title: MACE: model based analysis of ChIP-exo.
abstract: Understanding the role of a given transcription factor (TF) in regulating gene expression requires precise mapping of its binding sites in the genome. Chromatin immunoprecipitation-exo, an emerging technique using λ exonuclease to digest TF unbound DNA after ChIP, is designed to reveal transcription factor binding site (TFBS) boundaries with near-single nucleotide resolution. Although ChIP-exo promises deeper insights into transcription regulation, no dedicated bioinformatics tool exists to leverage its advantages. Most ChIP-seq and ChIP-chip analytic methods are not tailored for ChIP-exo, and thus cannot take full advantage of high-resolution ChIP-exo data. Here we describe a novel analysis framework, termed MACE (model-based analysis of ChIP-exo) dedicated to ChIP-exo data analysis. The MACE workflow consists of four steps: (i) sequencing data normalization and bias correction; (ii) signal consolidation and noise reduction; (iii) single-nucleotide resolution border peak detection using the Chebyshev Inequality and (iv) border matching using the Gale-Shapley stable matching algorithm. When applied to published human CTCF, yeast Reb1 and our own mouse ONECUT1/HNF6 ChIP-exo data, MACE is able to define TFBSs with high sensitivity, specificity and spatial resolution, as evidenced by multiple criteria including motif enrichment, sequence conservation, direct sequence pileup, nucleosome positioning and open chromatin states. In addition, we show that the fundamental advance of MACE is the identification of two boundaries of a TFBS with high resolution, whereas other methods only report a single location of the same event. The two boundaries help elucidate the in vivo binding structure of a given TF, e.g. whether the TF may bind as dimers or in a complex with other co-factors.
authors.affiliation: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA Division of Biostatistics, Dan L. Duncan Cancer Center and Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA wl1@bcm.edu.
authors.forename: Liguo
authors.initials: L
authors.lastname: Wang
authors.affiliation: School of Life Science and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Junsheng
authors.initials: J
authors.lastname: Chen
authors.affiliation: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA.
authors.forename: Chen
authors.initials: C
authors.lastname: Wang
authors.affiliation: Genetics & Genome Biology Program, SickKids Research Institute, 686 Bay St. Toronto, ON, M5G 0A4, Canada.
authors.forename: Liis
authors.initials: L
authors.lastname: Uusküla-Reimand
authors.affiliation: Division of Biostatistics, Dan L. Duncan Cancer Center and Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA.
authors.forename: Kaifu
authors.initials: K
authors.lastname: Chen
authors.affiliation: Genetics & Genome Biology Program, SickKids Research Institute, 686 Bay St. Toronto, ON, M5G 0A4, Canada.
authors.forename: Alejandra
authors.initials: A
authors.lastname: Medina-Rivera
authors.affiliation: Genetics & Genome Biology Program, SickKids Research Institute, 686 Bay St. Toronto, ON, M5G 0A4, Canada.
authors.forename: Edwin J
authors.initials: EJ
authors.lastname: Young
authors.affiliation: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA.
authors.forename: Michael T
authors.initials: MT
authors.lastname: Zimmermann
authors.affiliation: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA.
authors.forename: Huihuang
authors.initials: H
authors.lastname: Yan
authors.affiliation: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA.
authors.forename: Zhifu
authors.initials: Z
authors.lastname: Sun
authors.affiliation: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA.
authors.forename: Yuji
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA.
authors.forename: Stephen T
authors.initials: ST
authors.lastname: Wu
authors.affiliation: Department of Biochemistry and Molecular Biology, Mayo Clinic, MN 55905, USA.
authors.forename: Haojie
authors.initials: H
authors.lastname: Huang
authors.affiliation: Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S1A8, Canada.
authors.forename: Michael D
authors.initials: MD
authors.lastname: Wilson
authors.affiliation: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, USA wl1@bcm.edu.
authors.forename: Jean-Pierre A
authors.initials: JP
authors.lastname: Kocher
authors.affiliation: Division of Biostatistics, Dan L. Duncan Cancer Center and Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA wl1@bcm.edu.
authors.forename: Wei
authors.initials: W
authors.lastname: Li
mesh_terms: D000465:Algorithms; D000818:Animals; D001665:Binding Sites; D000076246:CCCTC-Binding Factor; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D003198:Computer Simulation; D004268:DNA-Binding Proteins / Q000378:metabolism; D005090:Exodeoxyribonucleases; D016678:Genome; D051559:Hepatocyte Nuclear Factor 6 / Q000378:metabolism; D006801:Humans; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D012097:Repressor Proteins / Q000378:metabolism; D029701:Saccharomyces cerevisiae Proteins / Q000378:metabolism; D017422:Sequence Analysis, DNA / Q000379:methods*; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D000076246:CCCTC-Binding Factor; C000619697:CTCF protein, human; C000619698:Ctcf protein, mouse; D004268:DNA-Binding Proteins; D051559:Hepatocyte Nuclear Factor 6; C496606:Onecut1 protein, mouse; C065681:REB1 protein, S cerevisiae; D012097:Repressor Proteins; D029701:Saccharomyces cerevisiae Proteins; D014157:Transcription Factors; D005090:Exodeoxyribonucleases