Sequencing Framework for the Sensitive Detection and Precise Mapping of Defective Interfering Particle-Associated Deletions across Influenza A and B Viruses

Abstract

The mechanisms and consequences of defective interfering particle (DIP) formation during influenza virus infection remain poorly understood. The development of next-generation sequencing (NGS) technologies has made it possible to identify large numbers of DIP-associated sequences, providing a powerful tool to better understand their biological relevance. However, NGS approaches pose numerous technical challenges, including the precise identification and mapping of deletion junctions in the presence of frequent mutation and base-calling errors, and the potential for numerous experimental and computational artifacts. Here, we detail an Illumina-based sequencing framework and bioinformatics pipeline capable of generating highly accurate and reproducible profiles of DIP-associated junction sequences. We use a combination of simulated and experimental control data sets to optimize pipeline performance and demonstrate the absence of significant artifacts. Finally, we use this optimized pipeline to reveal how the patterns of DIP-associated junction formation differ between different strains and subtypes of influenza A and B viruses and to demonstrate how these data can provide insight into mechanisms of DIP formation. Overall, this work provides a detailed roadmap for high-resolution profiling and analysis of DIP-associated sequences within influenza virus populations. IMPORTANCE Influenza virus defective interfering particles (DIPs) that harbor internal deletions within their genomes occur naturally during infection in humans and during cell culture. They have been hypothesized to influence the pathogenicity of the virus; however, their specific function remains elusive. The accurate detection of DIP-associated deletion junctions is crucial for understanding DIP biology but is complicated by an array of technical issues that can bias or confound results. Here, we demonstrate a combined experimental and computational framework for detecting DIP-associated deletion junctions using next-generation sequencing (NGS). We detail how to validate pipeline performance and provide the bioinformatics pipeline for groups interested in using it. Using this optimized pipeline, we detect hundreds of distinct deletion junctions generated during infection with a diverse panel of influenza viruses and use these data to test a long-standing hypothesis concerning the molecular details of DIP formation.

Single-Cell Analysis Uncovers a Vast Diversity in Intracellular Viral Defective Interfering RNA Content Affecting the Large Cell-to-Cell Heterogeneity in Influenza A Virus Replication

“…Indeed, using sequence analysis, we observed a high heterogeneity in the coverage profiles of viral mRNAs, in particular for S3, which may indicate the presence of DI mRNAs ( Figure S3). For a more detailed analysis, we developed a computational workflow (similarly seen elsewhere [39,57]) as illustrated in Figure 4A, aiming to pinpoint individual DI mRNAs. Briefly, paired-end reads were mapped against the influenza genome providing an estimate of the distance (insert size) of the mate pairs.…”

Differential alphavirus defective RNA diversity between intracellular and encapsidated compartments is driven by subgenomic recombination events

“…RNAseq libraries were then constructed using the previously described ClickSeq library preparation method optimized for the discovery of rare recombination events (43, 44) and sequenced on an Illumina NextSeq550. Reads were trimmed and filtered using fastp (45) and analyzed using the ViReMa v1.5 pipeline, which provides alignment data, recombination events, and associated count data (20, 44, 46). This study design was repeated once with one replicate and a second time with 3 replicates (used for statistical analyses).…”

Structure and Function of the Influenza Virus Transcription and Replication Machinery

“…Next-generation sequencing of DI RNAs has shown that deletions can occur in any genome segment, but that some segments are more prone to give rise to DI RNAs than other segments. Specifically, DI RNAs derived from the three polymerase encoding segments are most frequently observed (Saira et al 2013;Alnaji et al 2019). DI RNAs are generated through a still poorly defined mechanism, in which the viral polymerase ceases product elongation at one site of the viral RNA template, only to resume elongation at a downstream site, which results in a failure to copy the interlaying stretch of the template (Fig.…”

“…It has been hypothesized that an intramolecular copy-choice mechanism could be involved, in which resumption of RNA synthesis could be dependent on base-pairing between the 3 0 end of the nascent product and the RNA template. However, a recent analysis of the sequences that flank the deletion (i.e., polymerase stop and restart site) found no evidence for the enrichment of direct repeat sequences at junctions, which argues against a significant role for direct repeats in DI RNA formation (Alnaji et al 2019). Interestingly, DI RNAs encode open reading frames and could express viral protein fragments or novel proteins that may have a function in the viral replication cycle (Akkina et al 1984;Boergeling et al 2015).…”