Dataset Information

Meta-analysis discovery of tissue-specific DNA sequence motifs from mammalian gene expression data.

ABSTRACT:

Background

A key step in the regulation of gene expression is the sequence-specific binding of transcription factors (TFs) to their DNA recognition sites. However, elucidating TF binding site (TFBS) motifs in higher eukaryotes has been challenging, even when employing cross-species sequence conservation. We hypothesized that for human and mouse, many orthologous genes expressed in a similarly tissue-specific manner in both human and mouse gene expression data, are likely to be co-regulated by orthologous TFs that bind to DNA sequence motifs present within noncoding sequence conserved between these genomes.

Results

We performed automated motif searching and merging across four different motif finding algorithms, followed by filtering of the resulting motifs for those that contain blocks of information content. Applying this motif finding strategy to conserved noncoding regions surrounding co-expressed tissue-specific human genes allowed us to discover both previously known, and many novel candidate, regulatory DNA motifs in all 18 tissue-specific expression clusters that we examined. For previously known TFBS motifs, we observed that if a TF was expressed in the specified tissue of interest, then in most cases we identified a motif that matched its TRANSFAC motif; conversely, of all those discovered motifs that matched TRANSFAC motifs, most of the corresponding TF transcripts were expressed in the tissue(s) corresponding to the expression cluster for which the motif was found.

Conclusion

Our results indicate that the integration of the results from multiple motif finding tools identifies and ranks highly more known and novel motifs than does the use of just one of these tools. In addition, we believe that our simultaneous enrichment strategies helped to identify likely human cis regulatory elements. A number of the discovered motifs may correspond to novel binding site motifs for as yet uncharacterized tissue-specific TFs. We expect this strategy to be useful for identifying motifs in other metazoan genomes.

SUBMITTER: Huber BR

PROVIDER: S-EPMC1522027 | biostudies-literature | 2006 Apr

REPOSITORIES: biostudies-literature

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Publications

Meta-analysis discovery of tissue-specific DNA sequence motifs from mammalian gene expression data.

Huber Bertrand R BR Bulyk Martha L ML

BMC bioinformatics 20060427

<h4>Background</h4>A key step in the regulation of gene expression is the sequence-specific binding of transcription factors (TFs) to their DNA recognition sites. However, elucidating TF binding site (TFBS) motifs in higher eukaryotes has been challenging, even when employing cross-species sequence conservation. We hypothesized that for human and mouse, many orthologous genes expressed in a similarly tissue-specific manner in both human and mouse gene expression data, are likely to be co-regulat ...[more]

PMID: 16643658

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Project description:BackgroundIn the recent years, there has been a rise in gene expression profiling reports. Unfortunately, it has not been possible to make maximum use of available gene expression data. Many databases and programs can be used to derive the possible expression patterns of mammalian genes, based on existing data. However, these available resources have limitations. For example, it is not possible to obtain a list of genes that are expressed in certain conditions. To overcome such limitations, we have taken up a new strategy to predict gene expression patterns using available information, for one tissue at a time.ResultsThe first step of this approach involved manual collection of maximum data derived from large-scale (genome-wide) gene expression studies, pertaining to mammalian testis. These data have been compiled into a Mammalian Gene Expression Testis-database (MGEx-Tdb). This process resulted in a richer collection of gene expression data compared to other databases/resources, for multiple testicular conditions. The gene-lists collected this way in turn were exploited to derive a 'consensus' expression status for each gene, across studies. The expression information obtained from the newly developed database mostly agreed with results from multiple small-scale studies on selected genes. A comparative analysis showed that MGEx-Tdb can retrieve the gene expression information more efficiently than other commonly used databases. It has the ability to provide a clear expression status (transcribed or dormant) for most genes, in the testis tissue, under several specific physiological/experimental conditions and/or cell-types.ConclusionsManual compilation of gene expression data, which can be a painstaking process, followed by a consensus expression status determination for specific locations and conditions, can be a reliable way of making use of the existing data to predict gene expression patterns. MGEx-Tdb provides expression information for 14 different combinations of specific locations and conditions in humans (25,158 genes), 79 in mice (22,919 genes) and 23 in rats (14,108 genes). It is also the first system that can predict expression of genes with a 'reliability-score', which is calculated based on the extent of agreements and contradictions across gene-sets/studies. This new platform is publicly available at the following web address: http://resource.ibab.ac.in/MGEx-Tdb/.

Project description:Proteins that selectively transport water across the membranes of cells are recognized as important in the normal functioning of the body systems of vertebrates. There are 13 known mammalian aquaporins (AQP0 to AQP12), some of which have been shown to have unexpected cellular roles beyond transmembrane water transport. The availability of non-mammalian vertebrate animal models has the potential to provide insight into the emergence of diverse function in the aquaporins. The domesticated chicken (Gallus gallus) is the premier avian model for biological research; however, only a limited number of studies have compared chicken and mammalian aquaporins. The identification of aquaporins that share functional motifs or are expressed in the same tissues in human and chicken could allow the further functional analyses of homologous aquaporins in both species. We hypothesize that integrative analyses of protein sequences and body site expression of human, mouse, rat and chicken aquaporins has the potential to yield novel biological hypotheses about the unexpected cellular roles of aquaporins beyond transmembrane water transport.A total of 76 aquaporin transcript models derived from 47 aquaporin genes were obtained for human, mouse, rat and chicken. Eleven body sites (brain, connective tissue, head, heart, liver, muscle, ovary, pancreas, small intestine, spleen and testis) were identified in which there is suggested expression of at least one mammalian and one chicken aquaporin. This study demonstrates that modern on-line analysis tools, a novel matrix integration technique, and the availability of the chicken genome for comparative genomics and expression analysis enables hypothesis generation in several important areas including: (i) alternative transcription and speciation effects on the conservation of functional motifs in vertebrate aquaporins; (ii) the emergence of basolateral targeting in mammalian species; (iii) the potential of the cysteine-rich AQP11 as a possible target in the pathophysiology of neurodegenerative disorders such as autism that involve Purkinje cells; and (iv) possible impairment of function of pancreas-expressed AQP12 during pancreatotropic necrosis in avian influenza virus infection.The investigation of aquaporin function in chicken and mammalian species has the potential to accelerate the discovery of novel knowledge of aquaporins in both avian and mammalian species.

Project description:BackgroundA substantial fraction of non-coding DNA sequences of multicellular eukaryotes is under selective constraint. In particular, approximately 5% of the human genome consists of conserved non-coding sequences (CNSs). CNSs differ from other genomic sequences in their nucleotide composition and must play important functional roles, which mostly remain obscure.ResultsWe investigated relative abundances of short sequence motifs in all human CNSs present in the human/mouse whole-genome alignments vs. three background sets of sequences: (i) weakly conserved or unconserved non-coding sequences (non-CNSs); (ii) near-promoter sequences (located between nucleotides -500 and -1500, relative to a start of transcription); and (iii) random sequences with the same nucleotide composition as that of CNSs. When compared to non-CNSs and near-promoter sequences, CNSs possess an excess of AT-rich motifs, often containing runs of identical nucleotides. In contrast, when compared to random sequences, CNSs contain an excess of GC-rich motifs which, however, lack CpG dinucleotides. Thus, abundance of short sequence motifs in human CNSs, taken as a whole, is mostly determined by their overall compositional properties and not by overrepresentation of any specific short motifs. These properties are: (i) high AT-content of CNSs, (ii) a tendency, probably due to context-dependent mutation, of A's and T's to clump, (iii) presence of short GC-rich regions, and (iv) avoidance of CpG contexts, due to their hypermutability. Only a small number of short motifs, overrepresented in all human CNSs are similar to binding sites of transcription factors from the FOX family.ConclusionHuman CNSs as a whole appear to be too broad a class of sequences to possess strong footprints of any short sequence-specific functions. Such footprints should be studied at the level of functional subclasses of CNSs, such as those which flank genes with a particular pattern of expression. Overall properties of CNSs are affected by patterns in mutation, suggesting that selection which causes their conservation is not always very strong.

Dataset Information

Meta-analysis discovery of tissue-specific DNA sequence motifs from mammalian gene expression data.

Background

Results

Conclusion

Publications

Meta-analysis discovery of tissue-specific DNA sequence motifs from mammalian gene expression data.

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