GxE and Complex Traits
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ABSTRACT:
PROVIDER: PRJNA335523 | ENA |
REPOSITORIES: ENA
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Project description:Heritable epigenetic factors can contribute to complex disease etiology. In this study we examine, on a global scale, the contribution of DNA methylation to complex traits that are precursors to heart disease, diabetes and osteoporosis. We profiled DNA methylation patterns in the liver using bisulfite sequencing in 90 mouse inbred strains, genome-wide expression levels, proteomics, metabolomics and sixty-eight clinical traits, and performed epigenome-wide association studies (EWAS). We found associations with numerous clinical traits including bone mineral density, plasma cholesterol, insulin resistance, gene expression, protein and metabolite levels. A large proportion of associations were unique to EWAS and were not identified using GWAS. Methylation levels were regulated by genetics largely in cis, but we also found evidence of trans regulation, and we demonstrate that genetic variation in the methionine synthase reductase gene Mtrr affects methylation of hundreds of CpGs throughout the genome. Our results indicate that natural variation in methylation levels contributes to the etiology of complex clinical traits. Reduced representation bisulfite sequencing in mouse strains using liver genomic DNA
2015-04-02 | E-GEOD-67507 | biostudies-arrayexpress
Project description:Copy number variation (CNV) is an important type of genetic variation contributing to phenotypic differences among mammals. Up to now, GWAS analysis using CNV called by array CGH is lacking in livestock like Holstein cattle. The objectives of this work are to identify CNVs using high-density aCGH data and explore functional CNVs which are associated with complex traits by GWAS method in Holstein cattle. In this study, we reported a systematic CNV association analysis of CNVs and 39 complex production traits in Holsteins. This research identified 1043 CNV regions (CNVRs) by array CGH data in 47 Holstein bulls. Using a genome-wide association analysis (GWAS) approach, we identified 79 significant CNVRs associated with at least one complex traits after false discovery rate (FDR) correction. Notably, 24 CNVRs were markedly related to daughter pregnancy rate (DPR). This study observed the pleiotropy phenomenon of 39 CNV loci which can simultaneously regulate at least 2 complex traits. In summary, the significant CNVs identified in this research could be utilized additional molecular markers for genetic improvement programs in Holsteins.
2019-02-16 | GSE122478 | GEO
Project description:Heritable epigenetic factors can contribute to complex disease etiology. In this study we examine, on a global scale, the contribution of DNA methylation to complex traits that are precursors to heart disease, diabetes and osteoporosis. We profiled DNA methylation patterns in the liver using bisulfite sequencing in 90 mouse inbred strains, genome-wide expression levels, proteomics, metabolomics and sixty-eight clinical traits, and performed epigenome-wide association studies (EWAS). We found associations with numerous clinical traits including bone mineral density, plasma cholesterol, insulin resistance, gene expression, protein and metabolite levels. A large proportion of associations were unique to EWAS and were not identified using GWAS. Methylation levels were regulated by genetics largely in cis, but we also found evidence of trans regulation, and we demonstrate that genetic variation in the methionine synthase reductase gene Mtrr affects methylation of hundreds of CpGs throughout the genome. Our results indicate that natural variation in methylation levels contributes to the etiology of complex clinical traits.
2015-04-02 | GSE67507 | 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:Genetic variants in gene regulatory sequences can modify gene expression and mediate the molecular response to environmental stimuli. In addition, genotype–environment interactions (GxE) contribute to complex traits such as cardiovascular disease. Caffeine is the most widely consumed stimulant and is known to produce a vascular response. To investigate GxE for caffeine, we treated vascular endothelial cells with caffeine and used a massively parallel reporter assay to measure allelic effects on gene regulation for over 43,000 genetic variants. We identified 665 variants with allelic effects on gene regulation and 6 variants that regulate the gene expression response to caffeine (GxE, false discovery rate [FDR] < 5%). When overlapping our GxE results with expression quantitative trait loci colocalized with coronary artery disease and hypertension, we dissected their regulatory mechanisms and showed a modulatory role for caffeine. Our results demonstrate that massively parallel reporter assay is a powerful approach to identify and molecularly characterize GxE in the specific context of caffeine consumption.
2024-02-26 | GSE221514 | GEO
Project description:Epistatic regulation of complex traits and gene expression in mice
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Project description:We used microarrays to assess whole genome transcript profiles of the 40 homozygous Raleigh lines to understand the genetic basis of complex traits in Drosophila
2009-04-22 | E-MEXP-1594 | biostudies-arrayexpress
Project description:The genetic contribution of additive versus non-additive (epistasis) effects in the regulation of hematologic and other complex traits is unclear. While genome-wide association studies typically ignore gene-gene interactions, in part because of the lack of statistical power for detecting them, mouse chromosome substitution strains (CSSs) represent an alternate and powerful model for detecting epistasis given their limited allelic variation. Therefore, we utilized CSSs to identify and map both additive and epistatic loci that regulate a range of hematologic- and metabolism-related traits, as well as hepatic gene expression. Quantitative trait loci (QTLs) were identified using a modified backcross strategy involving the segregation of variants on the A/J-derived substituted chromosomes 4 and 6 on an otherwise C57BL/6J genetic background. By analyzing the transcriptomes of offspring from this cross, we identified and mapped additive QTLs regulating the expression of 768 genes, and epistatic QTLs for 519 genes. Similarly, we identified additive QTLs for fat pad weight, platelets, and percentage of granulocyte in the blood as well as epistatic QTLs controlling the percentage of lymphocytes in the blood and red cell distribution width. The variance attributed to the epistatic QTLs was approximately equal to that of the additive QTLs, demonstrating the importance of identifying genetic interactions to understand the genetic basis of complex traits. Of particular note, even the epistatic QTLs identified that accounted for the largest variances were undetected in our single loci GWAS-like association analyses, highlighting the need to account for epistasis in association studies.
2020-10-05 | GSE145607 | GEO
Project description:To investigate the role of the hypothalamus in complex traits, we generated ATAC-seq, RNA-seq, and Promoter Focused Capture C to gain insight into the gene regulatory arcitecture contacting promoters in an embryonic stem cell dervived model of hypothalamic neuron differentiation
2021-10-01 | GSE152090 | GEO