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After the rediscovery of the Mendel’s laws, the domesticated European rabbit (Orycolagus cuniculus) has been the objective of pioneering studies on coat colour genetics. However, despite the early role of this species in defining genetic mechanisms determining this phenotypic trait, only recently a few loci have been characterized at the molecular level analysing also in rabbits genes already shown to affect coat colour in mice. We herein investigated the rabbit premelanosome protein (PMEL) gene, also known as melanocyte protein Pmel 17 (PMEL17) or silver (SILV), as mutations in the homologous gene in mice and other species produce phenotypic effects similar to what is observed in the dilute coat colour in rabbit. The rabbit dilute locus is determined by a recessive coat colour mutation that dilutes the black to blue (grey) interacting with the basic colours influenced by the agouti and extension loci. To investigate this candidate gene, we isolated and sequenced cDNAs as well as portions of intronic and exonic regions of the PMEL gene in several rabbits with different coat colours and identified single nucleotide polymorphisms, including several missense mutations. One polymorphism, positioned in intron 7, was genotyped in a family in which there was segregation of the dilute coat colour. The results excluded PMEL as the causative gene for the dilute locus in rabbits, shortening the list of candidate genes that should be analysed to identify the mutation determining this phenotypic trait.

The PRKAG3 gene encodes for the regulatory gamma 3 subunit of adenosine monophosfate-activated protein kinase (AMPK) protein that acts as a regulator of carbohydrate and fat metabolism. Several single nucleotide polymorphisms (SNPs) have been identified in the porcine PRKAG3 gene. Two of them (c.595A>G or p.I199V and c.599G>A or p.R200Q) have been associated with variability of meat quality and carcass traits. In this study, we investigated the frequency of the c.595A>G and c.599G>A SNPs in 372 animals of five Italian autochthonous pig breeds (Apulo-Calabrese, Casertana, Cinta Senese, Mora Romagnola and Nero Siciliano). Genomic DNA were extracted from hair roots or blood and SNPs genotyping was performed by PCR-RFLP protocols. The c.599A (p.200Q) allele was carried by only 3 Nero Siciliano pigs. All five breeds were polymorphic at the c.595A>G site. The c.595A (p.I199) allele was the less frequent in the analysed breeds with minor allele frequency ranging from 0.144 (Nero Siciliano) to 0.464 (Casertana). Based on identified allele frequencies, the c.595A>G SNP can be useful in association studies with meat, carcass and ham quality traits in the Italian local pig breeds.

Extensive metabolic profiles of body fluids, obtained by nuclear magnetic resonance (NMR) spectroscopic or mass spectroscopic data, can provide information to deduce the effects of many different factors on biological processes. In particular, genetic factors can determine differences in physiological processes that are captured by metabolomics or metabonomics analyses. In this study we compared metabonomic profiles obtained from serum of two pig breeds (Italian Large White and Italian Duroc) with the aim to disentangle breed specific biological aspects. Twelve castrated males (6 Italian Large White and 6 Italian Duroc) were raised at the test station of the National Pig Breeders Association (ANAS) in the same conditions till they reached a live weight of about 160 kg. After a period of starvation, early in the morning pigs were transported all together at a commercial slaughterhouse, electrically stunned and jugulated within 10 minutes. Collected blood sample were processed after about 2 hours and serum was stored at -80°C till use. High Resolution Magic Angle Spinning-NMR serum spectra were recorded with a Bruker AVANCE spectrometer. Each sample was analysed in triplicate. Preliminary Principal Component Analysis of the obtained NMR spectra indicated that metabonomic analysis could be able to distinguish breed specific metabolic profiles. These results might represent useful information to disclose genetically determined regulatory pathways contributing to understand breed differences in biological processes indirectly linked with production traits.

Application of genomics (next generation sequencing and high throughput genotyping) and metabolomics technologies in farm animals are opening new opportunities for the identification of genetic factors affecting traits of economic relevance. In this study we combined several resources and data with the final aim to identify DNA polymorphisms and metabolites associated with production traits in Italian heavy pigs. Two genome wide association studies were carried out using a selective genotyping approach in Italian Large White pigs based on extreme and divergent estimated breeding values (EBVs) for average daily gain (ADG) and back fat thickness (BFT). Next generation sequencing was carried out using the Ion Torrent technology to identify single nucleotide polymorphisms (SNPs) from two reduced representation libraries constructed from pigs with extreme BFT EBVs. Metabolomics information was obtained using a mass spectrometry (MS/MS) analytical pipeline in a performance tested population. Integration of these data made it possible to identify markers (SNPs, copy number variation and metabolites) associated with ADG, BFT and several other correlated traits.

Coat colour in farm animals is one of the most important traits that distinguish breeds and populations. This phenotype is mainly determined by the distribution of eumelanins (black pigments) and pheomelanins (red/yellow pigments). Their synthesis is regulated by the melanocortin 1 receptor (MC1R/extension locus) that binds the a-melanocyte-stimulating hormone (alpha-MSH) and the agouti signalling protein (ASIP, coded by the agouti locus). Loss-of-function mutations in MC1R lead to red/yellow pigmentation, while gain-of-function mutations cause black/dark colours. Mutations at the agouti locus exert, in general, epistatic actions over the extension locus. These two key genes have been already characterized in most farm animal species, including the horse in which a few mutations are associated with different coat colours. Only partial sequence information is already available in donkey (Equus asinus) and no mutations affecting coat colour have been reported in this species so far. In this study, we used primer pairs designed on the horse ASIP and MC1R gene sequences to amplify genomic DNA from 10 donkeys (from Ragusano breed of bay coat colour and other not classified animals) with different coat colours and patterns. ASIP and MC1R gene sequences were obtained in Equus asinus, completing information available in GenBank database. Two polymorphic sites were identified in the MC1R gene whereas no variability was observed in the ASIP gene. Other studies are currently underway to evaluate if the identified mutations affect coat colour in donkeys and to identify other mutations associated with coat colour phenotypes in Equus asinus.

Melanocortin 4 receptor (MC4R) is a member of the G proteincoupled receptor (GPCR) superfamily consisting of seven transmembrane domains with an extracellular NH2 tail and an intracellular COOH terminus. MC4R is mainly expressed in the hypothalamus in which plays a key role in controlling energy homeostasis and food intake with effects on body weight and fat deposition. Polymorphisms in the melanocortin 4 receptor (MC4R) gene have been already associated with growth performance in different species, like pigs, cattle, sheep and chicken and in humans several mutations cause severe obesity. For these reasons MC4R can be considered a candidate gene to identify markers associated with production traits in rabbits. In this study we resequenced 1729 bp of the MC4R gene in 31 rabbits from different breeds and lines and identified ten polymorphisms: one was a missense mutation (p.G34D), located in a conserved position of the extracellular tail of the MC4R protein. The missense mutation was genotyped in 516 performance tested rabbits of a commercial paternal line under selection for growth efficiency. Association analysis indicated that rabbits with the less frequent genotype in this population (DD) had a lighter weight at 70 postnatal days than animals with genotype GD (P

The PRKAG3 gene encodes for the regulatory gamma 3 subunit of adenosine monophosfate-activated protein kinase (AMPK) protein that plays a relevant role as regulator of carbohydrate and fat metabolism in mammalian skeletal muscle cells. Several single nucleotide polymorphisms (SNPs) in the porcine PRKAG3 gene have been previously identified. Two missense mutations (c.595A>G and c.599G>A, giving p.I199V and p.R200Q aminoacid substitutions, respectively) were the most studied in different pig breeds and populations and have been associated with meat and carcass traits. Pigs that carry the dominant c.599A allele (p.200Q or allele RN-) have excessive skeletal muscle glycogen content and give the so-called acid meat (also referred to as Hampshire type meat). So far, the p.200Q allele has been identified in Hampshire and Hampshire derived lines. The c.595A>G SNP has been associated with variation of numerous traits including water holding capacity, pH, colour, carcass composition, and several

The identification of quantitative trait loci (QTL) and the subsequent characterization of quantitative trait genes (QTG) have been the objective of several studies in dairy cattle usually using cosmopolitan and widely spread breeds. The effects of these QTG have been only in few cases investigated in local breeds. Reggiana is a local dairy cattle breed that account less than 2000 cows reared in the North of Italy, mainly in the province of Reggio Emilia. Its milk is used for the the production of mono breed Parmigiano Reggiano cheese that is sold at a higher price than undifferentiated cheese. In this study, we analysed 24 candidate gene markers that other studies in other breeds have shown to be associated with milk production and composition traits. A total of 128 Reggiana sires (born from 1984 to 2001) were genotyped. Estimated breeding values were provided by the National Association of Reggiana Breeders (ANABORARE) for the following production traits: milk yield, protein yield and percentage, fat yield and percentage and cheese production index. The effects of the 23 markers on the 6 traits were estimated with a model that accounted for the year of birth and weighted for the reliability level. Two association study methods were used: i) GLM of the software package SAS, without including any pedigree information; ii) ASREML, including pedigree information, and including in the model the random animal effect. Significant associations (P

The development of high throughput genomics (next generation sequencing and high throughput genotyping) and metabolomics platforms has opened new perspectives for the identification of the genetics factors affecting traits of biological relevance in all species, including production traits in farm animals. In pigs, benefits derived from the recent sequencing of the pig genome can be fully exploited by combining advanced genomics and metabolomics approaches. In this work we integrated several resources, experiments and data with the final aim to identify markers (DNA polymorphisms and metabolites) associated with production traits in Italian Large White pigs. High throughput genotyping was carried out using the Illumina Porcine60SNP BeadChip array and customized Golden Gate system on extreme and divergent pigs for back fat thickness (BFT) estimated breeding values (EBVs) (300-560 animals) and average daily gain (ADG) EBVs (360 pigs), chosen among a population of about 12,000 performance tested pigs. Next generation sequencing was carried out using the Ion Torrent PGM machine to identify single nucleotide polymorphisms (SNPs) from two reduced representation libraries developed from pooled genomic DNA constructed from 50 pigs with most positive and 50 pigs with most negative BFT EBVs, respectively. A total of 7,510,918 reads were produced and 447,031 SNPs were called, using stringent criteria. Genome wide association studies made it possible to identify a quite large number of significant SNPs affecting BFT, ADG and correlated traits. In addition, several genome regions containing significant SNPs for BFT were enriched of SNPs identified from the Next Generation Sequencing experiment. Metabolomics information was obtained from 800 performance tested pigs using a mass spectrometry (MS/MS) analytical pipeline to measure 180 blood plasma metabolites. Estimated heritability and correlation among all these parameters and production traits indicated that a few metabolites could be useful predictors of EBVs for production traits. All these data will be used to develop a first systems biology platform to understand the fine biological mechanisms affecting production traits in pigs.

Next generation sequencing (NGS) is changing the way to analyse and extract genetic information from all species. One of the most promising NGS platforms is represented by the Ion Torrent PGM (Personal Genome Machine) technology. The sequencing process of this machine is based on the detection of pH variation which occurs when H+ is released during a nucleotide incorporation in the sequencing reaction. This chemical signal is then converted directly to a digital information. In this study we applied the Ion Torrent PGM technology to identify single nucleotide polymorphisms (SNPs) in the rabbit genome, a species for which massive SNP information is not available yet. Two reduced representation libraries (RRLs) were prepared. Genomic DNA pools were constructed with equimolar DNA of 10 rabbits from 4 breeds (Burgundy Fawn, Champagne d’Argent, Checkered Giant and Rhinelander) and from a commercial line. Pooled DNA was digested separately with two different restriction enzymes (HaeIII) and (RsaI). Digested DNA was electrophoresed on agarose gels from which a slice containing DNA fragments of about 500-600 bp was cut out and used to extract DNA. The isolated DNA was then prepared for the sequencing on 318 Ion Torrent chips following manufacturer instructions. From the two RRLs a total of 697.79 Mb (609.38 Mb with base quality > 20), derived from 6,964,750 reads (with a mean length of 100 bp) were sequenced. Of these reads, 6,312,660 were mapped on the reference rabbit genome sequence (oryCun2.0) and then used for variant calling analysis. Retaining only single nucleotide variation with a mapping quality >10 and detected in at least 4 bases, 65,695 SNPs were identified, with a mean distribution of 1 SNP every 287 bp. Annotation of these SNPs was based on the oryCun2.0 genome version. Some of the putative SNPs were validated by visual inspection using IGV (Integrative Genomics Viewer) and by Sanger sequencing. These SNPs could be useful to design a commercial SNP genotyping platform for the rabbit.

Candidate gene analysis, quantitative trait locus mapping in outbreed and experimental cross-populations and a genomewide association study in Holstein have reported that a few chromosome regions contribute to great variability in the degree of white/black spotting in cattle. In particular, an important region affecting this trait was localized on bovine chromosome 22 in the region containing the microphthalmia-associated transcription factor (MITF) gene. We sequenced a total of 7258 bp of the MITF gene in 40 cattle of different breeds, including 20 animals from spotted breeds (10 Italian Holstein and 10 Italian Simmental) and 20 animals from solid coloured breeds (10 Italian Brown and 10 Reggiana), and identified 17 single nucleotide polymorphisms (SNPs). The allele frequencies of one polymorphism (g.32386957AT) were clearly different between spotted (A = 0.875; T = 0.125) and non-spotted breeds (A = 0.125; T = 0.875) (P = 8.2E-12). This result was confirmed by genotyping additional animals of these four breeds (P1.0E-20). A total of 21 different haplotypes were inferred from the sequenced animals. Considering similarities among haplotypes, spotted and non-spotted groups of cattle showed significant differences in their haplotype distribution (P = 0.001), which was further supported by the analysis of molecular variance (amova) of two genotyped SNPs in an enlarged sample of cattle. Variability in the MITF gene clearly explained the differences between spotted and non-spotted phenotypes but, at the same time, it is evident that this gene is not the only genetic factor determining piebaldism in Italian Holstein and Italian Simmental cattle breeds.

Combining different approaches (resequencing of portions of 54 obesity candidate genes, literature mining for pig markers associated with fat deposition or related traits in 77 genes, and in silico mining of porcine expressed sequence tags and other sequences available in databases), we identified and analyzed 736 SNP within candidate genes to identify markers associated with back fat thickness (BFT) in Italian Large White sows. Animals were chosen using a selective genotyping approach according to their EBV for BFT (276 with most negative and 279 with most positive EBV) within a population of similar to 12,000 pigs. Association analysis between the SNP and BFT has been carried out using the MAX test proposed for case-control studies. The designed assays were successful for 656 SNP: 370 were excluded (low call rate or minor allele frequency A polymorphism (P-nominal < 1.0E-50). The second most significant SNP was the MC4R c.1426A>G polymorphism (P-nominal = 8.0E-05). The third top SNP (P-nominal = 6.2E04) was the intronic TBC1D1 g.219G>A polymorphic site, in agreement with our previous results obtained in an independent study. The list of significant markers also included SNP in additional genes (ABHD16A, ABHD5, ACP2, ALMS1, APOA2, ATP1A2, CALR, COL14A1, CTSF, DARS, DECR1, ENPP1, ESR1, GH1, GHRL, GNMT, IKBKB, JAK3, MTTP, NFKBIA, NT5E, PLAT, PPARG, PPP2R5D, PRLR, RRAGD, RFC2, SDHD, SERPINF1, UBE2H, VCAM1, and WAT). Functional relationships between genes were obtained using the Ingenuity Pathway Analysis (IPA) Knowledge Base. The top scoring pathway included 19 genes with a P-nominal < 0.1, 2 of which (IKBKB and NFKBIA) are involved in the hypothalamic IKK beta/NF kappa B program that could represent a key axis to affect fat deposition traits in pigs. These results represent a starting point to plan marker-assisted selection in Italian Large White nuclei for BFT. Because of similarities between humans and pigs, this study might also provide useful clues to investigate genetic factors affecting human obesity.

Mutations in the porcine KIT gene (Dominant white locus) have been shown to affect coat colours and colour distribution in pigs. We analysed this gene in several pig breeds and populations (Sicilian black, completely black or with white patches; Cinta Senese; grey local population; Large White; Duroc; Hampshire; Pietrain; wild boar; Meishan) with different coat colours and patterns, genotyping a few polymorphisms. The 21 exons and parts of the intronic regions were sequenced in these pigs and 69 polymorphisms were identified. The grey-roan coat colour observed in a local grey population was completely associated with a 4-bp deletion of intron 18 in a single copy KIT gene, providing evidence that this mutation characterizes the I(d) allele described in the early genetic literature. The white patches observed in black Sicilian pigs were not completely associated with the presence of a duplicated KIT allele (I(p) ), suggesting that genetic heterogeneity is a possible cause of different coat colours in this breed. Selection signature was evident at the KIT gene in two different belted pig breeds, Hampshire and Cinta Senese. The same mutation(s) may cause the belted phenotype in these breeds that originated in the 18th-19th centuries from English pigs (Hampshire) and in Tuscany (Italy) in the 14th century (Cinta Senese). Phylogenetic relationships of 28 inferred KIT haplotypes indicated two clades: one of Asian origin that included Meishan and a few Sicilian black haplotypes and another of European origin.

We identified, combining different approaches (sequencing, literature mining, and in silico porcine expressed sequence tag mining), a few hundreds of single nucleotide polymorphisms (SNPs; n. = 667) in candidate genes for fat deposition traits and genotyped these markers in Italian Large White pigs using a selective genotyping approach based on estimated breeding value for back fat thickness. Significant association (P nominal value

Fat deposition in pigs is a complex trait for which several studies in experimental populations have identified a large number of QTL, some of which segregating in outbred commercial populations. As pigs and humans have numerous physiological and phenotypic similarities for fat deposition, in order to identify the genetic factors affecting this trait in both species, it could be possible to take advantage of the results obtained in one species and, applying a comparative approach, transfer biological information to the other one, and vice versa. Therefore, such approach, on one hand, might provide useful information to improve selection efficiency in pig breeding and, on the other hand, could contribute to understand the genetic basis of human obesity and related diseases. With these aims, we designed a project based on a selective genotyping approach in commercial pig populations for which extreme and divergent groups of pigs have been chosen according to the estimated breeding value (EBV) for fat deposition traits. A candidate gene approach has been applied in order to identify markers associated with fatness in pigs. DNA markers are chosen and identified using different approaches: i) mutations already reported in pig genes affecting fat deposition; ii) discovery of new mutations in candidate genes by resequencing; iii) database mining. For the latter approach, a bioinformatic pipeline has been designed to mine pig sequences available in DNA databases. In the start up phase, about 560 Italian Large White pigs, selected according to their fatness EBV, are genotyped for more than 700 SNPs. Some preliminary results are reported. The project portal is: http://fagenomich.biocomp.unibo.it/

The increasing number of samples used for association studies in farm animals, the number of participating laboratories in such investigations and the involvement of several people and laboratory technicians in the sampling, labelling, storage, database codification, DNA isolation and analysis contribute to increase the risk of mistakes in the different sample handling stages. DNA analysis using the routine microsatellite panel for parentage verification could be used to obtain a fingerprinting of the samples but it cannot provide a quick and inexpensive way to verify if misclassification occurred. In order to verify the correct classification of a large number of male and female pigs sampled at slaughterhouses and to identify the sex of some animals for which gender was not recorded, we applied the amelogenin based sex determination method that we recently developed. The test analyses the fragment length difference between the AMELX and AMELY genes that are located on the X and Y chromosomes, respectively. The obtained PCR products can be easily resolved on polyacrylamide gels, agarose gels or by capillary electrophoresis using an automatic sequencer. Of the analysed animals, eight samples resulted misclassified, probably due to a frameshift between the sampling and the pre-available list of slaughtered animals. Their gender was also confirmed from a different DNA extraction and using other two sex determination methods based on the analysis of the ZFX and ZFY genes. Furthermore, other two samples for which gender was not recorded at the slaughterhouse were sexed using the amelogenin and ZFX/ZFY methods.

Obesity is a complex trait that, in humans, has been the objective of a large number of studies aimed to identify the genetic factors affecting different forms of this disease or being relevant for the related health problems. Mutations in several human genes have been associated to common and severe obesity. In addition, other investigations, combining gene expression and other biological evidences, have demonstrated that different genes may be important in muscle mass development. Starting from these evidences, we used a candidate gene approach to select genes that are worth to be investigated in pigs for association studies with fat and muscle deposition traits. As a first step, we mined pig expressed sequence databases and/or sequence trace records in order to identify porcine sequences for some of these genes. For a first list of selected genes, activin A receptor type II B (ACVR2B), cannabinoid receptor 1 (CNR1), cathepsin K (CTSK), myotubularin-related protein 9 (MTMR9), TBC1 domain family, member 1 (TBC1D1) and tubby (TUB), PCR primers were designed to amplify fragments containing exons and introns. Resequencing was carried out in a panel of 10-12 pigs of different breeds. Single nucleotide polymorphisms (SNPs) were identified in the ACVR2B (4 SNPs), CTSK (1 SNP) and TBC1D1 (4 SNPs) genes. These DNA markers will be used in association studies with fat and meat deposition traits in Italian heavy pigs.

In humans, mutations in the fat mass and obesity associated (FTO) gene are associated with the obesity phenotype in several populations. In pigs, we already identified three single nucleotide polymorphisms (SNPs) in the FTO gene that we genetically assigned to porcine chromosome 6 (SSC6), in an imprinted QTL region for fat deposition. Then, using a selective genotyping approach, we showed that an SNP in this gene (g.276T>G) was associated with visible intermuscular fat (VIF, a measure that resembles intermuscular fat content) in Italian Duroc pigs. Here, we refined the mapping of this gene to SSC6 using a radiation hybrid panel and evaluate the effect of the same mutation in two different pig samples. The first was constituted by 157 sib-tested Italian Duroc animals for which estimated breeding values (EBV) for average daily gain, feed:gain ratio, back-fat thickness, lean cuts, ham weight and VIF were calculated. The second group of pigs was constituted by 117 commercial hybrids measured for a total of 31 carcass and fatness traits. In the Italian Duroc pigs the FTO marker was associated only with VIF EBV (P = 0.027). In the second group of pigs, the FTO genotypes showed a tendency to be associated with several fat deposition traits. These results confirm that FTO is an important source of variability for intermuscular fat deposition in Italian Duroc pigs while the effects on fatness traits in commercial pig populations should be further investigated.

A candidate gene approach has been already successfully applied to identify several DNA markers associated with production traits in livestock. The principle is based on the fact that variability within genes coding for protein products involved in key physiological mechanisms and metabolic pathways directly or indirectly involved in determining an economic trait (e.g. feed efficiency, muscle mass accretion, reproduction efficiency, disease resistance, etc.) might probably explain a fraction of the genetic variability for the production trait itself. Growth hormone (GH) and myostatin (MSTN) genes play important roles in animal growth, development and muscle mass accretion. For their functions, these two genes can be considered candidate genes for meat production traits. Here we resequenced parts of these two genes in four rabbit breeds (Belgian Hare, Burgundy Fawn, Checkered Giant and Giant Grey) in order to identify DNA markers useful for association studies with economic traits. On the whole, resequencing of the GH and MSTN genes generated sequence information for 9988 bp. No mutation was detected in the sequenced regions of the GH gene suggesting the absence of common polymorphisms in this rabbit gene. Resequencing of the rabbit MSTN gene identified only a single nucleotide polymorphism (C>T) in intron 2. A PCR-RFLP protocol was designed to investigate this mutation in a larger number of rabbits (15 Checkered Giant, 9 Giant Grey, 6 Dwarf, 4 Burgundy Fawn, 3 Giant White, 3 Lop, 2 Belgian Hare, 1 New Zealand White). Allele frequencies across breeds were 0.51 for allele C and 0.49 for allele T. Considering the breeds for which at least 5 animals were analysed, allele C frequency was 0.56 in Checkered Giant, 0.60 in Burgundy Fawn and Giant Grey and 0.83 in Dwarf. For its allele distribution the identified polymorphism seems an useful gene marker for association studies with production traits in rabbits.

In this study we analysed two coat colour affecting genes, KIT and melanocortin 1 receptor (MC1R), with the aim to i) characterize the Nero Siciliano (Sicilian Black) pig breed at these two loci, ii) identify mutations associated with the presence of white coat colour patterns in some animals of this breed and iii) identify DNA markers useful for breed traceability of meat obtained from Nero Siciliano pigs. Two samples were considered in this study: 104 pigs collected from 13 different farms, without recorded information on coat colour; ii) 60 pigs sampled from 2 farms with recorded coat colour data. Four alleles (ED2, EP, ED and e) have been identified at the MC1R locus, thus markers at this gene cannot be used for Nero Siciliano product traceability. All analysed animals did not carry the exon/intron 17 splice site mutation of the KIT gene. Thus, the meat of Nero Siciliano pigs could be distinguished from meat of white pigs that have this mutation. As only 4 out of 12 pigs with white patches were the only carriers of the Ip allele at the KIT locus, white coat colour portions in this breed may be also determined by other mutation(s) of the KIT gene or influenced by different genes.

Coat colour phenotypes in European pig breeds are mainly due to alleles at the Extension and Dominant White loci. At the latter locus, several alleles are caused by mutations in the v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog (KIT) gene that are mainly originated by a combination of gene duplication and single nucleotide polymorphisms. Nero Siciliano is one of the few survived local Italian pig breed reared in the Nebrodi mountains of the island of Sicily The animals are usually completely black but a few show white portions mainly in the face or in the fore legs. In order to identify the genetic factors determining the presence of white portions, we genotyped 97 Nero Siciliano pigs (25 with white portions) for the splice site mutation of the intron 17 of the KIT gene that cause the Dominant White I allele. These animals were also analysed for the presence of the duplication of the same gene. None of the pigs carried the splice site mutation while 7 out of 25 animals with white portions were positive for the duplication test, suggesting that other alleles at this locus or other genes might affect this phenotype in Nero Siciliano pigs. Then, 8 of the 21 exons of the KIT gene were sequenced in eight Nero Siciliano pigs with different colour phenotypes. Several mutations were identified indicating that new alleles of the KIT gene are present in this breed. Further studies are under way to sequence all exons and evaluate the effect on coat colour of the identified mutations.

The use of molecular markers in functional genes as tool to characterize the genetic diversity in livestock populations can provide new opportunities for the identification of putative alleles of economic value. The aim of this study was to investigate on the genetic diversity among eleven pig breeds by typing SNPs in 23 genes coding for protein. DNA samples of five Italian native pig breeds (Calabrese, Casertana, Cinta Senese, Mora Romagnola and Nero Siciliano) and six cosmopolite breeds (Italian Large White, Italian Landrace, Italian Duroc, Belgian Landrace, Hampshire and Piétrain) were used. A sample of Meishan breed was also included. Allele frequencies, heterozygosity, Fst, Fis, Fit, and Reynold’s genetic distances were calculated and Neighbour-Joining tree with bootstrap resampling was obtained. The average expected heterozygosity over all loci ranged from 0.187 in Mora Romagnola to 0.342 in Italian Large White. Mora Romagnola and Meishan breeds showed the lowest within-population diversity. The results obtained for SNPs were compared with those produced previously in Pig Biodiversity project that analysed DNA samples of the same breeds of the present study, except for Mora Romagnola, using microsatellites markers. The SNP marker-based regression of heterozygosity vs distance from each population to origin produced a similar trend to that obtained with microsatellites. This analysis indicates that the founder expected heterozygosity is 0.382 for SNPs and 0.773 for microsatellites.