Monitoring of genetic polymorphism of DNA markers of dairy cattle productivity
Abstract
Background. Traditional dairy cattle improvement systems require significant resources and are not highly efficient. Selection based on DNA markers makes it possible to optimally form herds. Monitoring of genetic polymorphism of genes associated with improved qualities of dairy cattle is the basis for correction of breeding programs.
Purpose. To study the genotypic features of dairy cattle populations in the Omsk region.
Materials and methods. The object of the study is the genotypes of cows of the red steppe and black-mottled breeds. Monitoring of gene polymorphism was carried out on the basis of genetic passports of cows from 2020 to 2024. The number of genotypes of cows in the monitoring is 356 heads. Genotyping was carried out in the laboratories of KSITEST, Moscow and in the Federal State Budgetary Educational Institution "GAU Northern Trans-Urals", Tyumen. SNPs have been determined by the CSN2, LGB, and GH genes.
Results. The A1 allele, the CSN2 gene, has the highest proportion in the population, from 40% in the red steppe breed and up to 45% in the black-mottled one. The lowest frequency of occurrence in the black-and–white breed in the F allele is 0.71%. The proportion of CSN2A2A2 homozygotes in the red steppe breed is 23.33%, which is higher than in the black-mottled breed by 6.18%. The frequency of occurrence of the allele A of the LGB gene in black-and-white cows was 62.14% and 51.67% in the red steppe breed. From 2022 to 2024, the frequency of the desired allele of the CSN2 gene decreased by 0.06 – 0.07. The frequency of the desired allele of GH and LGB increased in 2024 in two populations. The genetic basis of the population has practically not changed over the period 2022-2024, which indicates the absence of breeding pressure, taking into account DNA markers.
Conclusion. Dairy cattle populations in the Omsk region are characterized by high genetic diversity in terms of genes-markers of dairy productivity, and regular monitoring of the genetic structure of breeds will optimize the breeding process.
EDN: SJLFAJ
Downloads
References
Дерюгина, А. В., Иващенко, М. Н., Метелин, В. Б. и др. (2023). Влияние технологического стресса на неспецифическую резистентность организма коров. Siberian Journal of Life Sciences and Agriculture, 15(3), 26–40. https://doi.org/10.12731/2658-6649-2023-15-3-26-40. EDN: https://elibrary.ru/RJKSHF
Дунин, И. М., Тяпугин, С. Е., Семенова, Н. В. и др. (2024). Эффективность селекции молочного скота при использовании различных методов прогноза племенной ценности. Молочное и мясное скотоводство, (2), 3–5. https://doi.org/10.33943/MMS.2024.18.25.001. EDN: https://elibrary.ru/VEEIZS
Иванова, И. П. (2024). Генетические особенности коров голштинской породы в Омской области. Вестник Омского государственного аграрного университета, (3(55)), 74–79. EDN: https://elibrary.ru/HSXABJ
Исупова, Ю. В., & Ачкасова, Е. В. (2021). Перспективы использования оценки геномной племенной ценности в селекции молочного скота в условиях Удмуртской Республики. Известия Оренбургского государственного аграрного университета, (4(90)), 307–311. EDN: https://elibrary.ru/YYBQKA
Карымсаков, Т. Н. (2021). Эффективность использования в селекции молочного скота методов индексной оценки. Вестник аграрной науки, (3(90)), 89–93. https://doi.org/10.17238/issn2587-666X.2021.3.89. EDN: https://elibrary.ru/LWHGIU
Олейник, С. А., Скрипкин, В. С., Лесняк, А. В. и др. (2023). Сравнительный анализ жирнокислотного состава молока коров красной степной породы в условиях разных природно климатических зон Северного Кавказа. Siberian Journal of Life Sciences and Agriculture, 15(4), 236–259. https://doi.org/10.12731/2658-6649-2023-15-4-236-259. EDN: https://elibrary.ru/LZRJFA
Попов, Н., Некрасов, А., & Федотова, Е. (2020). Генетическое маркирование в селекции скота. Животноводство России, (S2), 9–15. https://doi.org/10.25701/ZZR.2020.47.51.002. EDN: https://elibrary.ru/ZXFJUR
Скачкова, О. А., & Бригида, А. В. (2022). Селекция на повышение молочной продуктивности у крупного рогатого скота: значение генетических маркеров предикторов. Ветеринария и кормление, (2), 47–49. https://doi.org/10.30917/ATT-VK-1814-9588-2022-2-13. EDN: https://elibrary.ru/UKKPNR
Суров, А. И., Шумаенко, С. Н., Омаров, А. А. и др. (2023). Использование метода генотипирования для отбора животных желательного типа. Siberian Journal of Life Sciences and Agriculture, 15(4), 136–157. https://doi.org/10.12731/2658-6649-2023-15-4-136-157. EDN: https://elibrary.ru/KLDNAL
Чижова, Л. Н., Суржикова, Е. С., & Михайленко, Т. Н. (2020). Оценка генетического потенциала молодняка молочного скота по маркерным генам CSN3, GH, PIT 1, PRL. Вестник Курской государственной сельскохозяйственной академии, (6), 40–46. EDN: https://elibrary.ru/SWRWQT
Шевелева, О. М., Часовщикова, М. А., & Суханова, С. Ф. (2021). Продуктивные и некоторые биологические особенности генофондной породы скота салерс в условиях Западной Сибири. Siberian Journal of Life Sciences and Agriculture, 13(1), 156–173. https://doi.org/10.12731/2658-6649-2021-13-1-156-173. EDN: https://elibrary.ru/GERQEL
Barkema, H. W., Von Keyserlingk, M. A. G., Kastelic, J. P., Lam, T. J. G. M., Luby, C., Roy, J. P., Kastelic, & Kelton, D. F. (2015). Invited review: Changes in the dairy industry affecting dairy cattle health and welfare. Journal of Dairy Science, 98(11), 7426–7445. https://doi.org/10.3168/jds.2015-9377
Bijttebier, J., Hamerlinck, J., Moakes, S., Scollan, N., Van Meensel, J., & Lauwers, L. (2017). Low input dairy farming in Europe: exploring a context specific notion. Agricultural Systems, 156, 43–51. https://doi.org/10.1016/j.agsy.2017.05.016
Borusiewicz, A., & Mazur, K. (2017). Environmental and economic conditioning of the breeding of dairy cattle. Fresenius Environmental Bulletin, 26(10), 5824–5832.
Galloway, C., Conradie, B., Prozesky, H., & Esler, K. (2018). Opportunities to improve sustainability on commercial pasture based dairy farms by assessing environmental impact. Agricultural Systems, 166, 1–9. https://doi.org/10.1016/j.agsy.2018.07.008. EDN: https://elibrary.ru/VHGAEG
Kharzhau, A., Batyrgaliyev, Y. A., & Bogolyubova, N. V. (2023). Features of feeding dairy cows of cattle. Science and Education, (2–3(71)), 44–51. https://doi.org/10.52578/2305-9397-2023-2-3-44-51. EDN: https://elibrary.ru/XASXYG
Naumenkova, V. A., Khrabrova, L. A., & Atroshchenko, M. M. (2023). Analysis of the interconnection of stallion semen indicators with genetic markers of proteins. Siberian Journal of Life Sciences and Agriculture, 15(4), 197–209. https://doi.org/10.12731/2658-6649-2023-15-4-197-209. EDN: https://elibrary.ru/HURKBR
Rozhkova Timina, I. O. (2023). Feed allowance for Holstein cows during lactation and dry periods (Sakhalin island). Siberian Journal of Life Sciences and Agriculture, 15(4), 56–73. https://doi.org/10.12731/2658-6649-2023-15-4-56-73. EDN: https://elibrary.ru/IHVNLN
Sedykh, T. A., Kalashnikova, L. A., Dolmatova, I. Yu., et al. (2023). Developing meat productivity in bull calves of different DGAT1 genotypes. Siberian Journal of Life Sciences and Agriculture, 15(3), 155–174. https://doi.org/10.12731/2658-6649-2023-15-3-155-174. EDN: https://elibrary.ru/XIBFND
Sheveleva, O. M., & Bakharev, A. A. (2022). Meat productivity of French bred bulls due to adaptive technology in Western Siberia. Siberian Journal of Life Sciences and Agriculture, 14(4), 370–383. https://doi.org/10.12731/2658-6649-2022-14-4-370-383. EDN: https://elibrary.ru/BNQCIU
References
Deryugina, A. V., Ivashchenko, M. N., Metelin, V. B., et al. (2023). Effect of technological stress on nonspecific resistance of cows’ organisms. Siberian Journal of Life Sciences and Agriculture, 15(3), 26–40. https://doi.org/10.12731/2658-6649-2023-15-3-26-40. EDN: https://elibrary.ru/RJKSHF
Dunin, I. M., Tyapugin, S. E., Semenova, N. V., et al. (2024). Efficiency of dairy cattle selection using different methods of breeding value prediction. Milk and Meat Cattle Breeding, (2), 3–5. https://doi.org/10.33943/MMS.2024.18.25.001. EDN: https://elibrary.ru/VEEIZS
Ivanova, I. P. (2024). Genetic characteristics of Holstein cows in Omsk Oblast. Bulletin of Omsk State Agrarian University, (3(55)), 74–79. EDN: https://elibrary.ru/HSXABJ
Isupova, Yu. V., & Achkasova, E. V. (2021). Prospects for using genomic breeding value assessment in dairy cattle selection under conditions of the Udmurt Republic. Proceedings of Orenburg State Agrarian University, (4(90)), 307–311. EDN: https://elibrary.ru/YYBQKA
Karymsakov, T. N. (2021). Efficiency of using index assessment methods in dairy cattle breeding. Bulletin of Agrarian Science, (3(90)), 89–93. https://doi.org/10.17238/issn2587-666X.2021.3.89. EDN: https://elibrary.ru/LWHGIU
Oleynik, S. A., Skripkin, V. S., Lesnyak, A. V., et al. (2023). Comparative analysis of fatty acid composition of milk from Red Steppe cows under different natural and climatic zones of the North Caucasus. Siberian Journal of Life Sciences and Agriculture, 15(4), 236–259. https://doi.org/10.12731/2658-6649-2023-15-4-236-259. EDN: https://elibrary.ru/LZRJFA
Popov, N., Nekrasov, A., & Fedotova, E. (2020). Genetic marking in cattle breeding. Animal Husbandry of Russia, (S2), 9–15. https://doi.org/10.25701/ZZR.2020.47.51.002. EDN: https://elibrary.ru/ZXFJUR
Skachkova, O. A., & Brigida, A. V. (2022). Selection for increased milk productivity in cattle: significance of genetic marker predictors. Veterinary Medicine and Feeding, (2), 47–49. https://doi.org/10.30917/ATT-VK-1814-9588-2022-2-13. EDN: https://elibrary.ru/UKKPNR
Surov, A. I., Shumaenko, S. N., Omarov, A. A., et al. (2023). Use of genotyping method for selection of animals of desired type. Siberian Journal of Life Sciences and Agriculture, 15(4), 136–157. https://doi.org/10.12731/2658-6649-2023-15-4-136-157. EDN: https://elibrary.ru/KLDNAL
Chizhova, L. N., Surzhikova, E. S., & Mikhailenko, T. N. (2020). Assessment of genetic potential of young dairy cattle by marker genes CSN3, GH, PIT1, PRL. Bulletin of Kursk State Agricultural Academy, (6), 40–46. EDN: https://elibrary.ru/SWRWQT
Sheveleva, O. M., Chasovshchikova, M. A., & Sukhanova, S. F. (2021). Productive and some biological characteristics of the Salers cattle breed gene pool under conditions of Western Siberia. Siberian Journal of Life Sciences and Agriculture, 13(1), 156–173. https://doi.org/10.12731/2658-6649-2021-13-1-156-173. EDN: https://elibrary.ru/GERQEL
Barkema, H. W., Von Keyserlingk, M. A. G., Kastelic, J. P., Lam, T. J. G. M., Luby, C., Roy, J. P., Kastelic, & Kelton, D. F. (2015). Invited review: Changes in the dairy industry affecting dairy cattle health and welfare. Journal of Dairy Science, 98(11), 7426–7445. https://doi.org/10.3168/jds.2015-9377
Bijttebier, J., Hamerlinck, J., Moakes, S., Scollan, N., Van Meensel, J., & Lauwers, L. (2017). Low input dairy farming in Europe: exploring a context specific notion. Agricultural Systems, 156, 43–51. https://doi.org/10.1016/j.agsy.2017.05.016
Borusiewicz, A., & Mazur, K. (2017). Environmental and economic conditioning of the breeding of dairy cattle. Fresenius Environmental Bulletin, 26(10), 5824–5832.
Galloway, C., Conradie, B., Prozesky, H., & Esler, K. (2018). Opportunities to improve sustainability on commercial pasture based dairy farms by assessing environmental impact. Agricultural Systems, 166, 1–9. https://doi.org/10.1016/j.agsy.2018.07.008. EDN: https://elibrary.ru/VHGAEG
Kharzhau, A., Batyrgaliyev, Y. A., & Bogolyubova, N. V. (2023). Features of feeding dairy cows of cattle. Science and Education, (2–3(71)), 44–51. https://doi.org/10.52578/2305-9397-2023-2-3-44-51. EDN: https://elibrary.ru/XASXYG
Naumenkova, V. A., Khrabrova, L. A., & Atroshchenko, M. M. (2023). Analysis of the interconnection of stallion semen indicators with genetic markers of proteins. Siberian Journal of Life Sciences and Agriculture, 15(4), 197–209. https://doi.org/10.12731/2658-6649-2023-15-4-197-209. EDN: https://elibrary.ru/HURKBR
Rozhkova Timina, I. O. (2023). Feed allowance for Holstein cows during lactation and dry periods (Sakhalin island). Siberian Journal of Life Sciences and Agriculture, 15(4), 56–73. https://doi.org/10.12731/2658-6649-2023-15-4-56-73. EDN: https://elibrary.ru/IHVNLN
Sedykh, T. A., Kalashnikova, L. A., Dolmatova, I. Yu., et al. (2023). Developing meat productivity in bull calves of different DGAT1 genotypes. Siberian Journal of Life Sciences and Agriculture, 15(3), 155–174. https://doi.org/10.12731/2658-6649-2023-15-3-155-174. EDN: https://elibrary.ru/XIBFND
Sheveleva, O. M., & Bakharev, A. A. (2022). Meat productivity of French bred bulls due to adaptive technology in Western Siberia. Siberian Journal of Life Sciences and Agriculture, 14(4), 370–383. https://doi.org/10.12731/2658-6649-2022-14-4-370-383. EDN: https://elibrary.ru/BNQCIU
Copyright (c) 2025 Irina P. Ivanova, Elena N. Yurchenko, Yuliya A. Okoneshnikova

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.





















































