Evidence map›Paper›PMID 34845701›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Culture-Independent Discovery of Viroids by Deep Sequencing and Computational Algorithms.

Ali Raza, Shou-Wei Ding, Qingfa Wu

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 2 countries.

Ali RazaHefei National Laboratory for Physical Sciences at Microscale, School of Life Sciences, University of Science and Technology of China, Hefei, China.
Shou-Wei DingDepartment of Microbiology and Plant Pathology, University of California, Riverside, CA, USA. shou-wei.ding@ucr.edu.
Qingfa WuHefei National Laboratory for Physical Sciences at Microscale, School of Life Sciences, University of Science and Technology of China, Hefei, China. wuqf@ustc.edu.cn.
Hefei National Center for Physical Sciences at Nanoscale · CNUniversity of California, Riverside · USUniversity of Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Viroids are single-stranded circular RNA molecules that cause diseases in plants and do not encode any protein. Classical approaches for the identification of new viroids are challenging for many plant pathology laboratories as viroid cDNA synthesis and sequencing require purification and enrichment of the naked viroid RNA by two-dimensional gel electrophoresis. Conventional metagenomic approaches are not effective for viroid discovery because the total number of known viroids is small, and distinct viroids share limited nucleotide sequence similarity. In this chapter, we describe a homology-independent approach for the identification of both known and new viroids in disease samples. It is known that viroid infection of plants triggers production of overlapping viroid-derived small interfering RNAs (siRNAs) targeting the entire genome with high densities and that replication of viroids occurs via a rolling-circle mechanism to yield head-to-tail multiple-repeat replicative intermediates. Our approach involves deep sequencing of either long or small RNAs in a disease sample followed by viroid identification with a unique computational algorithm, progressive filtering of overlapping small RNAs (PFOR). Among the sequenced total small RNAs, PFOR retains viroid-derived siRNAs for viroid genome assembly by progressively eliminating nonoverlapping small RNAs and those that overlap but cannot be assembled into a direct repeat RNA, a unique feature of viroid RNA replication. In contrast, long RNAs sequenced after depletion of ribosomal RNAs are cut into 21-nucleotide virtual overlapping small RNAs with the algorithm SLS (splitting longer read into shorter fragments) before PFOR. We show that new viroids or viroids from the two known families are readily identified and their full-length sequences recovered by PFOR from long or small RNAs sequenced directly from infected plants. We propose that our approach can be used for viroid discovery in both plants and potentially animals since PFOR identifies viroids by searching for circular RNAs or a unique replication intermediate of the viroid genome in a sequence homology-independent manner.

Indexed as

ViroidsAlgorithmsHigh-Throughput Nucleotide SequencingHumansPlant DiseasesPlantsRNARNA, CircularRNA, ViralRNARNA, CircularRNA, ViralHomology-independent pathogen discoveryProgressive filtering of overlapping small RNAs (PFOR)Splitting longer read into shorter fragments (SLS)Viroids

Identifiers

PMID34845701
OpenAlexW3214755617

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.