Multi-environment fitness landscapes of a tRNA gene.

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  • Author(s): Li C;Li C;Li C; Zhang J; Zhang J
  • Source:
    Nature ecology & evolution [Nat Ecol Evol] 2018 Jun; Vol. 2 (6), pp. 1025-1032. Date of Electronic Publication: 2018 Apr 23.
  • Publication Type:
    Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.
  • Language:
    English
  • Additional Information
    • Source:
      Publisher: Springer Nature Country of Publication: England NLM ID: 101698577 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2397-334X (Electronic) Linking ISSN: 2397334X NLM ISO Abbreviation: Nat Ecol Evol Subsets: MEDLINE
    • Publication Information:
      Original Publication: [London] : Springer Nature
    • Subject Terms:
      Genetic Fitness* ; Genotype*; RNA, Transfer/*genetics ; Saccharomyces cerevisiae/*genetics; Environment ; Gene-Environment Interaction ; High-Throughput Nucleotide Sequencing ; RNA, Transfer/metabolism ; Saccharomyces cerevisiae/metabolism
    • Abstract:
      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 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. Epistasis-by-environment interaction 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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    • Grant Information:
      R01 GM103232 United States GM NIGMS NIH HHS
    • Accession Number:
      9014-25-9 (RNA, Transfer)
    • Publication Date:
      Date Created: 20180425 Date Completed: 20190522 Latest Revision: 20190522
    • Publication Date:
      20231215
    • Accession Number:
      PMC5966336
    • Accession Number:
      10.1038/s41559-018-0549-8
    • Accession Number:
      29686238