Biodiversity research is becoming increasingly dependent on genomics, which allows the unprecedented digitization and understanding of the planet’s biological heritage. The use of genetic markers i.e. DNA barcoding, has proved to be a powerful tool in species identification. However, full exploitation of this approach is hampered by the high sequencing costs and the absence of equipped facilities in biodiversity-rich countries. In the present work, we developed a portable sequencing laboratory based on the portable DNA sequencer from Oxford Nanopore Technologies, the MinION. Complementary laboratory equipment and reagents were selected to be used in remote and tough environmental conditions. The performance of the MinION sequencer and the portable laboratory was tested for DNA barcoding in a mimicking tropical environment, as well as in a remote rainforest of Tanzania lacking electricity. Despite the relatively high sequencing error-rate of the MinION, the development of a suitable pipeline for data analysis allowed the accurate identification of different species of vertebrates including amphibians, reptiles and mammals. In situ sequencing of a wild frog allowed us to rapidly identify the species captured, thus confirming that effective DNA barcoding in the field is possible. These results open new perspectives for real-time-on-site DNA sequencing thus potentially increasing opportunities for the understanding of biodiversity in areas lacking conventional laboratory facilities.

Genetic testing, which is now a routine part of clinical practice and disease management protocols, is often based on the assessment of small panels of variants or genes. On the other hand, continuous improvements in the speed and per-base costs of sequencing have now made whole exome sequencing (WES) and whole genome sequencing (WGS) viable strategies for targeted or complete genetic analysis, respectively. Standard WGS/WES data analytical workflows generally rely on calling of sequence variants respect to the reference genome sequence. However, the reference genome sequence contains a large number of sites represented by rare alleles, by known pathogenic alleles and by alleles strongly associated to disease by GWAS. It’s thus critical, for clinical applications of WGS and WES, to interpret whether non-variant sites are homozygous for the reference allele or if the corresponding genotype cannot be reliably called. Here we show that an alternative analytical approach based on the analysis of both variant and non-variant sites from WGS data allows to genotype more than 92% of sites corresponding to known SNPs compared to 6% genotyped by standard variant analysis. These include homozygous reference sites of clinical interest, thus leading to a broad and comprehensive characterization of variation necessary to an accurate evaluation of disease risk. Altogether, our findings indicate that characterization of both variant and non-variant clinically informative sites in the genome is necessary to allow an accurate clinical assessment of a personal genome. Finally, we propose a highly efficient extended VCF (eVCF) file format which allows to store genotype calls for sites of clinical interest while remaining compatible with current variant interpretation software.

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Recent works investigated the possibility to design solutions for pattern recognition problems by exploiting the huge amount of work done in bioinformatics. If the pattern recognition problem is cast in biological terms, then a huge range of algorithms, exploitable for classification, detection, visualization, etc. can be effectively borrowed. In this paper, we exploit biological sequence alignment tools to classify 2D shapes, tailoring the biological parameters of these tools to account for the different semantic of the 2D shape scenario. In particular, we propose a novel substitution matrix, which is the crucial parameter determining the sequence alignment solution. The new matrix, called S-BLOSUM, learns the rates of matches/mismatches in conserved portions of shapes belonging to the same category, and incorporates prior knowledge on the chosen representation for the 2D shape. On one hand, the experimental evaluation showed that the S-BLOSUM provides a significant improvement over the biological counterpart (BLOSUM); on the other hand, classification results prove that our approach is competitive with respect to the state of the art.

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