PSX-31 Late-Breaking Abstract: Improving the DNA database of genotypes using SNP markers for locally bred cattle in Kazakhstan

2020

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DOI 10.1093/jas/skaa278.626
Достоверность данных 70 средняя
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Аннотация

Abstract ICAR is recommending to use at least 14 STR loci or at least 100 SNP markers for cattle parentage verification recommended by ISAG. The existing database of genotyped DNA samples of meat and dairy breeds allows us to take into account not only microsatellite STR DNA loci, but since 2016 allows us to register data according to the results of studies of SNP markers. These works were supported by the Ministry of Education and Science of Kazakhstan under the grant project 1891 / GF4. The aim of the work was to study SNP in DNA for parentage verification of cattle. The following tasks have been implemented: 1) collect biological material, extract at least 1,000 DNA and conduct genotyping of DNA samples; 2) to test parentage verification and develop a database of SNPs for local cattle. 1,858 DNA samples were extracted using Stock Marks kits from Applied Biosystems. DNA testing was carried out at the Laboratory of Animal Genetics at the University of Queensland (Australia) and at the Neogen Laboratory (USA). Calculation of the reliability of parentage verification for 1067 animals was carried out automatically in the IAS system (www.plem.kz; table 1). The subbase “Database of SNPs for DNAs of local cattle” was developed, which includes up to 245 SNP markers and is filled with DNA indicators from 1,858 breeding animals. The studies conducted allowed the use of contemporary biotechnological methods with domestic breeds of beef cattle and for the first time to use the new method in breeding work with meat breeds. Already today, the created and updated database of genotyped DNA samples of beef and dairy breeds with an integrated program for calculating the reliability of livestock origin allows farmers to conduct breeding at a new higher level and meet international requirements for breeding animals (Zh.Tleulenov et al, 2017).