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How does DNA sequence motif discovery work?

Nature Biotechnology volume 24, pages 959–961 (2006)Cite this article

How can we computationally extract an unknown motif from a set of target sequences? What are the principles behind the major motif discovery algorithms? Which of these should we use, and how do we know we've found a 'real' motif?

Extracting regulatory motifs1 from DNA sequences seems to be all the rage these days. Take your favorite cluster of coexpressed genes, and with some luck you might hope to find a short pattern of nucleotides upstream of the transcription start sites of these genes, indicating a common transcription factor binding site responsible for their coordinate regulation. Easier said than done—the hunt for such a common motif may be like searching for the proverbial needle in a haystack. Consider the complexity of searching for imperfect copies of an unknown pattern, perhaps as small as 6–8 base pairs, occurring potentially thousands of bases upstream of some unknown subset of our genes of interest.

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Figure 1: Starting from a single site, expectation maximization algorithms such as MEME4 alternate between assigning sites to a motif (left) and updating the motif model (right).

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  1. Microbial Systems Division, Biosciences Directorate, Lawrence Livermore National Laboratory, 7000 East Ave., PO Box 808, L-448, Livermore, 94551, California, USA

    Patrik D'haeseleer

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D'haeseleer, P. How does DNA sequence motif discovery work?. Nat Biotechnol 24, 959–961 (2006). https://doi.org/10.1038/nbt0806-959

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