Dataset Information

Integrative Multi-omic Analysis of Human Platelet eQTLs Reveals Alternative Start Site in Mitofusin 2.

ABSTRACT: Platelets play a central role in ischemic cardiovascular events. Cardiovascular disease (CVD) is a major cause of death worldwide. Numerous genome-wide association studies (GWASs) have identified loci associated with CVD risk. However, our understanding of how these variants contribute to disease is limited. Using data from the platelet RNA and expression 1 (PRAX1) study, we analyzed cis expression quantitative trait loci (eQTLs) in platelets from 154 normal human subjects. We confirmed these results in silico by performing allele-specific expression (ASE) analysis, which demonstrated that the allelic directionality of eQTLs and ASE patterns correlate significantly. Comparison of platelet eQTLs with data from the Genotype-Tissue Expression (GTEx) project revealed that a number of platelet eQTLs are platelet specific and that platelet eQTL peaks localize to the gene body at a higher rate than eQTLs from other tissues. Upon integration with data from previously published GWASs, we found that the trait-associated variant rs1474868 coincides with the eQTL peak for mitofusin 2 (MFN2). Additional experimental and computational analyses revealed that this eQTL is linked to an unannotated alternate MFN2 start site preferentially expressed in platelets. Integration of phenotype data from the PRAX1 study showed that MFN2 expression levels were significantly associated with platelet count. This study links the variant rs1474868 to a platelet-specific regulatory role for MFN2 and demonstrates the utility of integrating multi-omic data with eQTL analysis in disease-relevant tissues for interpreting GWAS results.

SUBMITTER: Simon LM

PROVIDER: S-EPMC4863560 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Integrative Multi-omic Analysis of Human Platelet eQTLs Reveals Alternative Start Site in Mitofusin 2.

Simon Lukas M LM Chen Edward S ES Edelstein Leonard C LC Kong Xianguo X Bhatlekar Seema S Rigoutsos Isidore I Bray Paul F PF Shaw Chad A CA

American journal of human genetics 20160428 5

Platelets play a central role in ischemic cardiovascular events. Cardiovascular disease (CVD) is a major cause of death worldwide. Numerous genome-wide association studies (GWASs) have identified loci associated with CVD risk. However, our understanding of how these variants contribute to disease is limited. Using data from the platelet RNA and expression 1 (PRAX1) study, we analyzed cis expression quantitative trait loci (eQTLs) in platelets from 154 normal human subjects. We confirmed these re ...[more]

PMID: 27132591

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Project description:BackgroundBreast cancer is a complex and heterogeneous disease with distinct subtypes and molecular profiles corresponding to different clinical outcomes. Mouse models of breast cancer are widely used, but their relevance in capturing the heterogeneity of human disease is unclear. Previous studies have shown the heterogeneity at the gene expression level for the MMTV-Myc model, but have only speculated on the underlying genetics.MethodsTumors from the microacinar, squamous, and EMT histological subtypes of the MMTV-Myc mouse model of breast cancer underwent whole genome sequencing. The genomic data obtained were then integrated with previously obtained matched sample gene expression data and extended to additional samples of each histological subtype, totaling 42 gene expression samples. High correlation was observed between genetic copy number events and resulting gene expression by both Spearman's rank correlation coefficient and the Kendall rank correlation coefficient. These same genetic events are conserved in humans and are indicative of poor overall survival by Kaplan-Meier analysis. A supervised machine learning algorithm trained on METABRIC gene expression data was used to predict the analogous human breast cancer intrinsic subtype from mouse gene expression data.ResultsHerein, we examine three common histological subtypes of the MMTV-Myc model through whole genome sequencing and have integrated these results with gene expression data. Significantly, key genomic alterations driving cell signaling pathways were well conserved within histological subtypes. Genomic changes included frequent, co-occurring mutations in KIT and RARA in the microacinar histological subtype as well as SCRIB mutations in the EMT subtype. EMT tumors additionally displayed strong KRAS activation signatures downstream of genetic activating events primarily ascribed to KRAS activating mutations, but also FGFR2 amplification. Analogous genetic events in human breast cancer showed stark decreases in overall survival. In further analyzing transcriptional heterogeneity of the MMTV-Myc model, we report a supervised machine learning model that classifies MMTV-Myc histological subtypes and other mouse models as being representative of different human intrinsic breast cancer subtypes.ConclusionsWe conclude the well-established MMTV-Myc mouse model presents further opportunities for investigation of human breast cancer heterogeneity.

Dataset Information

Integrative Multi-omic Analysis of Human Platelet eQTLs Reveals Alternative Start Site in Mitofusin 2.

Publications

Integrative Multi-omic Analysis of Human Platelet eQTLs Reveals Alternative Start Site in Mitofusin 2.

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