Identification of combinations of genomic mutations using genome-wide association studies by example of Mycobacterium tuberculosis

Authors

  • Chen Yu-Xiang United Institute of Informatics Problems, National Academy of Sciences of Belarus, 6 Surganava Street, Minsk 220012, Belarus
  • Alexander M. Andrianov Institute of Bioorganic Chemistry, National Academy of Sciences of Belarus, 5 Akademika Kuprevicha Street, 2 building, Minsk 220084, Belarus
  • Alexander V. Tuzikov United Institute of Informatics Problems, National Academy of Sciences of Belarus, 6 Surganava Street, Minsk 220012, Belarus

Keywords:

genome-wide association studies, GWAS, single nucleotide polymorphism interaction, drug-resistant tuberculosis
Supporting Agencies
This work was supported by the drug-resistant tuberculosis consortium (https://tbportals.niaid. nih.gov), the International Science and Technology Centre (project PR150), as well as the China Scholarship Council (https://www.csc.edu.cn/).

Abstract

Genome-wide association studies play a key role in identifying relationships between genomes and phenotypes. Many studies in this field are devoted to the investigations of genetic variations and their interactions in genomes. However, despite significant progress achieved in this direction, the problem under consideration is still highly relevant and requires the development of effective methods and algorithms for solving it. In this paper, four new algorithms based on the study of single nucleotide polymorphism interactions in the two modes, additive and multiplicative, are proposed to find combinations of single nucleotide polymorphisms associated with phenotypes. In the first stage, the algorithms use exhaustive search of single nucleotide polymorphism pairs to predict their association with phenotype, and in the second stage, greedy procedures are applied to find combinations of up to five single nucleotide polymorphisms with the best association values. The developed computational approach is tested on the dataset containing 3178 Mycobacterium tuberculosis genomes to identify single nucleotide polymorphism combinations and predict resistance of Mycobacte-rium tuberculosis strains to 20 drugs. The results obtained are compared with those of the modern prediction software systems Mykrobe and TB-Profiler. For the 5 first-line drugs and the 1 second-line drug (Ofloxacin), Mykrobe and TB-Profiler systems slightly exceed the prediction accuracy of the proposed algorithms, but for the other 14 second-line drugs, they are inferior to them.

Author Biographies

  • Chen Yu-Xiang, United Institute of Informatics Problems, National Academy of Sciences of Belarus, 6 Surganava Street, Minsk 220012, Belarus

    junior researcher at the laboratory of mathematical cybernetics

  • Alexander M. Andrianov, Institute of Bioorganic Chemistry, National Academy of Sciences of Belarus, 5 Akademika Kuprevicha Street, 2 building, Minsk 220084, Belarus

    doctor of science (chemistry), full professor; chief researcher at the laboratory of protein engineering

  • Alexander V. Tuzikov, United Institute of Informatics Problems, National Academy of Sciences of Belarus, 6 Surganava Street, Minsk 220012, Belarus

    doctor of science (physics and mathematics), corresponding member of the National Academy of Sciences of Belarus, full professor; head of the laboratory of mathematical cybernetics

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Published

2024-12-02

Issue

No. 3 (2024): Journal of the Belarusian State University. Mathematics and Informatics

Section

Discrete Mathematics and Mathematical Cybernetics

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How to Cite

Identification of combinations of genomic mutations using genome-wide association studies by example of Mycobacterium tuberculosis. (2024). Journal of the Belarusian State University. Mathematics and Informatics, 3, 73-89. https://journals.bsu.by/index.php/mathematics/article/view/6617