Metazoans are the most complex life forms in which the complexity of body form is achieved by spatial and temporal patterns of gene expression and its regulation in the developing embryo. The Drosophila melanogaster has been a model system to study how this complexity arises by examining the gene expression patterns depicting the mRNA or protein localization of key genes in the developing embryo. Investigators exploring a specific set of genes or gene families are often interested in finding other genes with overlapping patterns of gene expression in order to elucidate developmental pathways. However, neither a biological database of these gene expression pattern images nor a computational framework exists (1) to find similar gene expression patterns, and (2) to access knowledge related to the known genetic interactions. Therefore, we propose to build a fruit-fly gene expression system (FlyExpress) for retrieval and visualization of spatial and temporal patterns of gene expression in Drosophila embryos and imaginal disks. The proposed bioinformatics framework will facilitate query for genes with similar expression patterns in the temporal, spatial, and organ specific contexts. In addition to text search based on biological attributes, we will develop a Basic Expression Search Tool visual-content query system to assist in the discovery of overlapping gene expression patterns (Fx-BEST). The Fx-BEST functionality will be analogous to that of BLAST search in molecular sequence analysis. We also plan to develop computational tools to generate organ and position specific gene expression pattern classes (Fx-Classify), where expression patterns showing significant overlap will be grouped in the same class. The resulting classification will allow expert investigators to use biological, developmental, and genetic attributes of these expression patterns to predict potentially new interactions among genes or members of developmental pathways. In addition, we plan to devise computational approaches to compare (in a manner similar to that done by developmental biologists) the expression pattern of a given gene in wild type and mutation backgrounds in order to infer the underlying genetic interactions (Fx-Interaction). This technique will be used to automatically generate all gene interactions constructed using the data curated in the Fx- Database. These interactions can be used to establish further hypotheses for testing in research laboratories. FlyExpress will be made freely accessible on the web (www.flyexpress.net). It will not only address the day-to-day needs of researchers, but will also provide a framework for further discovery using the existing knowledge (approximately 50,000 images and their attributes). Furthermore, the computational algorithms, statistical methods, and the bioinformatics technologies developed in this project will be useful and provide impetus for constructing similar frameworks for organizing gene expression pattern data from other model and non-model organisms. The proposed FlyExpress informatics system will directly facilitate basic and applied research in many areas of molecular biology crucial in human health research, including computational genomics, molecular genetics, developmental biology, genetics, and evolution. It is also likely to become a valuable teaching resource for undergraduate and graduate students at universities worldwide

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
1R01HG002516-01A1
Application #
6610139
Study Section
Genome Study Section (GNM)
Program Officer
Bonazzi, Vivien
Project Start
2003-07-11
Project End
2006-06-30
Budget Start
2003-07-11
Budget End
2004-06-30
Support Year
1
Fiscal Year
2003
Total Cost
$586,545
Indirect Cost
Name
Arizona State University-Tempe Campus
Department
Other Basic Sciences
Type
Schools of Arts and Sciences
DUNS #
943360412
City
Tempe
State
AZ
Country
United States
Zip Code
85287
Kumar, Sudhir; Konikoff, Charlotte; Sanderford, Maxwell et al. (2017) FlyExpress 7: An Integrated Discovery Platform To Study Coexpressed Genes Using in Situ Hybridization Images in Drosophila. G3 (Bethesda) 7:2791-2797
Stanley Jr, Craig E; Kulathinal, Rob J (2016) flyDIVaS: A Comparative Genomics Resource for Drosophila Divergence and Selection. G3 (Bethesda) 6:2355-63
Wisotzkey, Robert G; Quijano, Janine C; Stinchfield, Michael J et al. (2014) New gene evolution in the bonus-TIF1-?/TRIM33 family impacted the architecture of the vertebrate dorsal-ventral patterning network. Mol Biol Evol 31:2309-21
Montiel, Ivan; Konikoff, Charlotte; Braun, Bremen et al. (2014) myFX: a turn-key software for laboratory desktops to analyze spatial patterns of gene expression in Drosophila embryos. Bioinformatics 30:1319-21
Yuan, Lei; Pan, Cheng; Ji, Shuiwang et al. (2014) Automated annotation of developmental stages of Drosophila embryos in images containing spatial patterns of expression. Bioinformatics 30:266-73
Zhang, Wenlu; Feng, Daming; Li, Rongjian et al. (2013) A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis. BMC Bioinformatics 14:372
Shimmi, Osamu; Newfeld, Stuart J (2013) New insights into extracellular and post-translational regulation of TGF-? family signalling pathways. J Biochem 154:11-9
Sun, Qian; Muckatira, Sherin; Yuan, Lei et al. (2013) Image-level and group-level models for Drosophila gene expression pattern annotation. BMC Bioinformatics 14:350
Chen, Jianhui; Tang, Lei; Liu, Jun et al. (2013) A convex formulation for learning a shared predictive structure from multiple tasks. IEEE Trans Pattern Anal Mach Intell 35:1025-38
Wisotzkey, Robert G; Konikoff, Charlotte E; Newfeld, Stuart J (2012) Hippo pathway phylogenetics predicts monoubiquitylation of Salvador and Merlin/Nf2. PLoS One 7:e51599

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