Reliable prediction of regulator targets using 12 Drosophila genomes

Abstract

Gene expression is regulated pre-and post-transcriptionally via cis-regulatory DNA and RNA motifs. Identification of individual functional instances of such motifs in genome sequences is a major goal for inferring regulatory networks yet has been hampered due to the motifs' short lengths that lead to many chance matches and poor signal-to-noise ratios. In this paper, we develop a general methodology for the comparative identification of functional motif instances across many related species, using a phylogenetic framework that accounts for the evolutionary relationships between species, allows for motif movements, and is robust against missing data due to artifacts in sequencing, assembly, or alignment. We also provide a robust statistical framework for evaluating motif confidence, which enables us to translate evolutionary conservation into a confidence measure for each motif instance, correcting for varying motif length, composition, and background conservation of the target regions. We predict targets of fly transcription factors and miRNAs in alignments of 12 recently sequenced Drosophila species. When compared to extensive genome-wide experimental data, predicted targets are of high quality, matching and surpassing ChIP-chip microarrays and recovering miRNA targets with high sensitivity. The resulting regulatory network suggests significant redundancy between pre-and post-transcriptional regulation of gene expression.[Supplemental material is available online at www.genome.org. All data and predicted transcription factor and miRNA targets are freely available at

Most mammalian mRNAs are conserved targets of microRNAs

“…Detection of seed match conservation with increased sensitivity and statistical power When using a branch-length metric to evaluate motif conservation, the first step is to build a phylogenetic tree based on the genomic regions under investigation (Kheradpour et al 2007), which in our case was 3ЈUTRs. One major innovation of our method was to build the phylogeny in a way that controlled for the conservation of individual UTRs.…”

“…Sliding the branch-length cutoff from zero to the total length of all branches enables tuning of sensitivity and specificity. This method has been applied to the 12-genome alignments of flies to predict conserved miRNA sites with sensitivity substantially improved over the previous binary approach ( Kheradpour et al 2007;Ruby et al 2007) but has yet to be applied to mammalian site conservation.While whole-genome alignments have made it simple to detect the conservation of sites in orthologous locations of genes, it is much more difficult to distinguish those sites or motifs under selective pressure to be maintained from those conserved by chance. A general attempt to detect preferential conservation of any motif used a simple Z-score test but did not control for genomic location or sequence characteristics (Xie et al 2005).…”

“…To capture more of the conserved sites, a quantitative approach has been developed that makes the reasonable assumption that aligned sites within orthologous genes have a single origin and measures the portion of the phylogenetic tree that retains each site by summing the branch length over which each site has been preserved (Kheradpour et al 2007). Because it represents an estimate of the amount of evolutionary time over which a site has been conserved, this branch-length score yields a multivalued metric that accounts for phylogenetic relationships between the species studied (Kheradpour et al 2007). The score is interpreted by selecting a branch-length cutoff that separates more conserved and less conserved sites.…”

Uncovering cis-regulatory sequence requirements for context-specific transcription factor binding

“…We assessed the differential distribution of each motif between the context-specific binding sites by calculating a foldenrichment value as the ratio of the number of motif occurrences, corrected for differences in average sequence composition by the number of occurrences of shuffled control motifs as in Kheradpour et al (2007) and similar to Frith et al (2004), Ho Sui et al (2005, and Chang et al (2006). We assessed the statistical significance of the differential enrichment by a hypergeometric P-value and report only significant motifs (P-value # 0.05).…”

Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures

“…To account for the unique properties of regulatory motifs, we developed a phylogenetic framework to assess the conservation of each motif instance across many genomes 89 . Briefly, we searched for motif instances in each of the aligned genomes, and based on the set (.((...(........)..)).)))))))))))))))))).))))))..))).))…”