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Introduction
Milk is a liquid food of easy access with plenty of nutrients such as carbohydrates, proteins, minerals and vitamins (Drewnowski and Fulgoni 2008). In ruminants, the four caseins (⍺s1, β, ⍺s2 and к) represent about 80 % of milk proteins (Ramunno et al. 2004), and к-casein accounts for around 15 % of total caseins. к-casein is one of the most important proteins joined physically to the functional role in micelle formation and stabilization, determined by its size and function (Rijnkels et al. 2003). In addition, к-casein is different to other caseins due to its solubility in a wide interval of concentration of calcium ions which contain a c-terminal hydrophilic region (Yahyaoui et al. 2001). One of the most important characteristics of к-casein is its influence on the size of milk micelles, which are smaller, which has an impact on the coagulation features of the milk, reflected in a stronger curd and retention of a major amount of substances increasing cheese yield (Ahmed 2011).
In Mexico and other countries, goat milk is mainly used for cheese production and confectionery. The economic worth of this product depends mostly on the amount of total proteins and fats in the milk (Montaldo and Manfredi 2002). Therefore, the variable composition which determines cheese making depends on casein variability and hence the genetic variants that can affect the properties of this milk product (Martin et al. 2002, Barillet 2007).
A total of 14 genetic variants have been identified in the к-casein (CSN3) gene in different breeds of domestic goats (Jann et al. 2004, Prinzenberg et al. 2005); furthermore, other studies have shown that the number of alleles identified in the domestic goat is actually 16 (Yahyaoui et al. 2001, Angiolillo et al. 2002, Yahyaoui et al. 2003, Jann et al. 2004). From these variants, 13 are protein variants and 3 are silent mutations, with a total of 15 polymorphic sites in the exon 4 of the CSN3 gene (Kumar et al. 2009).
Different studies (Chiatti 2007, Caravaca et al. 2009, Caravaca et al. 2010) have shown that some variants have a significant effect on the production and nutritional composition of the milk. In a study conducted by Caravaca et al. (2009) in the Murciano-Granadina breed, it was found that the goats with the B allele show higher values of protein and casein percentages than the ones with the A allele. Therefore, their Identification in breeding populations is important and fundamental for the implementation of assisted selection strategies complementing traditional methods of genetic improvement. The Saanen is one of the most popular goat breeds in the world, due to its great performance in milk production and milk composition traits (Scheepers et al. 2010). In Mexico, it is one of the breeds with major inventory. The objective of the present study is to estimate the genotypic and allelic frequencies of CSN3 gene variants and to evaluate their association with milk yield and composition in Saanen breed animals.
Materials and methods
Sample source
Hair follicles of 130 Saanen breed animals were collected from La Pastorcita farm located in Apaseo el Grande, Guanajuato, located geographically at 20° 33' 01,81” North latitude, 100° 41' 19,80” West longitude and at an elevation of 1771 m above sea level. The zootechnical purpose of this farm is the production of breeding animals and milk. The origin of genetic material (i.e. semen) is mainly France, Canada and the United States, whereas stud animals are exclusively from the United States.
Goats were maintained under intensive conditions and feeding of animals was based on alfalfa hay, corn silage and a commercial concentrate with an 18 % level of raw protein. The procedure for the recording of productive indicators consisted of the collection of milk samples by a specialized technician every 28 days, in two lactation periods. A Lactoscan MCC (Milkotronic Ltd) was used to determine the components of protein, fat, lactose and total solids. The animals were maintained in a bodily condition of 3.5 to 4.5 (scale from 1 for thin goats to 5 for heavy goats). Data was revised and only animals with complete kidding date records from 2014 to 2015 were included in the study.
DNA extraction and identification of variants in the CSN3 gene
DNA extraction was achieved using the GenElute (Genelute Mammalian Genomic Miniprep, Sigma-Aldrich, Cat. G1N350). All samples were genotyped using specific probes and primers to discriminate genotypes of the A, B and C variants of the CSN3 gene were designed (Table 1). Primers and probes for a allelic discrimination assay were synthetized, using the previously reported sequences of the CSN3 gene variants (GenBank Accessions: AF485339, AF485340 and AF485341). Each assay was analyzed by 96-well optic plaques using Applied Biosystems 7500 Real Time PCR System (Applied BiosystemsTM) under the following conditions: one cycle of 2 min at 50 °C and 10 min at 95 °C, followed by 40 two-step cycles of 15 s at 92 °C and 1 min at 60 °C. For the genotyping of each genotype, the 7500 Real-Time PCR Products software package, version 2.0.5 (Applied BiosystemsTM) was used; each sample was verified through visual analysis to avoid false allele assignations.
Statistical analysis
An analysis of association of the genotypes of the variants identified in the CSN3 gene was performed for milk production per day (MPD, kg), protein (PR), fat (F), lactose (LC) and total solids (TS) percentages, at the 69th day of lactation. A general linear model was fitted including the fixed effects of year, month, genotype and goat age as linear covariates, and random effects of sire and error. No interaction effects among fixed traits were observed and were excluded from a final model. Animals with AA genotype were excluded from the analysis since no productive data was available for them. Means comparison was performed using a Tukey-Kramer adjustment test by PDIFF statement. All analyses were computed using SAS software v. 9.0 (SAS Institute, Cary, NC, USA).
Results
The overall means for MPD, PR, F, LC and TS were 3.34 kg, 2.74, 5.89, 4.38 and 12.08 %, respectively. The genotypic and allelic frequencies of CSN3 are presented in Table 2. Three variants in the studied population of Saanen goats were identified, with B allele being the most frequent (0.64), followed by A (0.23) and C (0.13). Five genotypes were identified, with the most frequent genotype being BB (0.46), followed by AB (0.35) and CC (0.11), while the other two genotypes were found in very low frequencies.
In relation to the genotype effect on the production traits and milk composition, CSN3 only showed a significant effect on the PR of the Saanen goats (p = 0.006). Results showed that the individuals with AC, BB and CC genotypes produce more protein in their milk (Table 3). However, the AC genotype doesn’t show significant differences with the AB genotype. The least square means showed that the animal carriers of AC, BB and CC genotypes have similar levels of protein in their milk.
Table 3. Least square means ± standard errors of milk yield and compositional traits in Saanen goats by kappa casein genotype effect.
MPD = Milk production per day; PP = Protein percentage, FP = Fat percentage, LP = Lactose percentage; TS = Total solids. a,b Means with different superscripts are significantly different (p < 0.01).
Discussion
The CSN3 gene is characterized by the presence of seven allelic variants, of which A, B and C have been reported in the Saanen breed, with the A and B variants being more frequent (Yahyaoui et al. 2003, Chessa et al. 2003). Yahyaoui et al. (2001), in a study conducted in Spain in the Saanen breed, found similar allelic frequencies, with a higher frequency for the B allelic variant. Previous studies have associated this variant with the protein and casein contents in milk, and the goats which have the B allele show higher values in the content of these nutrients compared to those of other variants (Caravaca et al. 2009). Similar results were reported by Kummar et al. (2009) and Scheepers et al. (2010), who, after evaluating polymorphisms of the CSN3 gene in different goat breeds of Asia, Africa and Europe, found an allelic frequency to the B allele of 0.66 and 1.00, respectively.
On the other hand, the A allele frequency was similar to that reported by Reale et al. (2005) a in research conducted in a Jónica goat population of southern Italy, with a frequency of 0.25. Similarly, higher frequencies of the A allele with 0.92, 0.94, 0.92, 0.75 and 0.93 have been reported in Saanen, Camosciata, Verzaschese, Orobica and Frisa breeds, respectively (Chiatti et al. 2005) in Italy. Probably the higher proportion of the A allele can be explained by the genetic flow provided by the selection of carrier animals directly or indirectly, which could be segregating this allele to the new generations. Regarding the C allele its incidence in this study was low (0.13), which is similar to that reported by Yahyaoui et al. (2001, 2003) in the Murciano, Granadina, Canaria, French Saanen and Italian Teramana breeds, among others. Landi et al. (2011) mentioned that in future generations this mutation could disappear because it is found in very low frequencies.
The BB genotype has been associated with a higher content of proteins and casein (Chiatti et al. 2005, 2007). The favorable effect of the BB genotype in the CSN3 gene on protein could be linked to the amino acid differences in the mature protein, which possibly affects the biological properties of к-casein (Meisel 2005) and its biochemical interactions with the other fractions in the casein micelles (Lucey et al. 2003). It has also been suggested that the genetic variation in CSN3 implies that the mature protein could be associated with other polymorphisms in the non-coding sequences (promoter), which could be mutations that cause different expressions among some alleles, such as two main alleles in the CSN3 gene in bovine cattle (Martin et al. 2002). Existing evidence has shown that when a null mutation was introduced in CSN3 and caused the destabilization of the casein micelles, there was a failure in the lactation process (Shekar et al. 2006).
In the present assessment, the BB genotype confirmed its association with a higher percentage of protein. However, its effect was lower than that reported by Caravaca et al. (2010) who, after evaluating the effect of CSN1S1 and CSN3 genotypes on the coagulation properties of the milk in Murciano-Granadina goats in Spain, reported an average 3.61 % effect of this variant on PB. Furthermore, Caravaca et al. (2010) found a similar effect as the present research, with an average 2.94 % effect on the BB genotype (Chiatti et al. 2007), in an Orobica population in Italy.
Some implications in the evidence found here are directly related to the productive purpose of the studied farm and the purebred breeding animal production as brood stock. All the animals that carry AC, BB and CC genotypes might contribute with favorable performance in protein percentage, which will be reflected by the improvement of industry cheese production. The interest in the use of CSN3 genes associated with milk production and composition traits has been strongly related to the potential of improving the global efficiency in different sectors of the dairy products industry, due to the increasing scientific evidence of association of genetic variants with the improvement of the physicochemical properties of the milk and cheese quality (Martin et al. 2002, Ng-Kwai-Hang 2006).
The identification of variants significantly associated with milk composition traits can be proposed to be implemented in marker-assisted selection strategies. Genotyping information can be used to increase the variant frequency positively associated with a trait, through the selection of animals which carry the copies of the favorable variant. However, it is important to consider that the results of association could be validated in larger populations and verified in local populations, since purported associations with economically important traits can change according to the selection history of the studied populations (Parra-Bracamonte et al. 2007).
Conclusions
The B variant genotype of the CSN3 gene is associated with the milk protein percentage of Saanen goats. The validation of this evidence in commercial populations could support strategies to improve the protein in milk and contribute to the industry with better cheese production. The segregation of more frequent and favorable alleles which are associated with a particular trait on the nutritional quality of the milk could be a main objective for improving the economic value of the Saanen breed in Mexico.
