Background: The analysis of the promoter sequence of genes with similar expression patterns is/na basic tool to annotate common regulatory elements. Multiple sequence alignments are on the/nbasis of most comparative approaches. The characterization of regulatory regions from coexpressed/ngenes at the sequence level, however, does not yield satisfactory results in many/noccasions as promoter regions of genes sharing similar expression programs often do not show/nnucleotide sequence conservation./nResults: ...
Background: The analysis of the promoter sequence of genes with similar expression patterns is/na basic tool to annotate common regulatory elements. Multiple sequence alignments are on the/nbasis of most comparative approaches. The characterization of regulatory regions from coexpressed/ngenes at the sequence level, however, does not yield satisfactory results in many/noccasions as promoter regions of genes sharing similar expression programs often do not show/nnucleotide sequence conservation./nResults: In a recent approach to circumvent this limitation, we proposed to align the maps of/npredicted transcription factors (referred as TF-maps) instead of the nucleotide sequence of two/nrelated promoters, taking into account the label of the corresponding factor and the position in the/nprimary sequence. We have now extended the basic algorithm to permit multiple promoter/ncomparisons using the progressive alignment paradigm. In addition, non-collinear conservation/nblocks might now be identified in the resulting alignments. We have optimized the parameters of/nthe algorithm in a small, but well-characterized collection of human-mouse-chicken-zebrafish/northologous gene promoters./nConclusion: Results in this dataset indicate that TF-map alignments are able to detect high-level/nregulatory conservation at the promoter and the 3'UTR gene regions, which cannot be detected/nby the typical sequence alignments. Three particular examples are introduced here to illustrate the/npower of the multiple TF-map alignments to characterize conserved regulatory elements in/nabsence of sequence similarity. We consider this kind of approach can be extremely useful in the/nfuture to annotate potential transcription factor binding sites on sets of co-regulated genes from/nhigh-throughput expression experiments.
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