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Strategies for the multiplex mapping of genes to traits

Rewiring and optimization of metabolic networks to enable the production of commercially valuable chemicals is a central goal of metabolic engineering. This prospect is challenged by the complexity of metabolic networks, lack of complete knowledge of gene function(s), and the vast combinatorial geno...

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Detalles Bibliográficos
Autores principales: Garst, Andrew, Lynch, Michael, Evans, Ron, Gill, Ryan T
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842685/
https://www.ncbi.nlm.nih.gov/pubmed/24171944
http://dx.doi.org/10.1186/1475-2859-12-99
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author Garst, Andrew
Lynch, Michael
Evans, Ron
Gill, Ryan T
author_facet Garst, Andrew
Lynch, Michael
Evans, Ron
Gill, Ryan T
author_sort Garst, Andrew
collection PubMed
description Rewiring and optimization of metabolic networks to enable the production of commercially valuable chemicals is a central goal of metabolic engineering. This prospect is challenged by the complexity of metabolic networks, lack of complete knowledge of gene function(s), and the vast combinatorial genotype space that is available for exploration and optimization. Various approaches have thus been developed to aid in the efficient identification of genes that contribute to a variety of different phenotypes, allowing more rapid design and engineering of traits desired for industrial applications. This review will highlight recent technologies that have enhanced capabilities to map genotype-phenotype relationships on a genome wide scale and emphasize how such approaches enable more efficient design and engineering of complex phenotypes.
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spelling pubmed-38426852013-11-29 Strategies for the multiplex mapping of genes to traits Garst, Andrew Lynch, Michael Evans, Ron Gill, Ryan T Microb Cell Fact Review Rewiring and optimization of metabolic networks to enable the production of commercially valuable chemicals is a central goal of metabolic engineering. This prospect is challenged by the complexity of metabolic networks, lack of complete knowledge of gene function(s), and the vast combinatorial genotype space that is available for exploration and optimization. Various approaches have thus been developed to aid in the efficient identification of genes that contribute to a variety of different phenotypes, allowing more rapid design and engineering of traits desired for industrial applications. This review will highlight recent technologies that have enhanced capabilities to map genotype-phenotype relationships on a genome wide scale and emphasize how such approaches enable more efficient design and engineering of complex phenotypes. BioMed Central 2013-10-30 /pmc/articles/PMC3842685/ /pubmed/24171944 http://dx.doi.org/10.1186/1475-2859-12-99 Text en Copyright © 2013 Garst 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 Review
Garst, Andrew
Lynch, Michael
Evans, Ron
Gill, Ryan T
Strategies for the multiplex mapping of genes to traits
title Strategies for the multiplex mapping of genes to traits
title_full Strategies for the multiplex mapping of genes to traits
title_fullStr Strategies for the multiplex mapping of genes to traits
title_full_unstemmed Strategies for the multiplex mapping of genes to traits
title_short Strategies for the multiplex mapping of genes to traits
title_sort strategies for the multiplex mapping of genes to traits
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842685/
https://www.ncbi.nlm.nih.gov/pubmed/24171944
http://dx.doi.org/10.1186/1475-2859-12-99
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