Sequencing-based approaches for the study of Lung-related diseases

My thesis is focused on sequencing-based methods for lung diseases monitoring. Modern sequencing techniques allow us to comprehensively characterize nucleic acids obtained from patient-derived biological material, with potential applications in both basic research and clinical practice. The thesis is divided in two sections: In Section 1: “Evidence for host-dependent RNA editing in the transcriptome of SARS-CoV-2” I describe the presence of RNA editing events in SARS-CoV-2, by analysing publicly available second generation RNA sequencing data from infected patients: Emerging viral infections represent a threat to global health, and the recent outbreak of novel coronavirus disease 2019 caused by SARS-CoV-2 exemplifies the risks. RNA editing is a physiological mechanism mediated by two enzyme families: APOBEC and ADAR, which introduce A-to-I and C-to-U mutations in double strand and single strand RNA respectively. RNA editing typically involves endogenous RNAs but, if targeting viral RNA, it is potentially deleterious for virus’ viability itself, by generating premature stop codons and missense mutations in the viral genome. On the other hand, RNA editing could fuel virus evolution by increasing the basal mutational rate. I have downloaded publicly available Illumina transcriptomic data, from BALF samples of infected patients; using a combination of published tools (Reditools2, JACUSA) I have detected an enrichment of APOBEC and ADAR related mutation on SARS-CoV-2 RNA. A similar enrichment was observed in genomic RNA SARS-CoV-2, SARS and MERS sequences downloaded from GISAID and NCBI virus. The evidence of RNA editing on SARS-CoV-2 suggests that APOBEC and ADAR can interact with viral RNAs, probably with an anti-viral purpose. C-to-U changes leading to stop codons are overrepresented in the transcriptomic data but—as expected—disappear in the genomic dataset. This might point—again—to an antiviral role for these editing enzymes. Also, the proportion of ADAR-related mutation was unexpectedly lower in genomic RNA sequences, compared to transcriptomic data. It is possible that A-to-I editing is somehow restricting viral propagation, thus reducing the number of viral progeny showing evidence of these changes. In Section 2: “Analysis of copy number variations from cell-free DNA of lung cancer patients via Nanopore sequencing” I have developed a customized workflow to exploit Nanopore sequence for the analysis of plasmatic cell-free DNA: Cancer is an extremely dynamic disease: malignant cells are constantly under selective pressure and the evolutionary path of each tumor can take different directions due to such pressure. It is hence important to monitor cancer development at multiple timepoints to closely follow its evolution; unfortunately, the risks and invasiveness of conventional biopsy make it unsuitable for repeated sampling. A valid and non-invasive alternative to tissue sampling is represented by the analysis of cfDNA from liquid biopsy samples (plasma). CNVs are an important class of genetic alterations that can affect tumor aggressivity and resistance to treatment. To date, the only reliable approach to obtain a whole-genome CNV profile from plasmatic cfDNA is Illumina sequencing. However the need for expensive sequencers is often an obstacle for smaller laboratories. Oxford Nanopore Technologies has recently released MinION: a fast and extremely inexpensive third generation sequencer based on the Nanopore technology. However, this technology is not designed for low quality DNA such as cfDNA (very fragmented, low concentration). I have modified Nanopore standard protocols to make them compatible with the characteristics of cfDNA. The technique has been tested on plasma samples obtained from lung cancer patients, with the aim of detecting tumor-specific copy number variations. The approach has been subsequently validated by comparing it with the current standard technique (Illumina). Nanopore and Illumina results strongly correlate (R = 0.96 – 0.99, p << 0.001), with concordant log2ratio values in 97-99% of genome positions. Nanopore features (i.e. reduced costs) represent advantages over current sequencing technologies, and might drive the adoption of molecular karyotyping from liquid biopsies as a tool for cancer monitoring in clinical settings.