| Literature DB >> 29195078 |
Aravind Subramanian1, Rajiv Narayan1, Steven M Corsello2, David D Peck1, Ted E Natoli1, Xiaodong Lu1, Joshua Gould1, John F Davis1, Andrew A Tubelli1, Jacob K Asiedu1, David L Lahr1, Jodi E Hirschman1, Zihan Liu1, Melanie Donahue1, Bina Julian1, Mariya Khan1, David Wadden1, Ian C Smith1, Daniel Lam1, Arthur Liberzon1, Courtney Toder1, Mukta Bagul1, Marek Orzechowski1, Oana M Enache1, Federica Piccioni1, Sarah A Johnson1, Nicholas J Lyons1, Alice H Berger2, Alykhan F Shamji1, Angela N Brooks2, Anita Vrcic1, Corey Flynn1, Jacqueline Rosains1, David Y Takeda2, Roger Hu1, Desiree Davison1, Justin Lamb1, Kristin Ardlie1, Larson Hogstrom1, Peyton Greenside1, Nathanael S Gray3, Paul A Clemons1, Serena Silver1, Xiaoyun Wu1, Wen-Ning Zhao4, Willis Read-Button1, Xiaohua Wu1, Stephen J Haggarty4, Lucienne V Ronco1, Jesse S Boehm1, Stuart L Schreiber5, John G Doench1, Joshua A Bittker1, David E Root1, Bang Wong1, Todd R Golub6.
Abstract
We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs, and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io.Entities:
Keywords: Functional genomics; chemical biology; gene expression profiling
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Year: 2017 PMID： 29195078 PMCID： PMC5990023 DOI： 10.1016/j.cell.2017.10.049
Source DB: PubMed Journal: Cell ISSN： 0092-8674 Impact factor: 41.582