Search

14 Pág. Departamento de ​Mejora Genética Animal, Coronaviruses silently circulate in human and animal populations, causing mild to severe diseases. Therefore, livestock are important components of a "One Health" perspective aimed to control these viral infections. However, at present there is no example that considers pig genetic resources in this context. In this study, we investigated the variability of four genes (ACE2, ANPEP and DPP4 encoding for host receptors of the viral spike proteins and TMPRSS2 encoding for a host proteinase) in 23 European (19 autochthonous and three commercial breeds and one wild boar population) and two Asian Sus scrofa populations. A total of 2229 variants were identified in the four candidate genes: 26% of them were not previously described; 29 variants affected the protein sequence and might potentially interact with the infection mechanisms. The results coming from this work are a first step towards a "One Health" perspective that should consider conservation programs of pig genetic resources with twofold objectives: (i) genetic resources could be reservoirs of host gene variability useful to design selection programs to increase resistance to coronaviruses; (ii) the described variability in genes involved in coronavirus infections across many different pig populations might be part of a risk assessment including pig genetic resources., This work has received funding from the University of Bologna RFO 2016-2019 programmes, the Italian MIUR 2017 PigPhenomics project, from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 634476 for the project with acronym TREASURE, from the European Open Science Cloud (EOSC) Secretariat, project “Application of animal genomics and data mining to predict and monitor novel coronavirus potential infections (VirAnimalOne)”, the EGI call for COVID-19 research projects (AnGen1H project) and from the Por Fesr Emilia-Romagna 2014-2020 (actions 1.1.4 and 1.2.2—Bando per sostenere progetti di ricerca ed innovazione per lo sviluppo di soluzioni finalizzate al contrasto dell’epidemia da COVID-19—Project LIVESTOCK-STOP-COVI). The content of this article reflects only the authors' view and the European Union Agency is not responsible for any use that may be made of the information it contains.

Most of the Italian pig genetic resources that existed at the beginning of the last century have been substituted by more productive populations. At present, only six original autochthonous pig breeds are officially recognized in Italy and have their own herd books managed by the National Pig Breeders Association. Another section of the breed herd book includes breeds that were completely lost but that were subsequently reconstructed through specific crossbreeding programmes. This is the case of the Nero di Parma breed that was officially recognized as reconstructed breed in 2016. This is a small breed, reared in the province of Parma (North of Italy), that accounts for 103 and 12 registered sow and boars, respectively. In this study, using single nucleotide polymorphisms genotyped with the Illumina PorcineSNP60 BeadChip array, we compared, at the genome level, the reconstructed Nero di Parma pig breed with three Italian commercial (Italian Large White, Italian Duroc and Italian Landrace) and four autochthonous (Apulo-Calabrese, Casertana, Cinta Senese and Nero Siciliano) pig breeds. Nero di Parma showed the highest level of linkage disequilibrium among all analysed breeds. Effective population size estimated over past generations was the lowest in this reconstructed breed. However, genomic inbreeding parameters did not suggest a high level of inbreeding in Nero di Parma. The comparative analysis against several other Italian pig breeds made it possible to evaluate the obtained information that could be helpful to define potential future conservation and breeding strategies for this small reconstructed breed.

Honey is one of the most frauded food products. Therefore, it is important to develop new analytical systems useful for its authentication. Honey contains intrinsic markers that can be used to identify and monitor its origin, including plant DNA mainly derived by pollen. In this study, we applied a next generation sequencing approach for honey authentication by detecting the prevalent botanical contribution and botanical composition of honeys of different origin. DNA was isolated from nine honeys (six monofloral honeys produced in Italy, two polyfloral honeys produced in East Europe and Chile respectively, and one honeydew honey) and PCR amplified for a chloroplast trnL barcoding fragment. Obtained amplicons were sequenced using the Ion Torrent sequencing platform. Sequence data was interpreted using a customized bioinformatic pipeline that used a reference plant sequence dataset derived by more than 150,000 entries. A total of 254 botanical groups were identified from the nine analysed samples, ranging from 37 groups in orange tree blossom honey to 74 in eucalyptus tree blossom honey. The prevalent expected botanical origin was confirmed in five out of six monofloral honeys. The plant signature of the labelled lime tree blossom honey did not confirm the expected botanical prevalence. The most represented botanical group in the honeydew honey was Castanea. The botanical composition of monofloral and polyfloral honey samples was useful to infer their geographical origin. The metabarcoding based system applied in this study captured the botanical signature of all analysed honey samples and provided information useful for their authentication.

Runs of homozygosity (ROH) in a diploid organism can be defined as continuous chromosome regions in which all loci have a homozygous genotype. Shared ROH within a livestock population identify chromosome regions in which a reduced haplotype variability produces ROH islands. ROH islands can provide information on hotspot of selection putatively derived from different selection history, genetic events and adaptation to several production systems. In this study we evaluated the distribution of ROH in the genome of a total of 2860 pigs belonging to seven Italian breeds, three commercial breeds (Italian Large White, Italian Duroc and Italian Landrace) and four autochthonous breeds (Apulo-Calabrese, Casertana, Cinta Senese and Nero Siciliano). All animals were genotyped with the Illumina PorcineSNP60 BeadChip array. PLINK software was used to call ROH. The largest number of ROH per animal was observed in the Italian Duroc breed. The mean largest size of ROH was detected in Apulo-Calabrese pigs. Nero Siciliano pigs had the lowest mean number of ROH per animal. Italian Large White pigs had the lowest mean length of ROH. ROH islands were identified in all breeds except in Nero Siciliano. ROH islands spanned from a total of 25.5 (Cinta Senese) to 33.1 Mbp (Italian Landrace) of genomic regions distributed from four to ten autosomes and encompassing from a total of 126 to 262 annotated genes. These selection hotspot regions differed among breeds. Functional inference of the observed ROH islands provided some insights into the mechanisms of adaptation of these pig genetic resources.

Nero Siciliano (or Sicilian Black) is an Italian autochthonous pig breed reared in the Sicily island, mainly under extensive management systems. Nero Siciliano pigs are black (with black skin and black hair), but animals with white face or partially white face ("suino facciolo") can be registered to the breed herd book. Sometimes, other white patterns on extreme portions of legs could appear in this population. This study took advantage from the rare occurrence of pigs with white patterns in the Nero Siciliano population to carry out a genome-wide association study and comparative genome-wide Fixation index (FST) analysis to identify genomic regions that could affect coat colour variability (solid black vs white patterns over black) in this autochthonous pig breed. Analyses have been conducted on 66 Nero Siciliano pigs: 30 completely black and 36 black with white patterns. All samples have been genotyped for the KIT gene duplication and MC1R mutations, two genes well known to affect coat colours in pigs. Only pigs that did not carry any duplication of the KIT gene and were homozygous for the ED2 black dominant MC1R gene allele (n = 26 completely black and n. 22 with white patterns) were genotyped with the Illumina PorcineSNP60 BeadChip. The genome-wide analyzes identified on chromosome 2 a significant marker (rs81329493) associated with the coat colour white patterns in this breed. The homologous chromosome region in felids contains the gene responsible for the blotched tabby and striped coat colour patterns. Further studies, including a larger number of pigs, are needed to confirm this result and identify the causative mutation(s) affecting this coat colour diversity, which might be used to design a conservation programme in this breed aiming to maintain phenotypic homogeneity (i.e. solid black) that is typically associated with Nero Siciliano pigs. This study demonstrated how genetic diversity segregating in an autochthonous genetic resource can be explored to understand the genetic mechanisms affecting phenotypic traits in a livestock species.

Honeydew produced from the excretion of plant-sucking insects (order Hemiptera) is a carbohydrate-rich material that is foraged by honey bees to integrate their diets. In this study, we used DNA extracted from honey as a source of environmental DNA to disclose its entomological signature determined by honeydew producing Hemiptera that was recovered not only from honeydew honey but also from blossom honey. We designed PCR primers that amplified a fragment of mitochondrial cytochrome c oxidase subunit 1 (COI) gene of Hemiptera species using DNA isolated from unifloral, polyfloral and honeydew honeys. Ion Torrent next generation sequencing metabarcoding data analysis assigned Hemiptera species using a customized bioinformatic pipeline. The forest honeydew honeys reported the presence of high abundance of Cinara pectinatae DNA, confirming their silver fir forest origin. In all other honeys, most of the sequenced reads were from the planthopper Metcalfa pruinosa for which it was possible to evaluate the frequency of different mitotypes. Aphids of other species were identified from honeys of different geographical and botanical origins. This unique entomological signature derived by environmental DNA contained in honey opens new applications for honey authentication and to disclose and monitor the ecology of plant-sucking insects in agricultural and forest landscapes.

Casertana is a local pig breed mainly raised in Central-South regions of Italy. Pigs of this breed are considered the descendants of the ancient Neapolitan population that largely influenced the constitution of the modern commercial pigs. The pigs of this breed are usually curly-tailed, like several other domestic pig populations. However, Casertana population shows some variability for this trait, including animals having straight tail as observed in wild boars. In this study, we run, for the first time, a genome wide association study (GWAS) comparing the curly tailed (no. = 53) and straight tailed (no. = 19) Casertana pigs to identify genomic regions associated with the tail shape phenotype in Sus scrofa. All animals were genotyped with the Illumina PorcineSNP60 BeadChip v.2. GEMMA software was used in the GWAS for which we were able to correct for stratification in the analysed cohort. A single nucleotide polymorphism (rs81439488), located on porcine chromosome 12, was significantly associated with the investigated trait. This marker is close to the SRY-box 9 (SOX9) gene that encodes for a transcription factor that is required during sequential steps of the chondrocyte differentiation pathway, notochord maintenance and skeletogenesis. As the shape of the tail could be important in relation to the problem of tail biting in pigs, the obtained results might open new perspectives for defining selection programs answering indirectly animal welfare issues. This work demonstrated that autochthonous animal genetic resources might be used to disclose genetic factors affecting peculiar traits by exploiting segregating phenotypes and genetic variability.

Honey bees are considered large-scale monitoring tools due to their environmental exploration and foraging activities. Traces of these activities can be recovered in the honey that also may reflect the hive ecological micro-conditions in which it has been produced. This study applied a next generation sequencing platform (Ion Torrent) for shotgun metagenomic analysis of honey environmental DNA (eDNA). The study tested a methodological framework to interpret DNA sequence information useful to describe the complex ecosystems of the honey bee colony superorganism, its pathosphere and the heterogeneity of the agroecological environments and environmental sources that left DNA marks in the honey. Analysis of two honeys reported sequence reads from five main organism groups (kingdoms or phyla): arthropods (that mainly included reads from Apis mellifera, several other members of the Hymenotpera, in addition to members of the Diptera, Coleoptera and Lepidoptera, as well as aphids and mites), plants (that clearly confirmed the botanical origin of the two honeys, i.e. orange tree blossom and eucalyptus tree blossom honeys), fungi and bacteria (including common hive and honey bee gut microorganisms, honey bee pathogens and plant pathogens), and viruses (which accounted for the largest number of reads in both honeys, mainly assigned to Apis mellifera filamentous virus). The shotgun metagenomic approach that was used in this study can be applied in large scale experiments that might have multiple objectives according to the multi-kingdom derived eDNA that is contained in the honey.

In this study, we tested the Ion Torrent next generation semiconductor based sequencing technology for meat species identification in several highly processed and complex meat products and meat derived broths (a doner kebab, a beef/pork pate, a meat based filling of tortellini, one instantaneous granular preparation of broth stock made by meat and two ready to use meat broths from different producers). The detection protocol included the sequencing of targeted mitochondrial DNA (mtDNA) regions amplified with universal primer pairs and a bioinformatic pipeline designed to interpret sequencing results. Six libraries were sequenced producing a total of 1,363,351 filtered reads. Data mining detected expected and unexpected meat species in the analysed products. Pork was identified in the kebab and Bubalus bubalis DNA was identified in the beef/pork pate. For products for which the precise meat species ingredient information was not available, it was possible to obtain it. Human contamination based on human detected reads could be useful to evaluate the hygienic level of highly processed products. Mitochondrial haplotypes (mitotypes) were identified for several mtDNA-species combinations providing another level of information useful for the authentication of meat derived products. This work defined a methodological framework to establish assays using this sequencing platform for routine species identification in complex and highly processed food.

In this study, we applied a next generation sequencing (NGS) technology (Ion Torrent) for species identification based on three mitochondrial DNA (mtDNA) regions amplified on DNA extracted from dairy products. Sequencing reads derived from three libraries, obtained from artificial DNA pools or from pooled amplicons, were used to test the method. Then, sequencing results from five libraries obtained from two mixed goat and cow milk samples, one buffalo mozzarella cheese, one goat crescenza cheese and one artisanal cured ricotta cheese, were able to detect all expected species in addition to undeclared species in a few of them. Mining generated reads it was possible to identify different dairy species mitotypes and the presence of human DNA that could constitute a potential marker to monitor the hygienic level of dairy products. Overall results demonstrated the usefulness of NGS for species identification in food products and its possible application for food authentication.

The GPR120 gene (also known as FFAR4 or O3FAR1) encodes for a functional omega-3 fatty acid receptor/sensor that mediates potent insulin sensitizing effects by repressing macrophage-induced tissue inflammation. For its functional role, GPR120 could be considered a potential target gene in animal nutrigenetics. In this work we resequenced the porcine GPR120 gene by high throughput Ion Torrent semiconductor sequencing of amplified fragments obtained from 8 DNA pools derived, on the whole, from 153 pigs of different breeds/populations (two Italian Large White pools, Italian Duroc, Italian Landrace, Casertana, Pietrain, Meishan, and wild boars). Three single nucleotide polymorphisms (SNPs), two synonymous substitutions and one in the putative 3'-untranslated region (g.114765469C > T), were identified and their allele frequencies were estimated by sequencing reads count. The g.114765469C > T SNP was also genotyped by PCR-RFLP confirming estimated frequency in Italian Large White pools. Then, this SNP was analyzed in two Italian Large White cohorts using a selective genotyping approach based on extreme and divergent pigs for back fat thickness (BFT) estimated breeding value (EBV) and average daily gain (ADG) EBV. Significant differences of allele and genotype frequencies distribution was observed between the extreme ADG-EBV groups (P < 0.001) whereas this marker was not associated with BFT-EBV.

Shot-gun next generation sequencing (NGS) on whole DNA extracted from specimens collected from mammals often produces reads that are not mapped (i.e. unmapped reads) on the host reference genome and that are usually discarded as by-products of the experiments. In this study, we mined Ion Torrent reads obtained by sequencing DNA isolated from archived blood samples collected from 100 performance tested Italian Large White pigs. Two reduced representation libraries were prepared from two DNA pools constructed each from 50 equimolar DNA samples. Bioinformatic analyses were carried out to mine unmapped reads on the reference pig genome that were obtained from the two NGS datasets. In silico analyses included read mapping and sequence assembly approaches for a viral metagenomic analysis using the NCBI Viral Genome Resource. Our approach identified sequences matching several viruses of the Parvoviridae family: porcine parvovirus 2 (PPV2), PPV4, PPV5 and PPV6 and porcine bocavirus 1-H18 isolate (PBoV1-H18). The presence of these viruses was confirmed by PCR and Sanger sequencing of individual DNA samples. PPV2, PPV4, PPV5, PPV6 and PBoV1-H18 were all identified in samples collected in 1998-2007, 1998-2000, 1997-2000, 1998-2004 and 2003, respectively. For most of these viruses (PPV4, PPV5, PPV6 and PBoV1-H18) previous studies reported their first occurrence much later (from 5 to more than 10 years) than our identification period and in different geographic areas. Our study provided a retrospective evaluation of apparently asymptomatic parvovirus infected pigs providing information that could be important to define occurrence and prevalence of different parvoviruses in South Europe. This study demonstrated the potential of mining NGS datasets non-originally derived by metagenomics experiments for viral metagenomics analyses in a livestock species.

Microbiota plays an important role in the homeostasis of the gastrointestinal tract. Understanding the variations of the commensal microbiota composition is crucial for a more efficient control of enteric infectious diseases and for the reduction of the use of antibiotics in animal production, which are the main points of interest for improved animal healthcare and welfare and for consumer health protection. Even though the intestinal microbiota has been extensively studied, little is known about the gastric microbiota. This pilot study was aimed at a descriptive analysis of the gastric microbiota in healthy pigs and at the identification of any differences among four potentially distinct microbial niches in the stomach. Gastric mucosal samples from the oxyntic area, the pylorus and the gastric groove, and a sample of gastric contents were collected from four healthy weaned pigs. Bacterial DNA was isolated and extracted from each sample and amplicons from the V6 region of the 16S rRNA gene were sequenced using Ion Torrent PGM. The data were analysed by an "unsupervised" and a "supervised" approach in the Ribosomal Database Project (RDP) pipeline. Proteobacteria was the dominant phylum in all the samples. Differences in bacterial community composition were found between mucosal and content samples (one-way ANOSIM pairwise post hoc test, p < 0.05); instead, the different mucosal regions did not show differences between them. The mucosal samples were characterised by Herbiconiux and Brevundimonas, two genera which include cellulolytic and xylanolytic strains. Nevertheless, additional larger trials are needed to support the data presented in this pilot study and to increase the knowledge regarding the resident microbiota of the stomach.

Nuclear DNA sequences of mitochondrial origin (numts) are derived by insertion of mitochondrial DNA (mtDNA), into the nuclear genome. In this study, we provide, for the first time, a genome picture of numts inserted in the pig nuclear genome. The Sus scrofa reference nuclear genome (Sscrofa10.2) was aligned with circularized and consensus mtDNA sequences using LAST software. A total of 430 numt sequences that may represent 246 different numt integration events (57 numt regions determined by at least two numt sequences and 189 singletons) were identified, covering about 0.0078% of the nuclear genome. Numt integration events were correlated (0.99) to the chromosome length. The longest numt sequence (about 11 kbp) was located on SSC2. Six numts were sequenced and PCR amplified in pigs of European commercial and local pig breeds, of the Chinese Meishan breed and in European wild boars. Three of them were polymorphic for the presence or absence of the insertion. Surprisingly, the estimated age of insertion of two of the three polymorphic numts was more ancient than that of the speciation time of the Sus scrofa, supporting that these polymorphic sites were originated from interspecies admixture that contributed to shape the pig genome.

The aim of this study was to identify single nucleotide polymorphisms (SNPs) that could be associated with back fat thickness (BFT) in pigs. To achieve this goal, we evaluated the potential and limits of an experimental design that combined several methodologies. DNA samples from two groups of Italian Large White pigs with divergent estimating breeding value (EBV) for BFT were separately pooled and sequenced, after preparation of reduced representation libraries (RRLs), on the Ion Torrent technology. Taking advantage from SNAPE for SNPs calling in sequenced DNA pools, 39,165 SNPs were identified; 1/4 of them were novel variants not reported in dbSNP. Combining sequencing data with Illumina PorcineSNP60 BeadChip genotyping results on the same animals, 661 genomic positions overlapped with a good approximation of minor allele frequency estimation. A total of 54 SNPs showing enriched alleles in one or in the other RRLs might be potential markers associated with BFT. Some of these SNPs were close to genes involved in obesity related phenotypes.