Protocol for single-cell ATAC sequencing using combinatorial indexing in mouse lung adenocarcinoma

Isabella Del Priore; Sai Ma; Jonathan Strecker; Tyler Jacks; Lindsay M LaFave; Jason D Buenrostro

doi:10.1016/j.xpro.2021.100583

Protocol for single-cell ATAC sequencing using combinatorial indexing in mouse lung adenocarcinoma

STAR Protoc. 2021 Jun 3;2(2):100583. doi: 10.1016/j.xpro.2021.100583. eCollection 2021 Jun 18.

Authors

Isabella Del Priore^{1

2}, Sai Ma^{2

3

4}, Jonathan Strecker³, Tyler Jacks^{1

2}, Lindsay M LaFave^{1

2

4}, Jason D Buenrostro^{3

4}

Affiliations

¹ David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
² Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
³ Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
⁴ Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA.

Abstract

Single-cell ATAC sequencing using combinatorial indexing (sciATAC-seq) enables the identification of chromatin accessibility profiles at single-cell resolution with a dual-barcoding approach during transposition and library construction. Unlike commercial droplet-based approaches, sciATAC-seq is a cost-effective, extensible strategy that permits flexibility in the experimental scale via multiplexed barcoding across samples or perturbations. In contrast, droplet-based approaches have higher cell recovery and may be advantageous when cell input is limited. The step-by-step sciATAC-seq protocol described here is amenable to diverse cell types and fixed samples. For complete details on the use and execution of this protocol, please refer to LaFave et al. (2020).

Keywords: Cancer; Genomics; Molecular Biology; Sequencing; Single Cell.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Adenocarcinoma of Lung / genetics*
Animals
Computational Biology / methods
Epigenesis, Genetic
Lung Neoplasms / genetics*
Mice
Single-Cell Analysis / methods*

Abstract

Publication types

MeSH terms

Grants and funding