**Use of the Bovine Prolactin Gene (***bPRL***) for Estimating Genetic Variation and Milk Production in Aboriginal Russian Breeds of** *Bos taurus* **L.**

I.V. Lazebnaya, O.E. Lazebny, S.R. Khatami and G.E. Sulimova

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54756

#### **1. Introduction**

34 Prolactin

40(1):57-60.

[45] Girolomoni G, Phillips JT, Bergstresser PR. Prolactin Stimulates Proliferation of Cultured Human Keratinocytes. Journal of Investigative Dermatology 1993; 101(3):275-279. [46] Crepin A, Bidaux G, Vanden-Abeele F, Dewailly E, Goffin V, Prevarskaya N, et al. Prolactin Stimulates Prostate Cell Proliferation by Increasing Endoplasmic Reticulum

[48] Kiya T, Endo T, Goto T, Yamamoto H, Ito E, Kudo R, et al. Apoptosis and Pcna Expression Induced by Prolactin in Structural Involution of the Rat Corpus Luteum.

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[53] Bogazzi F, Russo D, Raggi F, Ultimieri F, Urbani C, Gasperi M, et al. Transgenic Mice Overexpressing Growth Hormone (Gh) Have Reduced or Increased Cardiac Apoptosis hrough Activation of Multiple Gh-Dependent or -Independent Cell Death Pathways.

[54] Shepherd BS, Sakamoto T, Nishioka RS, Richman NH, 3rd, Mori I, Madsen SS, et al. Somatotropic Actions of the Homologous Growth Hormone and Prolactins in the Euryhaline Teleost, the Tilapia, *Oreochromis Mossambicus*. Proc Natl Acad Sci U S A

[55] Huang X, Jiao B, Fung CK, Zhang Y, Ho WK, Chan CB, et al. The Presence of Two Distinct Prolactin Receptors in Seabream with Different Tissue Distribution Patterns, Signal Transduction Pathways and Regulation of Gene Expression by Steroid

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Prolactin is a protein hormone mainly, but not exclusively produced by lactotroph cells of the anterior pituitary. Its role in lactogenesis and galactopoiesis (maintenance of milk secretion) is well demonstrated [1, 2]. Therefore, the gene encoding it (*PRL*) is considered to be one of the key links in the gene network constituting the hereditary component of milk productivity. Test systems for cattle breeding have been developed based on the associations of the *PRL* gene polymorphism with milk yield and quality.

Inbreeding, which decreases the genetic variation and viability of animals, is a well-known negative consequence of artificial selection. Its impact is further aggravated by the recent trend towards globalization of some cattle breeds [3]. Therefore, conservation of aboriginal breeds adapted to local conditions (which are not infrequently extreme) is necessary in countries with wide zonal climatic variations.

This is especially important when a breed in question has pronounced adaptive characteristics and its population is small. Yakut cattle represent one of such breeds (Figure 1a); it is unique among Russian breeds in terms of ecological plasticity. These cattle live in the northernmost part of the *Bos taurus* species range, a hardly accessible region of the subarctic zone of the Republic of Sakha (Yakutia), Russia, surrounded with mountain ridges. The morphological and physiological characteristics of Yakut cattle and their biochemical and behavioral adaptations allow free grazing almost round the year despite a severe continental climate, with the mean air temperatures usually varying from –43°C in winter to +25°C in summer (the lowest and highest temperatures on record are –65°C and +38°C,

© 2013 Lazebnaya et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

respectively). These animals can live on rough foods. Their body, including the udder, is covered with long, thick hair protecting them from cold and gnats. The color of aboriginal Yakut cattle varies from black and red to a leopard pattern with white spots on the head and lower trunk. This breed is exceptionally resistant to tuberculosis, leukemia, and brucellosis. Yakut cattle are small, with the shoulder height shorter than 1 m and the live weights of bulls and cows of 500–550 and 350–400 kg, respectively. The milk yield is low (2100–2350 kg in the breeding stock), but the fat content of milk is as high as 7.3% [4]. Yakut cattle have long been providing local residents (mostly Yakuts) with beef and dairy products. Cattle leather is widely used in Yakut ethnic handicrafts; Yakuts traditionally make comfortable, durable, beautiful leather clothes. Excavations in the Olekminsk district of Yakutia have revealed remnants of nomad camps containing fossil bones of domestic cattle, which suggests an ancient origin of this breed [5].

Use of the Bovine Prolactin Gene (*bPRL*)for Estimating Genetic Variation and

problem. Therefore, analysis of the variation of the gene markers that are affected by artificial selection because of their associations with milk yield and composition would be

The bovine prolactin gene (*bPRL*) is traditionally regarded as a good candidate gene for marker-assisted selection (MAS) [7] for milk production parameters, because it has been located to chromosome 23 at 43 cM, close to the quantitative trait loci (QTLs) (36, 41, and 42 cM) [8-11]. In addition, it is known that the binding of the *bPRL* gene product with its receptor (PRLR) initiates a signaling cascade that activates the transcription of a number of

genes, including the genes of milk proteins (caseins and lactalbumin).

**Figure 1.** (a) Yakut, (b) Bestuzhev, (c) Kostroma, and (d) Yaroslavl cattle breeds [12, 13, 14, 15].

and four introns) [17] and a common positive transcription factor (PITI) [18].

Note that this regulatory cascade involves growth hormone (Figure 2), because it is recognized not only by its own receptor (GHR), but also by PRLR [16]. The prolactin and growth hormone genes are very similar to each other, because they have resulted from duplication of a common ancestral gene. They have the same general structure (five exons

The specifics of the *bPRL* and *bGH* genes suggest their combined effect on milk production; however, this has been paid little attention until now. Most studies on the polymorphism of milk production genes deal with isolated effects of individual genes. Many data on the polymorphisms of both *bPRL* and *bGH* genes and their relationship with the milk yield and composition have been accumulated. For example, a synonymous A–G transition has been found in the codon of amino acid residue 103 of bPRL in the third exon of its gene; this

useful for breed monitoring.

Milk Production in Aboriginal Russian Breeds of *Bos taurus* L. 37

Bestuzhev and Kostroma cattle are dual-purpose breeds. Bestuzhev cattle selected for both beef and milk production were bred from local cattle in Samara province, Russia, in the late 18th century (Figure 1b). English Shorthorn cattle were used for its improvement, the offspring being crossed with the Holland, Shorthorn, Simmental, and some other breeds. The breed was completely formed by the mid-19th century. Bestuzhev cattle are well adapted to the continental climate of the Volga basin. The animals are red; the color intensity varies from light-red to dark-red or cherry-red. Some animals have white spots, mostly on the lower trunk, udder, and head. The mean milk yield of Bestuzhev cattle is 5502–8250 kg; the mean fat content of milk is 3.82–4.0% (the maximum content is 5.5%) [4]. Bestuzhev cattle are especially valuable because they are almost free of hereditary diseases and abnormalities and are resistant to tuberculosis and leukemia.

Kostroma cattle are classified with the group of brown cattle (Figure 1c). The breed was registered in 1944. These cattle are characterized by a high growing capacity, strong constitution, and steady inheritance of commercially valuable traits, including a good milk quality. The Kostroma breed is regarded as one of the most productive dual-purpose breeds. The live weights of Kostroma bulls and cows are 800–900 and 550–650 kg, respectively; the fat and protein contents of milk are as high as 3.9 and 3.6%, respectively. The milk yield varies from 6000–8000 to 10,500 kg [4]. The Kostroma breed is characterized by a high total frequency of the *BoLA–DRB3* gene alleles determining the leukemia resistance (on average, 35.9%) [6].

Yaroslavl cattle, formed as a native cattle breed in the 16th century, have the highest milk yield and the best milk composition among all native Russian breeds (Figure 1d). Their milk contains, on average, 4.37% of fat (maximum content, 5.0%) and 3.4–3.6% of protein; the dry matter content is 13.6% (compared to 12.3–12.5% in other breeds) [4]. Yaroslavl cattle are usually black, except the white head with a black mask around the eyes and the white lower trunk. Yaroslavl cattle were first mentioned in the literature in the mid-19th century. Bestuzhev cattle were named after the original breeder; Yaroslavl, Yakut, and Kostroma cattle, after the region of origin.

The balance between the increase in the milk yield and quality of cattle breeds and preservation of diversity both within and between breeds of *B. taurus* is a complicated problem. Therefore, analysis of the variation of the gene markers that are affected by artificial selection because of their associations with milk yield and composition would be useful for breed monitoring.

36 Prolactin

35.9%) [6].

cattle, after the region of origin.

suggests an ancient origin of this breed [5].

and abnormalities and are resistant to tuberculosis and leukemia.

respectively). These animals can live on rough foods. Their body, including the udder, is covered with long, thick hair protecting them from cold and gnats. The color of aboriginal Yakut cattle varies from black and red to a leopard pattern with white spots on the head and lower trunk. This breed is exceptionally resistant to tuberculosis, leukemia, and brucellosis. Yakut cattle are small, with the shoulder height shorter than 1 m and the live weights of bulls and cows of 500–550 and 350–400 kg, respectively. The milk yield is low (2100–2350 kg in the breeding stock), but the fat content of milk is as high as 7.3% [4]. Yakut cattle have long been providing local residents (mostly Yakuts) with beef and dairy products. Cattle leather is widely used in Yakut ethnic handicrafts; Yakuts traditionally make comfortable, durable, beautiful leather clothes. Excavations in the Olekminsk district of Yakutia have revealed remnants of nomad camps containing fossil bones of domestic cattle, which

Bestuzhev and Kostroma cattle are dual-purpose breeds. Bestuzhev cattle selected for both beef and milk production were bred from local cattle in Samara province, Russia, in the late 18th century (Figure 1b). English Shorthorn cattle were used for its improvement, the offspring being crossed with the Holland, Shorthorn, Simmental, and some other breeds. The breed was completely formed by the mid-19th century. Bestuzhev cattle are well adapted to the continental climate of the Volga basin. The animals are red; the color intensity varies from light-red to dark-red or cherry-red. Some animals have white spots, mostly on the lower trunk, udder, and head. The mean milk yield of Bestuzhev cattle is 5502–8250 kg; the mean fat content of milk is 3.82–4.0% (the maximum content is 5.5%) [4]. Bestuzhev cattle are especially valuable because they are almost free of hereditary diseases

Kostroma cattle are classified with the group of brown cattle (Figure 1c). The breed was registered in 1944. These cattle are characterized by a high growing capacity, strong constitution, and steady inheritance of commercially valuable traits, including a good milk quality. The Kostroma breed is regarded as one of the most productive dual-purpose breeds. The live weights of Kostroma bulls and cows are 800–900 and 550–650 kg, respectively; the fat and protein contents of milk are as high as 3.9 and 3.6%, respectively. The milk yield varies from 6000–8000 to 10,500 kg [4]. The Kostroma breed is characterized by a high total frequency of the *BoLA–DRB3* gene alleles determining the leukemia resistance (on average,

Yaroslavl cattle, formed as a native cattle breed in the 16th century, have the highest milk yield and the best milk composition among all native Russian breeds (Figure 1d). Their milk contains, on average, 4.37% of fat (maximum content, 5.0%) and 3.4–3.6% of protein; the dry matter content is 13.6% (compared to 12.3–12.5% in other breeds) [4]. Yaroslavl cattle are usually black, except the white head with a black mask around the eyes and the white lower trunk. Yaroslavl cattle were first mentioned in the literature in the mid-19th century. Bestuzhev cattle were named after the original breeder; Yaroslavl, Yakut, and Kostroma

The balance between the increase in the milk yield and quality of cattle breeds and preservation of diversity both within and between breeds of *B. taurus* is a complicated The bovine prolactin gene (*bPRL*) is traditionally regarded as a good candidate gene for marker-assisted selection (MAS) [7] for milk production parameters, because it has been located to chromosome 23 at 43 cM, close to the quantitative trait loci (QTLs) (36, 41, and 42 cM) [8-11]. In addition, it is known that the binding of the *bPRL* gene product with its receptor (PRLR) initiates a signaling cascade that activates the transcription of a number of genes, including the genes of milk proteins (caseins and lactalbumin).

**Figure 1.** (a) Yakut, (b) Bestuzhev, (c) Kostroma, and (d) Yaroslavl cattle breeds [12, 13, 14, 15].

Note that this regulatory cascade involves growth hormone (Figure 2), because it is recognized not only by its own receptor (GHR), but also by PRLR [16]. The prolactin and growth hormone genes are very similar to each other, because they have resulted from duplication of a common ancestral gene. They have the same general structure (five exons and four introns) [17] and a common positive transcription factor (PITI) [18].

The specifics of the *bPRL* and *bGH* genes suggest their combined effect on milk production; however, this has been paid little attention until now. Most studies on the polymorphism of milk production genes deal with isolated effects of individual genes. Many data on the polymorphisms of both *bPRL* and *bGH* genes and their relationship with the milk yield and composition have been accumulated. For example, a synonymous A–G transition has been found in the codon of amino acid residue 103 of bPRL in the third exon of its gene; this mutation results in an *Rsa*I polymorphic site [19]. The *AA* and *AB* genotypes have been shown to be associated with the milk yield and protein content in Polish Black & White, Holstein Friesian, and Brown Swiss cattle [19-21]. Other associations have been found in Russian Red Pied cattle [22]. The C–G transversion in the third exon of the *bGH* gene (nucleotide position 2141) is known to be related to milk production traits. This SNP entails the disappearance of an *Alu*I restriction site and the substitution of valine for leucine (Leu → Val) at position 127 of the bGH amino acid sequence. There is evidence for a stronger dependence of the milk yield on the *LL* genotype than the *LV* genotype in Black Pied and Holstein Friesian cattle [23, 24]. However, Mitra *et al.* [25] and Dybus *et al*. [20] note a positive dependence of the milk yield and both fat and protein contents on the *V* allele in Holstein and Polish Black & White cattle. Study of the combined effect of the *bPRL* and *bGH* genes might explain some contradictions about the associations of individual markers of these genes. Although associations of the *bPRL*(*Rsa*I) and *bGH*(*Alu*I) polymorphisms with milk yield and quality have been extensively studied, the combined effect of SNPs of these genes has been hardly considered at all.

Use of the Bovine Prolactin Gene (*bPRL*)for Estimating Genetic Variation and

breeds (literature data) with respect to genetic variation as estimated from the *Rsa*I polymorphism of the prolactin gene. Second, we estimated the effect of the *Rsa*I polymorphism of the *bPRL* gene, as well as the effect of its combination with the *Alu*I

We used PCR–RFLP analysis to study the *Rsa*I polymorphism of the *bPRL* gene in Yakut cattle (*n* = 41) in the Republic of Sakha (Yakutia), Bestuzhev cattle (*n* = 57) in Samara region, Kostroma cattle (*n* =124) in Kostroma region, and Yaroslavl cattle (*n* = 113) in Yaroslavl region of Russia. The possible effects of the *bPRL*(*Rsa*I) polymorphism and its combination with the *bGH*(*Alu*I) polymorphism on milk production in Yaroslavl cattle were estimated.

DNA was isolated from 200-μl samples of whole blood using a DiatomTM DNA Prep kit (IsoGeneLab., Russia). Fragments of *bPRL* (156 bp) and *bGH* (223 bp) [25] were amplified in a Tertsik thermal cycler by the standard methods using a GenePakTMPCR Core kit (IsoGene Lab., Russia). The DNA digestion with the *Rsa*I and *Alu*I restriction endonucleases was performed as recommended by the manufacturer (MBI Fermentas, Lithuania). The oligonucleotides F*PRL* (5'-CGAGTCCTTATGAGCTTGATTCTT-3') and R*PRL* (5'- GCCTTCCAGAAGTCGTTTGTTTTC-3') served as primers for the *bPRL* gene fragments; F*GH* (5'-GCTGCTCCTGAGGGCCCTTCG-3') and R*GH* (5'-GCGGCGGCACTTCATGACCCT-3'), for the *bGH* gene fragments. The following amplification profiles were used: for the *bPRL* gene fragments, one cycle of 94°C for 4 min; 35 cycles of 94°C for 30 s, 58°C for 30 s, and 72°C for 30 s; and one cycle of 72°C for 10 min; for the *bGH* gene fragments, one cycle of 94°C for 4 min; 35 cycles of 94°C for 45 s, 67°C for 45 s, and 72°C for 45 s; and one cycle of 72°C for 10 min. The amplification products were detected by means of 2% agarose gel electrophoresis (0.5 μg/ml ethidium bromide in 1X TBE buffer). The restriction products were visualized in 2% agarose gel (the *bGH* gene) or 6% polyacrylamide gel (the *bPRL* gene) (0.5 μg/ml ethidium bromide in 1X TBE buffer). The results of electrophoresis were recorded by means of a UVT-1 transilluminator (312 nm) and a ViTran-1 photodocumentation system (Biokom, Russia). The alleles were identified as follows: *Rsa*I(–) and *Rsa*I(+) corresponded to the *A* and *B* alleles of the *bPRL* gene, respectively; *Alu*I(–) and *Alu*I(+), to the *V* and *L* alleles

The PopGene [26] and STATISTICA 8.0 [25] software packages were used for statistical treatment of the results. Pairwise comparisons of the allele and heterozygote frequencies (observed heterozygosity, Hobs) in the group of breeds studied were performed using the Fisher exact test. For similar comparisons using published data on other Russian and foreign breeds, we additionally calculated the expected heterozygosity (Hexp) where its values were not presented. The G2 test was used for pairwise comparisons of the breeds with respect to the genotype frequencies and Hexp. The fit of the observed frequencies of heterozygous genotypes to those expected from the Hardy–Weinberg equilibrium was tested using the PopGene software. The dependence of the milk yield (in kilograms) and fat and protein contents (in percent) on the *bPRL* and *bGH* genotypes in Yaroslavl cattle was estimated by

one-way and two-way ANOVA with the use of the STATISTICA 8.0 software.

polymorphism of the *bGH* gene, on milk production in Yaroslavl cattle.

**2. Materials and methods** 

of the *bGH* gene, respectively.

Milk Production in Aboriginal Russian Breeds of *Bos taurus* L. 39

Top: an anterior pituitary cell. Chromosomes carrying the transcription factor (*Pit*-1), growth hormone (*GH*), and prolactin (*PRL*) genes are shown in the nucleus (a green oval). The product of *Pit*-1 (TF Pit-1) activates the transcription of the prolactin and growth hormone genes. The corresponding hormones (GH and PRL, shown in dark blue and light blue, respectively) enter the bloodstream and reach mammary cells, where they are recognized by transmembrane receptors (GHR and PRLR, respectively). This initiates regulatory cascades activating the transcription of the milk protein (β-casein and α-lactalbumin) genes. The prolactin and growth hormone receptors are shown in yellow and green, respectively. The growth hormone competes with prolactin for the prolactin receptor.

**Figure 2.** Schematic representation of the regulatory cascade involving the prolactin gene.

The goal of this study was twofold. First, we compared the Kostroma, Bestuzhev, Yakut, and Yaroslavl breeds both with one another and with some other Russian and foreign breeds (literature data) with respect to genetic variation as estimated from the *Rsa*I polymorphism of the prolactin gene. Second, we estimated the effect of the *Rsa*I polymorphism of the *bPRL* gene, as well as the effect of its combination with the *Alu*I polymorphism of the *bGH* gene, on milk production in Yaroslavl cattle.

#### **2. Materials and methods**

38 Prolactin

genes has been hardly considered at all.

mutation results in an *Rsa*I polymorphic site [19]. The *AA* and *AB* genotypes have been shown to be associated with the milk yield and protein content in Polish Black & White, Holstein Friesian, and Brown Swiss cattle [19-21]. Other associations have been found in Russian Red Pied cattle [22]. The C–G transversion in the third exon of the *bGH* gene (nucleotide position 2141) is known to be related to milk production traits. This SNP entails the disappearance of an *Alu*I restriction site and the substitution of valine for leucine (Leu → Val) at position 127 of the bGH amino acid sequence. There is evidence for a stronger dependence of the milk yield on the *LL* genotype than the *LV* genotype in Black Pied and Holstein Friesian cattle [23, 24]. However, Mitra *et al.* [25] and Dybus *et al*. [20] note a positive dependence of the milk yield and both fat and protein contents on the *V* allele in Holstein and Polish Black & White cattle. Study of the combined effect of the *bPRL* and *bGH* genes might explain some contradictions about the associations of individual markers of these genes. Although associations of the *bPRL*(*Rsa*I) and *bGH*(*Alu*I) polymorphisms with milk yield and quality have been extensively studied, the combined effect of SNPs of these

Top: an anterior pituitary cell. Chromosomes carrying the transcription factor (*Pit*-1), growth hormone (*GH*), and prolactin (*PRL*) genes are shown in the nucleus (a green oval). The product of *Pit*-1 (TF Pit-1) activates the transcription of the prolactin and growth hormone genes. The corresponding hormones (GH and PRL, shown in dark blue and light blue, respectively) enter the bloodstream and reach mammary cells, where they are recognized by transmembrane receptors (GHR and PRLR, respectively). This initiates regulatory cascades activating the transcription of the milk protein (β-casein and α-lactalbumin) genes. The prolactin and growth hormone receptors are shown in yellow and

The goal of this study was twofold. First, we compared the Kostroma, Bestuzhev, Yakut, and Yaroslavl breeds both with one another and with some other Russian and foreign

green, respectively. The growth hormone competes with prolactin for the prolactin receptor.

**Figure 2.** Schematic representation of the regulatory cascade involving the prolactin gene.

We used PCR–RFLP analysis to study the *Rsa*I polymorphism of the *bPRL* gene in Yakut cattle (*n* = 41) in the Republic of Sakha (Yakutia), Bestuzhev cattle (*n* = 57) in Samara region, Kostroma cattle (*n* =124) in Kostroma region, and Yaroslavl cattle (*n* = 113) in Yaroslavl region of Russia. The possible effects of the *bPRL*(*Rsa*I) polymorphism and its combination with the *bGH*(*Alu*I) polymorphism on milk production in Yaroslavl cattle were estimated.

DNA was isolated from 200-μl samples of whole blood using a DiatomTM DNA Prep kit (IsoGeneLab., Russia). Fragments of *bPRL* (156 bp) and *bGH* (223 bp) [25] were amplified in a Tertsik thermal cycler by the standard methods using a GenePakTMPCR Core kit (IsoGene Lab., Russia). The DNA digestion with the *Rsa*I and *Alu*I restriction endonucleases was performed as recommended by the manufacturer (MBI Fermentas, Lithuania). The oligonucleotides F*PRL* (5'-CGAGTCCTTATGAGCTTGATTCTT-3') and R*PRL* (5'- GCCTTCCAGAAGTCGTTTGTTTTC-3') served as primers for the *bPRL* gene fragments; F*GH* (5'-GCTGCTCCTGAGGGCCCTTCG-3') and R*GH* (5'-GCGGCGGCACTTCATGACCCT-3'), for the *bGH* gene fragments. The following amplification profiles were used: for the *bPRL* gene fragments, one cycle of 94°C for 4 min; 35 cycles of 94°C for 30 s, 58°C for 30 s, and 72°C for 30 s; and one cycle of 72°C for 10 min; for the *bGH* gene fragments, one cycle of 94°C for 4 min; 35 cycles of 94°C for 45 s, 67°C for 45 s, and 72°C for 45 s; and one cycle of 72°C for 10 min. The amplification products were detected by means of 2% agarose gel electrophoresis (0.5 μg/ml ethidium bromide in 1X TBE buffer). The restriction products were visualized in 2% agarose gel (the *bGH* gene) or 6% polyacrylamide gel (the *bPRL* gene) (0.5 μg/ml ethidium bromide in 1X TBE buffer). The results of electrophoresis were recorded by means of a UVT-1 transilluminator (312 nm) and a ViTran-1 photodocumentation system (Biokom, Russia). The alleles were identified as follows: *Rsa*I(–) and *Rsa*I(+) corresponded to the *A* and *B* alleles of the *bPRL* gene, respectively; *Alu*I(–) and *Alu*I(+), to the *V* and *L* alleles of the *bGH* gene, respectively.

The PopGene [26] and STATISTICA 8.0 [25] software packages were used for statistical treatment of the results. Pairwise comparisons of the allele and heterozygote frequencies (observed heterozygosity, Hobs) in the group of breeds studied were performed using the Fisher exact test. For similar comparisons using published data on other Russian and foreign breeds, we additionally calculated the expected heterozygosity (Hexp) where its values were not presented. The G2 test was used for pairwise comparisons of the breeds with respect to the genotype frequencies and Hexp. The fit of the observed frequencies of heterozygous genotypes to those expected from the Hardy–Weinberg equilibrium was tested using the PopGene software. The dependence of the milk yield (in kilograms) and fat and protein contents (in percent) on the *bPRL* and *bGH* genotypes in Yaroslavl cattle was estimated by one-way and two-way ANOVA with the use of the STATISTICA 8.0 software.
