Biology of Sport
eISSN: 2083-1862
ISSN: 0860-021X
Biology of Sport
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3/2020
vol. 37
 
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abstract:
Original paper

Whole genome sequencing of elite athletes

Eugenia A. Boulygina
1
,
Oleg V. Borisov
2, 3
,
Elena V. Valeeva
4, 5
,
Ekaterina A. Semenova
2, 4
,
Elena S Kostryukova
2
,
Nikolay A. Kulemin
2
,
Andrey K. Larin
2
,
Roza M. Nabiullina
4
,
Fanis A. Mavliev
6
,
Azat M. Akhatov
7
,
Oleg N. Andryushchenko
8
,
Liliya B. Andryushchenko
9
,
Piotr Zmijewski
10
,
Edward V. Generozov
2
,
Ildus I Ahmetov
2, 5, 9, 11

1.
“Omics Technologies” OpenLab, Kazan Federal University, Kazan, Russia
2.
Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia
3.
Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Bonn, Germany
4.
Department of Biochemistry, Biotechnology and Pharmacology, Kazan Federal University, Kazan, Russia
5.
Laboratory of Molecular Genetics, Central Research Laboratory, Kazan State Medical University, Kazan, Russia
6.
Sport Technology Research Center, Volga Region State Academy of Physical Culture, Sport and Tourism, Kazan, Russia
7.
Department of Theory and Methodology of Combat Sports, Volga Region State Academy of Physical Culture, Sport and Tourism, Kazan, Russia
8.
Department of Physical Education, Financial University under the Government of the Russian Federation, Moscow, Russia
9.
Department of Physical Education, Plekhanov Russian University of Economics, Moscow, Russia
10.
Institute of Sport - National Research Institute, Warsaw, Poland
11.
Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom
Biol Sport. 2020;37(3):295–304
Online publish date: 2020/06/16
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Whole genome sequencing (WGS) has great potential to explore all possible DNA variants associated with physical performance, psychological traits and health conditions of athletes. Here we present, for the first time, annotation of genomic variants of elite athletes, based on the WGS of 20 Tatar male wrestlers. The maximum number of high-quality variants per sample was over 3.8 M for single nucleotide polymorphisms (SNPs) and about 0.64 M for indels. The maximum number of nonsense mutations was 148 single nucleotide variants (SNVs) per individual. Athletes’ genomes on average contained 18.9 nonsense SNPs in a homozygous state per sample, while non-athletes’ exomes (Tatar controls, n = 19) contained 18 nonsense SNPs. Finally, we applied genomic data for the association analysis and used reaction time (RT) as an example. Out of 1884 known genome-wide significant SNPs related to RT, we identified four SNPs (KIF27 rs10125715, APC rs518013, TMEM229A rs7783359, LRRN3 rs80054135) associated with RT in wrestlers. The cumulative number of favourable alleles (KIF27 A, APC A, TMEM229A T, LRRN3 T) was significantly correlated with RT both in wrestlers (P = 0.0003) and an independent cohort (n = 43) of physically active subjects (P = 0.029). Furthermore, we found that the frequencies of the APC A (53.3 vs 44.0%, P = 0.033) and LRRN3 T (7.5 vs 2.8%, P = 0.009) alleles were significantly higher in elite athletes (n = 107) involved in sports with RT as an essential component of performance (combat sports, table tennis and volleyball) compared to less successful (n = 176) athletes. The LRRN3 T allele was also over-represented in elite athletes (7.5%) in comparison with 189 controls (2.9%, P = 0.009). In conclusion, we present the first WGS study of athletes showing that WGS can be applied in sport and exercise science.
keywords:

Genotype, polymorphism, wrestling, reaction time, athletic performance

 
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