MOPAT: a graph-based method to predict recurrent cis-regulatory modules from known motifs

The identification of cis-regulatory modules (CRMs) can greatly advance our understanding of eukaryotic regulatory mechanism. Current methods to predict CRMs from known motifs either depend on multiple alignments or can only deal with a small number of known motifs provided by users. These methods are problematic when binding sites are not well aligned in multiple alignments or when the number of input known motifs is large. We thus developed a new CRM identification method MOPAT (motif pair tree), which identifies CRMs through the identification of motif modules, groups of motifs co-occurring in multiple CRMs. It can identify 'orthologous' CRMs without multiple alignments. It can also find CRMs given a large number of known motifs. We have applied this method to mouse developmental genes, and have evaluated the predicted CRMs and motif modules by microarray expression data and known interacting motif pairs. We show that the expression profiles of the genes containing CRMs of the same motif module correlate significantly better than those of a random set of genes do. We also show that the known interacting motif pairs are significantly included in our predictions. Compared with several current methods, our method shows better performance in identifying meaningful CRMs.     

Systematic identification of mammalian regulatory motifs' target genes and functions

We developed an algorithm, Lever, that systematically maps metazoan DNA regulatory motifs or motif combinations to sets of genes. Lever assesses whether the motifs are enriched in cis-regulatory modules (CRMs), predicted by our PhylCRM algorithm, in the noncoding sequences surrounding the genes. Lever analysis allows unbiased inference of functional annotations to regulatory motifs and candidate CRMs. We used human myogenic differentiation as a model system to statistically assess greater than 25,000 pairings of gene sets and motifs or motif combinations. We assigned functional annotations to candidate regulatory motifs predicted previously and identified gene sets that are likely to be co-regulated via shared regulatory motifs. Lever allows moving beyond the identification of putative regulatory motifs in mammalian genomes, toward understanding their biological roles. This approach is general and can be applied readily to any cell type, gene expression pattern or organism of interest.     

SLiMPrints: conservation-based discovery of functional motif fingerprints in intrinsically disordered protein regions

Large portions of higher eukaryotic proteomes are intrinsically disordered, and abundant evidence suggests that these unstructured regions of proteins are rich in regulatory interaction interfaces. A major class of disordered interaction interfaces are the compact and degenerate modules known as short linear motifs (SLiMs). As a result of the difficulties associated with the experimental identification and validation of SLiMs, our understanding of these modules is limited, advocating the use of computational methods to focus experimental discovery. This article evaluates the use of evolutionary conservation as a discriminatory technique for motif discovery. A statistical framework is introduced to assess the significance of relatively conserved residues, quantifying the likelihood a residue will have a particular level of conservation given the conservation of the surrounding residues. The framework is expanded to assess the significance of groupings of conserved residues, a metric that forms the basis of SLiMPrints (short linear motif fingerprints), a de novo motif discovery tool. SLiMPrints identifies relatively overconstrained proximal groupings of residues within intrinsically disordered regions, indicative of putatively functional motifs. Finally, the human proteome is analysed to create a set of highly conserved putative motif instances, including a novel site on translation initiation factor eIF2A that may regulate translation through binding of eIF4E.     

Linear motifs confer functional diversity onto splice variants

The pre-translational modification of messenger ribonucleic acids (mRNAs) by alternative promoter usage and alternative splicing is an important source of pleiotropy. Despite intensive efforts, our understanding of the functional implications of this dynamically created diversity is still incomplete. Using the available knowledge of interaction modules, particularly within intrinsically disordered regions (IDRs), we analysed the occurrences of protein modules within alternative exons. We find that regions removed or included by pre-translational variation are enriched in linear motifs suggesting that the removal or inclusion of exons containing these interaction modules is an important regulatory mechanism. In particular, we observe that PDZ-, PTB-, SH2- and WW-domain binding motifs are more likely to occur within alternative exons. We also determine that regions removed or included by alternative promoter usage are enriched in IDRs suggesting that protein isoform diversity is tightly coupled to the modulation of IDRs. This study, therefore, demonstrates that short linear motifs are key components for establishing protein diversity between splice variants.     

Combining phylogenetic data with co-regulated genes to identify regulatory motifs

MOTIVATION: Discovery of regulatory motifs in unaligned DNA sequences remains a fundamental problem in computational biology. Two categories of algorithms have been developed to identify common motifs from a set of DNA sequences. The first can be called a 'multiple genes, single species' approach. It proposes that a degenerate motif is embedded in some or all of the otherwise unrelated input sequences and tries to describe a consensus motif and identify its occurrences. It is often used for co-regulated genes identified through experimental approaches. The second approach can be called 'single gene, multiple species'. It requires orthologous input sequences and tries to identify unusually well conserved regions by phylogenetic footprinting. Both approaches perform well, but each has some limitations. It is tempting to combine the knowledge of co-regulation among different genes and conservation among orthologous genes to improve our ability to identify motifs. RESULTS: Based on the Consensus algorithm previously established by our group, we introduce a new algorithm called PhyloCon (Phylogenetic Consensus) that takes into account both conservation among orthologous genes and co-regulation of genes within a species. This algorithm first aligns conserved regions of orthologous sequences into multiple sequence alignments, or profiles, then compares profiles representing non-orthologous sequences. Motifs emerge as common regions in these profiles. Here we present a novel statistic to compare profiles of DNA sequences and a greedy approach to search for common subprofiles. We demonstrate that PhyloCon performs well on both synthetic and biological data. AVAILABILITY: Software available upon request from the authors. http://ural.wustl.edu/softwares.html     

Structure of the mouse nucleolin gene. The complete sequence reveals that each RNA binding domain is encoded by two independent exons

Nucleolin is a multifunctional nucleolar protein involved in the synthesis, packaging and maturation of pre-rRNA in eukaryotic cells. We describe the molecular organization and complete sequence of the mouse nucleolin gene, the first higher eukaryotic gene encoding a protein that is both an RNA binding protein involved in rRNA processing and a specific nucleolar protein. The nucleolin gene extends over 9000 base-pairs and is split into 14 exons that encode the 706 amino acid residues of the protein. The promoter sequence is G + C-rich (67% G + C) with four G/C boxes, it lacks bona fide TATA and CAAT boxes and shows capping site heterogeneity. The existence of pyrimidine-rich motifs, similar to those found in the promoter of ribosomal protein genes, could be relevant to the co-regulation of genes whose products are involved in ribosome biogenesis. Nucleolin contains four RNA binding domains, each about 80 amino acid residues long, which include the 11-residue core ribonucleoprotein consensus motif. Each domain is encoded by two exons, with an intervening sequence interrupting the conserved core motif at roughly the same amino acid position. This latter result suggests that the RNA binding domains are composed of two independent subdomains, whose functions remain to be determined.