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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.