Loci of the genotyping panel by sequencing using AgriSeq technology in the Manych Merino breed

Using the genotyping of sheep of the Manych Merino breed on the basis of Illumina BeadChip Ovine 600K, loci suitable for genotyping by sequencing animals of this breed were found. Single nucleotide polymorphisms with a high frequency of occurrence in the range of 0.2850-0.3149 homozygotes of both wild and mutant variants were identified. Heterozygous variants of these substitutions occurred with a frequency of 0.379±0.012. The number of polymorphisms corresponding to the selected criteria was 521. Analysis of the location of the detected SNPs in the sheep genome showed their presence along the entire length of the genotyped DNA region. The largest number of polymorphisms were found on chromosomes 1, 2, 3, 17 and X. The least polymorphisms were detected on chromosomes 18, 21, 24 and 25. The resulting set of substitutions will effectively solve the problems of confirming the authenticity of the origin of sheep of the Manych Merino breed, accurately identify animals in the process of breeding work, and account for inbreeding in the population. The proposed set of SNPs is recommended both for use in genotyping by sequencing of a new generation, and for customization of SNP biochips.

1. De Camargo G. M. F. The role of molecular genetics in livestock production. Animal Production Science. 2018;59(2):201-206. DOI: https://doi.org/10.1071/AN18013

2. Xu S.-S., Gao L., Shen M., Lyu F. Whole-Genome Selective Scans Detect Genes Associated With Important Phenotypic Traits in Sheep (Ovis aries). Frontiers in Genetics. 2021;12:738879. DOI: https://doi.org/10.3389/fgene.2021.738879

3. Mrode R. A., Ojango J. M. K., Okeyo A. M., Mwacharo J. Genomic selection and use of molecular tools in breeding programs for indigenous and crossbred cattle in developing countries: current status and future prospects. Frontiers in Genetics. 2019;9:00694. DOI: https://doi.org/10.3389/fgene.2018.00694

4. Braz C. U., Rowan T. N., Schnabel R. D. Genome-wide association analyses identify genotype-byenvironment interactions of growth traits in Simmental cattle. Scientific reports. 2021;11:13335. DOI: https://doi.org/10.1038/s41598-021-92455-x

5. Gao G., Gao N., Li S., Kuang W., Zhu L., Jiang W., Yu W., Guo J., Li Z., Yang C., Zhao Y. GenomeWide Association Study of Meat Quality Traits in a Three-Way Crossbred Commercial Pig Population. Frontiers in Genetics. 2021;12:614087. DOI: https://doi.org/10.3389/fgene.2021.614087

6. Al-Atiyat Raed M. The power of 28 microsatellite markers for parentage testing in sheep. Electronic Journal of Biotechnology. 2015;18(2):116-121. DOI: https://doi.org/10.1016/j.ejbt.2015.01.001

7. Clarke S. M., Henry H. M., Dodds K. G., Jowett T. W. D., Manley T. R. A High Throughput Single Nucleotide Polymorphism Multiplex Assay for Parentage Assignment in New Zealand Sheep. PLOS ONE. 2014;9(4):e93392. DOI: https://doi.org/10.1371/journal.pone.0093392

8. Heaton M. P., Leymaster K. A., Kalbfleisch T. S., Kijas J. W., Clarke S. M., McEwan J., Maddox J. F., Basnayake V., Petrik D. T., Simpson B., Smith T. P. L., Chitko-McKown C. G. SNPs for Parentage Testing and Traceability in Globally Diverse Breeds of Sheep. PLOS ONE. 2014;9(4):e94851. DOI: https://doi.org/10.1371/journal.pone.0094851

9. De Donato M., Peters S. O., Mitchell S. E., Hussain T., Imumorin I. G. Genotyping-by-Sequencing (GBS): A Novel, Efficient and Cost-Effective Genotyping Method for Cattle Using Next-Generation Sequencing. PLOS ONE. 2013;8(5):e62137. DOI: https://doi.org/10.1371/journal.pone.0062137

10. Ciani E., Mastrangelo S., Da Silva A., Marroni F., Ferencakovic M., Ajmone-Marsan P. et al. On the origin of European sheep as revealed by the diversity of the Balkan breeds and by optimizing population-genetic analysis tools. Genetics Selection Evolution. 2020;52(1):1-14. DOI: https://doi.org/10.1186/s12711-020-00545-7

11. Willis R. C. A., Burrell M., Swimley P., Siddavatam R. Modular automation solution for genotyping by sequencing for animal breeding. Proc. W. Cong. Gen. App. Livest. Prod. 2018;11:313.

12. Gebrehiwot N. Z., Strucken E. M., Marshall K. SNP panels for the estimation of dairy breed proportion and parentage assignment in African crossbred dairy cattle, Genetics Selection Evolution. 2021;53(1):21. DOI: https://doi.org/10.1186/s12711-021-00615-4

13. Brito L. F., Clarke S. M., McEwan J. C., Miller S. P., Pickering N. K., Bain W. E., Dadds K. G., Sargolzaei M., Schenkel F. S. Prediction of genomic breeding values for growth, carcass and meat quality traits in a multi-breed sheep population using a HD SNP chip. BMC genetics. 2017;18:7. DOI: https://doi.org/10.1186/s12863-017-0476-8

14. Rahman M. A., Juyena N. S., Shmsuddin M. M., Bhuiyan M. U. Genomic tools and genetic improvement of crossbred Friesian cattle. Research in Agriculture Livestock and Fisheries. 2021;8(1):89-107. DOI: https://doi.org/10.3329/ralf.v8i1.53271

15. Holman B. W. B., Malau-Aduli A. E. O. A Review of Sheep Wool Quality Traits. Annual Review & Research in Biology. 2012;2(1):1-14.

16. Purcell S., Neale B., Todd-Brown K., Thomas L., Ferreira M. A. R., Bender D., Maller J., Sklar P., de Bakker P. I. W., Daly M. J., Sham P. C. PLINK: A tool set for whole-genome association and population-based linkage analyses. The American journal of human genetics. 2007;81(3):559-575. DOI: https://doi.org/10.1086/519795

17. McClure M. C., McCarthy J., Flynn P., McClure J. C., Dair E., O'Connell D. K., Kearney J. F. SNP Data Quality Control in a National Beef and Dairy Cattle System and Highly Accurate SNP Based Parentage Verification and Identification. Frontiers in Genetics. 2018;9:00084. DOI: https://doi.org/10.3389/fgene.2018.00084

18. Tortereau F., Moreno C. R., Tosser-Klopp G. Development of a SNP panel dedicated to parentage assignment in French sheep populations. BMC genetics. 2017;18:50. DOI: https://doi.org/10.1186/s12863-017-0518-2

19. Hulsegge I., Schoon M., Windig J., Neuteboom M., Hiemstra S.J., Schurink A. Development of a genetic tool for determining breed purity of cattle. Livestock Science. 2019;223:60-67. DOI: https://doi.org/10.1016/j.livsci.2019.03.002