skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

This content will become publicly available on November 13, 2020

Title: High-resolution lineage tracking reveals travelling wave of adaptation in laboratory yeast

Abstract

In rapidly adapting asexual populations, including many microbial pathogens and viruses, numerous mutant lineages often compete for dominance within the population. These complex evolutionary dynamics determine the outcomes of adaptation, but have been difficult to observe directly. Previous studies have used whole-genome sequencing to follow molecular adaptation; however, these methods have limited resolution in microbial populations. Here we introduce a renewable barcoding system to observe evolutionary dynamics at high resolution in laboratory budding yeast. We find nested patterns of interference and hitchhiking even at low frequencies. These events are driven by the continuous appearance of new mutations that modify the fates of existing lineages before they reach substantial frequencies. We observe how the distribution of fitness within the population changes over time, and find a travelling wave of adaptation that has been predicted by theory. We show that clonal competition creates a dynamical ‘rich-get-richer’ effect: fitness advantages that are acquired early in evolution drive clonal expansions, which increase the chances of acquiring future mutations. However, less-fit lineages also routinely leapfrog over strains of higher fitness. Finally, our results demonstrate that this combination of factors, which is not accounted for in existing models of evolutionary dynamics, is critical in determining themore » rate, predictability and molecular basis of adaptation.« less

Authors:
 [1];  [1];  [1];  [2];  [1];  [3];  [3];  [1]
  1. Harvard Univ., Cambridge, MA (United States)
  2. Harvard Univ., Cambridge, MA (United States); Massachusetts Inst. of Technology, Cambridge, MA (United States)
  3. Stanford Univ., CA (United States); Stony Brook Univ., NY (United States)
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Org.:
USDOE; National Science Foundation (NSF); National Institutes of Health (NIH); Simons Foundation
OSTI Identifier:
1596638
Grant/Contract Number:  
[AC02-76SF00515; DMS-1764269; HG008354; HL127522; 376196; DEB-1655960; GM104239]
Resource Type:
Accepted Manuscript
Journal Name:
Nature (London)
Additional Journal Information:
[Journal Name: Nature (London); Journal Volume: 575; Journal Issue: 7783]; Journal ID: ISSN 0028-0836
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; experimental evolution; molecular evolution; population genetics

Citation Formats

Nguyen Ba, Alex N., Cvijović, Ivana, Rojas Echenique, José I., Lawrence, Katherine R., Rego-Costa, Artur, Liu, Xianan, Levy, Sasha F., and Desai, Michael M. High-resolution lineage tracking reveals travelling wave of adaptation in laboratory yeast. United States: N. p., 2019. Web. doi:10.1038/s41586-019-1749-3.
Nguyen Ba, Alex N., Cvijović, Ivana, Rojas Echenique, José I., Lawrence, Katherine R., Rego-Costa, Artur, Liu, Xianan, Levy, Sasha F., & Desai, Michael M. High-resolution lineage tracking reveals travelling wave of adaptation in laboratory yeast. United States. doi:10.1038/s41586-019-1749-3.
Nguyen Ba, Alex N., Cvijović, Ivana, Rojas Echenique, José I., Lawrence, Katherine R., Rego-Costa, Artur, Liu, Xianan, Levy, Sasha F., and Desai, Michael M. Wed . "High-resolution lineage tracking reveals travelling wave of adaptation in laboratory yeast". United States. doi:10.1038/s41586-019-1749-3.
@article{osti_1596638,
title = {High-resolution lineage tracking reveals travelling wave of adaptation in laboratory yeast},
author = {Nguyen Ba, Alex N. and Cvijović, Ivana and Rojas Echenique, José I. and Lawrence, Katherine R. and Rego-Costa, Artur and Liu, Xianan and Levy, Sasha F. and Desai, Michael M.},
abstractNote = {In rapidly adapting asexual populations, including many microbial pathogens and viruses, numerous mutant lineages often compete for dominance within the population. These complex evolutionary dynamics determine the outcomes of adaptation, but have been difficult to observe directly. Previous studies have used whole-genome sequencing to follow molecular adaptation; however, these methods have limited resolution in microbial populations. Here we introduce a renewable barcoding system to observe evolutionary dynamics at high resolution in laboratory budding yeast. We find nested patterns of interference and hitchhiking even at low frequencies. These events are driven by the continuous appearance of new mutations that modify the fates of existing lineages before they reach substantial frequencies. We observe how the distribution of fitness within the population changes over time, and find a travelling wave of adaptation that has been predicted by theory. We show that clonal competition creates a dynamical ‘rich-get-richer’ effect: fitness advantages that are acquired early in evolution drive clonal expansions, which increase the chances of acquiring future mutations. However, less-fit lineages also routinely leapfrog over strains of higher fitness. Finally, our results demonstrate that this combination of factors, which is not accounted for in existing models of evolutionary dynamics, is critical in determining the rate, predictability and molecular basis of adaptation.},
doi = {10.1038/s41586-019-1749-3},
journal = {Nature (London)},
number = [7783],
volume = [575],
place = {United States},
year = {2019},
month = {11}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on November 13, 2020
Publisher's Version of Record

Save / Share:

Works referenced in this record:

Fierce Selection and Interference in B-Cell Repertoire Response to Chronic HIV-1
journal, June 2019

  • Nourmohammad, Armita; Otwinowski, Jakub; Łuksza, Marta
  • Molecular Biology and Evolution, Vol. 36, Issue 10
  • DOI: 10.1093/molbev/msz143

The dynamics of molecular evolution over 60,000 generations
journal, October 2017

  • Good, Benjamin H.; McDonald, Michael J.; Barrick, Jeffrey E.
  • Nature, Vol. 551, Issue 7678
  • DOI: 10.1038/nature24287

Beyond genome sequencing: Lineage tracking with barcodes to study the dynamics of evolution, infection, and cancer
journal, December 2014


The Speed of Evolution and Maintenance of Variation in Asexual Populations
journal, March 2007


Quantitative evolutionary dynamics using high-resolution lineage tracking
journal, February 2015

  • Levy, Sasha F.; Blundell, Jamie R.; Venkataram, Sandeep
  • Nature, Vol. 519, Issue 7542
  • DOI: 10.1038/nature14279

Clonal Interference in the Evolution of Influenza
journal, July 2012


Mutational Effects and Population Dynamics During Viral Adaptation Challenge Current Models
journal, November 2010


Tempo and mode of genome evolution in a 50,000-generation experiment
journal, August 2016

  • Tenaillon, Olivier; Barrick, Jeffrey E.; Ribeck, Noah
  • Nature, Vol. 536, Issue 7615
  • DOI: 10.1038/nature18959

Distribution of fixed beneficial mutations and the rate of adaptation in asexual populations
journal, February 2012

  • Good, B. H.; Rouzine, I. M.; Balick, D. J.
  • Proceedings of the National Academy of Sciences, Vol. 109, Issue 13
  • DOI: 10.1073/pnas.1119910109

The noisy edge of traveling waves
journal, December 2010

  • Hallatschek, Oskar
  • Proceedings of the National Academy of Sciences, Vol. 108, Issue 5
  • DOI: 10.1073/pnas.1013529108

The dynamics of adaptive genetic diversity during the early stages of clonal evolution
journal, December 2018

  • Blundell, Jamie R.; Schwartz, Katja; Francois, Danielle
  • Nature Ecology & Evolution, Vol. 3, Issue 2
  • DOI: 10.1038/s41559-018-0758-1

Genetic Draft, Selective Interference, and Population Genetics of Rapid Adaptation
journal, November 2013


The traveling-wave approach to asexual evolution: Muller's ratchet and speed of adaptation
journal, February 2008

  • Rouzine, Igor M.; Brunet, Éric; Wilke, Claus O.
  • Theoretical Population Biology, Vol. 73, Issue 1
  • DOI: 10.1016/j.tpb.2007.10.004

The Life History of 21 Breast Cancers
journal, May 2012


Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes
journal, November 2011

  • Lieberman, Tami D.; Michel, Jean-Baptiste; Aingaran, Mythili
  • Nature Genetics, Vol. 43, Issue 12
  • DOI: 10.1038/ng.997

Sex speeds adaptation by altering the dynamics of molecular evolution
journal, February 2016

  • McDonald, Michael J.; Rice, Daniel P.; Desai, Michael M.
  • Nature, Vol. 531, Issue 7593
  • DOI: 10.1038/nature17143

Deleterious Passengers in Adapting Populations
journal, September 2014


Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations
journal, July 2013

  • Lang, Gregory I.; Rice, Daniel P.; Hickman, Mark J.
  • Nature, Vol. 500, Issue 7464
  • DOI: 10.1038/nature12344

RNA Virus Evolution via a Fitness-Space Model
journal, June 1996


Beneficial Mutation–Selection Balance and the Effect of Linkage on Positive Selection
journal, May 2007


Saccharomyces cerevisiae commits to a programmed cell death process in response to acetic acid
journal, September 2001


Experimental Studies of Evolutionary Dynamics in Microbes
journal, September 2018

  • Cvijović, Ivana; Nguyen Ba, Alex N.; Desai, Michael M.
  • Trends in Genetics, Vol. 34, Issue 9
  • DOI: 10.1016/j.tig.2018.06.004

Some Genetic Aspects of Sex
journal, March 1932

  • Muller, H. J.
  • The American Naturalist, Vol. 66, Issue 703
  • DOI: 10.1086/280418

Diminishing Returns from Mutation Supply Rate in Asexual Populations
journal, January 1999


Evolution in Sexual and Asexual Populations
journal, September 1968

  • Smith, J. Maynard
  • The American Naturalist, Vol. 102, Issue 927
  • DOI: 10.1086/282559

Hitchhiking and epistasis give rise to cohort dynamics in adapting populations
journal, July 2017

  • Buskirk, Sean W.; Peace, Ryan Emily; Lang, Gregory I.
  • Proceedings of the National Academy of Sciences, Vol. 114, Issue 31
  • DOI: 10.1073/pnas.1702314114

Population genomics of intrapatient HIV-1 evolution
journal, December 2015