The Pelibuey sheep has adaptability to climatic variations, resistance to parasites, and good maternal ability, whereas some ewes present multiple births, which increases the litter size in farm sheep. The litter size in some wool sheep breeds is associated with the presence of mutations, mainly in the family of the transforming growth factor β (TGF-β) genes. To explore genetic mechanisms underlying the variation in litter size, we conducted a genome-wide association study in two groups of Pelibuey sheep (multiparous sheep with two lambs per birth vs. uniparous sheep with a single lamb at birth) using the OvineSNP50 BeadChip. We identified a total of 57 putative SNPs markers (p < 3.0 × 10⁻³, Bonferroni correction). The candidate genes that may be associated with litter size in Pelibuey sheep are CLSTN2, MTMR2, DLG1, CGA, ABCG5, TRPM6, and HTR1E. Genomic regions were also identified that contain three quantitative trait loci (QTLs) for aseasonal reproduction (ASREP), milk yield (MY), and body weight (BW). These results allowed us to identify SNPs associated with genes that could be involved in the reproductive process related to prolificacy.

Genomic and genetic variation among six Italian chicken native breeds (Livornese, Mericanel della Brianza, Milanino, Bionda Piemontese, Bianca di Saluzzo and Siciliana) were studied using single nucleotide polymorphism (SNP) and copy number variants (CNV) as markers. A total of 94 DNA samples genotyped with Axiom® Genome-Wide Chicken Genotyping Array (Affymetrix) were used in the analyses. The results showed the genetic and genomic variability occurring among the six Italian chicken breeds. The genetic relationship among animals was established with a principal component analysis. The genetic diversity within breeds was calculated using heterozygosity values (expected and observed) and with Wright’s F-statistics. The individual-based CNV calling, based on log R ratio and B-allele frequency values, was done by the Hidden–Markov Model (HMM) of PennCNV software on autosomes. A hierarchical agglomerative clustering was applied in each population according to the absence or presence of definite CNV regions (CNV were grouped by overlapping of at least 1 bp). The CNV map was built on a total of 1003 CNV found in individual samples, after grouping by overlaps, resulting in 564 unique CNV regions (344 gains, 213 losses and 7 complex), for a total of 9.43 Mb of sequence and 1.03% of the chicken assembly autosome. All the approaches using SNP data showed that the Siciliana breed clearly differentiate from other populations, the Livornese breed separates into two distinct groups according to the feather colour (i.e. white and black) and the Bionda Piemontese and Bianca di Saluzzo breeds are closely related. The genetic variability found using SNP is comparable with that found by other authors in the same breeds using microsatellite markers. The CNV markers analysis clearly confirmed the SNP results.

Copy number variations are genome polymorphism that influence phenotypic variation and are an important source of genetic variation in populations. The aim of this study was to investigate genetic variability in the Mexican Creole chicken population using CNVs. The Hidden Markov Model of the PennCNV software detected a total of 1924 CNVs in the genome of the 256 samples processed with Axiom® Genome-Wide Chicken Genotyping Array (Affymetrix). The mapped CNVs comprised 1538 gains and 386 losses, resulting at population level in 1216 CNV regions (CNVRs), of which 959 gains, 226 losses and 31 complex (i.e. containing both losses and gains). The CNVRs covered a total of 47 Mb of the whole genome sequence length, corresponding to 5.12% of the chicken galGal4 autosome assembly. This study allowed a deep insight into the structural variation in the genome of unselected Mexican chicken population, which up to now has not been genetically characterized. The genomic study disclosed that the population, even if presenting extreme morphological variation, cannot be organized in differentiated genetic subpopulations. Finally this study provides a chicken CNV map based on the 600 K SNP chip array jointly with a genome-wide gene copy number estimates in a native unselected for more than 500 years chicken population.

The overall goal of this study was to investigate milk flow traits in Italian Holstein-Friesian cows and, in particular, the bimodality of milk flow, defined as delayed milk ejection at the start of milking. Using a milkometer, 2,886 records were collected from 133 herds in northern Italy from 2001 to 2007. All records included 5 time-period measurements for milk flow, somatic cell score (SCS), milk yield, 8 udder type traits, and the presence or absence of bimodality in milk flow. Genetic parameters were estimated using linear animal models for continuous traits such as milk flow, udder type, SCS, and milk production, whereas bimodality was analyzed as a categorical trait. With the exception of decreasing time (which had a very small heritability value of 0.06), heritability values for milk flow traits were moderate, ranging from 0.10 (ascending time) to 0.41 (maximum milk flow). In addition, moderate to high genetic correlations were estimated between total milking time and other time measures (from 0.78 to 0.87), and among time flow traits (from 0.62 to 0.91). The decreasing time was the trait most genetically correlated with udder type traits, with correlation values of 0.92 with rear udder height, 0.85 with rear udder width, and 0.73 with teat placement. Large udders with strong attachments were also associated with greater milk production. Heritability estimated for bimodality was 0.43, and its genetic correlation with milk flow traits and SCS indicated a sizable genetic component underlying this trait. Bimodality was negatively associated with milk production; shorter milking times and greater peak milk levels were genetically correlated with more frequent bimodal flows, indicating that faster milk release would result in an increase in bimodal patterns. The negative genetic correlation of bimodality with SCS (-0.30) and the genetic correlation between milk flow traits and SCS suggest that the relationship between milkability and SCS is probably nonlinear and that intermediate flow rates are optimal with respect to mastitis susceptibility. Quicker milk flow over a shorter period would increase the frequency of bimodal curves in milking, whereas the correlation between bimodality and both ascending and descending time was less clear.

It is commonly assumed that prediction of genome-wide breeding values in genomic selection is achieved by capitalizing on linkage disequilibrium between markers and QTL but also on genetic relationships. Here, we investigated the reliability of predicting genome-wide breeding values based on population-wide linkage disequilibrium information, based on identity-by-descent relationships within the known pedigree, and to what extent linkage disequilibrium information improves predictions based on identity-by-descent genomic relationship information.