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Integrating Computational Biology and Forward Genetics in Drosophila

Genetic screens are powerful methods for the discovery of gene–phenotype associations. However, a systems biology approach to genetics must leverage the massive amount of “omics” data to enhance the power and speed of functional gene discovery in vivo. Thus far, few computational methods for gene fu...

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Autores principales: Aerts, Stein, Vilain, Sven, Hu, Shu, Tranchevent, Leon-Charles, Barriot, Roland, Yan, Jiekun, Moreau, Yves, Hassan, Bassem A., Quan, Xiao-Jiang
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2628282/
https://www.ncbi.nlm.nih.gov/pubmed/19165344
http://dx.doi.org/10.1371/journal.pgen.1000351
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author Aerts, Stein
Vilain, Sven
Hu, Shu
Tranchevent, Leon-Charles
Barriot, Roland
Yan, Jiekun
Moreau, Yves
Hassan, Bassem A.
Quan, Xiao-Jiang
author_facet Aerts, Stein
Vilain, Sven
Hu, Shu
Tranchevent, Leon-Charles
Barriot, Roland
Yan, Jiekun
Moreau, Yves
Hassan, Bassem A.
Quan, Xiao-Jiang
author_sort Aerts, Stein
collection PubMed
description Genetic screens are powerful methods for the discovery of gene–phenotype associations. However, a systems biology approach to genetics must leverage the massive amount of “omics” data to enhance the power and speed of functional gene discovery in vivo. Thus far, few computational methods for gene function prediction have been rigorously tested for their performance on a genome-wide scale in vivo. In this work, we demonstrate that integrating genome-wide computational gene prioritization with large-scale genetic screening is a powerful tool for functional gene discovery. To discover genes involved in neural development in Drosophila, we extend our strategy for the prioritization of human candidate disease genes to functional prioritization in Drosophila. We then integrate this prioritization strategy with a large-scale genetic screen for interactors of the proneural transcription factor Atonal using genomic deficiencies and mutant and RNAi collections. Using the prioritized genes validated in our genetic screen, we describe a novel genetic interaction network for Atonal. Lastly, we prioritize the whole Drosophila genome and identify candidate gene associations for ten receptor-signaling pathways. This novel database of prioritized pathway candidates, as well as a web application for functional prioritization in Drosophila, called Endeavour-HighFly, and the Atonal network, are publicly available resources. A systems genetics approach that combines the power of computational predictions with in vivo genetic screens strongly enhances the process of gene function and gene–gene association discovery.
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spelling pubmed-26282822009-01-23 Integrating Computational Biology and Forward Genetics in Drosophila Aerts, Stein Vilain, Sven Hu, Shu Tranchevent, Leon-Charles Barriot, Roland Yan, Jiekun Moreau, Yves Hassan, Bassem A. Quan, Xiao-Jiang PLoS Genet Research Article Genetic screens are powerful methods for the discovery of gene–phenotype associations. However, a systems biology approach to genetics must leverage the massive amount of “omics” data to enhance the power and speed of functional gene discovery in vivo. Thus far, few computational methods for gene function prediction have been rigorously tested for their performance on a genome-wide scale in vivo. In this work, we demonstrate that integrating genome-wide computational gene prioritization with large-scale genetic screening is a powerful tool for functional gene discovery. To discover genes involved in neural development in Drosophila, we extend our strategy for the prioritization of human candidate disease genes to functional prioritization in Drosophila. We then integrate this prioritization strategy with a large-scale genetic screen for interactors of the proneural transcription factor Atonal using genomic deficiencies and mutant and RNAi collections. Using the prioritized genes validated in our genetic screen, we describe a novel genetic interaction network for Atonal. Lastly, we prioritize the whole Drosophila genome and identify candidate gene associations for ten receptor-signaling pathways. This novel database of prioritized pathway candidates, as well as a web application for functional prioritization in Drosophila, called Endeavour-HighFly, and the Atonal network, are publicly available resources. A systems genetics approach that combines the power of computational predictions with in vivo genetic screens strongly enhances the process of gene function and gene–gene association discovery. Public Library of Science 2009-01-23 /pmc/articles/PMC2628282/ /pubmed/19165344 http://dx.doi.org/10.1371/journal.pgen.1000351 Text en Aerts et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Aerts, Stein
Vilain, Sven
Hu, Shu
Tranchevent, Leon-Charles
Barriot, Roland
Yan, Jiekun
Moreau, Yves
Hassan, Bassem A.
Quan, Xiao-Jiang
Integrating Computational Biology and Forward Genetics in Drosophila
title Integrating Computational Biology and Forward Genetics in Drosophila
title_full Integrating Computational Biology and Forward Genetics in Drosophila
title_fullStr Integrating Computational Biology and Forward Genetics in Drosophila
title_full_unstemmed Integrating Computational Biology and Forward Genetics in Drosophila
title_short Integrating Computational Biology and Forward Genetics in Drosophila
title_sort integrating computational biology and forward genetics in drosophila
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2628282/
https://www.ncbi.nlm.nih.gov/pubmed/19165344
http://dx.doi.org/10.1371/journal.pgen.1000351
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