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Using Trawler_standalone to discover overrepresented motifs in DNA and RNA sequences derived from various experiments including chromatin immunoprecipitation

Nature Protocols volume 5, pages 323–334 (2010)Cite this article

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Abstract

Genome-wide location analysis has become a standard technology to unravel gene regulation networks. The accurate characterization of nucleotide signatures in sequences is key to uncovering the regulatory logic but remains a computational challenge. This protocol describes how to best characterize these signatures (motifs) using the new standalone version of Trawler, which was designed and optimized to analyze chromatin immunoprecipitation (ChIP) data sets. In particular, we describe the three main steps of Trawler_standalone (motif discovery, clustering and visualization) and discuss the appropriate parameters to be used in each step depending on the data set and the biological questions addressed. Compared to five other motif discovery programs, Trawler_standalone is in most cases the fastest algorithm to accurately predict the correct motifs especially for large data sets. Its running time ranges within few seconds to several minutes, depending on the size of the data set and the parameters used. This protocol is best suited for bioinformaticians seeking to use Trawler_standalone in a high-throughput manner.

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Figure 1: Overview of the Trawler_standalone pipeline.
Figure 2: Tunable options of Trawler_standalone.
Figure 3: Trawler_standalone output summary.
Figure 4: Occurrences of the motifs in the given sequences.
Figure 5: Input and output information.

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Acknowledgements

We thank the Wittbrodt lab for fruitful discussions and Florence Besse, Dirk-Dominik Dolle and Mythily Ganapathi for testing Trawler_standalone. This work was supported by FP7-CISSTEM.

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Author notes

  1. Yannick Haudry, Mirana Ramialison, Joachim Wittbrodt & Laurence Ettwiller

    Present address: Present addresses: Heidelberg Institute of Zoology, University of Heidelberg, Heidelberg, Germany (Y.H., M.R., J.W. and L.E.); Institute for Toxicology and Genetics, Forschungszentrum Karlsruhe, Postfach 3640, Karlsruhe D-76021, Germany (J.W.).,

  2. Yannick Haudry and Mirana Ramialison: These authors contributed equally to this work.

Authors and Affiliations

  1. Developmental Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany

    Yannick Haudry, Mirana Ramialison, Joachim Wittbrodt & Laurence Ettwiller

  2. Center for Biomolecular Science and Engineering, University of California, Santa Cruz, California, USA.,

    Benedict Paten

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Contributions

Y.H. with the help of M.R. built the standalone distribution; Y.H., M.R. B.P. and L.E. have contributed to improve the algorithm; and Y.H., M.R., B.P. and L.E. have written the paper.

Corresponding author

Correspondence to Laurence Ettwiller.

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Haudry, Y., Ramialison, M., Paten, B. et al. Using Trawler_standalone to discover overrepresented motifs in DNA and RNA sequences derived from various experiments including chromatin immunoprecipitation. Nat Protoc 5, 323–334 (2010). https://doi.org/10.1038/nprot.2009.158

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