International Multiconference “Bioinformatics of Genome Regulation and Structure\Systems Biology”

Tag

GWAS

6 RESULTS
Genomics, transcriptomics, bioinformatics symposiumOn region based inference in genome wide association study

On region based inference in genome wide association study

No Comment on On region based inference in genome wide association study

Sergey V. Malov1, Alexey Antonik2, Andrey K. Shevchenko3
1St.-Petersburg State University, malovs@sm14820.spb.edu
2St.-Petersburg State University, alexey.antonik@gmail.com
3St.-Petersburg State University, andrey.k.shevchenko@gmail.com

We consider an advanced framework for genome wide association study (GWAS) based on the signal localization. Instead of looking for single genetic markers associated with the phenotype we attempt to discover regions of genetic markers, which are associated with phenotype. We focus on the localization by moving sums of negative logarithms of p-values, which is efficient for discovery of wide regions of genetic markers associated with phenotype. Particularly, we expect the method should be efficient for searching genes containing a number of genetic markers, if any reconstruction in a gene related to a phenotype. The method is implemented in GWATCH software for visualization and interpretation results of multiple statistical tests for genome associations. We discuss some features of the GWATCH software and apply them for HIV/AIDS cohort study from Botswana.

Genomics, transcriptomics, bioinformatics symposiumHigh performance pipeline for the calculation of Polygenic Risk Scores

High performance pipeline for the calculation of Polygenic Risk Scores

No Comment on High performance pipeline for the calculation of Polygenic Risk Scores

Poster (download)

[pdf-embedder url=”https://bgrssb.icgbio.ru/wp-content/uploads/2020/07/109.pdf”]
Video (download)

Arina Nostaeva1, Tatiana Shashkova2, Sodbo Sharapov3, Yakov Tsepilov4, Yurii Aulchenko5, Lennart C. Karssen6
1Laboratory of Recombination and Segregation Analysis, Institute of Cytology and Genetics, Novosibirsk, Russia, avnostaeva@gmail.com
2Laboratory of Recombination and Segregation Analysis, Institute of Cytology and Genetics, Novosibirsk, Russia, shashkova@phystech.edu
3Laboratory of Recombination and Segregation Analysis, Institute of Cytology and Genetics, Novosibirsk, Russia, sharapovsodbo@gmail.com
4Laboratory of Recombination and Segregation Analysis, Institute of Cytology and Genetics, Novosibirsk, Russia, drosophila.simulans@gmail.com
5Laboratory of Recombination and Segregation Analysis, Institute of Cytology and Genetics, Novosibirsk, Russia, yurii.aulchenko@gmail.com
6PolyKnomics, ’s-Hertogenbosch, The Netherlands, l.c.karssen@polyknomics.com

A polygenic risk score (PRS) is a value that reflects a person’s predisposition to a disease or any other trait which can (partly) be explained by genetic inheritance. PRSs are often used in reports provided by genetic testing companies like 23andMe, Genotek, etc. Another way of using PRSs is to look at the distribution of PRS values for a group of people and compare them, for example, in a case-control study to find case-dependent traits. PRS models are usually based on summary statistics data from genome-wide association studies (GWAS) and take into account the linkage disequilibrium (LD) structure. We have created a pipeline for high performance PRS calculations across many traits present in the GWAS-MAP platform. The pipeline only requires individual-level data and provides the ability to select a list of traits. This pipeline will be helpful for scientific groups, working with large amounts of individual genotype data, as well as for individuals with their own personal genotype data.

Genomics, transcriptomics, bioinformatics symposiumGenome-wide association study of Parkinson’s disease using MAX3 test

Genome-wide association study of Parkinson’s disease using MAX3 test

No Comment on Genome-wide association study of Parkinson’s disease using MAX3 test

Georgii Ozhegov1, Dmitry Poverin2, Sergey Medvedev3, Suren Zakian4, Yuri Vyatkin5, Sergey Postovalov6
1Kazan Federal University, Kazan, Russia; Novel Software Systems, Ltd., Novosibirsk, Russia, georgii_provisor@mail.ru
2Novosibirsk State Technical University, Novosibirsk, Russia, foxlandg@gmail.com
3Federal Research Center Institute of Cytology and Genetics, Novosibirsk, Russia, medvedev@bionet.nsc.ru
4Federal Research Center Institute of Cytology and Genetics, Novosibirsk, Russia, zakian@bionet.nsc.ru
5Novosibirsk State University, Novosibirsk, Russia; Novel Software Systems, Ltd., Novosibirsk, Russia, yuri@nprog.ru
6Novosibirsk State Technical University, Novosibirsk, Russia; Novosibirsk State University, Novosibirsk, Russia, postovalovsn@gmail.com

Whole exomes for a set of patients with Parkinson’s disease (PD) were sequenced to conduct a genome-wide association study (GWAS) using MAX3 test to find novel genomic variants associated with the disease. As a result, several new variants were identified.

Genomics,  bioinformatics  and evolution symposiumMethylation and expression profiles in Apoe vicinity point to specific neighboring interaction of Apoe and TOMM40 genes: implication for The Alzheimer disease.

Methylation and expression profiles in Apoe vicinity point to specific neighboring interaction of Apoe and TOMM40 genes: implication for The Alzheimer disease.

No Comment on Methylation and expression profiles in Apoe vicinity point to specific neighboring interaction of Apoe and TOMM40 genes: implication for The Alzheimer disease.

Vladimir Babenko1
1Institute of Cytology and Genetics SB_RAS, bob@bionet.nsc.ru

We assessed the dynamics of 8 genes including TOMM40, Apoe and other adjacent ones for overall chromatin marks landscape, including methylation profiles across ENCODE brain cell lines, and histone and ctcf marks. We revealed the region manifests Hi-C topology dynamics in a cell-specific manner. Additionally, based on methylation and histone marks profiles we underscore competitive manner of genes expression implying disrupted locus wide genes expression balance in Alzheimer patients due to Apoe extended locus methylation profile alteration.

Genomics, transcriptomics, bioinformatics symposiumA new method for combining of genetically correlated traits by maximizing of their shared heritability

A new method for combining of genetically correlated traits by maximizing of their shared heritability

No Comment on A new method for combining of genetically correlated traits by maximizing of their shared heritability

Video (download)

Gulnara R. Svishcheva1, Evgeny S. Tiys2, Sofya G. Feoktistova3, Elizaveta E. Elgaeva4, Sodbo Sharapov5, Yakov A. Tsepilov6
1Institute of cytology and genetics, gulsvi@mail.ru
2Institute of cytology and genetics, tiys@bionet.nsc.ru
3Institute of cytology and genetics, sayfutdinovas@gmail.com
4Institute of cytology and genetics, elizabeth.elgaeva@gmail.com
5Institute of cytology and genetics, sharapovsodbo@gmail.com
6Novosibirsk State University, drosophila.simulans@gmail.com

Genetic correlations between phenotypic traits are widely observed phenomena. Many groups of traits have a significant level of shared genetic background. In this work, we suggested a new method for extraction of shared genetic component for genetically correlated phenotypic traits. We applied the method to GWAS results for anthropometric traits.

Genomics, transcriptomics, bioinformatics symposiumGenome-wide Association Study Reveals Novel Genetic Variants Associated with HIV-1C Infection in Botswana Population

Genome-wide Association Study Reveals Novel Genetic Variants Associated with HIV-1C Infection in Botswana Population

No Comment on Genome-wide Association Study Reveals Novel Genetic Variants Associated with HIV-1C Infection in Botswana Population

Andrey Shevchenko1, Sergey V. Malov2, Alexey Antonik3
1Theodosius Dobzhansky Center for Genome Bioinformatics St.-Petersburg State University St-Petersburg, Russia, andrey.k.shevchenko@gmail.com
2Theodosius Dobzhansky Center for Genome Bioinformatics St.-Petersburg State University St-Petersburg, Russia, malovs@sm14820.spb.edu
3Theodosius Dobzhansky Center for Genome Bioinformatics St.-Petersburg State University St-Petersburg, Russia, alexey.antonik@gmail.com

Genome wide association studies (GWAS) allow to identify common variants associated with the trait in question. In order to efficiently search for the genetic associations we have previously developed Genome-Wide AssociationВ Tracks Chromosome Highway (GWATCH). The broad goal of the Botswana GWAS project is to identify genetic determinants of susceptibility and resistance to infection by HIV-1 subtype C among people severely affected by HIV/AIDS in Botswana. By conducting GWAS analysis on HIV1C case/control dataset consisting of 762 Tswana people (combined from two partly overlapping datasets of 809 microarray and 362 WGS samples), we found several gene regions slightly below significance level.