Evidence map›Paper›PMID 27649158›Full record

ArticleInternational journal of molecular sciences2016

Identification of Reference Genes for RT-qPCR Data Normalization in Cannabis sativa Stem Tissues.

Lauralie Mangeot-Peter, Sylvain Legay, Jean-Francois Hausman, Sergio Esposito, Gea Guerriero

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

22 citing papers in PubMed, 41 citations in OpenAlex.

  1. Article
  2. Selection and Validation of Reference Genes inPlants (Basel, Switzerland) · 2024
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  4. Challenges toInternational journal of molecular sciences · 2023
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  5. Article
  6. Assessing the adaptive role of cannabidiol (CBD) inFrontiers in plant science · 2023
    Article
  7. Article
  8. Article
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  13. Article
  14. Selection of reference genes for quantitative real-time PCR analysis of photosynthesis-related genes expression inPhysiology and molecular biology of plants : an international journal of functional plant biology · 2019
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  15. Article
  16. 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

5 authors at 2 institutions in 2 countries.

Lauralie Mangeot-PeterEnvironmental Research and Innovation (ERIN), Luxembourg Institute of Science and Technology (LIST), L-4362 Esch/Alzette, Luxembourg. lauralie.mangeot@yahoo.fr.
Sylvain LegayEnvironmental Research and Innovation (ERIN), Luxembourg Institute of Science and Technology (LIST), L-4362 Esch/Alzette, Luxembourg. sylvain.legay@list.lu.
Jean-Francois HausmanEnvironmental Research and Innovation (ERIN), Luxembourg Institute of Science and Technology (LIST), L-4362 Esch/Alzette, Luxembourg. jean-francois.hausman@list.lu.
Sergio EspositoDipartimento di Biologia, Università di Napoli "Federico II", Via Cinthia, I-80126 Napoli, Italy. sergio.esposito@unina.it.
Gea GuerrieroEnvironmental Research and Innovation (ERIN), Luxembourg Institute of Science and Technology (LIST), L-4362 Esch/Alzette, Luxembourg. gea.guerriero@list.lu.
Luxembourg Institute of Science and Technology · LUUniversity of Naples Federico II · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene expression profiling via quantitative real-time PCR is a robust technique widely used in the life sciences to compare gene expression patterns in, e.g., different tissues, growth conditions, or after specific treatments. In the field of plant science, real-time PCR is the gold standard to study the dynamics of gene expression and is used to validate the results generated with high throughput techniques, e.g., RNA-Seq. An accurate relative quantification of gene expression relies on the identification of appropriate reference genes, that need to be determined for each experimental set-up used and plant tissue studied. Here, we identify suitable reference genes for expression profiling in stems of textile hemp (Cannabis sativa L.), whose tissues (isolated bast fibres and core) are characterized by remarkable differences in cell wall composition. We additionally validate the reference genes by analysing the expression of putative candidates involved in the non-oxidative phase of the pentose phosphate pathway and in the first step of the shikimate pathway. The goal is to describe the possible regulation pattern of some genes involved in the provision of the precursors needed for lignin biosynthesis in the different hemp stem tissues. The results here shown are useful to design future studies focused on gene expression analyses in hemp.

Indexed as

Genes, PlantCannabisGene Expression Regulation, PlantPlant ProteinsPlant StemsReal-Time Polymerase Chain ReactionRNA, PlantPlant ProteinsRNA, PlantCannabis sativacell wallgene expressionlignificationreference genes

Identifiers

PMID27649158
PMCPMC5037828
OpenAlexW2519612541

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.