Genome-wide associations between genetic and epigenetic variation influence mRNA expression and insulin secretion in human pancreatic islets.
Genome-wide associations between genetic and epigenetic variation influence mRNA expression and insulin secretion in human pancreatic islets.
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DOI：
10.1371/journal.pgen.1004735
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发表时间：
2014-11
期刊：
影响因子：
4.5
通讯作者：
Ling C
中科院分区：
文献类型：
--
作者：
Olsson AH;Volkov P;Bacos K;Dayeh T;Hall E;Nilsson EA;Ladenvall C;Rönn T;Ling C
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的发展。然而，以前的大多数研究都是独立地研究遗传和表观遗传机制，而缺乏研究它们在整个人类基因组中的相互作用。为了确定与表观基因组相互作用的遗传基因座，我们在人类胰岛中进行了第一次全基因组DNA甲基化数量性状基因座(MQTL)分析。我们将574,553个单核苷酸多态(SNPs)与捐献者胰岛中针对99%RefSeq基因的468,787个CpG位点的全基因组甲基化数据相关联。我们在顺式基因中鉴定出67,438对SNP-CpG，对应36,783个SNP(6.4%的测试SNPs)和11,735个CpG位点(2.5%的测试CPGS)，以及2,562个显著的SNP-CpG对，对应1,465个SNP(测试的0.3%)和383个CpG位点(0.08%的测试的CPGS)，经多次检测校正后显示出显著的相关性。这些包括已报道的糖尿病基因座，例如ADCY5、KCNJ11、HLA-DQA1、INS、PDX1和GRB10。显著cis-mQTL的CpG在基因体和CpG岛外过表达。后续分析进一步确定了与人类胰岛基因表达和胰岛素分泌相关的mQTL。因果推断检验(CIT)确定了SNP-CpG对，其中人类胰岛中的DNA甲基化是基因表达或胰岛素分泌的遗传关联的潜在中介。功能分析进一步证明，已确定的候选基因(GPX7、GSTT1和SNX19)直接影响胰腺β-细胞的增殖和凋亡等关键生物学过程。最后，我们发现22,773个(4.9%)CPGS的DNA甲基化与4,876个基因的mRNA表达直接相关，当CPGS位于转录起始点附近时，90%的相关性为负。我们的研究首次展示了全基因组遗传和表观遗传变异如何相互作用，影响人类的基因表达、胰岛功能和潜在的糖尿病风险。遗传学和表观遗传学的个体间差异影响生物过程和疾病易感性。然而，大多数研究都是独立地研究遗传和表观遗传机制，为了揭示影响疾病易感性的新机制，突出需要在全基因组范围内研究这些因素之间的相互作用。为了确定影响胰岛功能和潜在糖尿病的新的基因座，我们在人类胰岛进行了第一次全基因组甲基化数量性状基因座(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，4,504个独特基因中11,735个CpG基因的DNA甲基化受位于顺式基因(67,438个SNP-CpG对)的遗传因素调控。此外，重要的mQTL覆盖了以前报道的糖尿病基因座，包括KCNJ11、INS、HLA、PDX1和GRB10。我们还在人类胰岛中发现了与基因表达和胰岛素分泌相关的mQTL。通过执行因果关系推断测试(CIT)，我们确定了CPGS，其中DNA甲基化潜在地介导了基因表达和胰岛素分泌的遗传影响。我们的功能跟踪实验进一步证明，已识别的mQTL/基因(GPX7、GSTT1和SNX19)直接影响胰腺β细胞的功能。总之，我们的研究提供了基因组范围内遗传和表观遗传变异之间的详细关系图，这些变异影响人类胰岛的基因表达和胰岛素分泌。
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. 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.
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影响因子：
4.4
作者：
Bibikova, Marina;Barnes, Bret;Shen, Richard
通讯作者：
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影响因子：
30.8
作者：
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作者：
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DOI：
10.1073/pnas.0502470102
发表时间：
2006-01-24
影响因子：
11.1
作者：
Doi, A;Shono, T;Nanjo, K
通讯作者：
Nanjo, K
影响因子：
4.5
作者：
Dayeh T;Volkov P;Salö S;Hall E;Nilsson E;Olsson AH;Kirkpatrick CL;Wollheim CB;Eliasson L;Rönn T;Bacos K;Ling C
通讯作者：
Ling C