Giuseppina Schiavo

Honey is primarily composed of sugars, along with various secondary components, including environmental DNA (eDNA) derived from all organisms directly or indirectly involved in its production process. Specifically, DNA of plant origin is mainly found in the pollen collected by honey bees from the same flowers where they collected nectar. The European chestnut ( Castanea sativa , Miller) is highly valued in beekeeping for its abundant nectar production. In this study, we gathered insights on the genetic variability of C. sativa by analyzing DNA extracted from 21 chestnut monofloral honey samples produced in four regions in Northern Italy. The DNA was amplified using six C. sativa microsatellite markers commonly used for genotyping chestnut tree genetic resources. All eDNA‐derived samples successfully amplified the microsatellite loci, showing a high level of genetic variability, with a total of 35 different alleles, averaging 23.95 ± 2.09 alleles per honey sample. Some unexpected and rare C. sativa alleles were also identified in several honey samples. Genetic diversity of C. sativa was evaluated using honey‐derived microsatellite fingerprints by categorizing honey samples based on their production region and comparing their profiles using the fixation index F _ST . The highest F _ST value was observed between honey samples from Emilia‐Romagna and Trentino‐Alto Adige regions, while the lowest F _ST value was between Veneto and Trentino‐Alto Adige samples. Cluster analysis and Principal Component Analysis using microsatellite data indicated distinct geographically defined groups corresponding to the honey production regions. The findings suggest that honey eDNA can be utilized to assess the genetic variability of chestnut accessions, aiding in determining the geographical origin of chestnut honey samples, thus indirectly supporting their geographic authentication.

Early genetic studies have suggested that body size in rabbits can be considered a quantitative trait. Several rabbit breeds can be distinguished based on body size, including a few dwarf breeds differentiated by other morphological characteristics. While a large deletion in the HMGA2 gene is a major locus associated with dwarfism in Netherland Dwarf rabbits, it may not fully explain the reduced body size in this breed or other dwarf breeds. In this study, we compared the genomes of two dwarf rabbit breeds (Dwarf Lop and Netherland Dwarf) with those of non‐dwarf rabbits by analysing whole‐genome sequencing data obtained using a DNA‐pool sequencing approach. We applied the fixation index (F_ST) and pooled heterozygosity (H_P) statistics to identify signatures of selection related to small body size by contrasting dwarf with non‐dwarf breeds and comparing dwarf breeds. We identified several genomic regions that contain genes previously linked to body dimensions in various species, including LCORL‐NCAPG, COL2A1, GHRHR and CENPE. Functional enrichment analysis of genes within the top differentiated regions revealed biological terms related to skeletal development, further supporting the biological relevance of these loci. Additionally, the use of the latest version of the reference rabbit genome enabled the identification of a genomic region containing FGFR3, a gene linked to achondroplasia. Some genomic regions showed differentiation between the two dwarf breeds, suggesting that their small body size may, in part, arise through different genetic mechanisms. Overall, these findings support a polygenic architecture underlying small size in rabbits, influenced by a few major loci.

The ability to differentiate between different Apis mellifera subspecies can have significant implications for their conservation. In this study, we explored the possibility of obtaining multi-level information that could be useful in assigning a colony to the A. m. ligustica subspecies. This was accomplished by combining (1) standard morphometric characteristics of the honeybees with mitochondrial DNA (mtDNA) sequence data obtained from both the (2) honeybees and (3) honey present in a honeycomb sampled from the same colony. Eighty colonies were sampled in the Emilia-Romagna region (Northern Italy). From these colonies, a total of 413 honeybees were analyzed to obtain sequence information of the tRNALeu-COII mtDNA region. When we combined the results obtained from all three methods, 63.75% of the colonies were found to be compatible with being assigned to A. m. ligustica. For 36.25% of the colonies, morphometric analysis indicated a hybrid origin and mtDNA from honeybees or honey samples indicated the presence of mtDNA haplotypes other than those characteristic for this subspecies. Cohen’s Kappa statistic indicated poor agreement in the classification of the colonies between morphometric analysis and the two DNA-based methods, which, in turn, were in substantial agreement with each other. Although not completely effective, mtDNA analysis of honey samples could serve as an initial and practical compromise to begin initiatives aimed at preserving the genetic integrity of A. m. ligustica in the Emilia-Romagna region, as well as in other regions where it is necessary to preserve the genetic integrity of autochthonous honeybee populations.

Pigs are affected by a variety of pathogenic agents that need to be identified correctly and diagnosed even when co-infections may complicate the application of specific and targeted assays. Next-generation sequencing can provide new perspective to monitor viruses infecting or co-infecting diseased pigs. In this study, we tested, for the first time for diagnostic purposes in a livestock species, a new method based on whole-genome sequencing of all the DNAs extracted from the blood of nine pigs sampled from a farm where there was a suspected outbreak of Post-weaning Multisystemic Wasting Syndrome. We then used unmapped reads on the porcine reference genome to mine for viral sequences using a specifically designed bioinformatic pipeline. Within this fraction of reads, viral sequences ranged from 0.002% to 4.4% of the total unmapped reads and were derived from twelve different viruses known to infect pigs, where three were herpesviruses, eight were parvoviruses, and one was a circovirus. All pig sequencing datasets were positive for one or more viruses, with various potential viral loads. Suid betaherpesvirus 2, also known as Porcine cytomegalovirus (PCMV), was the most frequently identified virus as five out of the nine pig sequencing datasets contained viral sequences from this virus. The results may suggest a heterogeneous viral profile of the diseased pigs that may be derived from potential secondary infections or co-infections. This pilot application demonstrated that a whole-genome sequencing approach can complement other routine diagnostic assays in veterinary virology. Other studies and improvements are needed to validate the results and apply this approach in routine monitoring applications.

Researchers focused on assessing differences in gene diversity within and between populations, whether cosmopolitan or local. However, the identification of patterns of variation in non-random heterozygous genomic stretches, known as Heterozygosity-Rich regions (HRRs), has not yet been determined in European local pig breeds. A total of 23 pig breeds (20 local and 3 cosmopolitan) were assessed and compared in terms of heterozygosity-rich regions. The breeds with the highest number of HRRs were Large White, Lithuanian Old type, and Landrace, followed by Lithuanian Native, Mora Romagnola, and Duroc. The breeds with the lowest number were Alentejana, Iberian, and Majorcan Black. No shared HRR islands were found in all breeds, but gene enrichment analysis performed in the most common HRRs revealed several biologically important genes that cluster together and play significant roles, primarily related to the immune system. Permutation analysis indicated that some local breeds serve as true reservoirs of genetic diversity, displaying distinct and unique characteristics in terms of heterozygosity. This study suggests the importance of investigating heterozygosity to develop a comprehensive picture of pig breeds, regardless of the production system, country of origin, or population size.