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Genome-Wide Associations between Genetic and Epigenetic Variation Influence mRNA Expression and Insulin Secretion in Human Pancreatic Islets

机译:遗传和表观遗传变异之间的全基因组关联影响人胰岛中的mRNA表达和胰岛素分泌

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Genetic and epigenetic mechanisms may interact and together affect biological processes and disease development. However, most previous studies have investigated genetic and epigenetic mechanisms independently, and studies examining their interactions throughout the human genome are lacking. To identify genetic loci that interact with the epigenome, we performed the first genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human pancreatic islets. We related 574,553 single nucleotide polymorphisms (SNPs) with genome-wide DNA methylation data of 468,787 CpG sites targeting 99% of RefSeq genes in islets from 89 donors. We identified 67,438 SNP-CpG pairs in cis , corresponding to 36,783 SNPs (6.4% of tested SNPs) and 11,735 CpG sites (2.5% of tested CpGs), and 2,562 significant SNP-CpG pairs in trans , corresponding to 1,465 SNPs (0.3% of tested SNPs) and 383 CpG sites (0.08% of tested CpGs), showing significant associations after correction for multiple testing. These include reported diabetes loci, e.g. ADCY5 , KCNJ11 , HLA-DQA1, INS, PDX1 and GRB10 . CpGs of significant cis -mQTLs were overrepresented in the gene body and outside of CpG islands. Follow-up analyses further identified mQTLs associated with gene expression and insulin secretion in human islets. Causal inference test (CIT) identified SNP-CpG pairs where DNA methylation in human islets is the potential mediator of the genetic association with gene expression or insulin secretion. Functional analyses further demonstrated that identified candidate genes ( GPX7 , GSTT1 and SNX19 ) directly affect key biological processes such as proliferation and apoptosis in pancreatic β-cells. Finally, we found direct correlations between DNA methylation of 22,773 (4.9%) CpGs with mRNA expression of 4,876 genes, where 90% of the correlations were negative when CpGs were located in the region surrounding transcription start site. Our study demonstrates for the first time how genome-wide genetic and epigenetic variation interacts to influence gene expression, islet function and potential diabetes risk in humans. Author Summary Inter-individual variation in genetics and epigenetics affects biological processes and disease susceptibility. However, most studies have investigated genetic and epigenetic mechanisms independently and to uncover novel mechanisms affecting disease susceptibility there is a highlighted need to study interactions between these factors on a genome-wide scale. To identify novel loci affecting islet function and potentially diabetes, we performed the first genome-wide methylation quantitative trait locus (mQTL) analysis in human pancreatic islets including DNA methylation of 468,787 CpG sites located throughout the genome. Our results showed that DNA methylation of 11,735 CpGs in 4,504 unique genes is regulated by genetic factors located in cis (67,438 SNP-CpG pairs). Furthermore, significant mQTLs cover previously reported diabetes loci including KCNJ11 , INS , HLA , PDX1 and GRB10 . We also found mQTLs associated with gene expression and insulin secretion in human islets. By performing causality inference tests (CIT), we identified CpGs where DNA methylation potentially mediates the genetic impact on gene expression and insulin secretion. Our functional follow-up experiments further demonstrated that identified mQTLs/genes ( GPX7 , GSTT1 and SNX19 ) directly affect pancreatic β-cell function. Together, our study provides a detailed map of genome-wide associations between genetic and epigenetic variation, which affect gene expression and insulin secretion in human pancreatic islets.
机译:遗传和表观遗传机制可能相互作用并共同影响生物过程和疾病发展。然而,大多数先前的研究都独立地研究了遗传和表观遗传机制,并且缺乏研究它们在整个人类基因组中相互作用的研究。为了鉴定与表观基因组相互作用的遗传基因座,我们在人胰岛中进行了首次全基因组DNA甲基化定量性状基因座(mQTL)分析。我们将574,553个单核苷酸多态性(SNP)与468,787个CpG位点的全基因组DNA甲基化数据相关,这些位点靶向89个捐赠者的胰岛中RefSeq基因的99%。我们在顺式中鉴定出67,438个SNP-CpG对,对应于36,783个SNP(占被测SNP的6.4%)和11,735个CpG位点(占被测CpG的2.5%),以及2,562个反式的重要SNP-CpG对,相当于1,465个SNP(0.3%测试的SNPs)和383个CpG位点(占测试的CpGs的0.08%),在多次测试校正后显示出显着的关联。这些包括已报道的糖尿病基因座,例如ADCY5,KCNJ11,HLA-DQA1,INS,PDX1和GRB10。重要的顺式-mQTL的CpGs在基因体内和CpG岛的外部都被过度表达。后续分析进一步确定了与人类胰岛中基因表达和胰岛素分泌相关的mQTL。因果推理测试(CIT)确定了SNP-CpG对,其中人胰岛中的DNA甲基化是与基因表达或胰岛素分泌发生遗传关联的潜在媒介。功能分析进一步证明,已鉴定的候选基因(GPX7,GSTT1和SNX19)直接影响关键的生物学过程,例如胰腺β细胞的增殖和凋亡。最后,我们发现22,773(4.9%)CpG的DNA甲基化与4,876个基因的mRNA表达之间存在直接相关性,其中当CpG位于转录起始位点附近时,90%的相关性为负。我们的研究首次证明了全基因组遗传和表观遗传变异如何相互作用以影响人类的基因表达,胰岛功能和潜在的糖尿病风险。作者摘要遗传和表观遗传学之间的个体差异会影响生物过程和疾病易感性。但是,大多数研究已经独立研究了遗传和表观遗传机制,并且为了发现影响疾病易感性的新机制,迫切需要在全基因组范围内研究这些因素之间的相互作用。为了鉴定影响胰岛功能和潜在糖尿病的新基因座,我们在人胰岛中进行了首个全基因组范围的甲基化定量性状基因座(mQTL)分析,包括位于整个基因组的468,787个CpG位点的DNA甲基化。我们的结果表明,在4,504个独特基因中的11,735个CpG的DNA甲基化受顺式(67,438个SNP-CpG对)的遗传因子调控。此外,重要的mQTL涵盖了先前报道的糖尿病基因座,包括KCNJ11,INS,HLA,PDX1和GRB10。我们还发现了与人类胰岛中基因表达和胰岛素分泌相关的mQTL。通过执行因果推断测试(CIT),我们确定了DNA甲基化可能介导基因表达和胰岛素分泌的遗传影响的CpG。我们的功能性后续实验进一步证明,已鉴定的mQTL /基因(GPX7,GSTT1和SNX19)直接影响胰腺β细胞功能。总之,我们的研究提供了遗传和表观遗传变异之间全基因组关联的详细图谱,这些变异影响人类胰岛中的基因表达和胰岛素分泌。

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