Increasing the productivity and effi ciency of lamb production is a key factor in the competitiveness of the meat sheep industry. Therefore, in order to conduct sheep breeding more effectively it is necessary to apply new approaches to increase and improve the quality of products.Considerable interest are modern technologies involving the use of DNA markers, which are widely used in national breeding programs of a number of countries with developed animal husbandry and have a signifi cant impact on improving productivity indicators. A significant number of genes associated with meat productivity and meat quality have been identifi ed. However, in sheep breeding, information about the main genes or loci that affect the growth characteristics and productive traits of sheep is relatively limited. Due to the growing interest in the production of young mutton and lamb, priority is given to the study of genes that control meat productivity. The greatest interests are studies on the evaluation of the polymorphism of the growth hormone (GH) gene, which controls growth and development, as well as infl uencing the meat productivity of sheep. In this regard, the purpose of this work was research aimed at fi nding associations between polymorphic variants of the growth hormone gene and the qualitative characteristics of meat in meat and wool sheep of the genotype ½ Poll Dorset × ½ North Caucasian Meat and Wool breed bred in the Stavropol Territory. The data obtained when studying the histostructure of the m. Longissimus dorsi, depending on the genotypes of GH gene, indicate that the muscle tissue in individuals with AB and BB genotypes was characterized by a large number of muscle fi bers by 5,7 and 6,4 %, their smaller diameter by 7,6 and 9,2 %, and a lower content of connective tissue compared to animals with the genotype AA of GH gene.

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At present, modern technologies involving the use of DNA markers, which are widely used in national breeding programs in a number of countries with developed animal husbandry are of considerable interest and have a signifi cant infl uence on improving productivity traits. A signifi cant number of genes associated with meat productivity and meat quality have been identifi ed. In sheep breeding such research has been developed only recently. Due to the growing interest in the production of young mutton and lamb, priority is given to the study of genes that control meat productivity. However, the most popular are genetic markers that are interconnected with candidate genes, whose protein products play a signifi cant role in the formation or regulation of physiological and biochemical processes. Alleles of the Growth Hormone (GH) gene and Calpastatin (CAST) gene are considered as potential markers of sheep meat productivity. In this regard, the purpose of this work was to study the polymorphism of GH and CAST genes in crossbred wool-and-meat producing sheep (1/2 Poll Dorset × 1/2 North Caucasian wool-and-meat producing breed) bred in the Stavropol Territory. The analysis of Somatotropin and Calpastatin gene polymorphism was performed by PCR-PDRF. When studying GH gene polymorphism, the genotypes AA, AB and BB have been found, the frequency of occurrence of which was 29,7; 42,8 and 27,5 %, respectively. Allele A prevailed in the studied animals – 0,786, allele B was – 0,214. The CAST gene was represented by two genotypes MM and MN (the NN genotype was absent in the animals of this group) with a frequency of 87,9 and 12,1 %, respectively. The frequency of the M allele was high at 0,94, while the n allele was low at 0,06. The results obtained during the researches indicate the establishment of a variety of allelic variants of Somatotropin and Calpastatin genes in wool-and-meat producing sheep. Further research will be aimed at studying the association of identifi ed polymorphisms with economically useful traits.

Improving the productive traits of animals through the use of genetic potential is impossible without a systematic evaluation of productivity characteristics and conformation traits. Special attention has always been paid to the study of the physique of animals in association with their productivity. The priorities in the selection of farm animals today are the parameters of meat productivity. For breeding work in order to increase productivity indicators in sheep, it is necessary to use the most informative parameters. The above dictates the need to apply new approaches to the evaluation of phenotypic parameters. Each trait has certain significance in the description of the phenotype, which can be evaluated on the basis of mathematical methods of analysis. Mathematical analysis, as well as mathematical modeling methods, is successfully used in animal husbandry. A new approach to the lifetime evaluation of sheep meat productivity using a multidimensional analysis method as the analysis of the main components has been presented in the article. The main purpose of the applied analysis method is to reduce the dimensionality for a multidimensional matrix of initial data. As a result of this analysis, a certain number of new variables are obtained which cannot be isolated during the direct study of the object, but has a high degree of correlation with the actual traits. We have described one of the possible ways to solve the problem of forming a complex numerical indicator using the principal component method. This indicator is called a complex indicator of productivity. At the same time, it is expected that the indicator under consideration does not impose restrictions on the number of parameters used in its formation. It is assumed that the high value of the complex productivity indicator obtained on the basis of lifetime measurements of the physique of animals will correspond to the same high value of the complex indicator obtained on the basis of slaughter parameters. As the result of the analysis, the mathematical and statistical method for calculating the correlation between lifetime traits and slaughter indicators of animal productivity has been carried out. On the base of conducted method of mathematical analysis, it can be assumed that the complex indicator can be used as the criterion for evaluating the productivity of sheep.