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Steven A. McCarroll, Hao Li Cornelia I. Bargmann

Identification of Transcriptional Regulatory Elements in Chemosensory Receptor Genes by Probabilistic Segmentation. Steven A. McCarroll, Hao Li Cornelia I. Bargmann. Background.

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Steven A. McCarroll, Hao Li Cornelia I. Bargmann

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  1. Identification of Transcriptional Regulatory Elements in Chemosensory Receptor Genes by Probabilistic Segmentation Steven A. McCarroll, Hao Li Cornelia I. Bargmann

  2. Background • The expression of genes in multigene families can diverge rapidly between related species, but the genes within the group are likely to share aspects of their regulation. • C. elegans chemoreceptor genes: 921genes of the sra, srb, src, srd, sre, srh, sri, srj, srm, srn, sro, srp, srr, srs, sru, srv, srw, srx, and str families (predicted by Hugh Robertson). • A sequence data set was generated with 1 kb upstream of the predicted start sites of these 921 genes. • Probabilistic segmentation is based on the identification of short DNA sequences that are statistically overrepresented in a set of sequences.

  3. Probabilistic Segmentation P(S|D): the likelihood of generating the same biological sequence by a series of random draws from the dictionary. • The sequence data are modeled as the concatenation of words (w) drawn randomly with frequency( pw) from a "dictionary" D. • The words can be of different lengths. Typically regulatory elements emerge as longer words whereas shorter words represent background.

  4. Optimal Segmentation of Chemoreceptor Promoter Sequences • 60% of the promoter sequence was segmented into one-letter words and more than 90% was segmented into words of length five or less. • About 8% of the sequence was segmented into 404 words of six or more nucleotides

  5. Several features suggesting that these 404 long words represent nonrandom regulatory elements. • Most known transcriptional control elements can appear on either the coding or the noncoding DNA strand. Among the 404 motifs, there were 35 pairs of inverse complements (versus fewer than two pairs expected by chance, p < 10−20). • In addition, 71 of these 404 long words fell into families of related sequences that differed at only one nucleotide or that shared a common six-nucleotide core.

  6. Positional and Functional Specificity of Candidate Motifs • 12 candidate motifs showed strong preference for the proximal 200 nt of the promoter region. • 9 additional motifs were overrepresented in the proximal 200 nt of sequence • Most of these motifs corresponded to known binding sites for families of transcription factors.

  7. Motifs with an E-Box Core (CANNTG ) • 12 motifs shared the E-box core sequence on coding or noncoding strand. • CACCTG, CAGGTG, and CAGCTG all peaked between −40 and −120 • The similar E-box sequence CACGTG (not appear in the probabilistic segmentation results) did not show any positional preference within the chemoreceptor gene family

  8. SMAD Binding Motifs 2 motifs,GTCTAG and CTAGAC, are complementary sequences with a common positional preference. The frequency of these motifs was greatest at positions between −40 and −180 CdxA Binding SequenceThe CTATAATT motif showed a positional preference that peaked between −60 and −120; the motif also showed a strand preference E-box, SMAD, and CdxA motifs typically appeared only once per chemoreceptor gene promoter.

  9. If these motifs represent elements dedicated to the chemosensory system, they should be overrepresented among chemosensory genes relative to their frequency in all genes. • To investigate the hypothsis: • Identified occurrence of each motif in the promoter of all predicted C.elegans genes. • Asked if each motif was statistically overrepresented in any of 600 categories of genes defined by common molecular functions, subcellular localization, or biological roles.

  10. Three motifs show high functional specificity By analyzing the flanking sequence around E-box motif, a larger motif WYCASCTGYY was defined. • The candidate SMAD binding motif and the candidate CdxA motif were both overrepresented specifically in G protein coupled receptors genes. • Unlike the E-box core, the CdxA motif and the SMAD motif did not appear to be part of larger consensus sequences.

  11. E-box sequences were strongly overrepresented in the srh and sri families The SMAD motif was overrepresented in genes of the str family: 14% versus the frequency in the genome of 3.2% The CdxA motif was randomly distributed among chemoreceptor subfamilies.

  12. The Extended E-Box Motif WWYCASCTGYY Appears in ADL-Expressed Genes and Acts as an ADL Enhancer Element

  13. These known and candidate ADL-expressed genes encode many proteins with neuronal functions. But the E-box motif is probably not the only route to ADL expression: some known ADL-expressed genes lack the motif, and deletion of the motif in the srh-220 promoter reduced but did not abolish expression in ADL.

  14. Conclusions • Identified an 11bp E-box motif associated with expression in the ADL neuron. Insertion of this ADL motif into the promoter of a gene normally expressed in AWA neurons was sufficient for expression in ADL. This ADL motif appears to be associated with a particular neuronal identity. • The simplicity of the ADL motif may contribute to evolvability of Caenorhabditis chemosensory behaviors: the appearance or disappearance of this sequence could easily alter receptor expression and thereby the behavioral responses to particular odors. • The presence of an ADL motif in about half of the promoters in the srh and sri chemoreceptor gene subfamilies might reflect the use of ADL to sense a particular class of ligands. • Probabilistic segmentation can be used to identify functional regulatory elements with no previous knowledge of gene expression or regulation. This approach may be of particular value for rapidly evolving genes in the immune system and the nervous system.

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