients in two groups. Moreover, a novel GNAS-AS2 DMR affects all PHP patients, and PHP patients seem sensitive to multi-locus methylation defects.

Genome-Wide Linkage and Association Analysis Identifies Major Gene Loci for Guttural Pouch Tympany in Arabian and German Warmblood Horses

Science.gov (United States)

Metzger, Julia; Ohnesorge, Bernhard; Distl, Ottmar

2012-01-01

Equine guttural pouch tympany (GPT) is a hereditary condition affecting foals in their first months of life. Complex segregation analyses in Arabian and German warmblood horses showed the involvement of a major gene as very likely. Genome-wide linkage and association analyses including a high density marker set of single nucleotide polymorphisms (SNPs) were performed to map the genomic region harbouring the potential major gene for GPT. A total of 85 Arabian and 373 German warmblood horses were genotyped on the Illumina equine SNP50 beadchip. Non-parametric multipoint linkage analyses showed genome-wide significance on horse chromosomes (ECA) 3 for German warmblood at 16–26 Mb and 34–55 Mb and for Arabian on ECA15 at 64–65 Mb. Genome-wide association analyses confirmed the linked regions for both breeds. In Arabian, genome-wide association was detected at 64 Mb within the region with the highest linkage peak on ECA15. For German warmblood, signals for genome-wide association were close to the peak region of linkage at 52 Mb on ECA3. The odds ratio for the SNP with the highest genome-wide association was 0.12 for the Arabian. In conclusion, the refinement of the regions with the Illumina equine SNP50 beadchip is an important step to unravel the responsible mutations for GPT. PMID:22848553

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....

Studies on the Interaction between Zinc-Hydroxybenzoite Complex and Genomic DNA

Directory of Open Access Journals (Sweden)

Hacali Necefoglu

2006-04-01

Full Text Available Zinc-Hydroxybenzoite ([Zn (H206] (p-HO-C6H4COO22H20 complex which wassynthesized and characterized by instrumental methods and the DNA samples which hadbeen isolated from cattle were allowed to interact at 37 oC for different time periods. Theinteraction of genomic DNA with this complex has been followed by agarose gelelectrophoresis at 50 V for 2 h. When DNA samples were allowed to interact with this metalcomplex, it was found that band intensities changed with the concentrations of the complex.In the result of interaction between this complex and genomic DNA samples, it wasdetermined that the intensities of bands were changed at the different concentrations of thecomplex. The brightness of the bands was increased and mobility of the bands wasdecreased, indicating the occurrence of increased covalent binding of the metal complexwith DNA. In this study it was concluded that the damage effect of ascorbate was reducedby Zinc-Hydroxybenzoite.

Joint genome-wide prediction in several populations accounting for randomness of genotypes: A hierarchical Bayes approach. I: Multivariate Gaussian priors for marker effects and derivation of the joint probability mass function of genotypes.

Science.gov (United States)

Martínez, Carlos Alberto; Khare, Kshitij; Banerjee, Arunava; Elzo, Mauricio A

2017-03-21

It is important to consider heterogeneity of marker effects and allelic frequencies in across population genome-wide prediction studies. Moreover, all regression models used in genome-wide prediction overlook randomness of genotypes. In this study, a family of hierarchical Bayesian models to perform across population genome-wide prediction modeling genotypes as random variables and allowing population-specific effects for each marker was developed. Models shared a common structure and differed in the priors used and the assumption about residual variances (homogeneous or heterogeneous). Randomness of genotypes was accounted for by deriving the joint probability mass function of marker genotypes conditional on allelic frequencies and pedigree information. As a consequence, these models incorporated kinship and genotypic information that not only permitted to account for heterogeneity of allelic frequencies, but also to include individuals with missing genotypes at some or all loci without the need for previous imputation. This was possible because the non-observed fraction of the design matrix was treated as an unknown model parameter. For each model, a simpler version ignoring population structure, but still accounting for randomness of genotypes was proposed. Implementation of these models and computation of some criteria for model comparison were illustrated using two simulated datasets. Theoretical and computational issues along with possible applications, extensions and refinements were discussed. Some features of the models developed in this study make them promising for genome-wide prediction, the use of information contained in the probability distribution of genotypes is perhaps the most appealing. Further studies to assess the performance of the models proposed here and also to compare them with conventional models used in genome-wide prediction are needed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genome-wide association studies in Alzheimer's disease.

Science.gov (United States)

Bertram, Lars; Tanzi, Rudolph E

2009-10-15

Genome-wide association studies (GWAS) have gained considerable momentum over the last couple of years for the identification of novel complex disease genes. In the field of Alzheimer's disease (AD), there are currently eight published and two provisionally reported GWAS, highlighting over two dozen novel potential susceptibility loci beyond the well-established APOE association. On the basis of the data available at the time of this writing, the most compelling novel GWAS signal has been observed in GAB2 (GRB2-associated binding protein 2), followed by less consistently replicated signals in galanin-like peptide (GALP), piggyBac transposable element derived 1 (PGBD1), tyrosine kinase, non-receptor 1 (TNK1). Furthermore, consistent replication has been recently announced for CLU (clusterin, also known as apolipoprotein J). Finally, there are at least three replicated loci in hitherto uncharacterized genomic intervals on chromosomes 14q32.13, 14q31.2 and 6q24.1 likely implicating the existence of novel AD genes in these regions. In this review, we will discuss the characteristics and potential relevance to pathogenesis of the outcomes of all currently available GWAS in AD. A particular emphasis will be laid on findings with independent data in favor of the original association.

Genome-wide analysis of cell wall-related genes in Tuber melanosporum.

Science.gov (United States)

Balestrini, Raffaella; Sillo, Fabiano; Kohler, Annegret; Schneider, Georg; Faccio, Antonella; Tisserant, Emilie; Martin, Francis; Bonfante, Paola

2012-06-01

A genome-wide inventory of proteins involved in cell wall synthesis and remodeling has been obtained by taking advantage of the recently released genome sequence of the ectomycorrhizal Tuber melanosporum black truffle. Genes that encode cell wall biosynthetic enzymes, enzymes involved in cell wall polysaccharide synthesis or modification, GPI-anchored proteins and other cell wall proteins were identified in the black truffle genome. As a second step, array data were validated and the symbiotic stage was chosen as the main focus. Quantitative RT-PCR experiments were performed on 29 selected genes to verify their expression during ectomycorrhizal formation. The results confirmed the array data, and this suggests that cell wall-related genes are required for morphogenetic transition from mycelium growth to the ectomycorrhizal branched hyphae. Labeling experiments were also performed on T. melanosporum mycelium and ectomycorrhizae to localize cell wall components.

Genome-wide association study for milking speed in French Holstein cows

DEFF Research Database (Denmark)

Marete, Andrew Gitahi; Sahana, Goutam; Fritz, Sebastian

2018-01-01

Using a combination of data from the BovineSNP50 BeadChip SNP array (Illumina, San Diego, CA) and a EuroGenomics (Amsterdam, the Netherlands) custom single nucleotide polymorphism (SNP) chip with SNP pre-selected from whole genome sequence data, we carried out an association study of milking speed...... associated with milking speed. As clinical mastitis and somatic cell score have an unfavorable genetic correlation with milking speed, we tested whether the most significant SNP on these 22 chromosomes associated with milking speed were also associated with clinical mastitis or somatic cell score. Nine...... hundred seventy-one genome-wide significant SNP were associated with milking speed. Of these, 86 were associated with clinical mastitis and 198 with somatic cell score. The most significant association signals for milking speed were observed on chromosomes 7, 8, 10, 14, and 18. The most significant signal...

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

From Genome-Wide Association Study to Phenome-Wide Association Study: New Paradigms in Obesity Research.

Science.gov (United States)

Zhang, Y-P; Zhang, Y-Y; Duan, D D

2016-01-01

Obesity is a condition in which excess body fat has accumulated over an extent that increases the risk of many chronic diseases. The current clinical classification of obesity is based on measurement of body mass index (BMI), waist-hip ratio, and body fat percentage. However, these measurements do not account for the wide individual variations in fat distribution, degree of fatness or health risks, and genetic variants identified in the genome-wide association studies (GWAS). In this review, we will address this important issue with the introduction of phenome, phenomics, and phenome-wide association study (PheWAS). We will discuss the new paradigm shift from GWAS to PheWAS in obesity research. In the era of precision medicine, phenomics and PheWAS provide the required approaches to better definition and classification of obesity according to the association of obese phenome with their unique molecular makeup, lifestyle, and environmental impact. Copyright © 2016 Elsevier Inc. All rights reserved.

Genome-wide identification and expression analysis of MAPK and MAPKK gene family in Malus domestica.

Science.gov (United States)

Zhang, Shizhong; Xu, Ruirui; Luo, Xiaocui; Jiang, Zesheng; Shu, Huairui

2013-12-01

MAPK signal transduction modules play crucial roles in regulating many biological processes in plants, which are composed of three classes of hierarchically organized protein kinases, namely MAPKKKs, MAPKKs, and MAPKs. Although genome-wide analysis of this family has been carried out in some species, little is known about MAPK and MAPKK genes in apple (Malus domestica). In this study, a total of 26 putative apple MAPK genes (MdMPKs) and 9 putative apple MAPKK genes (MdMKKs) have been identified and located within the apple genome. Phylogenetic analysis revealed that MdMAPKs and MdMAPKKs could be divided into 4 subfamilies (groups A, B, C and D), respectively. The predicted MdMAPKs and MdMAPKKs were distributed across 13 out of 17 chromosomes with different densities. In addition, analysis of exon-intron junctions and of intron phase inside the predicted coding region of each candidate gene has revealed high levels of conservation within and between phylogenetic groups. According to the microarray and expressed sequence tag (EST) analysis, the different expression patterns indicate that they may play different roles during fruit development and rootstock-scion interaction process. Moreover, MAPK and MAPKK genes were performed expression profile analyses in different tissues (root, stem, leaf, flower and fruit), and all of the selected genes were expressed in at least one of the tissues tested, indicating that the MAPKs and MAPKKs are involved in various aspects of physiological and developmental processes of apple. To our knowledge, this is the first report of a genome-wide analysis of the apple MAPK and MAPKK gene family. This study provides valuable information for understanding the classification and putative functions of the MAPK signal in apple. © 2013.

Genome-wide association study identifies shared risk loci common to two malignancies in golden retrievers.

Directory of Open Access Journals (Sweden)

Noriko Tonomura

2015-02-01

Full Text Available Dogs, with their breed-determined limited genetic background, are great models of human disease including cancer. Canine B-cell lymphoma and hemangiosarcoma are both malignancies of the hematologic system that are clinically and histologically similar to human B-cell non-Hodgkin lymphoma and angiosarcoma, respectively. Golden retrievers in the US show significantly elevated lifetime risk for both B-cell lymphoma (6% and hemangiosarcoma (20%. We conducted genome-wide association studies for hemangiosarcoma and B-cell lymphoma, identifying two shared predisposing loci. The two associated loci are located on chromosome 5, and together contribute ~20% of the risk of developing these cancers. Genome-wide p-values for the top SNP of each locus are 4.6×10-7 and 2.7×10-6, respectively. Whole genome resequencing of nine cases and controls followed by genotyping and detailed analysis identified three shared and one B-cell lymphoma specific risk haplotypes within the two loci, but no coding changes were associated with the risk haplotypes. Gene expression analysis of B-cell lymphoma tumors revealed that carrying the risk haplotypes at the first locus is associated with down-regulation of several nearby genes including the proximal gene TRPC6, a transient receptor Ca2+-channel involved in T-cell activation, among other functions. The shared risk haplotype in the second locus overlaps the vesicle transport and release gene STX8. Carrying the shared risk haplotype is associated with gene expression changes of 100 genes enriched for pathways involved in immune cell activation. Thus, the predisposing germ-line mutations in B-cell lymphoma and hemangiosarcoma appear to be regulatory, and affect pathways involved in T-cell mediated immune response in the tumor. This suggests that the interaction between the immune system and malignant cells plays a common role in the tumorigenesis of these relatively different cancers.

Genome-wide association study (GWAS) for molar-incisor hypomineralization (MIH).

Science.gov (United States)

Kühnisch, Jan; Thiering, Elisabeth; Heitmüller, Daniela; Tiesler, Carla M T; Grallert, Harald; Heinrich-Weltzien, Roswitha; Hickel, Reinhard; Heinrich, Joachim

2014-01-01

This genome-wide association study (GWAS) investigated the relationship between molar-incisor hypomineralization (MIH) and possible genetic loci. Clinical and genetic data from the 10-year follow-up of 668 children from the Munich GINI-plus and LISA-plus birth cohort studies were analyzed. The dental examinations included the diagnosis of MIH according to the criteria of the European Academy of Paediatric Dentistry (EAPD). Children with MIH were categorized as those with a minimum of one hypomineralized first permanent molar. A GWAS was implemented following a quality-control step and an additive genetic effect was assumed. A total of 2,013,491 single-nucleotide polymorphisms (SNPs) were available for analysis. Rs13058467, which is located near the SCUBE1 gene on chromosome 22 (p MIH when using a threshold of p value MIH.

A Genome-Wide Landscape of Retrocopies in Primate Genomes.

Science.gov (United States)