UNLABELLED: TURNIP comprises a suite of Perl scripts and modules that facilitates the resolution of microheterogeneity within hard-to-assemble repetitive DNA sequences. TURNIP was originally developed for the Saccharomyces Genome Resequencing Project (SGRP) within which the ribosomal DNA (rDNA) of 36 strains of S.cerevisiae were analysed to investigate the occurrence of potential polymorphisms. Here, 'partially resolved SNPs', or pSNPs, as well as indels, were found to be far more prevalent than previously suspected. More generally, the TURNIP software ascertains degrees of variation between large tandem repeats within a single locus, offering insights into mechanisms of genome stability and gene conversion in any organism for which genome sequence data are available. AVAILABILITY: The TURNIP source code, results files and online help are available at http://www.ncyc.co.uk/software/turnip.html.

UNLABELLED: MPP is a Java application, encompassing both new and established algorithms, for the analysis of gene and marker content datasets arising from high-throughput microarray techniques. MPP analyses flat file output from microarray experiments to determine the probability of the presence or absence of genes or markers within a genome. MPP can construct gene or marker content datasets for a number of genomes and can use the data to estimate an evolutionary tree or network. Results from gene content analyses may be validated by comparing them to known gene contents. MPP was initially developed to analyse data derived from comparative genome hybridization (CGH) microarray experiments in fungi and bacteria. It has recently been adapted to analyse retrotransposon-based insertion polymorphism (RBIP) marker scores derived from tagged microarray marker (TAM) experiments in pea. New analytical procedures may be added easily to MPP as plugins in order to increase the scope of the software. AVAILABILITY: MPP source code, executables and online help are available at http://cbr.jic.ac.uk/dicks/software/

MOTIVATION: Recombination can be a prevailing drive in shaping genome evolution. RAT (Recombination Analysis Tool) is a Java-based tool for investigating recombination events in any number of aligned sequences (protein or DNA) of any length (short viral sequences to full genomes). It is an uncomplicated and intuitive application and allows the user to view only the regions of sequence alignments they are interested in. RESULTS: RAT was applied to viral sequences. Its utility was demonstrated through the detection of a known recombinant of HIV and a detailed analysis of Noroviruses, the most common cause of viral gastroenteritis in humans. AVAILABILITY: RAT, along with a user's guide, is freely available from http://jic-bioinfo.bbsrc.ac.uk/bioinformatics-research/staff/graham_etherington/RAT.htm.

It has long been known that evolutionary trees (phylogenies) can be estimated by comparing the DNA or protein sequences of homologous genes across different organisms. More recently, attempts have been made to estimate phylogenies by comparing entire genomes. These attempts have focused largely on comparisons of gene content and gene order. Many different methods have been proposed for making these comparisons. These include primarily maximum parsimony and distance methods, although more recently maximum likelihood and Bayesian methods are being developed. This paper discusses each of these approaches in turn, including their merits and limitations, and any software which is available to make use of them.

MOTIVATION: Yeasts are often still identified with physiological growth tests, which are both time consuming and unsuitable for detection of a mixture of organisms. Hence, there is a need for molecular methods to identify yeast species. RESULTS: A hashing technique has been developed to search for unique DNA sequences in 702 26S rRNA genes. A unique DNA sequence has been found for almost every yeast species described to date. The locations of the unique defining sequences are in accordance with the variability map of large subunit ribosomal RNA and provide detail of the evolution of the D1/D2 region. This approach will be applicable to the rapid identification of unique sequences in other DNA sequence sets. AVAILABILITY: Freely available upon request from the authors. SUPPLEMENTARY INFORMATION: Results are available at http://www.sys.uea.ac.uk/~jjw/project/paper