Evidence map›Paper›PMID 34551006›Full record

ArticlePloS one2021

In silico analysis enabling informed design for genome editing in medicinal cannabis; gene families and variant characterisation.

L Matchett-Oates, S Braich, G C Spangenberg, S Rochfort, N O I Cogan

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Expanding Gene-Editing Potential in Crop Improvement with Pangenomes.International journal of molecular sciences · 2022
    Review
  3. Frontiers in plant science · 2022
    Article
  4. Manipulation of Cannabinoid BiosynthesisFrontiers in plant science · 2021
    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

5 authors at 1 institution in 1 country.

L Matchett-OatesAgriculture Victoria, AgriBio, The Centre for AgriBioscience, Bundoora, Victoria, Australia.ORCID 0000-0002-4953-7402
S BraichAgriculture Victoria, AgriBio, The Centre for AgriBioscience, Bundoora, Victoria, Australia.
G C SpangenbergAgriculture Victoria, AgriBio, The Centre for AgriBioscience, Bundoora, Victoria, Australia.
S RochfortAgriculture Victoria, AgriBio, The Centre for AgriBioscience, Bundoora, Victoria, Australia.
N O I CoganAgriculture Victoria, AgriBio, The Centre for AgriBioscience, Bundoora, Victoria, Australia.
La Trobe University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCannabis has been used worldwide for centuries for industrial, recreational and medicinal use, however, to date no successful attempts at editing genes involved in cannabinoid biosynthesis have been reported. This study proposes and develops an in silico best practices approach for the design and implementation of genome editing technologies in cannabis to target all genes involved in cannabinoid biosynthesis.

resultsA large dataset of reference genomes was accessed and mined to determine copy number variation and associated SNP variants for optimum target edit sites for genotype independent editing. Copy number variance and highly polymorphic gene sequences exist in the genome making genome editing using CRISPR, Zinc Fingers and TALENs technically difficult. Evaluation of allele or additional gene copies was determined through nucleotide and amino acid alignments with comparative sequence analysis performed. From determined gene copy number and presence of SNPs, multiple online CRISPR design tools were used to design sgRNA targeting every gene, accompanying allele and homologs throughout all involved pathways to create knockouts for further investigation. Universal sgRNA were designed for highly homologous sequences using MultiTargeter and visualised using Sequencher, creating unique sgRNA avoiding SNP and shared nucleotide locations targeting optimal edit sites.

conclusionsUsing this framework, the approach has wider applications to all plant species regardless of ploidy number or highly homologous gene sequences. SIGNIFICANCE STATEMENT: Using this framework, a best-practice approach to genome editing is possible in all plant species, including cannabis, delivering a comprehensive in silico evaluation of the cannabinoid pathway diversity from a large set of whole genome sequences. Identification of SNP variants across all genes could improve genome editing potentially leading to novel applications across multiple disciplines, including agriculture and medicine.

Indexed as

Genome, PlantCannabinoidsCannabisClustered Regularly Interspaced Short Palindromic RepeatsDNA Copy Number VariationsGene EditingPolymorphism, Single NucleotideRNA, Guide, CRISPR-Cas SystemsUser-Computer InterfaceCannabinoidsRNA, Guide, CRISPR-Cas Systems

Identifiers

PMID34551006
PMCPMC8457487
OpenAlexW3201314263

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.