Evolutionary regulation of the blind subterranean mole rat, Spalax, revealed by genome-wide gene expression.

We applied genome-wide gene expression analysis to the evolutionary processes of adaptive speciation of the Israeli blind subterranean mole rats of the Spalax ehrenbergi superspecies. The four Israeli allospecies climatically and adaptively radiated into the cooler, mesic northern domain (N) and warmer, xeric southern domain (S). The kidney and brain mRNAs of two N and two S animals were examined through cross-species hybridizations with two types of Affymetrix arrays (mouse and rat) and muscle mRNA of six N and six S animals with spotted cDNA mouse arrays. The initial microarray analysis was hypothesis-free, i.e., conducted without reference to the origin of animals. Principal component analysis revealed that 20-30% of the expression signal variability could be explained by the differentiation of N-S species. Similar N-S effects were obtained for all tissues and types of arrays: two Affymetrix microarrays using probe oligomer signals and the spotted array. Likewise, ANOVA and t test statistics demonstrated significant N-S ecogeographic divergence and region-tissue specificity in gene expression. Analysis of differential gene expression between species corroborates previous results deduced by allozymes and DNA molecular polymorphisms. Functional categories show significant N-S ecologic putative adaptive divergent up-regulation of genes highlighting a higher metabolism in N, and potential adaptive brain activity and kidney urine cycle pathways in S. The present results confirm ecologic-genomic separation of blind mole rats into N and S. Gene expression regulation appears to be central to the evolution of blind mole rats.

Adaptive algorithm of automated annotation.

MOTIVATION: It is common knowledge that the avalanche of data arriving from the sequencing projects cannot be annotated either experimentally or manually by experts. The need for a reliable and convenient tool for automated sequence annotation is broadly recognized. RESULTS: Here, we describe the Adaptive Algorithm of Automated Annotation (A(4)) based on a statistical approach to this problem. The mathematical model relates a set of homologous sequences and descriptions of their functional properties, and calculates the probabilities of transferring a sequence description onto its homologue. The proposed model is adaptive, its parameters (distribution characteristics, transference probabilities, thresholds, etc.) are dynamic, i.e. are generated individually for the sequences and various functional properties (words of the description). The proposed technique significantly outperforms the widely used test for frequency threshold, which is a special case of our model realized for the simplest set of parameters. The prediction technique has been realized as a computer program and tested on a random sequence sampling from SWISS-PROT. AVAILABILITY: The automated annotation program based on the proposed algorithm is available through the Web browser at http://www.genebee.msu.su/services/annot/basic.html.

A novel method of multiple alignment of biopolymer sequences.

A novel algorithm for multiple alignment of biological sequences is suggested. At the first step the DotHelix procedure is employed for construction of motifs, i.e. continuous fragments of local similarity of various "thickness" and strength, and then these motifs are concatenated into chains consistent with the order of letters in the sequences. The algorithm is implemented in the MA-Tools program of the GeneBee package. An example illustrating the effectivity of the algorithm is presented.

Construction of the full local similarity map for two biopolymers.

A novel algorithm for construction of complete maps of local similarity for two biopolymer sequences is described. The algorithm is much faster than the related Altschul-Erickson procedure, it is implemented as the Dot-Helix module within the GeneBee package. Performance of the algorithm is exemplified with the analysis of the polyproteins of two poliovirus type 3 strains and its effectivity is compared to the Staden method. Possible applications of the algorithm are briefly discussed.