Literature DB >> 31481796

Profiling chromatin states using single-cell itChIP-seq.

Shanshan Ai1, Haiqing Xiong1,2,3, Chen C Li1, Yingjie Luo1,2,3, Qiang Shi4, Yaxi Liu1, Xianhong Yu1,2,3, Cheng Li4, Aibin He5,6.   

Abstract

Single-cell measurement of chromatin states, including histone modifications and non-histone protein binding, remains challenging. Here, we present a low-cost, efficient, simultaneous indexing and tagmentation-based ChIP-seq (itChIP-seq) method, compatible with both low cellular input and single cells for profiling chromatin states. itChIP combines chromatin opening, simultaneous cellular indexing and chromatin tagmentation within a single tube, enabling the processing of samples from tens of single cells to, more commonly, thousands of single cells per assay. We demonstrate that single-cell itChIP-seq (sc-itChIP-seq) yields ~9,000 unique reads per cell. Using sc-itChIP-seq to profile H3K27ac, we sufficiently capture the earliest epigenetic priming event during the cell fate transition from naive to primed pluripotency, and reveal the basis for cell-type specific enhancer usage during the differentiation of bipotent cardiac progenitor cells into endothelial cells and cardiomyocytes. Our results demonstrate that itChIP is a widely applicable technology for single-cell chromatin profiling of epigenetically heterogeneous cell populations in many biological processes.

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Year:  2019        PMID: 31481796     DOI: 10.1038/s41556-019-0383-5

Source DB:  PubMed          Journal:  Nat Cell Biol        ISSN: 1465-7392            Impact factor:   28.824


  45 in total

1.  High-resolution genome-wide mapping of histone modifications.

Authors:  Tae-young Roh; Wing Chi Ngau; Kairong Cui; David Landsman; Keji Zhao
Journal:  Nat Biotechnol       Date:  2004-07-04       Impact factor: 54.908

2.  Whole-genome chromatin profiling from limited numbers of cells using nano-ChIP-seq.

Authors:  Mazhar Adli; Bradley E Bernstein
Journal:  Nat Protoc       Date:  2011-09-29       Impact factor: 13.491

3.  An ultra-low-input native ChIP-seq protocol for genome-wide profiling of rare cell populations.

Authors:  Julie Brind'Amour; Sheng Liu; Matthew Hudson; Carol Chen; Mohammad M Karimi; Matthew C Lorincz
Journal:  Nat Commun       Date:  2015-01-21       Impact factor: 14.919

Review 4.  Computational and analytical challenges in single-cell transcriptomics.

Authors:  Oliver Stegle; Sarah A Teichmann; John C Marioni
Journal:  Nat Rev Genet       Date:  2015-01-28       Impact factor: 53.242

5.  A chromatin integration labelling method enables epigenomic profiling with lower input.

Authors:  Akihito Harada; Kazumitsu Maehara; Tetsuya Handa; Yasuhiro Arimura; Jumpei Nogami; Yoko Hayashi-Takanaka; Katsuhiko Shirahige; Hitoshi Kurumizaka; Hiroshi Kimura; Yasuyuki Ohkawa
Journal:  Nat Cell Biol       Date:  2018-12-10       Impact factor: 28.824

6.  Resetting Epigenetic Memory by Reprogramming of Histone Modifications in Mammals.

Authors:  Hui Zheng; Bo Huang; Bingjie Zhang; Yunlong Xiang; Zhenhai Du; Qianhua Xu; Yuanyuan Li; Qiujun Wang; Jing Ma; Xu Peng; Feng Xu; Wei Xie
Journal:  Mol Cell       Date:  2016-09-15       Impact factor: 17.970

7.  Targeted in situ genome-wide profiling with high efficiency for low cell numbers.

Authors:  Peter J Skene; Jorja G Henikoff; Steven Henikoff
Journal:  Nat Protoc       Date:  2018-04-12       Impact factor: 13.491

Review 8.  Mapping human epigenomes.

Authors:  Chloe M Rivera; Bing Ren
Journal:  Cell       Date:  2013-09-26       Impact factor: 41.582

9.  Design and analysis of ChIP-seq experiments for DNA-binding proteins.

Authors:  Peter V Kharchenko; Michael Y Tolstorukov; Peter J Park
Journal:  Nat Biotechnol       Date:  2008-11-16       Impact factor: 54.908

10.  A microfluidic device for epigenomic profiling using 100 cells.

Authors:  Zhenning Cao; Changya Chen; Bing He; Kai Tan; Chang Lu
Journal:  Nat Methods       Date:  2015-07-27       Impact factor: 28.547

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  41 in total

1.  Self-Reporting Transposons Enable Simultaneous Readout of Gene Expression and Transcription Factor Binding in Single Cells.

Authors:  Arnav Moudgil; Michael N Wilkinson; Xuhua Chen; June He; Alexander J Cammack; Michael J Vasek; Tomás Lagunas; Zongtai Qi; Matthew A Lalli; Chuner Guo; Samantha A Morris; Joseph D Dougherty; Robi D Mitra
Journal:  Cell       Date:  2020-07-24       Impact factor: 41.582

2.  Single-cell joint detection of chromatin occupancy and transcriptome enables higher-dimensional epigenomic reconstructions.

Authors:  Haiqing Xiong; Yingjie Luo; Qianhao Wang; Xianhong Yu; Aibin He
Journal:  Nat Methods       Date:  2021-05-06       Impact factor: 28.547

3.  Multiplexed and Ultralow-Input ChIP-seq Enabled by Tagmentation-Based Indexing and Facile Microfluidics.

Authors:  Chengyu Deng; Travis W Murphy; Qiang Zhang; Lynette B Naler; Alice Xu; Chang Lu
Journal:  Anal Chem       Date:  2020-10-01       Impact factor: 6.986

Review 4.  Profiling chromatin regulatory landscape: insights into the development of ChIP-seq and ATAC-seq.

Authors:  Shaoqian Ma; Yongyou Zhang
Journal:  Mol Biomed       Date:  2020-10-10

Review 5.  Characterizing cis-regulatory elements using single-cell epigenomics.

Authors:  Sebastian Preissl; Kyle J Gaulton; Bing Ren
Journal:  Nat Rev Genet       Date:  2022-07-15       Impact factor: 59.581

6.  Efficient low-cost chromatin profiling with CUT&Tag.

Authors:  Hatice S Kaya-Okur; Derek H Janssens; Jorja G Henikoff; Kami Ahmad; Steven Henikoff
Journal:  Nat Protoc       Date:  2020-09-10       Impact factor: 13.491

7.  Deciphering Cell Fate Decision by Integrated Single-Cell Sequencing Analysis.

Authors:  Dominic Grün
Journal:  Annu Rev Biomed Data Sci       Date:  2020-03-02

Review 8.  The interplay between DNA and histone methylation: molecular mechanisms and disease implications.

Authors:  Yinglu Li; Xiao Chen; Chao Lu
Journal:  EMBO Rep       Date:  2021-04-12       Impact factor: 8.807

9.  Profiling single-cell histone modifications using indexing chromatin immunocleavage sequencing.

Authors:  Wai Lim Ku; Lixia Pan; Yaqiang Cao; Weiwu Gao; Keji Zhao
Journal:  Genome Res       Date:  2021-04-14       Impact factor: 9.043

Review 10.  The study of single cells in diabetic kidney disease.

Authors:  Harmandeep Kaur; Andrew Advani
Journal:  J Nephrol       Date:  2021-01-21       Impact factor: 3.902

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