Characterizing HIV-1 Splicing by Using Next-Generation Sequencing

Full-length human immunodeficiency virus type 1 (HIV-1) RNA serves as the genome or as an mRNA, or this RNA undergoes splicing using four donors and 10 acceptors to create over 50 physiologically relevant transcripts in two size classes (1.8 kb and 4 kb). We developed an assay using Primer ID-tagged deep sequencing to quantify HIV-1 splicing. Using the lab strain NL4-3, we found that A5 (env/nef) is the most commonly used acceptor (about 50%) and A3 (tat) the least used (about 3%). Two small exons are made when a splice to acceptor A1 or A2 is followed by activation of donor D2 or D3, and the high-level use of D2 and D3 dramatically reduces the amount of vif and vpr transcripts. We observed distinct patterns of temperature sensitivity of splicing to acceptors A1 and A2. In addition, disruption of a conserved structure proximal to A1 caused a 10-fold reduction in all transcripts that utilized A1. Analysis of a panel of subtype B transmitted/founder viruses showed that splicing patterns are conserved, but with surprising variability of usage. A subtype C isolate was similar, while a simian immunodeficiency virus (SIV) isolate showed significant differences. We also observed transsplicing from a downstream donor on one transcript to an upstream acceptor on a different transcript, which we detected in 0.3% of 1.8-kb RNA reads. There were several examples of splicing suppression when the env intron was retained in the 4-kb size class. These results demonstrate the utility of this assay and identify new examples of HIV-1 splicing regulation. IMPORTANCE During HIV-1 replication, over 50 conserved spliced RNA variants are generated. The splicing assay described here uses new developments in deep-sequencing technology combined with Primer ID-tagged cDNA primers to efficiently quantify HIV-1 splicing at a depth that allows even low-frequency splice variants to be monitored. We have used this assay to examine several features of HIV-1 splicing and to identify new examples of different mechanisms of regulation of these splicing patterns. This splicing assay can be used to explore in detail how HIV-1 splicing is regulated and, with moderate throughput, could be used to screen for structural elements, small molecules, and host factors that alter these relatively conserved splicing patterns.

A Comprehensive Analysis of Primer IDs to Study Heterogeneous HIV-1 Populations

Determining the composition of viral populations is becoming increasingly important in the field of medical virology. While recently developed computational tools for viral haplotype analysis allow for correcting sequencing errors, they do not always allow for the removal of errors occurring in the upstream experimental protocol, such as PCR errors. Primer IDs (pIDs) are one method to address this problem by harnessing redundant template resampling for error correction. By using a reference mixture of five HIV-1 strains, we show how pIDs can be useful for estimating key experimental parameters, such as the substitution rate of the PCR process and the reverse transcription (RT) error rate. In addition, we introduce a hidden Markov model for determining the recombination rate of the RT PCR process. We found no strong sequence-specific bias in pID abundances (the same RT efficiencies as compared to commonly used short, specific RT primers) and no effects of pIDs on the estimated distribution of the references viruses.

Fact and Fiction about 1%: Next Generation Sequencing and the Detection of Minor Drug Resistant Variants in HIV-1 Populations with and without Unique Molecular Identifiers

Next generation sequencing (NGS) platforms have the ability to generate almost limitless numbers of sequence reads starting with a PCR product. This gives the illusion that it is possible to analyze minor variants in a viral population. However, including a PCR step obscures the sampling depth of the viral population, the key parameter needed to understand the utility of the data set for finding minor variants. Also, these high throughput sequencing platforms are error prone at the level where minor variants are of interest, confounding the interpretation of detected minor variants. A simple strategy has been applied in multiple applications of NGS to solve these problems. Prior to PCR, individual molecules are “tagged” with a unique molecular identifier (UMI) that can be used to establish the actual sample size of viral genomes sequenced after PCR and sequencing. In addition, since PCR generates many copies of each sequence tagged to a specific UMI, a template consensus sequence (TCS) can be created from the many reads of each template, removing virtually all of the method error. From this perspective we examine our own use of a UMI, called Primer ID, in the detection of minor drug resistant variants in HIV-1 populations.