Computer Analysis of Glioma Transcriptome Profiling: Alternative Splicing Events.

Here we present the analysis of alternative splicing events on an example of glioblastoma cell culture samples using a set of computer tools in combination with database integration. The gene expression profiles of glioblastoma were obtained from cell culture samples of primary glioblastoma which were isolated and processed for RNA extraction. Transcriptome profiling of normal brain samples and glioblastoma were done by Illumina sequencing. The significant differentially expressed exon-level probes and their corresponding genes were identified using a combination of the splicing index method. Previous studies indicated that tumor-specific alternative splicing is important in the regulation of gene expression and corresponding protein functions during cancer development. Multiple alternative splicing transcripts have been identified as progression markers, including generalized splicing abnormalities and tumor- and stage-specific events. We used a set of computer tools which were recently applied to analysis of gene expression in laboratory animals to study differential splicing events. We found 69 transcripts that are differentially alternatively spliced. Three cancer-associated genes were considered in detail, in particular: APP (amyloid beta precursor protein), CASC4 (cancer susceptibility candidate 4) and TP53. Such alternative splicing opens new perspectives for cancer research.

Dysfunction in Ribosomal Gene Expression in the Hypothalamus and Hippocampus following Chronic Social Defeat Stress in Male Mice as Revealed by RNA-Seq.

Chronic social defeat stress leads to the development of anxiety- and depression-like states in male mice and is accompanied by numerous molecular changes in brain. The influence of 21-day period of social stress on ribosomal gene expression in five brain regions was studied using the RNA-Seq database. Most Rps, Rpl, Mprs, and Mprl genes were upregulated in the hypothalamus and downregulated in the hippocampus, which may indicate ribosomal dysfunction following chronic social defeat stress. There were no differentially expressed ribosomal genes in the ventral tegmental area, midbrain raphe nuclei, or striatum. This approach may be used to identify a pharmacological treatment of ribosome biogenesis abnormalities in the brain of patients with "ribosomopathies."

Analysis of differential gene expression by RNA-seq data in brain areas of laboratory animals.

Computer analysis of gene expression in the nervous system plays a fundamental role in biology, genetics, and neurosciences. We studied molecular and genetic mechanisms of enhanced aggressiveness in comparison with tolerant behaviour using experimental animal models developed at the Institute of Cytology and Genetics SB RAS. Grey rats (Rattus norvegicus) have been subjected to selection during several generations in two directions – friendly, tolerant behaviour towards man (tame grey rats) and increased aggressive behaviour. We used samples from hypothalamus, mesencephalic tegmentum and periaqueductum grey matter from brain areas of grey rats genetically selected by behaviour in many generations. The set of computer tools and data processing pipelines helped to find genes and gene regulation patterns related to behaviour patterns. RNA - profiling experiments revealed the lists of differentially expressed genes in the contrast samples as well as differentially spliced isoforms. The gene ontology categories of protein transport, phosphoproteins, and nucleotide binding are presented together with categories of transmission of nerve impulses and neuron development were identified. Differential alternative splicing events found in the brain areas studied are statistically significant. We discuss role of alternative splicing events for neurospecific genes in behaviour patterns as well as extension of brain transcriptomics profiling.

Accuracy of protein allergenicity prediction can be improved by taking into account data on allergenic protein discontinuous peptides.

Allergy poses major health problems in industrialized countries, affecting over 20% of the population. Proteins from transgenic foods, cosmetics, animal hair, and other ubiquitous sources can be allergens. For this reason, development of improved methods for the prediction of potential allergenicity of proteins is timely. The currently available approaches to allergenicity prediction are numerous. Some approaches relied heavily on information on protein three-dimensional (3D) structure for allergenicity prediction. They required knowledge about 3D structure of query protein, thereby considerably restricting analysis to only those proteins whose 3D structure was known. As a consequence, many proteins with unknown structure could be overlooked. We developed a new method for allergenicity prediction, using information on protein 3D structure only for training. Three-dimensional structures of known allergenic proteins were used for representing protein surface as patches designated as discontinuous peptides. Allergenicity was predicted through search of such peptides in query protein sequences. It was demonstrated that the information on the discontinuous peptides made feasible better prediction of allergenic proteins. The allergenicity prediction method is available at http://www-bionet.sscc.ru/psd/cgi-bin/programs/Allergen/allergen.cgi .

Visualization and analysis of a cardio vascular disease- and MUPP1-related biological network combining text mining and data warehouse approaches.

Detailed investigation of socially important diseases with modern experimental methods has resulted in the generation of large volume of valuable data. However, analysis and interpretation of this data needs application of efficient computational techniques and systems biology approaches. In particular, the techniques allowing the reconstruction of associative networks of various biological objects and events can be useful. In this publication, the combination of different techniques to create such a network associated with an abstract cell environment is discussed in order to gain insights into the functional as well as spatial interrelationships. It is shown that experimentally gained knowledge enriched with data warehouse content and text mining data can be used for the reconstruction and localization of a cardiovascular disease developing network beginning with MUPP1/MPDZ (multi-PDZ domain protein).