Evidence map›Paper›PMID 28813447›Full record

ArticlePloS one2017

The use of high-throughput small RNA sequencing reveals differentially expressed microRNAs in response to aster yellows phytoplasma-infection in Vitis vinifera cv. 'Chardonnay'.

Marius C Snyman, Marie-Chrystine Solofoharivelo, Rose Souza-Richards, Dirk Stephan, Shane Murray, Johan T Burger

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Fungal Effectoromics: A World in Constant Evolution.International journal of molecular sciences · 2022
    Review
  6. Differential Response of Grapevine to Infection with 'International journal of molecular sciences · 2021
    Article
  7. Article
  8. MicroRNAs in Woody Plants.Frontiers in plant science · 2021
    Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. The Emerging Role of microRNAs in Polyglutamine Diseases.Frontiers in molecular neuroscience · 2019
    Article
  15. Plant Hormones in Phytoplasma Infected Plants.Frontiers in plant science · 2019
    Review
  16. Plant Responses to Pathogen Attack: Small RNAs in Focus.International journal of molecular sciences · 2018
    Review
  17. 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

6 authors.

Marius C SnymanThe Vitis Laboratory, Department of Genetics, Stellenbosch University, Stellenbosch, South Africa.ORCID http://orcid.org/0000-0001-7793-5101
Marie-Chrystine SolofohariveloThe Vitis Laboratory, Department of Genetics, Stellenbosch University, Stellenbosch, South Africa.
Rose Souza-RichardsThe Vitis Laboratory, Department of Genetics, Stellenbosch University, Stellenbosch, South Africa.
Dirk StephanThe Vitis Laboratory, Department of Genetics, Stellenbosch University, Stellenbosch, South Africa.
Shane MurrayCentre for Proteomic and Genomic Research, Observatory, Cape Town, South Africa.
Johan T BurgerThe Vitis Laboratory, Department of Genetics, Stellenbosch University, Stellenbosch, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Phytoplasmas are cell wall-less plant pathogenic bacteria responsible for major crop losses throughout the world. In grapevine they cause grapevine yellows, a detrimental disease associated with a variety of symptoms. The high economic impact of this disease has sparked considerable interest among researchers to understand molecular mechanisms related to pathogenesis. Increasing evidence exist that a class of small non-coding endogenous RNAs, known as microRNAs (miRNAs), play an important role in post-transcriptional gene regulation during plant development and responses to biotic and abiotic stresses. Thus, we aimed to dissect complex high-throughput small RNA sequencing data for the genome-wide identification of known and novel differentially expressed miRNAs, using read libraries constructed from healthy and phytoplasma-infected Chardonnay leaf material. Furthermore, we utilised computational resources to predict putative miRNA targets to explore the involvement of possible pathogen response pathways. We identified multiple known miRNA sequence variants (isomiRs), likely generated through post-transcriptional modifications. Sequences of 13 known, canonical miRNAs were shown to be differentially expressed. A total of 175 novel miRNA precursor sequences, each derived from a unique genomic location, were predicted, of which 23 were differentially expressed. A homology search revealed that some of these novel miRNAs shared high sequence similarity with conserved miRNAs from other plant species, as well as known grapevine miRNAs. The relative expression of randomly selected known and novel miRNAs was determined with real-time RT-qPCR analysis, thereby validating the trend of expression seen in the normalised small RNA sequencing read count data. Among the putative miRNA targets, we identified genes involved in plant morphology, hormone signalling, nutrient homeostasis, as well as plant stress. Our results may assist in understanding the role that miRNA pathways play during plant pathogenesis, and may be crucial in understanding disease symptom development in aster yellows phytoplasma-infected grapevines.

Indexed as

Gene Expression Regulation, PlantHigh-Throughput Nucleotide SequencingPhytoplasmaBase SequenceComputational BiologyGene Expression ProfilingIndoleacetic AcidsMicroRNAsMolecular Sequence AnnotationNucleic Acid ConformationPlant DiseasesReproducibility of ResultsRNA InterferenceRNA, MessengerSignal TransductionVitisIndoleacetic AcidsMicroRNAsRNA, Messenger

Identifiers

PMID28813447
PMCPMC5558978

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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.