Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA549750 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Allele-specific NKX2-5 binding underlies multiple genetic associations with human electrocardiographic traits
| PRJNA554117 | ENA
Project description:Research into the genetic influences of impulsivity and reward motivated behavior relies heavily on outbred animal populations, including Heterogeneous Stock (HS) rats, for the genetic diversity necessary to identify genotype-trait associations. Many such associations have been detected, but it is not always clear which gene or other feature near the identified genomic location is functionally responsible for the association. Since these traits are in part mediated by gene expression, mapping the associations between genotype and gene expression in these animals will enable the discovery and deeper understanding of these trait associations. We therefore obtained genotypes and RNA-Seq gene expression for five brain regions from 88 HS rats and mapped expression quantitative trait loci (eQTLs) for each region. We identified cis-eQTLs in over 3,000 genes per brain region and validated their effect sizes using allele specific expression. This resource will enable new discoveries of the genetic influences of complex behavioral traits.
2021-04-23 | GSE173140 | GEO
Project description:Research into the genetic influences of impulsivity and reward motivated behavior relies heavily on outbred animal populations, including Heterogeneous Stock (HS) rats, for the genetic diversity necessary to identify genotype-trait associations. Many such associations have been detected, but it is not always clear which gene or other feature near the identified genomic location is functionally responsible for the association. Since these traits are in part mediated by gene expression, mapping the associations between genotype and gene expression in these animals will enable the discovery and deeper understanding of these trait associations. We therefore obtained genotypes and RNA-Seq gene expression for five brain regions from 88 HS rats and mapped expression quantitative trait loci (eQTLs) for each region. We identified cis-eQTLs in over 3,000 genes per brain region and validated their effect sizes using allele specific expression. This resource will enable new discoveries of the genetic influences of complex behavioral traits.
2021-04-23 | GSE173139 | GEO
Project description:Research into the genetic influences of impulsivity and reward motivated behavior relies heavily on outbred animal populations, including Heterogeneous Stock (HS) rats, for the genetic diversity necessary to identify genotype-trait associations. Many such associations have been detected, but it is not always clear which gene or other feature near the identified genomic location is functionally responsible for the association. Since these traits are in part mediated by gene expression, mapping the associations between genotype and gene expression in these animals will enable the discovery and deeper understanding of these trait associations. We therefore obtained genotypes and RNA-Seq gene expression for five brain regions from 88 HS rats and mapped expression quantitative trait loci (eQTLs) for each region. We identified cis-eQTLs in over 3,000 genes per brain region and validated their effect sizes using allele specific expression. This resource will enable new discoveries of the genetic influences of complex behavioral traits.
2021-04-23 | GSE173138 | GEO
Project description:Research into the genetic influences of impulsivity and reward motivated behavior relies heavily on outbred animal populations, including Heterogeneous Stock (HS) rats, for the genetic diversity necessary to identify genotype-trait associations. Many such associations have been detected, but it is not always clear which gene or other feature near the identified genomic location is functionally responsible for the association. Since these traits are in part mediated by gene expression, mapping the associations between genotype and gene expression in these animals will enable the discovery and deeper understanding of these trait associations. We therefore obtained genotypes and RNA-Seq gene expression for five brain regions from 88 HS rats and mapped expression quantitative trait loci (eQTLs) for each region. We identified cis-eQTLs in over 3,000 genes per brain region and validated their effect sizes using allele specific expression. This resource will enable new discoveries of the genetic influences of complex behavioral traits.
2021-04-23 | GSE173137 | GEO
Project description:Research into the genetic influences of impulsivity and reward motivated behavior relies heavily on outbred animal populations, including Heterogeneous Stock (HS) rats, for the genetic diversity necessary to identify genotype-trait associations. Many such associations have been detected, but it is not always clear which gene or other feature near the identified genomic location is functionally responsible for the association. Since these traits are in part mediated by gene expression, mapping the associations between genotype and gene expression in these animals will enable the discovery and deeper understanding of these trait associations. We therefore obtained genotypes and RNA-Seq gene expression for five brain regions from 88 HS rats and mapped expression quantitative trait loci (eQTLs) for each region. We identified cis-eQTLs in over 3,000 genes per brain region and validated their effect sizes using allele specific expression. This resource will enable new discoveries of the genetic influences of complex behavioral traits.
2021-04-23 | GSE173136 | GEO
Project description:Explaining the genetics of many diseases is challenging because most associations localize to regulatory regions. We present a novel computational method for discovering disease-driving mechanisms acting across multiple disease-associated, non-coding genomic regions. Application to a matrix of 213 phenotypes and 1,544 transcription factor (TF) binding datasets identifies 2,264 significant associations for hundreds of TFs in 92 phenotypes, including prostate and breast cancers. Strikingly, nearly half of the systemic lupus erythematosus risk loci are occupied by the Epstein-Barr virus EBNA2 protein and 24 human TFs, revealing an important gene-environment interaction. EBNA2-anchored associations also exist in multiple sclerosis, rheumatoid arthritis, inflammatory bowel disease, type 1 diabetes, juvenile idiopathic arthritis, and celiac disease. Instances of allele-dependent DNA binding and downstream effects on gene expression at plausibly causal autoimmune variants support a genetic mechanism of pathogenesis centered on EBNA2. Our results nominate mechanisms operating across disease risk loci, suggesting new paradigms of disease origins.
2018-01-17 | GSE93709 | GEO
Project description:Complex traits and diseases can be influenced by both genetics and environment. However, given the large number of environmental stimuli and power challenges for gene-by-environment testing, it remains a critical challenge to identify and prioritize specific disease-relevant environmental exposures. We propose a novel framework for leveraging signals from transcriptional responses to environmental perturbations to identify disease-relevant perturbations that can modulate genetic risk for complex traits and inform the functions of genetic variants associated with complex traits. We perturbed human skeletal muscle, fat, and liver relevant cell lines with 21 perturbations affecting insulin resistance, glucose homeostasis, and metabolic regulation in humans and identified thousands of environmentally responsive genes. By combining these data with GWAS from 31 distinct polygenic traits, we show that the heritability of multiple traits is enriched in regions surrounding genes responsive to specific perturbations and, further, that environmentally responsive genes are enriched for associations with specific diseases and phenotypes from the GWAS catalog. Overall, we demonstrate the advantages of large-scale characterization of transcriptional changes in diversely stimulated and pathologically relevant cells to identify disease-relevant perturbations.
2021-07-09 | GSE179347 | GEO
Project description:Coronary artery disease (CAD) is the leading cause of mortality and morbidity driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with CAD and myocardial infarction (MI) susceptibility in multi-ethnic populations. The majority of these variants reside in non-coding regulatory regions and are co-inherited with hundreds of candidate regulatory SNPs. Herein, we use integrative genomic, epigenomic, and transcriptomic fine-mapping in human coronary artery smooth muscle cells (HCASMC) and tissues to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps we prioritize 65 candidate variants and perform allele-specific binding and expression analyses on 7 top candidates. We validate our findings in two independent cohorts of diseased human arterial expression quantitative trait loci (eQTL), which together demonstrate fundamental links between CAD associations and regulatory function in the appropriate disease context.
2016-07-06 | GSE72696 | GEO