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Identification of genes associated with technological properties of cow milk using GWA analysis and gene ontology

https://doi.org/10.30766/2072-9081.2025.26.5.1112-1124

Abstract

In recent years, there has been a significant development of technologies in the field of genetics and breeding of cattle, which opens new opportunities for increasing productivity and quality of dairy products. The present work is devoted to the study of genetic determination of technological properties of cow milk, namely, thermostability and rennet coagulation.

The aim of the study was to perform a genome-wide association analysis (GWA) to identify positional candidate genes determining the formation of cow milk technological traits, followed by functional annotation for a thorough understanding of the mechanisms of gene action and their contribution to phenotype formation. As the result of GWA analysis there were identified 17 SNPs significantly associated with milk thermal stability located on chromosomes BTA3, BTA6, BTA8, BTA23, BTA24, BTA27, BTA28 and BTA29. There were also identified 34 SNPs associated with milk rennet coagulation localized on chromosomes BTA1, BTA2, BTA3, BTA5, BTA6, BTA9, BTA10, BTA12, BTA14, BTA15, BTA16, BTA18, BTA20, BTA23, BTA24, BTA26 and BTA27.Functional annotation revealed 144 genes grouped into 43 nodes and nine clusters. Among all nine clusters, four of them involved genes responsible for thermostability (CNOT7) and rennet milk coagulation (HHAT, NEDD9, ZNF423). Functional annotation of 11 identified candidate genes (HHAT, PDE3B, AK8, AK2, CNOT7, XRN2, NOP14, NEDD9, SMAD3, ZNF423, EBF1) using the DAVID database identified their involvement in biological processes such as protein palmitoylation, regulation of cellular activity, nucleotide biosynthesis and translation regulation. Associations between individual genes (HHAT, AK8, EBF1) and QTLs affecting milk productivity and milk quality composition were also identified. The results of the study contribute to the understanding of the genetic architecture of technological properties of milk and can be used in genomic selection to improve the quality of dairy products.

About the Authors

M. V. Levchenko
Federal Research Center for Animal Husbandry named after Academy Member L. K. Ernst
Russian Federation

Maria V Levchenko, researcher, the Department of Population Genetics and Genetic Foundations of Animal Breeding,

Dubrovitsy village, 60, Podolsk City District, Moscow Region, 142132



G. G. Karlikova
Federal Research Center for Animal Husbandry named after Academy Member L. K. Ernst
Russian Federation

Galina G Karlikova, DSc in Agricultural Science, senior researcher, the Department of Population Genetics and Genetic Foundations of Animal Breeding,

Dubrovitsy village, 60, Podolsk City District, Moscow Region, 142132



G. K. Petryakova
Federal Research Center for Animal Husbandry named after Academy Member L. K. Ernst
Russian Federation

Galina K Petryakova, Programmer, the Department of Population Genetics and Genetic Foundations of Animal Breeding,

Dubrovitsy village, 60, Podolsk City District, Moscow Region, 142132



I. A. Lashneva
Federal Research Center for Animal Husbandry named after Academy Member L. K. Ernst
Russian Federation

Irina A Lashneva, PhD in Biology, leading specialist, the Department of Population Genetics and Genetic Foundations of Animal Breeding, 

Dubrovitsy village, 60, Podolsk City District, Moscow Region, 142132



A. A. Sermyagin
All-Russian Research Institute of Genetics and Breeding of Farm Animals – Federal Research Center for Animal Husbandry named after Academy Member L. K. Ernst
Russian Federation

Alexander A Sermyagin, PhD in Agricultural Science, Director,

Moscow Shosse, 55a, Pushkin, St. Petersburg, 196601



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Review

For citations:


Levchenko M.V., Karlikova G.G., Petryakova G.K., Lashneva I.A., Sermyagin A.A. Identification of genes associated with technological properties of cow milk using GWA analysis and gene ontology. Agricultural Science Euro-North-East. 2025;26(5):1112-1124. (In Russ.) https://doi.org/10.30766/2072-9081.2025.26.5.1112-1124

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ISSN 2072-9081 (Print)
ISSN 2500-1396 (Online)