Literature DB >> 27008018

Genome-Scale Analysis of Cell-Specific Regulatory Codes Using Nuclear Enzymes.

Songjoon Baek1, Myong-Hee Sung2,3.   

Abstract

High-throughput sequencing technologies have made it possible for biologists to generate genome-wide profiles of chromatin features at the nucleotide resolution. Enzymes such as nucleases or transposes have been instrumental as a chromatin-probing agent due to their ability to target accessible chromatin for cleavage or insertion. On the scale of a few hundred base pairs, preferential action of the nuclear enzymes on accessible chromatin allows mapping of cell state-specific accessibility in vivo. Such accessible regions contain functionally important regulatory sites, including promoters and enhancers, which undergo active remodeling for cells adapting in a dynamic environment. DNase-seq and the more recent ATAC-seq are two assays that are gaining popularity. Deep sequencing of DNA libraries from these assays, termed genomic footprinting, has been proposed to enable the comprehensive construction of protein occupancy profiles over the genome at the nucleotide level. Recent studies have discovered limitations of genomic footprinting which reduce the scope of detectable proteins. In addition, the identification of putative factors that bind to the observed footprints remains challenging. Despite these caveats, the methodology still presents significant advantages over alternative techniques such as ChIP-seq or FAIRE-seq. Here we describe computational approaches and tools for analysis of chromatin accessibility and genomic footprinting. Proper experimental design and assay-specific data analysis ensure the detection sensitivity and maximize retrievable information. The enzyme-based chromatin profiling approaches represent a powerful and evolving methodology which facilitates our understanding of how the genome is regulated.

Entities:  

Keywords:  ATAC-seq; Chromatin remodeling; Computational genomics; DNase-seq; Genomic footprinting; High-throughput sequencing

Mesh:

Substances:

Year:  2016        PMID: 27008018      PMCID: PMC5142241          DOI: 10.1007/978-1-4939-3578-9_12

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  33 in total

1.  High-resolution genome-wide in vivo footprinting of diverse transcription factors in human cells.

Authors:  Alan P Boyle; Lingyun Song; Bum-Kyu Lee; Darin London; Damian Keefe; Ewan Birney; Vishwanath R Iyer; Gregory E Crawford; Terrence S Furey
Journal:  Genome Res       Date:  2010-11-24       Impact factor: 9.043

2.  Quantitative analysis of genome-wide chromatin remodeling.

Authors:  Songjoon Baek; Myong-Hee Sung; Gordon L Hager
Journal:  Methods Mol Biol       Date:  2012

3.  Genome-scale mapping of DNase I hypersensitivity.

Authors:  Sam John; Peter J Sabo; Theresa K Canfield; Kristen Lee; Shinny Vong; Molly Weaver; Hao Wang; Jeff Vierstra; Alex P Reynolds; Robert E Thurman; John A Stamatoyannopoulos
Journal:  Curr Protoc Mol Biol       Date:  2013-07

4.  F-Seq: a feature density estimator for high-throughput sequence tags.

Authors:  Alan P Boyle; Justin Guinney; Gregory E Crawford; Terrence S Furey
Journal:  Bioinformatics       Date:  2008-09-10       Impact factor: 6.937

Review 5.  Dynamic regulation of transcriptional states by chromatin and transcription factors.

Authors:  Ty C Voss; Gordon L Hager
Journal:  Nat Rev Genet       Date:  2013-12-17       Impact factor: 53.242

6.  Overlapping chromatin-remodeling systems collaborate genome wide at dynamic chromatin transitions.

Authors:  Stephanie A Morris; Songjoon Baek; Myong-Hee Sung; Sam John; Malgorzata Wiench; Thomas A Johnson; R Louis Schiltz; Gordon L Hager
Journal:  Nat Struct Mol Biol       Date:  2013-12-08       Impact factor: 15.369

7.  Refined DNase-seq protocol and data analysis reveals intrinsic bias in transcription factor footprint identification.

Authors:  Housheng Hansen He; Clifford A Meyer; Sheng'en Shawn Hu; Mei-Wei Chen; Chongzhi Zang; Yin Liu; Prakash K Rao; Teng Fei; Han Xu; Henry Long; X Shirley Liu; Myles Brown
Journal:  Nat Methods       Date:  2013-12-08       Impact factor: 28.547

8.  Wellington: a novel method for the accurate identification of digital genomic footprints from DNase-seq data.

Authors:  Jason Piper; Markus C Elze; Pierre Cauchy; Peter N Cockerill; Constanze Bonifer; Sascha Ott
Journal:  Nucleic Acids Res       Date:  2013-09-25       Impact factor: 16.971

9.  Genome accessibility is widely preserved and locally modulated during mitosis.

Authors:  Chris C-S Hsiung; Christapher S Morrissey; Maheshi Udugama; Christopher L Frank; Cheryl A Keller; Songjoon Baek; Belinda Giardine; Gregory E Crawford; Myong-Hee Sung; Ross C Hardison; Gerd A Blobel
Journal:  Genome Res       Date:  2014-11-04       Impact factor: 9.043

10.  An expansive human regulatory lexicon encoded in transcription factor footprints.

Authors:  Shane Neph; Jeff Vierstra; Andrew B Stergachis; Alex P Reynolds; Eric Haugen; Benjamin Vernot; Robert E Thurman; Sam John; Richard Sandstrom; Audra K Johnson; Matthew T Maurano; Richard Humbert; Eric Rynes; Hao Wang; Shinny Vong; Kristen Lee; Daniel Bates; Morgan Diegel; Vaughn Roach; Douglas Dunn; Jun Neri; Anthony Schafer; R Scott Hansen; Tanya Kutyavin; Erika Giste; Molly Weaver; Theresa Canfield; Peter Sabo; Miaohua Zhang; Gayathri Balasundaram; Rachel Byron; Michael J MacCoss; Joshua M Akey; M A Bender; Mark Groudine; Rajinder Kaul; John A Stamatoyannopoulos
Journal:  Nature       Date:  2012-09-06       Impact factor: 49.962

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  6 in total

1.  Anti-Inflammatory Chromatinscape Suggests Alternative Mechanisms of Glucocorticoid Receptor Action.

Authors:  Kyu-Seon Oh; Heta Patel; Rachel A Gottschalk; Wai Shing Lee; Songjoon Baek; Iain D C Fraser; Gordon L Hager; Myong-Hee Sung
Journal:  Immunity       Date:  2017-08-08       Impact factor: 31.745

2.  Bivariate Genomic Footprinting Detects Changes in Transcription Factor Activity.

Authors:  Songjoon Baek; Ido Goldstein; Gordon L Hager
Journal:  Cell Rep       Date:  2017-05-23       Impact factor: 9.423

3.  Transcription factors TCF-1 and GATA3 are key factors for the epigenetic priming of early innate lymphoid progenitors toward distinct cell fates.

Authors:  Gang Ren; Binbin Lai; Christelle Harly; Songjoon Baek; Yi Ding; Mingzhu Zheng; Yaqiang Cao; Kairong Cui; Yu Yang; Jinfang Zhu; Gordon L Hager; Avinash Bhandoola; Keji Zhao
Journal:  Immunity       Date:  2022-07-25       Impact factor: 43.474

Review 4.  Chromatin reprogramming in breast cancer.

Authors:  Erin E Swinstead; Ville Paakinaho; Gordon L Hager
Journal:  Endocr Relat Cancer       Date:  2018-04-24       Impact factor: 5.678

5.  Dual Roles for Ikaros in Regulation of Macrophage Chromatin State and Inflammatory Gene Expression.

Authors:  Kyu-Seon Oh; Rachel A Gottschalk; Nicolas W Lounsbury; Jing Sun; Michael G Dorrington; Songjoon Baek; Guangping Sun; Ze Wang; Kathleen S Krauss; Joshua D Milner; Bhaskar Dutta; Gordon L Hager; Myong-Hee Sung; Iain D C Fraser
Journal:  J Immunol       Date:  2018-06-13       Impact factor: 5.422

Review 6.  How far are the new wave of mRNA drugs from us? mRNA product current perspective and future development.

Authors:  Qiongyu Duan; Tianyu Hu; Qiuxia Zhu; Xueying Jin; Feng Chi; Xiaodong Chen
Journal:  Front Immunol       Date:  2022-09-12       Impact factor: 8.786

  6 in total

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