The Influence of Polyploidy on the Evolution of Yeast Grown in a Sub-Optimal Carbon Source

Amber L. Scott, Phillip A. Richmond, Robin D. Dowell, Anna M. Selmecki

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


Polyploidization events have occurred during the evolution of many fungi, plant, and animal species and are thought to contribute to speciation and tumorigenesis, however little is known about how ploidy level contributes to adaptation at the molecular level. Here we integrate whole genome sequencing, RNA expression analysis, and relative fitness of ∼100 evolved clones at three ploidy levels. Independent haploid, diploid, and tetraploid populations were grown in a low carbon environment for 250 generations. We demonstrate that the key adaptive mutation in the evolved clones is predicted by a gene expression signature of just five genes. All of the adaptive mutations identified encompass a narrow set of genes, however the tetraploid clones gain a broader spectrum of adaptive mutations than haploid or diploid clones. While many of the adaptive mutations occur in genes that encode proteins with known roles in glucose sensing and transport, we discover mutations in genes with no canonical role in carbon utilization (IPT1 and MOT3), as well as identify novel dominant mutations in glucose signal transducers thought to only accumulate recessive mutations in carbon limited environments (MTH1 and RGT1). We conclude that polyploid cells explore more genotypic and phenotypic space than lower ploidy cells. Our study provides strong evidence for the beneficial role of polyploidization events that occur during the evolution of many species and during tumorigenesis.

Original languageEnglish (US)
Pages (from-to)2690-2703
Number of pages14
JournalMolecular biology and evolution
Issue number10
StatePublished - Oct 1 2017
Externally publishedYes

Bibliographical note

Funding Information:
We thank members of the Selmecki and Dowell labs, in particular Robert W. Thomas and Hannah Chatwin. We are very grateful to David Deen for his artistic contributions. We thank the CU-Boulder and CU-Denver High-Throughput Sequencing Cores as well as the BioFrontiers Computing Core at the University of Colorado, Boulder for providing high performance computing resources (NIH 1S10OD012300) supported by BioFrontiers IT. This research was supported by Creighton University, LB692-Nebraska Tobacco Settlement Biomedical Research Development New Initiative Grant, LB506-Nebraska Department of Health and Human Services, and Nebraska EPSCoR First Award, and National Science Foundation Career award (NSF 1350915). All WGS and RNA-seq data have been deposited in the National Center for Biotechnology Information Sequence Read Archive database and Gene Expression Omnibus under accession numbers SRP047435 and GSE95069.

Publisher Copyright:
© 2017 The Author.


  • adaptive evolution
  • experimental evolution
  • expression data
  • genomics
  • polyploidy
  • yeast


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