Engineering, 2012, 5, 30-34
doi:10.4236/eng.2012.410B008 Published Online October 2012 (http://www.SciRP.org/journal/eng)
Mutations in Caprine DGAT1 and STAT5A Genes were
Associated with Milk Production Traits
——Combined Effects of DGAT1 and STAT5A Genes on Milk Yield and Fat
Xiaopeng An, Jinxing Hou, Haibo Zhao, Chunmei Zhu, Quanmei Yan, Y uxuan Song,
Jiangang Wang, Binyun Cao
College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi P.R. China
Received 2012
ABSTRACT
In this study, polymorphisms of the DGAT1 and STAT5A genes were detected in 528 individuals from Xinong Saanen and Gua-
nzhong goat breeds by PCR-RFLP, PCR-SSCP and DNA sequencing methods. Three allelic variants were identified: DQ380250:
g.407_408insC, AJ237937: g.6798C>T and g.6852C>T in both breeds. At g.407_408insC locus, the frequencies of C1 allele were
0.79–0.85, and frequencies of C2 allele were 0.21–0.15. At g.6852C>T locus, frequencies of C3 allele were 0.70–0.72, and frequen-
cies of T3 allele were 0.30–0.28. Compared with goats with C1C1 and C3C3, those with C1C2 and C3T3 genotypes had significant ef-
fects on milk yield and fat percentage (P<0.05), respectively. The result showed that does with C1C1C3T3 and C1C2C3T3 had higher
milk yield than those with C1C2C3C3 (P < 0.05). In addition, the combined effect of C1C2C3T3 on milk fat percen tage was th e highest
in comparison with other combination genotypes (P<0.05).
Keywords: Dairy Goat; Milk Production Traits; Fat Percentage; Pedi g r e e
1. Introduction
Milk production traits are of fundamental importance in live-
stock production and the related economy [1]. Selection aimed
at increas ing th e frequency of al leles with a p osit ive effect on a
given trait was initiated by geneticists [2]. Meanwhile, variation
of either candidate genes for production traits or linked genetic
markers h as informed t he basic biolo gy of milk production and
composition, and encouraged the use of gene for marker as-
sisted selection (MAS) in livestock [3]. In general, identifying
and validating genetic markers for milk production traits is the
initial and crucial step to establish a MAS system.
Diacylglycerol acyltransferases (DGATs) catalyse the final
step of the triacylglycerol (TAG) biosynthesis of the Kennedy
pathway [4]. Two genes (DGAT1 and DGAT2) have been
shown to encode DGATs. Both genes encode membrane-bound
proteins, with no sequence homology to each other [5]. DGAT1
gene was the first identified gene encoding a protein with
DGAT activity [6]. Diacylglycerol acyltransferase1 (DGAT1)
was identified as one underlying quantitative trait locus (QTL)
for milk production traits in the centromeric region of the bo-
vine chromosome 14 [7, 8]. The signal transducers and activa-
tors of transcription (ST ATs ), a family of transcription factors,
mediate the actions of a variety of peptide hormones and cyto-
kines [9]. STAT5, also known as mammary gland factor ( MGF),
was discovered initially as a PRL-induced transcription factor
[10]. It is a key intracellular mediator of prolactin signalling
and can activate trans cription of milk p rotein genes in response
to prolactin [10, 11]. STAT5 exists in two isoforms – A and B,
which differ by a few amino acids in the carboxylic end of the
protein molecule; separate genes code both of them [12]. In
cattle, the STAT5A and STAT5B genes wer e located close to
each other (within 40 Kb) at chromosome 19 [13]. Ant o ni ou et
al. (1999) described two SSCP variants of the gene fragment
that encodes the SH2 domain in bovine STAT5A protein [14].
Brym et al. (2004) detected a new SNP (A/G) located in the
intron 9 of STAT5A gene at position 9501 [15]. The aim of this
study was to investigate SNPs in DGAT1 and STAT5A genes,
and anal yze the combined effect of DGAT1 and STAT5A genes
on milk production traits to provide the theoretical basis for
goat breeding.
2. Materials and Methods
2.1. Animals and Genomic DNA Isolation
Blood samples were obtained from 528 goats belonging to two
breeds: Xinong Saanen (SN, n=285) and Guanzhong (GZ,
n=243). They were reared in Qianyang county and Zhouzhi
county of Shaanxi province, respectively. Health, fertility and
milk recording was carried out by dairymen and veterinarians.
Data was recorded in winter and spring parturitions of 2008 to
2011. Milk yi e ld s fr o m first to third lactation were standard ized
to 30 0 days in milk. For milk analysis, a milk sample was taken
from each animal once per month throughout the third lactation,
sampling first at least 20 days after parturition to exclude the
risk of contamination with colostrum. Goats were milked twice
a day at constant intervals an d a 10 ml sa mple from each milk-
ing session was mixed for the analysis. Milk constituents (pro-
tein, lactose and fat) were determined with an ultrasonic
S60SEC milk analyzer (Milkotronic Company, Nova Zagora,
Bulgaria). Five milliliters blood per goat were collected asep ti-

X. P. AN ET AL.
31
cally from the jugular vein and kept in a tube containing anti-
coagulant ACD (citric acid:sodium citrate:dextrose – 10: 27:
38). The genomic DNA was extracted from white blood cells
using standard phenol-chloroform extraction protocol [16].
2.2. PCR Amplification
According to bovine DGAT1 and STAT5A genes (GenBank
accession no. AJ318490 and AJ237937), fourteen pairs of pri-
mers were designed to amplify goat DGAT1 and STAT5A
genes. Pairs of primer 1 and 2 are shown in Table 1. Other
primer pairs with no polymorphism detected in their amplifica-
tion regions are not listed. The 25 μL volume contained 50 ng
genomic DNA, 12.5 µL 2 × reaction mix (including 500 µM
dNTP each; 20 mM Tris–HCl; pH 9; 100 mM KCl; 3 mM
MgCl2 ), 0.5 µM of each primer, and 0.5 units of Taq DNA
polymerase. The cycling protocol was 5 min at 95°C, 35 cycles
of denaturing at 94°C for 30 s, annealing at 59°C (primer pair 1)
and 63°C (primer pair 2) for 30 s, extending at 72°C for 30 s,
with a final extension at 72°C for 10 min.
2.3. SNP Genotyping and Sequencing
The SSCP analysis of PCR products of primer pair 2 refers to
An et al. (2011) [17]. In addition , PCR products (5μl) o f pri mer
pair 2 wer e mixed with 1 μl 10 × buffer, 3 U Eco81Ⅰ(TaKaRa,
Dalian, China) and 3.5 μl sterilized ddH2O, and then incubated
for 1.5 h at 37°C. Digested products were subjected to PAGE
(80 × 73 × 0.75 mm) in 1 × TBE buffer and constant voltage
(110 V) fo r 1.5 h. After the polymorphisms wer e detected, am-
plicons representing unique banding patterns were sequen ced in
both directions in ABI 377 DNA analyzer (Applied Biosystems ,
Foster , California, U SA) and the sequences were analyz e d with
DNAstar software (version 7.1) and Blast in NCBI (National
Center for Biotechnology Information).
2.4. Statistical Analysis
The allelic frequenci es, heterozygosi ty (He) and polymorphism
information content (PIC) were calculated using Cluster-analy-
sis so ft wa r e (version 1.2). Milk production traits analyzed in
the current study included milk yield, milk protein, lactose and
fat. Stati stical analysis was perfo rmed using univariate an alysis
in the general linear model procedure of SPSS 16 statistical
softwa r e. The linear model applied was:
Yiknjlm = µ + Gi + Bk + Pn + Nj + (PG) ni+ Sl + Eiknjlm (model 1)
where Yik njlm is the trait measured on each of the iknjlmth animal,
µ is the overall population mean, Gi is the fixed effect asso-
ciated with the ith genotype, Bk is the fixed effect associated
with the kth breed, Pn is the fixed effect associated with the nth
parity, Nj is the fixed effect associated with the jth number of
kids born, (PG)ni is the in teractio n bet ween the nth parity and ith
genotype. Sl is the random effect ass ociated with the lth sire, and
Eiknjlm is the random error. The combined effects of DGAT1 and
STAT5A genes o n mil k p ro du ction trai ts were an al yzed with the
following model:
Yik njlm = µ + Ci + Bk + Pn + Nj + (PC) ni + Sl + Eiknjlm (model 2)
where Yiknjlm, µ, Bk, Pn, Nj and Sl are the same as shown for
model 1, Ci is the fixed effect associated with the ith combina-
tion genotype, and (PC)ni is the in teracti on b etween the nth par-
ity and ith combination genotype.
3. Results
3.1. SNPs Identification and Genot ypes
The bands of different genotypes are shown in Figure 1A and
1B. Comparisons among these nucleotide sequences of differ-
ence genotypes indicated that one base insertion (g.407_
408insC, GenBank accession no. JF781126) was detected i n th e
Table 1. Primer sequences and information on goat DGAT1 and STAT5A genes.
Gene Pri me r Sequence (bp) Ta (℃) Amplicon Product size (bp)
DGAT1 P1 F: 5-AGGAACTCGG AGTCCATCAC-3 59 Exon 14-16 328
R: 5- TGAAGGCCCAGAGGCGGAAC-3
STAT5A P2 F: 5- CTGCAGGGCTGTTCTGAGAG-3 63 Exon 7 215
R: 5- TGGTACC AGGACTGTAGCACAT-3
Note: Fragments includ ing 36 bp of C3T3 genotype were invisib le
Figure 1. SNP d et ect i on o f PCR products at g.407_408insC (A) and g.6852C>T (B) loci for tw o goat breeds.

X. P. AN ET AL.
32
intron 14 of DGAT1 gene (primer pair 1). Two base substitu-
tions (g.6798C>T and g.6852C>T, GenBank no. JN091564)
were detected in PCR products of primer pair 2 (exon 7), which
were synonymous mutations. Because there is no homozygote
at the g.6798 C>T locus, relevant data are not listed in Figure
and Table. At g.407_408insC locus, C1C1 and C1C2 genotypes
were found in SN and GZ breeds (Figure 1A). At g.6852C>T
locus, C3C3 and C3T3 genotypes were detected in both breeds
(Figure 1B). Allelic frequencies, He, and PIC are shown in
Table 2. We found that the additive effect of DGAT1 and
STAT5A SNP s on milk yield and fat p ercentag e was extr emely
significant (P < 0.001), respectively. The additive effect be-
tween DGAT1 and STAT5A genes had extremely significant
effects on milk fat per centage (P < 0.001) (Table 3 ).
3.2. Association and Effects of the SNPs and
Comb ination Genotypes
In SN and GZ goat breeds, the genotypes of 528 individuals
were analyzed for association with phenotypic data for milk
yield and constituents at g. 407_408insC and g.6852C>T loci
(Table 4). Milk protein and lactose did not show any signifi-
cant association with genotypes. At g.407_408insC locus, the
does with C1C2 genotype had greater milk fat percentage than
those with C1C1 genotype (P < 0.05). At g.6852C>T locus, the
does with C3T3 genotype had greater milk yield than those with
C3C3 genotype (P < 0.05) (Table 4). The does with C1C1C3T3
and C1C2C3T3 had higher milk yield than those with C1C2C3C3
(P < 0.05) (Table 5). In addition, the combined effect of
C1C2C3T3 on milk fat percen tage was the highest in comparison
with other combination genotypes (P < 0.05).
4. Discussion
In this study, we analyzed the allelic frequencies of g.407_
408insC and g.6852C>T in two goat breeds (n=528). The re-
sults showed that the C2 (g.407_408insC locus) and T3
(g.6852C>T) alleles had low frequencies ( 0.15-0.30), and C2C2
Table 2. Genotypic d istributions, allelic frequencies of g.407_408insC and g.6852C>T lo ci in two g o at breeds.
Loc us Breed
SN GZ
g.407_408insC Genotype C1C1 197 141
C1C2 88 102
Allele C1 0.85 0.79
C2 0.15 0.21
He 0.31 0.42
PIC 0.23 0.28
g.6852C>T Genotype C3C3 112 106
C3T3 173 137
C3 0.70 0.72
Allele T3 0.30 0.28
He 0.61 0.56
PIC 0.33 0.32
Table 3. The additive effect of g.407_408insC and g.6852C>T on milk yield (kg) and fat percentage ( %).
Loc u s Effect Milk yield Milk fat percentage
g.407_408insC Additivet -1.58±4.93 0.15±0.03
P value 0.75 <0.001
g.6852C>T Additivet 18.78±10.08 0.03±0.06
P value < 0.001 0.36
g.407_408insC and g.6852C>T Additivet × Additivet -7.80±2.36 0.18±0.02
P value 0.43 <0.001
Table 4. Association analysis of g.407_408insC and g.6852C>T loci with milk yield (kg) and constituents (%) in goats (Xinong Saanen and
Guanzhong goats).
Gene Genotype Milk yield (kg) Milk fat (%) Milk protein (%) Lactose (%)
DGAT1 C1C1 (338) 653.71±2.25 3.38±0.03a 2.97±0.01 4.46±0.02
C1C2 (190) 660. 29±3.25 3.48±0.03b 2.96±0.01 4.45±0.02
STAT5A C3C3 (218) 642.22±3.06a 3.41±0.03 2.97±0.01 4.47±0.02
C3T3 (310) 665. 67±2.48b 3.45±0.03 2.96±0.01 4.45±0.01
Note: The data are expressed as least square means ± standard errors. Values with different superscripts within the
same column in particular population differ significantly at P < 0.05. Numbers in brackets indicate the number of
samples. Milk samples from third lactation have been analyzed for milk constituents.

X. P. AN ET AL.
33
Table 5. Combined effects of D GAT1 and S TA T5A genes on milk yield (kg) a nd fat percentage ( %) in goats (Xinong Saanen and Guanzhong
goats).
Genotypic combination Milk yield (kg) Milk fat (%) Milk protein (%) Lactose (%)
C1C1C3C3 (147) 642.10±3.65a 3.44±0 .03a 2.96±0.0 1 4.46±0.03
C1C1C3T3 (191) 664.35±3.32b 3.38±0.03a 2.95±0.01 4.42±0.02
C1C2C3C3 (70) 645.23±5.48 3.41±0.05a 2.97±0.02 4.45±0.04
C1C2C3T3 (120) 666.21±3.89b 3.59±0.04b 2.93±0.01 4.47±0.03
Note: The data are expressed as least square means ± standard errors. Values with different superscripts within the same column
in particular ge ner a t io n dif fer s ignific a ntl y at P < 0.05. Numbers in brackets indicate the number of s ample s . M il k s a mple s from
thi rd la c ta t io n have be en a na l yz e d fo r mil k con s t i t ue nt s .
(inset homozygote) and T3T3 (mutation homozygote) genotypes
were not obs erved, respectively at the two loci in SN and GZ
goat br eeds. Flisikowski et al. (2003) reported C→T at position
6853 within the exon 7 of STAT5A gene and they found the TT
genotype only in Polish native breeds (Polish Red and Polish
White-Back cattle) [1 8]. We consider that the results can be
explained by the following two reasons. (1) There is a lower
frequency for missing genotypes, and the samples are small. (2 )
The missing genotypes of the two loci have negative ef fects on
individual performance, so the individuals with missing geno-
types have been eliminated in breeding process.
We firstly revealed the significant association of DGAT1 in-
del (g.407_408insC) and STAT5A SNP (g.6852C>T) with milk
yi e ld and fat percentage in Chinese dairy goats (P < 0.05). Al-
though the mutations of g.407_408insC and g.6852C>T loci do
not concern the coding region and the change of amino acid,
they possibly influence the stability of the mRNA, and can
affect th e mechani sm of mRNA deadenylation and degradation
[19-21]. Linkage disequilibrium with the causal mutation pos-
sibly affects the variation of milk production traits in goat [22].
Previous studies have demonstrated the importance of DGAT1
and STAT5 A genes in milk production traits in cattle [7,8, 23].
DGAT1 candidate gene was found to have a significant effect
not only on milk yield and component traits but also on the
metabolism of intramuscular fat [7, 8 , 24] . Amills et al. (20 07)
indicated T to C substitution at the intron 16 of goat DGAT1
gene could be used as a marker in association studies with milk
traits [25]. Dario et al. (2009) studied the effect of STAT5A/
AvaI polymorphism on growth performance traits in Podolica
bulls and suggested the superiority of C allele for growth per-
formances because both CC and CT bulls tended to show a
higher live weight and a faster growth in comparison with TT
animals [11]. Sadeghi et al. (2009) studied the association be-
twe e n this polymorphism of STAT5A gene and the breeding
values of milk production traits in 134 Iranian Holstein bulls
[26]. Dario et al. (2009) reported a substitution C→T at posi-
tion 6853 of STAT5A gene led to three genotypes (CC, CT and
CT), and the cows with CC genotype had higher milk yield and
protein content than those with CT genotype [27]. The bio-
chemical and physiological functions, together with the results
obtained in our study, indicate that the DGAT1 and STAT5A
genes might play important roles affecting milk production
traits in goat. Genotypic value includes additive effect and do-
minant effect. Additive effect could be truly transmitted to
offspring, so it is the focus of marker-assisted selection [28]. In
this study, we took into account additive effect between SNP
loci and milk production traits. The result showed the additive
effect of g.407_408insC and g.6852C>T on milk yield and fat
percentage was extre mely signi fican t (P < 0.001), resp ectively.
Compared with single SNP analysis, combination genotypes
analysis provides more information on gene interactions. Mul-
tipl e lo cus anal ysis u s ed in th e s tudy revealed th at the combined
effect of DGAT1 g.407_408insC and S TAT5A g.6852C>T sig-
nificantly affected milk yield and fat percentage. Kong et al.
(2007) indicated no significant effects on economic traits in
Hanwoo cattle were found in the separate analysis of K232A
and T11993C polymorphisms of DGAT1 gene, but the interac-
tion between K232A and T11993C showed a significant effect
(P < 0.005) on marbling score [24]. Based on the above con-
siderations, we thought milk production traits were subjected to
the impacts of g.407_408insC and g.6852C>T loci, and there
was an i nteracti on between both loci.
5. Acknowledgements
This study was supported by the National Support Program of
China (2011BAD28B05-3) and Science and Technology Inno-
vation Project of Shaanxi Province (2011KTCL02-09)
REFERENCES
[1] X.P. An, S.G. Son g, J. X. Hou, C.M. Zhu, J.X. Peng, X.Q. Liu, et
al., “Polymorphism identification in goat DGAT2 gene a nd a sso-
ciation analysis with milk yield and fat percentage,” Small Ru-
minant Research, vol. 100, pp. 107-112, 2011.
[2] J.C. Dekkers, “Commercial application of marker- and
gene-assisted selection in livestock: strategies and lessons,”
Journal of Animal Science, vol. 82, pp. E313-328, 2004.
[3] I. Parmentier, D. Portetellea, N. Gengler, A. Prandic, C. Bertoz-
zia, L. Vleuricka, et al., “Can di da t e gene ma r k ers as so cia t ed wi t h
somatotropic axis and milk selection,” Domestic Animal Endo-
crinology, vol. 17, pp . 139-148, 1999.
[4] P. Hat zopoulos, G. B anila s, M. Karampelias, I. Makariti, and A.
Kou r ti , “The olive DGAT2 gene is developmentally regulated
and shares overlapping but distinct expression patterns with
DGAT1,” Journal of Experiment al Botany, val. 62, pp. 521-532,
2011.
[5] K. Giannoulia, K. Haralampidis, Z. Poghosyan, D.J. Murphy,
and P. Hatzopoulos, “Differential expression of diacylglycerol
acyltransferase (DGAT) gen es in olive t iss ues,” B io chemi cal So-
ciety Transactions, vol. 28, pp. 695-697, 2000.
[6] S. Cases, S.J. Sto ne, P. Zhou, E. Yen, B. Tow, K.D. Lardizabal,
et al., “Cloning of DGAT2, a second mammalian diacylglycerol
acyltransferase and related family members,” Journal of Biolog-

X. P. AN ET AL.
34
ical Che m istry, vol. 276, pp. 38870-38876, 2001.
[7] B. Grisart , W. Co ppi eters , F. Farnir, L. Karim, C. For d, P . Berzi,
et al., “Positional candidate cloning of a QTL in dairy cattle:
Identification of a missense mutation in the bovine DGAT1 gene
with major effect on milk yield and composition,” Genome Re-
search, vol. 12, pp. 222-231, 2002.
[8] A. Winter, W. Kramer, F.A.O. Werner, S. Kollers, S. Kata, G.
Durstewitz, et al., “Association of a lysine-232/alanine poly-
morphism in a bovine gene encoding acyl-CoA : diacylglycerol
acyltransferase (DGAT1) with variation at a quantitative trait
locus for milk fat content,” Proceedings of the National Acade-
my of Scien ces, vol. 99, p p. 9300-9305, 2002.
[9] J.E. Darnell, I.M. Kerr, and G.R.Stark, “Jak-Stat pathways and
transcriptional activation in response to IFNs and other extracel-
lular signaling proteins,” Science, vol. 264, pp. 1415-1421, 1994.
[10] H. Wakao, F. Gouilleux, and B.Grone r , “Mammary-gland factor
(Mgf) is a novel member of the cytokine regulated transcription
factor gene family and confers the prolactin response,” Embo
Journal, vol. 13, pp. 2182-2191, 1994.
[11] C. Dario, M. Selvaggi, D. Carnicella, and G. Bufano,
“STAT5A/AvaI polym orphism in Podoli ca bulls and its effect on
growth performance traits,” Livestock Science, vol. 123, pp.
83-87, 2009
[12] H.M. S eyfert, C. Pitra, L. Meyer, R.M. Brun ner, T.T. Wheel er, A.
Molenaar, et al., “Molecular characterization of STAT5A- and
STAT5B-encoding genes reveals extended intragenic sequence
homogeneity in cattle and mouse and different degrees of diver-
gent evolu ti on of vari ous domains,” Journ al of Molecu lar Evolu-
tion, vol. 50, pp. 550-561, 2000.
[13] A. Molenaar, T.T. Wheeler, J.Y. McCracken, and H.M. Seyfert,
“The STAT3-encoding gene resides within the 40 kbp gap be-
tween the STAT5A- and STAT5B-encoding genes in cattle,” An-
imal Genetics, vol. 31, pp. 339-340, 2000
[14] E. Antoniou, B.J. Hirts, M. Gros z , and J. Skidmorec, “A single
stra nd conformat ion polymorp his m in the bovine gene STAT5A,”
Animal Genetics, vol. 30, pp. 225-244, 1999
[15] P. B rym, S. Kamiński, and A. Ruść, “New SSCP polymorphism
within bovine STAT5A gene and its associations with milk per-
forma nc e trai ts in Black -and-Whit e and Jer sey ca tt le,” Journa l of
Applied Genetics, vol. 45, pp. 445-452, 2004.
[16] R. Mullenbach, P.J. Lagoda, and C. Welter, “An efficient salt
chloro-form extraction of DNA from blood and tissue,” Trends
in Genetics, vol. 5, pp. 391, 1989.
[17] X.P. An, J.G. Wang, J.X. Hou, H.B. Zhao, L. Bai, G. Li, et al.,
“Polymorphism identification in the goat MSTN gene and a ssoci-
ation analysis with growth traits,” Czech Journal of Animal
Science, vol. 56, pp. 529-535, 2011.
[18] K. Flisikowski, J. Oprzdek, E. Dymnicki, and L.Zwi e rzcho ws k i,
“New polymorphism in bovine STAT5A gene and its a ssociation
with meat production traits in beef cattle,” Animal Science Pa-
pers and Reports, vol. 21, pp. 147-157, 2003.
[19] D.R. Gallie, and T.E. Young, “The re gu lat ion of gen e-expression
in transformed maize aleurone and endosperm protop-
lasts-analysis of promoter activity, intron enhancement, and
messenger-RNA untranslated regions on expression ,” Plan t Phy-
siology, vol. 106, pp. 929-939, 1994.
[20] J.Q. Clement, S. Maiti, and M.F. Wilkinson, “Localization and
stability of introns spliced from the Pem homeobox gene,” Jour-
nal of Biological Chemistry, vol. 276, pp. 16919-16930, 2001.
[21] Z.E. Sauna, and C. Kimch i-Sarfaty, “Understanding the contri-
bution of synonymous mutations to human disease,” Nature Re-
views Genetics, vol. 12, pp. 683-691, 2011.
[22] J.H.J. Van der Werf, K. Marshall, and S. Lee, “Methods and
experimental designs for detection of QTL in sheep and goats,”
Small Ruminant Research, vol. 70, pp. 21-31, 2007.
[23] H. Khatib, R.L. Mons on, V. Schutzkus, D . M. Ko h l , G.J. M. Rosa,
J.J. Rutledge, “Mutations in the STAT5 A gene ar e ass o ciated with
embryonic survival and milk composition in cattle,” Journal of
Dairy Science, vol. 91, pp. 784-793, 2008.
[24] H.S. Kong, J. D. Oh , J.H. Lee, D.H. Yoon, Y.H. Choi , B.W. Ch,
et al., “Association of sequence variations in DGAT1 gene with
economic traits in Hanwoo (Korea cattle),” Asian-Australasian
Journal of Animal Sciences, vol. 20, pp. 817-820, 2007.
[25] M. Amills, A. Angi olil lo, B . Urrutia, A. Dom enec h , Y. Sastre, B.
Badaoui, et al., “Identification of a single nucleotide polymor-
phism at intron 16 of the caprine acyl-coenzyme A: Diacylgly-
cerol acyltransferase 1 (DGAT1) gene,” Journal of Dairy Re-
search, vol. 74, pp. 47-51, 2007.
[26] M. Sadeghi, M.M. Shahrbabak, G.R. Mianj, and A.N. Javaremi,
“Polymorphism at locus of STAT5A and its association with
breeding values of milk production traits in Iranian Holstein
bu lls,” Lives toc k Science, vol. 123, pp. 97-100, 2009.
[27] C. Dario, M. Selvaggi, G. Normanno, G.V. Celano, and M. Dar io ,
“Genetic polymorphism of STAT5A protein: relationships with
production traits and milk composition in Italian Brown cattle,”
Journal of Dairy Research, vol. 76, pp. 441-445, 2009.
[28] X.P. An, D. Ha n, J.X. Hou , G. Li , Y.N. Wa ng, L. Li, et al. , “Po-
lymorph ism of exon 2 of FSHβ gene and its relationship with re-
production performance in two goat breeds,” Agricultural
Science s in C hi na, vol. 9, pp. 880-886, 2010.