Tracing cellular heterogeneity in pooled genetic screens via multi-level barcoding.


Journal

BMC genomics
ISSN: 1471-2164
Titre abrégé: BMC Genomics
Pays: England
ID NLM: 100965258

Informations de publication

Date de publication:
06 Feb 2019
Historique:
received: 09 04 2018
accepted: 24 01 2019
entrez: 8 2 2019
pubmed: 8 2 2019
medline: 21 5 2019
Statut: epublish

Résumé

While pooled loss- and gain-of-function CRISPR screening approaches have become increasingly popular to systematically investigate mammalian gene function, the large majority of them have thus far not investigated the influence of cellular heterogeneity on screen results. Instead most screens are analyzed by averaging the abundance of perturbed cells from a bulk population of cells. Here we developed multi-level barcoded sgRNA libraries to trace multiple clonal Cas9 cell lines exposed to the same environment. The first level of barcoding allows monitoring growth kinetics and treatment responses of multiplexed clonal cell lines under identical conditions while the second level enables in-sample replication and tracing of sub-clonal lineages of cells expressing the same sgRNA. Using our approach, we illustrate how heterogeneity in growth kinetics and treatment response of clonal cell lines impairs the results of pooled genetic screens.

Sections du résumé

BACKGROUND BACKGROUND
While pooled loss- and gain-of-function CRISPR screening approaches have become increasingly popular to systematically investigate mammalian gene function, the large majority of them have thus far not investigated the influence of cellular heterogeneity on screen results. Instead most screens are analyzed by averaging the abundance of perturbed cells from a bulk population of cells.
RESULTS RESULTS
Here we developed multi-level barcoded sgRNA libraries to trace multiple clonal Cas9 cell lines exposed to the same environment. The first level of barcoding allows monitoring growth kinetics and treatment responses of multiplexed clonal cell lines under identical conditions while the second level enables in-sample replication and tracing of sub-clonal lineages of cells expressing the same sgRNA.
CONCLUSION CONCLUSIONS
Using our approach, we illustrate how heterogeneity in growth kinetics and treatment response of clonal cell lines impairs the results of pooled genetic screens.

Identifiants

pubmed: 30727954
doi: 10.1186/s12864-019-5480-0
pii: 10.1186/s12864-019-5480-0
pmc: PMC6364396
doi:

Substances chimiques

RNA, Guide 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

107

Subventions

Organisme : NHLBI NIH HHS
ID : K25 HL121295
Pays : United States
Organisme : NIH HHS
ID : 1U01MH105028
Pays : United States
Organisme : NIH HHS
ID : U01CA168370
Pays : United States

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Auteurs

Michael Boettcher (M)

Department of Microbiology and Immunology, UCSF Diabetes Center, University of California, San Francisco, San Francisco, CA, 94143, USA.

Sergio Covarrubias (S)

Department of Microbiology and Immunology, UCSF Diabetes Center, University of California, San Francisco, San Francisco, CA, 94143, USA.

Anne Biton (A)

Department of Medicine, Lung Biology Center, University of California, San Francisco, San Francisco, 94143, CA, USA.
Institut Pasteur, Hub Bioinformatique et Biostatistique, Centre de Bioinformatique, Biostatistique et Biologie Intégrative (C3BI, USR 3756 Institut Pasteur et CNRS), Paris, France.

James Blau (J)

Department of Microbiology and Immunology, UCSF Diabetes Center, University of California, San Francisco, San Francisco, CA, 94143, USA.

Haopeng Wang (H)

Departments of Medicine and of Microbiology & Immunology, the Rosalind Russell-Ephraim P. Engleman Medical Research Center for Arthritis, and the Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA, 94143, USA.

Noah Zaitlen (N)

Department of Medicine, Lung Biology Center, University of California, San Francisco, San Francisco, 94143, CA, USA.

Michael T McManus (MT)

Department of Microbiology and Immunology, UCSF Diabetes Center, University of California, San Francisco, San Francisco, CA, 94143, USA. Michael.McManus@ucsf.edu.

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Classifications MeSH