vetpressАграрная наукаAgrarian science0869-81552686-701XРедакция журнала "Аграрная наука"10.32634/0869-8155-2024-383-6-68-76vetpress-3112Research ArticleЗООТЕХНИЯZOOTECHNICSИдентификация генов, ассоциированных с цветовыми характеристиками мясной и жировой ткани скота абердин-ангусской породыIdentification of genes associated with color characteristics of meat and fat tissue of aberdeen-angus cattlehttps://orcid.org/0000-0001-7533-4281БелоусА. А.BelousA. A.

Анна Александровна Белоус, кандидат биологических наук, доцент

пос. Дубровицы, 60, г. о. Подольск, Московская обл., 142132

 

Anna Alexandrovna Belous, Candidate of Biological Sciences, Docent

60 Dubrovitsy, Podolsk Municipal District, Moscow Region, 142132

belousa663@gmail.comhttps://orcid.org/0000-0002-1799-6014СермягинА. А.SermyaginA. A.

Александр Александрович Сермягин, кандидат сельскохозяйственных наук, заведующий отделомпопуляционной генетики и генетических основ разведения животных

пос. Дубровицы, 60, г. о. Подольск, Московская обл., 142132

Alexander Alexandrovich Sermyagin, Candidate of Agricultural Sciences, Head of the Department of Population Genetics and Genetic Basis of Animal Breeding

60 Dubrovitsy, Podolsk Municipal District, Moscow Region, 142132

alex_sermyagin85@mail.ruЕлаткинН. П.ElatkinN. P.

Николай Павлович Елаткин, кандидат биологических наук, генеральный директор

ул. Нобеля, 5, эт. 2, пом. 7, раб. 3, территория инновационного центра Сколково, Москва, 121205

Nikolay Pavlovich Elatkin, Candidate of Biological Sciences, General Manager

5 Nobel Street, 2 floor, 7 room, 3 room, territory of the Skolkovo Innovation Center, Moscow, 121205

n.elatkin@agrohold.ruhttps://orcid.org/0000-0003-4017-6863ЗиновьеваН. А.ZinovievaN. A.

Наталия Анатольевна Зиновьева, доктор биологических наук, академик Российской академии наук, профессор, директор

пос. Дубровицы, 60, г. о. Подольск, Московская обл., 142132

Nataliya Anatolyevna Zinovieva, Doctor of Biological Sciences, Russian Academy of Sciences Academy Member, Professor, Director

60 Dubrovitsy, Podolsk Municipal District, Moscow Region, 142132

priemnaya-vij@mail.ruФедеральный исследовательский центр животноводства – ВИЖ им. академика Л.К. ЭрнстаРоссияL.K. Ernst Federal Research Center for Animal HusbandryRussian FederationООО «Мираторг-Генетика»РоссияLLC «Miratorg-Genetika»Russian Federation202414062024066876Copyright © Белоус А.А., Сермягин А.А., Елаткин Н.П., Зиновьева Н.А., 20242024Белоус А.А., Сермягин А.А., Елаткин Н.П., Зиновьева Н.А.Belous A.A., Sermyagin A.A., Elatkin N.P., Zinovieva N.A.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.vetpress.ru/jour/article/view/3112

В настоящее время полногеномные ассоциативные исследования и выявление генов-кандидатов по хозяйственно полезным признакам у сельскохозяйственных животных являются актуальными, научно обоснованными и практико-ориентированными, а также выполняют одну из задач Стратегии научно-технического развития Российской Федерации. В данной статье приведены результаты GWAS по цветовым спектральным значениям мяса и жировой ткани крупного рогатого скота абердин-ангусской породы, известной своими мясными характеристиками высокого сорта. Генотипирование животных осуществлялось на чипах высокой плотности BovineHD Genotyping BeadChip, содержащих ≈53 тыс. SNP. После контроля качества их осталось 39 928. По результатам анализа и структурной аннотации были выявлены 25 и 26 генов-кандидатов по цвету мяса и жира соответственно. По функциональной аннотации гены были разделены на 6 групп: функции нервной системы, развитие органов, сосудов, суставов, метаболические процессы и биосинтез, клеточные процессы, мышцы, ткани и кости, репродуктивные свойства и эмбриональное развитие. Полученные гены проверили через базу данных Animal QTL, в результате которого подтверждение нашли 13 генов, из них внутри 3 локализованы SNP, в связи с чем гены LRP2, SCIN и ANTXR1 имеют преимущества для дальнейшего их применения в молекулярной диагностике крупного рогатого скота не только мясного, но и молочного направления продуктивности.

Currently, full genome association studies and identification of candidate genes for economically useful traits in farm animals are topical, scientifically sound and practice-oriented, and fulfill one of the objectives of the Strategy for Scientific and Technical Development of the Russian Federation. This article presents the results of GWAS on color spectral values of meat and fat tissue of Aberdeen-Angus cattle, known for its meat characteristics of high grade. The animals were genotyped on high-density BovineHD Genotyping BeadChip chips containing ≈53,000 SNPs. After quality control, 39,928 remained. By analysis and structural annotation, 25 and 26 candidate genes for meat and fat color were identified, respectively. According to functional annotation, the genes were categorized into 6 groups: nervous system functions, organ development, vascular, joints, metabolic processes and biosynthesis, cellular processes, muscle, tissue and bone, reproduction and embryonic development. The obtained genes were checked through the Animal QTL database, as a result of which 13 genes were confirmed, of which 3 were localized SNPs, in connection with which the LRP2, SCIN and ANTXR1 genes have advantages for their further application in the molecular diagnostics of cattle not only meat, but also dairy productivity.

GWASцветовые характеристики мяса и жираструктурная аннотация геновфункциональная аннотация геновQTL-базакрупный рогатый скот мясного направления продуктивностиGWASmeat and fat color characteristicsstructural annotation of genesfunctional annotation of genesQTL basebeef cattleИсследования проведены при поддержке Министерства науки и высшего образования Российской Федерации (регистрационный № FGGN-2022-0011 темы государственного задания).The research was carried out with the support of the Ministry of Science and Higher Education of the Russian Federation (registration № FGGN-2022-0011 topics of the state assignment).ReferencesRamanathan R., Suman S.P., Faustman C. Biomolecular Interactions Governing Fresh Meat Color in Post-mortem Skeletal Muscle: A Review. Journal of Agricultural and Food Chemistry. 2020; 68(46): 12779–12787. https://doi.org/10.1021/acs.jafc.9b08098Ramanathan R., Suman S.P., Faustman C. Biomolecular Interactions Governing Fresh Meat Color in Post-mortem Skeletal Muscle: A Review. Journal of Agricultural and Food Chemistry. 2020; 68(46): 12779–12787. https://doi.org/10.1021/acs.jafc.9b08098Ramanathan R. et al. Economic Loss, Amount of Beef Discarded, Natural Resources Wastage, and Environmental Impact Due to Beef Discoloration. Meat and Muscle Biology. 2022; 6(1): 13218. https://doi.org/10.22175/mmb.13218Ramanathan R. et al. Economic Loss, Amount of Beef Discarded, Natural Resources Wastage, and Environmental Impact Due to Beef Discoloration. Meat and Muscle Biology. 2022; 6(1): 13218. https://doi.org/10.22175/mmb.13218Hernández B., Sáenz C., Diñeiro J.M., Alberdi Odriozola C. CIELAB color paths during meat shelf life. Meat Science. 2019; 157: 107889. https://doi.org/10.1016/j.meatsci.2019.107889Hernández B., Sáenz C., Diñeiro J.M., Alberdi Odriozola C. CIELAB color paths during meat shelf life. Meat Science. 2019; 157: 107889. https://doi.org/10.1016/j.meatsci.2019.107889Girolami A., Napolitano F., Faraone D., Braghieri A. Measurement of meat color using a computer vision system. Meat Science. 2013; 93(1): 111–118. https://doi.org/10.1016/j.meatsci.2012.08.010Girolami A., Napolitano F., Faraone D., Braghieri A. Measurement of meat color using a computer vision system. Meat Science. 2013; 93(1): 111–118. https://doi.org/10.1016/j.meatsci.2012.08.010Tomasevic I. et al. Evaluation of poultry meat colour using computer vision system and colourimeter: Is there a difference? British Food Journal. 2019; 121(5): 1078–1087. https://doi.org/10.1108/BFJ-06-2018-0376Tomasevic I. et al. Evaluation of poultry meat colour using computer vision system and colourimeter: Is there a difference? British Food Journal. 2019; 121(5): 1078–1087. https://doi.org/10.1108/BFJ-06-2018-0376Trinderup C.H., Kim Y.H.B. Fresh meat color evaluation using a structured light imaging system. Food Research International. 2015; 71: 100–107. https://doi.org/10.1016/j.foodres.2015.02.013Trinderup C.H., Kim Y.H.B. Fresh meat color evaluation using a structured light imaging system. Food Research International. 2015; 71: 100–107. https://doi.org/10.1016/j.foodres.2015.02.013Gagaoua M., Picard B., Monteils V. Associations among animal, carcass, muscle characteristics, and fresh meat color traits in Charolais cattle. Meat Science. 2018; 140: 145–156. https://doi.org/10.1016/j.meatsci.2018.03.004Gagaoua M., Picard B., Monteils V. Associations among animal, carcass, muscle characteristics, and fresh meat color traits in Charolais cattle. Meat Science. 2018; 140: 145–156. https://doi.org/10.1016/j.meatsci.2018.03.004Белоус А.А., Сермягин А.А., Зиновьева Н.А. Цветовая характеристика мяса товарных гибридов: первые результаты. Труды Кубанского государственного аграрного университета. 2020; 86: 140–145. https://doi.org/10.21515/1999-1703-86-140-145Belous A.A., Sermyagin A.A., Zinovieva N.A. Color characteristics of commercial hybrids’ meat: the first results. Proceedings of the Kuban State Agrarian University. 2020; 86: 140–145 (in Russian). https://doi.org/10.21515/1999-1703-86-140-145Отраднов П.И., Бардуков Н.В., Никипелов В.И., Никипелова А.К., Белоус А.А., Зиновьева Н.В. Применение морфометрических признаков для прогнозирования цветовых характеристик мяса сибирского осетра ленской популяции, разводимого в условиях установки замкнутого водоснабжения. Международный научно-исследовательский журнал. 2023; 11. https://doi.org/10.23670/IRJ.2023.137.63Otradnov P.I., Bardukov N.V., Nikipelov V.I., Nikipelova A.K., Belous A.A., Zinovieva N.A. Application of morphometric traits to predict colour characteristics of meat of Siberian sturgeon of the Lena population, bred under conditions of a closed water supply system. International Research Journal. 2023; 11 (in Russian). https://doi.org/10.23670/IRJ.2023.137.63Лисицын А.Б., Козырев И.В. Исследование цветовых характеристик мышечной и жировой ткани и мраморности говядины. Теория и практика переработки мяса. 2016; 1(4): 51–56. https://doi.org/10.21323/2414-438X-2016-1-4-51-56Lisitsyn A.B., Kozyrev I.V. Researching of meat and fat colour and marbling in beef. Theory and practice of meat processing. 2016; 1(4): 51–56. https://doi.org/10.21323/2414-438X-2016-1-4-51-56Ветох А.Н., Джагаев А.Ю., Белоус А.А., Волкова Н.А., Зиновьева Н.А. Полногеномные ассоциативные исследования качества мяса по показателям цвета грудки у кур (Gallus gallus L.). Сельскохозяйственная биология. 2023; 58(6): 1068–1078. https://doi.org/10.15389/agrobiology.2023.6.1068rusVetokh A.N., Dzhagaev A.Yu., Belous A.A., Volkova N.A., Zinovieva N.A. Genome-wide association studies of chicken (Gallus gallus L.) breast meat color characteristics. Agricultural Biology. 2023; 58(6): 1068–1078. https://doi.org/10.15389/agrobiology.2023.6.1068engСермягин А.А., Боголюбова Н.В., Белоус А.А., Петрякова Г.К., Елаткин Н.П., Зиновьева Н.А. Показатели мясной продуктивности, эффективности использования корма и химического состава мяса бычков абердин-ангусской породы. Аграрная наука. 2023; 12: 67–73. https://doi.org/10.32634/0869-8155-2023-377-12-67-73Sermyagin A.A., Bogolyubova N.V., Belous A.A., Petryakova G.K., Yelatkin N.P., Zinovieva N.A. Meat production, feed efficiency and chemical composition traits of meat for Aberdeen Angus steers bulls. Agrarian science. 2023; 12: 67–73 (in Russian). https://doi.org/10.32634/0869-8155-2023-377-12-67-73Zhou Y. et al. Genetic variation in the gene LRP2 increases relapse risk in multiple sclerosis. Journal of Neurology, Neurosurgery and Psychiatry. 2017; 88(10): 864–868. https://doi.org/10.1136/jnnp-2017-315971Zhou Y. et al. Genetic variation in the gene LRP2 increases relapse risk in multiple sclerosis. Journal of Neurology, Neurosurgery and Psychiatry. 2017; 88(10): 864–868. https://doi.org/10.1136/jnnp-2017-315971de Luis D.A., Izaola O., Primo D., de la Fuente B., Aller R. El polimorfismo rs3123554 en el gen receptor canabinoide tipo 2 (CNR2) se relaciona con el peso corporal y la resistencia a la insulina en obesos. Endocrinología, Diabetes y Nutrición. 2017; 64(8): 440–445. https://doi.org/10.1016/j.endinu.2017.06.001de Luis D.A., Izaola O., Primo D., de la Fuente B., Aller R. Polymorphism rs3123554 in the cannabinoid receptor gene type 2 (CNR2) reveals effects on body weight and insulin resistance in obese subjects. Endocrinología, Diabetes y Nutrición. 2017; 64(8): 440–445. https://doi.org/10.1016/j.endien.2017.06.002Ahluwalia M.K. Nutrigenetics and nutrigenomics — A personalized approach to nutrition. Advances in Genetics. 2021; 108: 277–340. https://doi.org/10.1016/bs.adgen.2021.08.005Ahluwalia M.K. Nutrigenetics and nutrigenomics — A personalized approach to nutrition. Advances in Genetics. 2021; 108: 277–340. https://doi.org/10.1016/bs.adgen.2021.08.005Chmurzynska A., Mlodzik M.A., Radziejewska A., Szwengiel A., Malinowska A.M., Nowacka-Woszuk J. Caloric restriction can affect one-carbon metabolism during pregnancy in the rat: A transgenerational model. Biochimie. 2018; 152: 181–187. https://doi.org/10.1016/j.biochi.2018.07.007Chmurzynska A., Mlodzik M.A., Radziejewska A., Szwengiel A., Malinowska A.M., Nowacka-Woszuk J. Caloric restriction can affect one-carbon metabolism during pregnancy in the rat: A transgenerational model. Biochimie. 2018; 152: 181–187. https://doi.org/10.1016/j.biochi.2018.07.007Aiken C.E., Ozanne S.E. Transgenerational developmental programming. Human Reproduction Update. 2014; 20(1): 63–75. https://doi.org/10.1093/humupd/dmt043Aiken C.E., Ozanne S.E. Transgenerational developmental programming. Human Reproduction Update. 2014; 20(1): 63–75. https://doi.org/10.1093/humupd/dmt043Ben-Jemaa S. et al. Genome-Wide Analysis Reveals Selection Signatures Involved in Meat Traits and Local Adaptation in Semi-Feral Maremmana Cattle. Frontiers in Genetics. 2021; 12: 675569. https://doi.org/10.3389/fgene.2021.675569Ben-Jemaa S. et al. Genome-Wide Analysis Reveals Selection Signatures Involved in Meat Traits and Local Adaptation in Semi-Feral Maremmana Cattle. Frontiers in Genetics. 2021; 12: 675569. https://doi.org/10.3389/fgene.2021.675569Lonergan E.H., Zhang W., Lonergan S.M. Biochemistry of postmortem muscle — Lessons on mechanisms of meat tenderization. Meat Science. 2010; 86(1): 184–195. https://doi.org/10.1016/j.meatsci.2010.05.004Lonergan E.H., Zhang W., Lonergan S.M. Biochemistry of postmortem muscle — Lessons on mechanisms of meat tenderization. Meat Science. 2010; 86(1): 184–195. https://doi.org/10.1016/j.meatsci.2010.05.004Chen P.R. et al. Disruption of anthrax toxin receptor 1 in pigs leads to a rare disease phenotype and protection from senecavirus A infection. Scientific Reports. 2022; 12: 5009. https://doi.org/10.1038/s41598-022-09123-xChen P.R. et al. Disruption of anthrax toxin receptor 1 in pigs leads to a rare disease phenotype and protection from senecavirus A infection. Scientific Reports. 2022; 12: 5009. https://doi.org/10.1038/s41598-022-09123-xChang T. et al. A rapid and efficient linear mixed model approach using the score test and its application to GWAS. Livestock Science. 2019; 220: 37–45. https://doi.org/10.1016/j.livsci.2018.12.012Chang T. et al. A rapid and efficient linear mixed model approach using the score test and its application to GWAS. Livestock Science. 2019; 220: 37–45. https://doi.org/10.1016/j.livsci.2018.12.012Белоус А.А., Сермягин А.А., Зиновьева Н.А. Система оценки мясного скота по показателям эффективности использования корма и энергии роста на основе применения цифровых и геномных технологий (обзор). Сельскохозяйственная биология. 2022; 57(6): 1055–1070. https://doi.org/10.15389/agrobiology.2022.6.1055rusBelous A.A., Sermyagin A.A., Zinovieva N.A. Beef cattle evaluation by feeding efficiency and growth energy indicators based on bioinformatic and genomic technologies (review). Agricultural Biology. 2022; 57(6): 1055–1070. https://doi.org/10.15389/agrobiology.2022.6.1055engGalliou J.M. et al. Identification of Loci and Pathways Associated with Heifer Conception Rate in U.S. Holsteins. Genes. 2020; 11(7): 767. https://doi.org/10.3390/genes11070767Galliou J.M. et al. Identification of Loci and Pathways Associated with Heifer Conception Rate in U.S. Holsteins. Genes. 2020; 11(7): 767. https://doi.org/10.3390/genes11070767Wu X. et al. Genome wide association studies for body conformation traits in the Chinese Holstein cattle population. BMC Genomics. 2013; 14: 897. https://doi.org/10.1186/1471-2164-14-897Wu X. et al. Genome wide association studies for body conformation traits in the Chinese Holstein cattle population. BMC Genomics. 2013; 14: 897. https://doi.org/10.1186/1471-2164-14-897Kayan A. et al. Polymorphism and expression of the porcine Tenascin C gene associated with meat and carcass quality. Meat Science. 2011; 89(1): 76–83. https://doi.org/10.1016/j.meatsci.2011.04.001Kayan A. et al. Polymorphism and expression of the porcine Tenascin C gene associated with meat and carcass quality. Meat Science. 2011; 89(1): 76–83. https://doi.org/10.1016/j.meatsci.2011.04.001Buitenhuis B., Janss L.L.G., Poulsen N.A., Larsen L.B., Larsen M.K., Sørensen P. Genome-wide association and biological pathway analysis for milk-fat composition in Danish Holstein and Danish Jersey cattle. BMC Genomics. 2014; 15: 1112. https://doi.org/10.1186/1471-2164-15-1112Buitenhuis B., Janss L.L.G., Poulsen N.A., Larsen L.B., Larsen M.K., Sørensen P. Genome-wide association and biological pathway analysis for milk-fat composition in Danish Holstein and Danish Jersey cattle. BMC Genomics. 2014; 15: 1112. https://doi.org/10.1186/1471-2164-15-1112

The authors declare that there are no conflicts of interest present.