Revealing posttranscriptional regulatory elements through network-level conservation - PubMed (original) (raw)

Revealing posttranscriptional regulatory elements through network-level conservation

Chang S Chan et al. PLoS Comput Biol. 2005 Dec.

Abstract

We used network-level conservation between pairs of fly (Drosophila melanogaster/D. pseudoobscura) and worm (Caenorhabditis elegans/C. briggsae) genomes to detect highly conserved mRNA motifs in 3' untranslated regions. Many of these elements are complementary to the 5' extremity of known microRNAs (miRNAs), and likely correspond to their target sites. We also identify known targets of RNA-binding proteins, and many novel sites not yet known to be functional. Coherent sets of genes with similar function often bear the same conserved elements, providing new insights into their cellular functions. We also show that target sites for distinct miRNAs are often simultaneously conserved, suggesting combinatorial regulation by multiple miRNAs. A genome-wide search for conserved stem-loops, containing complementary sequences to the novel sites, revealed many new candidate miRNAs that likely target them. We also provide evidence that posttranscriptional networks have undergone extensive rewiring across distant phyla, despite strong conservation of regulatory elements themselves.

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Conflict of interest statement

Competing interests. The authors have declared that no competing interests exist.

Figures

Figure 1

Figure 1. Schematic Representation of the Approach

(A) In the first stage of our approach, we scored exhaustive lists of _k_-mers for network level conservation. Schematic examples for a nonconserved _k_-mer (AAAAAAA) and a highly conserved one (UGUGAUA) are given in the left and right graphics, respectively. (B) In the miRNA discovery stage, seed _k_-mers are used to search the genome for conserved and stable stem-loops.

Figure 2

Figure 2. Distribution of Conservation Scores for the C. elegans/C. briggsae Analysis on 3′UTR Sequences

Distributions of actual (red) and randomized (black) sequences are shown. Scores corresponding to some of the known miRNA target sites and RNA-binding protein sites in worms are indicated by arrows. The top portion of both distributions are not shown, for the purpose of presentation.

Figure 3

Figure 3. High-Scoring _k_-Mers Are Complementary to the 5′ Ends of Many miRNAs

(A) Number of complementary worm miRNAs as a function of initial number of retained 7-mers. Solid lines correspond to complementarity anywhere within the miRNAs. Dashed lines correspond to complementarity to the 5′ extremity of miRNAs only. Complementarity to the 5′ extremity of a miRNA is defined as starting within 1 nt of the actual miRNA 5′ extremity. (B) Proportion of 7-mers complementary to the 5′ extremity of at least one miRNA, as a function of the conservation rank (using a sliding window [w] of size 50).

Figure 4

Figure 4. Distribution of Distances from the First Nucleotide of the _k_-Mer to the 5′ Extremity of the miRNA

Distances are given for all pairs of high-scoring _k_-mers/complementary miRNAs. The distribution clearly shows that complementarity between high-scoring worm _k_-mers and miRNAs occurs primarily at the 5′ extremity of the miRNAs.

Figure 5

Figure 5. Number of miRNA Targets

(A) Example showing that the number of predicted targets for D. melanogaster bantam is much larger than expected by chance. The number of predicted targets is the number of genes whose 3′UTR contains at least one conserved _k_-mer complementary to the 5′ extremity of the corresponding miRNA. The distribution of numbers of targets expected by chance was obtained by running the same analysis using 100 pairs of randomized genomes with the same level of divergence as the original ones (see Materials and Methods for details). (B) Estimated numbers of targets for C. elegans miRNAs (only for miRNAs that are complementary to at least one of our high-scoring _k_-mers). Each number corresponds to the number of predicted targets (as defined above) minus the average number of targets expected by chance over the 100 randomizations. The error bars correspond to two standard deviations.

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