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\def\RunningAuthor{Farit F. Zinnatov et al.}
\firstPage{1428}
\articleType{Original Article}
\receivedDate{20.09.2019}
\acceptedDate{18.12.2019}
\revisedDate{12.12.2019}
\journalVolume{2020, 11}
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\title{Studying the association of polymorphic variants of LEP, TG5, CSN3, LGB\textbf{\space }genes with signs of dairy productivity of cattle}
\author{Farit~F.~Zinnatov\textsuperscript{*}\textsuperscript{1},  
            Farida~F.~Zinnatova\textsuperscript{2},  
            Ali~H.~Volkov\textsuperscript{1},  
            Takhir~M.~Akhmetov\textsuperscript{1},  
            Azat~M.~Alimov\textsuperscript{1},  
            Talgat~R.~Yakupov\textsuperscript{1},  
            Damir~D.~Hairullin\textsuperscript{1}, 
            Natalia~Yu.~Safina\textsuperscript{1}~\\[5pt]{\textsuperscript{1}Kazan State Academy of Veterinary Medicine by N.E. Bauman, Sibirsky tract 35, Kazan city, 420029, Russia}~\\{\textsuperscript{2}Tatar Scientific Research Institute of Agriculture, FRC Kazan Scientific Center, Russian Academy of Sciences, Orenburg tract 48,  Kazan city, 420059, Russia}}

\begin{abstract}
The efficiency of selection and breeding work in animal husbandry depends largely on the accuracy of the evaluation of the breeding value of animals. The integration of molecular genetics into applied science made it possible to assess the genetic potential of animal productivity not only on the basis of phenotype data but also directly at the DNA level. The study was conducted on the basis of  Tatar Scientific Research Institute of Agriculture, FRC Kazan Scientific Center, Russian Academy of Sciences. The object of the study was DNA samples obtained from the blood of Holstein cows belonging to the stud farm ``named after Lenin'' of Atninsky district of the Republic of Tatarstan. Animal blood was taken from the tail vein using vacutainer tubes with 100mM EDTA. DNA was isolated from the blood in the amount of 100 \ensuremath{\mu}l using a set of reagents for DNA extraction from the ``Ampliprime DNA-sorb-B'' clinical material (NextBio, Russia), according to the method presented by the producer. After amplification, each DNA fragment obtained by us in the study of TG5, CSN3, LGB genes, was subjected to cleavage by a restriction endonuclease. Hydrolysis was conducted at 37\ensuremath{^\circ}C for 12 hours. The analysis of polymorphism of candidate genes of dairy productivity of leptin, thyroglobulin, kappa casein and beta-lactoglobulin with the use of PCR-RFLP was carried out. The most common were homozygous TG5\ensuremath{^{CC}}, CSN3\ensuremath{^{AA}} and heterozygous LEP\ensuremath{^{CT}}, LGB\ensuremath{^{AB}} genotypes. The study of the effect of polymorphism of these genes on milk production showed that animal carriers of LEP\ensuremath{^{CT}}, TG5\ensuremath{^{TT}}, CSN3\ensuremath{^{AB}}, LGB\ensuremath{^{BB}} genotypes have the best indicators of dairy productivity.
\end{abstract}\def\keywordstitle{Keywords}

\begin{keywords}genotype,\newline polymorphism,\newline DNA,\newline genes,\newline PCR-RFLP,\newline milk production,\newline fat,\newline cows
\end{keywords}
\twocolumn[ \maketitle {\printKwdAbsBox}]
\makeatletter{\raggedright\textsuperscript{*}Corresponding Author\par Name:\ Farit~F.~Zinnatov~\\ Phone:\ 89033146175~\\  Email:\ Smolentsev82@mail.ru
        \par}\vspace*{-11pt}\hrulefill\par{\fontsize{12}{14}\selectfont ISSN: 0975-7538}\par% 
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\section{Introduction}
The efficiency of selection and breeding work in animal husbandry depends largely on the accuracy of the evaluation of the breeding value of animals. The integration of molecular genetics into applied science made it possible to assess the genetic potential of animal productivity not only on the basis of phenotype data but also directly at the DNA level \unskip~\citep{660174:15545057,660174:15545058}. The adoption of laboratory developments in the field of DNA-diagnostics in breeding and commodity farms is intended to accelerate breeding work in the decision of culling and selection of farm animals \unskip~\citep{660174:15545059}. 

To date, cattle have been studied most widely in the molecular genetics aspect among farm animals. Most of the known genetic markers of economic traits were found in cattle, most of them are associated with indicators of dairy productivity. This quantitative trait is determined by a large number of genes with different individual participation. Different combinations of variants of these genes will differ in determining the characteristics of the dairy productivity of cattle \unskip~\citep{660174:15545060,660174:15545061}.

The genes of leptin (LEP), thyroglobulin (TG5), kappa casein (CSN3), beta-lactoglobulin (LGB) are of considerable interest in dairy farming. Lipid metabolism genes LEP and TG5 affect fat metabolism, percentage and fat yield in cow's milk \unskip~\citep{660174:15545062,660174:15545063}. CSN3 and LGB genes encoding kappa casein and beta-lactoglobulin milk proteins are associated with milk protein content and technological properties \unskip~\citep{660174:15545064,660174:15545066}. Complex genetic evaluation of animals, which is based on DNA-diagnostics, allows us to increase the accuracy of the evaluation of the breeding value of animals, and accelerate the selection decisions. As a result, the efficiency of selection and breeding work in dairy cattle breeding increases by 20-25\%\unskip~\citep{660174:15545068,660174:15545065,660174:15545067}. The aim of this work is to analyze the polymorphism of the candidate genes of dairy productivity of leptin (LEP), thyroglobulin (TG5), kappa casein (CSN3), beta-lactoglobulin (LGB), and to study the relationship of their polymorphic variants with the signs of milk productivity of cows using DNA-diagnostics.
    
\section{Materials and Methods}
The study was conducted on the basis of Tatar Scientific Research Institute of Agriculture, FRC Kazan Scientific Center, Russian Academy of Sciences. The object of the study was DNA samples obtained from the blood of Holstein cows belonging to the stud farm ``named after Lenin'' of Atninsky district of the Republic of Tatarstan. Animal blood was taken from the tail vein using vacutainer tubes with 100mM EDTA. DNA was isolated from the blood in the amount of 100 \ensuremath{\mu}l using a set of reagents for DNA extraction from the ``Ampliprime DNA-sorb-B'' clinical material (NextBio, Russia), according to the method presented by the producer. DNA fragment amplification was performed in T100 Thermal Cycler (Bio-Rad, USA) and on MyCycler programmable Thermal Cycler (Bio-Rad, USA). After amplification, each DNA fragment obtained by us in the study of TG5, CSN3, LGB genes, was subjected to cleavage by a restriction endonuclease. Hydrolysis was conducted at 37\ensuremath{^\circ}C for 12 hours. The results were analyzed by gel electrophoresis in agarose gel with an addition of 5 \ensuremath{\mu}l of 10\% ethidium bromide, followed by documentation of the results using the Gel\&Doc video system (Bio-Rad, USA). Dairy productivity was determined by test milkings. Milk quality analysis was performed on the ``Clover-2'' device in accordance with the producer's instructions.

The actual amount of milk obtained for 305 days of lactation from each group of cows understudy was recalculated to determine the basic fat content (standard weight) according to the following formula:
\begin{eqnarray*}M_{fat}=\frac{\left(M_{fact}\ast F_{fact}\right)}{F_{basis}} \end{eqnarray*}
where,

M\ensuremath{_{fat}} {\textendash} the conventional value of the net weight of dairy raw material by fat, kg;

M\ensuremath{_{fact}} {\textendash} the actual value of the net weight of dairy raw material, kg;

F\ensuremath{_{fact}} {\textendash} the actual value of the mass fraction of fat, \%;

F\ensuremath{_{basis}} {\textendash} the basic all-Russian norm of the mass fraction of fat,\%.

The data obtained were statistically processed by common methods.
    
\section{Results and Discussion}
During the study of polymorphism of the studied genes, the following results were obtained (Table~\ref{tw-9293544f2dd9}).


\begin{table*}[!htbp]
\caption{\boldmath {LEP, TG5, CSN3, LGB gene polymorphism} }
\label{tw-9293544f2dd9}
\centering 
\begin{threeparttable}

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\tbltoprule \rowcolor{kwdboxcolor}Gene & Genotype & \multicolumn{4}{p{\dimexpr(.4369\linewidth-2\tabcolsep)}}{\cAlignHack Genotype frequencies} & \multicolumn{2}{p{\dimexpr(.2277\linewidth-2\tabcolsep)}}{\cAlignHack Allele frequencies } & \cAlignHack Chi-square\\
\rowcolor{kwdboxcolor} &  & \cAlignHack n(f\ensuremath{_{o}}) & \cAlignHack \%(f\ensuremath{_{o}}) & \cAlignHack n(f\ensuremath{_{e}}) & \cAlignHack \%(f\ensuremath{_{e}}) & \cAlignHack  & \cAlignHack  & \\
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 &
  \cAlignHack TT &
  \cAlignHack 14 &
  \cAlignHack 28 &
  \cAlignHack 18 &
  \cAlignHack 35 &
  \cAlignHack T &
  \cAlignHack С &
  \cAlignHack \\
LEP &
  \cAlignHack СT &
  \cAlignHack 31 &
  \cAlignHack 62 &
  \cAlignHack 24 &
  \cAlignHack 48 &
  \multicolumn{1}{p{\dimexpr(.13080000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.59}} &
  \multicolumn{1}{p{\dimexpr(.09689999999999998\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.41}} &
  \cAlignHack 3.96*\\
 &
  \cAlignHack СС  &
  \cAlignHack 5 &
  \cAlignHack 10 &
  \cAlignHack 8 &
  \cAlignHack 17 &
   &
   &
  \\
 &
  \cAlignHack TT &
  \cAlignHack 6 &
  \cAlignHack 12 &
  \cAlignHack 5 &
  \cAlignHack 10 &
  \cAlignHack T &
  \cAlignHack С &
  \cAlignHack \\
TG5  &
  \cAlignHack TC &
  \cAlignHack 20 &
  \cAlignHack 40 &
  \cAlignHack 22 &
  \cAlignHack 44 &
  \multicolumn{1}{p{\dimexpr(.13080000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.32}} &
  \multicolumn{1}{p{\dimexpr(.09689999999999998\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.68}} &
  \cAlignHack 0.33*\\
 &
  \cAlignHack СС &
  \cAlignHack 24 &
  \cAlignHack 48 &
  \cAlignHack 23 &
  \cAlignHack 46 &
   &
   &
  \cAlignHack \\
 &
  \cAlignHack {{A}}{{A}} &
  \cAlignHack 33 &
  \cAlignHack 66 &
  \cAlignHack 33.5 &
  \cAlignHack 67 &
  \cAlignHack {{A}} &
  \cAlignHack {{B}} &
  \cAlignHack \\
CSN3  &
  \cAlignHack {{A}}{{B}} &
  \cAlignHack 16 &
  \cAlignHack 32 &
  \cAlignHack 14.5 &
  \cAlignHack 30 &
  \multicolumn{1}{p{\dimexpr(.13080000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.82}} &
  \multicolumn{1}{p{\dimexpr(.09689999999999998\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.18}} &
  \cAlignHack 0.35*\\
 &
  \cAlignHack {{B}}{{B}} &
  \cAlignHack 1 &
  \cAlignHack 2 &
  \cAlignHack 2 &
  \cAlignHack 3 &
   &
   &
  \cAlignHack \\
 &
  \cAlignHack {{A}}{{A}} &
  \cAlignHack 15 &
  \cAlignHack 30 &
  \cAlignHack 15.1 &
  \cAlignHack 30.3 &
  \cAlignHack {{A}} &
  \cAlignHack {{B}} &
  \cAlignHack \\
LGB &
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  \cAlignHack 50 &
  \cAlignHack 24.8 &
  \cAlignHack 49.4 &
  \multicolumn{1}{p{\dimexpr(.13080000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.55}} &
  \multicolumn{1}{p{\dimexpr(.09689999999999998\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.45}} &
  \cAlignHack 0.01*\\
 &
  \cAlignHack {{B}}{{B}} &
  \cAlignHack 10 &
  \cAlignHack 20 &
  \cAlignHack 10.1 &
  \cAlignHack 20.3 &
   &
   &
  \cAlignHack \\
\tblbottomrule 
\end{tabulary}\par 
\begin{tablenotes}\footnotesize 
    
\item{* - the significant difference P \textless\ 0.05}
\end{tablenotes}
\end{threeparttable}

\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Influence of LEP, TG5, CSN3, LGB gene polymorphism on dairy productivity of cows} }
\label{tw-84b054245483}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.1427\linewidth-2\tabcolsep}p{\dimexpr.17150000000000002\linewidth-2\tabcolsep}p{\dimexpr.1658\linewidth-2\tabcolsep}p{\dimexpr.1704\linewidth-2\tabcolsep}p{\dimexpr.16930000000000003\linewidth-2\tabcolsep}p{\dimexpr.18029999999999998\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}Genotype & \multicolumn{5}{p{\dimexpr(.8573\linewidth-2\tabcolsep)}}{\cAlignHack Milk production parameters}\\
\rowcolor{kwdboxcolor} & \cAlignHack Yield, kg & \cAlignHack Fat content, \% & \cAlignHack Protein content, \% & \cAlignHack Fat yield, kg & \cAlignHack Protein yield, kg\\
\tblmidrule 
\multicolumn{6}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack LEP }\\
TT &
  6303,5\ensuremath{\pm}380,4 &
  3,96\ensuremath{\pm}0,12 &
  2,95\ensuremath{\pm}0,05 &
  252,5\ensuremath{\pm}20,2 &
  186,2\ensuremath{\pm}11,7\\
CT &
  6537,4\ensuremath{\pm}220,9 &
  4,00\ensuremath{\pm}0,07 &
  2,96\ensuremath{\pm}0,03 &
  263,6\ensuremath{\pm}12,0 &
  193,2\ensuremath{\pm}7,0\\
СС  &
  6802,2\ensuremath{\pm}709,2 &
  3,78\ensuremath{\pm}0,13 &
  2,89\ensuremath{\pm}0,07 &
  260,2\ensuremath{\pm}36,2 &
  197,0\ensuremath{\pm}21,0\\
 &
   &
   &
   &
   &
  \\
\multicolumn{6}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack TG5 }\\
TT &
  7743,5\ensuremath{\pm}664,6 &
  4,22\ensuremath{\pm}0,17 &
  2,79\ensuremath{\pm}0,07 &
  328,8\ensuremath{\pm}35,8 &
  217,2\ensuremath{\pm}21,8\\
TC &
  5909,8\ensuremath{\pm}243,8 &
  3,86\ensuremath{\pm}0,09 &
  2,97\ensuremath{\pm}0,04 &
  229,2\ensuremath{\pm}11,7 &
  175,4\ensuremath{\pm}7,5\\
СС &
  6675,5\ensuremath{\pm}230,1 &
  4,00\ensuremath{\pm}0,08 &
  2,97\ensuremath{\pm}0,03 &
  268,7\ensuremath{\pm}13,0 &
  198,6\ensuremath{\pm}7,8\\
 &
   &
   &
   &
   &
  \\
\multicolumn{6}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack CSN3 }\\
AA  &
  6303,8\ensuremath{\pm}231,7 &
  3,90\ensuremath{\pm}0,06 &
  2,90\ensuremath{\pm}0,03 &
  249,9\ensuremath{\pm}11,5 &
  184,7\ensuremath{\pm}6,6\\
AB  &
  6897,4\ensuremath{\pm}288,3 &
  4,06\ensuremath{\pm}0,12 &
  2,90\ensuremath{\pm}0,04 &
  282,2\ensuremath{\pm}17,9 &
  206,9\ensuremath{\pm}10,3\\
 &
  6536 &
  3,72 &
  2,68 &
  242,8 &
  175,1\\
 &
   &
   &
   &
   &
  \\
\multicolumn{6}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack LGB }\\
AA  &
  6432,4\ensuremath{\pm}344,8 &
  4,03\ensuremath{\pm}0,12 &
  2,90\ensuremath{\pm}0,05 &
  260,3\ensuremath{\pm}17,5 &
  186,5\ensuremath{\pm}9,8\\
AB  &
  6483,6\ensuremath{\pm}252,8 &
  3,90\ensuremath{\pm}0,07 &
  2,90\ensuremath{\pm}0,04 &
  255,0\ensuremath{\pm}13,1 &
  192,2\ensuremath{\pm}8,2\\
 &
  6634,4\ensuremath{\pm}459,5 &
  4,06\ensuremath{\pm}0,16 &
  2,98\ensuremath{\pm}0,05 &
  272,8\ensuremath{\pm}27,2 &
  197,6\ensuremath{\pm}13,9\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Recalculation of the actual amount of milk on the base fat content (standard weight)} }
\label{tw-c23f54bbd2b1}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.171\linewidth-2\tabcolsep}p{\dimexpr.1958\linewidth-2\tabcolsep}p{\dimexpr.1917\linewidth-2\tabcolsep}p{\dimexpr.2179\linewidth-2\tabcolsep}p{\dimexpr.2236\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}Genotype  & The actual amount of milk for 305 days of lactation, kg & Fat content in milk,\% & Standard weight, kg & Difference between standard and actual weight,\%\\
\tblmidrule 
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack LEP }\\
LEP\ensuremath{^{TT}} &
  6303,50 &
  3,96 &
  7341,70 &
  16,5\\
LEP\ensuremath{^{CT}} &
  6537,40 &
  4,00 &
  7691,05 &
  17,6\\
LEP\ensuremath{^{CС}} &
  6802,20 &
  3,78 &
  7562,40 &
  11,2\\
 &
   &
   &
   &
  \\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack TG5}\\
TG5\ensuremath{^{TT}} &
  7743,50 &
  4,22 &
  9611,05 &
  24,1\\
TG5\ensuremath{^{TC}} &
  5909,75  &
  3,86 &
  6709,30 &
  13,5\\
TG5\ensuremath{^{СС}} &
  6675,45 &
  4,00 &
  7853,50 &
  17,6\\
 &
   &
   &
   &
  \\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack CSN3 }\\
CSN3\ensuremath{^{{{A}}{{A}}}} &
  6303,80 &
  3,90  &
  7230,80 &
  14,7\\
CSN3\ensuremath{^{{{A}}{{B}}}} &
  6897,40 &
  4,06 &
  8236,30 &
  19,4\\
CSN3\ensuremath{^{{{B}}{{B}}}} &
  6536,00 &
  3,72 &
  7151,10 &
  9,4\\
 &
   &
   &
   &
  \\
\multicolumn{5}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{\cAlignHack LGB}\\
LGB\ensuremath{^{{{A}}{{A}} }} &
  6432,40 &
  4,03 &
  7624,30 &
  18,5\\
LGB\ensuremath{^{{{A}}{{B}} }} &
  6483,60 &
  3,90 &
  7437,07 &
  14,7\\
LGB\ensuremath{^{{{B}}{{B}} }} &
  6634,40 &
  4,06 &
  7922,20 &
  19,4\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}
The leptin gene is dominated by the heterozygous CT genotype with a frequency of occurrence of 62\%, the proportion of homozygous TT and CC genotypes is 28\% and 10\%, respectively. It was found that animals with the desirable homozygous TT genotype have the lowest frequency of occurrence in cows by the thyroglobulin gene. The frequency distribution of genotypes was as follows: homozygous TT genotype {\textendash} 12\%, heterozygous TC genotype {\textendash} 40\%, homozygous CC genotype {\textendash} 48\%. For the kappa-casein gene, the homozygous AA genotype is more common {\textendash} 66\%, the proportion of the heterozygous AB genotype is 32\%, and the proportion of the homozygous BB genotype is only 2\%. For the LGB gene, the heterozygous AB genotype is more common {\textendash} 50\% and the least common is the homozygous BB genotype {\textendash} 20\%. We have obtained the following results in the study of the relationship of polymorphic variants of the studied genes with the signs of dairy productivity of cows using PCR-RFLP analysis (Table~\ref{tw-84b054245483}).

Cows with the homozygous leptin LEP\ensuremath{^{СС}} genotype have the best indicators of quantitative dairy productivity. Milk yield of cows in this group averaged 6802.2 kg, which is 498.7 kg more than in the group with the homozygous LEP\ensuremath{^{TT}} genotype (p{\textless}0.05). However, cows with the heterozygous LEP\ensuremath{^{CT}} genotype have the highest butter-fat yielding capacity {\textendash} 4.0\%, which, despite the average level of milk yield (6537.4 kg), increases the yield of milk fat to 263.6 kg. Furthermore, cows with the LEP\ensuremath{^{CT}} genotype have a high protein content in milk; the milk protein yield of cows in this group is 7.6 kg more than of cows with the homozygous LEP\ensuremath{^{TT}} genotype (p{\textless}0.05). Cows with the heterozygous LEP\ensuremath{^{CT}} genotype surpass homozygous individuals with the LEP\ensuremath{^{CC}} genotype by fat content in milk by 0.22\% (P{\textless}0.05), as well as by protein content by 0.07\%.

Analysis of the influence of TG5 gene polymorphism of lipid metabolism showed significantly high productivity for 305 days of lactation in animals with the homozygous TG5\ensuremath{^{ТТ}}\ensuremath{^{}}genotype, where the difference in relation to animals with the heterozygous TG5\ensuremath{^{ТС}} genotype was 1833.75 kg (p{\textless}0.05). Cows with the homozygous genotype by the T allele are superior to heterozygous individuals by fat content in milk by 0.36\% (p{\textless}0.05), as well as by milk fat yield by 99.6 kg and protein yield by 41.8 kg (p{\textless}0.05). Animals with the TG5\ensuremath{^{CC}} genotype showed good results in milk protein content in relation to cows with the TG5\ensuremath{^{TT}} genotype, the difference was 0.18\% (p{\textless}0.05).

The highest milk yield in respect of the kappa-casein gene was achieved in cows with the heterozygous CSN3\ensuremath{^{AB}} genotype. The milk yield of cows of this group averaged 6897.4 kg, the productivity of cows with the homozygous CSN3\ensuremath{^{AA}} genotype averaged 6303.8 kg, and with CSN3\ensuremath{^{{{B}}{{B}}}} {\textendash} 6536 kg. Cows with the CSN3\ensuremath{^{AA}} and CSN3\ensuremath{^{AB}} genotype had 2.9\% of protein and the protein content of cows with the CSN3\ensuremath{^{{{B}}{{B}}}} genotype fell, on average, 0.22\%, constituting 2.68\%. At the highest rates of milk yield, cows with the CSN3\ensuremath{^{AB}} genotype were superior to animals with the CSN3\ensuremath{^{AA}} genotype on the fat content in milk by 0.16\% (p{\textless}0.05). Cows with the LGB\ensuremath{^{BB}} genotype at the highest level of milk productivity had the best milk quality indicators and, accordingly, were characterized by higher protein milkiness, which averaged 2.98\%. Cows with the LGB\ensuremath{^{AA}} genotype with the lowest rates of milk yield, respectively, had the lowest protein yield, which averaged 186.5 kg. This is 5.5\% (p{\textless}0.05) less than the highest rate compared to cows with the LGB\ensuremath{^{BB}} genotype.

At mutual settlements between milk producers and milk processing plants, the actual quantity of milk is recalculated to determine the basic fat content {\textendash} the constant-coefficient on which all accounting on the reception workshop is based. The all-Russian basic fat content is 3.4\%. In the calculations, we obtained the following data (Table~\ref{tw-c23f54bbd2b1}). Individuals with the heterozygous LEP\ensuremath{^{CT}} genotype have an advantage, which the standard weight of milk is higher than the actual one by 17.6\%, with the homozygous TG5\ensuremath{^{TT}} genotype {\textendash} by 24.1\%; with CSN3\ensuremath{^{AB }}and LGB\ensuremath{^{BB}} genotypes {\textendash} by 19.4\%. Thus, the higher the actual fat content in milk than the basic fat content, the higher the standard weight of milk will be at the time of its delivery to the milk processing plants and, therefore, the amount earned for the sale of milk will increase. 
    
\section{Conclusion }
Analysis of polymorphism of candidate genes for dairy productivity of leptin, thyroglobulin, kappa-casein and beta-lactoglobulin showed that the most common genotypes are LEP\ensuremath{^{CT}} {\textendash} 62\%, TG5\ensuremath{^{CC}} {\textendash} 48\%, CSN3\ensuremath{^{AA}} {\textendash} 66\%, LGB\ensuremath{^{AB }} {\textendash} 50\%. When studying the relationship of polymorphic variants of these genes, it was found that animals with LEP\ensuremath{^{CT}}, TG5\ensuremath{^{TT}}, CSN3\ensuremath{^{AB}}, LGB\ensuremath{^{BB}} genotypes have the best indicators of milk productivity. Furthermore, individuals with these genotypes will lead to the enhancement of the economic efficiency of milk productivity by 17.6\% - 24.1\%. This requires the further accumulation of desirable genotypes in the herds of animal carriers.
\section*{Acknowledgement}This research was supported by the FASO Russia project AAAA-A18-118031390148-1.
    

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