MEME: discovering and analyzing DNA and protein sequence motifs

MEME (Multiple EM for Motif Elicitation) is one of the most widely used tools for searching for novel ‘signals’ in sets of biological sequences. Applications include the discovery of new transcription factor binding sites and protein domains. MEME works by searching for repeated, ungapped sequence patterns that occur in the DNA or protein sequences provided by the user. Users can perform MEME searches via the web server hosted by the National Biomedical Computation Resource () and several mirror sites. Through the same web server, users can also access the Motif Alignment and Search Tool to search sequence databases for matches to motifs encoded in several popular formats. By clicking on buttons in the MEME output, users can compare the motifs discovered in their input sequences with databases of known motifs, search sequence databases for matches to the motifs and display the motifs in various formats. This article describes the freely accessible web server and its architecture, and discusses ways to use MEME effectively to find new sequence patterns in biological sequences and analyze their significance

Predicting genes for orphan metabolic activities using phylogenetic profiles

Homology-based methods fail to assign genes to many metabolic activities present in sequenced organisms. To suggest genes for these orphan activities we developed a novel method that efficiently combines local structure of a metabolic network with phylogenetic profiles. We validated our method using known metabolic genes in Saccharomyces cerevisiae and Escherichia coli. We show that our method should be easily transferable to other organisms, and that it is robust to errors in incomplete metabolic networks

Recent enhancements to the Blocks Database servers.

The Blocks Database contains multiple alignments of conserved regions in protein families which can be searched by e-mail ([email protected]) and World Wide Web (http://blocks.fhcrc.org/ ) servers to classify protein and nucleotide sequences. Recent enhancements to the servers include: (i) improved calculation of position-specific scoring matrices from blocks; (ii) availability of the Prints protein fingerprint database for searching in Blocks format; (iii) a representative sequence biased towards the Blocks of a protein family; (iv) a tree constructed from the Blocks of a protein family; (v) links to related World Wide Web pages for a family; and (vi) the new Local Alignment of Multiple Alignments (LAMA) method to search a block against a database of blocks

Computational analysis of gene content in Xenacoelomorpha

Xenacoelomorpha are simple, marine worms with net-like nervous systems, no circulatory or respiratory systems and a blind gut. The phylogenetic position of Xenacoelomorpha is the subject of ongoing debate in the literature. The two possible locations for the Xenacoelomorpha within the animal tree are i) as the sister clade to all other bilaterians and ii) as deuterostomes, closely related to the Ambulacraria (echinoderms and hemichordates). The understanding of the phylogenetic position of Xenacoelomorpha has major implications in understanding the appearance of the Bilateria last common ancestor and the direction of the evolutionary process within the animal kingdom. If Xenacoelomorpha are in fact basal bilaterians, they can resemble many similarities to simple acoel-like bilaterian ancestor. However, if Xenacoelomorpha are sister group to Ambulacraria, they likely secondary simplified from a complex, segmented, coelomate Bilateria ancestor. I analysed the quality of 6 new xenacoelomorph genomic and 7 transcriptomic data sets (Symsagittifera roscoffensis, Pseudophanostoma variabilis, Paratomella rubra and Praesagittifera naikaiensis, the nemertodermatids Meara stichopi and Nemertoderma westbladi and the xenoturbellid Xenoturbella bocki), and have constructed comprehensive datasets of xenacoelomorph proteins (proteomes (entire set of proteins expressed by a specific organism (UniProt Consortium, 2010))). I used these, together with proteomes from 60 other species, to construct a database of gene families, which have descended from the same common ancestor within the broad range of 67 species within the animal kingdom. Based on inferred orthology/paralogy relations within 2 these families, I reconstructed the duplications, gains and losses of genes across the Metazoa. The analysis of ancestral gene family content is suggestive for the phylogenetic position of the Xenacoelomorpha, as ancestral Xenacoelomorpha gene content is more similar to inferred Xenambulacraria gene content then to ancestral Bilateria gene content. Moreover, Xenacoelomorpha show more simultaneous gene losses with Ambulacraria then with other major Bilateria clades. To reconstruct a molecular phylogenetic tree of Xenacoelomorpha, I first established a bioinformatics pipeline for large-scale molecular phylogeny reconstruction, by comparing 3 commonly used automated methods for orthology and paralogy prediction (OMA, CEGMA, OrthoMCL). I tested the application of these methods in constructing phylogenetic matrices from high throughput sequencing data. I used the best performing pipeline to infer the species tree involving 8 Xenacoelomorpha species. Our phylogenetic analysis tentatively supports the placement of Xenacoelomorpha as a sister group of Ambulacrari