Optimization of the Omni-ATAC protocol to chromatin accessibility profiling in snap-frozen rat adipose and muscle tissues.

ATAC-seq Bead-based tissue homogenization ENCODE quality standards Snap-frozen adipose and muscle tissue

Journal

MethodsX
ISSN: 2215-0161
Titre abrégé: MethodsX
Pays: Netherlands
ID NLM: 101639829

Informations de publication

Date de publication:
2022
Historique:
received: 25 10 2021
accepted: 22 03 2022
entrez: 25 4 2022
pubmed: 26 4 2022
medline: 26 4 2022
Statut: epublish

Résumé

ATAC-seq is a fast and sensitive method for the epigenomic profiling of open chromatin and for mapping of transcription factor binding sites [1]. Despite the development of the Omni-ATAC protocol for the profiling of chromatin accessibility in frozen tissues [2], studies in adipose tissue have been restricted due to technical challenges including the high lipid content of adipocytes and reproducibility issues between replicates. Here, we provide a modified Omni-ATAC protocol that achieves high data reproducibility in various tissue types from rat, including adipose and muscle tissues [3].•This protocol describes a methodology that enables chromatin accessibility profiling from snap-frozen rat adipose and muscle tissues.•The technique comprises an optimized bead-based tissue homogenization process that substitutes to Dounce homogenization, reduces variability in the experimental procedure, and is adaptable to various tissue types.•In comparison with the Omni-ATAC protocol, the method described here results in improved ATAC-seq data quality that complies with ENCODE quality standards.

Identifiants

pubmed: 35464805
doi: 10.1016/j.mex.2022.101681
pii: S2215-0161(22)00065-6
pmc: PMC9027329
doi:

Types de publication

Journal Article

Langues

eng

Pagination

101681

Subventions

Organisme : NIAMS NIH HHS
ID : R01 AR055246
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG055137
Pays : United States

Informations de copyright

© 2022 The Author(s).

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

Venugopalan D Nair (VD)

Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

Mital Vasoya (M)

Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

Vishnu Nair (V)

Department of Computer Sciences, Columbia University, New York, NY 10027, USA.

Gregory R Smith (GR)

Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

Hanna Pincas (H)

Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

Yongchao Ge (Y)

Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

Collin M Douglas (CM)

Department of Physiology and Functional Genomics, University of Florida, Gainesville, FL 32610, USA.

Karyn A Esser (KA)

Department of Physiology and Functional Genomics, University of Florida, Gainesville, FL 32610, USA.

Stuart C Sealfon (SC)

Department of Neurology, Center for Advanced Research on Diagnostic Assays, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

Classifications MeSH