Lymphocyte activation gene3 and coronary artery disease.

Purpose: Utilized Next-generation sequencing (NGS) to profile transcriptional differences between two populations, carriers (CC) of rs10846744 SNP associated with cardiovascular disease (CVD) and non-carriers (GG) who are disease free. Methods: Total RNA was isolated from three subjects homozygous for the rs10846744 reference (GG) allele and three subjects homozygous for the rs10846744 risk (CC) allele and then subjected to full transcriptome sequencing using the Perkin Elmer next gen sequencing platform (Perkin Elmer, Branford, CT). Bioinformatics was performed using Perkin Elmer GeneSifter software program. The data was adjusted by selecting total map reads, quality reads >20, log transformation, and using Benjamini Hochberg to correct for multiple testing. RNA targets of interest were validated by qRT–PCR using TaqMan assays and western blotting using standard methodologies. Results: Using Perkin Elmer''s Genesifter Analysis Edition Software, we mapped about 100 million sequence reads per sample to the human genome (build 37.2), normalized the raw read count by total mapped million reads and identified 937 upregulated and 587 downregulated transcripts in the EBV (Epstein Barr Virus)-transformed B lymphocyte cells isolated from 3 carriers of the risk (CC) allele and 3 non-carriers of the (GG) reference allele with BWA workflow. RNA-seq data confirmed differential expression of LAG3 and this was validated with qRT–PCR. Conclusions: Our study represents the first detailed analysis of differential LAG3 expression, contributing to CVD, with biologic replicates, generated by RNA-seq technology. Overall design: mRNA transcriptional profiles from EBV (Epstein Barr Virus)-transformed B lymphocyte cells, isolated from 3 carriers of the risk (CC) allele and 3 non-carriers of the (GG) reference allele, were generated by deep sequencing, in triplicate, using Illumina platform technology.

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Golden D, Kolmakova A, Sura S, Vella AT, Manichaikul A, Wang XQ, Bielinski SJ, Taylor KD, Chen YI, Rich SS, Rodriguez A