Alignment of RNA base pairing probability matrices

MOTIVATION: Many classes of functional RNA molecules are characterized by highly conserved secondary structures but little detectable sequence similarity. Reliable multiple alignments can therefore be constructed only when the shared structural features are taken into account. Since multiple alignments are used as input for many subsequent methods of data analysis, structure-based alignments are an indispensable necessity in RNA bioinformatics. RESULTS: We present here a method to compute pairwise and progressive multiple alignments from the direct comparison of base pairing probability matrices. Instead of attempting to solve the folding and the alignment problem simultaneously as in the classical Sankoff's algorithm, we use McCaskill's approach to compute base pairing probability matrices which effectively incorporate the information on the energetics of each sequences. A novel, simplified variant of Sankoff's algorithms can then be employed to extract the maximum-weight common secondary structure and an associated alignment. AVAILABILITY: The programs pmcomp and pmmulti described in this contribution are implemented in Perl and can be downloaded together with the example datasets from http://www.tbi.univie.ac.at/RNA/PMcomp/. A web server is available at http://rna.tbi.univie.ac.at/cgi-bin/pmcgi.pl     

Structural parameters affecting the kinetics of RNA hairpin formation

There is little experimental knowledge on the sequence dependent rate of hairpin formation in RNA. We have therefore designed RNA sequences that can fold into either of two mutually exclusive hairpins and have determined the ratio of folding of the two conformations, using structure probing. This folding ratio reflects their respective folding rates. Changing one of the two loop sequences from a purine- to a pyrimidine-rich loop did increase its folding rate, which corresponds well with similar observations in DNA hairpins. However, neither changing one of the loops from a regular non-GNRA tetra-loop into a stable GNRA tetra-loop, nor increasing the loop size from 4 to 6 nt did affect the folding rate. The folding kinetics of these RNAs have also been simulated with the program ‘Kinfold’. These simulations were in agreement with the experimental results if the additional stabilization energies for stable tetra-loops were not taken into account. Despite the high stability of the stable tetra-loops, they apparently do not affect folding kinetics of these RNA hairpins. These results show that it is possible to experimentally determine relative folding rates of hairpins and to use these data to improve the computer-assisted simulation of the folding kinetics of stem–loop structures.     

Stochastic traits of molecular evolution--acceptance of point mutations in native actin genes

A stochastic matrix of nucleotide mutation probabilities is derived by counting differences and identities in alignments of native actin genes, with the aim of obtaining a more reliable data base for regular modes of molecular evolution. The evolution of DNA sequences is thereby considered as a Markov process consisting of events (point mutations) characterized by a stochastic matrix for codon-codon interchanges. The genetic distance is set to 1 PAM (percentage of accepted point mutations). The results can be reproduced by Monte Carlo simulations which are subjected to selective constraints. The latter are observed as nonrandom codon usage and ratios of silent to recognizable point mutations. Specific patterns within the matrix of mutation probabilities attest to preferences of natural selection in the evolution of a specific protein.     

Endothelial Transient Receptor Potential Conical Channel (TRPC)-3 Activation Induces Vasogenic Edema Formation in the Rat Piriform Cortex Following Status Epilepticus

Transient receptor potential canonical channel (TRPC) is a nonselective cation channel permeable to Ca²⁺, which express in many cell types, including neurons. However the alterations in TRPC receptor expressions in response to status epilepticus (SE) have not been explored. Therefore, the present study was designated to elucidate the roles of TRPC3 in neuronal death and vasogenic edema within the rat piriform cortex (PC) following SE. In non-SE animals, TRPC3 immunoreactivity was abundantly detected in the PC. Following SE, TRPC3 immunoreactivity was increased in neurons. Furthermore, TRPC3 expression was detected in endothelial cells that did not contain it in non-SE animals. Loss of SMI-71 (a blood–brain barrier antigen) immunoreactivity was also observed in TRPC3 positive endothelial cells. In addition, FJB positive neurons and vasogenic edema were noticeably detected in the PC. To directly determine whether TRPC3 activation is correlated to SE-induced vasogenic edema formation and neuronal damages in the PC, the effect of Pyr-3 (a TRPC3 antagonist) on SE-induced insults were investigated. Pyr-3 infusion effectively attenuated vasogenic edema in the PC as compared to the vehicle. Therefore, our findings indicate that TRPC3 activation/overexpression induced by SE may involve BBB disruption and neuronal damages in the rat PC following SE. Therefore, the present study was TRPC3 may play an important role in SE-induced vasogenic edema formation through BBB disruptions in the rat PC.     

Vienna RNA secondary structure server

The Vienna RNA secondary structure server provides a web interface to the most frequently used functions of the Vienna RNA software package for the analysis of RNA secondary structures. It currently offers prediction of secondary structure from a single sequence, prediction of the consensus secondary structure for a set of aligned sequences and the design of sequences that will fold into a predefined structure. All three services can be accessed via the Vienna RNA web server at http://rna.tbi.univie.ac.at/.     

Prediction of consensus RNA secondary structures including pseudoknots

Most functional RNA molecules have characteristic structures that are highly conserved in evolution. Many of them contain pseudoknots. Here, we present a method for computing the consensus structures including pseudoknots based on alignments of a few sequences. The algorithm combines thermodynamic and covariation information to assign scores to all possible base pairs, the base pairs are chosen with the help of the maximum weighted matching algorithm. We applied our algorithm to a number of different types of RNA known to contain pseudoknots. All pseudoknots were predicted correctly and more than 85 percent of the base pairs were identified.