GWAS is an analysis of the biochemical and fatty acid composition of the milk of cows of red Belarusian cattle
https://doi.org/10.52419/issn2072-2419.2025.4.441
Abstract
A GWAS analysis was conducted to identify single-nucleotide polymorphism markers determining improved milk quality indicators. The final sample consisted of 454 genotypes of individuals: 129 Red Belarusian cattle, 325 Red Gorbatov breed. SNP genotyping was performed using the BovineSNP50 v3.0 biochip (Illumina). The genotype read efficiency averaged 0.979 (call rate). A search for candidate genes was performed in the NCBI database for the Bos_taurus_UMD_3.1.1 genome assembly. The CattleQTLdb database was used to search for QTL. The Bonferroni correction was used to adjust the resulting P value. Milk acidity is within the physiological norm, indicating the stability of protein and lipid metabolism. The freezing point corresponds to standard indicators of high-quality milk. Ketone body levels (acetone 0.08 mmol/L, beta-hydroxybutyrate 0.04 mmol/L) are low, indicating the absence of ketosis issues in the herd. Urea levels (23.29 mg/100 ml) are within the normal range, indicating a balanced protein diet for the animals. High levels of palmitic acid (1.03 g/100 g) are observed as the main component of milk fat, and among the acids, a significant proportion are long-chain (1.83 g/100 g) and mediumchain (1.69 g/100 g) fatty acids. However, the content of polyunsaturated acids (0.13 g/100 g) is low. A genome-wide analysis of milk component composition in Belarusian Red cattle revealed the most significant associations of polymorphisms in 17 genes: CTNND2, SEMA5A, POU6F2, MYO5A, FAM19A1, TNS3, PPP1R16A, CTNNA2, RCAN2, SYN3, UMAD1, PKHD1, BMP2K, KCTD8, CPNE5, OSBPL3, and EBF1. Moreover, the quantitative trait gene loci CTNND2, SEMA5A, FAM19A1, MYO5A, and POU6F2 are associated with several phenotypic traits. It was established that chromosomes 4, 5, 7, 11, 20, and 22 harbor genes associated with variability in a number of fatty acids, trace metabolites, casein, and trans fatty acid isomers for both Belarusian Red cattle and the Red Gorbatov breed of cows. Genes and QTLs characteristic only of Red Gorbatov cattle were identified on chromosomes 1, 2, 3, 9, 12, 13, 15, 17, 18, 24, 25, and 27-29. Significant polymorphisms were identified on chromosomes 6, 10, 14, and 23, determining variability in milk composition only for Belarusian Red cattle, which can be used for further breeding work.
Keywords
About the Authors
I. S. NedashkovskyRussian Federation
candidate of biology, senior scientific researcher, Head of the National Catalog Department of the National Center for Genetic Resources of Farm Animals
A. A. Sermyagin
Russian Federation
candidate of agricultural sciences, director All-Russian research institute of genetics and breeding of farm animals
M. E. Mikhailova
Belarus
candidate of biology, Head of Laboratory of animal genetics
N. I. Pesotsky
Belarus
candidate of agricultural sciences, Head of Laboratory of Dairy cattle breeding and selection laboratory
R. I. Sheiko
Belarus
doctor of agricultural sciences, professor, сorresponding member of the national academy of sciences of Belorus , major scientific researcher
I. P. Sheiko
Belarus
doctor of agricultural sciences, professor, academican of the national academy of sciences of Belorus, Honored Scientist, First Deputy Director General for Research, Scientific and Practical Center for Animal Husbandry of the National Academy of Sciences of Belarus
References
1. Gaiko, A.A. Red Belarusian cattle / A.A. Gaiko, S.I. Tuzov, M.P. Grin. - Minsk: Urajai, 1968:142 (In Russ.)
2. Tuzov, S.I. Red Belarusian cattle / S.I. Tuzov [et al.]. – Minsk: State Publishing House of the BSSR, 1961:50 (In Russ.)
3. Ernst, L. K. Red Belarusian cattle / [L. K. Ernst et al.] // Genetic resources of agricultural animals in Russia and adjacent countries - St. Petersburg: All-Russian Research Institute of Genetics and Breeding of Agricultural Animals, 1994:469 (In Russ.)
4. Pavlova, T. V. Evaluation of the genetic potential of milk productivity and the degree of its implementation in cows of the red-andwhite breeds imported to the Republic of Belarus / T. V. Pavlova [et al.] // Actual problems of intensive development of animal husbandry: collection of scientific papers. Belarusian State Agricultural Academy. - Gorki: BSAA, 2018:21(1):66-71. (In Russ.)
5. Felius, M. On the Breeds of Cattle - Historic and Current Classifications / M. Felius, P.A. Koolmees, B. Theunissen, European Cattle Genetic Diversity Consortium & J.A. Lenstra // Diversity. 2011:3(4):660-692. – DOI 10.3390/d3040660. URL: https://www.mdpi.com/1424-2818/3/4/660
6. Ernst, L.K., Genetic resources of farm animals in Russia and neighboring countries / L.K. Ernst, N.G. Dmitriev, I.A. Paronyan. – St. Petersburg: All-Russian research institute of animal genetics and breeding, 1994:469
7. Zinovieva, N.A. Genome-wide SNP analysis clearly distinguished the Belarusian Red cattle from other European cattle breeds / N.A. Zinovieva, I.P. Sheiko, A.V. Dotsev, R.I. Sheiko, M.E. Mikhailova, A.A. Sermyagin, A.S. Abdelmanova, V.R. Kharzinova, H. Reyer, K. Wimmers, J. Sölkner, N.V. Pleshanov, G. Brem // Animal Genetics. 2021:52(5):720-724. – DOI: 10.1111/age.13102 URL: https://pubmed.ncbi.nlm.nih.gov/34131930/
8. Li, M.-H. The genetic structure of cattle populations (Bos taurus) in northern Eurasia and the neighbouring Near Eastern regions: implications for breeding strategies and conservation. / M.-H. Li, I. Tapio, J. Vilkki, Z. Ivanova, T. Kiselyova, N. Marzanov, M. Cinkulov, S. Stojanović, I. Ammosov, R. Popov, J. Kantanen // Molecular Ecology. 2007:16:3839–53. – DOI: 10.1111/j.1365-294X.2007.03437.x URL: https://pubmed.ncbi.nlm.nih.gov/17850550/
9. Kantanen, J. Maternal and paternal genealogy of Eurasian taurine cattle (Bos taurus) / J. Kantanen, C.J. Edwards, D.G. Bradley, H. Viinalass, S. Thessler, Z. Ivanova, T. Kiselyova, M. Cinkulov, R. Popov, S. Stojanovic I.Ammosov, J. Vilkki // Heredity. 2009:103:404-15. – DOI: 10.1038/hdy.2009.68. URL: https://pubmed.ncbi.nlm.nih.gov/19603063/
10. Tiplady M. Kathryn Comparison of the genetic characteristics of directly measured and Fourier-transform mid-infraredpredicted bovine milk fatty acids and proteins / Kathryn M. Tiplady, Thomas J. Lopdell, Richard G. Sherlock, Thomas J.J. Johnson, Richard J. Spelman, Bevin L. Harris, Stephen R. Davis, Mathew D. Littlejohn, Dorian J. Garrick // Journal of Dairy Science. – 2022. – Vol 105(12). – P. 9763-9791. – DOI: doi.org/10.3168/jds.2022-22089 URL: https://www.sciencedirect.com/science/article/pii/S0022030222006142
11. Lewerentz Frida Re-sequencing of the casein genes in Swedish Red cattle giving milk with diverse protein profiles and extreme rennet coagulation properties / Frida Lewerentz, Tytti K. Vanhala, Lene Buhelt Johansen, Marie Paulsson, Maria Glantz, Dirk-Jan de Koning // JDS Communications. – 2024. – Vol. 5(4). – P. 299-304. – DOI: doi.org/10.3168/jdsc.2023-0412 URL: https://www.sciencedirect.com/science/article/pii/S2666910224000267
12. Benedet A. The use of mid-infrared spectra to map genes affecting milk composition / A. Benedet, P.N. Ho, R. Xiang, S. Bolormaa , M. De Marchi , M.E. Goddard, J.E. Pryce // Journal of Dairy Science. – 2019. – Vol.102(8). – P. 7189-7203. – DOI: doi.org/10.3168/jds.2018-15890 URL: https://www.sciencedirect.com/science/article/pii/S0022030219304850
13. Koncagül S. Genome-wide association study in the Holstein cattle population highlights candidate variants for milk production traits / S. Koncagül , A.Ö. Şen, M. Yıldırır, H. Koyun, E. Ünay, İ. Karakoyunlu, A. Kasakolu // Animal. – 2025. – Vol.19(12). – P. 101694. – DOI: doi.org/10.1016/j.animal.2025.101694 URL: https://www.sciencedirect.com/science/article/pii/S1751731125002770
14. Tepel, A. Chemistry and physics of milk / A. Tepel. - St. Petersburg, 2012:571(In Russ.)
15. Ostroumova, T.A. Influence of breed of cattle on structure of milk and manufacture of cheese / T.A. Ostroumova, I.V. Ivanov // Food Processing: Techniques and Technology. 2009:3:71–74. (In Russ.)
16. Chang, C. C. Second-generation PLINK: Rising to the challenge of larger and richer datasets / С.С. Chang, С.С. Chow, L. Tellier et al. // GigaScience. 2015:4(7). URL: https://pubmed.ncbi.nlm.nih.gov/25722852/
17. Hu, Z.-L. Bringing the Animal QTLdb and CorrDB into the future: meeting new challenges and providing updated services. / Z.-L. Hu, C.A. Park, J.M. Reecy // Nucleic Acids Research. 2022:50:D956–D961. – DOI 10.1093/nar/gkab1116 URL: https://pubmed.ncbi.nlm.nih.gov/34850103/
18. Banerjee, S. Bayesian multiple logistic regression for case-control GWAS / S. Banerjee, L. Zeng, H. Schunkert [et al.] // PLoS Genet. 2018:14(12). — DOI: 10.1371/journal.pgen.1007856. URL: https://pubmed.ncbi.nlm.nih.gov/30596640/
19. Naryshkina, E.N. Genome-wide analysis associations for fatty acids composition in cow's milk of red gorbatov breed / E.N. Naryshkina, A.A. Sermyagin, I.S. Nedashkovsky, I.A. Lashneva, M.E. Mikhailova, D.V. Todua, N.A. Zinovieva // Journal of Dairy and Beef Cattle Farming. 2023:6:3-9. – DOI 10.33943/MMS.2023.44.94.001. URL: https://elibrary.ru/item.asp?id=55928259 (In Russ.)
Review
For citations:
Nedashkovsky I.S., Sermyagin A.A., Mikhailova M.E., Pesotsky N.I., Sheiko R.I., Sheiko I.P. GWAS is an analysis of the biochemical and fatty acid composition of the milk of cows of red Belarusian cattle. International Journal of Veterinary Medicine. 2025;(4):441-467. (In Russ.) https://doi.org/10.52419/issn2072-2419.2025.4.441
JATS XML


















