Evidence map›Paper›PMID 33347517›Full record

ArticlePloS one2020

In silico identification and characterization of AGO, DCL and RDR gene families and their associated regulatory elements in sweet orange (Citrus sinensis L.).

Md Parvez Mosharaf, Hafizur Rahman, Md Asif Ahsan, Zobaer Akond, Fee Faysal Ahmed, Md Mazharul Islam, Mohammad Ali Moni, Md Nurul Haque Mollah

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Review
  3. Genome-wide identification and characterization ofFrontiers in plant science · 2026
    Article
  4. Article
  5. Genome-Wide Identification and Characterization ofInternational journal of molecular sciences · 2025
    Article
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  17. ComprehensiveBioMed research international · 2022
    Article
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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

8 authors.

Md Parvez MosharafBioinformatics Laboratory, Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh.
Hafizur RahmanDepartment of Microbiology, Rajshahi Institute of Biosciences, University of Rajshahi, Rajshahi, Bangladesh.
Md Asif AhsanBioinformatics Laboratory, Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh.
Zobaer AkondBioinformatics Laboratory, Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh.ORCID 0000-0002-8557-7145
Fee Faysal AhmedBioinformatics Laboratory, Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh.
Md Mazharul IslamBioinformatics Laboratory, Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh.
Mohammad Ali MoniThe University of Sydney, Sydney Medical School, School of Medical Sciences, Discipline of Biomedical Science, Sydney, New South Wales, Australia.
Md Nurul Haque MollahBioinformatics Laboratory, Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh.ORCID 0000-0002-3883-3396

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA interference (RNAi) plays key roles in post-transcriptional and chromatin modification levels as well as regulates various eukaryotic gene expressions which are involved in stress responses, development and maintenance of genome integrity during developmental stages. The whole mechanism of RNAi pathway is directly involved with the gene-silencing process by the interaction of Dicer-Like (DCL), Argonaute (AGO) and RNA-dependent RNA polymerase (RDR) gene families and their regulatory elements. However, these RNAi gene families and their sub-cellular locations, functional pathways and regulatory components were not extensively investigated in the case of economically and nutritionally important fruit plant sweet orange (Citrus sinensis L.). Therefore, in silico characterization, gene diversity and regulatory factor analysis of RNA silencing genes in C. sinensis were conducted by using the integrated bioinformatics approaches. Genome-wide comparison analysis based on phylogenetic tree approach detected 4 CsDCL, 8 CsAGO and 4 CsRDR as RNAi candidate genes in C. sinensis corresponding to the RNAi genes of model plant Arabidopsis thaliana. The domain and motif composition and gene structure analyses for all three gene families exhibited almost homogeneity within the same group members. The Gene Ontology enrichment analysis clearly indicated that the predicted genes have direct involvement into the gene-silencing and other important pathways. The key regulatory transcription factors (TFs) MYB, Dof, ERF, NAC, MIKC_MADS, WRKY and bZIP were identified by their interaction network analysis with the predicted genes. The cis-acting regulatory elements associated with the predicted genes were detected as responsive to light, stress and hormone functions. Furthermore, the expressed sequence tag (EST) analysis showed that these RNAi candidate genes were highly expressed in fruit and leaves indicating their organ specific functions. Our genome-wide comparison and integrated bioinformatics analyses provided some necessary information about sweet orange RNA silencing components that would pave a ground for further investigation of functional mechanism of the predicted genes and their regulatory factors.

Indexed as

Argonaute ProteinsCitrus sinensisComputer SimulationExpressed Sequence TagsFruitGene Expression ProfilingGene Expression Regulation, PlantGenes, PlantGenome, PlantMultigene FamilyPhylogenyPlant ProteinsRegulatory Sequences, Nucleic AcidRibonuclease IIIRNA-Dependent RNA PolymeraseRNA InterferenceArgonaute ProteinsPlant ProteinsRibonuclease IIIRNA-Dependent RNA PolymeraseTranscription Factors

Identifiers

PMID33347517
PMCPMC7751981

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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.