Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Protocol
  • Published:

Locating potential enhancer elements by comparative genomics using the EEL software

Abstract

This protocol describes the use of Enhancer Element Locator (EEL), a computer program that was designed to locate distal enhancer elements in long mammalian sequences. EEL will predict the location and structure of conserved enhancers after being provided with two orthologous DNA sequences and binding specificity matrices for the transcription factors (TFs) that are expected to contribute to the function of the enhancers to be identified. The freely available EEL software can analyze two 1-Mb sequences with 100 TF motifs in about 15 min on a modern Windows, Linux or Mac computer. The output provides several hypotheses about enhancer location and structure for further evaluation by an expert on enhancer function.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: The scoring function of EEL.
Figure 2: A file containing the position-specific binding profile for the TF Hunchback obtained from the JASPAR database.
Figure 3: The main window of EEL when the program is started.
Figure 4: Display shown during addition of new sequences to the analysis.
Figure 5: Display shown during addition of new binding motif matrices to the analysis.
Figure 6: The window for parameters of the TFBS search.
Figure 7: A window for parameters of the local alignment procedure for enhancer prediction.
Figure 8: The window showing the predicted enhancer elements.
Figure 9: The score distributions of genome-wide EEL alignments for human and mouse.

Similar content being viewed by others

References

  1. Hallikas, O. et al. Genome-wide prediction of mammalian enhancers based on analysis of transcription-factor binding affinity. Cell 124, 47–59 (2006).

    Article  CAS  PubMed  Google Scholar 

  2. Cameron, R.A. et al. An evolutionary constraint: Strongly disfavored class of change in DNA sequence during divergence of cis-regulatory modules. Proc. Natl. Acad. Sci. USA 102, 11769–11774 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Tompa, M. et al. Assessing computational tools for the discovery of transcription factor binding sites. Nat. Biotechnol. 23, 137–144 (2005).

    Article  CAS  PubMed  Google Scholar 

  4. Bejerano, G. et al. Ultraconserved elements in the human genome. Science 304, 1321–1325 (2004).

    Article  CAS  PubMed  Google Scholar 

  5. Nazina, A.G. & Papatsenko, D.A. Statistical extraction of Drosophila cis-regulatory modules using exhaustive assessment of local word frequency. BMC Bioinformatics 4, 65 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Grad, Y.H., Roth, F.P., Halfon, M.S. & Church, G.M. Prediction of similarly-acting cis-regulatory modules by subsequence profiling and comparative genomics in D. melanogaster and D. pseudoobscura. Bioinformatics 20, 2738–2750 (2004).

    Article  CAS  PubMed  Google Scholar 

  7. Segal, E. & Sharan, R. A discriminative model for identifying spatial cis-regulatory modules. J. Comput. Biol. 12, 822–834 (2005).

    Article  CAS  PubMed  Google Scholar 

  8. Durbin, R., Eddy, S.R., Krogh, A. & Mitchison, G. Biological Sequence Analysis: probabilistic Models of Proteins and Nucleic Acids (Cambridge Univ. Press, Cambridge, 1998).

  9. Berman, B.P. et al. Exploiting transcription factor binding site clustering to identify cis-regulatory modules involved in pattern formation in the Drosophila genome. Proc. Natl. Acad. Sci. USA 99, 757–762 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Alkema, W.B., Johansson, O., Lagergren, J. & Wasserman, W.W. MSCAN: identification of functional clusters of transcription factor binding sites. Nucleic Acids Res. 32, 169–176 (2004).

    Article  Google Scholar 

  11. Sharan, R., Ovcharenko, I., Ben-Hur, A. & Karp, R.M. CREME: a framework for identifying cis-regulatory modules in human-mouse conserved segments. Bioinformatics 19, i283–i291 (2003).

    Article  PubMed  Google Scholar 

  12. Donaldson, I.J. et al. Genome-wide identification of cis-regulatory sequences controlling blood and endothelial development. Hum. Mol. Gene. 14, 595–601 (2005).

    Article  CAS  Google Scholar 

  13. Philippakis, A.A., He, F.S. & Bulyk, M.L. Modulefinder: a tool for computational discovery of cis regulatory modules. in Proc. of the Pacific Symp. of Biocomputing 519–530 (2005).

  14. Blanchette, M. et al. Genome-wide computational prediction of transcriptional regulatory modules reveals new insights into human gene expression. Genome Res. 16, 656–668 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Zhou, Q. & Wong, W.H. CisModule: De novo discovery of cis-regulatory modules by hierarchical mixture modeling. Proc. Natl. Acad. Sci. USA 101, 12114–12119 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Rajewsky, N., Vergassola, M., Gaul, U. & Siggia, E.D. Computational detection of genomic cis-regulatory modules applied to body patterning in the early Drosophila embryo. BMC Bioinformatics 3, 30 (2002).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Sinha, S., van Nimwegen, E. & Siggia, E.D. A probabilistic method to detect regulatory modules. Bioinformatics, 19, i292–i301 (2003).

    Article  PubMed  Google Scholar 

  18. Bailey, T.L. & Noble, W.S. Searching for statistically significant regulatory modules. Bioinformatics 19, 16–25 (2003).

    Article  Google Scholar 

  19. Frith, M.C., Li, M.C. & Weng, Z. Cluster-Buster: finding dense clusters of motifs in DNA sequences. Nucleic Acids Res. 31, 3666–3668 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Xie, X. et al. Systematic discovery of regulatory motifs in human promoters and 3′ UTRs by comparison of several mammals. Nature 434, 338–345 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Wasserman, W.W. & Sandelin, A. Applied bioinformatics for the identification of regulatory elements. Nat. Rev. Genet. 5, 276–287 (2004).

    Article  CAS  PubMed  Google Scholar 

  22. Sinha, S. et al. Cross-species comparison significantly improves genome-wide prediction of cis-regulatory modules in Drosophila. BMC Bioinformatics 5, 129 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Vlieghe, D. et al. A new generation of JASPAR, the open-access repository for transcription factor binding site profiles. Nucleic Acids Res. 34, D95–D97 (2006).

    Article  CAS  PubMed  Google Scholar 

  24. Hallikas, O. & Taipale, J. High-throughput assay for determining specificity and affinity of protein-DNA binding interactions. Nat. Protoc. 10.1038/nprot2006. 33 (2006).

  25. Birney, E. et al. Ensembl 2006. Nucleic Acids Res. 34, D556–D561 (2006).

    Article  CAS  PubMed  Google Scholar 

  26. Kent, W.J. et al. The Human Genome Browser at UCSC. Genome Res. 12, 996–1006 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Benson, G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 27, 573–580 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by the 'Translational Genome-Scale Biology' and the 'From Data to Knowledge' Centers of Excellence of the Academy of Finland and by the 'BioSapiens' and the 'Regulatory Genomics' projects of the European Union.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kimmo Palin.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Palin, K., Taipale, J. & Ukkonen, E. Locating potential enhancer elements by comparative genomics using the EEL software. Nat Protoc 1, 368–374 (2006). https://doi.org/10.1038/nprot.2006.56

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nprot.2006.56

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing