Evidence map›Paper›PMID 28786034›Full record

ReviewRice (New York, N.Y.)2017

Bioinformatics resources for deciphering the biogenesis and action pathways of plant small RNAs.

Dongliang Yu, Xiaoxia Ma, Ziwei Zuo, Weishan Shao, Huizhong Wang, Yijun Meng

Abstract readReview
In one paragraph

Review in Rice (New York, N.Y.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. MepmiRDB: a medicinal plant microRNA database.Database : the journal of biological databases and curation · 2019
    Article
  11. Plant Responses to Pathogen Attack: Small RNAs in Focus.International journal of molecular sciences · 2018
    Review
  12. Article
  13. Review
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

6 authors.

Dongliang YuCollege of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China.
Xiaoxia MaCollege of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China.
Ziwei ZuoCollege of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China.
Weishan ShaoCollege of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China.
Huizhong WangCollege of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China.
Yijun MengCollege of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, 310036, People's Republic of China. mengyijun@zju.edu.cn.ORCID http://orcid.org/0000-0002-4654-0622

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The next-generation sequencing (NGS) technology has revolutionized our previous understanding of the plant genomes, relying on its innate advantages, such as high throughput and deep sequencing depth. In addition to the protein-coding gene loci, massive transcription signals have been detected within intergenic or intragenic regions. Most of these signals belong to non-coding ones, considering their weak protein-coding potential. Generally, these transcripts could be divided into long non-coding RNAs and small non-coding RNAs (sRNAs) based on their sequence length. In addition to the well-known microRNAs (miRNAs), many plant endogenous sRNAs were collectively referred to as small interfering RNAs. However, an increasing number of unclassified sRNA species are being discovered by NGS. The high heterogeneity of these novel sRNAs greatly hampered the mechanistic studies, especially on the clear description of their biogenesis and action pathways. Fortunately, public databases, bioinformatics softwares and NGS datasets are increasingly available for plant sRNA research. Here, by summarizing these valuable resources, we proposed a general workflow to decipher the RDR (RNA-dependent RNA polymerase)- and DCL (Dicer-like)-dependent biogenesis pathways, and the Argonaute-mediated action modes (such as target cleavages and chromatin modifications) for specific sRNA species in plants. Taken together, we hope that by summarizing a list of the public resources, this work will facilitate the plant biologists to perform classification and functional characterization of the interesting sRNA species.

Indexed as

ActionBiogenesisDatabaseNext-generation sequencing (NGS)Plant small RNASoftware

Identifiers

PMID28786034
PMCPMC5545994

What OpenQuestion holds

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Registered trials

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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.