April 5, 2018

BISTRO - Li Guan

4:00 PM

2036 Palmer Commons

BISTRO is restricted to U-M Bioinformatics Graduate Program students and faculty.

"Identification of trans-eQTLs in human skeletal muscle biopsies from Finnish participants"


Skeletal muscle represents approximately 40% of the weight of a lean body, and thus constitutes the largest organ in non-obese humans. Many diseases, e.g. type 2 diabetes, cancer cachexia and sepsis, affect skeletal muscle and the fluctuation of gene expression in muscle may reflect the progression or contribute to the etiology of such diseases. Here we identify trans-acting genetic variants (variants that work across chromosomes) that regulate protein coding or lincRNA gene expression using human skeletal muscle biopsies from 301 Finnish participants. Trans-eQTLs may have broad effects on the transcriptome and important phenotypic consequences.

At 10% FDR (pvalue = 2.97×10-10), we identified 256 variant-gene pairs, which included 21 distinct loci (pairwise SNP LD r2 < 0.2) and 26 unique genes (trans-eGenes). When comparing our results with those of the GTEx consortium, we identified 2 of the 9 trans-eGenes found in GTEx using 361 skeletal muscle samples. Our data replicated the trio (rs6511291-ZNF100-QSOX2) identified in GTEx, where rs6511291 was associated in cis with ZNF100, and in trans with QSOX2 and additionally found rs6511291 regulated FHAD1 in trans. To concentrate on variants with potential cis effects we restricted our trans analysis to the set of cis-eVariants (top variant per cis-eGene at 5% FDR), and identified 6 additional trans-eGenes (10% FDR, pvalue =3.20×10-9).

The present study confirmed and extended trans-eQTLs reported in GTEx. To increase power we plan to perform a trans-eQTL meta-analysis using skeletal muscle samples from the FUSION and GTEx projects. The results will advance our understanding of genetic regulation in human skeletal muscle and likely provide insight into the biological mechanisms through which the genetic variants exert their effects.