Gorham, J. | bioRxiv Science

bioRxiv2018

Sex differences in gene expression in response to ischemia in the human myocardium

Abstract and KeywordsO_ST_ABSBackgroundC_ST_ABSSex differences exist in the prevalence, presentation, and outcomes of ischemic heart disease. Females have higher risk of heart failure post myocardial infarction relative to males and the female sex is an independent risk factor for hospital and operative mortality after cardiac surgery. However, the mechanisms underlying this sexual dimorphism remain unclear. We examined sex differences in human myocardial gene expression in response to ischemia.\n\nMethodsLeft ventricular biopsies from 68 male and 46 female patients undergoing aortic valve replacement surgery were obtained at baseline and after a median 74 minutes of cold cardioplegic arrest/ischemia and respective transcriptomes were quantified by RNA-Seq. Sex-specific responses to ischemia were quantified by differential gene expression, expression quantitative trait loci (eQTL) and pathway and functional analysis. Cell-type enrichment analysis. was used to obtain an estimate of the identity and relative proportions of different cell types present in each sample.\n\nResultsA sex-specific response to ischemia was observed for 271 genes. Functional annotation analysis revealed sex-specific modulation of the oxytocin signaling pathway and common pathway of fibrin clot formation. The eQTL analysis identified variant-by-sex interaction eQTLs at baseline and post-ischemia, indicative of sex differences in the genotypic effects on gene expression, and cell-type enrichment analysis showed sex-bias in proportion of specific cell types.\n\nConclusionIn response to myocardial ischemia, the human left ventricle demonstrates changes in gene expression that differ between the sexes. These differences provide insight into the sexual dimorphism of ischemic heart disease and may aid in the development of sex-specific therapies that reduce myocardial injury.

genomics↗

bioRxiv2017

Robust identification of deletions in exome and genome sequence data based on clustering of Mendelian errors

Multiple tools have been developed to identify copy number variants (CNVs) from whole exome (WES) and whole genome sequencing (WGS) data. Current tools such as XHMM for WES and CNVnator for WGS identify CNVs based on changes in read depth. For WGS, other methods to identify CNVs include utilizing discordant read pairs and split reads and genome-wide local assembly with tools such as Lumpy and SvABA, respectively. Here, we introduce a new method to identify deletion CNVs from WES and WGS trio data based on the clustering of Mendelian errors (MEs). Using our Mendelian Error Method (MEM), we identified 127 deletions (inherited and de novo) in 2,601 WES trios from the Pediatric Cardiac Genomics Consortium, with a validation rate of 88% by digital droplet PCR. MEM identified additional de novo deletions compared to XHMM, and also identified sample switches, DNA contamination, a significant enrichment of 15q11.2 deletions compared to controls and eight cases of uniparental disomy. We applied MEM to WGS data from the Genome In A Bottle Ashkenazi trio and identified deletions with 97% specificity. MEM provides a robust, computationally inexpensive method for identifying deletions, and an orthogonal approach for verifying deletions called by other tools.

genetics↗