Dataset Information

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns.

ABSTRACT:

Background

Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods.

Results

Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values.

Conclusions

Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks.

SUBMITTER: Gruel J

PROVIDER: S-EPMC3215511 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature

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Publications

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns.

Gruel Jérémy J LeBorgne Michel M LeMeur Nolwenn N Théret Nathalie N

BMC bioinformatics 20110912

<h4>Background</h4>Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods.<h4>Results</h4>Here, ...[more]

PMID: 21910886

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Project description:BackgroundThe mouse vomeronasal organ (VNO) processes chemosensory information, including pheromone signals that influence reproductive behaviors. The sensory neurons of the VNO express two types of chemosensory receptors, V1R and V2R. There are ~165 V1R genes in the mouse genome that have been classified into ~12 divergent subfamilies. Each sensory neuron of the apical compartment of the VNO transcribes only one of the repertoire of V1R genes. A model for mutually exclusive V1R transcription in these cells has been proposed in which each V1R gene might compete stochastically for a single transcriptional complex. This model predicts that the large repertoire of divergent V1R genes in the mouse genome contains common regulatory elements. In this study, we have characterized V1R promoter regions by comparative genomics and by mapping transcription start sites.ResultsWe find that transcription is initiated from ~1 kb promoter regions that are well conserved within V1R subfamilies. While cross-subfamily homology is not evident by traditional methods, we developed a heuristic motif-searching tool, LogoAlign, and applied this tool to identify motifs shared within the promoters of all V1R genes. Our motif-searching tool exhibits rapid convergence to a relatively small number of non-redundant solutions (97% convergence). We also find that the best motifs contain significantly more information than those identified in controls, and that these motifs are more likely to be found in the immediate vicinity of transcription start sites than elsewhere in gene blocks. The best motifs occur near transcription start sites of ~90% of all V1R genes and across all of the divergent subfamilies. Therefore, these motifs are candidate binding sites for transcription factors involved in V1R co-regulation.ConclusionOur analyses show that V1R subfamilies have broad and well conserved promoter regions from which transcription is initiated. Results from a new motif-finding algorithm, LogoAlign, designed for this context and more generally for searching large, hierarchical datasets, suggest the existence of common information-rich regulatory motifs that are shared across otherwise divergent V1R subfamilies.

Project description:BACKGROUND: Accurate computational identification of cis-regulatory motifs is difficult, particularly in eukaryotic promoters, which typically contain multiple short and degenerate DNA sequences bound by several interacting factors. Enrichment in combinations of rare motifs in the promoter sequence of functionally or evolutionarily related genes among several species is an indicator of conserved transcriptional regulatory mechanisms. This provides a basis for the computational identification of cis-regulatory motifs. RESULTS: We have used a discriminative seeding DNA motif discovery algorithm for an in-depth analysis of 54 seed storage protein (SSP) gene promoters from three plant families, namely Brassicaceae (mustards), Fabaceae (legumes) and Poaceae (grasses) using backgrounds based on complete sets of promoters from a representative species in each family, namely Arabidopsis (Arabidopsis thaliana (L.) Heynh.), soybean (Glycine max (L.) Merr.) and rice (Oryza sativa L.) respectively. We have identified three conserved motifs (two RY-like and one ACGT-like) in Brassicaceae and Fabaceae SSP gene promoters that are similar to experimentally characterized seed-specific cis-regulatory elements. Fabaceae SSP gene promoter sequences are also enriched in a novel, seed-specific E2Fb-like motif. Conserved motifs identified in Poaceae SSP gene promoters include a GCN4-like motif, two prolamin-box-like motifs and an Skn-1-like motif. Evidence of the presence of a variant of the TATA-box is found in the SSP gene promoters from the three plant families. Motifs discovered in SSP gene promoters were used to score whole-genome sets of promoters from Arabidopsis, soybean and rice. The highest-scoring promoters are associated with genes coding for different subunits or precursors of seed storage proteins. CONCLUSION: Seed storage protein gene promoter motifs are conserved in diverse species, and different plant families are characterized by a distinct combination of conserved motifs. The majority of discovered motifs match experimentally characterized cis-regulatory elements. These results provide a good starting point for further experimental analysis of plant seed-specific promoters and our methodology can be used to unravel more transcriptional regulatory mechanisms in plants and other eukaryotes.

Project description:In previous studies, gene neighborhoods-spatial clusters of co-expressed genes in the genome-have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Scoring Tool (G-NEST) which combines genomic location, gene expression, and evolutionary sequence conservation data to score putative gene neighborhoods across all possible window sizes simultaneously.Using G-NEST on atlases of mouse and human tissue expression data, we found that large neighborhoods of ten or more genes are extremely rare in mammalian genomes. When they do occur, neighborhoods are typically composed of families of related genes. Both the highest scoring and the largest neighborhoods in mammalian genomes are formed by tandem gene duplication. Mammalian gene neighborhoods contain highly and variably expressed genes. Co-localized noisy gene pairs exhibit lower evolutionary conservation of their adjacent genome locations, suggesting that their shared transcriptional background may be disadvantageous. Genes that are essential to mammalian survival and reproduction are less likely to occur in neighborhoods, although neighborhoods are enriched with genes that function in mitosis. We also found that gene orientation and protein-protein interactions are partially responsible for maintenance of gene neighborhoods.Our experiments using G-NEST confirm that tandem gene duplication is the primary driver of non-random gene order in mammalian genomes. Non-essentiality, co-functionality, gene orientation, and protein-protein interactions are additional forces that maintain gene neighborhoods, especially those formed by tandem duplicates. We expect G-NEST to be useful for other applications such as the identification of core regulatory modules, common transcriptional backgrounds, and chromatin domains. The software is available at http://docpollard.org/software.html.

Dataset Information

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns.

Background

Results

Conclusions

Publications

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns.

Similar Datasets

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