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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory Press
2019
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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. |
format | Online Article Text |
id | pubmed-6442382 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Cold Spring Harbor Laboratory Press |
record_format | MEDLINE/PubMed |
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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