Integrative QTL analysis of gene expression and chromatin accessibility identifies multi-tissue patterns of genetic regulation (RNA-seq)
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE140872 | GEO | 2020/01/01
REPOSITORIES: GEO
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Project description:Gene transcription profiles across tissues are largely defined by the activity of regulatory elements, most of which correspond to regions of accessible chromatin. Regulatory element activity is in turn modulated by genetic variation, resulting in variable transcription rates across individuals. The interplay of these factors, however, is poorly understood. We characterize expression and chromatin state dynamics across three tissues—liver, lung, and kidney—in 47 strains of the Collaborative Cross (CC) mouse population, examining the regulation of these dynamics by expression quantitative trait loci (eQTL) and chromatin QTL (cQTL). QTL whose allelic effects were consistent across tissues were detected for 1,101 genes and 133 chromatin regions. Also detected were eQTL and cQTL whose allelic effects differed across tissues. Leveraging overlapping measurements of gene expression and chromatin accessibility on the same mice from multiple tissues, we used mediation analysis to identify chromatin and gene expression intermediates of eQTL effects. This analysis demonstrates the complexity of transcriptional and chromatin dynamics and their regulation over multiple tissues, as well as the value of the CC and related genetic resource populations for identifying specific regulatory mechanisms within cells and tissues.
2020-01-01 | GSE140871 | GEO
Project description:The integration of the results of QTL fine-mapping with microarray expression data offers a promising tool for understanding the genetic mechanisms influencing complex traits as fatty acid composition in pigs. The expression level of each probe may be treated as a quantitative trait and the marker genotypes used to map loci with regulatory effect on the gene expression level (eQTL) According to our previous linkage results, we carry out an eQTL scan focused on chromosomal regions showing tissue-consistent effects on fatty acids with Longissimus dorsi gene expression data in order to detect potentional candidate genes underlying the QTL previously detected.
2013-11-22 | GSE52626 | GEO
Project description:The integration of the results of QTL fine-mapping with microarray expression data offers a promising tool for understanding the genetic mechanisms influencing complex traits as fatty acid composition in pigs. The expression level of each probe may be treated as a quantitative trait and the marker genotypes used to map loci with regulatory effect on the gene expression level (eQTL) According to our previous linkage results, we carry out an eQTL scan focused on chromosomal regions showing tissue-consistent effects on fatty acids with Longissimus dorsi gene expression data in order to detect potentional candidate genes underlying the QTL previously detected. 102 IberianxLandrace backcross pigs were selected for RNA extraction and hybridization on Affymetrix microarrays. An eQTL scan was carried out with the data of 470 probes of the microarray taking into account they were related with fatty acid metabolism
2013-11-22 | E-GEOD-52626 | biostudies-arrayexpress
Project description:Genome-wide association studies (GWAS) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium (LD) makes it challenging to discern causal variants. Computational finemapping prioritized thousands of credible variants, ~98% of which lie within poorly characterized non-coding regions. To functionally validate their regulatory effects, we performed a massively parallel reporter assay (MPRA) on 5,173 finemapped schizophrenia GWAS variants in primary human neural progenitors (HNPs). We identified 440 variants with allelic regulatory effects (MPRA-positive variants), with 72% of GWAS loci containing at least one MPRA-positive variant. Transcription factor binding had modest predictive power for predicting the allelic activity of MPRA-positive variants, while GWAS association, finemap posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit eQTL signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. MPRA-positive variants differed from eQTLs, as they were more frequently located in distal neuronal enhancers. Therefore, we leveraged neuronal 3D chromatin architecture to identify 273 genes that physically interact with MPRA-positive variants. These genes annotated by chromatin interactome displayed higher mutational constraints and regulatory complexity than genes annotated by eQTLs, recapitulating a recent finding that eQTL- and GWAS-detected variants map to genes with different properties. Finally, we propose a model in which allelic activity of multiple variants within a GWAS locus can be aggregated to predict gene expression by taking chromatin contact frequency and accessibility into account. In conclusion, we demonstrate that MPRA can effectively identify functional regulatory variants and delineate previously unknown regulatory principles of schizophrenia.
2023-08-07 | GSE211045 | GEO
Project description:We used microarrays and a previously established linkage map to localize the genetic determinants of brain gene expression for a backcross family of lake whitefish species pairs (Coregonus sp.). Our goals were to elucidate the genomic distribution and sex-specificity of brain expression QTL (eQTL) and to determine the extent to which genes controlling transcriptional variation may underlie adaptive divergence in the recently evolved dwarf (limnetic) and normal (benthic) whitefish. We observed a sex-bias in transcriptional genetic architecture, with more eQTL observed in males, as well as divergence in genome location of eQTL between sexes. Hotspots of nonrandom aggregations of up to 32 eQTL in one location were observed. We identified candidate genes for species pair divergence involved with energetic metabolism, protein synthesis, and neural development based on co-localization of eQTL for these genes with eight previously identified adaptive phenotypic QTL and four previously identified outlier loci from a genome scan in natural populations. 88% of eQTL-phenotypic QTL co-localization involved growth rate and condition factor QTL, two traits central to adaptive divergence between whitefish species pairs. Hotspots co-localized with phenotypic QTL in several cases, revealing possible locations where master regulatory genes, such as a zinc finger protein in one case, control gene expression directly related to adaptive phenotypic divergence. We observed little evidence of co-localization of brain eQTL with behavioral QTL, which provides insight on the genes identified by behavioral QTL studies. These results extend to the transcriptome level previous work illustrating that selection has shaped recent parallel divergence between dwarf and normal lake whitefish species pairs and that metabolic, more than morphological differences appear to play a key role in this divergence. Keywords: eQTL mapping, gene expression, linkage mapping, adaptive radiation, Coregonus, microarrays
2008-09-01 | GSE12068 | GEO
Project description:In this study, early infection by F. graminearum was characterized in a doubled-haploid population derived from the cross of the moderately FHB resistant wheat genotypes Wuhan 1 and Nyubai. Three significant QTL were identified: 1AL was associated with reduced deoxynivalenol levels, and 4BS and 5A were associated with reduced F. graminearum levels at 2 days after infection. The early resistance alleles for 1AL and 4BS were inherited from Wuhan 1, and those for the 5A QTL were inherited from Nyubai. The LOD support interval for the 5A QTL was in the same region as FHB5, a QTL previously associated with field resistance to FHB. Cis and trans eQTL were identified using RNA sequencing data from infected head samples. In total, 240 cis eQTL and 17,401 trans eQTL were identified within LOD support intervals for the three QTL. Hotspots for trans eQTL were identified within LOD support intervals for the 1AL and 4BS QTL. Differential gene expression analysis revealed twenty genes with cis eQTL within one of the 3 QTL support intervals, that had higher expression associated with FHB early resistance, and 17 genes with higher expression associated with FHB early susceptibility. Among those, genes with a cis eQTL peak coinciding with QTL peaks were enriched in functions related to signaling and protein-protein interaction, including NBS-LRR, BAH, LRR/F-box and TPR domain-containing proteins. Several genes located within one of the three QTL support intervals also had a trans eQTL with a peak at the same position as QTL peaks on other chromosomes, suggesting interactions between the QTL.
2019-11-13 | GSE123548 | GEO
Project description:To fully comprehend how genetic variants influence phenotypes, we must understand the functions of the epigenome. To assess the degree to which genetic variants influence epigenome activity, we integrate epigenetic and genotypic data from lupus patient lymphoblastoid cell lines to identify variants that induce allelic imbalance in the magnitude of histone post-translational modifications, referred to herein as histone quantitative trait loci (hQTLs). We demonstrate that enhancer hQTLs are enriched on autoimmune disease risk haplotypes and disproportionately influence gene expression variability compared with non-hQTL variants in strong linkage disequilibrium. We show that the epigenome regulates HLA class II genes differently in individuals who carry HLA-DR3 or HLA-DR15 haplotypes, resulting in differential 3D chromatin conformation and gene expression. Finally, we identify significant expression QTL (eQTL) x hQTL interactions that reveal substructure within eQTL gene expression, suggesting potential implications for functional genomic studies that leverage eQTL data for subject selection and stratification.
2018-06-25 | GSE116193 | GEO
Project description:We used microarrays and a previously established linkage map to localize the genetic determinants of brain gene expression for a backcross family of lake whitefish species pairs (Coregonus sp.). Our goals were to elucidate the genomic distribution and sex-specificity of brain expression QTL (eQTL) and to determine the extent to which genes controlling transcriptional variation may underlie adaptive divergence in the recently evolved dwarf (limnetic) and normal (benthic) whitefish. We observed a sex-bias in transcriptional genetic architecture, with more eQTL observed in males, as well as divergence in genome location of eQTL between sexes. Hotspots of nonrandom aggregations of up to 32 eQTL in one location were observed. We identified candidate genes for species pair divergence involved with energetic metabolism, protein synthesis, and neural development based on co-localization of eQTL for these genes with eight previously identified adaptive phenotypic QTL and four previously identified outlier loci from a genome scan in natural populations. 88% of eQTL-phenotypic QTL co-localization involved growth rate and condition factor QTL, two traits central to adaptive divergence between whitefish species pairs. Hotspots co-localized with phenotypic QTL in several cases, revealing possible locations where master regulatory genes, such as a zinc finger protein in one case, control gene expression directly related to adaptive phenotypic divergence. We observed little evidence of co-localization of brain eQTL with behavioral QTL, which provides insight on the genes identified by behavioral QTL studies. These results extend to the transcriptome level previous work illustrating that selection has shaped recent parallel divergence between dwarf and normal lake whitefish species pairs and that metabolic, more than morphological differences appear to play a key role in this divergence. Keywords: eQTL mapping, gene expression, linkage mapping, adaptive radiation, Coregonus, microarrays The objective of this study was to elucidate the genomic distribution and sex-specificity of brain eQTL in dwarf and normal lake whitefish. Dissected brain tissue (250-350 mg) was sampled for 55 individuals from a hybrid x dwarf backcross mapping family. We used a loop design (YANG and SPEED 2002; CHURCHILL 2002) to maximize the number of sampled meioses. Each of 55 samples was technically replicated on two distinct slides, while performing dye swapping (Cy3 and Alexa) to estimate the dye intensity variation bias. After correcting for local background, raw intensity values were both log2 transformed and normalized using the regional LOWESS method implemented in the R/MANOVA software (KERR et al. 2000). We used a previously generated linkage map based on the same backcross individuals for which gene expression was measured. eQTL mapping was performed with QTL Cartographer.
2008-09-01 | E-GEOD-12068 | biostudies-arrayexpress
Project description:Grain weight is an important crop yield component; however, its underlying regulatory mechanisms are largely unknown. Here, we identify a grain-weight quantitative trait locus (QTL) encoding a new-type GNAT-like protein that harbors intrinsic histone acetyltransferase activity (OsglHAT1). Our genetic and molecular evidences pinpointed the QTL-OsglHAT1’s allelic variations to a 1.2-kilobase region upstream of the gene body, which is consistent with its function as a positive regulator of the traits. Elevated OsglHAT1 expression enhances grain weight and yield by enlarging spikelet hulls via increasing cell number and accelerating grain filling, and increases global acetylation levels of histone H4. OsglHAT1 localizes to the nucleus, where it likely functions through the regulation of transcription. Despite its positive agronomical effects on grain weight, yield and plant biomass, the rare allele elevating OsglHAT1 expression has so far escaped human selection. Our findings reveal the first example, to our knowledge, of a QTL for a yield component trait being due to a chromatin modifier that has the potential to improve crop high-yield breeding. Two replicates of Nipponbare as control, three replicates of GW6a-4.6 substitution lines and three replicates of OsglHAT1-OE transgenic lines.
2015-02-10 | E-GEOD-62554 | biostudies-arrayexpress
Project description:Abstract:Genetical genomics has been suggested and proven to be a powerful approach to study the genotype-phenotype gap. However, the relatively low power of these experiments (usually related to the high cost) has hindered fulfilment of its promise, especially for loci (QTL) of moderate effects. One strategy to overcome the issue is to use a targeted approach: to focus the experiment on one QTL of particular interest. It has two clear advantages: (i) It reduces the problem to a simple comparison between different genotypic groups at the QTL and (ii) it is a good starting point to investigate downstream effects of the QTL. In the present study, from 698 F2 birds used for QTL mapping, gene expression profiles of 24 (12 from each homozygote genotypes at the QTL) were investigated. The targeted QTL was located on chromosome 1 and affected initial pH of meat. The biological mechanisms controlling this trait can be similar to those affecting malignant hyperthermia or muscle fatigue in human. The gene expression study identified ten strong local signals (potentially cis-eQTL) which were markedly more significant compared to the rest of the genome. The differentially expressed genes all mapped to a region < 1 Mb, suggesting a remarkable reduction of the QTL interval compared to the linkage study. These results combined with analysis of downstream effect of the QTL (using gene network analysis) suggest that the QTL is controlling pH by governing oxidative stress. The eQTL results were reproducible with using as few as 4 arrays on pooled samples (with lower significance level). The results demonstrate that this cost effective approach is promising not only for characterization of a QTL also for studying its downstream effects. there are 24 samples from to different genotypes. Each group of genotype has 12 samples. The two groups are compared using a dye balanced design.
2014-05-02 | E-GEOD-47800 | biostudies-arrayexpress