Gene Network of Type 2 Diabetes: Reconstruction and Analysis

Zamyatin Vladimir Igorevich1, Mustafin Zakhar Sergeevich2, Matushkin Yury Georgievich3, Afonnikov Dmitry Arkadievich4, Klimontov Vadim Valerievich5, Lashin Sergey Aleksandrovich61Institute of Cytology and Genetics, Novosibirsk State University, zamyatin@bionet.nsc.ru2Institute of Cytology and Genetics, Novosibirsk State University, mustafin@bionet.nsc.ru3Institute of Cytology and Genetics, Novosibirsk State University, mat@bionet.nsc.ru4Institute of Cytology and Genetics, Novosibirsk State University, ada@bionet.nsc.ru5Institute of Cytology and Genetics, Novosibirsk State University, klimontov@mail.ru6Institute of Cytology and Genetics, Novosibirsk State University, lashin@bionet.nsc.ru Currently, due to the appearance of an increasing number of genomic, molecular, histological data, there is an intensive detailing of individual molecular genetic systems of the human body and phenotypic deviations caused by violations in one or more elements of these systems. At the same time, there is no, as such, a holistic understanding of the nature of the formation and course of type II diabetes, which includes a sufficient amount of available experimental data. In this study, we reconstructed gene networks of transcriptional regulation, functional connectivity, and protein-protein interactions for type 2 diabetes. Information on the evolutionary age of genes was superimposed on the network; it was shown that the genes in question are predominantly “evolutionarily old”. New genes have been found that were not previously associated with type 2 diabetes, such as PER1, PER3, ARHGEF4, genes whose homologues are associated with the onset of diabetes in mice – CLOCK, ARNTL (encoding transcription factors) – the goals for subsequent experimental confirmation. Validation of gene networks by analysis of tissue-specific expression has shown that most genes included in putative signal transduction pathways are expressed in the same tissues.

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Reconstruction of Dementia Gene Network Using Online Bioinformatics Tools

Poster (download) Oleg Fateev1, Sergey S. Kovalev2, Yuriy L. Orlov31I.M.Sechenov First Moscow State Medical University, Moscow, Russia, fodmr1997@gmail.com2Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia, kovalev@bionet.nsc.ru3Institute of Digital Medicine I.M.Sechenov First Moscow State Medical University), Moscow, Russia, orlov@bionet.nsc.ru In this work, the set of genes associated with mental diseases such as dementia was examined and analyzed using previously developed gene ontology annotation tools and databases. The aim of the study is to describe the molecular mechanisms of dementia based on the analysis of the gene set as a whole, using available bioinformatics databases, annotation and recent publications. Dementia is a chronic, general, usually irreversible decrease in cognitive function that affects all aspects of cognitive activity. The enriched gene ontology categories for dementia genes are regulation of neuronal death, regulation of cell death, organization of cellular components, and cognition. The study of the structure of the gene network shows a high connectivity of genes and their products.

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