Literature DB >> 20144209

An effective approach for identification of in vivo protein-DNA binding sites from paired-end ChIP-Seq data.

Congmao Wang1, Jie Xu, Dasheng Zhang, Zoe A Wilson, Dabing Zhang.   

Abstract

BACKGROUND: ChIP-Seq, which combines chromatin immunoprecipitation (ChIP) with high-throughput massively parallel sequencing, is increasingly being used for identification of protein-DNA interactions in vivo in the genome. However, to maximize the effectiveness of data analysis of such sequences requires the development of new algorithms that are able to accurately predict DNA-protein binding sites.
RESULTS: Here, we present SIPeS (Site Identification from Paired-end Sequencing), a novel algorithm for precise identification of binding sites from short reads generated by paired-end solexa ChIP-Seq technology. In this paper we used ChIP-Seq data from the Arabidopsis basic helix-loop-helix transcription factor ABORTED MICROSPORES (AMS), which is expressed within the anther during pollen development, the results show that SIPeS has better resolution for binding site identification compared to two existing ChIP-Seq peak detection algorithms, Cisgenome and MACS.
CONCLUSIONS: When compared to Cisgenome and MACS, SIPeS shows better resolution for binding site discovery. Moreover, SIPeS is designed to calculate the mappable genome length accurately with the fragment length based on the paired-end reads. Dynamic baselines are also employed to effectively discriminate closely adjacent binding sites, for effective binding sites discovery, which is of particular value when working with high-density genomes.

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Year:  2010        PMID: 20144209      PMCID: PMC2831849          DOI: 10.1186/1471-2105-11-81

Source DB:  PubMed          Journal:  BMC Bioinformatics        ISSN: 1471-2105            Impact factor:   3.169


  21 in total

1.  Genome-wide location and function of DNA binding proteins.

Authors:  B Ren; F Robert; J J Wyrick; O Aparicio; E G Jennings; I Simon; J Zeitlinger; J Schreiber; N Hannett; E Kanin; T L Volkert; C J Wilson; S P Bell; R A Young
Journal:  Science       Date:  2000-12-22       Impact factor: 47.728

2.  The ABORTED MICROSPORES regulatory network is required for postmeiotic male reproductive development in Arabidopsis thaliana.

Authors:  Jie Xu; Caiyun Yang; Zheng Yuan; Dasheng Zhang; Martha Y Gondwe; Zhiwen Ding; Wanqi Liang; Dabing Zhang; Zoe A Wilson
Journal:  Plant Cell       Date:  2010-01-29       Impact factor: 11.277

3.  High-resolution profiling of histone methylations in the human genome.

Authors:  Artem Barski; Suresh Cuddapah; Kairong Cui; Tae-Young Roh; Dustin E Schones; Zhibin Wang; Gang Wei; Iouri Chepelev; Keji Zhao
Journal:  Cell       Date:  2007-05-18       Impact factor: 41.582

4.  The Arabidopsis ABORTED MICROSPORES (AMS) gene encodes a MYC class transcription factor.

Authors:  Anna-Marie Sorensen; Sandra Kröber; Ulrike S Unte; Peter Huijser; Koen Dekker; Heinz Saedler
Journal:  Plant J       Date:  2003-01       Impact factor: 6.417

5.  An efficient chromatin immunoprecipitation (ChIP) protocol for studying histone modifications in Arabidopsis plants.

Authors:  Abdelaty Saleh; Raúl Alvarez-Venegas; Zoya Avramova
Journal:  Nat Protoc       Date:  2008       Impact factor: 13.491

6.  Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing.

Authors:  Gordon Robertson; Martin Hirst; Matthew Bainbridge; Misha Bilenky; Yongjun Zhao; Thomas Zeng; Ghia Euskirchen; Bridget Bernier; Richard Varhol; Allen Delaney; Nina Thiessen; Obi L Griffith; Ann He; Marco Marra; Michael Snyder; Steven Jones
Journal:  Nat Methods       Date:  2007-06-11       Impact factor: 28.547

7.  Genome-wide mapping of in vivo protein-DNA interactions.

Authors:  David S Johnson; Ali Mortazavi; Richard M Myers; Barbara Wold
Journal:  Science       Date:  2007-05-31       Impact factor: 47.728

8.  Genome-wide maps of chromatin state in pluripotent and lineage-committed cells.

Authors:  Tarjei S Mikkelsen; Manching Ku; David B Jaffe; Biju Issac; Erez Lieberman; Georgia Giannoukos; Pablo Alvarez; William Brockman; Tae-Kyung Kim; Richard P Koche; William Lee; Eric Mendenhall; Aisling O'Donovan; Aviva Presser; Carsten Russ; Xiaohui Xie; Alexander Meissner; Marius Wernig; Rudolf Jaenisch; Chad Nusbaum; Eric S Lander; Bradley E Bernstein
Journal:  Nature       Date:  2007-07-01       Impact factor: 49.962

9.  FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology.

Authors:  Anthony P Fejes; Gordon Robertson; Mikhail Bilenky; Richard Varhol; Matthew Bainbridge; Steven J M Jones
Journal:  Bioinformatics       Date:  2008-07-03       Impact factor: 6.937

10.  Genome-wide identification of in vivo protein-DNA binding sites from ChIP-Seq data.

Authors:  Raja Jothi; Suresh Cuddapah; Artem Barski; Kairong Cui; Keji Zhao
Journal:  Nucleic Acids Res       Date:  2008-08-06       Impact factor: 16.971

View more
  10 in total

1.  A functional and evolutionary perspective on transcription factor binding in Arabidopsis thaliana.

Authors:  Ken S Heyndrickx; Jan Van de Velde; Congmao Wang; Detlef Weigel; Klaas Vandepoele
Journal:  Plant Cell       Date:  2014-10-31       Impact factor: 11.277

2.  Ritornello: high fidelity control-free chromatin immunoprecipitation peak calling.

Authors:  Kelly P Stanton; Jiaqi Jin; Roy R Lederman; Sherman M Weissman; Yuval Kluger
Journal:  Nucleic Acids Res       Date:  2017-12-01       Impact factor: 16.971

3.  Evaluation of algorithm performance in ChIP-seq peak detection.

Authors:  Elizabeth G Wilbanks; Marc T Facciotti
Journal:  PLoS One       Date:  2010-07-08       Impact factor: 3.240

4.  Detection and removal of biases in the analysis of next-generation sequencing reads.

Authors:  Schraga Schwartz; Ram Oren; Gil Ast
Journal:  PLoS One       Date:  2011-01-31       Impact factor: 3.240

5.  ZINBA integrates local covariates with DNA-seq data to identify broad and narrow regions of enrichment, even within amplified genomic regions.

Authors:  Naim U Rashid; Paul G Giresi; Joseph G Ibrahim; Wei Sun; Jason D Lieb
Journal:  Genome Biol       Date:  2011-07-25       Impact factor: 13.583

6.  Depletion of Arabidopsis SC35 and SC35-like serine/arginine-rich proteins affects the transcription and splicing of a subset of genes.

Authors:  Qingqing Yan; Xi Xia; Zhenfei Sun; Yuda Fang
Journal:  PLoS Genet       Date:  2017-03-08       Impact factor: 5.917

7.  dPeak: high resolution identification of transcription factor binding sites from PET and SET ChIP-Seq data.

Authors:  Dongjun Chung; Dan Park; Kevin Myers; Jeffrey Grass; Patricia Kiley; Robert Landick; Sündüz Keleş
Journal:  PLoS Comput Biol       Date:  2013-10-17       Impact factor: 4.475

8.  Practical guidelines for the comprehensive analysis of ChIP-seq data.

Authors:  Timothy Bailey; Pawel Krajewski; Istvan Ladunga; Celine Lefebvre; Qunhua Li; Tao Liu; Pedro Madrigal; Cenny Taslim; Jie Zhang
Journal:  PLoS Comput Biol       Date:  2013-11-14       Impact factor: 4.475

9.  CMT: a constrained multi-level thresholding approach for ChIP-Seq data analysis.

Authors:  Iman Rezaeian; Luis Rueda
Journal:  PLoS One       Date:  2014-04-15       Impact factor: 3.240

Review 10.  A survey of motif finding Web tools for detecting binding site motifs in ChIP-Seq data.

Authors:  Ngoc Tam L Tran; Chun-Hsi Huang
Journal:  Biol Direct       Date:  2014-02-20       Impact factor: 4.540

  10 in total

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