Probing-directed identification of novel structured RNAs.

Transcripts often harbor RNA elements, which regulate cell processes co- or post-transcriptionally. The functions of many regulatory RNA elements depend on their structure, thus it is important to determine the structure as well as to scan genomes for structured elements. State of the art ab initio approaches to predict structured RNAs rely on DNA sequence analysis.

Comparative genome analysis of Pseudogymnoascus spp. reveals primarily clonal evolution with small genome fragments exchanged between lineages.

Background: Pseudogymnoascus spp. is a wide group of fungi lineages in the family Pseudorotiaceae including an aggressive pathogen of bats P. destructans.

RegPrecise 3.0--a resource for genome-scale exploration of transcriptional regulation in bacteria.

Background: Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different taxonomic groups, whose lifestyles and natural environments are substantially different, possess highly diverged transcriptional regulatory networks. The comparative genomics approaches are useful for in silico reconstruction of bacterial regulons and networks operated by both transcription factors (TFs) and RNA regulatory elements (riboswitches).

The miniature genome of a carnivorous plant Genlisea aurea contains a low number of genes and short non-coding sequences.

Background: Genlisea aurea (Lentibulariaceae) is a carnivorous plant with unusually small genome size - 63.6 Mb - one of the smallest known among higher plants. Data on the genome sizes and the phylogeny of Genlisea suggest that this is a derived state within the genus.

Functional implications of splicing polymorphisms in the human genome.

Proper splicing is often crucial for gene functioning and its disruption may be strongly deleterious. Nevertheless, even the essential for splicing canonical dinucleotides of the splice sites are often polymorphic. Here, we use data from The 1000 Genomes Project to study single-nucleotide polymorphisms (SNPs) in the canonical dinucleotides.

CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation.

Identification of transcriptional regulatory regions and tracing their internal organization are important for understanding the eukaryotic cell machinery. Cis-regulatory modules (CRMs) of higher eukaryotes are believed to possess a regulatory 'grammar', or preferred arrangement of binding sites, that is crucial for proper regulation and thus tends to be evolutionarily conserved. Here, we present a method CORECLUST (COnservative REgulatory CLUster STructure) that predicts CRMs based on a set of positional weight matrices.

Recognition of transmembrane segments in proteins: review and consistency-based benchmarking of internet servers.

Membrane proteins perform a number of crucial functions as transporters, receptors, and components of enzyme complexes. Identification of membrane proteins and prediction of their topology is thus an important part of genome annotation. We present here an overview of transmembrane segments in protein sequences, summarize data from large-scale genome studies, and report results of benchmarking of several popular internet servers.

The channel in transporters is formed by residues that are rare in transmembrane helices.

Transmembrane transport is an essential component of the cell life. Many genes encoding known or putative transport proteins are found in bacterial genomes. In most cases their substrate specificity is not experimentally determined and only approximately predicted by comparative genomic analysis.

BATMAS30: amino acid substitution matrix for alignment of bacterial transporters.

Aligned amino acid sequences of three functionally independent samples of transmembrane (TM) transport proteins have been analyzed. The concept of TM-kernel is proposed as the most probable transmembrane region of a sequence. The average amino acid composition of TM-kernels differs from the published amino acid composition of transmembrane segments.