Literature DB >> 24469817

Identifying and mapping cell-type-specific chromatin programming of gene expression.

Troels T Marstrand1, John D Storey.   

Abstract

A problem of substantial interest is to systematically map variation in chromatin structure to gene-expression regulation across conditions, environments, or differentiated cell types. We developed and applied a quantitative framework for determining the existence, strength, and type of relationship between high-resolution chromatin structure in terms of DNaseI hypersensitivity and genome-wide gene-expression levels in 20 diverse human cell types. We show that ∼25% of genes show cell-type-specific expression explained by alterations in chromatin structure. We find that distal regions of chromatin structure (e.g., ±200 kb) capture more genes with this relationship than local regions (e.g., ±2.5 kb), yet the local regions show a more pronounced effect. By exploiting variation across cell types, we were capable of pinpointing the most likely hypersensitive sites related to cell-type-specific expression, which we show have a range of contextual uses. This quantitative framework is likely applicable to other settings aimed at relating continuous genomic measurements to gene-expression variation.

Entities:  

Keywords:  association; computational biology; encode; epigenetics; gene regulation

Mesh:

Substances:

Year:  2014        PMID: 24469817      PMCID: PMC3926062          DOI: 10.1073/pnas.1312523111

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  57 in total

Review 1.  Next-generation genomics: an integrative approach.

Authors:  R David Hawkins; Gary C Hon; Bing Ren
Journal:  Nat Rev Genet       Date:  2010-07       Impact factor: 53.242

Review 2.  The dominant control region of the human beta-globin domain.

Authors:  F Grosveld; D Greaves; S Philipsen; D Talbot; S Pruzina; E deBoer; O Hanscombe; P Belhumeur; J Hurst; P Fraser
Journal:  Ann N Y Acad Sci       Date:  1990       Impact factor: 5.691

3.  Regulation of interleukin 12 p40 expression through an NF-kappa B half-site.

Authors:  T L Murphy; M G Cleveland; P Kulesza; J Magram; K M Murphy
Journal:  Mol Cell Biol       Date:  1995-10       Impact factor: 4.272

4.  DNaseI hypersensitive sites 1, 2 and 3 of the human beta-globin dominant control region direct position-independent expression.

Authors:  P Fraser; J Hurst; P Collis; F Grosveld
Journal:  Nucleic Acids Res       Date:  1990-06-25       Impact factor: 16.971

5.  Architecture of the human regulatory network derived from ENCODE data.

Authors:  Mark B Gerstein; Anshul Kundaje; Manoj Hariharan; Stephen G Landt; Koon-Kiu Yan; Chao Cheng; Xinmeng Jasmine Mu; Ekta Khurana; Joel Rozowsky; Roger Alexander; Renqiang Min; Pedro Alves; Alexej Abyzov; Nick Addleman; Nitin Bhardwaj; Alan P Boyle; Philip Cayting; Alexandra Charos; David Z Chen; Yong Cheng; Declan Clarke; Catharine Eastman; Ghia Euskirchen; Seth Frietze; Yao Fu; Jason Gertz; Fabian Grubert; Arif Harmanci; Preti Jain; Maya Kasowski; Phil Lacroute; Jing Jane Leng; Jin Lian; Hannah Monahan; Henriette O'Geen; Zhengqing Ouyang; E Christopher Partridge; Dorrelyn Patacsil; Florencia Pauli; Debasish Raha; Lucia Ramirez; Timothy E Reddy; Brian Reed; Minyi Shi; Teri Slifer; Jing Wang; Linfeng Wu; Xinqiong Yang; Kevin Y Yip; Gili Zilberman-Schapira; Serafim Batzoglou; Arend Sidow; Peggy J Farnham; Richard M Myers; Sherman M Weissman; Michael Snyder
Journal:  Nature       Date:  2012-09-06       Impact factor: 49.962

6.  DNase I sensitivity QTLs are a major determinant of human expression variation.

Authors:  Jacob F Degner; Athma A Pai; Roger Pique-Regi; Jean-Baptiste Veyrieras; Daniel J Gaffney; Joseph K Pickrell; Sherryl De Leon; Katelyn Michelini; Noah Lewellen; Gregory E Crawford; Matthew Stephens; Yoav Gilad; Jonathan K Pritchard
Journal:  Nature       Date:  2012-02-05       Impact factor: 49.962

7.  CCAAT box binding protein NF-Y facilitates in vivo recruitment of upstream DNA binding transcription factors.

Authors:  K L Wright; B J Vilen; Y Itoh-Lindstrom; T L Moore; G Li; M Criscitiello; P Cogswell; J B Clarke; J P Ting
Journal:  EMBO J       Date:  1994-09-01       Impact factor: 11.598

8.  An integrated encyclopedia of DNA elements in the human genome.

Authors: 
Journal:  Nature       Date:  2012-09-06       Impact factor: 49.962

9.  The long-range interaction landscape of gene promoters.

Authors:  Amartya Sanyal; Bryan R Lajoie; Gaurav Jain; Job Dekker
Journal:  Nature       Date:  2012-09-06       Impact factor: 49.962

10.  The accessible chromatin landscape of the human genome.

Authors:  Robert E Thurman; Eric Rynes; Richard Humbert; Jeff Vierstra; Matthew T Maurano; Eric Haugen; Nathan C Sheffield; Andrew B Stergachis; Hao Wang; Benjamin Vernot; Kavita Garg; Sam John; Richard Sandstrom; Daniel Bates; Lisa Boatman; Theresa K Canfield; Morgan Diegel; Douglas Dunn; Abigail K Ebersol; Tristan Frum; Erika Giste; Audra K Johnson; Ericka M Johnson; Tanya Kutyavin; Bryan Lajoie; Bum-Kyu Lee; Kristen Lee; Darin London; Dimitra Lotakis; Shane Neph; Fidencio Neri; Eric D Nguyen; Hongzhu Qu; Alex P Reynolds; Vaughn Roach; Alexias Safi; Minerva E Sanchez; Amartya Sanyal; Anthony Shafer; Jeremy M Simon; Lingyun Song; Shinny Vong; Molly Weaver; Yongqi Yan; Zhancheng Zhang; Zhuzhu Zhang; Boris Lenhard; Muneesh Tewari; Michael O Dorschner; R Scott Hansen; Patrick A Navas; George Stamatoyannopoulos; Vishwanath R Iyer; Jason D Lieb; Shamil R Sunyaev; Joshua M Akey; Peter J Sabo; Rajinder Kaul; Terrence S Furey; Job Dekker; Gregory E Crawford; John A Stamatoyannopoulos
Journal:  Nature       Date:  2012-09-06       Impact factor: 49.962

View more
  13 in total

1.  Incorporating chromatin accessibility data into sequence-to-expression modeling.

Authors:  Pei-Chen Peng; Md Abul Hassan Samee; Saurabh Sinha
Journal:  Biophys J       Date:  2015-03-10       Impact factor: 4.033

2.  Modeling the causal regulatory network by integrating chromatin accessibility and transcriptome data.

Authors:  Yong Wang; Rui Jiang; Wing Hung Wong
Journal:  Natl Sci Rev       Date:  2016-04-19       Impact factor: 17.275

3.  Predicting gene expression in massively parallel reporter assays: A comparative study.

Authors:  Anat Kreimer; Haoyang Zeng; Matthew D Edwards; Yuchun Guo; Kevin Tian; Sunyoung Shin; Rene Welch; Michael Wainberg; Rahul Mohan; Nicholas A Sinnott-Armstrong; Yue Li; Gökcen Eraslan; Talal Bin Amin; Ryan Tewhey; Pardis C Sabeti; Jonathan Goke; Nikola S Mueller; Manolis Kellis; Anshul Kundaje; Michael A Beer; Sunduz Keles; David K Gifford; Nir Yosef
Journal:  Hum Mutat       Date:  2017-03-09       Impact factor: 4.878

4.  Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases.

Authors:  Daniel Marbach; David Lamparter; Gerald Quon; Manolis Kellis; Zoltán Kutalik; Sven Bergmann
Journal:  Nat Methods       Date:  2016-03-07       Impact factor: 28.547

Review 5.  Techniques and Approaches to Genetic Analyses in Nephrological Disorders.

Authors:  Laurel K Willig
Journal:  J Pediatr Genet       Date:  2015-08-13

6.  Heat-Triggered Remote Control of CRISPR-dCas9 for Tunable Transcriptional Modulation.

Authors:  Lena Gamboa; Erick V Phung; Haoxin Li; Jared P Meyers; Anna C Hart; Ian C Miller; Gabriel A Kwong
Journal:  ACS Chem Biol       Date:  2020-01-13       Impact factor: 5.100

7.  Functional transcription factor target discovery via compendia of binding and expression profiles.

Authors:  Christopher J Banks; Anagha Joshi; Tom Michoel
Journal:  Sci Rep       Date:  2016-02-09       Impact factor: 4.379

8.  HNF4A defines tissue-specific circadian rhythms by beaconing BMAL1::CLOCK chromatin binding and shaping the rhythmic chromatin landscape.

Authors:  Meng Qu; Han Qu; Zhenyu Jia; Steve A Kay
Journal:  Nat Commun       Date:  2021-11-03       Impact factor: 14.919

9.  Pluripotency, Differentiation, and Reprogramming: A Gene Expression Dynamics Model with Epigenetic Feedback Regulation.

Authors:  Tadashi Miyamoto; Chikara Furusawa; Kunihiko Kaneko
Journal:  PLoS Comput Biol       Date:  2015-08-26       Impact factor: 4.475

10.  Predicting stimulation-dependent enhancer-promoter interactions from ChIP-Seq time course data.

Authors:  Tomasz Dzida; Mudassar Iqbal; Iryna Charapitsa; George Reid; Henk Stunnenberg; Filomena Matarese; Korbinian Grote; Antti Honkela; Magnus Rattray
Journal:  PeerJ       Date:  2017-09-28       Impact factor: 2.984

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.