4.8 Article

Effect of predicted protein-truncating genetic variants on the human transcriptome

Journal

SCIENCE
Volume 348, Issue 6235, Pages 666-669

Publisher

AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.1261877

Keywords

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Funding

  1. National Institutes of Health [NIGMS R01GM104371, NIMH R01MH101814, R01MH090941, U01HG007593, R01MH101810]
  2. Academy of Finland [257654]
  3. Hewlett-Packard Stanford Graduate Fellowship
  4. Natural Science and Engineering Research Council of Canada
  5. National Defense Science and Engineering Graduate Fellowship (NDSEG) from the United States Department of Defense (DoD)
  6. European Research Council
  7. Swiss National Science Foundation
  8. Louis-Jeantet Foundation
  9. Wellcome Trust [095552/Z/11/Z, 090532/Z/09/Z, 098381]
  10. University of Oxford
  11. Common Fund of the Office of the Director of NIH
  12. NCI/SAIC-Frederick, Inc. (SAIC-F) [X10S172]
  13. University of Geneva [MH090941]
  14. University of Chicago [MH090951, MH090937]
  15. University of North Carolina-Chapel Hill [MH090936]
  16. Harvard University [MH090948]
  17. [HHSN268201000029C]
  18. [10ST1035]
  19. [DA006227]
  20. Academy of Finland (AKA) [257654, 257654] Funding Source: Academy of Finland (AKA)
  21. Biotechnology and Biological Sciences Research Council [BBS/E/I/00001942] Funding Source: researchfish
  22. BBSRC [BBS/E/I/00001942] Funding Source: UKRI

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Accurate prediction of the functional effect of genetic variation is critical for clinical genome interpretation. We systematically characterized the transcriptome effects of protein-truncating variants, a class of variants expected to have profound effects on gene function, using data from the Genotype-Tissue Expression (GTEx) and Geuvadis projects. We quantitated tissue-specific and positional effects on nonsense-mediated transcript decay and present an improved predictive model for this decay. We directly measured the effect of variants both proximal and distal to splice junctions. Furthermore, we found that robustness to heterozygous gene inactivation is not due to dosage compensation. Our results illustrate the value of transcriptome data in the functional interpretation of genetic variants.

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