Abstract 1269 Optimizing Nanopore Sequencing for Genomic Analysis and Nucleotide-Level Insights in Double-Stranded RNA Viruses

My objective is to develop and optimize a method for performing Nanopore sequencing technology on samples of double-stranded RNA viruses.Long-read Nanopore sequencing offers a powerful approach to study full viral genomes and uncover nucleotide-level variation across viral populations.Although Nanopore sequencing protocols have been highly developed for DNA genomic samples, there is less support for double-stranded RNA samples.The protocol I develop will be used in our laboratory to identify mutations in viral populations that were evolved in the presence of hightemperature heat shocks, providing insight into the mutations that allow viruses to adapt to extreme thermal environments.Methods: In a typical Nanopore sequence protocol, we isolate genetic material, ligate Nanopore adapters to the genome to create libraries, and add the libraries to a Nanopore flow cell for sequencing.I have added a heating step to denature the RNA strands before creating libraries.My first test sample used viral RNA extracted from a cell-free lysate.I repeated sequencing using a lysate that was pre-treated with DNase.I expected that this pre-treatment would effectively digest bacterial genomic components before extracting the viral genome.Then I performed Nanopore sequencing on a lysate pretreated with both RNase and DNase to remove both host genome and host transcripts.Results: In the untreated sample, I collected 8,000 reads, of which 10% matched our viral reference and 60% matched the bacterial genome.The high proportion of bacterial reads compared to viral reads indicated a need to optimize the purification of viral RNA and its separation from bacterial RNA and DNA.In the DNase pretreated sample, I obtained a total of 1,178 reads.Of these, 1% matched our viral reference genome, while 2% matched the bacterial genome.In the sample pre-treated with both RNase and DNase, I collected 7,786 reads.However, the results showed that only 0.17% matched with the viral genome and 0.05% matched with the bacterial reference.Conclusion: My results indicate that DNase treatment alone was less effective at reducing non-viral genomic material, as the bacterial content remained higher than the viral content.Although the RNase and DNase-treated sample showed substantially fewer reads, the relative percentage of viral content increased relative to bacterial content.The decrease in reads may have been due to poor quality of extracted RNA or flow cells used in this sample, suggesting that our current purification methods need improvement.I am exploring alternative extraction methods, such as modifying the spin column protocol or using phenolchloroform separation to better isolate double-stranded RNA.RNA tagging is also being considered to enable multiplexing of samples in future experiments.