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Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactions
BACKGROUND: Synthetic lethal genetic interactions among proteins have been widely used to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions is still unclear. RESULTS: In this study, we demonstrated that yeast synt...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3113237/ https://www.ncbi.nlm.nih.gov/pubmed/21586150 http://dx.doi.org/10.1186/1752-0509-5-73 |
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author | Li, Bo Cao, Weiguo Zhou, Jizhong Luo, Feng |
author_facet | Li, Bo Cao, Weiguo Zhou, Jizhong Luo, Feng |
author_sort | Li, Bo |
collection | PubMed |
description | BACKGROUND: Synthetic lethal genetic interactions among proteins have been widely used to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions is still unclear. RESULTS: In this study, we demonstrated that yeast synthetic lethal genetic interactions can be explained by the genetic interactions between domains of those proteins. The domain genetic interactions rarely overlap with the domain physical interactions from iPfam database and provide a complementary view about domain relationships. Moreover, we found that domains in multidomain yeast proteins contribute to their genetic interactions differently. The domain genetic interactions help more precisely define the function related to the synthetic lethal genetic interactions, and then help understand how domains contribute to different functionalities of multidomain proteins. Using the probabilities of domain genetic interactions, we were able to predict novel yeast synthetic lethal genetic interactions. Furthermore, we had also identified novel compensatory pathways from the predicted synthetic lethal genetic interactions. CONCLUSION: The identification of domain genetic interactions helps the understanding of originality of functional relationship in SLGIs at domain level. Our study significantly improved the understanding of yeast mulitdomain proteins, the synthetic lethal genetic interactions and the functional relationships between proteins and pathways. |
format | Online Article Text |
id | pubmed-3113237 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-31132372011-06-14 Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactions Li, Bo Cao, Weiguo Zhou, Jizhong Luo, Feng BMC Syst Biol Research Article BACKGROUND: Synthetic lethal genetic interactions among proteins have been widely used to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions is still unclear. RESULTS: In this study, we demonstrated that yeast synthetic lethal genetic interactions can be explained by the genetic interactions between domains of those proteins. The domain genetic interactions rarely overlap with the domain physical interactions from iPfam database and provide a complementary view about domain relationships. Moreover, we found that domains in multidomain yeast proteins contribute to their genetic interactions differently. The domain genetic interactions help more precisely define the function related to the synthetic lethal genetic interactions, and then help understand how domains contribute to different functionalities of multidomain proteins. Using the probabilities of domain genetic interactions, we were able to predict novel yeast synthetic lethal genetic interactions. Furthermore, we had also identified novel compensatory pathways from the predicted synthetic lethal genetic interactions. CONCLUSION: The identification of domain genetic interactions helps the understanding of originality of functional relationship in SLGIs at domain level. Our study significantly improved the understanding of yeast mulitdomain proteins, the synthetic lethal genetic interactions and the functional relationships between proteins and pathways. BioMed Central 2011-05-17 /pmc/articles/PMC3113237/ /pubmed/21586150 http://dx.doi.org/10.1186/1752-0509-5-73 Text en Copyright ©2011 Li et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Li, Bo Cao, Weiguo Zhou, Jizhong Luo, Feng Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactions |
title | Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactions |
title_full | Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactions |
title_fullStr | Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactions |
title_full_unstemmed | Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactions |
title_short | Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactions |
title_sort | understanding and predicting synthetic lethal genetic interactions in saccharomyces cerevisiae using domain genetic interactions |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3113237/ https://www.ncbi.nlm.nih.gov/pubmed/21586150 http://dx.doi.org/10.1186/1752-0509-5-73 |
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