Comprehensive Analyses of 723 Transcriptomes Enhance GWAS Biological Interpretation and Genomic Prediction for Complex Traits in Cattle
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ABSTRACT:
ORGANISM(S): Bos taurus
PROVIDER: GSE128075 | GEO | 2020/04/30
REPOSITORIES: GEO
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Project description:Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes-notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10-3.
| S-EPMC5871013 | biostudies-literature
Project description:Comprehensive Analyses of 723 Transcriptomes Enhance GWAS Biological Interpretation and Genomic Prediction for Complex Traits in Cattle
| PRJNA526257 | ENA
Project description:In this study, we generated whole genome bisulfite sequencing data of 19 samples for 13 tissues in Holstein cattle. We analyzed the variations of DNA methylation among tissues. In this study, we generated whole genome bisulfite sequencing data of 6 samples for 5 tissues in Hereford cattle. We analyzed the variations of DNA methylation among tissues.
2020-04-30 | GSE147087 | GEO
Project description:We present a comprehensive toolkit for post-processing, visualization and advanced analysis of GWAS results. In the spirit of comparable tools for gene-expression analysis, we attempt to unify and simplify several procedures that are essential for the interpretation of GWAS results. This includes the generation of advanced Manhattan and regional association plots including rare variant display as well as novel interaction network analysis tools for the investigation of systems-biology aspects. Our package supports virtually all model organisms and represents the first cohesive implementation of such tools for the popular language R. Previous software of that range is dispersed over a wide range of platforms and mostly not adaptable for custom work pipelines. We demonstrate the utility of this package by providing an example workflow on a publicly available dataset.
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Project description:As a key epigenetic modification, DNA methylation is essential for normal development by regulating processes like gene expression, genomic imprinting, and suppression of repetitive elements. However, DNA methylation in the cattle genome is not well understood. Here we presented the first single-base-resolution maps of DNA methylation in 10 diversely somatic tissues harvested from the sequenced Hereford cow L1 Dominette 01449 and her relatives using reduced representation bisulphite sequencing (RRBS). In total, we observed 1,868,049 high accuracy cytosines that located in the CG enriched regions. Similar to the methylation patterning in other species, the CG context was predominant methylated. Widespread differences were identified between the methylation patterns of CG and non-CG contexts. They were distributed differentially among the genomic features, including the genic regions, CpG islands, and repetitive sequences. Autocorrelation analysis among adjacent residues illustrated that methylation level of CGs were highly correlated in a region. In contrast, weak or no correlation was found among non-CGs or between CGs and non-CGs. The distinct distribution and low correlation of CG and non-CG methylation suggested that non-CG methylation may be independent from CG methylation and may be mediated by different mechanisms. We also detected 798 tissue-specific differentially methylated cytosines (tDMC) and 131 tissue-specific differentially methylated CpG islands. Combined analysis with the RNA-seq data, we discovered several non-CGs in tDMCs also highly correlated with gene expression, which implied the potential function of non-CG methylation in somatic cells in addition to pluripotent cells. In summary, we showed that non-CGs exist in bovine tissues and some of them were correlated with tissue-specific functions. This study provided essential information for the cytosine methylation patterning in bovine somatic tissues.
2017-02-14 | GSE86323 | GEO
Project description:As a key epigenetic modification, DNA methylation is essential for normal development by regulating processes like gene expression, genomic imprinting, and suppression of repetitive elements. However, DNA methylation in the cattle genome is not well understood. Here we presented the first single-base-resolution maps of DNA methylation in 10 diversely somatic tissues harvested from the sequenced Hereford cow L1 Dominette 01449 and her relatives using reduced representation bisulphite sequencing (RRBS). In total, we observed 1,868,049 high accuracy cytosines that located in the CG enriched regions. Similar to the methylation patterning in other species, the CG context was predominant methylated. Widespread differences were identified between the methylation patterns of CG and non-CG contexts. They were distributed differentially among the genomic features, including the genic regions, CpG islands, and repetitive sequences. Autocorrelation analysis among adjacent residues illustrated that methylation level of CGs were highly correlated in a region. In contrast, weak or no correlation was found among non-CGs or between CGs and non-CGs. The distinct distribution and low correlation of CG and non-CG methylation suggested that non-CG methylation may be independent from CG methylation and may be mediated by different mechanisms. We also detected 798 tissue-specific differentially methylated cytosines (tDMC) and 131 tissue-specific differentially methylated CpG islands. Combined analysis with the RNA-seq data, we discovered several non-CGs in tDMCs also highly correlated with gene expression, which implied the potential function of non-CG methylation in somatic cells in addition to pluripotent cells. In summary, we showed that non-CGs exist in bovine tissues and some of them were correlated with tissue-specific functions. This study provided essential information for the cytosine methylation patterning in bovine somatic tissues.
2017-02-14 | GSE76346 | GEO
Project description:Expression QTL (eQTL) detection has emerged as an important tool for unraveling the relationship between genetic risk factors and disease or clinical phenotypes. Most studies are predicated on the assumption that only a single causal variant explains the association signal in each interval. This greatly simplifies the statistical modeling, but is liable to biases in scenarios where multiple local causal-variants are responsible. Here, our primary goal was to address the prevalence of secondary cis-eQTL signals regulating peripheral blood gene expression locally, utilizing two large human cohort studies, each >2500 samples with accompanying whole genome genotypes. The CAGE (Consortium for the Architecture of Gene Expression) dataset is a compendium of Illumina microarray studies, and the Framingham Heart Study is a two-generation Affymetrix dataset. We also describe Bayesian colocalization analysis of the extent of sharing of cis-eQTL detected in both studies as well as with the BIOS RNAseq dataset. Stepwise conditional modeling demonstrates that multiple eQTL signals are present for ∼40% of over 3500 eGenes in both microarray datasets, and that the number of loci with additional signals reduces by approximately two-thirds with each conditioning step. Although <20% of the peak signals across platforms fine map to the same credible interval, the colocalization analysis finds that as many as 50-60% of the primary eQTL are actually shared. Subsequently, colocalization of eQTL signals with GWAS hits detected 1349 genes whose expression in peripheral blood is associated with 591 human phenotype traits or diseases, including enrichment for genes with regulatory functions. At least 10%, and possibly as many as 40%, of eQTL-trait colocalized signals are due to nonprimary cis-eQTL peaks, but just one-quarter of these colocalization signals replicated across the gene expression datasets. Our results are provided as a web-based resource for visualization of multi-site regulation of gene expression and its association with human complex traits and disease states.
| S-EPMC6614888 | biostudies-literature
Project description:We investigated miRNA expression in Holstein dairy cow of mammary gland with different producing quality milk using high-throughput sequence and qRT-PCR techniques. miRNA libraries were constructed from mammary gland tissues taken from a high producing quality milk and a low producing quality milk Holstein dairy cow, the small RNA digitalization analysis based on HiSeq high-throughput sequencing takes the SBS-sequencing by synthesis.The libraries included 4732 miRNAs. A total of 124 miRNAs in the high producing quality milk mammary gland showed significant differences in expression compared to low producing quality milk mammary gland (P<0.05). Conclusion: Our study provides a broad view of the bovine mammary gland small RNA expression profile characteristics. Differences in types and expression levels of miRNAs were observed between high producing quality milk and a low producing quality milk Holstein dairy cow
2016-12-31 | GSE57991 | GEO
Project description:We evaluated liver transcriptome throughout gestation and early lactation of purebred and crossbred beef cows (Angus, Hereford and their F1 crossbreeds, CR), grazing high or low herbage allowances (HA) of native grasslands (4 and 2.5 kg DM/kg BW annual mean; n = 16) using an Agilent 4x44k bovine array. A total of 4,661 transcripts were affected by days (272 M-bM-^IM-% 2.5-fold difference, FDR M-bM-^IM-$ 0.10) and 47 pathways were altered during winter gestation (-165 to -15 days relative to calving, d). Gluconeogenesis and fatty acid oxidation pathways were substantially upregulated, while cell growth, DNA replication and transcription pathways were downregulated (FDR M-bM-^IM-$ 0.25). We observed only small changes in the liver transcriptome during the early lactation period (+15 to +60 d). A total of 225 genes were differentially expressed (47 M-bM-^IM-% 2-fold difference, FDR M-bM-^IM-$ 0.10) between HA. The majority of those were related to glucose and pyruvate metabolism and were upregulated in high HA, reflecting their better metabolic status. Two genes were upregulated in CR cows, but 148 transcripts (74 M-bM-^IM-% 2-fold change difference, FDR M-bM-^IM-$ 0.10) were affected by the HA and cow genotype interaction. The transcriptional changes observed indicates a complex and previously unrecognized adaptive program in beef cow liver. We report novel candidate genes, metabolic pathways, and regulatory mechanisms, which can be used as targets of future studies. Complete randomized block design with two spatial replications and a factorial arrangement of herbage allowance (HA) and cow genotype (CG). Herbage allowance treatments represented 4 and 2.5 kg DM/kg BW of annual mean (HI and LO, respectively). Four purebred (PU M-bM-^@M-^S Hereford, H and Angus, A) and four crossbred (CR - F1, HA and AH) multiparous pregnant cows (5 to 6 year-old), were evaluated per treatment (HI-CR, HI-PU, LO-CR, and LO-PU) throughout the gestation and lactation period (-165 to +60 days relative to parturition, days). Cows belonged to or were descendants of experimental animals generated as part of a diallel crossbreeding experiment carried out for 10 years at the Experimental Station and were assigned to the same forage allowance (HI or LO) since May 2007 and gestated and lactated one calf every year from 2007 to 2009.
2014-03-07 | E-GEOD-52085 | biostudies-arrayexpress
Project description:BackgroundCombining the results of within-population genome-wide association studies (GWAS) based on whole-genome sequences into a single meta-analysis (MA) is an accurate and powerful method for identifying variants associated with complex traits. As part of the H2020 BovReg project, we performed sequence-level MA for beef production traits. Five partners from France, Switzerland, Germany, and Canada contributed summary statistics from sequence-based GWAS conducted with 54,782 animals from 15 purebred or crossbred populations. We combined the summary statistics for four growth, nine morphology, and 15 carcass traits into 16 MA, using both fixed effects and z-score methods.ResultsThe fixed-effects method was generally more informative to provide indication on potentially causal variants, although we combined substantially different traits in each MA. In comparison with within-population GWAS, this approach highlighted (i) a larger number of quantitative trait loci (QTL), (ii) QTL more frequently located in genomic regions known for their effects on growth and meat/carcass traits, (iii) a smaller number of genomic variants within the QTL, and (iv) candidate variants that were more frequently located in genes. MA pinpointed variants in genes, including MSTN, LCORL, and PLAG1 that have been previously associated with morphology and carcass traits. We also identified dozens of other variants located in genes associated with growth and carcass traits, or with a function that may be related to meat production (e.g., HS6ST1, HERC2, WDR75, COL3A1, SLIT2, MED28, and ANKAR). Some of these variants overlapped with expression or splicing QTL reported in the cattle Genotype-Tissue Expression atlas (CattleGTEx) and could therefore regulate gene expression.ConclusionsBy identifying candidate genes and potential causal variants associated with beef production traits in cattle, MA demonstrates great potential for investigating the biological mechanisms underlying these traits. As a complement to within-population GWAS, this approach can provide deeper insights into the genetic architecture of complex traits in beef cattle.
| S-EPMC10568825 | biostudies-literature