Abstract
Efforts to decipher the causal relationships between differences in gene regulation and corresponding differences in phenotype have been stymied by several basic technical challenges. Although detecting local, cis-eQTLs is now routine, trans-eQTLs, which are distant from the genes of origin, are far more difficult to find because millions of SNPs must currently be compared to thousands of transcripts. Here, we demonstrate an alternative approach: we looked for SNPs associated with the expression of many genes simultaneously and found that hundreds of trans-eQTLs each affect hundreds of transcripts in lymphoblastoid cell lines across three African populations. These trans-eQTLs target the same genes across the three populations and show the same direction of effect. We discovered that target transcripts of a high-confidence set of trans-eQTLs encode proteins that interact more frequently than expected by chance, are bound by the same transcription factors, and are enriched for pathway annotations indicative of roles in basic cell homeostasis. We thus demonstrate that our approach can uncover trans-acting transcriptional control circuits that affect co-regulated groups of genes: a key to understanding how cellular pathways and processes are orchestrated.
Original language | English (US) |
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Pages (from-to) | 581-591 |
Number of pages | 11 |
Journal | American journal of human genetics |
Volume | 100 |
Issue number | 4 |
DOIs | |
State | Published - Apr 6 2017 |
Funding
Computing resources at Yale were funded partly by NIH grants RR19895 and RR029676-01. B.B. was supported by a post-doctoral fellowship from the Swedish Research Council (grant 524-2012-6881).
Keywords
- cross phenotype meta analysis
- master regulator
- regulatory network
- trans-eQTL
- transcription
ASJC Scopus subject areas
- Genetics
- Genetics(clinical)