Whole-genome sequencing of a laboratory-evolved yeast strain
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Background: Experimental evolution of microbial populations provides a unique opportunity to study evolutionary adaptation in response to controlled selective pressures. However, until recently it has been difficult to identify the precise genetic changes underlying adaptation at a genome-wide scale. New DNA sequencing technologies now allow the genome of parental and evolved strains of microorganisms to be rapidly determined. Results: We sequenced >93.5% of the genome of a laboratory-evolved strain of the yeast Saccharomyces cerevisiae and its ancestor at >28× depth. Both single nucleotide polymorphisms and copy number amplifications were found, with specific gains over array-based methodologies previously used to analyze these genomes. Applying a segmentation algorithm to quantify structural changes, we determined the approximate genomic boundaries of a 5× gene amplification. These boundaries guided the recovery of breakpoint sequences, which provide insights into the nature of a complex genomic rearrangement. Conclusions: This study suggests that whole-genome sequencing can provide a rapid approach to uncover the genetic basis of evolutionary adaptations, with further applications in the study of laboratory selections and mutagenesis screens. In addition, we show how single-end, short read sequencing data can provide detailed information about structural rearrangements, and generate predictions about the genomic features and processes that underlie genome plasticity.
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Changes in enterobactin biosynthetic processes (ent genes) were observed in independent E. coli studies.
“Furthermore, changes in enterobactin biosynthetic processes (ent genes) were also observed in independent studies [84,85,91].”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [91]
In a recent study towards increased n-butanol tolerance in E. coli, a drastic increase in solvent tolerance was rapidly achieved by combining laboratory evolution and genome shuffling of the evolved clones.
“In a recent study towards increased n-butanol tolerance in E. coli, a drastic increase in solvent tolerance was rapidly achieved by combining laboratory evolution and genome shuffling of the evolved clones [91].”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [91]
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Selection in Variable Environments
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- Authors
- Araya, C. L., Payen, C., Dunham, M. J., & Fields, S.
- Affiliations
- University of Washington (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Fields, Stanley
- Venue
- BMC Genomics
- Published
- 2010-02-03
- Volume
- 11
- Issue
- 1
- Pages
- 88-88
- ISSN
- 1471-2164 (ISSN-L)
- PMC
- PMC2829512
- OpenAlex
- W2162383089
- Cited by
- 113
- References
- 37
- Citations by year
- 2026: 4 · 2025: 1 · 2024: 21 · 2023: 3 · 2022: 4 · 2021: 1 · 2020: 3 · 2019: 3 · 2018: 2 · 2017: 8 · 2016: 6 · 2015: 10 · 2014: 9 · 2013: 10 · 2012: 10
- FWCI
- 4.95
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMC Genomics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Keywords
- experimental evolution, Saccharomyces cerevisiae, single nucleotide polymorphisms, copy number amplification, gene amplification, genome rearrangement, genome plasticity, structural variants, mutagenesis screen
- MeSH terms
- Algorithms, DNA, Fungal, Saccharomyces cerevisiae, Genomic Library, Genome, Fungal, Point Mutation, Sequence Analysis, DNA, Gene Dosage, Evolution, Molecular, Polymorphism, Single Nucleotide, Chromosome Breakpoints
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