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Milk yield and composition are of great economic importance for the dairy goat industry. The identification of genes associated with phenotypic differences for these traits could allow for the implementation of gene-assisted selection programs in goats. Associations between polymorphisms at 3 candidate genes and milk production traits in Alpine goats farmed in Italy were investigated in the present research. Considered genes were acetyl-coenzyme A carboxylase α (ACACA), the major regulatory enzyme of fatty acid biosynthesis; stearoyl-coenzyme A desaturase (SCD), involved in the biosynthesis of monounsaturated fatty acids in the mammary gland; and lipoprotein lipase (LPL), which plays a central role in plasma triglyceride metabolism. An approach somewhat similar to the granddaughter design for detecting quantitative trait loci in dairy cattle was followed. Effects of genotypes of a sample of 59 Alpine bucks on phenotypes of their 946 daughters raised in 75 flocks were investigated. Data comprised 13,331 daily records for milk yields (L/d), fat and protein yields (kg/d), and fat and protein contents (%) of 2,200 lactations. Population genetics parameters were calculated and associations between milk production traits and 10 single nucleotide polymorphisms (SNP) at the 3 genes were tested. Two markers at the ACACA, 1 for the SCD and 1 at the LPL locus, deviated significantly from the Hardy-Weinberg equilibrium, with an observed heterozygosity lower than expected. Flock, age of the goat, kidding season, and stage of lactation affected all traits considered, except fat percentage. Three SNP were found to be significantly associated with milk production traits. The SNP located on the ACACA gene showed an effect on milk yield, with daughters of TT bucks having an average test-day milk yield of about 0.3 to 0.25 L/d lower than the other 2 genotypes. The marker on the LPL locus was highly associated with milk yield, with the largest values for CC daughters (about 0.50L more than GG). The TGT deletion located on the untranslated region of the SCD gene showed significant effects on average milk and protein yields. The homozygote-deleted genotype had values about 0.5 L/d and 16 g/d lower for milk and protein daily yield, respectively, compared with the TGT/TGT genotype. Differences between genotypes were quite constant across most of the lactation. Associations found in the present study, which should be tested in a larger sample, especially for those markers that show rare genotypes, may offer useful indications for the genetic improvement of dairy traits in goats.

Accurate pedigrees are essential to optimize genetic improvement and conservation of animal genetic resources. In goats, the use of mating groups and kidding management procedures hamper the identification of parentage. Small panels of single nucleotide polymorphisms (SNP) have been proposed in other species to substitute microsatellites for parentage assessment. Using data from the current GoatSNP50 chip, we developed a new 3-step procedure to identify a low-density SNP panel for highly accurate parentage assessment. Methodologies for SNP selection used in other species are less suitable in the goat because of uncertainties in the genome assembly. The procedure developed in this study is based on parent-offspring identification and on estimation of Mendelian errors, followed by canonical discriminant analysis identification and stepwise regression reduction. Starting from a reference sample of 109 Alpine goats with known pedigree relationships, we first identified a panel of 200 SNP that was further reduced to 2 final panels of 130 and 114 SNP with random coincidental match inclusion of 1.51×10(-57) and 2.94×10(-34), respectively. In our reference data set, all panels correctly identified all parent-offspring combinations, revealing a 40% pedigree error rate in the information provided by breeders. All reference trios were confirmed by official tests based on microsatellites. Panels were also tested on Saanen and Teramana breeds. Although the testing on a larger set of breeds in the reference population is still needed to validate these results, our findings suggest that our procedure could identify SNP panels for accurate parentage assessment in goats or in other species with unreliable marker positioning.

Genetic variation at the ?S1-casein locus (CSN1S1) is recognized as being crucial in the selection of dairy goats for cheese yield. At this locus, the existence of alleles that have strong, intermediate, weak, and null favorable effects on cheese yield and curd firmness is well known. Selection for alleles that have a strong favorable effect has been deliberately carried out, espe- cially in France. In fact, the importance of ?S1-casein in selection was recently confirmed in the selling policies of semen, where bucks are marketed according to their genotypes. We evaluated genotypes and alleles frequen- cies at the ?S1-casein locus in 491 Italian Saanen and Alpine goats and compared them with previous data to investigate their evolution over the past decade. We also estimated soft cheese yield in a subset of the most represented genotypes to quantify the economic im- portance of considering the genetic trend of ?S1-casein genotype frequencies. We found a significant increase in frequency of the allele with the strongest favorable ef- fect, A (+12 and +13%), and of the intermediate allele E (+17 and +7%) in Saanen and Alpine goats, respec- tively. Surprisingly, the frequency of the strong allele B decreased strikingly over time (-12% in Saanen, -6% in Alpine from 2004 to 2012). This is consistent with the current marketing of semen, in that bucks that are homozygous for strong (AA and BB) and intermediate alleles (EE) and even heterozygous for these alleles (BE and AE) are considered equal. It is worth noting that this practice strongly penalizes the best breeders that have flocks composed almost entirely of goats that are homozygous for strong alleles. For heterozygous goats, we estimated an economic loss of EUR85 and EUR215 per goat per lactation, respectively, for AE and BE, compare with AA and BB genotypes. The marketing of buck se- men should clearly differentiate these 2 alleles to ensure the best economic genetic progress at this locus.