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Am J Hum Genet. 2017 Apr 6;100(4):581-591. doi: 10.1016/j.ajhg.2017.02.004. Epub 2017 Mar 9.

Large-Scale trans-eQTLs Affect Hundreds of Transcripts and Mediate Patterns of Transcriptional Co-regulation.

Author information

1
Department of Neurology, Yale University School of Medicine, New Haven, CT 06520, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA.
2
Department of Neurology, Yale University School of Medicine, New Haven, CT 06520, USA.
3
Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Division of Genetics, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA.
4
Department of Computer Science, Yale University, New Haven, CT 06510, USA.
5
Institute for Genomics and Systems Biology The University of Chicago, Chicago, IL 60637, USA.
6
Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA; Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA.
7
Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute of Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
8
Department of Neurology, Yale University School of Medicine, New Haven, CT 06520, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA. Electronic address: cotsapas@broadinstitute.org.

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.

KEYWORDS:

cross phenotype meta analysis; master regulator; regulatory network; trans-eQTL; transcription

PMID:
28285767
PMCID:
PMC5384037
DOI:
10.1016/j.ajhg.2017.02.004
[Indexed for MEDLINE]
Free PMC Article

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