Italy counts several sheep breeds, arisen over centuries as a consequence of ancient and recent genetic and demographic events. To finely reconstruct genetic structure and relationships between Italian sheep, 496 subjects from 19 breeds were typed at 50K single nucleotide polymorphism loci. A subset of foreign breeds from the Sheep HapMap dataset was also included in the analyses. Genetic distances (as visualized either in a network or in a multidimensional scaling analysis of identical by state distances) closely reflected geographic proximity between breeds, with a clear north-south gradient, likely because of high levels of past gene flow and admixture all along the peninsula. Sardinian breeds diverged more from other breeds, a probable consequence of the combined effect of ancient sporadic introgression of feral mouflon and long-lasting genetic isolation from continental sheep populations. The study allowed the detection of previously undocumented episodes of recent introgression (Delle Langhe into the endangered Altamurana breed) as well as signatures of known, or claimed, historical introgression (Merino into Sopravissana and Gentile di Puglia; Bergamasca into Fabrianese, Appenninica and, to a lesser extent, Leccese). Arguments that would question, from a genomic point of view, the current breed classification of Bergamasca and Biellese into two separate breeds are presented. Finally, a role for traditional transhumance practices in shaping the genetic makeup of Alpine sheep breeds is proposed. The study represents the first exhaustive analysis of Italian sheep diversity in an European context, and it bridges the gap in the previous HapMap panel between Western Mediterranean and Swiss breeds.

Identification of genomic regions that have been targets of selection for phenotypic traits is one of the most challenging applications of dense marker panels in animal genetics. In this study, a genomewide scan using approximately 50,000 SNP was performed in an attempt to identify genomic regions associated with fat deposition in sheep, the importance of this not only being limited to livestock facing future climate changes but also for elucidating the physiology of lipid metabolism. The genotyping results obtained with the Ovine SNP50K BeadChip in 2 fat tail breeds were compared with those obtained in 13 thin tail breeds. Direct sequencing of the annotated genes located in proximity to the markers with opposite allele frequency in thin tail vs. fat tail sheep gave additional SNP of interest. To further confirm the results of the genomewide scan, we genotyped the SNP within these genes in the 2 groups of sheep. A missense mutation in the gene, with different allele frequency in the 2 groups, was detected. The results indicated and as the most probable genes involved in the fat tail phenotype.

BackgroundMerino and Merino-derived sheep breeds have been widely distributed across the world, both as purebred and admixed populations. They represent an economically and historically important genetic resource which over time has been used as the basis for the development of new breeds. In order to examine the genetic influence of Merino in the context of a global collection of domestic sheep breeds, we analyzed genotype data that were obtained with the OvineSNP50 BeadChip (Illumina) for 671 individuals from 37 populations, including a subset of breeds from the Sheep HapMap dataset.ResultsBased on a multi-dimensional scaling analysis, we highlighted four main clusters in this dataset, which corresponded to wild sheep, mouflon, primitive North European breeds and modern sheep (including Merino), respectively. The neighbor-network analysis further differentiated North-European and Mediterranean domestic breeds, with subclusters of Merino and Merino-derived breeds, other Spanish breeds and other Italian breeds. Model-based clustering, migration analysis and haplotype sharing indicated that genetic exchange occurred between archaic populations and also that a more recent Merino-mediated gene flow to several Merino-derived populations around the world took place. The close relationship between Spanish Merino and other Spanish breeds was consistent with an Iberian origin for the Merino breed, with possible earlier contributions from other Mediterranean stocks. The Merino populations from Australia, New Zealand and China were clearly separated from their European ancestors. We observed a genetic substructuring in the Spanish Merino population, which reflects recent herd management practices.ConclusionsOur data suggest that intensive gene flow, founder effects and geographic isolation are the main factors that determined the genetic makeup of current Merino and Merino-derived breeds. To explain how the current Merino and Merino-derived breeds were obtained, we propose a scenario that includes several consecutive migrations of sheep populations that may serve as working hypotheses for subsequent studies.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-015-0139-z) contains supplementary material, which is available to authorized users.

An experimental cattle population was screened for polymorphisms in the leptin gene and five SNPs were found in the regions containing the coding sequences. The association of these polymorphisms with feed intake and fat-related traits was evaluated. The results suggest an association between a polymorphism in exon 2, described here for the first time, and feed intake. Individuals with genotype A/T at this position had 19% greater mean feed intake than individuals with genotype A/A. There was also evidence for a link between leptin haplotypes and some fat-related traits.

No abstract

Variations in body weight and in the distribution of body fat are associated with feed availability, thermoregulation, and energy reserve. Ethiopia is characterized by distinct agro-ecological and human ethnic farmer diversity of ancient origin, which have impacted on the variation of its indigenous livestock. Here, we investigate autosomal genome-wide profiles of 11 Ethiopian indigenous sheep populations using the Illumina Ovine 50 K SNP BeadChip assay. Sheep from the Caribbean, Europe, Middle East, China, and western, northern and southern Africa were included to address globally, the genetic variation and history of Ethiopian populations. Population relationship and structure analysis separated Ethiopian indigenous fat-tail sheep from their North African and Middle Eastern counterparts. It indicates two main genetic backgrounds and supports two distinct genetic histories for African fat-tail sheep. Within Ethiopian sheep, our results show that the short fat-tail sheep do not represent a monophyletic group. Four genetic backgrounds are present in Ethiopian indigenous sheep but at different proportions among the fat-rump and the long fat-tail sheep from western and southern Ethiopia. The Ethiopian fat-rump sheep share a genetic background with Sudanese thin-tail sheep. Genome-wide selection signature analysis identified eight putative candidate regions spanning genes influencing growth traits and fat deposition (NPR2, HINT2, SPAG8, INSR), development of limbs and skeleton, and tail formation (ALX4, HOXB13, BMP4), embryonic development of tendons, bones and cartilages (EYA2, SULF2), regulation of body temperature (TRPM8), body weight and height variation (DIS3L2), control of lipogenesis and intracellular transport of long-chain fatty acids (FABP3), the occurrence and morphology of horns (RXFP2), and response to heat stress (DNAJC18). Our findings suggest that Ethiopian fat-tail sheep represent a uniquely admixed but distinct genepool that presents an important resource for understanding the genetic control of skeletal growth, fat metabolism and associated physiological processes.

Contradictory results have been reported on the use of goats' milk in cows' milk allergy. In this study the hypothesis was tested, using a guinea pig model of cows' milk allergy, that these discrepancies could be due to the high genetic polymorphism of goats' milk proteins. Forty guinea pigs were fed over a 20 d period with pelleted diets containing one of the following: soyabean proteins (group S), cows' milk proteins (group CM), goats' milk proteins with high (group GM1) or low (group GM2) αs1-casein content. Parenteral sensitization to GM1 and GM2 proteins was also assessed. The sensitization was measured (1) by systemic IgG1 antibodies directed against bovine or caprine β-lactoglobulin (β-lg), α-lactalbumin (α-la) and whole caseins, and (2) by intestinal anaphylaxis measured in vitro in Ussing chambers, by the rise in short-circuit current (ΔIsc) in response to milk proteins. Guinea pigs fed on CM and GM1 developed high titres (> 1500) of anti-β-lg IgG1, with an important cross reactivity between goat and cow β-lg. However, in guinea pigs fed on GM2, anti-goat β-lg IgG1 antibodies were significantly decreased compared with GM1 guinea pigs (mean IgG1 titres were 546 and 2046 respectively), and the intestinal anaphylaxis was significantly decreased (3·5±4·5 μA/cm2) compared with that observed in GM1 guinea pigs (8·3±7·6 μA/cm2). Animals receiving GM1 or GM2 proteins via the parenteral route developed a marked sensitization. These results suggest that the discrepancies observed in the use of goats' milk in cows' milk allergy could be due, at least in part, to the high genetic polymorphism of goats' milk proteins.

Summary 18The availability of dense single-nucleotide polymorphism (SNP) assays allows for the 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 F o r P e e r R e v i e wThe abundance of single-nucleotide polymorphisms (SNPs) throughout the genome and the 44 availability of dense SNP assays, makes these markers particularly suitable for the detection of 45 genomic regions where a reduction in heterozygosity occurred (Kim et al. 2013). Runs of 46 homozygosity (ROH) are contiguous segments of homozygous genotypes that are present in an 47 individual due to parents transmitting identical haplotypes to their offspring (Gibson et al. 2006). 48In animal genetics, ROH are used as predictors of whole genome inbreeding levels (Purfield et 49 al. 2012; Marras et al. 2015; Mastrangelo et al. 2016), to characterize the genomic distribution of 50 inbreeding depression on a phenotype (Biscarini et al. 2014; Pryce et al. 2014), and to identify 51 genes associated with traits of economic interest present in these regions (Zhang et al. 2015; 52 Szmatola et al. 2016; Purfield et al. 2017). Selection pressure and mating schemes can be 53 disentangled by ROH; therefore, ROH detection can also be used to minimize inbreeding and to 54 improve mating systems (Bosse et al. 2012; Zhang et al. 2015 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 Runs of homozygosity definition 106Runs of homozygosity were estimated for each animal using PLINK (Purcell et al. 2007). No where L ROH is the total length of all ROH in the genome of an individual, and L aut the specified 118 length of the autosomal genome covered by SNPs on the chip (2 452.06 Mb). 119Each ROH was categorized based on its physical length into 1 to <5 Mb, 5 to <10 Mb, 10 to <15 and averaging this per breed. 123The genomic inbreeding coefficient based on the difference between observed vs. expected 124 number of homozygous genotypes (F HOM ) was also estimated using PLINK (Purcell et al. 2007). 125Pearson's correlation between the two measures of inbreeding was calculated. 127Detection of common runs of homozygosity 128To identify the genomic regions most commonly associated with ROH for the meta-population, 129and for groups on the basis of production purposes (milk, meat, wool and "milk and meat"), the 136Genomic coordinates for all the identified ROH islands were used for the annotation of genes 137 that were fully or partially contained within each selected region using the UCSC Genome 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59...