Experimental Evolution and Resequencing Analysis of Yeast

  • Celia Payen
  • Maitreya J. Dunham
Part of the Methods in Molecular Biology book series (MIMB, volume 1361)


Experimental evolution of microbes is a powerful tool to study adaptation to strong selection, the mechanism of evolution and the development of new traits. The development of high-throughput sequencing methods has given researchers a new ability to cheaply and easily identify mutations genome wide that are selected during the course of experimental evolution. Here we provide a protocol for conducting experimental evolution of yeast using chemostats, including fitness measurement and whole genome sequencing of evolved clones or populations collected during the experiment. Depending on the number of generations appropriate for the experiment, the number of samples tested and the sequencing platform, this protocol takes from 1 month to several months to be completed, with the possibility of processing several strains or mutants at once.

Key words

Yeast Chemostats Fitness Whole genome sequencing Nextera MiSeq 



Thanks to Emily Mitchell and Giang T. Ong for their protocols. This work was supported by grants R01 GM094306 and P41 GM103533 from the National Institute of General Medical Sciences from the National Institutes of Health, and National Science Foundation grant 1120425. MJD is a Rita Allen Foundation Scholar, and a Fellow in the Genetic Networks program at the Canadian Institute for Advanced Research.


  1. 1.
    Monod J (1950) La technique de culture continue, theorie et applications. Ann Inst Pasteur 79:390–410Google Scholar
  2. 2.
    Novick A, Szilard L (1950) Description of the chemostat. Science 112(2920):715–716CrossRefPubMedGoogle Scholar
  3. 3.
    Skelly DA et al (2013) Integrative phenomics reveals insight into the structure of phenotypic diversity in budding yeast. Genome Res 23(9):1496–1504PubMedCentralCrossRefPubMedGoogle Scholar
  4. 4.
    Dykhuizen DE, Hartl DL (1983) Selection in chemostats. Microbiol Rev 47(2):150–168PubMedCentralPubMedGoogle Scholar
  5. 5.
    Paquin C, Adams J (1983) Frequency of fixation of adaptive mutations is higher in evolving diploid than haploid yeast populations. Nature 302(5908):495–500CrossRefPubMedGoogle Scholar
  6. 6.
    Dunham MJ et al (2002) Characteristic genome rearrangements in experimental evolution of Saccharomyces cerevisiae. Proc Natl Acad Sci U S A 99(25):16144–16149PubMedCentralCrossRefPubMedGoogle Scholar
  7. 7.
    Gresham D et al (2008) The repertoire and dynamics of evolutionary adaptations to controlled nutrient-limited environments in yeast. PLoS Genet 4(12), e1000303PubMedCentralCrossRefPubMedGoogle Scholar
  8. 8.
    Payen C et al (2014) The dynamics of diverse segmental amplifications in populations of Saccharomyces cerevisiae adapting to strong selection. G3 (Bethesda) 4(3):399–409CrossRefGoogle Scholar
  9. 9.
    Gresham D et al (2010) Adaptation to diverse nitrogen-limited environments by deletion or extrachromosomal element formation of the GAP1 locus. Proc Natl Acad Sci U S A 107(43):18551–18556PubMedCentralCrossRefPubMedGoogle Scholar
  10. 10.
    Kvitek DJ, Sherlock G (2013) Whole genome, whole population sequencing reveals that loss of signaling networks is the major adaptive strategy in a constant environment. PLoS Genet 9(11), e1003972PubMedCentralCrossRefPubMedGoogle Scholar
  11. 11.
    Brown CJ, Todd KM, Rosenzweig RF (1998) Multiple duplications of yeast hexose transport genes in response to selection in a glucose-limited environment. Mol Biol Evol 15(8):931–942CrossRefPubMedGoogle Scholar
  12. 12.
    Wenger JW et al (2011) Hunger artists: yeast adapted to carbon limitation show trade-offs under carbon sufficiency. PLoS Genet 7(8), e1002202PubMedCentralCrossRefPubMedGoogle Scholar
  13. 13.
    Hong J, Gresham D (2014) Molecular specificity, convergence and constraint shape adaptive evolution in nutrient-poor environments. PLoS Genet 10(1), e1004041PubMedCentralCrossRefPubMedGoogle Scholar
  14. 14.
    Adams J, Paquin C, Oeller PW, Lee LW (1985) Physiological characterization of adaptive clones in evolving populations of the yeast, Saccharomyces cerevisiae. Genetics 110(2):173–185PubMedCentralPubMedGoogle Scholar
  15. 15.
    Zhang E, Ferenci T (1999) OmpF changes and the complexity of Escherichia coli adaptation to prolonged lactose limitation. FEMS Microbiol Lett 176(2):395–401CrossRefPubMedGoogle Scholar
  16. 16.
    Miller AW, Befort C, Kerr EO, Dunham MJ (2013) Design and use of multiplexed chemostat arrays. J Vis Exp (72):e50262Google Scholar
  17. 17.
    Ziv N, Brandt NJ, Gresham D (2013) The use of chemostats in microbial systems biology. J Vis Exp (80):e50168Google Scholar
  18. 18.
    Adey A et al (2010) Rapid, low-input, low-bias construction of shotgun fragment libraries by high-density in vitro transposition. Genome Biol 11(12):R119PubMedCentralCrossRefPubMedGoogle Scholar
  19. 19.
    Hoffman CS, Winston F (1987) A ten-minute DNA preparation from yeast efficiently releases autonomous plasmids for transformation of Escherichia coli. Gene 57(2-3):267–272CrossRefPubMedGoogle Scholar
  20. 20.
    Li H et al (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25(16):2078–2079PubMedCentralCrossRefPubMedGoogle Scholar
  21. 21.
    Alkan C et al (2009) Personalized copy number and segmental duplication maps using next-generation sequencing. Nat Genet 41(10):1061–1067PubMedCentralCrossRefPubMedGoogle Scholar
  22. 22.
    Karakoc E et al (2011) Detection of structural variants and indels within exome data. Nat Methods 9(2):176–178PubMedCentralCrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Genome SciencesUniversity of WashingtonSeattleUSA

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