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This article is part of the supplement: First International Conference on Phylogenomics

Open Access Open Badges Research

Detecting non-coding selective pressure in coding regions

Hui Chen and Mathieu Blanchette*

Author affiliations

McGill Centre for Bioinformatics, McGill University, 3775 University St., room 332, Montreal, QC, Canada H3A 2B4

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Citation and License

BMC Evolutionary Biology 2007, 7(Suppl 1):S9  doi:10.1186/1471-2148-7-S1-S9

Published: 8 February 2007



Comparative genomics approaches, where orthologous DNA regions are compared and inter-species conserved regions are identified, have proven extremely powerful for identifying non-coding regulatory regions located in intergenic or intronic regions. However, non-coding functional elements can also be located within coding region, as is common for exonic splicing enhancers, some transcription factor binding sites, and RNA secondary structure elements affecting mRNA stability, localization, or translation. Since these functional elements are located in regions that are themselves highly conserved because they are coding for a protein, they generally escaped detection by comparative genomics approaches.


We introduce a comparative genomics approach for detecting non-coding functional elements located within coding regions. Codon evolution is modeled as a mixture of codon substitution models, where each component of the mixture describes the evolution of codons under a specific type of coding selective pressure. We show how to compute the posterior distribution of the entropy and parsimony scores under this null model of codon evolution. The method is applied to a set of growth hormone 1 orthologous mRNA sequences and a known exonic splicing elements is detected. The analysis of a set of CORTBP2 orthologous genes reveals a region of several hundred base pairs under strong non-coding selective pressure whose function remains unknown.


Non-coding functional elements, in particular those involved in post-transcriptional regulation, are likely to be much more prevalent than is currently known. With the numerous genome sequencing projects underway, comparative genomics approaches like that proposed here are likely to become increasingly powerful at detecting such elements.