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.gov). Considering the base composition of the HCV ORFs, both UA and UU dinucleotides were less frequent than predicted in each of 162 HCV RNAs. UA dinucleotides were significantly less frequent than predicted at each of the three codon positions while UU dinucleotides were less frequent than predicted predominantly at the wobble position of codons. UA and UU dinucleotides were among the least abundant dinucleotides in HCV RNA ORFs. Furthermore, HCV genotype 1 RNAs have a lower frequency of UA and UU dinucleotides than genotype 2 and 3 RNAs, perhaps contributing to increased resistance of HCV genotype 1 infections to interferon therapy. In vitro, RNase L cleaved both HCV genotype 1 and 2 RNAs efficiently. Thus, RNase L can cleave HCV RNAs efficiently and variably reduced frequencies of UA and UU dinucleotides in HCV RNA ORFs are consistent with the selective pressure of RNase L.

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. Phylogenies constructed on nitrogen fixation genes are not in agreement with the tree-of-life based on 16S rRNA but do not conclusively distinguish between gene loss and LGT hypotheses. Using a series of analyses on a set of complete genomes, our results distinguish two structurally distinct classes of MoFe nitrogenases whose distribution cuts across lines of vertical inheritance and makes us believe that a conclusive case for LGT has been made.

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. This observation can be used in the discovery of transcription factor binding sites. Here we present a rigorous means to accomplish this. In particular, we constrain the order of the information (entropy) in the columns of the position specific weight matrix (PWM) which characterizes the motif being sought. We then show how to compute the maximum likelihood estimate of a PWM under such order restrictions. This computation is easily integrated with the EM algorithm or the Gibbs sampler to enhance performance in the search for motifs in unaligned sequences. We demonstrate our method on a well-known data set of binding sites of the transcription factor Crp in E. coli.

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. This method is applied to two families: the phycobiliproteins, light-harvesting proteins in cyanobacteria, red algae, and cryptomonads, and the globins that function in oxygen storage and transport. The sites identified by the procedure are located in key structural positions and merit further experimental study.