Pervasive Genetic Hitchhiking and Clonal Interference in 40 Evolving Yeast Populations

The dynamics of adaptation determine which mutations fix in a population, and hence how reproducible evolution will be. This is central to understanding the spectra of mutations recovered in the evolution of antibiotic resistance, the response of pathogens to immune selection, and the dynamics of cancer progression. In laboratory evolution experiments, demonstrably beneficial mutations are found repeatedly, but are often accompanied by other mutations with no obvious benefit. Here we use whole-genome whole-population sequencing to examine the dynamics of genome sequence evolution at high temporal resolution in 40 replicate Saccharomyces cerevisiae populations growing in rich medium for 1,000 generations. We find pervasive genetic hitchhiking: multiple mutations arise and move synchronously through the population as mutational ‘cohorts’. Multiple clonal cohorts are often present simultaneously, competing with each other in the same population. Our results show that patterns of sequence evolution are driven by a balance between these chance effects of hitchhiking and interference, which increase stochastic variation in evolutionary outcomes, and the deterministic action of selection on individual mutations, which favours parallel evolutionary solutions in replicate populations.

[1]  K. Atwood,et al.  Periodic selection in Escherichia coli. , 1951, Proceedings of the National Academy of Sciences of the United States of America.

[2]  D. Hartl,et al.  A primer of population genetics , 1981 .

[3]  C. Paquin,et al.  Frequency of fixation of adaptive mutations is higher in evolving diploid than haploid yeast populations , 1983, Nature.

[4]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[5]  J. Bull,et al.  Short-sighted evolution and the virulence of pathogenic microorganisms. , 1994, Trends in microbiology.

[6]  R. Lenski,et al.  Diminishing returns from mutation supply rate in asexual populations. , 1999, Science.

[7]  J. Bull,et al.  Different trajectories of parallel evolution during viral adaptation. , 1999, Science.

[8]  J. Coffin,et al.  The solitary wave of asexual evolution , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[9]  R. Lenski,et al.  The fate of competing beneficial mutations in an asexual population , 2004, Genetica.

[10]  David W Hall,et al.  Spontaneous Mutations in Diploid Saccharomyces cerevisiae , 2004, Genetics.

[11]  Nigel F. Delaney,et al.  Darwinian Evolution Can Follow Only Very Few Mutational Paths to Fitter Proteins , 2006, Science.

[12]  Dominique Schneider,et al.  Tests of parallel molecular evolution in a long-term experiment with Escherichia coli. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Jonathan P. Bollback,et al.  Clonal interference is alleviated by high mutation rates in large populations. , 2007, Molecular biology and evolution.

[14]  Isabel Gordo,et al.  Adaptive Mutations in Bacteria: High Rate and Small Effects , 2007, Science.

[15]  Michael M. Desai,et al.  The Speed of Evolution and Maintenance of Variation in Asexual Populations , 2007, Current Biology.

[16]  Michael M. Desai,et al.  Beneficial Mutation–Selection Balance and the Effect of Linkage on Positive Selection , 2006, Genetics.

[17]  Gavin Sherlock,et al.  Molecular Characterization of Clonal Interference during Adaptive Evolution in Asexual Populations of Saccharomyces cerevisiae , 2008, Nature Genetics.

[18]  David Botstein,et al.  The Repertoire and Dynamics of Evolutionary Adaptations to Controlled Nutrient-Limited Environments in Yeast , 2008, PLoS genetics.

[19]  Jeffrey E. Barrick,et al.  Genome evolution and adaptation in a long-term experiment with Escherichia coli , 2009, Nature.

[20]  Jeffrey E. Barrick,et al.  Genome-wide mutational diversity in an evolving population of Escherichia coli. , 2009, Cold Spring Harbor symposia on quantitative biology.

[21]  A. Betancourt.  Genomewide Patterns of Substitution in Adaptively Evolving Populations of the RNA Bacteriophage MS2 , 2009, Genetics.

[22]  Gonçalo R. Abecasis,et al.  The Sequence Alignment/Map format and SAMtools , 2009, Bioinform..

[23]  Richard Durbin,et al.  Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .

[24]  J. Salk.  Clonal evolution in cancer , 2010 .

[25]  M. Doebeli,et al.  The Repeatability of Adaptive Radiation During Long-Term Experimental Evolution of Escherichia coli in a Multiple Nutrient Environment , 2010, PloS one.

[26]  Helga Thorvaldsdóttir,et al.  Integrative Genomics Viewer , 2011, Nature Biotechnology.

[27]  Gergely J. Szöllősi,et al.  Emergent Neutrality in Adaptive Asexual Evolution , 2011, Genetics.

[28]  Michael M. Desai,et al.  Genetic Variation and the Fate of Beneficial Mutations in Asexual Populations , 2011, Genetics.

[29]  Craig R. Miller,et al.  Mutational Effects and Population Dynamics During Viral Adaptation Challenge Current Models , 2011, Genetics.

[30]  M. Lässig,et al.  Clonal Interference in the Evolution of Influenza , 2012, Genetics.

[31]  A. Børresen-Dale,et al.  The Life History of 21 Breast Cancers , 2012, Cell.

[32]  Carlo C. Maley,et al.  Cancer in Light of Experimental Evolution , 2012, Current Biology.

[33]  Alex Wong,et al.  Evolutionary insight from whole‐genome sequencing of experimentally evolved microbes , 2012, Molecular ecology.

[34]  Benjamin H. Good,et al.  Distribution of fixed beneficial mutations and the rate of adaptation in asexual populations , 2012, Proceedings of the National Academy of Sciences.

[35]  Carlo C. Maley,et al.  Clonal evolution in cancer , 2012, Nature.

[36]  A. F. Bennett,et al.  The Molecular Diversity of Adaptive Convergence , 2012, Science.

[37]  Helga Thorvaldsdóttir,et al.  Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration , 2012, Briefings Bioinform..