Evolution of SINE S1 retroposons in Cruciferae plant species

The S1 element is a plant short interspersed element (SINE) that was first described and studied in Brassica napus. In this work, we investigated the distribution and the molecular phylogeny of the S1 element within the Cruciferae (= Brassicaceae). S1 elements were found to be widely distributed within the Cruciferae, especially in species of the tribe Brassiceae. The molecular phylogeny of S1 elements in eight Cruciferae species (Brassica oleracea, Brassica rapa, Brassica napus, Brassica nigra, Sinapis, arvensis, Sinapis pubescens, Coincya monensis, and Vella spinosa) was inferred using 14-36 elements per species. Significant neighbor-joining and maximum-parsimony phylogenetic clusters, supported by high bootstrap P values and/or represented in 100% of the most-parsimonious trees, were observed for each species. Most of these clusters probably correspond to recent species-specific bursts of S1 amplification. Since these species diverged recently, S1 amplification in Cruciferae plants is proposed to be a highly dynamic process that could contribute to genome rearrangements and eventually lead to reproductive isolation. S1 sequence analysis also revealed putative gene conversion events that occurred between different S1 elements of a given species. These events suggest that gene conversion is a minor but significant component of the molecular drive governing S1 concerted evolution.      

Size homoplasy and mutational processes of interrupted microsatellites in two bee species, Apis mellifera and Bombus terrestris (Apidae)

Similar microsatellite electromorphs (PCR products of the same size) can arise from independent mutational events. Such alleles are not identical by descent. This phenomenon, termed size homoplasy, was studied by sequencing electromorphs of two microsatellite loci in which the stretch of basic repeats is interrupted by different short (1-2 bp) DNA motifs. The number and position of these interruptions were established for electromorphs from closely and distantly related populations of honeybees and bumblebees. No sequence difference was found when electromorphs came from the same subspecies or from closely related subspecies, suggesting that they were probably identical by descent. In contrast, sequence differences were often detected in distantly related subspecies, showing that size homoplasy frequently occurs at this level of population differentiation. Size homoplasy is increased by limits to free length variation of alleles, a phenomenon that seems to act on interrupted microsatellites when comparing distantly related taxa, that is, honeybee subspecies from different evolutionary lineages. Electromorph sequences suggest that, within the scope of these limits, large mutation events have occurred frequently at both interrupted loci studied. In good agreement with the molecular data, computations based on the observed heterozygosity and number of electromorphs and simulation studies showed that neither locus fits the one-step stepwise mutant model (SMM). We speculate that interrupted microsatellites in general could be characterized by a higher variance in repeat number and consequently a lower homoplasy rate than pure ones. Hence, interrupted microsatellites should be most appropriate for investigating population differentiation and evolutionary relationship between relatively distant populations.      

The effect of oligonucleotide microarray data pre-processing on the analysis of patient-cohort studies

Background  

Intensity values measured by Affymetrix microarrays have to be both normalized, to be able to compare different microarrays by removing non-biological variation, and summarized, generating the final probe set expression values. Various pre-processing techniques, such as dChip, GCRMA, RMA and MAS have been developed for this purpose. This study assesses the effect of applying different pre-processing methods on the results of analyses of large Affymetrix datasets. By focusing on practical applications of microarray-based research, this study provides insight into the relevance of pre-processing procedures to biology-oriented researchers.     

An interactive tool for visualization of relationships between gene expression profiles

Background  

Application of phenetic methods to gene expression analysis proved to be a successful approach. Visualizing the results in a 3-dimentional space may further enhance these techniques.