Literature DB >> 35755130

Protocol for single-nucleus ATAC sequencing and bioinformatic analysis in frozen human brain tissue.

Zechuan Shi1, Sudeshna Das1, Samuel Morabito2, Emily Miyoshi1, Vivek Swarup3.   

Abstract

Single-nucleus ATAC sequencing (snATAC-seq) employs a hyperactive Tn5 transposase to gain precise information about the cis-regulatory elements in specific cell types. However, the standard protocol of snATAC-seq is not optimized for all tissues, including the brain. Here, we present a modified protocol for single-nuclei isolation from postmortem frozen human brain tissue, followed by snATAC-seq library preparation and sequencing. We also describe an integrated bioinformatics analysis pipeline using an R package (ArchRtoSignac) to robustly analyze snATAC-seq data. For complete details on the use and execution of this protocol, please refer to Morabito et al. (2021).
© 2022 The Authors.

Entities:  

Keywords:  Bioinformatics; Genomics; Health Sciences; Neuroscience; Sequence analysis; Sequencing

Mesh:

Substances:

Year:  2022        PMID: 35755130      PMCID: PMC9218237          DOI: 10.1016/j.xpro.2022.101491

Source DB:  PubMed          Journal:  STAR Protoc        ISSN: 2666-1667


  13 in total

1.  A discriminative learning approach to differential expression analysis for single-cell RNA-seq.

Authors:  Vasilis Ntranos; Lynn Yi; Páll Melsted; Lior Pachter
Journal:  Nat Methods       Date:  2019-01-21       Impact factor: 28.547

Review 2.  Genome-wide analysis of chromatin accessibility using ATAC-seq.

Authors:  Tanvi Shashikant; Charles A Ettensohn
Journal:  Methods Cell Biol       Date:  2018-12-21       Impact factor: 1.441

3.  GREAT improves functional interpretation of cis-regulatory regions.

Authors:  Cory Y McLean; Dave Bristor; Michael Hiller; Shoa L Clarke; Bruce T Schaar; Craig B Lowe; Aaron M Wenger; Gill Bejerano
Journal:  Nat Biotechnol       Date:  2010-05-02       Impact factor: 54.908

4.  Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data.

Authors:  Hannah A Pliner; Jonathan S Packer; José L McFaline-Figueroa; Darren A Cusanovich; Riza M Daza; Delasa Aghamirzaie; Sanjay Srivatsan; Xiaojie Qiu; Dana Jackson; Anna Minkina; Andrew C Adey; Frank J Steemers; Jay Shendure; Cole Trapnell
Journal:  Mol Cell       Date:  2018-08-02       Impact factor: 17.970

5.  Single-cell chromatin state analysis with Signac.

Authors:  Tim Stuart; Avi Srivastava; Shaista Madad; Caleb A Lareau; Rahul Satija
Journal:  Nat Methods       Date:  2021-11-01       Impact factor: 47.990

6.  chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data.

Authors:  Alicia N Schep; Beijing Wu; Jason D Buenrostro; William J Greenleaf
Journal:  Nat Methods       Date:  2017-08-21       Impact factor: 28.547

7.  The single-cell transcriptional landscape of mammalian organogenesis.

Authors:  Junyue Cao; Malte Spielmann; Xiaojie Qiu; Xingfan Huang; Daniel M Ibrahim; Andrew J Hill; Fan Zhang; Stefan Mundlos; Lena Christiansen; Frank J Steemers; Cole Trapnell; Jay Shendure
Journal:  Nature       Date:  2019-02-20       Impact factor: 49.962

8.  Single-cell ATAC-Seq in human pancreatic islets and deep learning upscaling of rare cells reveals cell-specific type 2 diabetes regulatory signatures.

Authors:  Vivek Rai; Daniel X Quang; Michael R Erdos; Darren A Cusanovich; Riza M Daza; Narisu Narisu; Luli S Zou; John P Didion; Yuanfang Guan; Jay Shendure; Stephen C J Parker; Francis S Collins
Journal:  Mol Metab       Date:  2019-12-20       Impact factor: 7.422

9.  Comprehensive analysis of single cell ATAC-seq data with SnapATAC.

Authors:  Rongxin Fang; Sebastian Preissl; Yang Li; Xiaomeng Hou; Jacinta Lucero; Xinxin Wang; Amir Motamedi; Andrew K Shiau; Xinzhu Zhou; Fangming Xie; Eran A Mukamel; Kai Zhang; Yanxiao Zhang; M Margarita Behrens; Joseph R Ecker; Bing Ren
Journal:  Nat Commun       Date:  2021-02-26       Impact factor: 14.919

10.  Single-cell epigenomics reveals mechanisms of human cortical development.

Authors:  Ryan S Ziffra; Chang N Kim; Jayden M Ross; Amy Wilfert; Tychele N Turner; Maximilian Haeussler; Alex M Casella; Pawel F Przytycki; Kathleen C Keough; David Shin; Derek Bogdanoff; Anat Kreimer; Katherine S Pollard; Seth A Ament; Evan E Eichler; Nadav Ahituv; Tomasz J Nowakowski
Journal:  Nature       Date:  2021-10-06       Impact factor: 69.504

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