Abstract
Half of all human transcription factors are zinc finger proteins and yet very little is known concerning the biological role of the majority of these factors. In particular, very few genome-wide studies of the in vivo binding of zinc finger factors have been performed. Based on in vitro studies and other methods that allow selection of high affinity-binding sites in artificial conditions, a zinc finger code has been developed that can be used to compose a putative recognition motif for a particular zinc finger factor (ZNF). Theoretically, a simple bioinformatics analysis could then predict the genomic locations of all the binding sites for that ZNF. However, it is unlikely that all of the sequences in the human genome having a good match to a predicted motif are in fact occupied in vivo (due to negative influences from repressive chromatin, nucleosomal positioning, overlap of binding sites with other factors, etc). A powerful method to identify in vivo binding sites for transcription factors on a genome-wide scale is the chromatin immunoprecipitation (ChIP) assay, followed by hybridization of the precipitated DNA to microarrays (ChIP-chip) or by high throughput DNA sequencing of the sample (ChIP-seq). Such comprehensive in vivo binding studies would not only identify target genes of a particular zinc finger factor, but also provide binding motif data that could be used to test the validity of the zinc finger code. This chapter describes in detail the steps needed to prepare ChIP samples and libraries for high throughput sequencing using the Illumina GA2 platform and includes descriptions of quality control steps necessary to ensure a successful ChIP-seq experiment.
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
Emerson, R.O. and Thomas, J.H. (2008) Adaptive evolution in zinc finger transcription factors. PLOS Genet. 5, e1000325.
Liu, J. and Stormo, G.D. (2008) Context-dependent DNA recognition code for C2H2 zinc-finger transcription factors. Bioinformatics. 24, 1850–1857.
Cho, S.Y., Chung, M., Park, M., Park, S., and Lee, Y.S. (2008) ZIFIBI: prediction of DNA binding sites for zinc finger proteins. BBRC. 369, 845–848.
Segal, D.J. and Barbas, C.F., 3rd (1999) Design of novel sequence-specific DNA-binding proteins. Curr Opin Chem Biol. 4, 34–39.
Weinmann, A.S., Yan, P.S., Oberley, M.J., Huang, T.H.-M., and Farnham, P.J. (2002) Isolating human transcription factor targets by coupling chromatin immunoprecipitation and CpG island microarray analysis. Genes Dev. 16, 235–244.
Johnson, D.S., Li, W., Gordon, D.B., Bhattacharjee, A., Curry, B., Ghosh, J., Brizuela, L., Carroll, J.S., Brown, M., Flicek, P., Koch, C.M., Dunham, I., Bieda, M., et al. (2008) Systematic evaluation of variability in ChIP-chip experiments using predefined DNA targets. Genome Res. 18, 393–403.
Kirmizis, A., Bartley, S.M., Kuzmichev, A., Margueron, R., Reinberg, D., Green, R., and Farnham, P.J. (2004) Silencing of human polycomb target genes is associated with methylation of histone H3 lysine 27. Genes Dev. 18, 1592–1605.
Kim, T.H., Barrera, L.O., Zheng, M., Qu, C., Singer, M.A., Richmond, T.A., Wu, Y., Green, R.D., and Ren, B. (2005) A high-resolution map of active promoters in the human genome. Nature. 436, 876–880.
Cawley, S., Bekiranov, S., Ng, H.H., Kapranov, P., Sekinger, E.A., Kampa, D., Piccolboni, A., Sementchenko, V., Cheng, J., Williams, A.J., Wheeler, R., Wong, B., Drenkow, J., Yamanaka, M., Patel, S., Brubaker, S., Tammana, H., Helt, G., Struhl, K., and Gingeras, T.R. (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.
Carroll, J.S., Liu, X.S., Brodsky, A.S., Li, W., Meyer, C.A., Szary, A.J., Eeckhoute, J., Shao, W., Hestermann, E.V., Geistlinger, T.R., Fox, E.A., Silver, P.A., and Brown, M. (2005) Chromosome-wide mapping of estrogen receptor binding reveals long-range regulation requiring the forkhead protein FoxA1. Cell. 122, 33–43.
Hoffman, B.G. and Jones, S.J. (2009) Genome-wide identification of DNA-protein interactions using chromatin immunoprecipitation coupled with flow cell sequencing. J Endocrinol. 201, 1–13.
Weinmann, A.S., Bartley, S.M., Zhang, M.Q., Zhang, T., and Farnham, P.J. (2001) The use of chromatin immunoprecipitation to clone novel E2F target promoters. Mol Cell Biol. 21, 6820–6832.
Loh, Y.-H., Wu, Q., Chew, J.-L., Vega, V.B., Zhang, W., Chen, X., Bourque, G., George, J., Leong, B., Liu, J., Wong, K.-Y., Sung, K.W., Lee, C.W., Zhao, X.D., Chiu, K.P., Lipovich, L., Kuznetsov, V.A., Robson, P., Stanton, L.W., Wei, C.L., Ruan, Y., Lim, B., and Ng, H.H. (2006) The Oct4 and Nanog transcription network regulates pluripotency in mouse embryonic stem cells. Nat Genet. 38(4), 431-440, on line March 5, 2006.
Robertson, G., Hirst, M., Bainbridge, M., Bilenky, M., Zhao, Y., Zeng, T., Euskirchen, G., Bernier, B., Varhol, R., Delaney, A., Thiessen, N., Griffith, O.L., He, A., Marra, M., Snyder, M., and Jones, S. (2007) Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing. Nat Methods. 4, 1–7.
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.
Cuddapah, S., Jothi, R., Schones, D.E., Roh, T.-Y., Cui, K., and Zhao, K. (2009) Global analysis of the insulator CTCF in chromatin barrier regions reveals demarcation of active and repressive domains. Genome Res. 19, 24–32.
Frietze, S., Lan, X., Jin, V.X., and Farnham, P.J. (2010) Genomic targets of the KRAB and SCAN domain-containing zinc finger protein 263. J Biol Chem. 285, 1393–1403.
Blahnik, K.R., Dou, L., OʹGeen, H., McPhillips, T., Xu, X., Cao, A.R., Iyengar, S., Nicolet, C.M., Ludäscher, B., Korf, I., and Farnham, P.J. (2010) Sole-Search: an integrated analysis program for peak detection and functional annotation using ChIP-seq data. Nucleic Acids Res. 38, e13.
Fejes, A.P., Robertson, G., Bilenky, M., Varhol, R., Bainbridge, M., and Jones, S.J.M. (2008) FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology. Bioinformatics. 24, 1729–1730.
Xu, H., Wei, C.-L., Lin, F., and Sung, W.-K. (2008) An HMM approach to genome-wide identification of differential histone modification sites from ChIP-seq data. Bioinformatics. 24, 2344–2349.
Zhang, Y., Liu, T., Meyer, C.A., Eeckhoute, J., Johnson, D.S., Bernstein, B.E., Nussbaum, C., Myers, R.M., Brown, M., Li, W., and Liu, X.S. (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.
Rozen, S. and Skaletsky, H.J. (2000) Primer3 on the WWW for general users and for biologist programmers. In: (Krawetz, S., and Misener, S., Eds.), Bioinformatics methods and protocols: methods in molecular biology, pp. 365–386. Humana Press, Totowa.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media, LLC
About this protocol
Cite this protocol
O’Geen, H., Frietze, S., Farnham, P.J. (2010). Using ChIP-seq Technology to Identify Targets of Zinc Finger Transcription Factors. In: Mackay, J., Segal, D. (eds) Engineered Zinc Finger Proteins. Methods in Molecular Biology, vol 649. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60761-753-2_27
Download citation
DOI: https://doi.org/10.1007/978-1-60761-753-2_27
Published:
Publisher Name: Humana Press, Totowa, NJ
Print ISBN: 978-1-60761-752-5
Online ISBN: 978-1-60761-753-2
eBook Packages: Springer Protocols