Epigenomic variation atlas across human tissues and individuals in GTEx

摘要： 基因类型-组织表达计划(GTEx)正在扩大初级组织的可用性 研究遗传变异对基因表达的影响的样本 纸巾。然而，基因表达水平的个体间差异通常是由于 多个变种的联合作用，每个变种都可能影响不同调控的活性 区域以复杂的方式，也整合复杂的转录后事件。因此，要 直接评估序列变异对调控元件的影响，我们建议 对储存的GTEx生物样品进行系统的表观遗传修饰以增强 GTEx联盟已经提供并计划进行的基因表达变异分析。 目的1.我们将使用全基因组亚硫酸氢盐测序(WGBS)来分析DNA甲基化 在8个GTEx组织中的20个个体的基因组中所有28M CPGS的水平。我们将使用这些工具 识别不同细胞类型和不同个体的可变甲基化区域(VMR)，以 评估eQTL SNPs对邻近CPGS DNA甲基化水平的影响，并 识别等位基因特异性甲基化(ASM)区域及其组织特异性。目标2.我们将 系统分析同一8个组织中250个个体的DNA甲基化水平 选择的2M个区域的子集的混合选择亚硫酸氢盐测序(HSBS) 增强子相关、eQTL相关和个体间可变区。我们将使用这些 为了预测每个组织中的甲基化数量性状基因座(MeQTL)，将这些基因与GTEx联系起来 同一组织的表达QTL(EQTL)为相互作用提供机制假说 单个基因表达的变异，并发现没有单个eQTL的基因的meQTL 意义重大。目的3.我们将使用染色质免疫沉淀测序(CHIP-SEQ)来 6个GTEx脑中的组蛋白修饰基因H3K27ac 100个个体的样本，以识别与基因相关的增强子区域和 增强QTL。我们将把这些与在相同组织中发现的eQTL和使用 在增强子近端和eQTL近端CPGS上的HSBS为其生成机制模型 与基因变异相关的调控变化。我们将与GTEx密切合作 分析联盟将GTEx eQTL与我们预测的meQTL、ASM区域和 将调节区变异与基因表达变异和全基因组联系起来的增强QTL 关联研究以了解序列变异在组织特异性基因中的作用 调控、基因表达和人类疾病。

Abstract: The Genotype-Tissue Expression project (GTEx) is expanding the availability of primary tissue samples for studying the impact of genetic variation on gene expression across individuals and tissues. However, inter-individual variation in gene expression level can often result from the combined effects of multiple variants, each of which may affect the activity of different regulatory regions in complex ways, and also integrate complex post-transcriptional events. Thus, to directly assess the effect of sequence variants on regulatory elements, we propose to systematic profile epigenetic modifications on stored GTEx biospecimens to enhance the analysis of gene expression variation already available and planned by the GTEx consortium. Aim 1. We will use whole-genome bisulfite sequencing (WGBS) to profile DNA methylation levels for all 28M CpGs in the genome of 20 individuals in 8 GTEx tissues. We will use these to identify variable methylated regions (VMRs) across cell types and across individuals, to evaluate the effects of eQTL SNPs on DNA methylation levels of neighboring CpGs, and to recognize allele-specific methylation (ASM) regions and their tissue specificity. Aim 2. We will systematically profile DNA methylation levels across 250 individuals in the same 8 tissues using hybrid-selection bisulfite sequencing (HSBS) for a subset of 2M regions selected within enhancer-associated, eQTL-associated, and inter-individual variable regions. We will use these to predict methylation quantitative trait loci (meQTLs) in each tissue, relate these to GTEx expression QTLs (eQTLs) for the same tissues to provide mechanistic hypotheses for inter- individual gene expression variation, and to discover meQTLs for genes where no single eQTL is significant. Aim 3. We will use chromatin immunoprecipitation sequencing (ChIP-Seq) to profile enhancer- and promoter-associated histone modification H3K27ac in 6 GTEx brain samples across 100 individuals, to recognize genotype-associated enhancer regions and enhQTLs. We will relate these to eQTLs in the same tissues and meQTLs discovered using HSBS on enhancer-proximal and eQTL proximal CpGs to generate mechanistic models for regulatory changes associated with genotype variation. We will work closely with the GTEx Analysis Consortium to integrate GTEx eQTLs with our predicted meQTLs, ASM regions, and enhQTLs to relate regulatory region variation to gene expression variation and to genome-wide association studies to understand the role of sequence variation in tissue-specific gene regulation, gene expression, and human disease.