Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed
- Peter Orchard
- Thomas W. Blackwell
- Linda Kachuri
- Peter J. Castaldi
- Michael H. Cho
- Stephanie A. Christenson
- Peter Durda
- Stacey Gabriel
- Craig P. Hersh
- Scott Huntsman
- Seungyong Hwang
- Roby Joehanes
- Mari Johnson
- Xingnan Li
- Honghuang Lin
- Ching-Ti Liu
- Yongmei Liu
- Angel C. Y. Mak
- Ani W. Manichaikul
- David T. Paik
- Aabida Saferali
- Joshua D. Smith
- Kent D. Taylor
- Russell P. Tracy
- Jiongming Wang
- Mingqiang Wang
- Joshua S. Weinstock
- Jeffrey Weiss
- Heather E. Wheeler
- Ying Zhou
- Sebastian Zöllner
- Joseph C. Wu
- Luisa Mestroni
- Sharon Graw
- Matthew R. G. Taylor
- Victor E. Ortega
- W. Craig Johnson
- Weiniu Gan
- Gonçalo Abecasis
- Deborah A. Nickerson
- Namrata Gupta
- Kristin Ardlie
- Prescott G. Woodruff
- Russell P. Bowler
- Deborah A. Meyers
- Alex Reiner
- Charles Kooperberg
- Elad Ziv
- Ramachandran S. Vasan
- Martin G. Larson
2026-07-16
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.