Literature DB >> 16722805

Genome-wide analysis of protein-DNA interactions.

Tae Hoon Kim1, Bing Ren.   

Abstract

The human genome is predominantly composed of nonprotein-coding sequences whose function remains largely undefined. A significant portion of the noncoding DNA is believed to serve as transcriptional regulatory elements that control gene expression in specific cell types at appropriate developmental stages. Identifying these regulatory sequences and determining the mechanisms by which they act present a great challenge in the postgenomic era. Previous investigations using genetic, molecular, and biochemical approaches have uncovered a large number of proteins involved in regulating transcription. Knowledge of the genomic locations of DNA binding for these proteins in the nucleus should define the identity and nature of the transcriptional regulatory sequences and reveal the gene regulatory networks in cells. Chromatin immunoprecipitation (ChIP) is a common method for detecting interactions between a protein and a DNA sequence in vivo. In recent years, this method has been combined with DNA microarrays and other high-throughput technologies to enable genome-wide identification of DNA-binding sites for various nuclear proteins. Here, we review recent advances in ChIP-based methods for genome-wide detection of protein-DNA interactions, and discuss their significance in enhancing our knowledge of the gene regulatory networks and epigenetic mechanisms in cells.

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Year:  2006        PMID: 16722805     DOI: 10.1146/annurev.genom.7.080505.115634

Source DB:  PubMed          Journal:  Annu Rev Genomics Hum Genet        ISSN: 1527-8204            Impact factor:   8.929


  74 in total

1.  A computational pipeline for comparative ChIP-seq analyses.

Authors:  Anaïs F Bardet; Qiye He; Julia Zeitlinger; Alexander Stark
Journal:  Nat Protoc       Date:  2011-12-15       Impact factor: 13.491

Review 2.  DNA-protein interactions: methods for detection and analysis.

Authors:  Bipasha Dey; Sameer Thukral; Shruti Krishnan; Mainak Chakrobarty; Sahil Gupta; Chanchal Manghani; Vibha Rani
Journal:  Mol Cell Biochem       Date:  2012-03-08       Impact factor: 3.396

3.  Discover regulatory DNA elements using chromatin signatures and artificial neural network.

Authors:  Hiram A Firpi; Duygu Ucar; Kai Tan
Journal:  Bioinformatics       Date:  2010-05-07       Impact factor: 6.937

4.  Genome-wide profiling of the core clock protein BMAL1 targets reveals a strict relationship with metabolism.

Authors:  Fumiyuki Hatanaka; Chiaki Matsubara; Jihwan Myung; Takashi Yoritaka; Naoko Kamimura; Shuichi Tsutsumi; Akinori Kanai; Yutaka Suzuki; Paolo Sassone-Corsi; Hiroyuki Aburatani; Sumio Sugano; Toru Takumi
Journal:  Mol Cell Biol       Date:  2010-10-11       Impact factor: 4.272

5.  Genome-wide mapping and analysis of active promoters in mouse embryonic stem cells and adult organs.

Authors:  Leah O Barrera; Zirong Li; Andrew D Smith; Karen C Arden; Webster K Cavenee; Michael Q Zhang; Roland D Green; Bing Ren
Journal:  Genome Res       Date:  2007-11-27       Impact factor: 9.043

6.  Systematic evaluation of variability in ChIP-chip experiments using predefined DNA targets.

Authors:  David S Johnson; Wei Li; D Benjamin Gordon; Arindam Bhattacharjee; Bo Curry; Jayati Ghosh; Leonardo Brizuela; Jason S Carroll; Myles Brown; Paul Flicek; Christoph M Koch; Ian Dunham; Mark Bieda; Xiaoqin Xu; Peggy J Farnham; Philipp Kapranov; David A Nix; Thomas R Gingeras; Xinmin Zhang; Heather Holster; Nan Jiang; Roland D Green; Jun S Song; Scott A McCuine; Elizabeth Anton; Loan Nguyen; Nathan D Trinklein; Zhen Ye; Keith Ching; David Hawkins; Bing Ren; Peter C Scacheri; Joel Rozowsky; Alexander Karpikov; Ghia Euskirchen; Sherman Weissman; Mark Gerstein; Michael Snyder; Annie Yang; Zarmik Moqtaderi; Heather Hirsch; Hennady P Shulha; Yutao Fu; Zhiping Weng; Kevin Struhl; Richard M Myers; Jason D Lieb; X Shirley Liu
Journal:  Genome Res       Date:  2008-02-07       Impact factor: 9.043

7.  Chromatin structure analyses identify miRNA promoters.

Authors:  Fatih Ozsolak; Laura L Poling; Zhengxin Wang; Hui Liu; X Shirley Liu; Robert G Roeder; Xinmin Zhang; Jun S Song; David E Fisher
Journal:  Genes Dev       Date:  2008-11-15       Impact factor: 11.361

8.  SND1 transcription factor-directed quantitative functional hierarchical genetic regulatory network in wood formation in Populus trichocarpa.

Authors:  Ying-Chung Lin; Wei Li; Ying-Hsuan Sun; Sapna Kumari; Hairong Wei; Quanzi Li; Sermsawat Tunlaya-Anukit; Ronald R Sederoff; Vincent L Chiang
Journal:  Plant Cell       Date:  2013-11-26       Impact factor: 11.277

9.  Bayesian network analysis of targeting interactions in chromatin.

Authors:  Bas van Steensel; Ulrich Braunschweig; Guillaume J Filion; Menzies Chen; Joke G van Bemmel; Trey Ideker
Journal:  Genome Res       Date:  2009-12-09       Impact factor: 9.043

Review 10.  How eukaryotic genes are transcribed.

Authors:  Bryan J Venters; B Franklin Pugh
Journal:  Crit Rev Biochem Mol Biol       Date:  2009-06       Impact factor: 8.250

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