Skip to main content
SpringerLink
Log in

Mapping Protein–DNA Interactions Using ChIP-Sequencing

  • Protocol
  • First Online:
Book cover Transcriptional Regulation

Part of the book series: Methods in Molecular Biology ((MIMB,volume 809))

Abstract

Chromatin immunoprecipitation (ChIP) allows enrichment of genomic regions which are associated with specific transcription factors, histone modifications, and indeed any other epitopes which are present on chromatin. The original ChIP methods used site-specific PCR and Southern blotting to confirm which regions of the genome were enriched, on a candidate basis. The combination of ChIP with genomic tiling arrays (ChIP-chip) allowed a more unbiased approach to map ChIP-enriched sites. However, limitations of microarray probe design and probe number have a detrimental impact on the coverage, resolution, sensitivity, and cost of whole-genome tiling microarray sets for higher eukaryotes with large genomes. The combination of ChIP with high-throughput sequencing technology has allowed more comprehensive surveys of genome occupancy, greater resolution, and lower cost for whole genome coverage. Herein, we provide a comparison of high-throughput sequencing platforms and a survey of ChIP-seq analysis tools, discuss experimental design, and describe a detailed ChIP-seq method.

Chromatin immunoprecipitation (ChIP) allows enrichment of genomic regions which are associated with specific transcription factors, histone modifications, and indeed any other epitopes which are present on chromatin. The original ChIP methods used site-specific PCR and Southern blotting to confirm which regions of the genome were enriched, on a candidate basis. The combination of ChIP with genomic tiling arrays (ChIP-chip) allowed a more unbiased approach to map ChIP-enriched sites. However, limitations of microarray probe design and probe number have a detrimental impact on the coverage, resolution, sensitivity, and cost of whole-genome tiling microarray sets for higher eukaryotes with large genomes. The combination of ChIP with high-throughput sequencing technology has allowed more comprehensive surveys of genome occupancy, greater resolution, and lower cost for whole genome coverage. Herein, we provide a comparison of high-throughput sequencing platforms and a survey of ChIP-seq analysis tools, discuss experimental design, and describe a detailed ChIP-seq method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Barski, A., Cuddapah, S., Cui, K., Roh, T. Y., Schones, D. E., Wang, Z., Wei, G., Chepelev, I., and Zhao, K. (2007) High-resolution profiling of histone methylations in the human genome, Cell 129, 823–837.

    Google Scholar 

  2. Carroll, J. S., Meyer, C. A., Song, J., Li, W., Geistlinger, T. R., Eeckhoute, J., Brodsky, A. S., Keeton, E. K., Fertuck, K. C., Hall, G. F., Wang, Q., Bekiranov, S., Sementchenko, V., Fox, E. A., Silver, P. A., Gingeras, T. R., Liu, X. S., and Brown, M. (2006) Genome-wide analysis of estrogen receptor binding sites, Nature Genetics 38, 1289–1297.

    Google Scholar 

  3. Massie, C. E., Adryan, B., Barbosa-Morais, N. L., Lynch, A. G., Tran, M. G., Neal, D. E., and Mills, I. G. (2007) New androgen receptor genomic targets show an interaction with the ETS1 transcription factor, EMBO Reports 8, 871–878.

    Google Scholar 

  4. Wang, Q., Li, W., Zhang, Y., Yuan, X., Xu, K., Yu, J., Chen, Z., Beroukhim, R., Wang, H., Lupien, M., Wu, T., Regan, M. M., Meyer, C. A., Carroll, J. S., Manrai, A. K., Janne, O. A., Balk, S. P., Mehra, R., Han, B., Chinnaiyan, A. M., Rubin, M. A., True, L., Fiorentino, M., Fiore, C., Loda, M., Kantoff, P. W., Liu, X. S., and Brown, M. (2009) Androgen receptor regulates a distinct transcription program in androgen-independent prostate cancer, Cell 138, 245–256.

    Google Scholar 

  5. Bolton, E. C., So, A. Y., Chaivorapol, C., Haqq, C. M., Li, H., and Yamamoto, K. R. (2007) Cell- and gene-specific regulation of primary target genes by the androgen receptor, Genes Dev 21, 2005–2017.

    Google Scholar 

  6. Dahl, J. A., Reiner, A. H., and Collas, P. (2009) Fast genomic muChIP-chip from 1,000 cells, Genome Biol 10, R13.

    Google Scholar 

  7. Acevedo, L. G., Iniguez, A. L., Holster, H. L., Zhang, X., Green, R., and Farnham, P. J. (2007) Genome-scale ChIP-chip analysis using 10,000 human cells, BioTechniques 43, 791–797.

    Google Scholar 

  8. 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.

    Google Scholar 

  9. Goren, A., Ozsolak, F., Shoresh, N., Ku, M., Adli, M., Hart, C., Gymrek, M., Zuk, O., Regev, A., Milos, P. M., and Bernstein, B. E. (2010) Chromatin profiling by directly sequencing small quantities of immunoprecipitated DNA, Nature Methods 7, 47–49.

    Google Scholar 

  10. Ji, H., Jiang, H., Ma, W., Johnson, D. S., Myers, R. M., and Wong, W. H. (2008) An integrated software system for analyzing ChIP-chip and ChIP-seq data, Nat Biotechnol 26, 1293–1300.

    Google Scholar 

  11. Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., and Wold, B. (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq, Nature methods 5, 621–628.

    Google Scholar 

  12. Boyle, A. P., Guinney, J., Crawford, G. E., and Furey, T. S. (2008) F-Seq: a feature density estimator for high-throughput sequence tags, Bioinformatics 24, 2537–2538.

    Google Scholar 

  13. 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.

    Google Scholar 

  14. 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.

    Google Scholar 

  15. Zhang, X., Robertson, G., Krzywinski, M., Ning, K., Droit, A., Jones, S., and Gottardo, R. PICS: Probabilistic Inference for ChIP-seq, Biometrics.

    Google Scholar 

  16. Schmidt, D., Schwalie, P. C., Ross-Innes, C. S., Hurtado, A., Brown, G. D., Carroll, J. S., Flicek, P., and Odom, D. T. A CTCF-independent role for cohesin in tissue-specific transcription, Genome Res 20, 578–588.

    Google Scholar 

  17. 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.

    Google Scholar 

  18. Spyrou, C., Stark, R., Lynch, A. G., and Tavare, S. (2009) BayesPeak: Bayesian analysis of ChIP-seq data, BMC Bioinformatics 10, 299.

    Google Scholar 

  19. Qin, Z. S., Yu, J., Shen, J., Maher, C. A., Hu, M., Kalyana-Sundaram, S., and Chinnaiyan, A. M. HPeak: an HMM-based algorithm for defining read-enriched regions in ChIP-Seq data, BMC Bioinformatics 11, 369.

    Google Scholar 

  20. 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, Nature methods 4, 651–657.

    Google Scholar 

  21. Valouev, A., Johnson, D. S., Sundquist, A., Medina, C., Anton, E., Batzoglou, S., Myers, R. M., and Sidow, A. (2008) Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data, Nature methods 5, 829–834.

    Google Scholar 

  22. Fejes, A. P., Robertson, G., Bilenky, M., Varhol, R., Bainbridge, M., and Jones, S. J. (2008) FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology, Bioinformatics 24, 1729–1730.

    Google Scholar 

  23. 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.

    Google Scholar 

  24. Rozowsky, J., Euskirchen, G., Auerbach, R. K., Zhang, Z. D., Gibson, T., Bjornson, R., Carriero, N., Snyder, M., and Gerstein, M. B. (2009) PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls, Nat Biotechnol 27, 66–75.

    Google Scholar 

  25. Ku, M., Jaffe, D. B., Issac, B., Lieberman, E., Giannoukos, G., Alvarez, P., Brockman, W., Kim, T. K., Koche, R. P., Lee, W., Mendenhall, E., O’Donovan, A., Presser, A., Russ, C., Xie, X., Meissner, A., Wernig, M., Jaenisch, R., Nusbaum, C., Lander, E. S., and Bernstein, B. E. (2007) Genome-wide maps of chromatin state in pluripotent and lineage-committed cells, Nature 448, 553–560.

    Google Scholar 

  26. 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.

    Google Scholar 

  27. Hon, G., Ren, B., and Wang, W. (2008) ChromaSig: a probabilistic approach to finding common chromatin signatures in the human genome, PLoS Comput Biol 4, e1000201.

    Google Scholar 

  28. Feng, W., Liu, Y., Wu, J., Nephew, K. P., Huang, T. H., and Li, L. (2008) A Poisson mixture model to identify changes in RNA polymerase II binding quantity using high-throughput sequencing technology, BMC Genomics 9 Suppl 2, S23.

    Google Scholar 

  29. Blahnik, K. R., Dou, L., O’Geen, H., McPhillips, T., Xu, X., Cao, A. R., Iyengar, S., Nicolet, C. M., Ludascher, B., Korf, I., and Farnham, P. J. Sole-Search: an integrated analysis program for peak detection and functional annotation using ChIP-seq data, Nucleic Acids Res 38, e13.

    Google Scholar 

  30. http://sourceforge.net/projects/useq/files/CommunityChIPSeqChallenge/. ChIP-seq community chal.

  31. Schmidt, D., Wilson, M. D., Spyrou, C., Brown, G. D., Hadfield, J., and Odom, D. T. (2009) ChIP-seq: using high-throughput sequencing to discover protein-DNA interactions, Methods (San Diego, Calif) 48, 240–248.

    Google Scholar 

  32. 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, Nature Methods 4, 651–657.

    Google Scholar 

  33. http://www.nanoporetech.com/. Nanopore.

  34. http://cistrome.dfci.harvard.edu/ap/. Cistrome.

  35. http://chipseq.genomecenter.ucdavis.edu/cgi-bin/chipseq.cgi. Sole Search.

  36. Nowak, D. E., Tian, B., and Brasier, A. R. (2005) Two-step cross-linking method for identification of NF-kappaB gene network by chromatin immunoprecipitation, BioTechniques 39, 715–725.

    Google Scholar 

  37. West, A. G., Huang, S., Gaszner, M., Litt, M. D., and Felsenfeld, G. (2004) Recruitment of histone modifications by USF proteins at a vertebrate barrier element, Molecular Cell 16, 453–463.

    Google Scholar 

  38. http://www.chiponchip.org/Antibody/chip.html. Compendium of ChIP grade antibodies.

  39. http://www.abcam.com/index.html?c=917. Abcam ChIP grade antibodies.

  40. http://www.diagenode.com/en/topics/antibodies/antibodies.php. Diagenode ChIP antibodies.

  41. http://www.cellsignal.com/technologies/chip.html. Cell Signalling ChIP antibodies.

  42. http://www.activemotif.com/catalog/18/chip-validated-antibodies.html. Active motif ChIP antibodies.

  43. http://www.millipore.com/microsites/search.do?q=&filterProductTypes=taxonomy%3a%5e73UUAR%2f73UUB8&module=antibody&tabValue=ANTIBODY&filter=61964%3a%5e%22Epigenetics+%26+Nuclear+Function%22%24&filter=61965%3a%5e%22Chromatin+Biology%22%24&filter=60679%3a%5e%22Chromatin+Immunoprecipitation+(ChIP)%22%24&show=10#0:0. Millipore ChIP antibodies.

  44. http://www.invitrogen.com/site/us/en/home/Products-and-Services/Applications/RNAi-Epigenetics-and-Gene-Regulation/Chromatin-Remodeling/Chromatin-Immunoprecipitation-ChIP/antibodies-for-chip.html. Invitrogen ChIP antibodies.

  45. Quail, M. A., Kozarewa, I., Smith, F., Scally, A., Stephens, P. J., Durbin, R., Swerdlow, H., and Turner, D. J. (2008) A large genome center’s improvements to the Illumina sequencing system, Nature Methods 5, 1005–1010.

    Google Scholar 

  46. Pepke, S., Wold, B., and Mortazavi, A. (2009) Computation for ChIP-seq and RNA-seq studies, Nature Methods 6, S22–32.

    Google Scholar 

Download references

Acknowledgements

C. E. Massie is a postdoctoral researcher at the Department of Haematology, University of Cambridge. I. G. Mills is a research group leader within the Centre for Molecular Medicine (Norway), a Visiting Scientist at Cancer Research UK and an Honorary Senior Visiting Research Fellow within the Department of Oncology at the University of Cambridge.

Author information

Authors and Affiliations

  1. CRUK Cambridge Research Institute, Cambridge, UK

    Charles E. Massie & Ian G. Mills

  2. Department of Haematology, Cambridge Institute for Medical Research, Cambridge, UK

    Charles E. Massie

  3. Centre for Molecular Medicine Norway, Nordic European Molecular Biology Laboratory Partnership, University of Oslo, Oslo, Norway

    Ian G. Mills

Authors
  1. Charles E. Massie
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ian G. Mills
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ian G. Mills .

Editor information

Editors and Affiliations

  1. , Department of Biological Sciences, St. John's University, Utopia Parkway 8000, Queens, 11439, New York, USA

    Ales Vancura

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Science+Business Media, LLC

About this protocol

Cite this protocol

Massie, C.E., Mills, I.G. (2012). Mapping Protein–DNA Interactions Using ChIP-Sequencing. In: Vancura, A. (eds) Transcriptional Regulation. Methods in Molecular Biology, vol 809. Springer, New York, NY. https://doi.org/10.1007/978-1-61779-376-9_11

Download citation

  • DOI: https://doi.org/10.1007/978-1-61779-376-9_11

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-61779-375-2

  • Online ISBN: 978-1-61779-376-9

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation