Introduction

Many agricultural traits are complex and highly influenced by environmental and genetic factors [1]. For domestic animals to be more productive, it is imperative to understand the genetic basis of these traits [2]. Moreover, genetic studies on sheep breeds revealed gene candidates associated with productivity [3]. Among candidates for productive traits is the adiponectin gene (ADIPOQ) [4]. This gene is positioned on the bovine chromosome (BTA) 1 [5] and chromosome 1q27 in sheep. It consists of three exons and two introns (NCBI Reference Sequence NC_019480.2). It encodes adiponectin (MW 30 kDa and 244 amino acids), one of several biologically active adipokines secreted from white adipose tissue [6]. Adiponectin plays a central role in maintaining energy homeostasis, and it has a newly identified role as a “starvation gene” [7]. Additionally, studies suggest that adiponectin improves insulin sensitivity and glucose tolerance through crosstalk with insulin [8, 9]. It appears that adiponectin is involved in a variety of tissue-specific signaling pathways. Muscle fatty acid oxidation and glucose uptake are enhanced by adiponectin through AMP-activated protein kinase (AMPK) (9). Adiponectin stimulates the proliferation of skeletal muscle via the p38-AMPK pathway, which can influence carcass characteristics [10]. Furthermore, adiponectin inhibits the accumulation of ectopic lipids in adipocytes and is negatively correlated with body fat, which affects meat quality traits [11].

Using these markers effectively requires an investigation of polymorphisms in candidate genes that affect traits of economic importance. Several polymorphisms within the adiponectin gene have been reported in domestic animals concerning body weight and productivity. It has been shown that the ovine ADIPOQ gene has been implicated in low birth weight and metabolic disorders in Merino rams [12]. In addition, the ADIPOQ gene polymorphism affects muscle area and fat thickness in Angus cattle [13], indicating that it can be beneficial for animal production. There is also evidence that this gene affects goat growth traits, where a novel BC140488:m.832T > A polymorphism in the caprine ADIPOQ gene showed significant associations with chest circumference [14]. Choi et al. [15] found that three genetic variants (g.81966235CNT, g.81,966,377 TNC, and g.81966364DNI) in Hanwoo cattle are associated with marbling score and carcass traits. Moreover, ADIPOQ polymorphisms have been linked to the sheep fatness trait [16]. Although these findings are based on polymorphisms in an ADIPOQ gene, no reports have identified concerning Awassi sheep productivity.

Materials and methods

Animals and experimental design

The study was approved by the research committee at Al-Qasim Green University and carried out according to international animal care and use standards (Agri no. 020,7,18) from July 2020 to March 2021. Two hundred sexually mature ewes were included, aged 2.5 to 5 years, not pregnant, and not lactating. In this study, ewes were randomly selected from two stations (Babylon and Karbala). All of the ewes were fed seasonal grass, concentrated food, and fresh water ad libitum. The measurements of live body weight and body measurements were taken phenotypically.

DNA extraction, genotyping, and sequencing reaction

A salting-out technique was employed to isolate genomic DNA from whole blood [17]. To determine the quality of the DNA samples and as a template for polymerase chain reaction (PCR), a NanodropµLITE spectrophotometer (Biodrop, UK) was used. A PCR reaction containing 10 pmol of each primer, 50 ng genomic DNA, 50 µM dNTPs, 10mM Tris-HCl (pH 9.0), 30mM KCl, 1.5mM MgCl2, and 1U Top DNA polymerase was performed. The ADIPOQ gene (exon 1) primer was designed using the ovine sequence in GenBank (NC_019480.2) and Primer-BLAST. A forward primer and a reverse primer were designed to be 5 ́- CCTGTATCTCT CCCCACCCT − 3 ́ and 5 ́- GTGTGATGCCTGCAGCTCTA − 3 ́ respectively. A PCR reaction involving four minutes of denaturation at 94 °C, followed by 35 cycles of 30 s denaturation at 94 °C, annealing for 30 s at 57 °C, extension for 30 s at 72 °C, and extension for 10 min at 72 °C. An agarose gel (2%) was used for the visualization of the PCR products [18].

In the following step, PCR-SSCP (single strand conformation polymorphisms) was performed to genotype the samples [19]. For each PCR amplicon, SSCP denaturing-loading buffer was added in equal quantities. After being denatured for seven minutes, samples were cooled on frozen ice for 10 min, then transferred to polyacrylamide gels (10%) in a 0.5X TBE buffer. Electrophoresis was conducted for four hours at room temperature using 200 mA and 100 V. The gels were stained using the rapid protocol according to Byun et al. [20]. All samples were sequenced by Macrogen (Geumchen, Korea), then edited and visualized using BioEdit 7.1 (DNASTAR, Madison) and SnapGene Viewer ver. 4.0.4(https://www.snapgene.com). To verify the novelty of the observed variants of ADIPOQ, Ensemble genome browser 96 was used (https://asia.ensembl.org/index.html).

Statistical analysis

Analyses of the ADIPOQ gene’s genetic diversity were conducted utilizing the PopGen32 software, v. 1.31. A Chi (χ2) test was employed to verify deviations from the Hardy-Weinberg Equilibrium (HWE). The ssociation between variants of the ADIPOQ genotype and traits of interest was calculated using the following SPSS statistical model (version 23.0):

$$Y_{ijk} = \mu \; +\; G_{i}\; +\; P_{j}\; + \; e_{ijk}$$

Where: Yijk = phenotype characteristics, µ = the mean of all traits, Gi = fixed effect of ith genotypes (i = CC, CA, AA) Pj = fixed effect of jth parity (j = 1, 2, 3, 4), and eijk = random error. The Tukey-Kramer test was used to compare means. The correlation coefficient was calculated using a Pearson correlation coefficient, and (P < 0.05) was set as the significance level. Preliminary statistical analysis concluded that factor interaction, seasonality, station, and nutrition did not significantly influence the traits studied, so these variables were excluded from the model.

Results

Genotyping, sequencing, and genetic diversity analysis of ADIPOQ gene

An ADIPOQ gene fragment of 368 bp along with its flanking regions was screened using PCR design (Fig. 1, A). Within the 368 bp amplicon of exon 1, three distinct PCR-SSCP were detected (Fig. 1, B). One of the SSCP variants contained the c.198,473,337 C > A SNP, verifying the heterogeneity in exon 1 based on the sequencing reactions. Using the c.198,473,337 C > A substitutions, this variant was assigned the CC, CA, and AA genotypes, for homozygous C/C and A/A and heterozygous C/A patterns (Fig. 1, C). Analyses of the ADIPOQ gene diversity in Awassi ewes demonstrated that genotype CC had the highest prevalence of 0.48 (n = 97) over genotypes CA (n = 66) and AA (n = 37) (Table 1). Furthermore, the Chi-square test indicated a significant deviation from HWE for polymorphisms of the ADIPOQ gene at the c.198,473,337 C > A SNP locus (P < 0.05).

Fig. 1
figure 1

Analysis of the ADIPOQ gene in the Awassi sheep. (A) PCR products amplifications of the ADIPOQ gene electrophoresed on agarose gels. B) SSCP non-denaturing polyacrylamide gel electrophoresis of PCR products of the ADIPOQ gene (exon 1) determined CC, CA, and AA genotypes in the Awassi ewes. C) DNA sequencing revealed a mutation at the c.198,473,337 C > A SNP.

Full size image
Table 1 Genetic diversity of the ADIPOQ gene in Awassi ewes detected by PCR- SSCP
Full size table

Association analysis of ADIPOQ genotypes with productive traits of Awassi ewes

Live body weights were significantly different (P ≤ 0.05) between the three ADIPOQ genotypes (Table 2). AA genotypes were typically heavier (51.01 ± 1.31) (Kg) than CC and CA genotypes. In terms of morphometric traits, the AA genotype in ewes was associated with a longer body length (73.54 ± 1.25) (cm), hip height (73.33 ± 1.14) (cm), and chest width (25.15 ± 0.41) (cm) compared to those with the CC and CA genotypes (Table 2). Furthermore, the AA genotype correlated strongly with body weight and measurements shown in Table 3.

Table 2 The association of the ADIPOQ genotypes with the live body weight, age and body measurement of Awassi ewes
Full size table
Table 3 Correlation between ADIPOQ genotypes and other variables in Awassi ewes
Full size table

Discussion

The CC genotype was most prevalent in the ADIPOQ gene population (0.48, n = 97), and the AA genotype was less prevalent (0.19, n = 37). The Chi-square test showed significant deviations from the HWE for polymorphisms at the c.198473337 C > A SNP within the ADIPOQ gene (P ≤ 0.05). In livestock, several authors reported genetic polymorphisms in various fragments of the ADIPOQ gene. A study by Pandy et al. [21] demonstrated three genotypes in the promoter region of the bovine ADIPOQ gene using PCR-RFLP for Indian Sahiwal Cattle. Shin and Chung [22] also determined three genotypes – CC, CT, and TT – within the ADIPOQ promoter region in the Hanwoo cattle population using TsaI/PCR-RFLP. According to An et al. [4], the ADIPOQ gene is polymorphic in two exon 1 and 3 and intron 2 in Romney lambs from New Zealand. Furthermore, An et al. [23] explored 13 SNPs identified in the ADIPOQ exon 1 and exon 2 regions in the Romney lambs. The A1 and B1 alleles dominated in exon 1, whereas A2 and D2 dominated in exon 2, and their frequencies differed. Recently, Pandey et al. [5] explored the SNPs located in the ADIPOQ gene promoter in Indian dairy cattle and determined three genotypes, the most common genotype being CT (62.32%), second the CC (24.64%), and finally TT (13.04%) genotypes. Despite this, very limited information has been found about ADIPOQ polymorphism in Awassi sheep.

Regarding the association analysis, the three genotypes showed significant differences (P ≤ 0.05) in live body weight and morphometric traits. Ewes with AA genotypes have higher live body weight, body length, hip height, and chest width than those with CC and CA genotypes. Physiologically, adiponectin is necessary to maintain energy homeostasis [7]. Moreover, adiponectin synergizes with insulin signaling in order to improve insulin sensitivity and glucose tolerance in different tissues [9]. This protein stimulates AMPK to increase the oxidation of fatty acids and glucose in skeletal muscle and stimulates the proliferation of skeletal muscle tissue through the p38-MAPK pathway, which may have effect on these productive traits of sheep [10]. In livestock, ADIPOQ gene variability determines the expression of productive traits. Genetic variability in this gene could also affect productivity and reproductive traits [4]. Polymorphism analysis of the ADIPOQ gene is conducted concerning its association to the thickness of carcass fat, meat marbling, and muscle area of the ribeye in cattle [21], with the growth and carcass traits in New Zealand (NZ) Romney lambs [4], and with productivity and reproduction in Indian dairy cattle [5]. The ADIPOQ polymorphisms in Chinese cattle are associated with growth traits (body weight and measurements) as reported in a previous study by Zhang et al. [24]. The AA genotype also correlates significantly with body weight and dimensions. The morphometric indices and live weight of animals are good indicators of animal utility. This study is consistent with the study conducted by Zhang et al. [25], which showed a significant correlation between ADIPOQ polymorphism and body measurements in seven Chinese cattle breeds.

Conclusions

The ADIPOQ gene regulates several productive traits. Sheep with the AA genotype have heavier and larger body dimensions, thereby improving their productivity and reproducibility. Further studies are required in other breeds to prove the results.