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Improved discovery of genetic interactions using CRISPRiSeq across multiple environments

Large-scale genetic interaction (GI) screens in yeast have been invaluable for our understanding of molecular systems biology and for characterizing novel gene function. Owing in part to the high costs and long experiment times required, a preponderance of GI data has been generated in a single envi...

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Autores principales: Jaffe, Mia, Dziulko, Adam, Smith, Justin D., St.Onge, Robert P., Levy, Sasha F., Sherlock, Gavin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6442382/
https://www.ncbi.nlm.nih.gov/pubmed/30782640
http://dx.doi.org/10.1101/gr.246603.118
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author Jaffe, Mia
Dziulko, Adam
Smith, Justin D.
St.Onge, Robert P.
Levy, Sasha F.
Sherlock, Gavin
author_facet Jaffe, Mia
Dziulko, Adam
Smith, Justin D.
St.Onge, Robert P.
Levy, Sasha F.
Sherlock, Gavin
author_sort Jaffe, Mia
collection PubMed
description Large-scale genetic interaction (GI) screens in yeast have been invaluable for our understanding of molecular systems biology and for characterizing novel gene function. Owing in part to the high costs and long experiment times required, a preponderance of GI data has been generated in a single environmental condition. However, an unknown fraction of GIs may be specific to other conditions. Here, we developed a pooled-growth CRISPRi-based sequencing assay for GIs, CRISPRiSeq, which increases throughput such that GIs can be easily assayed across multiple growth conditions. We assayed the fitness of approximately 17,000 strains encompassing approximately 7700 pairwise interactions in five conditions and found that the additional conditions increased the number of GIs detected nearly threefold over the number detected in rich media alone. In addition, we found that condition-specific GIs are prevalent and improved the power to functionally classify genes. Finally, we found new links during respiratory growth between members of the Ras nutrient–sensing pathway and both the COG complex and a gene of unknown function. Our results highlight the potential of conditional GI screens to improve our understanding of cellular genetic networks.
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spelling pubmed-64423822019-04-17 Improved discovery of genetic interactions using CRISPRiSeq across multiple environments Jaffe, Mia Dziulko, Adam Smith, Justin D. St.Onge, Robert P. Levy, Sasha F. Sherlock, Gavin Genome Res Method Large-scale genetic interaction (GI) screens in yeast have been invaluable for our understanding of molecular systems biology and for characterizing novel gene function. Owing in part to the high costs and long experiment times required, a preponderance of GI data has been generated in a single environmental condition. However, an unknown fraction of GIs may be specific to other conditions. Here, we developed a pooled-growth CRISPRi-based sequencing assay for GIs, CRISPRiSeq, which increases throughput such that GIs can be easily assayed across multiple growth conditions. We assayed the fitness of approximately 17,000 strains encompassing approximately 7700 pairwise interactions in five conditions and found that the additional conditions increased the number of GIs detected nearly threefold over the number detected in rich media alone. In addition, we found that condition-specific GIs are prevalent and improved the power to functionally classify genes. Finally, we found new links during respiratory growth between members of the Ras nutrient–sensing pathway and both the COG complex and a gene of unknown function. Our results highlight the potential of conditional GI screens to improve our understanding of cellular genetic networks. Cold Spring Harbor Laboratory Press 2019-04 /pmc/articles/PMC6442382/ /pubmed/30782640 http://dx.doi.org/10.1101/gr.246603.118 Text en © 2019 Jaffe et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by/4.0/ This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.
spellingShingle Method
Jaffe, Mia
Dziulko, Adam
Smith, Justin D.
St.Onge, Robert P.
Levy, Sasha F.
Sherlock, Gavin
Improved discovery of genetic interactions using CRISPRiSeq across multiple environments
title Improved discovery of genetic interactions using CRISPRiSeq across multiple environments
title_full Improved discovery of genetic interactions using CRISPRiSeq across multiple environments
title_fullStr Improved discovery of genetic interactions using CRISPRiSeq across multiple environments
title_full_unstemmed Improved discovery of genetic interactions using CRISPRiSeq across multiple environments
title_short Improved discovery of genetic interactions using CRISPRiSeq across multiple environments
title_sort improved discovery of genetic interactions using crispriseq across multiple environments
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6442382/
https://www.ncbi.nlm.nih.gov/pubmed/30782640
http://dx.doi.org/10.1101/gr.246603.118
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