| Literature DB >> 26320097 |
Lizabeth A Perkins1, Laura Holderbaum1, Rong Tao1, Yanhui Hu1, Richelle Sopko1, Kim McCall2, Donghui Yang-Zhou1, Ian Flockhart1, Richard Binari3, Hye-Seok Shim1, Audrey Miller1, Amy Housden1, Marianna Foos1, Sakara Randkelv1, Colleen Kelley1, Pema Namgyal1, Christians Villalta3, Lu-Ping Liu4, Xia Jiang5, Qiao Huan-Huan5, Xia Wang5, Asao Fujiyama6, Atsushi Toyoda6, Kathleen Ayers7, Allison Blum8, Benjamin Czech9, Ralph Neumuller1, Dong Yan1, Amanda Cavallaro10, Karen Hibbard10, Don Hall10, Lynn Cooley7, Gregory J Hannon9, Ruth Lehmann8, Annette Parks11, Stephanie E Mohr1, Ryu Ueda6, Shu Kondo12, Jian-Quan Ni4, Norbert Perrimon13.
Abstract
To facilitate large-scale functional studies in Drosophila, the Drosophila Transgenic RNAi Project (TRiP) at Harvard Medical School (HMS) was established along with several goals: developing efficient vectors for RNAi that work in all tissues, generating a genome-scale collection of RNAi stocks with input from the community, distributing the lines as they are generated through existing stock centers, validating as many lines as possible using RT-qPCR and phenotypic analyses, and developing tools and web resources for identifying RNAi lines and retrieving existing information on their quality. With these goals in mind, here we describe in detail the various tools we developed and the status of the collection, which is currently composed of 11,491 lines and covering 71% of Drosophila genes. Data on the characterization of the lines either by RT-qPCR or phenotype is available on a dedicated website, the RNAi Stock Validation and Phenotypes Project (RSVP, http://www.flyrnai.org/RSVP.html), and stocks are available from three stock centers, the Bloomington Drosophila Stock Center (United States), National Institute of Genetics (Japan), and TsingHua Fly Center (China).Entities:
Keywords: Drosophila; RNAi; functional genomics; phenotypes; screens
Mesh:
Year: 2015 PMID: 26320097 PMCID: PMC4649654 DOI: 10.1534/genetics.115.180208
Source DB: PubMed Journal: Genetics ISSN: 0016-6731 Impact factor: 4.562