Decoding HIV Splicing Patterns with Long-Read RNA Sequencing

I watched Christian Gallardo from the Seattle Children’s Research Institute present at the Nanopore Community Meeting tonight. The title of the five-minute session was “Decoding the spliced HIV-1 transcriptome with accurate long-read RNA sequencing.” They described HIV as a retrovirus that infects CD4 T-cells and behaves like a gene upon integration. Gene expression is regulated through splicing. HIV can also become transcriptionally latent. Gallardo noted that very little is known about the transcriptional patterns. Long reads could, therefore, help decode HIV splicing. Single-molecule and PCR-free approaches were used. The approach was validated with synthetic RNAs. Latent CD4 cells and T-cell substrates were found to show different HIV splicing patterns. RNA structure probing and subcellular fractionation are now being used. The goal is to integrate all the data to develop novel therapeutics that target the virus.

How can RNA-seq with ONT help identify new HIV therapeutic targets? AI-generated image.