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Novel and concordant eQTLs from analysis of iPSC-derived megakaryocytes and platelets in the GeneticStudies of Atherosclerosis Risk (GeneSTAR) project. Kammers, Kai


Kai Kammers1, Margaret A Taub2, Benjamin Rodriguez4, Ingo Ruczinski2, Lisa R Yanek3, Andrew D Johnson4, Nauder Faraday3, Lewis C Becker3, Rasika A Mathias3. 1 Division of Biostatistics and Bioinformatics, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Johns Hopkins University School of Medicine, Baltimore, MD 2 Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 3 The GeneSTAR Research Program, Johns Hopkins University School of Medicine, Baltimore, MD 4 NHLBI Population Sciences Branch, The Framingham Heart Study, Framingham, MA GWAS studies have identified common variants associated with platelet aggregation, but because these variants are largely intronic/intergenic, their mechanistic link to platelet function is unclear. Additionally, extensive missing heritability may be resolved by integrating genetics and transcriptomics. To better understand the transcriptome signature and its genetic regulatory landscape in platelets and megakaryocytes (MKs), we performed expression-quantitative trait locus (eQTL) analyses of RNA sequencing (RNA-seq) data on both cell types in African American (AA) and European American (EA) subjects from the Genetic Studies of Atherosclerosis Risk (GeneSTAR) project. Using genotypes from the Illumina 1M GWAS array (1,003,451 SNPs), eQTL analyses were carried out stratified by ancestry and cell type, with a 1Mb window around each gene and adjusting for relevant covariates with the R package MatrixEQTL. Significance was defined as q-value < 0.05. Genes with median FPKM

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