| Literature DB >> 25954003 |
Manuel A Rivas1, Matti Pirinen2, Donald F Conrad3, Monkol Lek4, Emily K Tsang5, Konrad J Karczewski4, Julian B Maller4, Kimberly R Kukurba6, David S DeLuca7, Menachem Fromer8, Pedro G Ferreira9, Kevin S Smith6, Rui Zhang10, Fengmei Zhao4, Eric Banks7, Ryan Poplin7, Douglas M Ruderfer11, Shaun M Purcell12, Taru Tukiainen4, Eric V Minikel4, Peter D Stenson13, David N Cooper13, Katharine H Huang7, Timothy J Sullivan7, Jared Nedzel7, Carlos D Bustamante10, Jin Billy Li10, Mark J Daly4, Roderic Guigo14, Peter Donnelly15, Kristin Ardlie7, Michael Sammeth16, Emmanouil T Dermitzakis9, Mark I McCarthy17, Stephen B Montgomery6, Tuuli Lappalainen18, Daniel G MacArthur19.
Abstract
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.Entities:
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Year: 2015 PMID： 25954003 PMCID： PMC4537935 DOI： 10.1126/science.1261877
Source DB: PubMed Journal: Science ISSN： 0036-8075 Impact factor: 47.728