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Multi-environment fitness landscapes of a tRNA gene

A fitness landscape (FL) describes the genotype-fitness relationship in a given environment. To explain and predict evolution, it is imperative to measure the FL in multiple environments because the natural environment changes frequently. Using a high-throughput method that combines precise gene rep...

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Detalles Bibliográficos
Autores principales: Li, Chuan, Zhang, Jianzhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5966336/
https://www.ncbi.nlm.nih.gov/pubmed/29686238
http://dx.doi.org/10.1038/s41559-018-0549-8
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author Li, Chuan
Zhang, Jianzhi
author_facet Li, Chuan
Zhang, Jianzhi
author_sort Li, Chuan
collection PubMed
description A fitness landscape (FL) describes the genotype-fitness relationship in a given environment. To explain and predict evolution, it is imperative to measure the FL in multiple environments because the natural environment changes frequently. Using a high-throughput method that combines precise gene replacement with next-generation sequencing, we determine the in vivo FL of a yeast tRNA gene comprising over 23,000 genotypes in four environments. Although genotype-by-environment interaction (G×E) is abundantly detected, its pattern is so simple that we can transform an existing FL to that in a new environment with fitness measures of only a few genotypes in the new environment. Under each environment, we observe prevalent, negatively biased epistasis between mutations (G×G). Epistasis-by-environment interaction (G×G×E) is also prevalent, but trends in epistasis difference between environments are predictable. Our study thus reveals simple rules underlying seemingly complex FLs, opening the door to understanding and predicting FLs in general.
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spelling pubmed-59663362018-10-23 Multi-environment fitness landscapes of a tRNA gene Li, Chuan Zhang, Jianzhi Nat Ecol Evol Article A fitness landscape (FL) describes the genotype-fitness relationship in a given environment. To explain and predict evolution, it is imperative to measure the FL in multiple environments because the natural environment changes frequently. Using a high-throughput method that combines precise gene replacement with next-generation sequencing, we determine the in vivo FL of a yeast tRNA gene comprising over 23,000 genotypes in four environments. Although genotype-by-environment interaction (G×E) is abundantly detected, its pattern is so simple that we can transform an existing FL to that in a new environment with fitness measures of only a few genotypes in the new environment. Under each environment, we observe prevalent, negatively biased epistasis between mutations (G×G). Epistasis-by-environment interaction (G×G×E) is also prevalent, but trends in epistasis difference between environments are predictable. Our study thus reveals simple rules underlying seemingly complex FLs, opening the door to understanding and predicting FLs in general. 2018-04-23 2018-06 /pmc/articles/PMC5966336/ /pubmed/29686238 http://dx.doi.org/10.1038/s41559-018-0549-8 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:https://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Li, Chuan
Zhang, Jianzhi
Multi-environment fitness landscapes of a tRNA gene
title Multi-environment fitness landscapes of a tRNA gene
title_full Multi-environment fitness landscapes of a tRNA gene
title_fullStr Multi-environment fitness landscapes of a tRNA gene
title_full_unstemmed Multi-environment fitness landscapes of a tRNA gene
title_short Multi-environment fitness landscapes of a tRNA gene
title_sort multi-environment fitness landscapes of a trna gene
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5966336/
https://www.ncbi.nlm.nih.gov/pubmed/29686238
http://dx.doi.org/10.1038/s41559-018-0549-8
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