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Comparative evaluation of genomic inbreeding parameters in seven commercial and autochthonous pig breeds
- G. Schiavo, S. Bovo, F. Bertolini, S. Tinarelli, S. Dall’Olio, L. Nanni Costa, M. Gallo, L. Fontanesi
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Single nucleotide polymorphism (SNP) genotyping tools, which can analyse thousands of SNPs covering the whole genome, have opened new opportunities to estimate the inbreeding level of animals directly using genome information. One of the most commonly used genomic inbreeding measures considers the proportion of the autosomal genome covered by runs of homozygosity (ROH), which are defined as continuous and uninterrupted chromosome portions showing homozygosity at all loci. In this study, we analysed the distribution of ROH in three commercial pig breeds (Italian Large White, n = 1968; Italian Duroc, n = 573; and Italian Landrace, n = 46) and four autochthonous breeds (Apulo-Calabrese, n = 90; Casertana, n = 90; Cinta Senese, n = 38; and Nero Siciliano, n = 48) raised in Italy, using SNP data generated from Illumina PorcineSNP60 BeadChip. We calculated ROH-based inbreeding coefficients (FROH) using ROH of different minimum length (1, 2, 4, 8, 16 Mbp) and compared them with several other genomic inbreeding coefficients (including the difference between observed and expected number of homozygous genotypes (FHOM)) and correlated all these genomic-based measures with the pedigree inbreeding coefficient (FPED) calculated for the pigs of some of these breeds. Autochthonous breeds had larger mean size of ROH than all three commercial breeds. FHOM was highly correlated (0.671 to 0.985) with FROH measures in all breeds. Apulo-Calabrese and Casertana had the highest FROH values considering all ROH minimum lengths (ranging from 0.273 to 0.189 and from 0.226 to 0.152, moving from ROH of minimum size of 1 Mbp (FROH1) to 16 Mbp (FROH16)), whereas the lowest FROH values were for Nero Siciliano (from 0.072 to 0.051) and Italian Large White (from 0.117 to 0.042). FROH decreased as the minimum length of ROH increased for all breeds. Italian Duroc had the highest correlations between all FROH measures and FPED (from 0.514 to 0.523) and between FHOM and FPED (0.485). Among all analysed breeds, Cinta Senese had the lowest correlation between FROH and FPED. This might be due to the imperfect measure of FPED, which, mainly in local breeds raised in extensive production systems, cannot consider a higher level of pedigree errors and a potential higher relatedness of the founder population. It appeared that ROH better captured inbreeding information in the analysed breeds and could complement pedigree-based inbreeding coefficients for the management of these genetic resources.
Comparative selection signature analyses identify genomic footprints in Reggiana cattle, the traditional breed of the Parmigiano-Reggiano cheese production system
- F. Bertolini, G. Schiavo, S. Bovo, M. T. Sardina, S. Mastrangelo, S. Dall’Olio, B. Portolano, L. Fontanesi
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Reggiana is an autochthonous cattle breed reared mainly in the province of Reggio Emilia, located in the North of Italy. Reggiana cattle (originally a triple-purpose population largely diffused in the North of Italy) are characterised by a typical solid red coat colour. About 2500 cows of this breed are currently registered to its herd book. Reggiana is now considered a dual-purpose breed even if it is almost completely dedicated to the production of a mono-breed branded Protected Designation of Origin Parmigiano-Reggiano cheese, which is the main driver of the sustainable conservation of this local genetic resource. In this study, we provided the first overview of genomic footprints that characterise Reggiana and define the diversity of this local cattle breed. A total of 168 Reggiana sires (all bulls born over 35 years for which semen was available) and other 3321 sires from 3 cosmopolitan breeds (Brown, Holstein and Simmental) were genotyped with the Illumina BovineSNP50 panel. ADMIXTURE analysis suggested that Reggiana breed might have been influenced, at least in part, by the other three breeds included in this study. Selection signatures in the Reggiana genome were identified using three statistical approaches based on allele frequency differences among populations or on properties of haplotypes segregating in the populations (fixation index (FST); integrated haplotype score; cross-population extended haplotype homozygosity). We identified several regions under peculiar selection in the Reggiana breed, particularly on bovine chromosome (BTA) 6 in the KIT gene region, that is known to be involved in coat colour pattern distribution, and within the region of the LAP3, NCAPG and LCORL genes, that are associated with stature, conformation and carcass traits. Another already known region that includes the PLAG1 gene (BTA14), associated with conformation traits, showed a selection signature in the Reggiana cattle. On BTA18, a signal of selection included the MC1R gene that causes the red coat colour in cattle. Other selection sweeps were in regions, with high density of quantitative trait loci for milk production traits (on BTA20) and in several other large regions that might have contributed to shape and define the Reggiana genome (on BTA17 and BTA29). All these results, overall, indicate that the Reggiana genome might still contain several signs of its multipurpose and non-specialised utilisation, as already described for other local cattle populations, in addition to footprints derived by its ancestral origin and by its adaptation to the specialised Parmigiano-Reggiano cheese production system.
A machine learning approach for the identification of population-informative markers from high-throughput genotyping data: application to several pig breeds
- G. Schiavo, F. Bertolini, G. Galimberti, S. Bovo, S. Dall’Olio, L. Nanni Costa, M. Gallo, L. Fontanesi
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Single nucleotide polymorphisms (SNPs) able to describe population differences can be used for important applications in livestock, including breed assignment of individual animals, authentication of mono-breed products and parentage verification among several other applications. To identify the most discriminating SNPs among thousands of markers in the available commercial SNP chip tools, several methods have been used. Random forest (RF) is a machine learning technique that has been proposed for this purpose. In this study, we used RF to analyse PorcineSNP60 BeadChip array genotyping data obtained from a total of 2737 pigs of 7 Italian pig breeds (3 cosmopolitan-derived breeds: Italian Large White, Italian Duroc and Italian Landrace, and 4 autochthonous breeds: Apulo-Calabrese, Casertana, Cinta Senese and Nero Siciliano) to identify breed informative and reduced SNP panels using the mean decrease in the Gini Index and the Mean Decrease in Accuracy parameters with stability evaluation. Other reduced informative SNP panels were obtained using Delta, Fixation index and principal component analysis statistics, and their performances were compared with those obtained using the RF-defined panels using the RF classification method and its derived Out Of Bag rates and correct prediction proportions. Therefore, the performances of a total of six reduced panels were evaluated. The correct assignment of the animals to its breed was close to 100% for all tested approaches. Porcine chromosome 8 harboured the largest number of selected SNPs across all panels. Many SNPs were included in genomic regions in which previous studies identified signatures of selection or genes (e.g. ESR1, KITL and LCORL) that could contribute to explain, at least in part, phenotypically or economically relevant traits that might differentiate cosmopolitan and autochthonous pig breeds. Random forest used as preselection statistics highlighted informative SNPs that were not the same as those identified by other methods. This might be due to specific features of this machine learning methodology. It will be interesting to explore if the adaptation of RF methods for the identification of selection signature regions could be able to describe population-specific features that are not captured by other approaches.
Genome-wide association studies for seven production traits highlight genomic regions useful to dissect dry-cured ham quality and production traits in Duroc heavy pigs
- F. Bertolini, G. Schiavo, G. Galimberti, S. Bovo, M. D’Andrea, M. Gallo, L. Buttazzoni, M. F. Rothschild, L. Fontanesi
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Protected designation of origin dry-cured hams are obtained from heavy pigs (slaughtered at about 160 kg of live weight). A specific breeding program designed to improve meat quality for this production has included as key traits the level of intermuscular fat between the leg muscles and ham weight loss during the seasoning period together with a balance between fat and lean cuts. In this study we carried out genome-wide association studies for seven traits used in the genetic merit of Italian Duroc heavy pigs, five related to meat and carcass quality traits (visible intermuscular fat, ham weight loss at first salting, backfat thickness, ham weight and lean cuts), and two related to performance and efficiency traits (average daily gain and feed : gain ratio). A total of 573 performance-tested pigs were genotyped with the Illumina PorcineSNP60 BeadChip and genome-wide association analyses were carried out using the Bayes B approach with the 1 Mb window option of GenSel and random residuals for each of the seven traits. Detected windows were supported by independent single nucleotide polymorphism analyses with a linear mixed model (LMM) approach on the same animals for the same traits. A total of 30 windows identifying different quantitative trait loci (QTL) were detected and among those, 27 were confirmed by LMM in one of these traits. Among the confirmed windows, three QTL were reported for visible intermuscular fat, seven for ham weight loss at first salting and five and four for backfat thickness and lean cut, respectively. A total of eight QTL were detected for the other production traits. No overlapping QTL were reported except for one window on porcine chromosome 10 between lean cuts and ham weight that contained the CACNB2 gene that has been already associated with loin marbling score in other Duroc pigs. Several regions contained genes that have been already associated with production traits in other pig breeds, including Duroc lines, related to fat deposition or muscle structure. This work reports, for the first time, genome-wide association study results for several traits in Italian Duroc heavy pigs. These results will be useful to dissect the genetic basis for dry-cured ham production traits that determine the total genetic merit index of Italian Duroc pigs.
Genome-wide identification of runs of homozygosity islands and associated genes in local dairy cattle breeds
- S. Mastrangelo, M. T. Sardina, M. Tolone, R. Di Gerlando, A. M. Sutera, L. Fontanesi, B. Portolano
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Runs of homozygosity (ROH) are widely used as predictors of whole-genome inbreeding levels in cattle. They identify regions that have an unfavorable effect on a phenotype when homozygous, but also identify the genes associated with traits of economic interest present in these regions. Here, the distribution of ROH islands and enriched genes within these regions in four dairy cattle breeds were investigated. Cinisara (71), Modicana (72), Reggiana (168) and Italian Holstein (96) individuals were genotyped using the 50K v2 Illumina BeadChip. The genomic regions most commonly associated with ROHs were identified by selecting the top 1% of the single nucleotide polymorphisms (SNPs) most commonly observed in the ROH of each breed. In total, 11 genomic regions were identified in Cinisara and Italian Holstein, and eight in Modicana and Reggiana, indicating an increased ROH frequency level. Generally, ROH islands differed between breeds. The most homozygous region (>45% of individuals with ROH) was found in Modicana on chromosome 6 within a quantitative trail locus affecting milk fat and protein concentrations. We identified between 126 and 347 genes within ROH islands, which are involved in multiple signaling and signal transduction pathways in a wide variety of biological processes. The gene ontology enrichment provided information on possible molecular functions, biological processes and cellular components under selection related to milk production, reproduction, immune response and resistance/susceptibility to infection and diseases. Thus, scanning the genome for ROH could be an alternative strategy to detect genomic regions and genes related to important economic traits.
Potential sensitivity of pork production situations aiming at high-quality products to the use of entire male pigs as an alternative to surgical castrates
- M. Bonneau, M. Čandek-Potokar, M. Škrlep, M. Font-i-Furnols, M. Aluwé, The Castrum network, L. Fontanesi
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The perspective of a possible ban on surgical castration of male pigs in the EU is a real challenge for pork production systems aiming at (very) high-quality products. Information was collected from a total of 272 situations in 16 European countries, including 170 situations related to EU protected designations (Database of Origin & Registration (DOOR) database) and 102 other situations related to high-quality products or differentiated production systems, in order to evaluate their potential sensitivity to the use of entire male pigs along four dimensions: BT_Inc, likelihood of increased levels of boar taint compounds compared with conventional production of entire males; BT_Per, extent to which (some of) the associated pork product(s) are susceptible to perception of boar taint by consumers; FatQQ, likelihood that the quality of (some of) the related products is decreased due to the lower fat quantity and quality in entire males; Manag, increased likelihood of animal management and welfare problems compared with conventional production of entire males. Situations corresponding to EU protected designations (DOOR situations) were on average more sensitive to entire male production but 11% of the non-DOOR situations were highly potentially sensitive, whereas one-third of the DOOR situations had low potential sensitivity. In total, 37% of the situations where castration is not formally specified as mandatory exhibited high potential sensitivity to entire male production. Three main patterns of situations were identified via ascending hierarchical clustering. A first pattern including 31% of the DOOR situations and 74% of the other ones, had potentially no increased risk compared with conventional production of entire males. A second pattern including 28% of the DOOR situations and 16% of the other ones had a high, moderate and low potential sensitivity for FatQQ, BT_Inc and Manag, respectively. The third pattern including 41% of the DOOR situations and 11% of the other situations had high potential sensitivity for BT_Inc and FatQQ, associated with moderate to high sensitivity for Manag. The approach used to evaluate the sensitivity to entire male pig production from the limited information collected for this study has many limitations. More precise approaches using more specific information are needed to evaluate the actual sensitivity of individual situations to the use of entire male pigs. Still, the present study provides a first global insight on the capacity of European production systems aiming at high-quality products to use entire male pigs as an alternative to surgical castration.
Preselection statistics and Random Forest classification identify population informative single nucleotide polymorphisms in cosmopolitan and autochthonous cattle breeds
- F. Bertolini, G. Galimberti, G. Schiavo, S. Mastrangelo, R. Di Gerlando, M. G. Strillacci, A. Bagnato, B. Portolano, L. Fontanesi
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Commercial single nucleotide polymorphism (SNP) arrays have been recently developed for several species and can be used to identify informative markers to differentiate breeds or populations for several downstream applications. To identify the most discriminating genetic markers among thousands of genotyped SNPs, a few statistical approaches have been proposed. In this work, we compared several methods of SNPs preselection (Delta, Fst and principal component analyses (PCA)) in addition to Random Forest classifications to analyse SNP data from six dairy cattle breeds, including cosmopolitan (Holstein, Brown and Simmental) and autochthonous Italian breeds raised in two different regions and subjected to limited or no breeding programmes (Cinisara, Modicana, raised only in Sicily and Reggiana, raised only in Emilia Romagna). From these classifications, two panels of 96 and 48 SNPs that contain the most discriminant SNPs were created for each preselection method. These panels were evaluated in terms of the ability to discriminate as a whole and breed-by-breed, as well as linkage disequilibrium within each panel. The obtained results showed that for the 48-SNP panel, the error rate increased mainly for autochthonous breeds, probably as a consequence of their admixed origin lower selection pressure and by ascertaining bias in the construction of the SNP chip. The 96-SNP panels were generally more able to discriminate all breeds. The panel derived by PCA-chrom (obtained by a preselection chromosome by chromosome) could identify informative SNPs that were particularly useful for the assignment of minor breeds that reached the lowest value of Out Of Bag error even in the Cinisara, whose value was quite high in all other panels. Moreover, this panel contained also the lowest number of SNPs in linkage disequilibrium. Several selected SNPs are located nearby genes affecting breed-specific phenotypic traits (coat colour and stature) or associated with production traits. In general, our results demonstrated the usefulness of Random Forest in combination to other reduction techniques to identify population informative SNPs.
Metabolomics evidences plasma and serum biomarkers differentiating two heavy pig breeds
- S. Bovo, G. Mazzoni, G. Galimberti, D. G. Calò, F. Fanelli, M. Mezzullo, G. Schiavo, A. Manisi, P. Trevisi, P. Bosi, S. Dall’Olio, U. Pagotto, L. Fontanesi
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In pigs, many production traits are known to vary among breeds or lines. These traits can be considered end phenotypes or external traits as they are the final results of complex biological interactions and processes whose fine biological mechanisms are still largely unknown. This study was designed to compare plasma and serum metabolomic profiles between animals of two heavy pig breeds (12 Italian Large White and 12 Italian Duroc), testing indirectly the hypothesis that different genetic backgrounds might be the determining factors of differences observed on the level of metabolites in the analyzed biofluids between breeds. We used a targeted metabolomic approach based on mass spectrometric detection of about 180 metabolites and applied a statistical validation pipeline to identify differences in the metabolomic profiles of the two heavy pig breeds. Blood samples were collected after jugulation at the slaughterhouse and prepared for metabolomics analysis that was carried out using the Biocrates AbsoluteIDQ p180 Kit, covering five different biochemical classes: glycerophospholipids, amino acids, biogenic amines, hexoses and acylcarnitines. A statistical pipeline that included the selection of the most relevant metabolites differentiating the two breeds by sparse Partial Least Squares Discriminant Analysis (sPLS-DA) was coupled with a stability test and significance test determined with leave one out and permutation procedures. sPLS-DA plots clearly separated the pigs of the two investigated breeds. A few metabolites (a total of five metabolites considering the two biofluids) involved in key metabolic pathways largely contributed to these differences between breeds. In particular, a higher level of the sphingomyelins SM (OH) C14:1 (both in plasma and serum), SM (OH) C16:1 (in serum) and SM C16:0 (in serum) were observed in Italian Duroc than in Italian Large White pigs and the inverse was for the biogenic amine kynurenine (in plasma). The level of another biogenic amine (acetylornithine) was higher in Italian Large White than in Italian Duroc pigs in both analysed biofluids. These results provided biomarkers that could be important to understand the biological differences between these two heavy pig breeds. In particular, according to the functional role played by sphingomyelins in obesity-induced inflammatory responses, it could be possible to speculate that a higher level of sphingomyelins in Italian Duroc might be related to the higher interrmuscular fat deposition of this breed compared with the Italian Large White. Additional studies will be needed to evaluate the relevance of these biomarkers for practical applications in pig breeding and nutrition.
Genomic inbreeding estimation in small populations: evaluation of runs of homozygosity in three local dairy cattle breeds
- S. Mastrangelo, M. Tolone, R. Di Gerlando, L. Fontanesi, M. T. Sardina, B. Portolano
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In the local breeds with small population size, one of the most important problems is the increase of inbreeding coefficient (F). High levels of inbreeding lead to reduced genetic diversity and inbreeding depression. The availability of high-density single nucleotide polymorphism (SNP) arrays has facilitated the quantification of F by genomic markers in farm animals. Runs of homozygosity (ROH) are contiguous lengths of homozygous genotypes and represent an estimate of the degree of autozygosity at genome-wide level. The current study aims to quantify the genomic F derived from ROH (FROH) in three local dairy cattle breeds. FROH values were compared with F estimated from the genomic relationship matrix (FGRM), based on the difference between observed v. expected number of homozygous genotypes (FHOM) and the genomic homozygosity of individual i (FMOL i). The molecular coancestry coefficient (fMOL ij) between individuals i and j was also estimated. Individuals of Cinisara (71), Modicana (72) and Reggiana (168) were genotyped with the 50K v2 Illumina BeadChip. Genotypes from 96 animals of Italian Holstein cattle breed were also included in the analysis. We used a definition of ROH as tracts of homozygous genotypes that were >4 Mb. Among breeds, 3661 ROH were identified. Modicana showed the highest mean number of ROH per individual and the highest value of FROH, whereas Reggiana showed the lowest ones. Differences among breeds existed for the ROH lengths. The individuals of Italian Holstein showed high number of short ROH segments, related to ancient consanguinity. Similar results showed the Reggiana with some extreme animals with segments covering 400 Mb and more of genome. Modicana and Cinisara showed similar results between them with the total length of ROH characterized by the presence of large segments. High correlation was found between FHOM and FROH ranged from 0.83 in Reggiana to 0.95 in Cinisara and Modicana. The correlations among FROH and other estimated F coefficients were generally lower ranged from 0.45 (FMOL i−FROH) in Cinisara to 0.17 (FGRM−FROH) in Modicana. On the basis of our results, recent inbreeding was observed in local breeds, considering that 16 Mb segments are expected to present inbreeding up to three generations ago. Our results showed the necessity of implementing conservation programs to control the rise of inbreeding and coancestry in the three Italian local dairy cattle breeds.
Genomic selection in a pig population including information from slaughtered full sibs of boars within a sib-testing program
- A. B. Samorè, L. Buttazzoni, M. Gallo, V. Russo, L. Fontanesi
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Genomic selection is becoming a common practise in dairy cattle, but only few works have studied its introduction in pig selection programs. Results described for this species are highly dependent on the considered traits and the specific population structure. This paper aims to simulate the impact of genomic selection in a pig population with a training cohort of performance-tested and slaughtered full sibs. This population is selected for performance, carcass and meat quality traits by full-sib testing of boars. Data were simulated using a forward-in-time simulation process that modeled around 60K single nucleotide polymorphisms and several quantitative trait loci distributed across the 18 porcine autosomes. Data were edited to obtain, for each cycle, 200 sires mated with 800 dams to produce 800 litters of 4 piglets each, two males and two females (needed for the sib test), for a total of 3200 newborns. At each cycle, a subset of 200 litters were sib tested, and 60 boars and 160 sows were selected to replace the same number of culled male and female parents. Simulated selection of boars based on performance test data of their full sibs (one castrated brother and two sisters per boar in 200 litters) lasted for 15 cycles. Genotyping and phenotyping of the three tested sibs (training population) and genotyping of the candidate boars (prediction population) were assumed. Breeding values were calculated for traits with two heritability levels (h2=0.40, carcass traits, and h2=0.10, meat quality parameters) on simulated pedigrees, phenotypes and genotypes. Genomic breeding values, estimated by various models (GBLUP from raw phenotype or using breeding values and single-step models), were compared with the classical BLUP Animal Model predictions in terms of predictive ability. Results obtained for traits with moderate heritability (h2=0.40), similar to the heritability of traits commonly measured within a sib-testing program, did not show any benefit from the introduction of genomic selection. None of the considered genomic models provided improvements in prediction ability of pigs with no recorded phenotype. However, a few advantages were found for traits with low heritability (h2=0.10). These heritability levels are characteristic for meat quality traits recorded after slaughtering or for reproduction or health traits, typically recorded on field and not in performance stations. Other scenarios of data recording and genotyping should be evaluated before considering the implementation of genomic selection in a pig-selection scheme based on sib testing of boars.
Polymorphisms in an obesity-related gene (PCSK1) are associated with fat deposition and production traits in Italian heavy pigs
- L. Fontanesi, F. Bertolini, E. Scotti, P. Trevisi, L. Buttazzoni, S. Dall'Olio, R. Davoli, P. Bosi, V. Russo
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The proprotein convertase subtilisin/kexin type 1 (PCSK1) gene encodes the prohormone convertase 1/3 enzyme that processes prohormones into functional hormones that, in turn, regulate central and peripheral energy metabolism. Mutations in the human PCSK1 gene cause severe monogenic obesity or confer risk of obesity. We herein investigated the porcine PCSK1 gene with the aim of identifying polymorphisms associated with fat deposition and production traits in Italian heavy pigs. By re-sequencing about 5.1 kb of this gene in 21 pigs of different breeds, we discovered 14 polymorphisms that were organized in nine haplotypes, clearly distributed in two clades of putative European and Asian origin. Then we re-mapped this gene on porcine chromosome 2 and analysed its expression in several tissues including gastric oxyntic mucosa of weanling pigs in which PCSK1 processes the pre-pro-ghrelin into ghrelin, which in turn is involved in the control of feed intake and energy metabolism. Association analyses between PCSK1 single-nucleotide polymorphisms (SNPs) and production, carcass and several other traits were conducted on five groups of pigs from three different experimental designs, for a total of 1221 animals. Results indicated that the analysed SNPs were associated (P < 0.01 or P < 0.05) with several traits including backfat thickness and visible intermuscular fat in Italian Duroc (ID) and growth performances in Italian Large White (ILW) and in ILW × Italian Landrace pigs. However, the effects estimated in the ILW were opposite to the effects reported in the ID pigs. Suggestive association (P < 0.10) was observed with muscle cathepsin B activity, opening, if confirmed, potential applications to reduce the excessive softness defect of the green hams that is of particular concern for the processing industry. The results obtained supported the need to further investigate the PCSK1 gene to fully exploit the value of its variability and apply this information in pig breeding programmes.
Coat colours in the Massese sheep breed are associated with mutations in the agouti signalling protein (ASIP) and melanocortin 1 receptor (MC1R) genes
- L. Fontanesi, S. Dall’Olio, F. Beretti, B. Portolano, V. Russo
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Massese is an Italian dairy sheep breed characterized by animals with black skin and horns and black or apparent grey hairs. Owing to the presence of these two coat colour types, this breed can be considered an interesting model to evaluate the effects of coat colour gene polymorphisms on this phenotypic trait. Two main loci have been already shown to affect coat colour in sheep: Agouti and Extension coding for the agouti signalling protein (ASIP) and melanocortin 1 receptor (MC1R) genes, respectively. The Agouti locus is affected by a large duplication including the ASIP gene that may determine the Agouti white and tan allele (AWt). Other disrupting or partially inactivating mutations have been identified in exon 2 (a deletion of 5 bp, D5; and a deletion of 9 bp, D9) and in exon 4 (g.5172T>A, p.C126S) of the ASIP gene. Three missense mutations in the sheep MC1R gene cause the dominant black ED allele (p.M73K and p.D121N) and the putative recessive e allele (p.R67C). Here, we analysed these ASIP and MC1R mutations in 161 Massese sheep collected from four flocks. The presence of one duplicated copy allele including the ASIP gene was associated with grey coat colour (P = 9.4E-30). Almost all animals with a duplicated copy allele (37 out of 41) showed uniform apparent grey hair and almost all animals without a duplicated allele (117 out of 120) were completely black. Different forms of duplicated alleles were identified in Massese sheep including, in almost all cases, copies with exon 2 disrupting or partially inactivating mutations making these alleles different from the AWt allele. A few exceptions were observed in the association between ASIP polymorphisms and coat colour: three grey sheep did not carry any duplicated copy allele and four black animals carried a duplicated copy allele. Of the latter four sheep, two carried the ED allele of the MC1R gene that may be the cause of their black coat colour. The coat colour of all other black animals may be determined by non-functional ASIP alleles (non-agouti alleles, Aa) and in a few cases by the EDExtension allele. At least three frequent ASIP haplotypes ([D5:g.5172T], [N:g.5172A] and [D5:g.5172A]) were detected (organized into six different diplotypes). In conclusion, the results indicated that coat colours in the Massese sheep breed are mainly derived by combining ASIP and MC1R mutations.