Evidence map›Paper›PMID 32020912›Full record

ReviewJournal of biosciences2020

Target-specific gene delivery in plant systems and their expression: Insights into recent developments.

Debdyuti Nandy, Amrita Maity, Arup Kumar Mitra

Abstract readReview
PubMed
In one paragraph

Review in Journal of biosciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

7 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Application of Nanotechnology in Plant Genetic Engineering.International journal of molecular sciences · 2023
    Review
  4. Review
  5. Review
  6. Review
  7. CRISPR-Cas9/CRISPRi tools for cell factory construction in E. coli.World journal of microbiology & biotechnology · 2020
    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

3 authors at 2 institutions in 1 country.

Debdyuti NandyCSIR-Indian Institute of Chemical Biology, Jadavpur, Kolkata 700 032, India.
Amrita Maity
Arup Kumar Mitra
St Xavier’s College · INIndian Institute of Chemical Biology · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to improve crop plants in terms of their yield, drought resistance, pest resistance, nutritional value, etc., modern agriculture has relied upon plant genetic engineering. Since the advent of recombinant DNA technology, several tools have been used for genetic transformations in plants such as Agrobacterium tumefaciens, virus-mediated gene transfer, direct gene transfer systems such as electroporation, particle gun, microinjection and chemical methods. All these traditional methods lack specificity and the transgenes are integrated at random sites in the plant DNA. Recently novel techniques for gene targeting have evolved such as engineered nucleases such as Zinc Finger Nucleases, Transcription Activator like effector nucleases, Clustered regular interspaced short palindromic repeats. Other advances include improvement in tools for delivery of gene editing components which include carrier proteins, and carbon nanotubes. The present review focuses on the latest techniques for target specific gene delivery in plants, their expression and future directions in plant biotechnology.

Indexed as

CRISPR-Cas SystemsEndonucleasesGene EditingGene TargetingGenetic EngineeringGenetic TherapyHomologous RecombinationNanotubes, CarbonPlantsTranscription Activator-Like Effector NucleasesZinc Finger NucleasesEndonucleasesNanotubes, CarbonTranscription Activator-Like Effector NucleasesZinc Finger Nucleases

Identifiers

PMID32020912
OpenAlexW3007420592

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.