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gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution

Cellular lineage tracking provides a means to observe population makeup at the clonal level, allowing exploration of heterogeneity, evolutionary and developmental processes and individual clones’ relative fitness. It has thus contributed significantly to understanding microbial evolution, organ diff...

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Autores principales: Rezenman, Shahar, Knafo, Maor, Tsigalnitski, Ivgeni, Barad, Shiri, Jona, Ghil, Levi, Dikla, Dym, Orly, Reich, Ziv, Kapon, Ruti
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246843/
https://www.ncbi.nlm.nih.gov/pubmed/37285353
http://dx.doi.org/10.1371/journal.pone.0286696
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author Rezenman, Shahar
Knafo, Maor
Tsigalnitski, Ivgeni
Barad, Shiri
Jona, Ghil
Levi, Dikla
Dym, Orly
Reich, Ziv
Kapon, Ruti
author_facet Rezenman, Shahar
Knafo, Maor
Tsigalnitski, Ivgeni
Barad, Shiri
Jona, Ghil
Levi, Dikla
Dym, Orly
Reich, Ziv
Kapon, Ruti
author_sort Rezenman, Shahar
collection PubMed
description Cellular lineage tracking provides a means to observe population makeup at the clonal level, allowing exploration of heterogeneity, evolutionary and developmental processes and individual clones’ relative fitness. It has thus contributed significantly to understanding microbial evolution, organ differentiation and cancer heterogeneity, among others. Its use, however, is limited because existing methods are highly specific, expensive, labour-intensive, and, critically, do not allow the repetition of experiments. To address these issues, we developed gUMI-BEAR (genomic Unique Molecular Identifier Barcoded Enriched Associated Regions), a modular, cost-effective method for tracking populations at high resolution. We first demonstrate the system’s application and resolution by applying it to track tens of thousands of Saccharomyces cerevisiae lineages growing together under varying environmental conditions applied across multiple generations, revealing fitness differences and lineage-specific adaptations. Then, we demonstrate how gUMI-BEAR can be used to perform parallel screening of a huge number of randomly generated variants of the Hsp82 gene. We further show how our method allows isolation of variants, even if their frequency in the population is low, thus enabling unsupervised identification of modifications that lead to a behaviour of interest.
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spelling pubmed-102468432023-06-08 gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution Rezenman, Shahar Knafo, Maor Tsigalnitski, Ivgeni Barad, Shiri Jona, Ghil Levi, Dikla Dym, Orly Reich, Ziv Kapon, Ruti PLoS One Research Article Cellular lineage tracking provides a means to observe population makeup at the clonal level, allowing exploration of heterogeneity, evolutionary and developmental processes and individual clones’ relative fitness. It has thus contributed significantly to understanding microbial evolution, organ differentiation and cancer heterogeneity, among others. Its use, however, is limited because existing methods are highly specific, expensive, labour-intensive, and, critically, do not allow the repetition of experiments. To address these issues, we developed gUMI-BEAR (genomic Unique Molecular Identifier Barcoded Enriched Associated Regions), a modular, cost-effective method for tracking populations at high resolution. We first demonstrate the system’s application and resolution by applying it to track tens of thousands of Saccharomyces cerevisiae lineages growing together under varying environmental conditions applied across multiple generations, revealing fitness differences and lineage-specific adaptations. Then, we demonstrate how gUMI-BEAR can be used to perform parallel screening of a huge number of randomly generated variants of the Hsp82 gene. We further show how our method allows isolation of variants, even if their frequency in the population is low, thus enabling unsupervised identification of modifications that lead to a behaviour of interest. Public Library of Science 2023-06-07 /pmc/articles/PMC10246843/ /pubmed/37285353 http://dx.doi.org/10.1371/journal.pone.0286696 Text en © 2023 Rezenman 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, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Rezenman, Shahar
Knafo, Maor
Tsigalnitski, Ivgeni
Barad, Shiri
Jona, Ghil
Levi, Dikla
Dym, Orly
Reich, Ziv
Kapon, Ruti
gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution
title gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution
title_full gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution
title_fullStr gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution
title_full_unstemmed gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution
title_short gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution
title_sort gumi-bear, a modular, unsupervised population barcoding method to track variants and evolution at high resolution
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246843/
https://www.ncbi.nlm.nih.gov/pubmed/37285353
http://dx.doi.org/10.1371/journal.pone.0286696
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