Wyeth W. Wasserman
The Wasserman laboratory focuses on the creation, evaluation and application of computational methods for the analysis of genome sequences, with international strength in the study of cis-regulatory elements regulating gene expression. The lab creates widely used software and databases, performs applied analyses of genome sequences, and partners with diverse research teams on projects at the intersection of the computational and life sciences.
Genome Sequencing has disrupted health research. The lab has been developing computational methods and tools to allow researchers and clinicians to identify functional consequences of genetic variations within cis-regulatory elements such as transcription factor binding sites. The 1500 transcription factors (TFs) within the human genome perform a key role in determining the set of active genes within a specific cell, as well as the magnitude of activity. Defects within TFs are widely recognized to contribute to genetic disorders - such changes may block the formation of certain cell types. Alterations in the DNA sequences bound by these factors can contribute causally to phenotypes, but much work remains to develop the essential computational detection methods.
The lab studies gene regulation via multiple lines. First, the lab creates novel algorithms and software to predict interactions between TFs and DNA. The software incorporates diverse types of data to maximize prediction quality. Second, the lab collaborates internationally on the analysis of emerging data, such as an international FANTOM project to map regulatory sequence positions through the study of the 5’ end of RNA transcripts. Third, the lab engages in the applied analysis of genomes, in part to improve the delivery of information to clinicians. Such work is key to translating basic research advances into clinical impacts.
Computational biology is a critical need in an era of high-throughput methods. The lab’s trainees have done well, taking on positions at leading institutions.
MAJOR ACHIEVEMENTS & PUBLICATIONS
UBC Killam Teaching Prize, University of British Columbia - 2013
Basic Science Teaching Award, Department of Medical Genetics, UBC - 2011
Cheung WA, Ouellette BF, Wasserman WW. Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs). BMC Bioinformatics 13:249. (2012)
Shah SP, Roth A, Goya R, Oloumi A, Ha G, Zhao Y, Turashvili G, Ding J, Tse K, Haffari G, Bashashati A, Prentice LM, Khattra J, Burleigh A, Yap D, Bernard V, McPherson A, Shumansky K, Crisan A, Giuliany R, Heravi-Moussavi A, Rosner J, Lai D, Birol I, Varhol R, Tam A, Dhalla N, Zeng T, Ma K, Chan SK, Griffith M, Moradian A, Cheng SW, Morin GB, Watson P, Gelmon K, Chia S, Chin SF, Curtis C, Rueda OM, Pharoah PD, Damaraju S, Mackey J, Hoon K, Harkins T, Tadigotla V, Sigaroudinia M, Gascard P, Tlsty T, Costello JF, Meyer IM, Eaves CJ, Wasserman WW, Jones S, Huntsman D, Hirst M, Caldas C, Marra MA, Aparicio S. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 486(7403):395-9.(2012)
Yusuf D, Butland SL, Swanson MI, Bolotin E, Ticoll A, Cheung WA, Zhang XY, Dickman CT, Fulton DL, Lim JS, Schnabl JM, Ramos OH, Vasseur-Cognet M, de Leeuw CN, Simpson EM,... over 100 national and international scientists ..., Portales-Casamar E, Sladek FM, Bradley PH, Wasserman WW. The Transcription Factor Encyclopedia. Genome Biol. 13(3):R24. (2012)
Kwon AT, Chou AY, Arenillas DJ, Wasserman WW. Validation of skeletal muscle cis-regulatory module predictions reveals nucleotide composition bias in functional enhancers. PLoS Comput. Biol. 7(12):e1002256. (2011)
Portales-Casamar E, Swanson DJ, Liu L, de Leeuw CN, Banks KG, Ho Sui SJ, Fulton DL, Ali J, Amirabbasi M, Arenillas DJ, ......, Jones SJ, Holt RA, Goldowitz D, Wasserman WW, Simpson EM. A regulatory toolbox of MiniPromoters to drive selective expression in the brain. Proc. Natl. Acad. Sci. U.S.A. 07(38):16589-94. (2010)