ABSTRACT
Objective: To evaluate native RNA sequencing for sequencing HIV-1 viral genomes
Methods: Fifteen HIV-1 strains were processed with Direct RNA Sequencing (SQK-RNA002) library kits and sequenced on MinION Mk1B devices with RevD flow cells (Oxford Nanopore Technologies (ONT), Oxford, UK). Raw reads were converted to FASTQ, aligned to reference sequences, and assembled into contigs. Multi-sequence alignments of the contigs were generated and used for cladistics analysis.
Results: We sequenced full-length HIV-1 from the transcriptional start site to 3’ LTR (100% virion genome) in 3 out of 15 isolates (89.6, NLAD8, AD17), achieving majority coverage (defined as > 50%) in another 7 out of 15 isolates. Inspection of NLAD8 sequence alignments revealed splicing or deletion signatures. Despite the strong 3’ bias, read coverage was sufficient to evaluate single-nucleotide variants (SNVs), insertions and deletions in 9 isolates, and to assemble HIV-1 genomes directly from viral RNA, achieving a maximum of 94% assembly coverage for NLAD8. Phylogenetic relationships were maintained at the level of contigs, as well as individual reads.
Conclusions: ONT native RNA sequencing performed as expected, covering full-length HIV-1 RNA without PCR or cDNA sequencing. Native single-molecule RNA sequencing supported previous models of HIV-1 replication, and samples exhibited strain-specific transcriptional signals. We propose Context Dependency Variant Classification to describe variants occurring in information-dense regions of HIV. These data provide rich resources for emerging RNA modification detection schemes. Future work will expand HIV-1 transcript profiling to infection models and clinical samples.
Footnotes
Funding: This work was funded in part by institutional support from Baylor College of Medicine; private funding by East Coast Oils, Inc., Jacksonville, Florida, and ARG’s own private funding, including Student Genomics (manuscripts in prep). ARG also received the PFLAG of Jacksonville scholarship for multiple years. The work was also supported in part by NIH grant AI116167 to JTK.