FlyExpress 7: An Integrated Discovery Platform To Study Coexpressed Genes Using in Situ Hybridization Images in Drosophila. Issue 8 (1st August 2017)

• Record Type: Journal Article
• Authors: Kumar, Sudhir; Konikoff, Charlotte; Sanderford, Maxwell; Liu, Li; Newfeld, Stuart; Ye, Jieping; Kulathinal, Rob J
• Is Part Of: G3. Volume 7:Issue 8(2017)
• Page Start: 2791
• Page End: 2797
• Publication Date: 2017-08-01
• Subjects: dotplot -- embryonic expression patterns -- gene regulation -- image analysis -- intergenic regions; Genetics -- Research -- Periodicals; Genomics -- Periodicals; Genetics; Genomics; Genes; Genetics -- Research; Genomics; Electronic journals; Periodical; Periodicals; Fulltext; Internet Resources; Periodicals; 572.8
• DOI: 10.1534/g3.117.040345
• Languages: English
• ISSNs: 2160-1836

Abstract

Abstract: Gene expression patterns assayed across development can offer key clues about a gene's function and regulatory role. Drosophila melanogaster is ideal for such investigations as multiple individual and high-throughput efforts have captured the spatiotemporal patterns of thousands of embryonic expressed genes in the form of in situ images. FlyExpress (www.flyexpress.net ), a knowledgebase based on a massive and unique digital library of standardized images and a simple search engine to find coexpressed genes, was created to facilitate the analytical and visual mining of these patterns. Here, we introduce the next generation of FlyExpress resources to facilitate the integrative analysis of sequence data and spatiotemporal patterns of expression from images. FlyExpress 7 now includes over 100, 000 standardized in situ images and implements a more efficient, user-defined search algorithm to identify coexpressed genes via Genomewide Expression Maps (GEMs). Shared motifs found in the upstream 5′ regions of any pair of coexpressed genes can be visualized in an interactive dotplot. Additional webtools and link-outs to assist in the downstream validation of candidate motifs are also provided. Together, FlyExpress 7 represents our largest effort yet to accelerate discovery via the development and dispersal of new webtools that allow researchers to perform data-driven analyses of coexpression (image) and genomic (sequence) data.