Literature DB >> 33975951

Discovering unknown human and mouse transcription factor binding sites and their characteristics from ChIP-seq data.

Chun-Ping Yu1, Chen-Hao Kuo1, Chase W Nelson1,2, Chi-An Chen1, Zhi Thong Soh1, Jinn-Jy Lin1, Ru-Xiu Hsiao1, Chih-Yao Chang1, Wen-Hsiung Li3,4.   

Abstract

Transcription factor binding sites (TFBSs) are essential for gene regulation, but the number of known TFBSs remains limited. We aimed to discover and characterize unknown TFBSs by developing a computational pipeline for analyzing ChIP-seq (chromatin immunoprecipitation followed by sequencing) data. Applying it to the latest ENCODE ChIP-seq data for human and mouse, we found that using the irreproducible discovery rate as a quality-control criterion resulted in many experiments being unnecessarily discarded. By contrast, the number of motif occurrences in ChIP-seq peak regions provides a highly effective criterion, which is reliable even if supported by only one experimental replicate. In total, we obtained 2,058 motifs from 1,089 experiments for 354 human TFs and 163 motifs from 101 experiments for 34 mouse TFs. Among these motifs, 487 have not previously been reported. Mapping the canonical motifs to the human genome reveals a high TFBS density ±2 kb around transcription start sites (TSSs) with a peak at -50 bp. On average, a promoter contains 5.7 TFBSs. However, 70% of TFBSs are in introns (41%) and intergenic regions (29%), whereas only 12% are in promoters (-1 kb to +100 bp from TSSs). Notably, some TFs (e.g., CTCF, JUN, JUNB, and NFE2) have motifs enriched in intergenic regions, including enhancers. We inferred 142 cobinding TF pairs and 186 (including 115 completely) tethered binding TF pairs, indicating frequent interactions between TFs and a higher frequency of tethered binding than cobinding. This study provides a large number of previously undocumented motifs and insights into the biological and genomic features of TFBSs.

Entities:  

Keywords:  ChIP-seq; binding site; position weight matrix; promoter; transcription factor

Mesh:

Substances:

Year:  2021        PMID: 33975951      PMCID: PMC8158016          DOI: 10.1073/pnas.2026754118

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


  34 in total

1.  Cytoscape: a software environment for integrated models of biomolecular interaction networks.

Authors:  Paul Shannon; Andrew Markiel; Owen Ozier; Nitin S Baliga; Jonathan T Wang; Daniel Ramage; Nada Amin; Benno Schwikowski; Trey Ideker
Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

2.  Compact, universal DNA microarrays to comprehensively determine transcription-factor binding site specificities.

Authors:  Michael F Berger; Anthony A Philippakis; Aaron M Qureshi; Fangxue S He; Preston W Estep; Martha L Bulyk
Journal:  Nat Biotechnol       Date:  2006-09-24       Impact factor: 54.908

3.  Defining the sequence specificity of DNA-binding proteins by selecting binding sites from random-sequence oligonucleotides: analysis of yeast GCN4 protein.

Authors:  A R Oliphant; C J Brandl; K Struhl
Journal:  Mol Cell Biol       Date:  1989-07       Impact factor: 4.272

4.  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

5.  An atlas of active enhancers across human cell types and tissues.

Authors:  Robin Andersson; Claudia Gebhard; Michael Rehli; Albin Sandelin; Irene Miguel-Escalada; Ilka Hoof; Jette Bornholdt; Mette Boyd; Yun Chen; Xiaobei Zhao; Christian Schmidl; Takahiro Suzuki; Evgenia Ntini; Erik Arner; Eivind Valen; Kang Li; Lucia Schwarzfischer; Dagmar Glatz; Johanna Raithel; Berit Lilje; Nicolas Rapin; Frederik Otzen Bagger; Mette Jørgensen; Peter Refsing Andersen; Nicolas Bertin; Owen Rackham; A Maxwell Burroughs; J Kenneth Baillie; Yuri Ishizu; Yuri Shimizu; Erina Furuhata; Shiori Maeda; Yutaka Negishi; Christopher J Mungall; Terrence F Meehan; Timo Lassmann; Masayoshi Itoh; Hideya Kawaji; Naoto Kondo; Jun Kawai; Andreas Lennartsson; Carsten O Daub; Peter Heutink; David A Hume; Torben Heick Jensen; Harukazu Suzuki; Yoshihide Hayashizaki; Ferenc Müller; Alistair R R Forrest; Piero Carninci
Journal:  Nature       Date:  2014-03-27       Impact factor: 49.962

6.  ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia.

Authors:  Stephen G Landt; Georgi K Marinov; Anshul Kundaje; Pouya Kheradpour; Florencia Pauli; Serafim Batzoglou; Bradley E Bernstein; Peter Bickel; James B Brown; Philip Cayting; Yiwen Chen; Gilberto DeSalvo; Charles Epstein; Katherine I Fisher-Aylor; Ghia Euskirchen; Mark Gerstein; Jason Gertz; Alexander J Hartemink; Michael M Hoffman; Vishwanath R Iyer; Youngsook L Jung; Subhradip Karmakar; Manolis Kellis; Peter V Kharchenko; Qunhua Li; Tao Liu; X Shirley Liu; Lijia Ma; Aleksandar Milosavljevic; Richard M Myers; Peter J Park; Michael J Pazin; Marc D Perry; Debasish Raha; Timothy E Reddy; Joel Rozowsky; Noam Shoresh; Arend Sidow; Matthew Slattery; John A Stamatoyannopoulos; Michael Y Tolstorukov; Kevin P White; Simon Xi; Peggy J Farnham; Jason D Lieb; Barbara J Wold; Michael Snyder
Journal:  Genome Res       Date:  2012-09       Impact factor: 9.043

7.  MEME-ChIP: motif analysis of large DNA datasets.

Authors:  Philip Machanick; Timothy L Bailey
Journal:  Bioinformatics       Date:  2011-04-12       Impact factor: 6.937

8.  A novel alignment-free method for comparing transcription factor binding site motifs.

Authors:  Minli Xu; Zhengchang Su
Journal:  PLoS One       Date:  2010-01-20       Impact factor: 3.240

9.  Identification of C2H2-ZF binding preferences from ChIP-seq data using RCADE.

Authors:  Hamed S Najafabadi; Mihai Albu; Timothy R Hughes
Journal:  Bioinformatics       Date:  2015-05-06       Impact factor: 6.937

10.  Expanded encyclopaedias of DNA elements in the human and mouse genomes.

Authors:  Jill E Moore; Michael J Purcaro; Henry E Pratt; Charles B Epstein; Noam Shoresh; Jessika Adrian; Trupti Kawli; Carrie A Davis; Alexander Dobin; Rajinder Kaul; Jessica Halow; Eric L Van Nostrand; Peter Freese; David U Gorkin; Yin Shen; Yupeng He; Mark Mackiewicz; Florencia Pauli-Behn; Brian A Williams; Ali Mortazavi; Cheryl A Keller; Xiao-Ou Zhang; Shaimae I Elhajjajy; Jack Huey; Diane E Dickel; Valentina Snetkova; Xintao Wei; Xiaofeng Wang; Juan Carlos Rivera-Mulia; Joel Rozowsky; Jing Zhang; Surya B Chhetri; Jialing Zhang; Alec Victorsen; Kevin P White; Axel Visel; Gene W Yeo; Christopher B Burge; Eric Lécuyer; David M Gilbert; Job Dekker; John Rinn; Eric M Mendenhall; Joseph R Ecker; Manolis Kellis; Robert J Klein; William S Noble; Anshul Kundaje; Roderic Guigó; Peggy J Farnham; J Michael Cherry; Richard M Myers; Bing Ren; Brenton R Graveley; Mark B Gerstein; Len A Pennacchio; Michael P Snyder; Bradley E Bernstein; Barbara Wold; Ross C Hardison; Thomas R Gingeras; John A Stamatoyannopoulos; Zhiping Weng
Journal:  Nature       Date:  2020-07-29       Impact factor: 69.504

View more
  2 in total

1.  Stroke-associated intergenic variants modulate a human FOXF2 transcriptional enhancer.

Authors:  Jae-Ryeon Ryu; Suchit Ahuja; Corey R Arnold; Kyle G Potts; Aniket Mishra; Qiong Yang; Muralidharan Sargurupremraj; Douglas J Mahoney; Sudha Seshadri; Stéphanie Debette; Sarah J Childs
Journal:  Proc Natl Acad Sci U S A       Date:  2022-08-22       Impact factor: 12.779

2.  Motif models proposing independent and interdependent impacts of nucleotides are related to high and low affinity transcription factor binding sites in Arabidopsis.

Authors:  Anton V Tsukanov; Victoria V Mironova; Victor G Levitsky
Journal:  Front Plant Sci       Date:  2022-07-28       Impact factor: 6.627

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.