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The αs2-casein (CN) is a milk protein fraction encoded by the CSN1S2 gene. Previous studies on dromedary milk proteins mainly focused on the other three fractions (αs1-, β- and k-CN), and, although there is globally growing interested in camel milk, studies focusing on αs2-CN are very limited. In this respect, no information has been reported on retrotransposons (RTs). These repeats, also known as Interspersed elements (INEs), are informative genetic markers useful as phylogenetic tools for clustering, evolutionary and population structure studies, rather than for the setup of food traceability methods. Aim of this study was to identify and characterize INEs in the dromedary CSN1S2 gene. Analysis has been carried out using RepeatMasker as bioinformatic tool. Three long interspersed elements (LINEs) were found in introns 1, 10 and 11. The first and the last elements are truncated LINEs 2, respectively 50 bp and 97 bp long. Conversely, the repeat in intron 10 is 149bp long and it is a truncated LINE 1. In addition, three short interspersed elements (SINEs) have been found in introns 8, 9 and 16, with a size of 190bp, 149bp and 207 bp, respectively. The observed six repetitive elements cover 5.6% of the whole dromedary CSN1S2 gene sequence. Camel CSN1S2 gene has more INEs compared with CSN2 gene (five RTs) and they belong to the same types except for the MER5B, which was not found in CSN1S2 gene. Conversely, the CSN1S2 has less INEs compared with CSN3 (7 RTs) and is distinguished by the presence of LINE 2 type, which was not found in camels CSN3. Camel CSN1S2 also shows less INEs than the homologous bovine gene (8 RTs, 5 of them are SINEs and 3 are LINEs). These results agree with previous studies on CSN2 and CSN3 genes and confirm that camel casein genes have lower repetitive elements than cattle. This characteristic is an indication that Tylopoda diverged from Ruminantia before additional retrotransposition events took place at different times during the divergence.

Leptin is a 16 kDa protein highly expressed in the adipose tissue, in pituitary gland, brain and mammary gland. Leptin is responsible for the regulation of body weight and energy homeostasis and is one of the potential biomarker for high animal performances leading to better adaptability and productivity. In dairy and beef cattle, many studies have been reported on associations between Leptin gene (Lep) and traits like meat quality, carcass characteristics, fertility, feed intake, protein yield, energy balance and body weight. Different studies have also reported that this hormone can influence milk’s quality in dairy cattle, sheep and goats. On contrary, there have been limited research regarding association studies between SNPs at this locus and milk traits in buffalo. Lep gene in buffalo consists of three exons and two introns (GenBank:AH013754.2) and it has been mapped on chromosome 8 (BBU8q32). The aim of the present research was to identify and analyse the variability of the Lep locus in Italian Mediterranean river buffalo and to test possible associations with milk fat traits. Individual fresh milk and blood samples were collected from 766 unrelated lactating buffaloes reared in 14 farms of Southern Italy. 306 milk samples were used for fat analysis (fat content, fatty acid composition and fatty acid classes), whereas blood samples were treated for genomic DNA isolation. We sequenced the exon 3 (over 1.8 kb) of 8 buffaloes randomly chosen. Nucleotide alignment showed a synonymous transition GA at the 231th nucleotide of exon 3 that identifies a new allele named A1. The entire panel of DNA samples was genotyped in outsourcing (KBiosciences, Herts, UK). The allele frequency of the common allele (Lep A) was 0.84 (genotype distribution: 547 A/A, 196 A/A1, 23 Lep A1/A1). The statistical analysis, using a mixed linear model, showed no direct effect of Lep g.231G>A genotype on milk fatty acids composition. However, this result does not exclude the existence of an association of this SNP in other buffalo populations for other traits of economic interest.

Lipoprotein lipase is a key enzyme for the lipid metabolism playing a fundamental role in the composition of fat in adipose tissue as well as in milk. LPL gene was poorly investigated in dairy ruminants, and it has been never studied in river buffalo. Aims of this work were to explore the genetic diversity of LPL (from exon 1 to 4) in this species; to characterize the gene promoter; and to achieve an association study with milk traits. Genomic DNA of 14 individual samples of Mediterranean Italian breed was amplified and sequenced. Thirteen consensus sequences for transcription factors were found. C/EBPα and Oct-1 are the main regulatory motifs together with LP-α, although a deeper investigation is necessary to elucidate the role of the latter element, which in buffalo (and ruminants in general) is lacking the downstream cis-acting motifs (LP-β) compared to human. A total of 11 SNPs have been detected. The SNP g.107A>G was the only polymorphism found at exon level, therefore a genotyping was achieved by PCR-RFLP in a population of 523 Mediterranean buffaloes. The allele frequency was 0.63 and 0.37 respectively for the G and A allele. This SNP was significantly associated with n3-PUFA (P

Fatty acid (FA) profile is a crucial factor in defining milk properties and quality. Increasing attention is placed on those FA having a positive role on human health, such as polyunsaturated FA (PUFA), oleic acid, vaccenic acid and conjugated linoleic acid (CLA). In the present work, the FA profile obtained from gas-chromatographic analysis of 703 individual milk samples (289 cows, 214 buffaloes and 200 ewes), were used to evaluate the suitability of principal component (PC) analysis (PCA) to investigate differences in milk FA profile among these species. Thirty-six FA were analyzed by PCA. The first and second PC (PC1 and PC2) accounted for 51% of the total variability (30%, 21%, for PC1, PC2, respectively). Elements of eigenvector of PC1 were positively associated with few FA, including C16:0 (0.50), the most abundant FA in milk of the 3 species (~29.3% of FA). Among those negatively correlated with PC1, some relevant FA for human health were retrieved: C18:1t11 (−0.75), CLAc9t11 (−0.79), C18:3n-3 (−0.76), EPA (−0.81) and DPA (−0.89). Negative correlations with PC2 were observed, in general, for medium chain FA (e.g., C15:0, C16:0), whereas long chain FA (e.g., C18:1 isomers, C18:2n-6 and other PUFA) exhibited positive values. Score values of PC1 and PC2 allowed the description of the relationship among animals based exclusively on the milk FA profile, revealing a clear discrimination of the 3 species: PC1 discriminated ewes milk from that of cows and buffaloes, whereas, PC2 was able to discriminate cows from buffaloes, with ewes showing intermediate values. In general, the use of PCA evidenced as a great part of variance of FA profile of ruminants (PC1) is related to the distinction between small or large ruminants, also evidencing higher amount of beneficial FA for ewes. An important part of variance (PC2) indicates as ewes milk FA has intermediate characteristics compared with cow and buffalo milk

Summary Several market research studies have shown that consumers are primarily concerned with the provenance of the food they eat. Among the available identification methods, only DNA-based techniques appear able to completely prevent frauds. In this study, a new method to discriminate among different bovine breeds and assign new individuals to groups was developed. Bulls of three cattle breeds farmed in Italy – Holstein, Brown, and Simmental – were genotyped using the 50K SNP Illumina BeadChip. Multivariate canonical discriminant analysis was used to discriminate among breeds, and discriminant analysis (DA) was used to assign new observations. This method was able to completely identify the three groups at chromosome level. Moreover, a genome-wide analysis developed using 340 linearly independent SNPs yielded a significant separation among groups. Using the reduced set of markers, the DA was able to assign 30 independent individuals to the proper breed. Finally, a set of 48 high discriminant SNPs was selected and used to develop a new run of the analysis. Again, the procedure was able to significantly identify the three breeds and to correctly assign new observations. These results suggest that an assay with the selected 48 SNP could be used to routinely track monobreed products.