Genomic architecture of an experimental population of crossbred cattle based on the analysis of genome-wide SNP genotypes

The crossing of European (Bos taurus) and Zebu (Bos indicus) cattle is considered asone of the assay aimed at improving economically important traits and maintaining biodiversity in farm animal populations. The purpose of this work was to evaluate the genetic structure of an experimental population of crossbred cattle to develop the breeding program aimed at improving economically important traits while preserving Zebu-specific genomic components. The studied sample was represented by animals of experimental farm "Snegiri" of the Main Botanical Garden of the Russian Academy of Sciences, which were genotyped by approx. 50 thousands SNP using the Bovine SNP BeadChip (Zebucow, n=221). In the dataset used for the analysis was completed by genotypes of 494 samples from 27 groups of cattle, including 21 groups of Zebu of different origin, 4 groups of crossbred cattle, as well as 2 groups of European (Holstein and Black-and-White) cattle, as comparison groups. The shared genetic origin of the studied experimental population of crossbred cattle with the gene pool population of Black-and-White cattle has been shown at formation of its own genetic structure, which differs it from both Black-and-White and Holstein cattle. The presence of Zebu-specific genomic components in the studied sample, which should become a priority object for conservation, is shown. The preservation of authentic components of Black-and-White cattle in the experimental population allows considering it as a significant national genetic resource that requires further conservation as a reserve of variability. The results of the conducted research can be used in the development of balanced breeding programs based on the involvement in further reproduction of animals carrying genomic components, both Blackand-White and Zebu cattle, and aimed at increasing their breeding value for main economically important traits.

1. Глазко В.И., Боронецкая О.И., Эркенов Т.А., Кахович Б.В., Глазко Т.Т. Генетические взаимосвязи между Bos taurus и Bos indicus : (обзор) // Генетика и разведение животных. 2019. № 3. С. 48 – 57. URL: https://doi.org/10.31043/2410-2733-2019-3-48-57.

2. Hansen P.J. Physiological and cellular adaptations of zebu cattle to thermal stress // Anim. Reprod. Sci. 82 – 83 (2004). рp. 349 – 360. doi: 10.1016/j.anireprosci.2004.04.011.

3. Rodrigues Souza R.T. de, Chizzotti M.L., Vital C.E. et al. Differences in Beef Quality between Angus (Bos taurus taurus) and Nellore (Bos taurus indicus) cattle through a proteomic and phosphoproteomic approach // PLoS ONE. 2017. 12. Article e0170294. doi: 10.1371/journal.pone.0170294.

4. Moura G.A.B., de Melo Costa C.C., Fonsêca V.F.C. et al. Are crossbred cattle (F1, Bos indicus x Bos taurus) thermally different to the purebred Bos indicus cattle under moderate conditions? // Livest Sci. 2021. 246: 104457. doi: 10.1016/j.livsci.2021.104457.

5. Упелниек В.П., Завгородний С.В., Махнова Е.Н., Сенатор С.А. История происхождения и перспективы распространения зебувидного типа черно-пестрой породы крупного рогатого скота : (обзор) // Достижения науки и техники АПК. 2020. Т. 34. № 11. С. 66 – 72. doi: 10.24411/0235-2451-2020-11211.

6. Амерханов Х.А., Соловьева О.И., Морозова Н.И. и др. Оценка экономического эффекта использования в молочном скотоводстве животных черно-пестрой породы с кровностью зебу // Изв. ТСХА. 2020. Вып. 2. С. 116 – 133. doi: 10.26897/0021-342X-2020-2-116-135.

7. Родригез К.С. Характеристика генетической структуры у животных гибридного стада по полиморфным системам белков крови и молока: дис. на соиск. уч. степ. канд. биол. наук. М., 2009. 105 с.

8. Бекетов С.В., Свищева Г.Р., Упелниек В.П. и др. Сравнительный микросателлитный анализ зебувидного скота с породами Bos taurus // Генетика. 2024. Т. 60. № 3. С. 68 – 75.

9. Steemers F.J., Gunderson K.L. Whole genome genotyping technologies on the BeadArrayTM platform // Biotechnol. J. 2007. V. 2. Р. 41 – 49.

10. Зиновьева Н.А., Доцев А.В., Сермягин А.А. и др. Изучение генетического разнообразия и популяционной структуры пяти российских пород крупного рогатого скота с использованием полногеномного анализа SNP // С.-х. биология. 2016. Т. 51. № 6. С. 788–800. doi: 10.15389/agrobiology.2016.6.788rus.

11. McTavish E.J., Decker J.E., Schnabel R.D., Taylor J.F., Hillis D.M. New World cattle show ancestry from multiple independent domestication events // Proceedings of the National Academy of Sciencesof the United States of America. 2013. V. 110 (15). E1398 – E1406. doi:10.1073/pnas.1303367110.

12. Decker J.E., McKay S.D., Rolf M.M. et al. Worldwide Patterns of Ancestry, Divergence, and Admixture in Domesticated Cattle (G McVean, Ed.) // PLoS Genet. 2014. V. 10. e1004254. doi:10.1371/journal.pgen.1004254.

13. Абдельманова А.С., Харзинова В.Р., Форнара М.С. и др. Оценка генетических взаимосвязей пород крупного рогатого скота черно-пестрого корня с предковыми популяциями на основе полногеномного SNP-генотипирования современных и музейных образцов // С.-х. биология. 2024. Т. 59. № 4. С. 605 – 619.

14. Sermyagin A.A., Dotsev A.V., Gladyr E.A. et al. Whole-genome SNP analysis elucidates the genetic structure of Russian cattle and its relationship with Eurasian taurine breeds // Genetics, Selection, Evolution. 2018. 50: 37. doi: 10.1186/s12711-018-0408-8.

15. Zinovieva N.A., Dotsev A.V., Sermyagin A.A. et al. Selection signatures in two oldest Russian native cattle breeds revealed using high-density single nucleotide polymorphism analysis // PLoS One. 2020. 15 (11): e0242200. doi: 10.1371/journal.pone.0242200.

16. Yurchenko A., Yudin N., Aitnazarov R. et al. Genome-wide genotyping uncovers genetic profiles and history of the Russian cattle breeds // Heredity (Edinb). 2018. 120: 125 – 137. doi: 10.1038/s41437-017-0024-3.

17. Абдельманова А.С., Доцев А.В., Сермягин А.А. и др. Полногеномные исследования структуры популяций российских локальных пород черно-пестрого корня // Генетика. 2022. Т. 58. № 7. С. 787 – 797. doi: 10.31857/S0016675822070025.

18. Nayee N., Sahana G., Gajjar S. et al. Suitability of existing commercial single nucleotide polymorphism chips for genomic studies in Bos indicus cattle breeds and their Bos taurus crosses // J. Anim. Breed Genet. 2018. Oct. 135 (6): 432 – 441. doi: 10.1111/jbg.12356.

19. Volkandari S.D., Rahmawati I., Cahyadi M. et al. Admixture study of Ongole grade cattle based on genome-wide SNP data // IOP Conf. Ser.: Earth Environ. Sci. 2021. 762 012047. Doi: 10.1088/1755-1315/762/1/012047.

20. Hartati, Putra W.P.B. Genome-Wide Association Study for Body Weight and Carcass Weight in Sumba Ongole Bulls (Bos indicus) // Tropical Animal Science Journal. 2023. 46 (4). 389 – 395. URL: https://doi.org/10.5398/tasj.2023.46.4.389/.

21. Dixit S.P., Bhatia A.K., Ganguly I. et al. Genome analyses revealed genetic admixture and selection signatures in Bos indicus // Sci Rep 11. Article 21924. 2021. URL: https://doi.org/10.1038/s41598-021-01144-2.

22. Al Kalaldeh M., Swaminathan M., Podtar V. et al. Detection of genomic regions that differentiate Bos indicus from Bos taurus ancestral breeds for milk yield in Indian crossbred cows // Front Genet. 2023. Jan. 9:13:1082802. doi: 10.3389/fgene.2022.1082802.

23. Purcell S., Neale B., Todd-Brown K. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses // Am. J. Hum. Genet. 2007. V. 81. № 3. P. 559 – 575. doi: 10.1086/519795.

24. Nei M. Estimation of average heterozygosity and genetic distance from small number of individuals // Genetics. 1978. № 89. P. 583 – 590ю

25. Weir B.S., Cockerham C.C. Estimating F-Statistics for the analysis of population structure // Evolution. 1984. V. 38. № 6. P. 1358 – 1370.

26. Kalinowski S.T. Counting alleles with rarefaction: Private alleles and hierarchical sampling designs // Conserv. Genet. 2004. № 5. P. 539 – 543. doi:10.1023/B:COGE.0000041021.91777.1a.

27. Keenan K., McGinnity P., Cross T.F., Crozier W.W., Prodöhl P.A. diveRsity: An R package for the estimation of population genetics parameters and their associated errors // Methods in Ecology and Evolution. 2013. V. 4. № 8. P. 782 – 788. doi: 10.1111/2041-210X.12067.

28. Wickham H. ggplot2: elegant graphics for data analysis. New York: Springer. 2009. P. 268.

29. Huson D.H., Bryant D. Application of phylogenetic networks in evolutionary studie // Mol. Biol. Evol. 2006. V. 23. № 2. P. 254 – 267. doi: 10.1093/molbev/msj030.

30. Alexander D.H., Novembre J., Lange K. Fast model-based estimation of ancestry in unrelated individuals // Genome Res. 2009. № 19. P. 1655 – 1664. doi: 10.1101/gr.094052.109.

31. Milanesi M., Capomaccio S., Vajana E. et al. BITE: an R package for biodiversity analyses // bioRxiv. 2017. doi: 10.1101/181610.

32. Ogunbawo A.R., Mulim H.A., Campos G.S. et al. Tailoring Genomic Selection for Bos taurus indicus: A Comprehensive Review of SNP Arrays and Reference Genomes // Genes. 2024. 15 (12): 1495. URL: https://doi.org/10.3390/genes15121495.