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BY 4.0 license Open Access Published by De Gruyter Open Access September 14, 2023

Identification of genetic polymorphisms in the stearoyl CoA desaturase gene and its association with milk quality traits in Najdi sheep

  • Abdulkareem M. Matar EMAIL logo , Maged A. Al-Garadi , Riyadh S. Aljummah , Islem Abid and Moez Ayadi
From the journal Open Chemistry

Abstract

The nutritional quality of milk, which is determined by its fatty acid (FA) composition, and the candidate gene stearoyl-CoA desaturase (SCD) can be used in conjunction with these traits to improve the quality of dairy products. The aim of this study was to identify single nucleotide polymorphism (SNP) of the SCD gene and its associations with the milk composition and FA profiles of Najdi dairy sheep and 72 multiparous Najdi ewes under the same feeding system. Milk and blood samples were taken during the first lactation (<30 days in milk). Analysis and alignment DNA sequences identified SNP g.87C>A in the promoter and SNP g.1033G>A in exon 2 of the SCD gene. Association analysis showed that SNP g.87C>A was significantly associated (P ≤ 0.05) with palmitic acid (C16:0), alpha linoleic acid (ALA – C18:3-n3), linolenic acid (LA – C18:2-n6), and polyunsaturated fatty acid (PUFA). In addition, the SNP g.1033G>A showed a significant (P < 0.05) association with odd-chain FAs (heptadecanoic acid [C17:0] and heneicosanoic acid [C21:0]). The results showed that SCD gene may be important in the synthesis of PUFA and contributes to healthier dairy products. Overall, the Najdi breed SNP SCD gene showed that the association with milk traits is crucial, particularly with essential fatty acids: ALA-n3 and LA-n6 in milk fat.

1 Introduction

Recently, there has been increased interest in improving the compositional properties of milk in order to improve its nutritional value. Milk fat is controversial among health professionals as it is associated with an increased risk of atherosclerosis, cardiovascular disease, and hypertension [1]. Some consumers have reduced their consumption of sheep’s milk products such as cheese, due to their high levels of saturated fatty acid (SFA) and low level of polyunsaturated fatty acid (PUFA) (beneficial to health). In order to reduce the amount of SFA in the diet, it is recommended to increase the consumption of healthy foods such as foods containing omega-3 PUFAs or conjugated linoleic acid (CLA). The change in milk composition (MC) and fatty acid (FA) profile in milk depends on individual genetics, lactation stage, and feeding strategy [2]. Milk fat and long-chain fatty acid (LCFA) are mainly derived from diet; acetic acid results from ruminal microbial activity and body fat stores [3]. Many studies indicate that the genetic polymorphism of candidate genes, such as stearoyl CoA desaturase (SCD), fatty acid synthase (FAS), and acetyl COA carboxylase (ACAC), has an impact on milk quality [4]. Numerous mammals have been analyzed for their SCD genes, including mice [5], sheep [6], goats [7], and cattle [8].

A variety of nutritional, hormonal, and developmental factors play key roles in the regulation of the SCD gene (9-desaturases) at both the transcriptional and post-transcriptional levels [5]. SCD is the main enzyme responsible for introducing a double bond between carbons 9 and 10 of an SFA to produce a monounsaturated fatty acid (MUFA), which is considered a candidate gene as it alters the fat content and FA modulated in milk and meat [9]. MUFAs such as oleic acid C18:1 cis9 and vaccenic acid C18:1 trans11 are major biosynthesized substrates for the synthesis of PUFAs in the rumen biohydrogenation process and are almost exclusively represented by LA C18:2-n6 and ALA C18:3-n3 and complex lipids (triglycerides, phospholipids, and cholesterol esters), which serve as energy stores, biological membrane components, and signaling molecules [10]. In addition, oleic acid is important MUFA accounting for about 15–25% of total and most abundant FAs in fat milk. The extent of regulation of SCD is surprising, as is the fact that it exists in multiple isoforms [5]. The SCD gene differs from other genes expressed in the mammary gland in terms of the transcript with only six exons and five introns [11]. As a result, SCD may be required to maintain FA composition and membrane patterning, thus preventing the accumulation of SFAs that occur during active de novo synthesis in transformed cells [12]. It has been found that apoptosis requires an increase in SFA content and a decrease in MUFA content in cellular phospholipids along with a decrease in SCD or a decrease in membrane fluidity [13].

In dairy animals, the genetic improvement programs used are primarily aimed at improving milk quantity and quality. In the two decades of genomic research, some of the most important achievements in dairy animals have been the development of molecular markers to identify and differentiate animal populations and the discovery and characterization of DNA markers with broad coverage in the genome that are related to productive traits by genomic-wide association study [14].

The regions where these variations are found are called quantitative trait loci (QTLs) and are discovered by mapping the relationship between genotypes and phenotypes [14]. The discovery of QTLs has been relatively fruitful through the implementation of linkage and association methods [15]. However, because of their advantages, they have been increasingly replaced by single nucleotide polymorphisms (SNPs), which are more commonly used to conduct association studies, which have a higher level of precision using a larger number of markers, and do not require information about family or population structure [15].

Based on biological and physiological information, genetic polymorphism of candidate genes is suspected, and production traits are related to a variation in some genes. Therefore, correlation analysis is performed to test a specific genotype (SNP) or haplotype (a set of alleles), piece of DNA, and traits of interest (e.g., fat traits or milk production). In recent years, a strategy to discover new genomic variations that explain the phenotype of traits with economic importance has been successfully implemented [16]. The authors suggested the possibility of using genetic strategies to improve FA composition in sheep milk [17]. Najdi sheep are mainly distributed in the central and eastern areas of Saudi Arabia. The Najdi breed of sheep has proved satisfactory under better breeding and management systems, with high potential for milk production in intensive production [18]. No studies on the genetic polymorphism of SCD in Najdi breed sheep have been performed. Therefore, the main aim of this study was to identify genetic polymorphisms of SCD gene in Najdi sheep and their association with the MC and FA profiles of milk fat.

2 Materials and methods

2.1 Animal management and experimental design

A total of 72 ewes aged 2–2.5 years (multiparous) were selected for this study from Al-Khalidiyah sheep station in Riyadh. All ewes were multiparous, kept on the same farm to eliminate differences in management, and fed the same diet of alfalfa hay (30%) and concentrate (70%), with no supplements as shown in Table 1. The animals had free access to fresh clean water and ad libitum meals. All animals were tested for mastitis using the California mastitis test (CMT) to ensure they were healthy. The examined lactating Najdi ewes had a body weight of 61.71 ± 2.96 kg and a milk yield of 0.749 ± 0.347 L/day. In addition, the body condition score of 3.37 ± 0.55 was measured at the beginning of the study according to Buonaiuto et al. [19].

Table 1

Chemical composition and FA profile of traditional forage (alfalfa hay) and concentrate based on dry matter

Nutrition Alfalfa Hay 30% Concentrate 70%
Chemical composition%
Dry matter% 27.41 62.97
Crude protein% 11.19 9.11
ME 0.82 2.01
NDF% 13.29 26.11
ADF% 10.97 16.87
Ash% 3.138 8.44
Fat% 0.002 1.71
FA composition%
C6:0 1.14
C8:0 3.12 0.12
C12:0 0.48
C14:0 1.83 0.12
C16:0 22.66 15.04
C16:1 cis 9 1.29 0.18
C17:0 0.76 0.12
C18:0 6.26 2.29
C18:1 trans 11 1.29
C18:1 cis 9 10.20 23.70
C18:2 cis 9, 12 17.42 51.43
C20:0 3.72 0.39
C18:3 cis 9, 12,15 25.32 4.93
C22:0 3.92 0.29
C20:4 cis 7,10,13,16 1.87 0.10
SFA 43.89 18.37
UFA 56.11 81.63

ME: metabolism energy; NDF: neutral detergent fiber; ADF: acid detergent fiber; SFA: saturated fatty acid; UFA: unsaturated fatty acid.

2.2 Milk sampling and analysis

The ewes used in this study were in the start lactation (day 30 of lactation) and were milked once at 8 am. Milk samples (50 mL) were taken after morning milking and divided into two subsamples. Milk components including fat, protein, and lactose were analyzed immediately after milk collection using the Milko-Scan FT6000 (Foss, Hillerød, Denmark). Other samples were stored in the freezer at −20°C until fat extraction and analyzed for FA profiles as described by Luna et al. [20]. Extracted milk fat while FA methyl ester analysis procedure has been reported by previous studies [21,22]. The individual FA proportions were determined based on the ratio of the peak areas of the standard FA to the sum peak area for each FA in the milk fat sample. The desaturation index (DI) was calculated as follows: DI = 100 × [(cis 9 C14:1 + cis 9 C16:1 + cis 9 C18:1 + cis 9, trans 11 CLA)/(cis 9 C14:1 + cis 9 C16:1 + cis 9 C18:1 + cis 9, trans 11 CLA + C14:0 + C16:0 + C18:0 + trans 11 C18:1)] according to the study by Malau-Aduli et al. [23].

2.3 Blood sampling and extraction of DNA

Blood samples (10 mL) were collected into tubes containing ethylenediaminetetraacetic acid (EDTA) using a jugular vein puncture from each animal and stored at −4°C. For the extraction of genomic DNA from blood, we used the commercial kit (GFX genomic blood DNA 27-9603-01 100-purification kit -GE Healthcare) according to the instructions of the manufacturers. The concentration and purity rate (the ratio between the concentration of nucleic acids and the concentration of protein) of the samples were determined by spectrophotometry at 260 and 280 nm. In addition, their quality was assessed by electrophoresis on a 1% agarose gel. The degree of purity was measured in samples between optical density 1.8 and 2.2.

2.4 SCD gene amplification using PCR

The genes (promoter, exon 1, intron 1, and exon 2) were amplified by polymerase chain reaction (PCR) using specific primers targeting as shown in Table 2, according to García-Fernández et al. [6]. The reaction mix for the PCR was prepared in a final volume of 20 µL and contains 10 µL of Taq Hot Start Green Master Mix (Promega), 1 µL of each primer (forward 0.5 µL and reverse 0.5 µL), DNA (4 µL concentration 5%), and 4 µL of nuclease-free water. The amplification conditions were as follows: initial denaturation, 95°C for 5 min, plus 35 cycles (denaturation, 95°C – 30 s; alignment 58–61°C – 45 s, and extension 72°C – 40 s, and final extension 72°C – 10 min). The resulting amplicons were separated and visualized using 2% agarose gel electrophoresis in 1% Tris–borate–EDTA running buffer, at 80 volts for 40 min. Ethidium bromide was used for staining gels prior to sequencing.

Table 2

Primers used for sequencing (promoter, exon1, intron1, and exon 2) of the SCD gene

Target Sequence AnnealingTM (°C) PCR (bp)
Promoter F-AAATTCCCTTCGGCCAATGAC 60 527
R-TCTCACCTCCTCTTGCAGCAA
Exon 1 F-CTTTAAATCCCCAGCACAGC 61 317
R-CGCGGTGATCTCAACTCTTC
Intron 1 F-ACTTGCTGCAAGAGGAGGTGA 60 524
R-TGTGTAGGAGCTAGAGATCTGGA
Exon 2 F-TATTGGGACCAGGTCTAT 58 425
R-TATTGGGACCGGGTCTAT

2.5 Gene sequencing and analysis

DNA sequencing and purification of promoter, exon 1, intron 1, and exon 2 were performed at Macrogen Sequencing Service (Macrogen Inc., Seoul, Korea). Each sample was sequenced using the same amplification primers of each gene. The sequences of each gene were aligned with the similar sequences to determine the degree of similarity and to detect polymorphisms using the program Geneious 5.5.9, version Biomatters Ltd software. The sequences are referenced by GenBank accession numbers FJ513370.1 and GQ904712.2 compared to sequences obtained with the respective genes.

2.6 Statistical analysis

The frequency of allelic and genetic equilibrium in the population was estimated using the Hardy–Weinberg equilibrium and the chi-square test (https://wpcalc.com/en/equilibrium-hardy-weinberg/). The milk traits including fat, protein, lactose, and FA profiles were analyzed to determine their association with SNPs using the general liner model by PROC Mixed procedure in SAS 9.4 software (SAS Institute Inc.) [24]:

y i j k l m = μ + Age i + BI j + SNP k l + Animal m + e i j k l m ,

where y ijklm is the observed variable (MC and FA); µ is the mean; Age i is a fixed effect of age ith class of animal’s age at calving expressed in years for two levels (level 1 from 2 to 2.5 years and level 2 more than 2.5 years); BI j is a fixed effect of type of birth by two levels (single and twins); SNP jl is a fixed effect of the SCD genotype with three different alleles (AA, AB, and BB); Animal m is a random effect of ewes nested the genotype; and e ijklm is a residual error.

The SNPs in SCD gene association with MC and FA profiles in Najdi sheep’s milk fat were analyzed using the linear regression model by PROC REG procedure, using SAS 9.4 (SAS Institute Inc.):

y = β 0 + β 1 xi + ε ,

where y is the phenotypic vector, which is the MC and FA profile observation for each ewe and considered a dependent variable; xi is the independent variable; β 0 and β 1 are the regression parameters (SNP genotypes – AA, AB, and BB); and ε is the random error [25]. For two models, significance was declared when P ≤ 0.05.

2.7 Linkage disequilibrium (LD) estimation

The LD between SNP haplotypes was determined by Haploview 4.2 software (Broad Institute of MIT and Harvard, Cambridge, MA, USA).

3 Results

Genomic DNA from 72 samples was successfully amplified using specific primers that produced a fragment of 527 bp (promoter), 524 bp (intron 1), 317 bp (exon 1), and 425 bp (exon 2) (Figure 1). The sequence of the Najdi sheep promoter SCD gene with accession number (MW286839) has 100% homology compared to the reference sequencing, but the second accession number (MW286840) was unique in the Najdi sheep breed (Figure 2). In addition, the sequence of exon 2 in the SCD gene Najdi sheep with accession numbers (MW314007 and MW314008) showed 99.9 similarity to the sequence of exon 2 of the sheep SCD gene according to NCBI Reference (FJ513370.1).

Figure 1 
               PCR product in agarose gel electrophoresis (2%) of SCD gene (PR1: promoter; EX1: exon1; IN: intron 1 and EX2: exon2) in Najdi sheep.
Figure 1

PCR product in agarose gel electrophoresis (2%) of SCD gene (PR1: promoter; EX1: exon1; IN: intron 1 and EX2: exon2) in Najdi sheep.

Figure 2 
               Pairwise alignment of the promoter in Najdi sheep SCD gene sequences with GenBank accession number database.
Figure 2

Pairwise alignment of the promoter in Najdi sheep SCD gene sequences with GenBank accession number database.

A multiple sequence alignment of each fragment was performed to identify the two SNPs: the g.87C>A SNP and the g.1033G>A SNP, as shown in Figures 3 and 4. No difference in the sequences of Intron 1 and Exon 1 was found between all samples. All sequences were submitted to the GenBank database (accession numbers SNP g.87C>A: MW286839 and MW286840, SNP g.1033G>A: MW314007 and MW314008). The genotype and allele frequency analyzed are given in Table 3. Using the Hardy–Weinberg equilibrium, no significant deviation was found for any SNPs. Poor-quality sequences are excluded from alignment and analysis.

Figure 3 
               SNP 87C>A at promoter in SCD gene as shown in AA, CC, and AC in Najdi sheep.
Figure 3

SNP 87C>A at promoter in SCD gene as shown in AA, CC, and AC in Najdi sheep.

Figure 4 
               SNP 1033G>A at exon2 in SCD gene as shown in GG and GA in Najdi sheep.
Figure 4

SNP 1033G>A at exon2 in SCD gene as shown in GG and GA in Najdi sheep.

Table 3

Allele frequencies and genotype diversity in SNPs of the SCD gene in Najdi sheep

Allele frequencies Hardy–Weinberg frequencies Chi-squared (χ 2)
Promoter
g.87C>A C = 0.78 A = 0.22 CC, n = 44, *E = 43.55 CA, n = 24, E = 24.88 AA, n = 4, E = 3.55 0.09
Exon 2
g.1033G>A G = 0.86 A = 0.14 GG, n = 45, E = 46.28 AG, n = 18, E = 15.43 AA, n = 0, E = 1.28 1.75

*E: Expected Hardy–Weinberg frequencies.

The structure of the sequence promoter SCD gene in Najdi sheep contains two TATA boxes (TAAA) at 235–238 bp and (TAAAT) at 290–293 bp and only one stimulator protein 1 (SP1) (CTGCCAG) binding site at position 273–279 bp. Enhancer-binding protein (EBP) CCAAT was located at the first promoter 14–18 bp, and sterol regulatory element-binding protein (SREBP) TCAC was located at position 266–269 bp, as shown in Figure 2.

Analysis of preliminary data of the SNPs in the SCD gene of Najdi sheep showed no significant (P > 0.05) effect on the MC and FA profile; therefore, the results are not included in the tables. The association analysis for the SNPs in the SCD gene with MC and FA profiles of Najdi sheep is shown in Tables 4 and 5. In the promoter region of the SCD gene, SNP g.87C>A showed a significant association (P ≤ 0.05) with palmitic acid (C16:0), linoleic acid (LA-C18:2: n6), alpha-linolenic acid (ALA-C18:3: n3), and PUFA. In addition, the CC genotype showed high (P ≤ 0.05) levels of PUFA, LA, and ALA, while the CA genotype showed high (P ≤ 0.05) levels of palmitic acid (Table 4).

Table 4

Association analysis of SNP g.87C>A at the promoter of SCD gene on milk components (%) and FA profile (g/100 g FAs) in Najdi sheep

FA profile% Promoter–SNP g.87C>A P value
CC n = 44 CA n = 24 AA n = 4
C6:0 1.09 ± 0.07 1.02 ± 0.08 1.13 ± 0.13 0.36
C8:0 1.41 ± 0.12 1.35 ± 0.14 1.46 ± 0.22 0.51
C10:0 4.77 ± 0.46 4.79 ± 0.50 4.73 ± 0.81 0.74
C12:0 3.14 ± 0.30 3.30 ± 0.32 3.14 ± 0.50 0.98
C14:0 8.80 ± 0.38 9.48 ± 0.42 8.64 ± 0.76 0.21
C15:0 iso 0.48 ± 0.02 0.49 ± 0.02 0.47 ± 0.06 0.91
C15:0 0.95 ± 0.04 0.97 ± 0.04 0.94 ± 0.09 0.85
C16:0 26.44 ± 0.55b 27.75 ± 0.65a 26.35 ± 1.35c 0.053
C17:0 iso 1.02 ± 0.03 1.01 ± 0.04 1.02 ± 0.08 0.23
C16:1(n − 9) 0.74 ± 0.03 0.71 ± 0.04 0.69 ± 0.07 0.43
C16:1(n − 7) 0.30 ± 0.04 0.36 ± 0.05 0.32 ± 0.12 0.96
C17:0 antiso 0.69 ± 0.01 0.68 ± 0.02 0.71 ± 0.04 0.87
C17:0 1.02 ± 0.03 1.01 ± 0.04 1.02 ± 0.09 0.80
C17:1cis10 0.31 ± 0.02 0.31 ± 0.02 0.30 ± 0.3 0.86
C18:0 13.30 ± 0.54 12.75 ± 0.62 14.20 ± 1.16 0.58
C18:1(n − 9) 26.86 ± 1.24 25.83 ± 1.37 26.57 ± 2.40 0.59
C18:1(n − 7) cis-11 0.49 ± 0.02 0.50 ± 0.02 0.49 ± 0.04 0.56
C18:1 cis-13 0.32 ± 0.01 0.29 ± 0.02 0.29 ± 0.03 0.10
C18:1 cis-14 0.30 ± 0.01 0.28 ± 0.01 0.30 ± 0.03 0.17
C18:2(n − 6) trans 0.23 ± 0.01 0.22 ± 0.01 0.22 ± 0.03 0.25
C18:2(n − 6) cis 4.12 ± 0.18a 3.79 ± 0.19b 4.11 ± 0.34a 0.04
C19:1 0.09 ± 0.01 0.11 ± 0.01 0.09 ± 0.02 0.94
C20:0 0.30 ± 0.01 0.30 ± 0.01 0.30 ± 0.02 0.79
C18:3(n − 3) 0.84 ± 0.06a 0.79 ± 0.06b 0.67 ± 0.11c 0.04
C18:2 cis-9, trans-11(CLA) 0.77 ± 0.03 0.75 ± 0.03 0.70 ± 0.07 0.25
C21:0 0.08 ± 0.01 0.08 ± 0.01 0.07 ± 0.01 0.61
C22:0 0.13 ± 0.02 0.16 ± 0.02 0.14 ± 0.04 0.69
C20:4(n − 6) 0.32 ± 0.02 0.32 ± 0.02 0.37 ± 0.04 0.22
C22:4(n − 6) 0.04 ± 0.005 0.04 ± 0.005 0.05 ± 0.01 0.83
C22:5(n − 3) 0.17 ± 0.01 0.16 ± 0.01 0.15 ± 0.02 0.75
SFA 64.06 ± 1.30 65.54 ± 1.44 64.63 ± 2.55 0.33
UFA 35.94 ± 1.29 34.45 ± 1.44 35.36 ± 2.55 0.34
MUFA 29.41 ± 0.69 28.39 ± 1.05 29.67 ± 3.39 0.62
PUFA 6.57 ± 0.14a 5.94 ± 0.15c 6.28 ± 0.14b 0.02
DI 0.36 ± 0.01 0.35 ± 0.02 0.36 ± 0.02 0.15
MC
Fat% 3.70 ± 0.22 3.62 ± 0.28 3.89 ± 0.69 0.38
Protein% 4.48 ± 0.21 4.47 ± 0.22 4.95 ± 0.34 0.25
Lactose% 4.93 ± 0.22 4.81 ± 0.25 4.08 ± 0.47 0.59

a, b, c: there is a significant difference in means between rows with different superscript letters (P ≤ 0.05). SFA: saturated fatty acid; UFA: unsaturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; DI: desaturation index; CLA: conjugated linoleic acid; SE, standard error.

Table 5

Association analysis of SNP g.1033G>A at exon 2 of SCD gene on milk components (%) and FA profile (g/100 g FAs) in Najdi sheep

FA profile% Exon 2- g.1033G>A P value
GG; n = 45 AG; n = 18
C6:0 1.05 ± 0.04 1.17 ± 0.05 0.88
C8:0 1.36 ± 0.06 1.55 ± 0.11 0.95
C10:0 4.61 ± 0.22 5.37 ± 0.43 0.71
C12:0 3.12 ± 0.14 3.58 ± 0.31 0.61
C14:0 8.89 ± 021 9.54 ± 0.64 0.22
C15:0 iso 0.47 ± 0.02 0.49 ± 0.04 0.98
C15:0 0.94 ± 0.02 1.02 ± 0.06 0.31
C16:0 26.67 ± 0.35 27.99 ± 1.62 0.71
C17:0 iso 1.03 ± 0.02 1.08 ± 0.04 0.17
C16:1(n − 9) 0.73 ± 0.02 0.75 ± 0.07 0.81
C16:1(n − 7) 0.30 ± 0.03 0.51 ± 0.02 0.56
C17:0 antiso 0.68 ± 0.01 0.72 ± 0.02 0.11
C17:0 1.01 ± 0.03b 1.08 ± 0.04a 0.051
C17:1cis10 0.32 ± 0.01 0.30 ± 0.02 0.09
C18:0 13.27 ± 0.32 12.33 ± 0.56 0.93
C18:1(n − 9) 27.15 ± 0.63 24.12 ± 1.43 0.62
C18:1 cis-11 (n − 7) 0.50 ± 0.01 0.48 ± 0.03 0.68
C18:1 cis-13 0.31 ± 0.01 0.31 ± 0.02 0.83
C18:1 cis-14 0.30 ± 0.01 0.27 ± 0.02 0.17
C18:2(n − 6) trans 0.23 ± 0.01 0.22 ± 0.02 0.75
C18:2(n6) cis 3.97 ± 0.09 4.11 ± 0.33 0.38
C19:1 0.09 ± 0.01 0.10 ± 0.01 0.45
C20:0 0.30 ± 0.01 0.28 ± 0.01 0.92
C18:3(n − 3) 0.80 ± 0.02 1.00 ± 0.14 0.09
C18:2 cis9, trans11(CLA) 0.76 ± 0.02 0.73 ± 0.05 0.98
C21:0 0.08 ± 0.01a 0.09 ± 0.01b 0.03
C22:0 0.14 ± 0.01 0.13 ± 0.01 0.56
C20:4(n − 6) 0.33 ± 0.01 0.29 ± 0.03 0.39
C22:4(n − 6) 0.04 ± 0.004 0.05 ± 0.007 0.85
C22:5(n − 3) 0.17 ± 0.01 0.16 ± 0.03 0.91
SFA 63.99 ± 0.68 66.65 ± 1.62 0.51
UFA 36.01 ± 0.68 33.35 ± 1.62 0.51
MUFA 28.85 ± 0.67 29.76 ± 1.09 0.64
PUFA 6.27 ± 0.10 6.56 ± 0.10 0.21
DI 0.37 ± 0.01 0.34 ± 0.29 0.45
MC
Fat% 3.74 ± 0.21 3.79 ± 0.71 0.12
Protein% 4.54 ± 0.10 4.40 ± 0.20 0.87
Lactose% 4.76 ± 0.13 5.14 ± 0.33 0.43

a,bValues having different superscripts within a row are significantly different at P ≤ 0.05. SFA: saturated fatty acid; UFA: unsaturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; CLA: conjugated linoleic acid; DI: desaturation index; SE: standard error.

On the other hand, SNP g.1033G>A showed a significant (P < 0.05) effect on odd-chain fatty acids (OCFAs) such as heptadecanoic acid (C17:0) and heneicosanoic acid (C21:0), although there is no relationship between this SNP and other FAs of milk fat. The AG genotype of the SNP g.1033G>A showed high levels of heptadecanoic acid and heneicosanoic acid compared to the GG genotype as shown in Table 5.

In particular, as shown in Tables 4 and 5, there is no significant association between DI and SCD polymorphism. In contrast, there was a weak linkage (22 %) between two SNPs in the Najdi sheep SCD gene as shown by LD analysis of the SCD gene promoter and exon 2.

4 Discussion

The SFAs (palmitic acid and stearic acid) are the main substrates for the action of SCD, a microsomal enzyme that catalyzes the desaturation of various acyl-CoA in cis configuration between carbon atoms 9 and 10, hence called 9-desaturase [26]. The SCD plays a key role in the biosynthesis of several MUFAs, and a variation in the SCD sequence has been shown to affect the milk fat content [9]. In addition, the SCD gene is a promising candidate gene for improving the MUFA amount of dairy products [27]. To this end, the aim of this study was to identify the genetic polymorphism of the SCD gene and its relationship with the MC and FA profiles of Najdi sheep’s milk. Additionally, this can help select ewes’ genotypes that produce healthy dairy products with minimal SFA.

The partial sequence of the Najdi sheep SCD gene, 1335 bp, was analyzed and compared to the previously reported sheep SCD gene (GenBank accession numbers: FJ513370, GQ904712.2) [6,28,29]. The genotype distribution of the sequence promoter SCD gene showed that the C allele is the most common in the Najdi sheep breed. The structure of the SCD gene promoter in Najdi sheep showed two TATA boxes, which are also found in river buffalo. In contrast, the river buffalo had two SREBP and four Sp1 [30], possibly reflecting high lipid metabolism and increased fat synthesis in the buffalo milk. As reported by Pauciullo and colleagues [30], transcription factors such as TATA, SREBP, EBP, and SP1 play key roles in the regulation of lipid metabolism, adipogenesis, and adipocyte gene expression.

In the current study, the SNP g.87C>A identified in the Najdi sheep SCD gene was identical with the results by Aali et al. [28] on Lori-Bakhtiari (fat-tailed), Zel (thin-tailed), and Zel-Atabay crossbred sheep (with medium-fat-tailed sheep). In addition, the SNP g.1033G>C with two (GG and AG) was identified for the first time in exon 2 of the SCD gene in Najdi sheep. A recent study reported an incidence of SCD gene exon 3 SNP c.20393081T>A identified in Awassi sheep with two polymorphisms, homozygous (T/T) and heterozygous (T/A) [31]. Other study on Iranian tailed sheep reported that the SCD gene sequence of a SNP g.379A with two allelic variations was detected in the untranslated region – 5′-UTR [32]. In addition, Churra sheep showed SNP g.31A>C in promoter and two SNPs in intron 2 of SCD gene [6]. In contrast, a study on buffalo showed that the SNP g.133A>C is located in the promoter of the SCD gene [11]. However, in Hanwoo Korean Cattle, three SNPs g.10153A>G, g.10213T>C, and g.10329C>T were identified in exon 5 SCD gene [33].

Association analysis in this study showed that the g.87C>A SNP was significantly associated with palmitic acid (C16:0), LA (C18:2-n6), ALA (C18:3-n3), and PUFA. The SNP in the SCD gene showed a significant association with MC and FA in milk fat similar results reported by García-Fernández et al. [10], in Spanish Churra sheep, that established the SNP_SCD01, in the promoter SCD gene, was a significant association with milk fat percentage and LA (C18:2-n6). Aali et al. [32] found in Chall and Zel lambs that SCD genotypes A and B have a significant association with LA (C18:2-n6), arachidonic acid, and eicosapentaenoic acid in LD muscle. In Hanwoo Korean Cattle, SNP genotypes (GA, CT, and CT) in exon 5 of SCD gene revealed high levels of oleic acid (C18:1 cis9) and MUFA in intramuscular fat [33]. However, in Japanese black cattle, allele V in the SCD gene had high levels of MUFA (C14:1 and C18:1) compared to allele A, which had a high proportion of longissimus thoracis, muscle SFA [34]. In contrast, a study on Purebred Santa Inês, Black Dorper, White Dorper, Texel, Lacaune, and East Friesian sheep found no influence of genetic polymorphism of the SCD gene on the FA profile of meat [35].

As shown in Najdi sheep, the CC genotype had high levels of PUFA, LA, and ALA, while the CA genotype had high levels of palmitic acid (C16:0). In a study on Polish Holstein Friesian cows, the SNP g.293AV of the SCD gene was detected and it was shown that heterozygous cows have high levels of C8:0 and C10:0 compared to homozygous cows [36]. Likewise, the milk fat content of oleic acid (C18:1cis 9) and MUFA was higher in genotype AA than in VV of Italian Holstein cows [37]. In contrast, homozygous Alpine goats in the SCD gene had the highest PUFA and total CLA content, but this genotype had the lowest milk production [38]. In the current study, in Najdi sheep, the SNPs of SCD gene have no effect on CLA content; this finding agreed with the results of Moioli et al. [39]. According to previous reports, the disparity is explained by the genetics of the phenotypes tested and the effects of candidate gene SNPs vary by population.

Furthermore, in the current study, the SNP in exon 2 of the Najdi sheep SCD gene showed a significant association with OCFAs (heptadecanoic acid [C17:0] and heneicosanoic acid [C21:0]). As shown, the heterozygous ewes with AG genotype had higher levels of heptadecanoic acid and heneicosanoic acid than the homozygous ewes. A recent study of the Awassi sheep SCD gene, the TA and TT genotypes, showed a significant association with monounsaturated FAs and intramuscular fat [31]. In this context, the goats’ breeds Murciano, Granadina, and Malaguea found an association between the genetic variability of the SCD locus and the levels of lactose, stearic acid, PUFA, and CLA [40]. On the other hand, in river buffalo, the AC and CC genotypes of the promoter SCD gene were found to have a strong association with MUFA, especially with oleic acid (C18:1 cis 9) [11]. However, Holstein Friesian cows with the SCD gene V allele showed a higher proportion of capric acid (C10:0), lauric acid (C12:0), myristic acid (C14:0), palmitoleic acid (C16:1), and CLA [41]. It was also found that SCD alleles have a significant effect on C14:1 and C10:1 FA in Jersey and Valdostana breeds [39]. This suggests that the FAs are generated by de novo synthesis and SCD desaturation is required for the production of CLA in most mammalian tissues through the conversion of vaccenic acid (C18:1cis 11) [42,43]. In general, as we mentioned when discussing our results, results may vary by breed and species. However, we used their results to acquire a more detailed understanding.

The previous reports explained the activity of the endoplasmic reticulum-bound enzyme SCD, which can produce endogenous monounsaturated MUFA [9]. Due to the incomplete bio-hydrogenation process of the rumen, some of the FAs that reach the mammary gland are unsaturated FAs [44]. Furthermore, SCD is the primary enzyme responsible for MUFA synthesis, mainly via the introduction of a double bond at the 9-position of myristoyl, palmitoyl, and stearoyl-CoA [45]. The desaturation of C14:0 and C16:0 is considered an important signal because C14:1 and C16:1 in milk are produced by SCD in the mammary gland, while the precursors of milk fat derivatives derived from dietary or body-derived FAs activate lipid metabolism [46].

The lack of an association between SNPs in the SCD gene and the DI in this study suggests that many other dominant variables regulate milk FA. This was consistent with that observed in previous studies on SCD gene expression [11]. In addition, SCD mRNA showed a non-significant correlation with the Δ9-desaturase index in dairy cows [47]. In contrast to the results of this study, a positive correlation was observed between the SCD gene with oleic acid [48] and the DI in lactating sheep and goat [49]. SCD mRNA expression decreases after 2 months of milking, showing the role of SCD in different stages of lactation [47]. Marchitelli et al. [50] pointed out that the lack of association between the SCD gene and the proportion of most FA in milk could be due to several factors affecting the desaturation activity of the mammary gland, such as uptake and turnover of the FA, or possibly, the presence of other polymorphisms can affect the examined traits.

5 Conclusions

In this study, two SNPs were identified in the Najdi sheep SCD gene, SNP g.87C>A and SNP g.1033G>A. A significant association between SNPs of SCD gene and ALA (C18:3 – n3), LA (C18:2 – n6), PUFA, and OCFA can be used as an indicator to improve FA profile in milk fat of Najdi sheep breed. The results of the current study indicate that the genetic polymorphisms of the SCD gene need to be further investigated in a large number of animals to provide a theoretical basis for the MC and FA composition of sheep’s milk.

Acknowledgements

The authors extend their appreciation to the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia, for funding this research work through project no IFKSUOR3–554–1.

  1. Funding information: This research was funded by the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia, through project no. IFKSUOR3–554–1.

  2. Author contributions: R.S.A. and A.M.M. – conceptualization; A.M.M., M.A.A. and R.S.A. – methodology; A.M.M. and M.A.A-G. – software; R.S.A. and A.M.M. – validation; R.S.A. and M.A.A-G. – formal analysis; A.M.M. and R.S.A. – investigation; A.M.M., I.A. and M.A.A-G. – resources; R.S.A. and A.M.M. – data curation; A.M.M. – writing – original draft preparation; A.M.M. and R.S.A. – writing – review and editing; R.S.A.; supervision, R.S.A. – visualization; R.S.A. – project administration; R.S.A. and A.M.M. – funding acquisition. All authors have read and agreed to the published version of the manuscript.

  3. Conflict of interest: The authors declare no conflict of interest.

  4. Ethics statements: All experimental procedures were performed in strict adherence to the guidelines of the Saudi Arabia Regulations for the Use and Care of Animals in Research and approved by the Research Ethics Committee at King Saud University (KSU‐SE‐20‐19).

  5. Data availability statement: The datasets generated during and analyzed during the current study are available from the corresponding author on a reasonable request.

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Received: 2023-04-02
Revised: 2023-07-10
Accepted: 2023-08-20
Published Online: 2023-09-14

© 2023 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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