Abstract
Chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-seq) is a new technology to map protein–DNA interactions in a genome. The genome-wide transcription factor binding site and chromatin modification data produced by ChIP-seq provide invaluable information for studying gene regulation. This chapter reviews basic characteristics of ChIP-seq data and introduces a computational procedure to identify protein–DNA interactions from ChIP-seq experiments.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Johnson, D.S., Mortazavi, A., Myers, R.M., and Wold, B. (2007) Genome-wide mapping of in vivo protein-DNA interactions. Science 316, 1497–1502.
Robertson, G., Hirst, M., Bainbridge, M. et al. (2007) Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing. Nat Methods 4, 651–657.
Mikkelsen, T.S., Ku, M., Jaffe, D.B. et al. (2007) Genome-wide maps of chromatin state in pluripotent and lineage-committed cells. Nature 448, 553–560.
Barski, A., Cuddapah, S., Cui, K. et al. (2007) High-resolution profiling of histone methylations in the human genome. Cell 129, 823–837.
Shendure, J., and Ji, H. (2008) Next-generation DNA sequencing. Nat Biotechnol 26, 1135–1145.
Ren, B., Robert, F., Wyrick, J.J. et al. (2000) Genome-wide location and function of DNA binding proteins. Science 290, 2306–2309.
Cawley, S., Bekiranov, S., Ng, H.H. et al. (2004) Unbiased mapping of transcription factor binding sites along human chromosomes 21 and 22 points to widespread regulation of noncoding RNAs. Cell 116, 499–509.
Park, P.J. (2009) ChIP-seq: advantages and challenges of a maturing technology. Nat Rev Genet 10, 669–680.
Ji, H., Jiang, H., Ma, W. et al. (2008) An integrated software system for analyzing ChIP-chip and ChIP-seq data. Nat Biotechnol 26, 1293–1300.
Rozowsky, J., Euskirchen, G., Auerbach, R.K. et al. (2009) PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls. Nat Biotechnol 27, 66–75.
Kharchenko, P.V., Tolstorukov, M.Y., and Park, P.J. (2008) Design and analysis of ChIP-seq experiments for DNA-binding proteins. Nat Biotechnol 26, 1351–1359.
Marson, A., Levine, S.S., Cole, M.F. et al. (2008) Connecting microRNA genes to the core transcriptional regulatory circuitry of embryonic stem cells. Cell 134, 521–533.
Schmid, C.D., and Bucher, P. (2007) ChIP-Seq data reveal nucleosome architecture of human promoters. Cell 131, 831–832.
Valouev, A., Johnson, D.S., Sundquist, A. et al. (2008) Genome-wide analysis of transcription factor binding sites based on ChIP-seq data. Nat Methods 5, 829–834.
Zhang, Y., Liu, T., Meyer, C.A. et al. (2008) Model-based analysis of ChIP-seq (MACS). Genome Biol 9, R137.
Jothi, R., Cuddapah, S., Barski, A., Cui, K., and Zhao, K. (2008) Genome-wide identification of in vivo protein-DNA binding sites from ChIP-seq data. Nucleic Acids Res 36, 5221–5231.
Langmead, B., Trapnell, C., Pop, M., and Salzberg, S.L. (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10, R25.
Li, H., Ruan, J., and Durbin, R. (2008) Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res 18, 1851–1858.
Jiang, H., and Wong, W.H. (2008) SeqMap : mapping massive amount of oligonucleotides to the genome. Bioinformatics 24, 2395–2396.
Rumble, S.M., Lacroute, P., Dalca, A.V. et al. (2009) SHRiMP: accurate mapping of short color-space reads. PLoS Comput Biol 5, e1000386.
Subramanian, A., Tamayo, P., Mootha, V.K. et al. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102, 15545–15550.
Kent, W.J., Sugnet, C.W., Furey, T.S. et al. (2002) The human genome browser at UCSC. Genome Res 12, 996–1006.
Smyth, G.K. (2004) Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 3, 1–9 (Article 3).
Fejes, A.P., Robertson, G., Bilenky, M. et al. (2008) FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology. Bioinformatics 24, 1729–1730.
Nix, D.A., Courdy, S.J., and Boucher, K.M. (2008) Empirical methods for controlling false positives and estimating confidence in ChIP-seq peaks. BMC Bioinformatics 9, 523.
Ji, H., Vokes, S.A., and Wong, W.H. (2006) A comparative analysis of genome-wide chromatin immunoprecipitation data for mammalian transcription factors. Nucleic Acids Res 34, e146.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media, LLC
About this protocol
Cite this protocol
Ji, H. (2010). Computational Analysis of ChIP-seq Data. In: Ladunga, I. (eds) Computational Biology of Transcription Factor Binding. Methods in Molecular Biology, vol 674. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60761-854-6_9
Download citation
DOI: https://doi.org/10.1007/978-1-60761-854-6_9
Published:
Publisher Name: Humana Press, Totowa, NJ
Print ISBN: 978-1-60761-853-9
Online ISBN: 978-1-60761-854-6
eBook Packages: Springer Protocols