International conference on bioinformatics of genome regulation
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Key words: Mosaic gene network, Mathematical modeling, Apoptosis, Tumor necrosis factor, Hepatitis C virus Motivation and Aim: Modeling of gene networks is widely used in systems biology to study the functioning of molecular genetic systems, including pathogen-host interac- tions. Most of the existing mathematical modeling techniques are useful for the analysis of the well-studied biological processes, for which there is complete information about rates of reactions. However, the complex biological processes corresponding to, for ex- ample, phenotypic traits of an organism, or pathological disease processes, including pathogen-host interaction, usually involves a set of interacting networks that can be rep- resented by a mosaic gene network. In such networks, for each mosaic fragment there is a mathematical model, however, information about the molecular and genetic relation- ships between these fragments may be missing. Methods and Algorithms: The approach of mosaic gene networks modeling in case of absence of precise information about the molecular and genetic links between the mosa- ic pieces is based on the genetic screening data on the effect of the elements perturbation of one piece and response of elements in remaining piece. The method uses approaches of control theory and applies mathematical models, written in the form of a system of ordinary differential equations (ODE). Results: Modeling of random mosaic gene regulatory networks, consisting of two piec- es, has shown high efficiency of developed method (mean deviation of the dynamics of mosaic networks elements from behavior of the original gene networks has been less than 10%). Using this approach, we have been integrated the model of hepatitis C virus subgenomic replicon replication and the model of apoptosis in cells. Such mosaic network allowed us to describe the regulation of apoptosis process by HCV. Analy- sis of the mosaic model revealed that the regulation of TNF-induced signaling by the HCV network is crucially dependent on the RIP1, TRADD, TRAF2, FADD, IKK, IκBα, c-FLIP, and BAR genes. Conclusion: Overall, the developed mosaic gene network modelling approach demon- strated good predictive power and allowed the prediction of new regulatory nodes in HCV action on apoptosis and the NF-κB pathway. Those theoretical predictions could be a basis for further experimental verification. 236 THE TENTH INTERNATIONAL CONFERENCE ON BIOINFORMATICS OF GENOME REGULATION AND STRUCTURE\SYSTEMS BIOLOGY GUT MICROBIOTA IN CASE OF PARKINSON'S DISEASE AND OTHER NEUROLOGICAL PATHOLOGIES: COMPARATIVE STUDY V.A. Petrov 1 *, V.M. Alifirova 1 , I.V. Saltykova 1 , Y.B. Dorofeyeva 1 , A.V. Tyakht 2 , E.S. Kostryukova 2 , A.E. Sazonov 1, 3 1 Siberian State Medical University, Tomsk, Russia 2 Scientific Research Institute for Physical-Chemical Medicine, Moscow, Russia 3 Lomonosov Moscow State University, Moskow, Russia * Corresponding author: vyacheslav.a.petrov@mail.ru Key words: gut microbiota, metagenome, Parkinson's disease, 16S sequencing Motivation and Aim: Recently it is shown that nervous system of host organism interact with gut microbiota. In case of neurological disorders, especially for Parkinson's disease gut microbiota altered1. But little known about differences in microbiota composition among different neurological pathologies. Methods and Algorithms: The study was conducted in a three groups of patients (60 con- trol subjects, 60 subjects with Parkinson's disease and 32 subjects with other neurologi- cal pathologies, including multiple sclerosis, idiopathic dystonia and essential tremor). After the total DNA isolation and library preparation sequencing of the variable V3–V4 16S rRNA gene regions was performed by using MiSeq Reagent Kit v2 and MiSDefault device according to the manufacturer's recommendations. Taxonomic classification, al- pha- and beta-diversity performed using QIIME Software 1.9.0. Determination of opera- tion taxonomic units (OTU) performed with the usage of Greengenes v. 13.5 database (OTU's representative set picking) and HITdb (taxonomy assigning using RDP Classi- fier). Statistical comparison of the groups of samples was performed using Galaxy-based LefSe algorithm. Results: The overall composition of fecal microbiota was affected by disease status both in terms of α- (chao1, Shannon and observed OTUs indices) and β- (weighted UniFrac) diversity. Gut microbiota of patients with Parkinson's disease and other neurological pa- thologies is characterized by lower taxonomic diversity in comparison with healthy con- trol without significant difference between Parkinson's disease and other neurological pathologies. In addition, there were significant differences in compositional dissimilarity between groups based upon ANOSIM and MRPP statistical algorithms. According to LefSe algorithm, there were 44 species and 22 genera of bacteria and archaea with dif- ference in abundance within groups. The top bacterial markers with highest LDA scores among the groups were Christensenella minuta on the species level and Bifidobacterium on the genus level for Parkinson's disease group, Bacteroides massiliensis on the species level and Bacteroides on the genus level for control group, Anoxystipes fissicatena and Blautia for other neurological pathologies group. Conclusion: Gut microbiota composition is specifically altered in case of different neu- rological disorders. Acknowledgements Ministry of Education and Science of the Russian Federation sup- ported the work (RFMEFI60414X0075, № 14.604.21.0075). 1. F. Scheperjans et al. (2015). Gut microbiota are related to Parkinson's disease and clinical phenotype// Mov Disord, 30(3):350-8. 237 THE TENTH INTERNATIONAL CONFERENCE ON BIOINFORMATICS OF GENOME REGULATION AND STRUCTURE\SYSTEMS BIOLOGY WORKFLOW FOR EXOME SEQUENCING IN IDENTIFICA- TION OF DE NOVO MUTATION IN THE NCL6 GENE D.A. Petukhova*, N.R. Maksimova, P.I. Guryeva, V.S. Kaymonov, M.T. Savvina Laboratory of Genome Medicine, Clinics of Medical Institute, North-Eastern Federal University * Corresponding author: todanilovadiana@gmail.com Key words: Next-generation sequencing, whole-exome sequencing, de novo mutation, neuronal ceroid lipo- fuscinosis type 6 (NCL6), trio family analysis Whole-exome sequencing using next-generation sequencing (NGS) technologies is gaining popularity in clinical practice. Associations between undescribed mutation with the clinical picture of disease is the true difficulty in analyzing of NGS data. Trio family analysis (father, mother and affected child) is a very powerful approach to identify potentially pathogenic ‘de novo’ mutations in the proband. We sequenced the exome (~552 genes) of affected child with suspected of leukodystrophy and both unaffected parents by using the TruSight Inherited Disease sequencing panel (Illumina inc., San Diego, CA, USA) on a Miseq sequencing system (Illumina inc., San Diego, CA, USA). In total, we obtained 7 Gb of sequence data with 2091 variations from the human reference genome sequence that were subjected to several filtering steps. The MiSeq system provides fully integrated on-instrument data analysis software. Basespace software performs secondary analyses on the base calls during the sequencing run. SNP’s and short INDEL’s are identified using the Genome Analysis Toolkit (GATK) by default. The number of candidate variants is reduced using a three-step filtration strategy to generate a short candidate mutation list. For the variant filtering and annotation we used Variant Studio version 2.2 (Illumina inc., San Diego, CA, USA) data analysis software. Initial quality filter removed less reliable variant calls and resulted in the identification of 1499 genetic variants. In the second step given the rare incidence of autosomal – recessive disease, we excluded known dbSNP variants from our variants database, reducing the number of candidate by more than 98% to a total of 37 variants. For further analysis, we applied an autosomal-recessive disease model and assumed that the mutation was inherited from both parents [1,2,3]. Therefore, we have customized trio family data filtering and have found a common homozygous mutation c.396dupT (p.Val133fs) in exon 4 of CLN6. Validation by Sanger sequencing also confirmed that the c.396dupT (p.Val133fs) mutation was indeed present in a homozygous state in the affected child and in a heterozygous state in the both parents. We identified a pathogenic de novo mutation c.396dupT (p.Val133fs) in the CLN6 gene, and made a diagnosis of neuronal ceroid lipofuscinosis type 6, suggesting that relatively high number of patients with neuronal ceroid lipofuscinosis type 6 may be hidden under the guise of leukodystrophy in Yakut population. References: 1. Yohe S, Hauge A, Bunjer K, Kemmer T, Bower M, Schomaker M, et al. Clinical validation of targeted next-generation sequencing for inherited disorders. Arch Pathol Lab Med. 2015;139:204–10. doi: 10.5858/arpa.2013-0625-OA. 2. Becker J, Semler O, Gilissen C, Li Y, Bolz HJ, Giunta C, et al. Exome sequencing identifies truncating mutations in human SERPINF1 in autosomal-recessive osteogenesis imperfecta. American journal of human genetics. 2011;88(3):362–71. doi: 10.1016/j.ajhg.2011.01.015 pmid:21353196; PubMed Central PMCID: PMC3059418. 3. Kmoch S, Stranecky V, Emes RD, Mitchison HM. Bioinformatic perspectives in the neuronal ceroid lipofuscinoses. Biochim Biophys Acta. 2012 S0925-4439(12)00301-8 [pii] 10.1016/j. bbadis.2012.12.010. 238 THE TENTH INTERNATIONAL CONFERENCE ON BIOINFORMATICS OF GENOME REGULATION AND STRUCTURE\SYSTEMS BIOLOGY MIRNA BINDING SITES IN THE MRNA OF HUMAN TITIN GENE I.V. Pinsky 1 *, A.T. Ivashchenko 1 , S.B. Labeit 2 1 Al-Farabi Kazakh National University, Almaty, Kazakhstan 2 Institute of Integrative Pathophysiplogy, Mannheim, Germany *Сorresponding author: ilya.pinskyi@mail.ru Keywords: titin, sarcomeres, isoform, miRNAs, mRNAs, CDS Motivation and Aim: Titin, the human muscle protein, is the largest in the nature (the longest isoform IC contains 35991 amino acid residues) and plays an important role in providing the elasticity and structural integrity of sarcomeres. Interruption of its synthesis leads to the development of a number of serious cardiovascular diseases such as heart failure, car- diomyopathy, ischemic heart disease, and myocardial infarction. Titin gene expression is controlled by miRNAs (microRNAs) that bind with the mRNAs of the gene and block their translation. Therefore, it is important to determine which miRNAs most strongly regulate the synthesis of human titin and what exons of the gene contain the binding sites because different exons of the gene are expressed in different types of muscle tissue at different stages of the human body development. Methods and Algorithms: The binding of 2563 human microRNAs with mRNA of human titin IC isoform, including all 363 exons of the human titin gene was determined using program miRTarget. The human miRNA sequences were taken from miRBase site (www. mirbase.org/), and the mRNA sequence of the titin gene was taken from Genbank (www. ncbi.nlm.nih.gov/genbank). The degree of binding (ΔG/ΔG m , %) was estimated according to the value of the ΔG/ΔG m ratio, where ΔG was equal to the free energy of miRNA-mRNA binding and ΔG m was equal to the energy of miRNA binding with its perfect complementary nucleotide sequence. Results: As a result of this research, 15 miRNA binding sites with scores not less than 90% were found and marked in exons of titin mRNA. miR-6861-5p has the largest number of binding sites. This miRNA bound with the mRNA of titin at positions 37324, 38077, and 38830 nt at the boundaries of exons 178-179, 187-188, and 196-197, respectively. Other miRNAs had only one binding site each. miR-494-5p bound with titin mRNA at position 1301 nt in the seventh exon. miR-578 bound with titin mRNA in the eleventh exon at posi- tion 1960 nt. The 58 th exon contained overlapping binding sites of two miRNAs (miR-374b- 3p and miR-374c-3p) in positions 17239 nt and 17241 nt, respectively. Exon 59 was a target for miR-3714, which interacted with the mRNA at position 17450 nt. Exon 75 was the target of miR-34a-3p, which interacted with the mRNA at position 22116 nt. The 85 th exon of the titin gene was the target for miR-1278, which interacted with titin mRNA at the position of 24928 nt. The 89 th exon had a binding site for miR-544b at position 26044 nt. The 326 th exon contained binding sites for miR-4738-3p and miR-136-3p. miR-4738-3p interacted with titin mRNA at position 74955 nt and miR-136-3p bound with mRNA of titin at position 71469 nt. Exon 339 also contained binding sites for miR-4693-5p and miR-4495, which bound with the mRNA for titin at positions 92464 nt and 93909 nt, respectively. Conclusion: The results of the computer analysis provide a theoretical basis for further experiments to validate the miRNA binding sites found in the mRNA of titin and to de- termine the miRNA concentrations in the blood and other cells and tissues of humans and mice. These results could then be used for diagnosis and treatment of human cardiovascular diseases. 239 THE TENTH INTERNATIONAL CONFERENCE ON BIOINFORMATICS OF GENOME REGULATION AND STRUCTURE\SYSTEMS BIOLOGY BIOSTORE: A CLOUD-COMPATIBLE HUB FOR BIOINFORMATICS RELATED TOOLS AND PLATFORMS S. Pintus 1 *, T. Valeev 1, 2 , I. Yevshin 1, 2 , F. Kolpakov 1, 2 1 Institute of Systems Biology Ltd., Novosibirsk, Russia 2 Design Technological Institute of Digital Techniques SB RAS, Novosibirsk, Russia * Corresponding author: sspintus@biouml.org Key words: containerization, Docker, cloud, workflow, web-server Motivation and Aim: The growing demand of flexible access and control of computa- tional resources and big data in bioinformatics have recently resulted in development of a wide range of cloud-based approaches targeted to bioinformatics, from cloud- compatible pipelines like GATK and workflow managers like Galaxy to large-scale bioinformatics oriented cloud services like Google Genomics. Today there is high demand for web based scalable platforms which would allow bio- medical and computations researchers and specialists to collaborate in developing and making use of bioinformatics solutions. Results: Here we introduce BioStore – a cloud-compatible hub for bioinformatics re- lated tools and platforms. The BioStore web server uses VNC client and command prompt SSH client to access GUI-based and command-line applications, respectively, which, in turn are organized in containerized manner. We use Docker to apply containerized approach which allows to create an isolated working environment for each project, and efficiently allocate computational resources. The union filesystem (AUFS) used in Docker allows to in- herit from already developed images and thus develop new containers. At the current state BioStore provides a number of tools for systems biology – Cell De- signer, Tellurium, COPASI, Cytoscape and , chemoinformatics, gene expression regu- lation and genome annotation The concept of BioStore suggests three kinds of users – developers of conainerized bioinformatics workplaces, advanced computational biologists who fluently use the functional of the tools and platforms and “layman” pure biologists or medical scientists who would prefer to run production-ready workflows The workflows are available in BioUML platform which also could be used as an IDE for various bioinformatics environments like R or Python Availability: http://wiki.biouml.org 240 THE TENTH INTERNATIONAL CONFERENCE ON BIOINFORMATICS OF GENOME REGULATION AND STRUCTURE\SYSTEMS BIOLOGY COMPUTATIONAL MODEL FOR MAMMALIAN CIRCADIAN OSCILLATOR INTERACTING WITH NAD+ / SIRT1 PATHWAY O.A. Podkolodnaya 1 , N.N. Tverdokhleb 1, 3 , N.L. Podkolodnyy 1, 2, 3 * 1 Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia 2 Institute of Computational Mathematics and Mathematical Geophysics SB RAS, Novosibirsk 3 Novosibirsk State University, Novosibirsk * Corresponding author: pnl@bionet.nsc.ru Key words: computer modeling, mammalian circadian oscillator, SIRT1 pathway Motivation and Aim: The mammalian circadian timing system is a finely tuned hierar- chical system which regulates a wide range of processes in the body (molecular genetic, physiological and behavioral) with a period close to 24 hours, allowing the body to optimally adapt to the cyclical changes of environment. Almost every cell in an organ- ism contains autonomous molecular genetic circadian oscillator (CO). The structure of this oscillator can be described by a complex gene network with the feedback process mediated transcription, post-translational modification of proteins, protein-protein inter- actions, chromatin modification, and others. The basis of the circadian oscillator struc- ture constitute by the two interlocked negative feedback loops generating the circadian rhythm. Additional feedbacks of this gene network provide stability of the oscillator functioning and its relationship with the other molecular-genetic systems and pathways of the organism. One of them is formed with the participation of NAD-dependent deacet- ylase SIRT1, which couples the deacetylation of a number of transcription factors and co-factors to the cleavage of NAD+. Therefore, SIRT1 play a vital role in metabolism, inflammation, apoptosis, stress resistance, energy responses to restriction and high calo- rie intake, development, and reproduction, which will ultimately affect the processes of aging and disease. Methods and Algorithms: The circadian rhythm gene network was reconstructed using the GeneNet system (Ananko et al., 2005). Computer model for mammalian circadian oscillator was implemented in MATLAB (Mathworks) as a system of 187 ordinary dif- ferential equations. Results and conclusion: We have modified and extended the most detailed circadian clock mathematical model, developed by Kim and Forger in 2012. In particular, the sub- system comprising genes / proteins NAMPT and SIRT1, as well as NAD + and NAM was added into the model. The clock gene expression data, kinetic constants and charac- teristics of the dynamics of the mammalian circadian processes for the wild type geno- type and different mutations in the clock genes were collected and used to verify the extended mathematical model. A numerical study have demonstrated that the dynamic characteristics of the model, including the period, the amplitude and phase changes of concentrations agrees well with the experimentally observed values. Acknowledgements: The work was supported by the RSF (the project № 14-24-00123). References 1. Ananko EA, Podkolodnyy NL, Stepanenko IL, Podkolodnaya OA, et al. GeneNet in 2005 // Nucleic Acids Res.,2005, vol. 33, (Database issue), pp. D425-D427. 241 THE TENTH INTERNATIONAL CONFERENCE ON BIOINFORMATICS OF GENOME REGULATION AND STRUCTURE\SYSTEMS BIOLOGY COMPUTER ANALYSIS OF BIOLOGICAL NETWORKS OF MAMMALIAN CIRCADIAN OSCILLATOR N.L. Podkolodnyy 1, 2, 3 *, N.N. Tverdokhleb 1, 3 , E.O. Sambilova 3 , S.A. Lobynya 3 , Z.D. Yakubova 3 , O.A. Podkolodnaya 1 1 Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia 2 Institute of Computational Mathematics and Mathematical Geophysics SB RAS, Novosibirsk 3 Novosibirsk State University, Novosibirsk * Corresponding author: opodkol@bionet.nsc.ru, nata@bionet.nsc.ru, pnl@bionet.nsc.ru Key words: computer network analysis, gene network, interatomic network, mammalian circadian oscillator The methods of network analysis and searching patterns of structural organization of biological networks including gene networks, interactomics networks, gene co-expres- sion networks, the diseases networks, etc. currently used for solving practical problems of bioinformatics and systems computational biology. The paper presents the methods for analysis of biological networks, including methods for analysis the local and global topological properties of networks, methods for identifying the subsystems on the net- work, the methods for comparing of network structures, etc., and the results of analy- sis of gene network applied to research mammalian circadian oscillator. A method for constructing structural models of biological networks (null model) as random graphs with structural patterns similar to the patterns found in the analyzed biological network are developed. Null structural models of biological networks are important for building statistical hypotheses for solving various types of applications is proposed. The original method for description of the integrated structural characteristic of the biological net- work was proposed. The integrated structural characteristic of the network corresponds to a principal component, built on the basis of the structural characteristics of local units - graphlets frequencies (small related isomorphic induced subgraphs), which include the vertex. On this basis, we developed a method of comparing the network and a statistical criterion for testing the hypothesis under consideration the network of its structural mod- el in the form of random graphs. The circadian rhythm gene network was reconstructed using the GeneNet system (Ananko, 2005). A network of protein-protein interactions (PPI) in the liver at different times of day was reconstructed using experimental data on protein-protein interactions, gene/protein expression data in liver tissue. A PPI network in the liver at different times of day and an expanded version of the gene network of the mammalian circadian oscillator have been reconstructed. A computer analysis of the gene regulatory network of the circadian oscillator and biological interpretation of the identified structural features, including central peaks gene network (hubs), structural pat- terns of regulation and non-random structural motifs, strongly connected components, regulatory circuits and structural-functional units (clusters) were done. As a result, we identify the central component of the circadian oscillator, which includes basic regula- tory circuits passing through the key element of the circadian clock---the protein Clock/ Bmal1. The reconstructed structural model, which includes both the central component and functional subsystems interacting with it, became the basis for building an extended mathematical model of the dynamics of the gene network regulating the circadian oscil- lator. The work was supported by the RSF (the project № 14-24-00123). 242 THE TENTH INTERNATIONAL CONFERENCE ON BIOINFORMATICS OF GENOME REGULATION AND STRUCTURE\SYSTEMS BIOLOGY QUANTITATIVE CONTRIBUTION OF IL2RΓ TO THE DYNAMIC FORMATION OF IL2-IL2R COMPLEXES L.F. Ponce*, K.García-Martínez, K. León Center of Molecular Immunology, System Biology Department, Habana, Cuba * Corresponding author:luisf@cim.sld.cu Download 3.91 Kb. Do'stlaringiz bilan baham: |
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