Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Parallel evolution of mutational fitness effects over 50,000 generations

View ORCID ProfileAnurag Limdi, View ORCID ProfileSiân V. Owen, View ORCID ProfileCristina M. Herren, View ORCID ProfileRichard E. Lenski, View ORCID ProfileMichael Baym
doi: https://doi.org/10.1101/2022.05.17.492023
Anurag Limdi
1Department of Biomedical Informatics and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA
2Molecules, Cells, and Organisms Graduate Program, Harvard University, Cambridge, Massachusetts 02138, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Anurag Limdi
Siân V. Owen
1Department of Biomedical Informatics and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Siân V. Owen
Cristina M. Herren
1Department of Biomedical Informatics and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA
3Harvard Data Science Initiative, Harvard University, Boston, Massachusetts 02115, USA
4Department of Marine and Environmental Sciences, Northeastern University, Boston, Massachusetts 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Cristina M. Herren
Richard E. Lenski
5Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan 48824, USA
6Ecology, Evolution, and Behavior Program, Michigan State University, East Lansing, Michigan 48824, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Richard E. Lenski
Michael Baym
1Department of Biomedical Informatics and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA
3Harvard Data Science Initiative, Harvard University, Boston, Massachusetts 02115, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Michael Baym
  • For correspondence: baym@hms.harvard.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Data/Code
  • Preview PDF
Loading

Abstract

As evolving populations accumulate mutations, the benefits and costs of subsequent mutations change. As fitness increases, the relative benefit of new mutations typically decreases. However, the question remains whether deleterious mutations tend to have larger or smaller costs as a population adapts; theory and experiments provide support for both conflicting hypotheses. To address this question, we compared the effects of insertion mutations in every gene in Escherichia coli between ancestral and 12 independently derived strains after 50,000 generations in a uniform environment. We found both increases and decreases in the fitness costs of mutations, leaving the overall distribution of effects largely unchanged. However, at the extreme, more genes became essential over evolution than vice versa. Both changes in fitness effects and essentiality evolved in parallel across the independent populations, and most changes were not explained by structural variation or altered gene expression. Thus, the macroscopic features of the local fitness landscape remained largely unchanged, even as access to particular evolutionary trajectories changed consistently during adaptation to the experimental environment.

One Sentence Summary Limdi et al. report parallel changes in the cost of mutations in replicate lineages of a decades-long E. coli evolution experiment.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Manuscript updated and revised, particularly title and introduction, to reflect broader scope of results

  • https://github.com/baymlab/2022_Limdi-TnSeq-LTEE

  • https://doi.org/10.5281/zenodo.6547536

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted March 07, 2023.
Download PDF

Supplementary Material

Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Parallel evolution of mutational fitness effects over 50,000 generations
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Parallel evolution of mutational fitness effects over 50,000 generations
Anurag Limdi, Siân V. Owen, Cristina M. Herren, Richard E. Lenski, Michael Baym
bioRxiv 2022.05.17.492023; doi: https://doi.org/10.1101/2022.05.17.492023
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Parallel evolution of mutational fitness effects over 50,000 generations
Anurag Limdi, Siân V. Owen, Cristina M. Herren, Richard E. Lenski, Michael Baym
bioRxiv 2022.05.17.492023; doi: https://doi.org/10.1101/2022.05.17.492023

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Evolutionary Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4654)
  • Biochemistry (10299)
  • Bioengineering (7614)
  • Bioinformatics (26189)
  • Biophysics (13445)
  • Cancer Biology (10620)
  • Cell Biology (15333)
  • Clinical Trials (138)
  • Developmental Biology (8452)
  • Ecology (12754)
  • Epidemiology (2067)
  • Evolutionary Biology (16763)
  • Genetics (11356)
  • Genomics (15400)
  • Immunology (10548)
  • Microbiology (25041)
  • Molecular Biology (10152)
  • Neuroscience (54095)
  • Paleontology (398)
  • Pathology (1655)
  • Pharmacology and Toxicology (2877)
  • Physiology (4314)
  • Plant Biology (9196)
  • Scientific Communication and Education (1579)
  • Synthetic Biology (2541)
  • Systems Biology (6752)
  • Zoology (1452)