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

著者: Manuel A. Rivas, Matti Pirinen, Donald F. Conrad, Monkol Lek, Emily K. Tsang, Konrad J. Karczewski, Julian Maller, Kimberly R. Kukurba, David S. DeLuca, Menachem Fromer, Pedro G. Ferreira, Kevin S. Smith, Rui Zhang, Fengmei Zhao, Eric Banks, Ryan Poplin, Douglas M. Ruderfer, Shaun Purcell, Taru Tukiainen, Eric Vallabh Minikel, Peter D. Stenson, D.N. Cooper, Katharine H. Huang, Timothy J. Sullivan, Jared L. Nedzel, Carlos D. Bustamante, Jin Billy Li, Mark J. Daly, Roderic Guigó, Peter Donnelly, Kristin Ardlie, Michael Sammeth, Emmanouil T. Dermitzakis, Mark I. McCarthy, Stephen B. Montgomery, Tuuli Lappalainen, Daniel G. MacArthur, Ayellet V. Segrè, Taylor Young, Ellen Gelfand, Casandra A. Trowbridge, Lucas D. Ward, Pouya Kheradpour, Benjamin Iriarte, Yan Meng, Cameron D. Palmer, Tõnu Esko, Wendy Winckler, Joel N. Hirschhorn, Manolis Kellis, Gad Getz, Andrey A. Shablin, Gen Li, Yi‐Hui Zhou, Andrew B. Nobel, Ivan Rusyn, Fred A. Wright, Alexis Battle, Sara Mostafavi, Marta Melé, Ferrán Reverter, Jakob M. Goldmann, Daphne Koller, Eric R. Gamazon, Hae Kyung Im, Anuar Konkashbaev, Dan L. Nicolae, Nancy J. Cox, Timothe Flutre, Xiaoquan Wen, Matthew Stephens, Jonathan K. Pritchard, Zhidong Tu, Bin Zhang, Tao Huang, Quan Long, Luan Lin, Jialiang Yang, Jun Zhu, Jun S. Liu, Amanda Brown, Bernadette Mestichelli, Denee Tidwell, Edmund Lo, Mike Salvatore, Saboor Shad, Jeffrey A. Thomas, John T. Lonsdale, Roswell Christopher Choi, Ellen Karasik, Kimberly Ramsey, Michael T. Moser, Barbara A. Foster, Bryan M. Gillard, John Syron, Johnelle Fleming, Harold I. Magazine, Rick Hasz, Gary Walters, Jason Bridge, Mark Miklos, Susan Sullivan, Laura K. Barker, Heather M. Traino, Magboeba Mosavel, Laura A. Siminoff, Dana R. Valley, Daniel C. Rohrer, Scott Jewel, Philip A. Branton, Leslie H. Sobin, Mary E. Barcus, Liqun Qi, Pushpa Hariharan, Shenpei Wu, David E. Tabor, Charles Shive, Anna M. Smith, Stephen A. Buia, Anita H. Undale, Karna Robinson, Nancy Roche, Kimberly M. Valentino, Angela Britton, Robin Burges, Debra Bradbury, Kenneth W. Hambright, John Seleski, Greg E. Korzeniewski, Kenyon Erickson, Yvonne Marcus, Jorge Tejada, Mehran Taherian, Chunrong Lu, Barnaby E. Robles, Margaret J. Basile, Deborah C. Mash, Simona Volpi, Jeffery P. Struewing, Gary F. Temple, Joy T Boyer, Deborah Colantuoni, Roger Little, Susan E. Koester, Latarsha J. Carithers, Helen M. Moore, Ping Guan, Carolyn C. Compton, Sherilyn J. Sawyer, Joanne P. Demchok, Jimmie B. Vaught, Chana A. Rabiner, Nicole C. Lockhart, Marc R. Friedländer, Peter A.C. ’t Hoen, Jean Monlong, Mar Gonzàlez-Porta, Natalja Kurbatova, Thasso Griebel, Matthias Barann, Thomas Wieland, Liliana Greger, Maarten van Iterson, Jonas Carlsson Almlöf, Paolo Ribeca, Irina Pulyakhina, Daniela Esser, Thomas Giger, Andrew Tikhonov, Marc Sultan, Gabrielle Bertier, Esther Lizano, Henk P.J. Buermans, Ismaël Padioleau, Thomas Schwarzmayr, Olof Karlberg, Halit Ongen, Helena Kilpinen, Sergi Beltrán, Marta Gut, Katja Kahlem, Vyacheslav Amstislavskiy, Oliver Stegle, Paul Flicek, Tim M. Strom, Hans Lehrach, Stefan Schreiber, Ralf Sudbrak, Ángel Carracedo, Stylianos E. Antonarakis, Robert Häsler, Ann‐Christine Syvänen, Gert‐Jan B. van Ommen, Alvis Brāzma, Thomas Meitinger, Philip Rosenstiel, Marta Gut, Xavier Estivill - Science 2015 被引用: 345

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.