Francesca Bertolini

A Next Generation Semiconductor Based Sequencing Approach for the Identification of Meat Species in DNA Mixtures

The identification of the species of origin of meat and meat products is an important issue to prevent and detect frauds that might have economic, ethical and health implications. In this paper we evaluated the potential of the next generation semiconductor based sequencing technology (Ion Torrent Personal Genome Machine) for the identification of DNA from meat species (pig, horse, cattle, sheep, rabbit, chicken, turkey, pheasant, duck, goose and pigeon) as well as from human and rat in DNA mixtures through the sequencing of PCR products obtained from different couples of universal primers that amplify 12S and 16S rRNA mitochondrial DNA genes. Six libraries were produced including PCR products obtained separately from 13 species or from DNA mixtures containing DNA from all species or only avian or only mammalian species at equimolar concentration or at 1:10 or 1:50 ratios for pig and horse DNA. Sequencing obtained a total of 33,294,511 called nucleotides of which 29,109,688 with Q20 (87.43%) in a total of 215,944 reads. Different alignment algorithms were used to assign the species based on sequence data. Error rate calculated after confirmation of the obtained sequences by Sanger sequencing ranged from 0.0003 to 0.02 for the different species. Correlation about the number of reads per species between different libraries was high for mammalian species (0.97) and lower for avian species (0.70). PCR competition limited the efficiency of amplification and sequencing for avian species for some primer pairs. Detection of low level of pig and horse DNA was possible with reads obtained from different primer pairs. The sequencing of the products obtained from different universal PCR primers could be a useful strategy to overcome potential problems of amplification. Based on these results, the Ion Torrent technology can be applied for the identification of meat species in DNA mixtures.

Polymorphisms in an obesity-related gene (PCSK1) are associated with fat deposition and production traits in Italian heavy pigs.

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.

Next Generation Semiconductor Based Sequencing of the Donkey (Equus asinus) Genome Provided Comparative Sequence Data against the Horse Genome and a Few Millions of Single Nucleotide Polymorphisms.

Few studies investigated the donkey (Equus asinus) at the whole genome level so far. Here, we sequenced the genome of two male donkeys using a next generation semiconductor based sequencing platform (the Ion Proton sequencer) and compared obtained sequence information with the available donkey draft genome (and its Illumina reads from which it was originated) and with the EquCab2.0 assembly of the horse genome. Moreover, the Ion Torrent Personal Genome Analyzer was used to sequence reduced representation libraries (RRL) obtained from a DNA pool including donkeys of different breeds (Grigio Siciliano, Ragusano and Martina Franca). The number of next generation sequencing reads aligned with the EquCab2.0 horse genome was larger than those aligned with the draft donkey genome. This was due to the larger N50 for contigs and scaffolds of the horse genome. Nucleotide divergence between E. caballus and E. asinus was estimated to be ~ 0.52-0.57%. Regions with low nucleotide divergence were identified in several autosomal chromosomes and in the whole chromosome X. These regions might be evolutionally important in equids. Comparing Y-chromosome regions we identified variants that could be useful to track donkey paternal lineages. Moreover, about 4.8 million of single nucleotide polymorphisms (SNPs) in the donkey genome were identified and annotated combining sequencing data from Ion Proton (whole genome sequencing) and Ion Torrent (RRL) runs with Illumina reads. A higher density of SNPs was present in regions homologous to horse chromosome 12, in which several studies reported a high frequency of copy number variants. The SNPs we identified constitute a first resource useful to describe variability at the population genomic level in E. asinus and to establish monitoring systems for the conservation of donkey genetic resources.

Deconstructing the pig sex metabolome: Targeted metabolomics in heavy pigs revealed sexual dimorphisms in plasma biomarkers and metabolic pathways

Metabolomics has opened new possibilities to investigate metabolic differences among animals. In this study, we applied a targeted metabolomic approach to deconstruct the pig sex metabolome as defined by castrated males and entire gilts. Plasma from 545 performance-tested Italian Large White pigs (172 castrated males and 373 females) sampled at about 160 kg live weight were analyzed for 186 metabolites using the Biocrates AbsoluteIDQ p180 Kit. After filtering, 132 metabolites (20 AA, 11 biogenic amines, 1 hexose, 13 acylcarnitines, 11 sphingomyelins, 67 phosphatidylcholines, and 9 lysophosphatidylcholines) were retained for further analyses. The multivariate approach of the sparse partial least squares discriminant analysis was applied, together with a specifically designed statistical pipeline, that included a permutation test and a 10 cross-fold validation procedure that produced stability and effect size statistics for each metabolite. Using this approach, we identified 85 biomarkers (with metabolites from all analyzed chemical families) that contributed to the differences between the 2 groups of pigs ( < 0.05 at the stability statistic test). All acylcarnitines and almost all biogenic amines were higher in castrated males than in gilts. Metabolites involved in tryptophan catabolism had the largest differences (i.e., delta = 20% for serotonin) between castrated males (higher) and gilts (lower). The level of several AA (Ala, Arg, Gly, His, Lys, Ser, Thr, and Trp) was higher in gilts (delta was from approximately 1.0 to approximately 4.8%) whereas products of AA catabolism (taurine, 2-aminoadipic acid, and methionine sulfoxide) were higher in castrated males (delta was approximately 5.0-6.0%), suggesting a metabolic shift in castrated males toward energy storage and lipid production. Similar general patterns were observed for most sphingomyelins, phosphatidylcholines, and lysophosphatidylcholines. Metabolomic pathway analysis and pathway enrichment identified several differences between the 2 sexes. This metabolomic overview opened new clues on the biochemical mechanisms underlying sexual dimorphism that, on one hand, might explain differences in terms of economic traits between castrated male pigs and entire gilts and, on the other hand, could strengthen the pig as a model to define metabolic mechanisms related to fat deposition.

Combined use of principal component analysis and random forests identify population‐informative single nucleotide polymorphisms: application in cattle breeds

The genetic identification of the population of origin of individuals, including animals, has several practical applications in forensics, evolution, conservation genetics, breeding and authentication of animal products. Commercial high-density single nucleotide polymorphism (SNP) genotyping tools that have been recently developed in many species provide information from a large number of polymorphic sites that can be used to identify population-/breed-informative markers. In this study, starting from Illumina BovineSNP50 v1 BeadChip array genotyping data available from 3711 cattle of four breeds (2091 Italian Holstein, 738 Italian Brown, 475 Italian Simmental and 407 Marchigiana), principal component analysis (PCA) and random forests (RFs) were combined to identify informative SNP panels useful for cattle breed identification. From a PCA preselected list of 580 SNPs, RFs were computed using ranking methods (Mean Decrease in the Gini Index and Mean Accuracy Decrease) to identify the most informative 48 and 96 SNPs for breed assignment. The out-of-bag (OOB) error rate for both ranking methods and SNP densities ranged from 0.0 to 0.1% in the reference population. Application of this approach in a test population (10% of individuals pre-extracted from the whole data set) achieved 100% of correct assignment with both classifiers. Linkage disequilibrium between selected SNPs was relevant (r(2) > 0.6) only in few pairs of markers indicating that most of the selected SNPs captured different fractions of variance. Several informative SNPs were in genes/QTL regions that affect or are associated with phenotypes or production traits that might differentiate the investigated breeds. The combination of PCA and RF to perform SNP selection and breed assignment can be easily implemented and is able to identify subsets of informative SNPs useful for population assignment starting from a large number of markers derived by high-throughput genotyping platforms.

Next Generation Semiconductor Based-Sequencing of a Nutrigenetics Target Gene (GPR120) and Association with Growth Rate in Italian Large White Pigs

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.

Copy number variants in Italian Large White pigs detected using high-density single nucleotide polymorphisms and their association with back fat thickness

The aim of this study was to identify copy number variants (CNVs) in Italian Large White pigs and test them for association with back fat thickness (BFT). Within a population of 12 000 performance-tested pigs, two groups of animals with extreme and divergent BFT estimated breeding values (EBVs; 147 with negative and 150 with positive EBVs) were genotyped with the Illumina Porcine SNP60 BeadChip. CNVs were detected with PENNCNV software. We identified a total of 4146 CNV events in 170 copy number variation regions (CNVRs) located on 15 porcine autosomes. Validation of detected CNVRs was carried out (i) by comparing CNVRs already detected by other studies and (ii) by semiquantitative fluorescent multiplex (SQFM) PCR of a few CNVRs. Most of CNVRs detected in Italian Large White pigs (71.2%) were already reported in other pig breeds/populations, and 82.1% of the CNV events detected by PENNCNV were confirmed by SQFM PCR. For each CNVR, we compared the occurrence of CNV events between the pigs of the high and low BFT EBV tails. Sixteen regions showed significance at P < 0.10, and seven were significant at P < 0.05 but were not significant after Bonferroni correction (Fishers exact test). These results indicated that CNVs could explain a limited fraction of the genetic variability of fat deposition in Italian Large White pigs. However, it was interesting to note that one of these CNVRs encompassed the ZPLD1 gene. In humans, a rare CNV event including this gene is associated with obesity. Studies identifying CNVs in pigs could assist in elucidating the genetic mechanisms underlying human obesity.

High‐throughput SNP discovery in the rabbit (Oryctolagus cuniculus) genome by next‐generation semiconductor‐based sequencing

The European rabbit (Oryctolagus cuniculus) is a domesticated species with one of the broadest ranges of economic and scientific applications and fields of investigation. Rabbit genome information and assembly are available (oryCun2.0), but so far few studies have investigated its variability, and massive discovery of polymorphisms has not been published yet for this species. Here, we sequenced two reduced representation libraries (RRLs) to identify single nucleotide polymorphisms (SNPs) in the rabbit genome. Genomic DNA of 10 rabbits belonging to different breeds was pooled and digested with two restriction enzymes (HaeIII and RsaI) to create two RRLs which were sequenced using the Ion Torrent Personal Genome Machine. The two RRLs produced 2 917 879 and 4 046 871 reads, for a total of 280.51 Mb (248.49 Mb with quality >20) and 417.28 Mb (360.89 Mb with quality >20) respectively of sequenced DNA. About 90% and 91% respectively of the obtained reads were mapped on the rabbit genome, covering a total of 15.82% of the oryCun2.0 genome version. The mapping and ad hoc filtering procedures allowed to reliably call 62 491 SNPs. SNPs in a few genomic regions were validated by Sanger sequencing. The Variant Effect Predictor Web tool was used to map SNPs on the current version of the rabbit genome. The obtained results will be useful for many applied and basic research programs for this species and will contribute to the development of cost-effective solutions for high-throughput SNP genotyping in the rabbit.

Reduced Representation Libraries from DNA Pools Analysed with Next Generation Semiconductor Based-Sequencing to Identify SNPs in Extreme and Divergent Pigs for Back Fat Thickness

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.

Analysis of Association Between the MUC4 g.8227C>G Polymorphism and Production Traits in Italian Heavy Pigs Using a Selective Genotyping Approach

In pigs, susceptibility to enterotoxigenic Escherichia coli (ETEC) K88 strains (locus F4bcR) is determined by a dominant allele, with the recessive allele determining resistance. The susceptible allele also appeared to be associated with higher growth rate even with discordant results. A single nucleotide polymorphism (SNP) in exon 7 of the mucin 4 (MUC4) gene (DQ848681:g.8227C>G), shown to be in close linkage disequilibrium with the F4bcR locus, has been used as marker to identify susceptible pigs, substituting invasive villous adhesion tests. We herein analyzed this SNP in Italian local breeds and applied a selective genotyping approach in Italian Large White, Italian Landrace, and Italian Duroc comparing allele frequency distribution in groups of pigs with extreme estimated breeding values (EBV) for average daily gain (ADG) and backfat thickness (BFT) to evaluate if this marker is associated with these traits. Allele G (associated with susceptibility to ETEC) was associated with higher ADG and BFT in Italian Large White (P = 6.66E-04 and P = 0.012, respectively) and higher ADG in Italian Landrace (P = 7.23E-12). This polymorphism was poorly informative in Italian Duroc. Antagonistic associations of the MUC4 g.8227C>G alleles on susceptibility to ETEC and growth performances evidence the complexity of applying marker assisted selection in pig breeding.