ArticleViruses2020
Determining the Suitability of MinION's Direct RNA and DNA Amplicon Sequencing for Viral Subtype Identification.
Article in Viruses, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Pooled it
- Primer-Less Species Identification Throughout Fungal (International journal of molecular sciences · 2026Article
- Unveiling the Human Gastrointestinal Tract Microbiome: The Past, Present, and Future of Metagenomics.Biomedicines · 2023Review
- How do emerging long-read sequencing technologies function in transforming the plant pathology research landscape?Plant molecular biology · 2022Review
- Expedited retrieval of high-quality Usutu virus genomesFrontiers in microbiology · 2022Article
- Third-Generation Sequencing: The Spearhead towards the Radical Transformation of Modern Genomics.Life (Basel, Switzerland) · 2021Review
- Grapevine Virology in the Third-Generation Sequencing Era: From Virus Detection to Viral Epitranscriptomics.Plants (Basel, Switzerland) · 2021Review
- Long-read sequencing reveals the evolutionary drivers of intra-host diversity across natural RNA mycovirus infections.Virus evolution · 2021Article
- Characterising Foot-and-Mouth Disease Virus in Clinical Samples Using Nanopore Sequencing.Frontiers in veterinary science · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The MinION sequencer is increasingly being used for the detection and outbreak surveillance of pathogens due to its rapid throughput. For RNA viruses, MinION's new direct RNA sequencing is the next significant development. Direct RNA sequencing studies are currently limited and comparisons of its diagnostic performance relative to different DNA sequencing approaches are lacking as a result. We sought to address this gap and sequenced six subtypes from the mycovirus CHV-1 using MinION's direct RNA sequencing and DNA sequencing based on a targeted viral amplicon. Reads from both techniques could correctly identify viral presence and species using BLAST, though direct RNA reads were more frequently misassigned to closely related CHV species. De novo consensus sequences were error prone but suitable for viral species identification. However, subtype identification was less accurate from both reads and consensus sequences. This is due to the high sequencing error rate and the limited sequence divergence between some CHV-1 subtypes. Importantly, neither RNA nor amplicon sequencing reads could be used to obtain reliable intra-host variants. Overall, both sequencing techniques were suitable for virus detection, though limitations are present due to the error rate of MinION reads.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.