Corton, M. | bioRxiv Science

bioRxiv2022

Mini-IsoQLR: a pipeline for isoform quantification using long-reads sequencing data for single locus analysis

DNA variants altering the pre-mRNA splicing process represent an underestimated cause of human genetic diseases. Their association with disease traits should be confirmed using functional assays from patient cell lines or other alternative models to detect the formation of aberrant mRNAs. Long-read sequencing is a suitable technique to identify and quantify mRNA isoforms. Available isoform clusterization and/or quantification tools are generally designed for the whole transcriptome analysis. Experiments focusing on a single locus analysis need more precise data fine-tuning and visualization tools. Here we describe VIsoQLR, an interactive analyzer, viewer and editor for the semi-automated identification and quantification of known and novel isoforms using long-read sequencing data. VIsoQLR is tailored to thoroughly analyze mRNA expression and maturation in low-throughput splicing assays. This tool takes sequences aligned to a reference, defines consensus splice sites, and quantifies isoforms. Users can edit splice sites through dynamic and interactive graphics and tables as part of their manual curation. Known transcripts, or isoforms detected by other methods, can also be imported as references for comparison. Here, we explain VIsoQLR principles and features, and show its applicability in a case study example using Nanopore sequencing. VIsoQLR is available at https://github.com/TBLabFJD/VIsoQLR.

bioinformatics↗

bioRxiv2022

SARS-CoV-2 Point Mutation and Deletion Spectra, and Their Association with Different Disease Outcome

Mutant spectra of RNA viruses are important to understand viral pathogenesis, and response to selective pressures. There is a need to characterize the complexity of mutant spectra in coronaviruses sampled from infected patients. In particular, the possible relationship between SARS-CoV-2 mutant spectrum complexity and disease associations has not been established. In the present study, we report an ultra-deep sequencing (UDS) analysis of the mutant spectrum of amplicons from the nsp12 (polymerase)- and spike (S)-coding regions of thirty nasopharyngeal isolates (diagnostic samples) of SARS-CoV-2 of the first COVID-19 pandemic wave (Madrid, Spain, April 2020) classified according to the severity of ensuing COVID-19. Low frequency mutations and deletions, counted relative to the consensus sequence of the corresponding isolate, were overwhelmingly abundant. We show that the average number of different point mutations, mutations per haplotype and several diversity indices was significantly higher in SARS-CoV-2 isolated from patients who developed mild disease than in those associated with moderate or severe disease (exitus). No such bias was observed with RNA deletions. Location of amino acid substitutions in the three dimensional structures of nsp12 (polymerase) and S suggest significant structural or functional effects. Thus, patients who develop mild symptoms may be a richer source of genetic variants of SARS-CoV-2 than patients with moderate or severe COVID-19. IMPORTANCEThe study shows that mutant spectra of SARS-CoV-2 from diagnostic samples differ in point mutation abundance and complexity, and that significantly larger values were observed in virus from patients who developed mild COVID-19 symptoms. Mutant spectrum complexity is not a uniform trait among isolates. The nature and location of low frequency amino acid substitutions present in mutant spectra anticipate great potential for phenotypic diversification of SARS-CoV-2.

microbiology↗