Hepatitis C virus RNA: dinucleotide frequencies and cleavage by RNase L.

Ribonuclease L (RNase L) is an antiviral endoribonuclease that cleaves hepatitis C virus (HCV) RNA at single-stranded UA and UU dinucleotides throughout the open reading frame (ORF). To determine whether RNase L exerts evolutionary pressure on HCV we examined the frequencies of UA and UU dinucleotides in 162 RNA sequences from the Los Alamos National Labs HCV Database (http://hcv.lanl.

Quantitative exploration of the occurrence of lateral gene transfer by using nitrogen fixation genes as a case study.

Lateral gene transfer (LGT) is now accepted as an important factor in the evolution of prokaryotes. Establishment of the occurrence of LGT is typically attempted by a variety of methods that includes the comparison of reconstructed phylogenetic trees, the search for unusual GC composition or codon usage within a genome, and identification of similarities between distant species as determined by best blast hits. We explore quantitative assessments of these strategies to study the prokaryotic trait of nitrogen fixation, the enzyme-catalyzed reduction of N(2) to ammonia.

Estimating motifs under order restrictions.

Transcription factors and many other DNA-binding proteins recognize more than one specific sequence. Among sequences recognized by a given DNA-binding protein, different positions exhibit varying degrees of conservation. The reason is that base pairs that are more extensively contacted by the protein tend to be more conserved.

Detecting DNA regulatory motifs by incorporating positional trends in information content.

On the basis of the observation that conserved positions in transcription factor binding sites are often clustered together, we propose a simple extension to the model-based motif discovery methods. We assign position-specific prior distributions to the frequency parameters of the model, penalizing deviations from a specified conservation profile. Examples with both simulated and real data show that this extension helps discover motifs as the data become noisier or when there is a competing false motif.

Finding important sites in protein sequences.

By using sequence information from an aligned protein family, a procedure is exhibited for finding sites that may be functionally or structurally critical to the protein. Features based on sequence conservation within subfamilies in the alignment and associations between sites are used to select the sites. The sites are subject to statistical evaluation correcting for phylogenetic bias in the collection of sequences.