CloneSifter: enrichment of rare clones from heterogeneous cell populations.
Authors | |
Abstract | BACKGROUND: Many biological processes, such as cancer metastasis, organismal development, and acquisition of resistance to cytotoxic therapy, rely on the emergence of rare sub-clones from a larger population. Understanding how the genetic and epigenetic features of diverse clones affect clonal fitness provides insight into molecular mechanisms underlying selective processes. While large-scale barcoding with NGS readout has facilitated cellular fitness assessment at the population level, this approach does not support characterization of clones prior to selection. Single-cell genomics methods provide high biological resolution, but are challenging to scale across large populations to probe rare clones and are destructive, limiting further functional analysis of important clones. RESULTS: Here, we develop CloneSifter, a methodology for tracking and enriching rare clones throughout their response to selection. CloneSifter utilizes a CRISPR sgRNA-barcode library that facilitates the isolation of viable cells from specific clones within the barcoded population using a sequence-specific retrieval reporter. We demonstrate that CloneSifter can measure clonal fitness of cancer cell models in vitro and retrieve targeted clones at abundance as low as 1 in 1883 in a heterogeneous cell population. CONCLUSIONS: CloneSifter provides a means to track and access specific and rare clones of interest across dynamic changes in population structure to comprehensively explore the basis of these changes. |
Year of Publication | 2020
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Journal | BMC Biol
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Volume | 18
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Issue | 1
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Pages | 177
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Date Published | 2020 11 24
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ISSN | 1741-7007
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DOI | 10.1186/s12915-020-00911-3
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PubMed ID | 33234154
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PubMed Central ID | PMC7687773
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Links | |
Grant list | CA201592-02 / NH / NIH HHS / United States
1U54CA224068-01 / NH / NIH HHS / United States
CA188228 / NH / NIH HHS / United States
CA219943 / NH / NIH HHS / United States
HG009283 / NH / NIH HHS / United States
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