eLife (Jan 2021)
Phenotypic and molecular evolution across 10,000 generations in laboratory budding yeast populations
- Milo S Johnson,
- Shreyas Gopalakrishnan,
- Juhee Goyal,
- Megan E Dillingham,
- Christopher W Bakerlee,
- Parris T Humphrey,
- Tanush Jagdish,
- Elizabeth R Jerison,
- Katya Kosheleva,
- Katherine R Lawrence,
- Jiseon Min,
- Alief Moulana,
- Angela M Phillips,
- Julia C Piper,
- Ramya Purkanti,
- Artur Rego-Costa,
- Michael J McDonald,
- Alex N Nguyen Ba,
- Michael M Desai
Affiliations
- Milo S Johnson
- ORCiD
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; Quantitative Biology Initiative, Harvard University, Cambridge, United States; NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States
- Shreyas Gopalakrishnan
- ORCiD
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; Quantitative Biology Initiative, Harvard University, Cambridge, United States; NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States; Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States
- Juhee Goyal
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; John A Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, United States
- Megan E Dillingham
- Quantitative Biology Initiative, Harvard University, Cambridge, United States; Graduate Program in Systems, Synthetic, and Quantitative Biology, Harvard University, Cambridge, United States
- Christopher W Bakerlee
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; Quantitative Biology Initiative, Harvard University, Cambridge, United States; NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States; Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States
- Parris T Humphrey
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; Quantitative Biology Initiative, Harvard University, Cambridge, United States; NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States
- Tanush Jagdish
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; Quantitative Biology Initiative, Harvard University, Cambridge, United States; NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States; Graduate Program in Systems, Synthetic, and Quantitative Biology, Harvard University, Cambridge, United States
- Elizabeth R Jerison
- ORCiD
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; Department of Physics, Harvard University, Cambridge, United States; Department of Applied Physics, Stanford University, Stanford, United States
- Katya Kosheleva
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; Department of Physics, Harvard University, Cambridge, United States
- Katherine R Lawrence
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; Quantitative Biology Initiative, Harvard University, Cambridge, United States; NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States; Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
- Jiseon Min
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; Quantitative Biology Initiative, Harvard University, Cambridge, United States; NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States; Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States; John A Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, United States
- Alief Moulana
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States
- Angela M Phillips
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States
- Julia C Piper
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; AeroLabs, Aeronaut Brewing Co, Somerville, United States
- Ramya Purkanti
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; The Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
- Artur Rego-Costa
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States
- Michael J McDonald
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; School of Biological Sciences, Monash University, Victoria, Monash, Australia
- Alex N Nguyen Ba
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; Quantitative Biology Initiative, Harvard University, Cambridge, United States; NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States; Department of Physics, Harvard University, Cambridge, United States; Department of Cell and Systems Biology, University of Toronto, Toronto, Canada
- Michael M Desai
- ORCiD
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States; Quantitative Biology Initiative, Harvard University, Cambridge, United States; NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, United States; Department of Physics, Harvard University, Cambridge, United States
- DOI
- https://doi.org/10.7554/eLife.63910
- Journal volume & issue
-
Vol. 10
Abstract
Laboratory experimental evolution provides a window into the details of the evolutionary process. To investigate the consequences of long-term adaptation, we evolved 205 Saccharomyces cerevisiae populations (124 haploid and 81 diploid) for ~10,000 generations in three environments. We measured the dynamics of fitness changes over time, finding repeatable patterns of declining adaptability. Sequencing revealed that this phenotypic adaptation is coupled with a steady accumulation of mutations, widespread genetic parallelism, and historical contingency. In contrast to long-term evolution in E. coli, we do not observe long-term coexistence or populations with highly elevated mutation rates. We find that evolution in diploid populations involves both fixation of heterozygous mutations and frequent loss-of-heterozygosity events. Together, these results help distinguish aspects of evolutionary dynamics that are likely to be general features of adaptation across many systems from those that are specific to individual organisms and environmental conditions.
Keywords