2C-ChIP: measuring chromatin immunoprecipitation signal from defined genomic regions with deep sequencing.


Journal

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

Informations de publication

Date de publication:
28 Feb 2019
Historique:
received: 06 08 2018
accepted: 15 02 2019
entrez: 2 3 2019
pubmed: 2 3 2019
medline: 14 6 2019
Statut: epublish

Résumé

Understanding how transcription occurs requires the integration of genome-wide and locus-specific information gleaned from robust technologies. Chromatin immunoprecipitation (ChIP) is a staple in gene expression studies, and while genome-wide methods are available, high-throughput approaches to analyze defined regions are lacking. Here, we present carbon copy-ChIP (2C-ChIP), a versatile, inexpensive, and high-throughput technique to quantitatively measure the abundance of DNA sequences in ChIP samples. This method combines ChIP with ligation-mediated amplification (LMA) and deep sequencing to probe large genomic regions of interest. 2C-ChIP recapitulates results from benchmark ChIP approaches. We applied 2C-ChIP to the HOXA cluster to find that a region where H3K27me3 and SUZ12 linger encodes HOXA-AS2, a long non-coding RNA that enhances gene expression during cellular differentiation. 2C-ChIP fills the need for a robust molecular biology tool designed to probe dedicated genomic regions in a high-throughput setting. The flexible nature of the 2C-ChIP approach allows rapid changes in experimental design at relatively low cost, making it a highly efficient method for chromatin analysis.

Sections du résumé

BACKGROUND BACKGROUND
Understanding how transcription occurs requires the integration of genome-wide and locus-specific information gleaned from robust technologies. Chromatin immunoprecipitation (ChIP) is a staple in gene expression studies, and while genome-wide methods are available, high-throughput approaches to analyze defined regions are lacking.
RESULTS RESULTS
Here, we present carbon copy-ChIP (2C-ChIP), a versatile, inexpensive, and high-throughput technique to quantitatively measure the abundance of DNA sequences in ChIP samples. This method combines ChIP with ligation-mediated amplification (LMA) and deep sequencing to probe large genomic regions of interest. 2C-ChIP recapitulates results from benchmark ChIP approaches. We applied 2C-ChIP to the HOXA cluster to find that a region where H3K27me3 and SUZ12 linger encodes HOXA-AS2, a long non-coding RNA that enhances gene expression during cellular differentiation.
CONCLUSIONS CONCLUSIONS
2C-ChIP fills the need for a robust molecular biology tool designed to probe dedicated genomic regions in a high-throughput setting. The flexible nature of the 2C-ChIP approach allows rapid changes in experimental design at relatively low cost, making it a highly efficient method for chromatin analysis.

Identifiants

pubmed: 30819105
doi: 10.1186/s12864-019-5532-5
pii: 10.1186/s12864-019-5532-5
pmc: PMC6394006
doi:

Substances chimiques

RNA, Long Noncoding 0
long noncoding RNA HOXA-AS2, human 0

Types de publication

Journal Article Validation Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

162

Subventions

Organisme : Canadian Institutes of Health Research
ID : 142451
Pays : Canada

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Auteurs

Xue Qing David Wang (XQD)

Department of Biochemistry and Rosalind & Morris Goodman Cancer Research Center, McGill University, Montréal, Québec, H3G 1Y6, Canada.

Christopher J F Cameron (CJF)

Department of Biochemistry and Rosalind & Morris Goodman Cancer Research Center, McGill University, Montréal, Québec, H3G 1Y6, Canada.
School of Computer Science and McGill Center for Bioinformatics, McGill University, Montréal, Québec, H3A 0E9, Canada.

Denis Paquette (D)

Department of Biochemistry and Rosalind & Morris Goodman Cancer Research Center, McGill University, Montréal, Québec, H3G 1Y6, Canada.

Dana Segal (D)

Department of Biochemistry and Rosalind & Morris Goodman Cancer Research Center, McGill University, Montréal, Québec, H3G 1Y6, Canada.

Reid Warsaba (R)

Department of Biochemistry and Rosalind & Morris Goodman Cancer Research Center, McGill University, Montréal, Québec, H3G 1Y6, Canada.

Mathieu Blanchette (M)

School of Computer Science and McGill Center for Bioinformatics, McGill University, Montréal, Québec, H3A 0E9, Canada.

Josée Dostie (J)

Department of Biochemistry and Rosalind & Morris Goodman Cancer Research Center, McGill University, Montréal, Québec, H3G 1Y6, Canada. josee.dostie@mcgill.ca.

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Classifications MeSH