Procedures for genetic traceability of animal products and parentage testing mainly focus on microsatellites or SNPs panels. Nevertheless, current availability of high-throughput sequencing technologies must be considered as an appealing alternative. This research focused on the evaluation of low-coverage whole-genome sequencing for traceability and paternity testing purposes, within a context of evidential statistics. Analyses were performed on a simulation basis and assumed individuals with 30 100-Mb/100-cM chromosome pairs and ~1,000,000 polymorphic SNPs per chromosome. Ten independent populations were simulated under recombination and mutation with effective populations size 100 (generations 1–1000), 10,000 (generation 1001) and 25,000 (generation 1002), and this last generation was retained for analytical purposes. Appropriate both traceability and paternity tests were developed and evaluated on different high-throughput sequencing scenarios accounting for genome coverage depth (0.01×, 0.05×, 0.1× and 0.5×), length of base-pair reads (100, 1000 and 10,000 bp), and sequencing error rate (0%, 1% and 10%). Assuming true sequencing error rates and genotypic frequencies, 0.05× genome coverage depth guaranteed 100% sensitivity and specificity for traceability and paternity tests (n = 1000). Same results were obtained when sequencing error rate was arbitrarily set to 0, or the maximum value assumed during simulation (i.e., 1%). In a similar way, uncertainly about genotypic frecuencies did not impair sensitivity under 0.05× genome coverage, although it reduced specificity for paternity tests up to 85.2%. These results highlighted low-coverage whole-genome sequencing as a promising tool for the livestock and food industry with both technological and (maybe) economic advantages.
- Evidential statistics