Livestock Research for Rural Development 28 (2) 2016 | Guide for preparation of papers | LRRD Newsletter | Citation of this paper |
This study was done to evaluate live weight performance of different growth hormone (GH) genotypes (BC+/+, BC+/–, BC–/–) of progeny generation (G1) derived from parental generation (G0) of three genotypes in cows (C+/+, C+/–, C–/–) and two homozygous genotypes in sires (B+/+ and B–/–) mated by artificial insemination (AI) in Indonesian-grade cattle at rural areas in Minahasa regency, North Sulawesi province of Indonesia. To indentify the presence of GH genotypes, the totals of 222 blood samples of Indonesian-grade cows (G0) and their female progeny (G1) as well as 2 blood samples of Ongole-breed sires (G0) were used in this study by PCR-RFLP involving Msp1 enzyme-restriction. To eliminate different age effects of the animals, live weight data of 111 G1 progeny were adjusted for the 50 and 345 days old of ages for the first and second weighing, respectively. Cows and their progeny grazed onto places within local grass pasture all days starting at 07.00 a.m. to 17.30 p.m. without supplementary feeds of concentrate as the main management system practised by 116 farmers as the animal owners.
The breeding herds were on the range pasture year around. Farmers supervised their cows and the animals showing signs of estrus were brought at the rural AI service center of government to be mated freely by AI inseminator using thawing straw of frozen germ plasma of Ongole-breed sires in liquid Nitrogen. Data on live weight and average daily gain (ADG) were recorded on individual animal basis of different GH genotypes and analyzed using general linear models. The results showed that GH genotypes were associated with differences on live weight and ADG of Indonesian-grade progeny (G1) during 50 to 345 days of age. The heterozygous GH genotype (BC+/-) excelled over their homozygous GH genotypes (BC+/+ and BC-/-) in respects of progeny live weight gain. It is concluded, the homozygous GH genotypes of sire (B+/+, B–/–) and cow (C+/+, C–/–) and the heterozygous GH genotype of cow (C+/–) can be used as the potential GH genotypes in Indonesian grade cattle for progeny live weight gain improvement at rural areas.
Key Words: live weight gain, growth hormone genotypes, Indonesian local-grade cattle
The Indonesian cattle breeds are supposed to be of unknown compositions of mixed species origin. The Indonesian local-grade cattle is composed of unknown proportion of the Madura, the Sumba, and the Ongole breed combinations, all were combined into a single group because it was impossible to delineate the exact breed composition and is so far only supported by preliminary molecular analysis (Mohamad et al 2009). They have adapted to harsh environment under hot and humid climate as well as low-quality feed to produce meat and power to plough a farm land prior to planting. Cattle and buffaloes are important on smallholder farms in most developing countries to provide meat, milk, traction power and manure in integrated crop and livestock farming systems (Preston and Leng 2009). In Indonesia, the local-grade cattle play a role for increasing income of smallholder animal agriculture including this location study in North Sulawesi province.
Nowadays, selection for better performance of such important Indonesian local indigenous breed has found more priority in advance of genetically molecular biotechnology. Growth hormone (GH) in beef cattle plays a vital role in post-natal growth and general metabolism (Zhao et al 2004; Kish 2008). Therefore, GH has been the most intensive object of studies and research in ruminant animals to relate the mutation of GH gene with the productive traits (Zhao et al 2004; Pawar et al 2007). With the development of molecular biology and biotechnology, scientists are able to achieve more accurate and efficient selection goal by marker-assisted selection (MAS). In general, validating the genetic markers of growth traits is the initial and crucial step to establish a MAS system (Allan et al 2007).
Growth hormone (GH) is an anabolic hormone synthesized and secreted by the somatotroph cells of the anterior lobe of the pituitary in a circadian and pulsate manner, the pattern of which plays an important role in postnatal longitudinal growth and development, tissue growth, lactation, reproduction, as well as protein, lipid and carbohydrate metabolism (Ayuk and Sheppard 2006). Effects of GH on growth are observed in several tissues, including bone, muscle and adipose tissue, so that GH gene, with its functional and positional potential, has been widely used for marker in several livestock species, including the cattle such as Bos taurus and Bos indicus (Beauchemin et al 2006). It has been reported that the restriction fragment length polymorphisms (RFLP) of GH were associated with body weight in Grati dairy cows (Maylinda 2011) and in sheep (Malewa et al 2014). Restricted enzyme for specific growth hormone gene was produced by the bacteria of “Moraxella species” (Msp) with one enzyme. This enzyme of the “Moraxella species” (Msp) bacteria was used in notation of the specific growth hormone gene as the Msp1 genotype for GH gene identification by procedure of polymerase chain reaction (PCR) with the restriction fragment length polymorphisms (RFLP) (Rifa’i 2010).
The studies of GH gene restricted by enzyme of MspI locus have been reported in Ongole crossbred cattle (Sutarno et al 2005, Sutarno 2010), Brahman cattle (Beauchemin et al 2006), Indian Zebu cattle (Shodi et al 2007), West coastal Sumatera cattle (Jakaria et al 2007), and Grati dairy cows (Maylinda 2011). Their studies indicated that growth hormone genotypes of Msp1+/+ and Msp1+/- can be used as the candidate genes in cattle selection for breeding program of beef cattle. Moreover, these genotypes had a stronger correlation to the higher body weight than Msp1-/- genotype in Grati dairy cows (Maylinda 2011).
In view of the above genetically studies, the objective of current study was to evaluate live weight performance of three different growth hormone (GH) genotypes (BC+/+, BC+/–, BC–/–) of progeny generation (G1) derived from parental generation (G0) of three genotypes in cows (C+/+, C+/–, C–/–) and two homozygous genotypes in sires (B+/+ and B–/–) mated by artificial insemination (AI) in Indonesian-grade cattle. The genetic information would be useful in an attempt to produce superior genetic stocks that would be suitable for development of Indonesian local large ruminant production at rural areas.
The genotyping process was conducted at the Biotechnology Laboratory, Department of Biological Science, Faculty of Mathematics and Natural Science, Sam Ratulangi University, Manado. DNA extraction and genotyping for growth hormone (GH) and allele identification in the animals were done using the protocols in DNA Laboratory (Photo 1) as described by Paputungan et al (2012). The indentified alleles and genotypes of the animals were presented in Table 1.
The selected GH loci using alleles of Msp1+ and Msp1– enzyme restriction in Indonesian-grade parental sires and cows were inherited to their progeny following Mendelian mode inheritance (Paputungan et al 2012). In addition, the female progeny maternal performance was also derived from their sire performance (Paputungan et al 2000).
Photo 1. Part of GH genotyping and allele identification in Indonesian-grade cattle: (A) Calf progeny blood collection; (B) Cow and Calf blood samples; (C) Blood DNA extraction; (D) DNA band resulted in part of Ongole-breed sire called “Tunggul” with GH genotype Tu_B-/- and sire called “Krista” with GH genotype Kr_B+/+, other grade cow genotypes (C-/-, C+/-, C-/-) and other progeny genotypes (BC+/+, BC+/-, BC-/-). |
Table 1. Band of the fragment after Msp1 enzyme restriction in Indonesian-grade cattle |
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Length of DNA band (bp) |
Identified allele |
Genotype notation |
Parental genotype notation used in this study |
223 |
Normal allele (Msp1+)* |
Msp1+/+ |
B+/+ (homozygous genotype in sire) |
104 |
C+/+ (homozygous genotype in cow) |
||
327 |
Msp1+ and Msp1 – |
Msp1+/– |
B+/– (not available in sire genotype) |
223 |
C+/– (heterozygous genotype in cow) |
||
104 |
|||
327 |
Mutant allele (Msp1–)** |
Msp1–/– |
B–/– (homozygous genotype in sire) |
C–/– (homozygous genotype in cow) |
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* ) Cut by Msp1 enzyme; **) Uncut by Msp1 enzyme; bp = base pair. |
The total of 222 animals were used in this study, comprising 111 cows at the age of 4 to 5 years old and their 111 female progeny of Indonesian grade cattle in North Sulawesi province at the ages ranging from 5 days to 50 days old for the first weighing and 295 days to 345 days old for the second weighing. All cows were reared under private areas belong to farmers with unknown ancestors. Progeny were born from those cows mated by artificial insemination (AI) technique using germ plasmas (semen) of the two sires of Ongole breeds called “Kirsta” with genotype of B+/+ and “Tunggul” with genotype of B–/– as the parental stocks taken from “the artificial insemination (AI) sire germ plasma center” at the Singosari district, East Java province of Indonesia. The mating arrangement for production of experimental progeny was shown in Table 2.
Table 2. Mating arrangement of sires (G0) and cows (G0) to produce 111 heads of the experimental progeny genotypic groups (G1). |
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Sire Name |
Two geno-types of sire |
Three different genotypes of cows |
||
G0: C +/+ (35) |
G0: C +/– (38) |
G0: C –/– (38) |
||
“Krista” (Kr) |
G0: B +/+ |
G1: BC +/+ (17) |
G1: BC +/+ (11); BC +/– (6) |
G1: BC +/– (18) |
“Tunggul” (Tu) |
G0: B –/– |
G1: BC +/– (18) |
G1: BC –/– (13), BC +/– (8) |
G1: BC –/– (20) |
G0: Parental groups; G1: Progeny group; Figures in parenthesis represent numbers of breeding progeny and parental cows |
The Indonesian local-grade cattle were raised by smallholder under traditional management using local grass around coconut plantation and opened grass field surrounding rural areas. Cows and their progeny grazed onto places within local grass pasture all days starting at 07.00 a.m. to 17.30 p.m. without supplementary feeds of concentrate as the main management system practiced by 116 farmers as the animal owners at rural areas of Tumaratas village, West Langowan district, North Sulawesi province of Indonesia used in this study. The breeding herds were on the range pasture year around. Farmers supervised their cows and when they showed signs of estrus, cows were brought at the rural artificial insemination (AI) service center of government to be mated freely by inseminator using thawing straw of frozen germ plasmas of the Ongole-breed bulls stored in liquid Nitrogen supporting the animal breeding development program by the government for local community development at rural areas.
The average data of conception rates (C/R) was 55.56 percents and the service per conception (S/C) was 1.44 in this herd based on the annual data of the AI service center of Minahasa regency, North Sulawesi province 2013-2014 (Kasehung et al 2015). The value of C/R indicated that the total cow acceptors of AI mating, about 55.56 percents of them were pregnant for the first services of AI and 44.44 percents of the cows were pregnant for the second services of AI at the next estrus period. The value of S/C indicated that the total of 100 pregnant cows need 144 services of AI using straws of frozen germ plasmas. These values were classified into moderate reproductive performance of local-grade cattle using AI method (Winarti and Supriyadi 2010). This moderate reproductive performance of local-grade cows might be due to part of late supervision of the farmers on the signs of animal estrus causing opened cows at the time of AI application.
The data of the parental cows within 5 years old age were used in this study. Body weights of animals were determined by using a digital weighing scale. The parameters of the animal body weight were measured using digital weighing scale when animals were standing as described in Ozkaya and Bozkurt (2008). The female progeny used in this study comprised 45 heads within 5 days old, 30 heads within 20 days old, 9 heads within 30 days old and 27 heads within 50 days old. Data of these progeny were corrected by adjusting for the 50 days old of age for the first weighing and for the 345 days old of age for the second weighing for elimination of different effects of age on animals using the formula (Zulkharnaim et al 2010) as follows:
= x
Data of age adjustment were analyzed using simple software of the statistical program function in Excel XP 2007.
The data on live weights of animals were analyzed using the General Linear Models (GLM) procedure of SAS (2003) with mathematical model as follows (Steel and Torrie 1993),
Yijkl = µ + Bi + Cj + P (BC)ijkl+ eijkl
Where:
Yijkl = observation from the 1th genotypic progeny within the kth mating interaction associated with the jth genotypic parental cow groups and the ith genotypic parental sire groups,
µ = general mean common to all animals in the experiment,
Bi= the fixed effect associated with the ith genotypic parental sire groups (i=2, Kr-B +/+, Tu-B –/–),
Cj= the fixed effect associated with the jth genotypic parental cow groups (j=3, C +/+, C +/–, C –/–),
P (BC)ijkl = the random effect of the lth genotypic progeny (l=3, BC+/+, BC+/–, BC–/–) within the kth mating interaction [k=6, (Kr-B +/+ x C +/+), (Tu-B –/– x C +/+), (Kr-B +/+ x C+/–), (Tu-B –/– x C+/–), (Kr-B +/+ x C –/–), (Tu-B –/– x C –/–)] associated with the jth genotypic parental cow groups and the ith genotypic parental sire groups,
eijkl = random effects peculiar to each individual progeny.
Comparison of the significant means of live weight measurement variables within animal genotype was tested using least significant different (Byrkit 1987; Mendenhall 1987) to test associations between genotypic groups.
Results in Table 3 showed the least squares means for live weight of progeny associated with sire and cow genotypes. From the total of 111 parental cows in this study, the 59 cows were mated by AI technique using germ sperms of Ongole breed sire called “Tunggul” (Tu: B–/– ), and the 52 cows were also mated by AI technique using germ sperms of Ongole breed sire called “Krista” (Kr: B+/+). The overall means for live weight of 50 days, 345 days and ADG of 50-345 days of the progeny were 49.62± 6.23 kg, 171.62±12.98 kg, and 0.417 ± 0.053 kg, respectively. The random effects of sire (G0) genotypes were not significantly associated with all growth traits of the progeny (G1) under this study. The parental heterozygous genotypes of the C+/- of cows (G0) were significantly associated with live weight at 345 days old and ADG at 50-345 days old of the progeny (G1) compared with live weight and ADG of (G1) derived from the homozygous C+/+ genotype cows (G0) (Table 3).
In this present study, there were significant differences in live weight and ADG between progeny (G1) with homozygous genotypes born by the cows (G0) and the live weight and ADG of G1 with heterozygous genotypes of the progeny produced by both homozygous genotypes (G0) of sires (Krista, Kr: B+/+ and Tunggul, Tu: B–/–). The cows (G0) with heterozygous genotype of C+/- were significantly associated with weight at 345 days old and ADG of the progeny (G1) considered in this study (Table 3).
Table 3. The averages and standard deviations of live weight of the progeny generation (G1) derived from parental Indonesian grade cattle (G0) mated by the artificial insemination (AI) at the village AI service center in Minahasa regency, North Sulawesi province of Indonesia |
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Sources |
No. of G1 |
Weight at 50 days old (kg) |
Weight at 345 days old (kg) |
ADG 50-345 days (kg) |
Overall mean Sire (G0) genotypes: G0: Krista (Kr-B +/+) G0: Tunggul (Tu-B –/–) |
111 52 59 |
49.6 ± 6.23 48.9 ± 6.35 50.1 ± 6.25 |
172 ± 12.9 173 ± 10.8 171 ± 14.7 |
0.42 ± 0.05 0.42 ± 0.03 0.41 ± 0.06 |
Cow (G0) genotypes: G0: C +/+ G0: C +/– G0: C –/– |
35 38 38 |
46.4 ± 7.30 50.7 ± 5.93 49.6 ± 6.23 |
166 ± 8.5 a 174 ± 8.3 b 172 ± 16.6 ab |
0.40 ± 0.01 a 0.42 ± 0.02 b 0.41 ± 0.07 ab |
Parental (G0) genotypic mating interaction: G0: Kr-B +/+ x 17 C +/+ = G1: 17 BC+/+ G0: Tu-B –/– x 18 C +/+ = G1: 18 BC+/– G0: Kr-B +/+ x 17 C+/– = G1: 11BC+/+, 6BC+/– G0: Tu-B –/– x 21 C+/– = G1: 13BC-/-, 8BC+/– G0: Kr-B +/+ x 18 C –/– = G1: 18 BC+/– G0: Tu-B –/– x 20 C –/– = G1: 20 BC–/– |
17 18 17 21 18 20 |
45.0 ± 5.20 a 48.5 ± 12.0 ab 49.9 ± 7.03 ab 52.2 ± 3.27 b 49.7 ± 5.68 ab 49.6 ± 6.58 ab |
168 ± 4.6 a 172 ± 9.2 ab 175 ± 7.0 b 178 ± 5.0 b 177 ± 4.7 b 166 ± 6.8 a |
0.40 ± 0.01 a 0.42 ± 0.02 b 0.42 ± 0.02 b 0.42 ± 0.03 b 0.44 ± 0.03 b 0.41 ± 0.08 ab |
Progeny (G1) Genotypes: G1: BC +/+ G1: BC +/– G1: BC –/– |
28 50 33 |
47.6 ± 6.70 50.3 ± 6.11 48.9 ± 6.31 |
167 ± 7.4 a 176 ± 7.8 b 173 ± 7.7 ab |
0.41 ± 0.09 a 0.44 ± 0.07 b 0.43 ± 0.06 ab |
The values bearing different superscript in the same column differ significantly (p<0.05). |
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In the interaction effects, the cows (G0) with homozygous (C+/+) and heterozygous (C+/–) genotypes (using restriction of Msp1 enzyme) mated by sires (G0) with the opposite genotypes (using restriction of Msp1 enzyme) produced higher live weight and ADG of progeny (G1) compared with live weight and ADG of progeny (G1) produced by the parents (G0) with same homozygous genotypes (Figure 1). This study revealed that there was definite pattern of outstanding progeny (G1) with the heterozygous GH genotypes in growth traits produced by mating of different growth hormone genotypes (Msp1 restricted enzyme) of both parental cows and sires (G0).
Figure 1. Progeny (G1) average live weight (ALW, kg) and average daily gain (ADG, kg) derived from different parental cow (G0) genotypes |
The selected growth hormone locus using alleles of Msp1+ (B+ and C+) and Msp1– (B– and C–) enzyme restriction in Ongole-crossbred parental sires and cows was inherited to their progeny following Mendelian mode inheritance (Paputungan et al 2012). The genotypes of sire (G0) were not associated with progeny (G1) live weight at 50 and 345 days old and average daily gain (ADG) of 50-345 days. The same case was also found for live weight of progeny (G1) at 50 days old within cow (G0) genotypes (Figure 2). This might be due to the fact that too few sires and dams involved in this study. The progeny (G1) live weight at 345 days old and ADG of 50-345 days were significantly different among genotypes of the parental cows (G0). The progeny (G1) heterozygous genotype group of the BC +/– were heavier than those variables of both homozygous genotypic groups of the BC+/+ and the BC –/– of the progeny (G1) in this study (Figure 2).
The heterozygous genotype (BC+/–) of progeny (G1) would indicate a trend of heterosis effect. This heterozygous genotype was associated with the animal live weight and average daily gain (ADG). This is in agreement with some reports (Fahmi 2004; Marson et al 2005; Javanmard et al 2005) who stated that heterosis effect was a productive trait advantage of outstanding progeny derived from crossing of both parents (G0) producing lower productive trait average compared with that of their progeny (G1). This study revealed that the animal progeny (G1) with the heterozygous BC+/– genotype performed the outstanding averages of live weight and ADG compared with the averages of those in both homozygous BC +/+ and BC–/– genotypes of animals. This is also in agreement with Katule (1992) observations that the highest performance is expected in the breed which had been developed purposely for higher performance in that trait.
Figure 2. Progeny (G1) average live weight (ALW, kg) and average daily gain (ADG, kg) by their different genotypes |
The least squares means for live weight of progeny (G1) within sire and cow (G0) genotypic mating interaction groups showed significant differences at 50, 345 days old and ADG (Table 3). The progeny (G1) genotype group of the BC+/– were also heavier than those variables of both homozygous genotypic groups of the BC+/+ and the BC–/– of progeny (G1). The heterozygous BC+/– genotype would indicate a trend of heterosis effect (Figure 3). This genotype might be associated with the animal average live weight (ALW) and average daily gain (ADG).
Differentiations of the B+ or C+ and B– or C– alleles in animals were characterized by number of restricted fragment. The B+ or C+ allele had two fragments with length of each fragment was 104 base pair (bp) and 223 bp. Meanwhile, the B– or C– allele had only one fragment with its length of 327 bp. The differences of these two fragments of B+ or C+ and B– or C– alleles were caused by mutation of Cytosine to Thymine (Rifa ‘i 2010). This was in agreement with study reported by Nei (1972) that the growth hormone gene had high variability due to mutation. Mutation occurred on DNA level due to nucleotide changes, either transition or insertion (Cambell and Reece 2008). Based on the difference of nucleotide restriction sites of each allele, the mutation of Cytosine into Thymine occurred due to nucleotide transition.
Figure 3. Progeny (G1) average live weight (ALW, kg) and average daily gain (ADG, kg) associated with different parental genotypic mating interactions (G0). |
The transition of Cytosine into Thymine changed the restriction site of Msp1 enzyme (Rifa’i 2010). The homozygous genotype B+/+ (224 bp and 104 bp) was detected in one Ongole sire called “Krista” with genotypic code of Kr: B+/+, while the homozygous genotype B –/– (327 bp) was detected in one Ongole sire called “Tunggul” with genotypic code of Tu: B–/–. These genotypes were the same with research reported by Zhou et al (2005) to show that amplification of PCR-RFLP for GH gene using Msp1 enzyme restriction in Beijing Holstein produced three genotypic animals (Msp1+/+, Msp1+/– and Msp1–/–). This enzyme recognized only the restriction site of four nucleotides for C*CGG (C for Cytosine and G for Guanine).
Gene variation of GH locus for Msp1 in cattle was detected in the position of intron 3 (Rifa’i 2010) at the sequence position of 1547 based on nucleotide sequence from GenBank, number: M57764.1 in Gordon et al (1983). The intron area was the internal space in which protein code in gene sequence was disappearing during transcription due to mutation effect occurring in GH locus of Msp1 in term of silent mutation (Cambell and Reece 2008; Rifa’i 2010). Silent mutation did not occur at site of active protein and did not cause the amino acid change, because several amino acids were encoded by different codons (Cambell and Reece 2008).
Breeding program must be continued as the first step to increase the frequency of the favorable allele in breeding station (Jawasreh et al 2012). Animal breeding program for community development in North Sulawesi province, the artificial insemination service center applied the frozen straw containing spermatozoa germ plasmas of both Ongole sires called “Krista” (base molecular detection bearing GH genotype of Kr-B+/+) and “Tunggul” (base molecular detection bearing GH genotype of Tu-B-/-) from cattle germ plasma center (Balai Benih Inseminasi Buatan) in Singosari district, East Java province of Indonesia. Carter et al (2005) reported the analysis of gene interaction and found that it might be two or more genes can interact to express a particular phenotype.
The growth of animals was under the hormonal control of GH, growth hormone receptor (GHR) and insulin-like growth factor 1(IGF-1) (Reyna et al 2010). Polymorphism occurring in the regulatory region (promoter region) and coding region (exons) of the gene responsible for those three hormones would influence the expression of the genes and the function of protein during the translation process (Kish 2008). This indicated that the level of blood GH reflects the GH genotype. This study revealed that superior animals differ genetically from inferior animals mainly in their regulation of nutrient utilization and the GH release (Rejduch 2008).
Growth hormone (GH) genotypes were associated with live weight and ADG of Indonesian-grade progeny (G1) during 50 to 345 days of age. The heterozygous GH genotypes (BC+/-) excelled over their homozygous GH genotypes (BC+/+ and BC-/-) in respects of the progeny (G1) live weight gain. The parental GH homozygous genotypes (G0) of sire (B+/+, B–/–) and cow (C+/+, C–/–), and GH heterozygous genotype (G0) of cow (C+/–) can be used as the potential GH genes in Indonesian grade cattle for progeny (G1) live weight gain improvement. The genotypic records of GH genotype in each individual animal combined with the application of AI technique should be maintained for breeding development program in increasing the favorable heterozygous genotypes of BC+/– in large population of animals supporting the local farmer community development at the rural areas.
The authors acknowledge J. Kuhu and his farmer group members at Tumaratas village, district of West Langowan, under development of the artificial insemination service center of Minahasa regency, North Sulawesi province for their assistance in data collection.
Allan M F, Thallman R M, Cushman R A, Echternkamp S E, White S N and Kuehn L A 2007 Association of a single nucleotide polymorphism in SPP1 with growth traits and twinning in a cattle population selected for twinning rate. Journal of Animal Science 85 (2):341-347.
Ayuk J and Sheppard M C 2006 Growth hormone and its disorder. Postgraduate Medical Journal 82 (63):24-30.
Beauchemin V R, Thomas M G, Franke D E and Silver G A 2006 Evolution of DNA polymorphisms involving growth hormone relative to growth and carcass characteristics in Brahman steers. Genetic Molecular Research 5 (3):438-447.
Byrkit D R. 1987 Statistics Today: A Comprehensive Introduction. The Benjamin/Cummings Publishing Company, Inc. 2727 Sand Hill Road Menlo Park, California, 94025, USA.
Cambell N A and Reece J B 2008 Biology. Eighth Edition. Pearson Education Inc. Terjemahan: Wulandari DT (2010). Penerbit Erlangga.
Carter A J, Hermisson R J and. Hansen T F 2005 The role of epistatic gene interactions in the response to selection and the evolution of evolvability. Theoretical Population Biology 68:179-196.
Dybus A 2002 Associations of growth hormone (GH) and prolactin (PRL) genes polymorphism with milk production traits in Polish Black-and-White cattle. Animal Science Papers Reports 20(4):203-212.
Fahmi M H 2004 Simplified principle for breeding sheep. Agriculture and Agri-Food Canada, Ottawa, Ontario, K1A 0C7.
Gordon D F, Quick D P, Erwin C R, Donelson J E and Maurer R A 1983 Nucleotide sequence of the bovine growth hormone chromosomal gene. Molecular Cell Endocrinology 33 (1): 81-95. www.ncbi.nlm.nih.gov/nuccore/m57764. Accessed on December 26, 2015.
Jakaria D, Duryadi, Noor R R, Tappa B and Martojo H 2007 Evaluasi keragaman genetik hormon pertumbuhan (GH) pada sapi pesisir Sumateri Barat menggunakan penciri PCR-RFLP. Media Peternakan 30 (1):1-10.
Jawasreh K I Z, Ababneh H, Awawdeh F T, AL-Massad M A and Al-Majali A M 2012 Genotype and allelic frequencies of a newly identified mutation causing blindness in Jordanian Awassi sheep flocks. Asian-Australasian Journal of Animal Science 25 (1):33-36.
Javanmard A, Asadzadeh N, Banabazi M H and Tvakolian J 2005 The allele and genotype frequencies of bovine pituitary specific transcription factor and leptin genes in Iranian cattle and buffalo population using PCR-RFLP. Iranian Journal of Biotechnology 2 (2): 104-108.
Katule A M 1992 Crossbreeding as a tool for genetic improvement of chickens in sub-optimum environments. Bulletin of Animal Production in Africa 41:71-80.
Kasehung J, Paputungan U, Adiani S dan Paath J 2015 Performans reproduksi induk sapi local PO yang dikawinkan dengan teknik inseminasi buatan di kecamatan Tompaso Barat, Kabupaten Minahasa, Sulawesi Utara. Jurnal Zootek 35: 177-187.
Kish S 2008 Exploring How Growth Hormone are Released in Animals. National Institute of Food and Agriculture, USDA.
Malewa A D, Hakim L, Maylinda S and Husain M H 2014 Growth hormone gene polymorphisms of Indonesia fat tailed sheep using PCR-RFLP and their relationship with growth traits. Livestock Research for Rural Development 26 (6) # 115 Article #115. http://www.lrrd.org/lrrd26/6/male26115.htm
Maylinda S 2011 Genetic polymorphism of growth hormone locus and its association with body weight in Grati dairy cows. International Journal of Biotechnology and Molecular Biology Research 2 (7):117-120.
Marson E P, Ferraz J B S, Meirelles F V, Balieiro J C C, Eler J P, Figuerido L G G and Mourao G B 2005 Genetic characterization of European-Zebu composite bovine using RFLP markers. Genetics and Molecular Research 4:496-505.
Mendenhall, W. 1987. Introduction to Probability and Statistics. Seventh Ed. PWS Publishers. 20 Park Plaza. Boston, Massachusetts, USA.
Mitra A, Sciilee P, Balakrisiinan C R and Pirciiner F 1995 Polymorphisms at growth hormone and prolactine loci in Indian cattle and buffalo. Journal of Animal Breeding and Genetics 12:71-74.
Mohamad K, Olsson M, van Tol H T A, Mikko S, Vlamings B H, Andersson G, Rodriguez-Martinez H, Purwantara B, Paling R W, Colenbrander B and Lenstra J A 2009 On the origin of Indonesian cattle. PLoS ONE 4(5):e5490. Doi:10.1371.
Nei M 1972 Genetic distance between populations. The American Naturalist 106 (949):283-292.
Ozkaya S and Bozkurt Y 2008 The relationships of parameters of body measures and body weight by using digital image analysis in pre-slaughter cattle. Arch Tiers, Dummerstorf 51 (2):120-128.
Paputungan U, Makarechian M and Liu M F 2000 Effects of sire birth weight on calving difficulty and maternal performance of their female progeny. Asian-Australasian Journal of Animal Sciences 13 (13):729-732.
Paputungan U, Hakim L, Ciptadi G and Lapian H F N 2012 Detection of Mendelian and genotype frequency of growth hormone gene in Ongole crossbred cattle mated by artificial insemination technique. Journal of Indonesian Tropical Animal Agriculture 37 (2):79-85.
Pawar R.S, Tajane K R, Joshi C G, Rank D N and Bramkshtri B P 2007 Growth hormone gene polymorphism and its association with lactation yield in dairy cattle. Indian Journal of Animal Science 77 (9):884-888.
Preston T R and Leng R A 2009 Matching Livestock Systems to Available Resources in the Tropics and Subtropics. Penambul Books Australia.Web version http://www.utafoundation.org/P&L/preston&leng.htm
Rejduch B 2008 Genes associated with production and health in farm animals. Jourmal of Central European Agriculture. 9, 4:829-836.
Reyna X F D L R, Montoya H M, Castrellon V V, Rincon A M S, Bracamonte M P and Vera W A 2010 Polymorphisms in the IGF1 gene and their effect on growth traits in Mexican beef cattle. Genetics and Molecular Research, 9 (2): 875-883.
Rifa’i M 2010 Genetika Rekombinasi dan Populasi. Edisi Pertama. Penerbit Galaxy Science, Malang, 65145. ISBN: 978-602-97628-1-5.
Sodhi M, Mukesh M, Prakash B, Misha BP, Sobti R C and Singh K P 2007 Msp1 allelic pattern of bovine gene in Indian zebu cattle (Bos indicus) breeds. Biochem Genet 45 (1-2):145-153.
Steel R G D and Torrie J H 1993 Principles and Procedures of Statistics. Second edition. McGraw-Hill Book Co. Inc. Singapore.
Sulandari S and Zein M S A 2003 Protocols in DNA Laboratory, Center of Biology Research, The Indonesian Institute of Sciences, pp.23-45.
Sutarno, Junaidi A and Tappa B 2005 Polimorfisme MspI pada lokus 2 gen hormon pertumbuhan sapi PO dan pengaruhnya terhadap capaian berat badan harian. Biodiversitas 6 (2):77-81.
Sutarno 2010 Genetic variation among Indonesian native cattle breeds based on polymorphisms analysis in the growth hormone loci and mitochondrial DNA. Biodiversitas 11:1-5. ISSN: 2085-4722 (electronic).
Winarti dan Supriyadi 2010 Penampilan reproduksi ternak sapi potong betina di daerah istimewah Yogyakarta. Prosiding Seminar Nasional Teknologi Peternakan dan Veteriner 2010, hal: 64-67.
Zhao Q, Davis M E and Hines H H 2004 Associations of polymorphisms in the Pit-1 gene with growth and carcass traits in Angus beef cattle. Journal of Animal Science 82:2229-2233.
Zhou G L, Liu H, Liu C, Guo S L, Zhu Q and Wu Y H 2005 Association of genetic polymorphism in GH gene with milk production traits in Beijing Holstein cows. Journal of Biosciences 30 (5):595-598.
Zulkharnaim, Jakaria and Noo R R 2010 Identifikasi keragaman genetic gen reseptor hormone pertumbuhan (GHR׀Alu I) pada sapi Bali. Media Peternakan 33 (2):81-87.
Received 31 December 2015; Accepted 12 January 2016; Published 1 February 2016