Introduction
Sheep play an important role to meet the sustenance needs of rural populations especially in developing countries through the supply of meat, milk and wool. Sheep rearing in India forms a vital part of the rural economy in most of the areas of the country, particularly in the arid, semi-arid and mountainous areas. As per the 20th Livestock Census (2019), India stands at third position for the world sheep population, with 74.26 million sheep, and is a rich repository of sheep genetic resources having 44 breeds. Consequently, it is imperative to improve the growth, production and reproduction performance of sheep breeds. Munjal sheep is one of the lesser known breeds of sheep that is very popular among farmers of Haryana, Punjab, and Rajasthan states for their height and heavy weight. Munjal sheep are large in size, tall and rectangular in shape (Dahiya et al., Reference Dahiya, Malik and Pander2018). The origin of Munjal sheep is not known exactly, but they are supposed to have originated in India through the sheep breeders of Rajasthan, Punjab and Haryana breeding Nali with Lohi sheep (Arora et al., Reference Arora, Singh, Kalra and Balaine1986; Mason, Reference Mason1988). The demand for meat and meat products is increasing very fast in India and in the world, resulting in an enhanced interest from researchers to increase the meat production through selective breeding and marker-assisted selection. A genetic variation in sheep breeds is an important area as the preservation of unique resources is essential for addressing emerging demands (Kumar et al., Reference Kumar, Dahiya, Malik, Patil and Magotra2018; Chauhan et al., Reference Chauhan, Dahiya, Bangar and Magotra2021).
The insulin-like growth factor-1 gene (IGF-1 gene or somatomedin C) is located on chromosome 3 in sheep, i.e. near to a quantitative trait locus for growth rate and production and is considered to be a candidate gene for predicting growth and meat quality traits (Machado et al., Reference Machado, Alencar, Pereira, Oliveira, Casas, Coutinho and Regitano2003). IGF-1 is linked to the accumulation of lean tissue because it mediates some of the metabolic effects of growth hormone (GH) (Gluckman et al., Reference Gluckman, Douglas, Ambler, Breier, Hodgkinson, Koea and Shaw1991). IGF-1 is renowned for its involvement in a variety of anabolic processes in adults and mature animals, as well as its function in early animal development. It is a component of the GH axis, and so plays a role in animal growth (Laron, Reference Laron2001). The IGF-1 gene is primarily involved in the growth process and, as a result, contributes to increased meat output. The IGF-1 gene regulates somatic growth in response to dietary circumstances. Polymorphisms in the IGF-1 gene are reported to be significantly associated with many growth traits. According to Franco et al. (Reference Franco, Williams, Trofimov, Malkin, Surdulescu, Spector and Livshits2014), genetic as well as metabolic factors, nutritional status and disease-related physiological conditions regulate the circulating IGF-1 levels in the animal body. Siadkowska et al. (Reference Siadkowska, Zwierzchowski, Oprządek, Strzałkowska, Bagnicka and Krzyżewski2006) reported that IGF-1 plays a significant role in growth, lactation, reproduction, fetal development, cell differentiation, embryogenesis and the regulation of metabolism. SNPs in the IGF-1 gene have been associated with birth weight (Curi et al., Reference Curi, de Oliveira, Silveira and Lopes2005), live weight (Zhang et al., Reference Zhang, Zhang, Luo, Yue, Gao and Jia2008; Trukhachev et al., Reference Trukhachev, Skripkin, Kvochko, Kulichenko, Kovalev, Pisarenko, Volynkina, Selionova, Aybazov and Shumaenko2016), carcass traits (Islam et al., Reference Islam, Vinsky, Crews, Okine, Moore, Crews and Li2009) and daily live weight gain (Casas-Carrillo et al., Reference Casas-Carrillo, Prill-Adams, Price, Clutter and Kirkpatrick1997; Reyna et al., Reference Reyna, Montoya, Castrellón, Rincón, Bracamonte and Vera2010). The IGF-1 gene is considered to be a major candidate gene for predicting growth and meat quality traits in animal genetic breeding schemes (Machado et al., Reference Machado, Alencar, Pereira, Oliveira, Casas, Coutinho and Regitano2003). Very little work at the molecular level has been done on Munjal sheep (Kumar et al., Reference Kumar, Dahiya, Magotra, Bangar and Garg2022a). Keeping in view the importance of the IGF-1 gene, the present study was conducted to detect polymorphisms in the 5′ flanking region of the IGF-1 gene and to study its association with performance traits in Munjal sheep.
Materials and methods
Sample collection and DNA extraction
The present study was conducted with prior permission from the Institutional Ethics Committee. The animals for the study consisted of randomly selected Munjal sheep maintained at the Sheep Breeding Farm, Department of Animal Genetics and Breeding, Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar, India. In total, 50 animals were taken under this study for screening to detect the presence of polymorphisms in the genomic region of the IGF-1 gene. In total, 5 ml blood were collected aseptically from the jugular vein in a vacutainer tube containing EDTA (2.7%). The samples were transported to the Animal Genomic Laboratory of the Department of Animal Genetics and Breeding, LUVAS, Hisar in an ice box and stored at −20°C until further processing. DNA was extracted in the Automated Maxell RSC DNA/RNA purification system (Promega) using a Maxwell RSC whole blood DNA kit. Quality and quantity of the DNA was also assessed using a Scandrop Nano-Volume spectrophotometer (Analytika Jena).
DNA amplification and genotyping
A reported set of primers was used to amplify g.857G>A of 5′ flanking coding sequences of the IGF-1 gene (Table 1). DNA template concentrations varied between 100 and 125 ng per 25 μl of reaction mixture. There was no apparent difference in the yield and specificity of the polymerase chain reaction (PCR) product observable by visual appraisal on agarose gels for different samples. Therefore, a concentration of 100–125 ng per 25-μl reaction mixture was used. The optimum level of primer used was standardized to 10 pmol/μl. When primers were used at less or higher than the optimum level, lower and non-specific yields of the PCR product were obtained. This might have been due to the limited amount of primers (Sambrook et al., Reference Sambrook, Fritsch and Maniatis1989). PCR amplification was carried out in a total volume of 25 µl with 100–125 ng DNA template using the Dream Taq Green PCR Master Mix (Promega). PCR was carried out in thermal cycler (T-100 BIO-RAD) under the conditions listed in Table 2. The PCR product was checked on a 1.5% agarose gel. PCR-RFLP was also performed to genotype animal to screen targeted g.857G>A mutation in the IGF-1 gene. Amplified PCR products (10 μl) from all animals were digested with 2 U HaeII restriction enzyme (Thermo Scientific) at 37°C for 10 h and were subsequently resolved on 2.5% agarose gels and stained with ethidium bromide.
Table 1. Primer sets designed for amplification of the target region of the IGF-1 gene
AT, annealing temperature; bp, base pair.
Table 2. PCR protocol
DNA sequencing and SNP identification
PCR amplicons were purified from gels using gel extraction kits (DNA Clean and Concentrator TM-5) and three samples for each genotype were sent for sequencing to the Biotechnology Laboratory, Department of Animal Biotechnology, Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar. Nucleotide sequences were visualized and edited using Chromas software version 2.5.1. to validate the PCR-RFLP results.
Performance traits considered
Information was recorded on various performance traits, namely birth weight (BWT), weaning weight (W-WT), 6-month body weight (6M-WT), 1-year body weight (Y-WT), adult body weight (A-WT), age at first service (AFS), weight at first service (WFS), age at first lambing (AFL), weight at first lambing (WFL) and grease fleece weight (GFW), along with four body conformation traits, namely body length (BL), body height (BH), heart girth (HG) and paunch girth (PG).
Statistical analysis
The data were classified according to genotype, period of birth, sex of lamb (male and female), weight of dam at lambing (three classes). The data were extended over a period of 6 years from 2011 to 2016. The effect of period of birth was included in the model to account for the variation caused by this effect. A total duration of 6 years was divided in two periods each having 3 years’ duration.
Before studying the effects of the IGF-1 gene on performance traits, the data were standardized for significant effects. So, to study the effect of various tangible factors on performance traits, a least-squares and maximum likelihood computer programme from Harvey (Reference Harvey1990) using mixed linear model was used with the following statistical model:
$${{\rm{Y}}_{{\rm{ijkl}}}} = {\rm{ }}{\unicode{x03BC} _ + }{{\rm{P}}_{\rm{i}}} + {\rm{ }}{{\rm{S}}_{\rm{j}}} + {\rm{ }}{{\rm{D}}_{\rm{k}}} + {\rm{ }}{{\rm{e}}_{{\rm{ijkl}}}}$$
where Yijkl is the observation on lth animal belonging to ith period of birth, jth sex and kth dam’s weight group; μ is the overall mean; Pi is the fixed effect of ith period of birth (i = 1, 2); Sj is the fixed effect of jth sex (j = 1, 2); Dk is the fixed effect of kth dam’s weight at lambing (k = 1, 2, 3) and eijkl is the random error component NID (0, σe 2).
Genotypic and allelic frequencies
Genotypic frequencies were calculated using following formula:
$$\eqalign{& \hbox{Genotypic frequency} =\, {\rm no.\ of\ animals\ with\ specific\ genotypes/}\cr & \hskip 7.9pc{\hbox {total no. of animals}} }$$
Allelic frequencies were calculated as follows:
$$\hbox{Allelic frequency of A} = {\rm AA + 1/2 AB}$$
$${\hbox{Allelic frequency of B} = {\rm{BB}} + {\rm{1}}/{\rm{2 AB}}}$$
in which, AA and BB = genotypic frequency of homozygote; AB = genotypic frequency of heterozygote; A and B = allelic frequencies. Furthermore, the effects of genetic variants of the IGF-1 gene on performance and body conformation traits were studied using the following model after correcting data for significant effects:
$${{\rm{Y}}_{{\rm{ij}}}} = {\unicode{x03BC} _ + }{{\rm{G}}_{\rm{i}}} + {{\rm{e}}_{{\rm{ij}}}}$$
in which, Yij is the observation on jth animal belonging to ith genotype; μ is the overall mean; Gi is the fixed effect of ith genotype; and eij is the random error component NID (0, σe 2).
Results and Discussion
Effect of genetic and non-genetic factors on production and body conformation traits
In the present study, the period of birth showed significant effects (P < 0.05) on BWT, W-WT, 6M-WT and WFS in Munjal sheep (Table 3). The period of birth also had significant (P < 0.01) effects on BH (Table 4). The performance of Munjal sheep regarding all growth traits was higher in the 1st period and this variation might be attributed to managerial differences and the different availabilities of quality and quantity of feed and fodder. The decline in growth performance in Munjal sheep over periods might be due to an inbreeding effect, as it was a small flock. A similar significant effect of period of birth on birth weight was reported by Narula et al. (Reference Narula, Patel, Chopra and Mehrotra2017) in Magra sheep, Reddy et al. (Reference Reddy, Sreenivas, Gnanaprakash and Harikrishna2017) in Nellore brown sheep, and Kumar et al. (Reference Kumar, Dahiya, Magotra, Ratwan and Bangar2022b) in Harnali sheep. However, a non-significant effect of period of birth on birth weight was reported by Das et al. (Reference Das, Chakraborty, Kumar, Gupta, Khan and Bukhari2014) and Vivekanand et al. (Reference Vivekanand, Narula, Singh and Chopra2014). The sex of the lamb had a highly significant effect (P < 0.01) on 6M-WT, Y-WT, A-WT, GFW and all considered conformational traits. Significant sex differences in birth weight were also reported by Vivekanand et al. (Reference Vivekanand, Narula, Singh and Chopra2014) in Magra sheep, Kannojia et al. (Reference Kannojia, Yadav, Narula, Pannu and Singh2016) in Marwari sheep, Lalit et al. (Reference Lalit, Dalal, Dahiya, Patil and Dahiya2016) in Harnali sheep, and Reddy et al. (Reference Reddy, Sreenivas, Gnanaprakash and Harikrishna2017) in Nellore brown sheep. The males gave higher estimates for all traits compared with females and this superiority of males was observed from 3 months of age to adult age. Kumar et al. (Reference Kumar, Dahiya, Magotra, Ratwan and Bangar2022b) also reported sex differences in 6-month and yearly body weight in Harnali sheep. This difference of birth weights between the two sexes might be due to hormonal influences. This superiority of male lambs increased with advancement of age. Better prenatal and post-natal growth of male lambs might be due to differences in their endocrine profiles. Dam’s weight at lambing showed a significant (P < 0.01) effect on BWT, W-WT, A-WT, WFS, WFL, GFW and all considered conformational traits in Munjal sheep. Significant effects of dam’s weight at lambing were also reported by Singh et al. (Reference Singh, Pannu, Narula, Chopra and Murdia2013), Devendran et al. (Reference Devendran, Cauveri, Murali and Kumarasamy2014), Nirban et al. (Reference Nirban, Joshi, Narula, Singh and Bhakar2015), Chauhan et al. (Reference Chauhan, Dahiya, Magotra and Bangar2022), and Kumar et al. (Reference Kumar, Dahiya, Magotra, Ratwan and Bangar2022b) in different breeds of sheep. The heavier lambs born out of heavier dams tended to maintain their better vigour and growth. This might be because the well fed dams were expected to produce more milk to feed their lambs up to weaning. So, weaning weight might be considered as a selection criterion for dams for good mothering ability.
Table 3. Least-squares means along with standard error for performance traits in Munjal sheep
*Significant (P < 0.05); **(P < 0.01). Mean values with different superscripts differ significantly.
Table 4. Least-squares means along with standard error for body conformation traits in Munjal sheep
**Significant (P < 0.01). Mean values with different superscripts differ significantly.
Polymorphisms in the IGF-1 gene
In the present study, the PCR product of 294 bp for the IGF-1 gene was screened (Figure 1) encompassing the 5′ flanking region of the IGF-1 gene and genotyped using PCR-RFLP and DNA sequencing methods. Only 47 Munjal sheep out of 50 samples had the PCR product (294 bp) of the IGF-1 gene tested. DNA from three samples was degraded and did not yield any results excluded from the study. The PCR product of 294 bp size harbouring the g.857G>A mutation in the 5′ flanking region of the IGF-1 gene was digested with the HaeII enzyme. The three possible genotypes were defined by distinct banding patterns, i.e. GG (194, 100 bp), GA (294, 194, 100 bp) and AA (294 bp) in the studied population (Figure 2). Similar genotypes were observed previously by Yilmaz et al. (Reference Yilmaz, Davis, Ch and Chung2005) in mixed breed sheep; Tahmoorespur et al. (Reference Tahmoorespur, Valeh, Nassiry, Moussavi and Ansary2009) in the indigenous Iranian Baluchi breed; Honarvar et al. (Reference Honarvar, Sadeghi, Moradi-Shahrebabak, Behzadi, Mohammadi and Lavaf2012) in native Iranian tailed Zel sheep; Gholibeikifard et al. (Reference Gholibeikifard, Aminafshar and Mashhadi2013) in Baluchi sheep; Chelongar et al. (Reference Chelongar, Hajihosseinlo and Ajdary2014) in Makoei sheep; Darwish et al. (Reference Darwish, El-Shorbagy, Abou-Eisha, El-Din and Farag2017) in Egyptian Barki sheep; Grochowska et al. (Reference Grochowska, Borys, Janiszewski, Knapik and Mroczkowski2017) in Polish Merino sheep; and Sankhyan et al. (Reference Sankhyan, Thakur and Dogra2019) in Gaddi and Rampur-Bushair sheep breeds. Niznikowski et al. (Reference Niznikowski, Czub, Kaminski, Nieradko, Swiatek, Glowacz and Slezak2014) found no polymorphisms in the IGF-1 gene (exon 3) in Polish Lowland Sheep. The PCR products for each genotype were purified and three samples of each genotype were sent for sequencing to the Biotechnology Laboratory of the ABT Department (LUVAS, Hisar). Sequence analysis and alignment were carried out using the NCBI/BLAST/blastn suite and the results of the endonuclease restriction were analyzed using FastPCR. Post-sequencing chromatograms showed two SNPs, i.e. g.855G>C and g.857G>A in the 5′ flanking region of the IGF-1 gene. Similarly, He et al. (Reference He, Zhang, Chu, Wang, Feng, Cao, Di, Fang, Huang, Tang and Li2012) determined two polymorphisms named C1511G and A1513G in the 5′ regulatory region of the IGF-1 gene in Small Tail Han, Hu, Texel and Dorset sheep breeds in China. Scatà et al. (Reference Scatà, Catillo, Annicchiarico, De Matteis, Napolitano, Signorelli and Moioli2010) also detected two mutations in the the 5′ regulatory region of the ovine IGF-1 gene (G855C and G857A) in Gentile di Puglia, Altamurana, and Sarda sheep breeds. Trukhachev et al. (Reference Trukhachev, Skripkin, Kvochko, Kulichenko, Kovalev, Pisarenko, Volynkina, Selionova, Aybazov and Shumaenko2016) also reported SNPs in the 5′ regulatory region of the ovine IGF-1 gene (5363.C>T), the 5′UTR (5188.G>C, 5186.G>A), and the first intron (4088.G>A) associated with live weight.
Figure 1. PCR amplicons of the IGF-1 gene in Munjal sheep. M: ladder 100 bp.
Figure 2. PCR-RFLP genotypes of the IGF-1 gene using the HaeII restriction enzyme in Munjal sheep. GG genotype: 194, 100 bp. GA genotype: 294, 194, 100 bp. AA genotype: 294 bp. M: 100 bp ladder.
Gene and genotypic frequencies
Gene and genotype frequencies for the IGF-1 gene are summarized in Table 5. The genotypic and allelic frequencies g.857G>A SNP of the IGF-1 gene indicated that the frequency of the A allele was higher in the studied Munjal population, i.e. 0.59. The GA genotype was found to be the predominant genotype in Munjal sheep (0.66). Similar to the present findings, Grochowska et al. (Reference Grochowska, Borys, Janiszewski, Knapik and Mroczkowski2017) also reported the highest frequency of the A allele (91.6%), whereas the B allele had a low frequency of 8.4% and they found that the most frequent group was AA homozygotes (83.3%), whereas 16.7% of lambs carried the AB genotype in Coloured Polish Merino sheep, but in this study the heterozygote genotype (GA) was found to be predominant. Yilmaz et al. (Reference Yilmaz, Davis, Ch and Chung2005) also reported a high frequency of the A allele and the AA genotype (89% and 77%, respectively) in Polypay sheep. By contrast, Tahmoorespur et al. (Reference Tahmoorespur, Valeh, Nassiry, Moussavi and Ansary2009) and Nazari et al. (Reference Nazari, Noshary and Hemati2016) detected lower frequencies of AA (0.45) and BB (0.09) homozygotes in Baluchi and Zandi sheep, respectively. Ramasamy (Reference Ramasamy2018) found allele frequencies of A (0.974) and G (0.026) and the genotype frequencies of AA, AG, and GG were 0.963, 0.022, and 0.015, respectively, in Madras Red sheep. He et al. (Reference He, Zhang, Chu, Wang, Feng, Cao, Di, Fang, Huang, Tang and Li2012) reported allele frequencies of A and B in Small Tail Han sheep (0.809–0.191), Hu sheep (0.638–0.362), Texel sheep (0.969–0.031) and Dorset sheep (1.000–0.000), respectively. Trukhachev et al. (Reference Trukhachev, Skripkin, Kvochko, Kulichenko, Kovalev, Pisarenko, Volynkina, Selionova, Aybazov and Shumaenko2016) reported the allele frequencies of the 5′ regulatory region of the IGF-1 gene as 0.87 (C) and 0.13 (T) in Russian Soviet Merino sheep breed. Moradian et al. (Reference Moradian, Esmailnia and Hajihosseinlo2013) found the allele frequencies of IGF-1 (exon 1) as 0.73(A) and 0.27(G) in Makoei sheep. Kaplan and Atalay (Reference Kaplan and Atalay2018) found allele frequencies of IGF-1 (5′ flanking region) as 0.915 (A) and 0.085 (B). The genotype frequencies of the IGF-1 gene were 0.85 (AA), 0.13 (AB) and 0.02 (BB). Kazemi et al. (Reference Kazemi, Amirinia, Emrani and Gharahveysi2011) studied the promoter region of the IGF-1 gene in the Zel sheep population and showed the allele frequencies 0.71 (A) and 0.29 (B). Yilmaz et al. (Reference Yilmaz, Davis, Ch and Chung2005) studied the 5′ flanking region of the sheep IGF-I gene in mixed breed sheep. Three genotypes were reported as AA (0.70), AB (0.25) and BB (0.05), which arose from a one-locus, two alleles (A and B) polymorphism. In the present study, chi-squared values revealed that the studied population with respect to the target locus was not under Hardy–Weinberg equilibrium (P < 0.05). Nazari et al. (Reference Nazari, Noshary and Hemati2016), who studied the IGF-I locus in Zandi sheep, also reported that the population was not under the Hardy–Weinberg equilibrium (P < 0.01). Conversely, Negahdary et al. (Reference Negahdary, Hajihosseinlo and Ajdary2013) and Grochowska et al. (Reference Grochowska, Borys, Janiszewski, Knapik and Mroczkowski2017) studied polymorphism in the 5′ flanking region of the IGF-I gene in populations of Makoei sheep and Coloured Polish Merino sheep and found that populations were in the Hardy–Weinberg equilibrium (P > 0.05).
Table 5. Genotype and allele frequency of IGF-1 gene in studied population
*Significant (P < 0.05).
Effect of polymorphism on performance and body conformation traits
The effect of the IGF-1 genotype was significant (P < 0.05) on W-WT, 6M-WT, Y-WT and WFL in Munjal sheep (Table 6). The AA genotype had a higher body weight compared with the GA and GG genotypes and this superiority of the AA genotype was observed from 6 months of age to adult age. However, the non-significant effect of the IGF-1 genotype on growth traits was reported by El-Hanafy and Salem (Reference El-Hanafy and Salem2009) in Egyptian sheep breeds, Gholibeikifard et al. (Reference Gholibeikifard, Aminafshar and Mashhadi2013) in Baluchi sheep and Sankhyan et al. (Reference Sankhyan, Thakur and Dogra2019) in Gaddi sheep, Rasouli et al. (Reference Rasouli, Abdolmohammadi, Zebarjadi and Mostafaei2017) also reported that the IGF-1 genotypes had no significant effect on birth weight and body weight at 6, 9 and 12 months in Markhoz goat. Tahmoorespur et al. (Reference Tahmoorespur, Valeh, Nassiry, Moussavi and Ansary2009) reported that effect of the IGF-1 genotype (5′ flanking region) was non-significant on growth traits in the indigenous Iranian Baluchi breed. Ramasamy (Reference Ramasamy2018) found no significant effect (P > 0.05) between genotypes on all age groups and weight gain and birth weight, breed, management and sex effects. Gholibeikifard et al. (Reference Gholibeikifard, Aminafshar and Mashhadi2013) reported no significant association between the polymorphism of IGF-I and body weights. Grochowska et al. (Reference Grochowska, Borys, Janiszewski, Knapik and Mroczkowski2017) reported a non-significant association of the IGF-1 genotype with growth traits in Coloured Polish Merino sheep. Similarly, Nazari et al. (Reference Nazari, Noshary and Hemati2016) did not find significant associations between SNP in the 5′ flanking region of the IGF-I gene and growth traits in Zandi sheep. Also, Proskura and Szewczuk (Reference Proskura and Szewczuk2014) did not show any relationship between the C/T substitution (g.271C>T) in the IGF-I gene and growth traits in Pomeranian Coarse wool sheep in Poland.
Table 6. Effect of the IGF-1 genotype on performance traits
*Significant (P < 0.05). Mean values with different superscripts differ significantly.
Similar to the present findings, Zhang et al. (Reference Zhang, Zhang, Luo, Yue, Gao and Jia2008) also found a significant (P < 0.05) association of the IGF-I gene polymorphism with birth weight and body weight at 6 and 12 months in Nanjing Huang goats. Negahdary et al. (Reference Negahdary, Hajihosseinlo and Ajdary2013) reported a significant association of the IGF-1 genotype with B-WT, W-WT and 6M-WT in Makooei sheep. Al Qasimi et al. (Reference Al Qasimi, Hassan and Khudair2019) found a significant (P < 0.05) effect of IGF-1 genotypes on weights of lambs at weaning and at 6 months of age with the superior genotype GC and non-significant effects on birth weight. Hajihosseinlo et al. (Reference Hajihosseinlo, Hashemi, Razavi-Sheshdeh and Pirany2013) observed the significant effects of nucleotide variation in the 5′ flanking region of the IGF-I gene with several growth traits in Makooei sheep: birth weight (BWT), weaning weight (W-WT), 6-month weight (6M-WT) and average daily gains from birth to weaning (GBW). Sun et al. (Reference Sun, Su, Li, Musa, Kong, Ding, Ma, Chen, Zhang and Wu2014) who investigated the effects of different factors on the level of the IGF-I gene expression and its association with growth traits, observed a positive correlation of this gene’s expression with body weight in Hu sheep.
The effect of the IGF-1 genotype was found to be significant on HG and PG (P < 0.05) in Munjal sheep (Table 7). The estimates of body conformation traits were higher in the AA genotype compared with GG and GA genotypes. Naicy et al. (Reference Naicy, Venkatachalapathy, Aravindakshan, Raghavan, Mini and Shyama2017) reported a significant association of the IGF-1 genotype with BH and chest circumference in Attappady Black goats of Kerala. Al Qasimi et al. (Reference Al Qasimi, Hassan and Khudair2019) found a significant (P < 0.05) effect of IGF-1 genotypes on BH, HG and PG. Zhang et al. (Reference Zhang, Zhang, Luo, Yue, Gao and Jia2008) investigated the polymorphism of the IGF-I gene and its association with growth and body size traits in Nanjiang Huang goats. They found a significant effect of G/C substitution on birth weight, body weight at 6 months, body weight at 12 months, HG at 2 months, BL at 6 months, wither height at 6 months, wither height at 12 months, and HG at 12 months in the goats. Grochowska et al. (Reference Grochowska, Borys, Janiszewski, Knapik and Mroczkowski2017) reported a non-significant association of the IGF-1 genotype with body conformation traits (BL, BH and HG) in Coloured Polish Merino sheep. Conversely, Hajihosseinlo et al. (Reference Hajihosseinlo, Hashemi, Razavi-Sheshdeh and Pirany2013), who investigated the associations of the IGF-I gene polymorphism in the 5′ flanking region with such body size traits as height and length of body, wither height, chest width and rump length in Makooei sheep, found a significant effect of this gene’s genotypes on sheep BL. Chelongar et al. (Reference Chelongar, Hajihosseinlo and Ajdary2014) observed a significant effect of SNPs in the first exon of the IGF-I gene on fat-tail fat thickness (the thick rump). AA homozygotes were superior in terms of this trait, whereas GG male lambs had the lowest fat thickness. The associations of nucleotide variation in the first exon of the IGF-I gene with tail length and width (rump length and width) in Makooei sheep was not significant (Chelongar et al., Reference Chelongar, Hajihosseinlo and Ajdary2014). Zhang et al. (Reference Zhang, Zhang, Luo, Yue, Gao and Jia2008) found the significant effects of G/C substitution in the fourth intron of the IGF-I gene on HG at 2 months, BL at 6 months, wither height at 6 months, wither height at 12 months, and HG at 12 months in Nanjiang Huang goats. Gao et al. (Reference Gao, Shi, Xu, Li, Ren and Xu2009) showed that the polymorphism in the IGF-3 locus was associated with rump width and HG at 24 and 36 months in Chinese beef cattle. Mullen et al. (Reference Mullen, Berry, Howard, Diskin, Lynch, Giblin, Kenny, Magee, Meade and Waters2011) reported that a SNP in the IGF-I gene was positively associated (P < 0.05) with body condition score in Holstein–Friesian dairy cattle.
Table 7. Effect of the IGF-1 genotype on body conformation traits
*Significant (P < 0.05). Mean values with different superscripts differ significantly.
In conclusion, allele A of the IGF-1 gene was found to be associated with higher body weight and can be used in the selection criteria for improving the performance of Munjal flock. The positive effect of the IGF-1 gene on several conformational traits as observed in this study suggests that this area of the ovine IGF-I gene is particularly important and warrants further investigation.
Acknowledgements
The authors acknowledge the permission and facilities provided by the Vice Chancellor, LUVAS, Hisar for conducting this research work.
Declaration of competing interest
Authors declare that they have no conflict of interest.
Funding statement
The funds for the conduct of this research were provided by LUVAS, Hisar administration.
