Literature DB >> 31169445

aFARP-ChIP-seq, a convenient and reliable method for genome profiling in as few as 100 cells with a capability for multiplexing ChIP-seq.

Wenbin Liu1,2, Sibiao Yue1, Xiaobin Zheng1, Minjie Hu1, Jia Cao2, Yixian Zheng1.   

Abstract

Much effort has been devoted to understand how chromatin modification regulates development and disease. Despite recent progress, however, it remains difficult to obtain high-quality epigenomic maps using chromatin-immunoprecipitation-coupled deep sequencing (ChIP-seq) in samples with low-cell numbers. Here, we present an Atlantis dsDNase-based technology, aFARP-ChIP-seq, that provides accurate profiling of genome-wide histone modifications in as few as 100 cells. By mapping histone lysine trimethylation (H3K4me3) and acetylation (H3K27Ac) in group I innate lymphoid cells (ILC1) sorted from different tissues in parallel, aFARP-ChIP-seq uncovers putative active promoter and enhancer landscapes of several tissue-specific Natural Killer cells (NK) and ILC1. aFARP-ChIP-seq is also highly effective in mapping transcription factor binding sites in small number of cells. Thus, aFARP-ChIP-seq offers multiplexing mapping of both epigenome and transcription factor binding sites using a small number of cells.

Entities:  

Keywords:  ChIP-seq; Epigenetics; H3K27Ac; H3K4me3; ILC1; NK cell; low cell numbers

Mesh:

Substances:

Year:  2019        PMID: 31169445      PMCID: PMC6691993          DOI: 10.1080/15592294.2019.1621139

Source DB:  PubMed          Journal:  Epigenetics        ISSN: 1559-2294            Impact factor:   4.528


  51 in total

1.  Sonication of proteins causes formation of aggregates that resemble amyloid.

Authors:  Peter B Stathopulos; Guenter A Scholz; Young-Mi Hwang; Jessica A O Rumfeldt; James R Lepock; Elizabeth M Meiering
Journal:  Protein Sci       Date:  2004-09-30       Impact factor: 6.725

2.  Genome-wide prediction of mammalian enhancers based on analysis of transcription-factor binding affinity.

Authors:  Outi Hallikas; Kimmo Palin; Natalia Sinjushina; Reetta Rautiainen; Juha Partanen; Esko Ukkonen; Jussi Taipale
Journal:  Cell       Date:  2006-01-13       Impact factor: 41.582

3.  ChIP-Seq of transcription factors predicts absolute and differential gene expression in embryonic stem cells.

Authors:  Zhengqing Ouyang; Qing Zhou; Wing Hung Wong
Journal:  Proc Natl Acad Sci U S A       Date:  2009-12-07       Impact factor: 11.205

4.  Genome-wide chromatin maps derived from limited numbers of hematopoietic progenitors.

Authors:  Mazhar Adli; Jiang Zhu; Bradley E Bernstein
Journal:  Nat Methods       Date:  2010-07-11       Impact factor: 28.547

5.  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

6.  Spi-C has opposing effects to PU.1 on gene expression in progenitor B cells.

Authors:  Brock L Schweitzer; Kelly J Huang; Meghana B Kamath; Alexander V Emelyanov; Barbara K Birshtein; Rodney P DeKoter
Journal:  J Immunol       Date:  2006-08-15       Impact factor: 5.422

7.  Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities.

Authors:  Sven Heinz; Christopher Benner; Nathanael Spann; Eric Bertolino; Yin C Lin; Peter Laslo; Jason X Cheng; Cornelis Murre; Harinder Singh; Christopher K Glass
Journal:  Mol Cell       Date:  2010-05-28       Impact factor: 17.970

Review 8.  ChIP-seq: advantages and challenges of a maturing technology.

Authors:  Peter J Park
Journal:  Nat Rev Genet       Date:  2009-09-08       Impact factor: 53.242

9.  Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data.

Authors:  Anton Valouev; David S Johnson; Andreas Sundquist; Catherine Medina; Elizabeth Anton; Serafim Batzoglou; Richard M Myers; Arend Sidow
Journal:  Nat Methods       Date:  2008-09       Impact factor: 28.547

10.  Model-based analysis of ChIP-Seq (MACS).

Authors:  Yong Zhang; Tao Liu; Clifford A Meyer; Jérôme Eeckhoute; David S Johnson; Bradley E Bernstein; Chad Nusbaum; Richard M Myers; Myles Brown; Wei Li; X Shirley Liu
Journal:  Genome Biol       Date:  2008-09-17       Impact factor: 13.583

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