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A novel single nucleotide polymorphism in the coding region of goat growth hormone receptor gene and its association with lactose content and somatic cell count in milk
Small Ruminant Research 90 (2010) 139–141
Contents lists available at ScienceDirect
Small Ruminant Research journal homepage: www.elsevier.com/locate/smallrumres
Short communication
A novel single nucleotide polymorphism in the coding region of goat growth hormone receptor gene and its association with lactose content and somatic cell count in milk Andrzej Maj a , Emilia Bagnicka a,∗ , Jarosław Kaba b , Mariusz Nowicki b , Ewa Ko´sciuczuk a , a ´ , Lech Zwierzchowski a Krzysztof Słoniewski a , Karina Horbanczuk a
Institute of Genetics and Animal Breeding, Polish Academy of Sciences, Jastrz˛ebiec, 05-552 Wólka Kosowska, Poland Division of Infectious Diseases and Epidemiology, Department of Clinical Sciences Faculty of Veterinary Medicine, Warsaw Agricultural University, Nowoursynowska 159C, Warsaw, Poland
b
a r t i c l e
i n f o
Article history: Received 24 August 2009 Received in revised form 8 December 2009 Accepted 10 December 2009 Available online 12 January 2010 Keywords: Growth hormone receptor Gene polymorphism Association Milk traits Goat
a b s t r a c t A novel single nucleotide polymorphism—a C/T transition (RFPL-MspI) was found upon sequencing of a 439 bp DNA fragment, comprising whole exon 4 and parts of adjacent introns of the goat growth hormone receptor gene. This mutation was located at 8th nucleotide of exon 4 (position 94 according to GenBank Acc. No. AY739707). The nucleotide substitution has no effect on the amino acid sequence of the GHR protein. Within the cohort of 227 Polish dairy goats three genotypes were found: CC (frequency 0.96), CT (0.036), and TT (0.004). The frequency of C and T alleles was 0.978 and 0.022, respectively. It was shown that CC genotype goats had significantly higher lactose content and lower somatic cell count than those with the CT genotype. No association was found with the other milk production traits studied. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Hormones, growth factors, and other regulatory proteins associated with the so-called “somatotropic axis” are candidate markers for quantitative traits in farm animals (Parmentier et al., 1999). The biological effects of growth hormone (GH) concern a variety of tissues and the metabolism of all nutrient classes. In farm ruminants, the GH actions play a key role in increasing growth performance and milk yield (Etherton and Bauman, 1998). Therefore, there is a great interest in using growth hormone to improve the production in farm animals. Growth hormone’s actions on target cells depend on GH receptor (GHR) (Burton et al., 1994). The GHR is a member
of the cytokine/hematopoietin superfamily of receptors. In most mammalian species the gene encoding GHR consists of nine exons (from 2 to 10) in the translated part. In all species studied so far, GHR gene characterizes a complex structure of exon 1, coding for the 5 -untraslated region (5 -UTR) (Jiang and Lucy, 2001). It has been reported that some productive traits of cattle, e.g. milk yield and composition, are associated with the GHR gene polymorphism (Aggrey et al., 1999; Blott et al., 2003; Maj et al., 2004). The objective of this study was to search for nucleotide sequence polymorphism in exon 4 of the goat GHR gene and for its possible association with milk production traits. 2. Materials and methods
∗ Corresponding author at: Institute of Genetics and Animal Breeding, Polish Academy of Sciences, Department of Animal Science, Postepu 1, ˛ Jastrzebiec, 05-552 Wólka Kosowska, Poland. Tel.: +48 22 756 17 11; fax: +48 22 756 16 99. E-mail address: [email protected] (E. Bagnicka). 0921-4488/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.smallrumres.2009.12.006
2.1. Animals Studies were conducted on 227 dairy goats—156 Polish White Improved (PWI) and 71 Polish Fawn Improved (PFI) goats maintained in three dairy herds. The mean productive values were as follows: daily milk yield: 2.36 kg, fat: 3.37%, and protein: 3.28%. The goats were kept in loose
140
A. Maj et al. / Small Ruminant Research 90 (2010) 139–141
barns with outside run (except winter). During the test period the animals were fed according to the INRA system (Jarrige, 1988). Water was available ad libitum. 2.2. Genotype determination Blood samples were collected from the jugular vein to the tubes containing K3 EDTA. DNA for GHR gene sequencing and genotyping was isolated from blood by the method of Kanai et al. (1994). The 439 bp DNA fragment, comprising 113 bp of intron 3, whole 130-bp of exon 4, and 196 bp of intron 4, was amplified using the following primers: forward—GCCCA-GAGAAACAGCATTTCTA and reverse—TCACTGCCATATTTCCAGCATC. Polymerase chain reactions and DNA sequencing were performed as previously described (Maj and Zwierzchowski, 2006). For restriction fragment length polymorphism (RFLP) analyses the amplified DNA was digested with MspI endonuclease. Restriction products were separated by electrophoresis in 2% agarose (Gibco-BRL, England) in 1× TBE buffer (0.09 M Tris-boric acid, 0.002 M EDTA) with 0.5 g/ml ethidium bromide (Et-Br), visualized under UV light, and scanned in an FX Phosphorimager apparatus (Bio-Rad, Hercules, CA, USA). 2.3. Analysis of milk composition The experiment lasted during 6 successive lactations. The goats were milked twice a day. Milk samples were taken from each goat once a month during the whole lactation period (270 days in average). The daily milk yield (kg) and content of the major milk components (%): fat, protein and lactose, and also somatic cell count (SCC) were evaluated in each milk sample. The fat, protein and lactose content were estimated in the milk preserved with Broad Spectrum Microtabs II (Bentley, Poland), using Milko Scan 104A/B (FOSS A/S, Hillerød, Denmark). Somatic cells were counted by means of a Fossomatic apparatus (FOSS A/S). Somatic cell count and lactose concentration in milk were used as indicators of the health status of the udder. 2.4. Statistical calculations Altogether 2905 records about milk yield, fat and protein content and 1181 records about lactose content and SCC, from 180 does were used in statistical analyses. The SCC values (expressed in thousands) were transformed to the natural logarithm scale (ln of SCC). In order to determine associations between the GHR gene polymorphism and the investigated traits the multi-trait repeatability test-day model was used. The DMU program was used for computation (Madsen and Jansen, 2000). The model included the animal’s genotype, breed, year of birth, herd-year-season of kidding and parity as fixed effects and the additive genetic effect, permanent environmental influence and the date of the test as random effects. Legendre polynomials nested within parity were applied taking into account of stage of lactation effects (Brotherstone et al., 2000). The differences between solutions for genotypes were checked using Student’s t-test with Bonferroni adjustment. The significance of the differences between observed and expected genotype frequencies was estimated using 2 test.
3. Results and discussion In this study a 439 bp DNA fragment was sequenced, comprising whole exon 4 and parts of adjacent introns of the goat growth hormone (GHR) gene to search for nucleotide sequence polymorphisms. Sequencing DNA samples from 36 goats revealed one single nucleotide polymorphism—a C/T transition at 8th nucleotide of exon 4 (position 94 according to GenBank Acc. No. AY739707). Since the whole sequence of the goat GHR gene is not known the PCR primers were used, designed previously by Blott et al. (2003) for the amplification of the corresponding fragment of the bovine GHR gene. In the bovine gene they match sequences between nucleotides 1594 and 1615 (forward primer) and 2011 and 2032 (reverse) (Gen-
Fig. 1. Agarose gel electrophoresis showing RFLP-MspI genotyping of C/T single nucleotide polymorphism in the goat GHR gene exon 4: M—100–1000 bp DNA marker (Sigma); ND—non-digested 439 bp PCR product; CC, CT, TT—GHR genotypes. Digestion of the 439 bp PCR product with MspI restriction endonuclease resulted in two DNA bands (318 and 121 bp) for homozygote CC, three bands (439, 318 and 121 bp) for the CT heterozygote, and one band (439 bp) for homozygous TT genotype animals.
Bank AM161140.1). With the caprine DNA as a template they gave a good quality PCR product of the expected length of 439 bp (Fig. 1). Known is the complete mRNA sequence (cds) of the goat GHR-exons 2–10 (GenBank Acc. No. EF559245). This allowed us to localise the C/T mutation at mRNA position 437. The nucleotide substitution has no effect on the amino acid sequence of the GHR protein; both triplets—TCC and TCT encode serine. As the C → T mutation removes the MspI restriction site, the polymorphism could be identified using RFLP techniques. After digestion with the MspI endonuclease three genotypes were identified: homozygotes either digested (CC) or non-digested (TT) by MspI, and CT heterozygotes (Fig. 1). The genotype frequencies were as follows: CC = 0.96, CT = 0.036, TT = 0.004 (one animal only among 227 genotyped). The frequency of C and T alleles was 0.978 and 0.022, respectively. The distribution of genotypes followed the Hardy–Weinberg rule. Maj and Zwierzchowski (2006) searched for sequence variation in the GHR gene in different ruminant species—Bovidae and Caprine. Only two differences were found in 130 bp long exon 4 sequence of GHR gene between bovine (Bos indicus) vs. (Capra hircus): T → C at position 8 and C → T at position 16. Associations were studied of the GHR polymorphism with the goat’s milk traits. The mean values and standard deviations of the investigated traits and the effects of GHR genotypes are shown in Table 1. The animal carrying the TT genotype was not included in the statistical analysis. No associations were found between the C/T polymorphism in GHR gene exon 4 and the milk yield and fat and protein content. But there were differences found (p ≤ 0.01) between goat GHR genotypes as concerns lactose content and somatic cell count (SCC) in the milk. The CC goats had a higher lactose content and lower SCC than those with the CT genotype. Both lactose content and SCC in milk are the indicators of health status of the goat’s mammary gland (Lerondelle et al., 1992; Leitner et al., 2004).
A. Maj et al. / Small Ruminant Research 90 (2010) 139–141
141
Table 1 Means and standard deviations of investigated traits and estimates for, genotypes effects with their standard errors (SE). Trait
Overall Mean
Milk yield [kg] Fat [%] Protein [%] Trait
2.36 3.37 3.28
Genotype SD
1.03 1.13 0.85
Overall Mean
CC
CT
Estimate (N = 2821a )
SE
Estimate (N = 83a )
SE
2.41 3.07 3.44
0.21 0.23 0.15
2.42 3.12 3.34
0.27 0.26 0.18
Genotype SD
CC
CT
Estimate (N = 1129a ) Lactose [%] SCC [ln] a
4.38 6.81
0.34 1.25
A
4.21 7.06A
SE 0.08 0.25
Estimate (N = 44a ) B
4.08 7.62B
SE 0.11 0.38
Number of milk samples analysed; the different letters within rows indicate differences at A—p ≤ 0.01.
There is very little information about polymorphism of the goat GHR gene and its association with production traits. The possible effects of the TG-repeat variants in the goat GHR gene 5 -noncoding region were studied with milk production traits but no association was found (Maj et al., 2007). More studies were conducted on the polymorphism of the bovine GHR gene. Association was established between A/T polymorphism in the GHR gene exon 8 (position 914, according to GenBank AY748827), which resulted in amino acid substitution Phe279Tyr in the transmembrane domain of the receptor, and milk, fat and protein yield and fat and protein content in milk of Holstein-Friesian cows (Blott et al., 2003). Effects of two SNPs (RFLP-NsiI and -AccI) and their combination were shown on milk production traits of Holstein-Friesian cows (Maj et al., 2004). Moreover, the A257G polymorphism was found in the GHR gene exon 10 which was connected with milk fat and protein yield ´ (Kaminski et al., 2006). 4. Conclusion This study presents a novel polymorphism of the caprine GHR gene—the C/T transition in exon 4. An association was found between the GHR genetic polymorphism and lactose concentration and somatic cell count in goat’s milk, the traits which are highly related to udder health. Therefore, we suggest the potential use of C/T polymorphism in exon 4 of the GHR as a genetic marker of goat’s resistance/susceptibility to mastitis. However, to prove this, further study must be done with more numerous animal cohorts, including more animals representing the homozygous genotype TT. Acknowledgement This study was supported by IGAB grant S.V.3. References Aggrey, S.E., Yao, J., Sabour, M.P., Lin, C.Y., Zadworny, D., Hayes, J.F., Kunlein, U., 1999. Markers within the regulatory region of the growth
hormone receptor gene and their association with milk-related traits in Holsteins. J. Hered. 90, 148–151. Blott, S., Kim, J.J., Moisio, S., Schmidt-Kuntzel, A., Cornet, A., Berzi, P., Cambisano, N., Ford, C., Grisart, B., Johnson, D., Karim, L., Simon, P., Snell, R., Spelman, R., Wong, J., Vilkki, J., Georges, M., Farnir, F., Coppieters, W., 2003. Molecular dissection of a Quantitative Trait Locus. A phenylalanine-to-tyrosine substitution in the transmembrane domain of the bovine growth hormone receptor is associated with a major effect on milk yield and composition. Genetics 163, 253–266. Burton, J.L., McBride, B.W., Block, E., Glimm, D.R., Kenelly, J.J., 1994. A review of bovine growth hormone. Can. J. Anim. Sci. 74, 167–201. Brotherstone, S., White, I.M.S., Meyer, K., 2000. Genetic modelling of daily milk yield using orthogonal polynomials and parametric curves. Anim. Sci. 70, 407–415. Etherton, T.D., Bauman, D.E., 1998. Biology of somatotropin in growth and lactation of domestic animals. Physiol. Rev. 78, 745–761. Jarrige, R. (Ed.), 1988. Alimentation des Bovins, Ovins & Caprins. INRA, Paris, 465 pp. Jiang, H., Lucy, M.C., 2001. Variants of the 5’-untranslated region of the bovine growth hormone receptor mRNA: isolation, expression and effects on translational efficiency. Gene 265, 45–53. ´ ´ A., Wójcik, E., Ahman, A., Mägi, R., 2006. Kaminski, S., Brym, P., Ru´sc, Associations between milk performance traits in Holstein cows and 16 candidate SNPs identified by arrayed primer extension (APEX) microarray. Anim. Biotechnol. 17, 1–11. Kanai, N., Fujii, T., Saito, K., Yokoyama, T., 1994. Rapid and simple method for preparation of genomic DNA from easily obtained clotted blood. J. Clin. Pathol. 47, 1043–1044. Leitner, G., Merin, U., Silanikove, N., 2004. Changes in milk composition as affected by subclinical mastitis in goats. J. Dairy Sci. 87, 1719– 1726. Lerondelle, C., Richard, Y., Issartial, J., 1992. Factors affecting somatic cell counts in goat milk. Small Rumin. Res. 8, 129–139. Madsen, P., Jansen, J., 2000. A User’s Guide to DMU. A Package for Analysing Multivariate Mixed Models. Version 6 Release 4. Maj, A., Korczak, M., Bagnicka, E., Zwierzchowski, L., Pierzchała, M., 2007. A TG-repeat polymorphism in the 5 -noncoding region of the goat growth hormone receptor gene and search for its association with milk production traits. Small Rumin. Res. 67, 279–284. ˙ ˛ Maj, A., Strzałkowska, N., Słoniewski, K., Krzyzewski, J., Oprzadek, J., Zwierzchowski, L., 2004. Single nucleotide polymorphism (SNP) in the 5 -noncoding region of the bovine growth hormone receptor gene and its association with dairy production traits in Polish Black-and-White cattle. Czech J. Anim. Sci. 49, 419–429. Maj, A., Zwierzchowski, L., 2006. Molecular evolution of coding and noncoding sequences of the growth hormone receptor (GHR) gene in the family bovidae. Folia Biologica (Kraków) 54, 31–36. Parmentier, I., Portetelle, D., Gengler, N., Prandi, A., Bertozzi, C., Vleurick, L., Gilson, R., Renaville, R., 1999. Candidate gene markers associated with somatotropic axis and milk selection. Domest. Anim. Endocrinol. 17, 139–148.
Contents lists available at ScienceDirect
Small Ruminant Research journal homepage: www.elsevier.com/locate/smallrumres
Short communication
A novel single nucleotide polymorphism in the coding region of goat growth hormone receptor gene and its association with lactose content and somatic cell count in milk Andrzej Maj a , Emilia Bagnicka a,∗ , Jarosław Kaba b , Mariusz Nowicki b , Ewa Ko´sciuczuk a , a ´ , Lech Zwierzchowski a Krzysztof Słoniewski a , Karina Horbanczuk a
Institute of Genetics and Animal Breeding, Polish Academy of Sciences, Jastrz˛ebiec, 05-552 Wólka Kosowska, Poland Division of Infectious Diseases and Epidemiology, Department of Clinical Sciences Faculty of Veterinary Medicine, Warsaw Agricultural University, Nowoursynowska 159C, Warsaw, Poland
b
a r t i c l e
i n f o
Article history: Received 24 August 2009 Received in revised form 8 December 2009 Accepted 10 December 2009 Available online 12 January 2010 Keywords: Growth hormone receptor Gene polymorphism Association Milk traits Goat
a b s t r a c t A novel single nucleotide polymorphism—a C/T transition (RFPL-MspI) was found upon sequencing of a 439 bp DNA fragment, comprising whole exon 4 and parts of adjacent introns of the goat growth hormone receptor gene. This mutation was located at 8th nucleotide of exon 4 (position 94 according to GenBank Acc. No. AY739707). The nucleotide substitution has no effect on the amino acid sequence of the GHR protein. Within the cohort of 227 Polish dairy goats three genotypes were found: CC (frequency 0.96), CT (0.036), and TT (0.004). The frequency of C and T alleles was 0.978 and 0.022, respectively. It was shown that CC genotype goats had significantly higher lactose content and lower somatic cell count than those with the CT genotype. No association was found with the other milk production traits studied. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Hormones, growth factors, and other regulatory proteins associated with the so-called “somatotropic axis” are candidate markers for quantitative traits in farm animals (Parmentier et al., 1999). The biological effects of growth hormone (GH) concern a variety of tissues and the metabolism of all nutrient classes. In farm ruminants, the GH actions play a key role in increasing growth performance and milk yield (Etherton and Bauman, 1998). Therefore, there is a great interest in using growth hormone to improve the production in farm animals. Growth hormone’s actions on target cells depend on GH receptor (GHR) (Burton et al., 1994). The GHR is a member
of the cytokine/hematopoietin superfamily of receptors. In most mammalian species the gene encoding GHR consists of nine exons (from 2 to 10) in the translated part. In all species studied so far, GHR gene characterizes a complex structure of exon 1, coding for the 5 -untraslated region (5 -UTR) (Jiang and Lucy, 2001). It has been reported that some productive traits of cattle, e.g. milk yield and composition, are associated with the GHR gene polymorphism (Aggrey et al., 1999; Blott et al., 2003; Maj et al., 2004). The objective of this study was to search for nucleotide sequence polymorphism in exon 4 of the goat GHR gene and for its possible association with milk production traits. 2. Materials and methods
∗ Corresponding author at: Institute of Genetics and Animal Breeding, Polish Academy of Sciences, Department of Animal Science, Postepu 1, ˛ Jastrzebiec, 05-552 Wólka Kosowska, Poland. Tel.: +48 22 756 17 11; fax: +48 22 756 16 99. E-mail address: [email protected] (E. Bagnicka). 0921-4488/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.smallrumres.2009.12.006
2.1. Animals Studies were conducted on 227 dairy goats—156 Polish White Improved (PWI) and 71 Polish Fawn Improved (PFI) goats maintained in three dairy herds. The mean productive values were as follows: daily milk yield: 2.36 kg, fat: 3.37%, and protein: 3.28%. The goats were kept in loose
140
A. Maj et al. / Small Ruminant Research 90 (2010) 139–141
barns with outside run (except winter). During the test period the animals were fed according to the INRA system (Jarrige, 1988). Water was available ad libitum. 2.2. Genotype determination Blood samples were collected from the jugular vein to the tubes containing K3 EDTA. DNA for GHR gene sequencing and genotyping was isolated from blood by the method of Kanai et al. (1994). The 439 bp DNA fragment, comprising 113 bp of intron 3, whole 130-bp of exon 4, and 196 bp of intron 4, was amplified using the following primers: forward—GCCCA-GAGAAACAGCATTTCTA and reverse—TCACTGCCATATTTCCAGCATC. Polymerase chain reactions and DNA sequencing were performed as previously described (Maj and Zwierzchowski, 2006). For restriction fragment length polymorphism (RFLP) analyses the amplified DNA was digested with MspI endonuclease. Restriction products were separated by electrophoresis in 2% agarose (Gibco-BRL, England) in 1× TBE buffer (0.09 M Tris-boric acid, 0.002 M EDTA) with 0.5 g/ml ethidium bromide (Et-Br), visualized under UV light, and scanned in an FX Phosphorimager apparatus (Bio-Rad, Hercules, CA, USA). 2.3. Analysis of milk composition The experiment lasted during 6 successive lactations. The goats were milked twice a day. Milk samples were taken from each goat once a month during the whole lactation period (270 days in average). The daily milk yield (kg) and content of the major milk components (%): fat, protein and lactose, and also somatic cell count (SCC) were evaluated in each milk sample. The fat, protein and lactose content were estimated in the milk preserved with Broad Spectrum Microtabs II (Bentley, Poland), using Milko Scan 104A/B (FOSS A/S, Hillerød, Denmark). Somatic cells were counted by means of a Fossomatic apparatus (FOSS A/S). Somatic cell count and lactose concentration in milk were used as indicators of the health status of the udder. 2.4. Statistical calculations Altogether 2905 records about milk yield, fat and protein content and 1181 records about lactose content and SCC, from 180 does were used in statistical analyses. The SCC values (expressed in thousands) were transformed to the natural logarithm scale (ln of SCC). In order to determine associations between the GHR gene polymorphism and the investigated traits the multi-trait repeatability test-day model was used. The DMU program was used for computation (Madsen and Jansen, 2000). The model included the animal’s genotype, breed, year of birth, herd-year-season of kidding and parity as fixed effects and the additive genetic effect, permanent environmental influence and the date of the test as random effects. Legendre polynomials nested within parity were applied taking into account of stage of lactation effects (Brotherstone et al., 2000). The differences between solutions for genotypes were checked using Student’s t-test with Bonferroni adjustment. The significance of the differences between observed and expected genotype frequencies was estimated using 2 test.
3. Results and discussion In this study a 439 bp DNA fragment was sequenced, comprising whole exon 4 and parts of adjacent introns of the goat growth hormone (GHR) gene to search for nucleotide sequence polymorphisms. Sequencing DNA samples from 36 goats revealed one single nucleotide polymorphism—a C/T transition at 8th nucleotide of exon 4 (position 94 according to GenBank Acc. No. AY739707). Since the whole sequence of the goat GHR gene is not known the PCR primers were used, designed previously by Blott et al. (2003) for the amplification of the corresponding fragment of the bovine GHR gene. In the bovine gene they match sequences between nucleotides 1594 and 1615 (forward primer) and 2011 and 2032 (reverse) (Gen-
Fig. 1. Agarose gel electrophoresis showing RFLP-MspI genotyping of C/T single nucleotide polymorphism in the goat GHR gene exon 4: M—100–1000 bp DNA marker (Sigma); ND—non-digested 439 bp PCR product; CC, CT, TT—GHR genotypes. Digestion of the 439 bp PCR product with MspI restriction endonuclease resulted in two DNA bands (318 and 121 bp) for homozygote CC, three bands (439, 318 and 121 bp) for the CT heterozygote, and one band (439 bp) for homozygous TT genotype animals.
Bank AM161140.1). With the caprine DNA as a template they gave a good quality PCR product of the expected length of 439 bp (Fig. 1). Known is the complete mRNA sequence (cds) of the goat GHR-exons 2–10 (GenBank Acc. No. EF559245). This allowed us to localise the C/T mutation at mRNA position 437. The nucleotide substitution has no effect on the amino acid sequence of the GHR protein; both triplets—TCC and TCT encode serine. As the C → T mutation removes the MspI restriction site, the polymorphism could be identified using RFLP techniques. After digestion with the MspI endonuclease three genotypes were identified: homozygotes either digested (CC) or non-digested (TT) by MspI, and CT heterozygotes (Fig. 1). The genotype frequencies were as follows: CC = 0.96, CT = 0.036, TT = 0.004 (one animal only among 227 genotyped). The frequency of C and T alleles was 0.978 and 0.022, respectively. The distribution of genotypes followed the Hardy–Weinberg rule. Maj and Zwierzchowski (2006) searched for sequence variation in the GHR gene in different ruminant species—Bovidae and Caprine. Only two differences were found in 130 bp long exon 4 sequence of GHR gene between bovine (Bos indicus) vs. (Capra hircus): T → C at position 8 and C → T at position 16. Associations were studied of the GHR polymorphism with the goat’s milk traits. The mean values and standard deviations of the investigated traits and the effects of GHR genotypes are shown in Table 1. The animal carrying the TT genotype was not included in the statistical analysis. No associations were found between the C/T polymorphism in GHR gene exon 4 and the milk yield and fat and protein content. But there were differences found (p ≤ 0.01) between goat GHR genotypes as concerns lactose content and somatic cell count (SCC) in the milk. The CC goats had a higher lactose content and lower SCC than those with the CT genotype. Both lactose content and SCC in milk are the indicators of health status of the goat’s mammary gland (Lerondelle et al., 1992; Leitner et al., 2004).
A. Maj et al. / Small Ruminant Research 90 (2010) 139–141
141
Table 1 Means and standard deviations of investigated traits and estimates for, genotypes effects with their standard errors (SE). Trait
Overall Mean
Milk yield [kg] Fat [%] Protein [%] Trait
2.36 3.37 3.28
Genotype SD
1.03 1.13 0.85
Overall Mean
CC
CT
Estimate (N = 2821a )
SE
Estimate (N = 83a )
SE
2.41 3.07 3.44
0.21 0.23 0.15
2.42 3.12 3.34
0.27 0.26 0.18
Genotype SD
CC
CT
Estimate (N = 1129a ) Lactose [%] SCC [ln] a
4.38 6.81
0.34 1.25
A
4.21 7.06A
SE 0.08 0.25
Estimate (N = 44a ) B
4.08 7.62B
SE 0.11 0.38
Number of milk samples analysed; the different letters within rows indicate differences at A—p ≤ 0.01.
There is very little information about polymorphism of the goat GHR gene and its association with production traits. The possible effects of the TG-repeat variants in the goat GHR gene 5 -noncoding region were studied with milk production traits but no association was found (Maj et al., 2007). More studies were conducted on the polymorphism of the bovine GHR gene. Association was established between A/T polymorphism in the GHR gene exon 8 (position 914, according to GenBank AY748827), which resulted in amino acid substitution Phe279Tyr in the transmembrane domain of the receptor, and milk, fat and protein yield and fat and protein content in milk of Holstein-Friesian cows (Blott et al., 2003). Effects of two SNPs (RFLP-NsiI and -AccI) and their combination were shown on milk production traits of Holstein-Friesian cows (Maj et al., 2004). Moreover, the A257G polymorphism was found in the GHR gene exon 10 which was connected with milk fat and protein yield ´ (Kaminski et al., 2006). 4. Conclusion This study presents a novel polymorphism of the caprine GHR gene—the C/T transition in exon 4. An association was found between the GHR genetic polymorphism and lactose concentration and somatic cell count in goat’s milk, the traits which are highly related to udder health. Therefore, we suggest the potential use of C/T polymorphism in exon 4 of the GHR as a genetic marker of goat’s resistance/susceptibility to mastitis. However, to prove this, further study must be done with more numerous animal cohorts, including more animals representing the homozygous genotype TT. Acknowledgement This study was supported by IGAB grant S.V.3. References Aggrey, S.E., Yao, J., Sabour, M.P., Lin, C.Y., Zadworny, D., Hayes, J.F., Kunlein, U., 1999. Markers within the regulatory region of the growth
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