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High-throughput analysis of adaptation using barcoded strains of Saccharomyces cerevisiae

BACKGROUND: Experimental evolution of microbes can be used to empirically address a wide range of questions about evolution and is increasingly employed to study complex phenomena ranging from genetic evolution to evolutionary rescue. Regardless of experimental aims, fitness assays are a central com...

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Autores principales: Fasanello, Vincent J., Liu, Ping, Botero, Carlos A., Fay, Justin C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571412/
https://www.ncbi.nlm.nih.gov/pubmed/33088623
http://dx.doi.org/10.7717/peerj.10118
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author Fasanello, Vincent J.
Liu, Ping
Botero, Carlos A.
Fay, Justin C.
author_facet Fasanello, Vincent J.
Liu, Ping
Botero, Carlos A.
Fay, Justin C.
author_sort Fasanello, Vincent J.
collection PubMed
description BACKGROUND: Experimental evolution of microbes can be used to empirically address a wide range of questions about evolution and is increasingly employed to study complex phenomena ranging from genetic evolution to evolutionary rescue. Regardless of experimental aims, fitness assays are a central component of this type of research, and low-throughput often limits the scope and complexity of experimental evolution studies. We created an experimental evolution system in Saccharomyces cerevisiae that utilizes genetic barcoding to overcome this challenge. RESULTS: We first confirm that barcode insertions do not alter fitness and that barcode sequencing can be used to efficiently detect fitness differences via pooled competition-based fitness assays. Next, we examine the effects of ploidy, chemical stress, and population bottleneck size on the evolutionary dynamics and fitness gains (adaptation) in a total of 76 experimentally evolving, asexual populations by conducting 1,216 fitness assays and analyzing 532 longitudinal-evolutionary samples collected from the evolving populations. In our analysis of these data we describe the strengths of this experimental evolution system and explore sources of error in our measurements of fitness and evolutionary dynamics. CONCLUSIONS: Our experimental treatments generated distinct fitness effects and evolutionary dynamics, respectively quantified via multiplexed fitness assays and barcode lineage tracking. These findings demonstrate the utility of this new resource for designing and improving high-throughput studies of experimental evolution. The approach described here provides a framework for future studies employing experimental designs that require high-throughput multiplexed fitness measurements.
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spelling pubmed-75714122020-10-20 High-throughput analysis of adaptation using barcoded strains of Saccharomyces cerevisiae Fasanello, Vincent J. Liu, Ping Botero, Carlos A. Fay, Justin C. PeerJ Evolutionary Studies BACKGROUND: Experimental evolution of microbes can be used to empirically address a wide range of questions about evolution and is increasingly employed to study complex phenomena ranging from genetic evolution to evolutionary rescue. Regardless of experimental aims, fitness assays are a central component of this type of research, and low-throughput often limits the scope and complexity of experimental evolution studies. We created an experimental evolution system in Saccharomyces cerevisiae that utilizes genetic barcoding to overcome this challenge. RESULTS: We first confirm that barcode insertions do not alter fitness and that barcode sequencing can be used to efficiently detect fitness differences via pooled competition-based fitness assays. Next, we examine the effects of ploidy, chemical stress, and population bottleneck size on the evolutionary dynamics and fitness gains (adaptation) in a total of 76 experimentally evolving, asexual populations by conducting 1,216 fitness assays and analyzing 532 longitudinal-evolutionary samples collected from the evolving populations. In our analysis of these data we describe the strengths of this experimental evolution system and explore sources of error in our measurements of fitness and evolutionary dynamics. CONCLUSIONS: Our experimental treatments generated distinct fitness effects and evolutionary dynamics, respectively quantified via multiplexed fitness assays and barcode lineage tracking. These findings demonstrate the utility of this new resource for designing and improving high-throughput studies of experimental evolution. The approach described here provides a framework for future studies employing experimental designs that require high-throughput multiplexed fitness measurements. PeerJ Inc. 2020-10-16 /pmc/articles/PMC7571412/ /pubmed/33088623 http://dx.doi.org/10.7717/peerj.10118 Text en ©2020 Fasanello et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Evolutionary Studies
Fasanello, Vincent J.
Liu, Ping
Botero, Carlos A.
Fay, Justin C.
High-throughput analysis of adaptation using barcoded strains of Saccharomyces cerevisiae
title High-throughput analysis of adaptation using barcoded strains of Saccharomyces cerevisiae
title_full High-throughput analysis of adaptation using barcoded strains of Saccharomyces cerevisiae
title_fullStr High-throughput analysis of adaptation using barcoded strains of Saccharomyces cerevisiae
title_full_unstemmed High-throughput analysis of adaptation using barcoded strains of Saccharomyces cerevisiae
title_short High-throughput analysis of adaptation using barcoded strains of Saccharomyces cerevisiae
title_sort high-throughput analysis of adaptation using barcoded strains of saccharomyces cerevisiae
topic Evolutionary Studies
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571412/
https://www.ncbi.nlm.nih.gov/pubmed/33088623
http://dx.doi.org/10.7717/peerj.10118
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