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Merging Absolute and Relative Quantitative PCR Data to Quantify STAT3 Splice Variant Transcripts
Published on: October 9, 2016
Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed
Peter Orchard1, Thomas W Blackwell2,3, Linda Kachuri4
1Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
None:
Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood (n = 6454) and lung (n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank-derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.
