ArticleBMC plant biology2026
The identification of gibberellin 2-oxidase gene family in cotton and functional analysis.
Article in BMC plant biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- The Gibberellin 2-Oxidase GeneInternational journal of molecular sciences · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
backgroundGibberellin (GA) homeostasis is critical for plant growth and development, with gibberellin 2-oxidases (GA2oxs) functioning as key regulators by deactivating bioactive GAs. Mepiquat chloride (MC), a widely used plant growth regulator in cotton production, effectively suppresses vegetative growth to improve yield and fiber quality, yet its molecular mechanisms, particularly concerning GA catabolism, remain incompletely understood.
methodsIn this study, a genome-wide identification of GA2ox genes was performed in upland cotton (Gossypium hirsutum), followed by systematic analysis of their gene structures, conserved protein motifs, chromosomal locations, and expression patterns. Virus-induced gene silencing (VIGS) technology was used for perform functional validation of two candidate genes, GhGA2ox6 and GhGA2ox31. RNA-sequencing was used to explore the differentially expressed genes and enriched pathways in GhGA2ox6-silenced plants. Weighted gene co-expression network analysis (WGCNA) was further employed to explore the key gene modules and Hub genes associated with hormone pathways.
resultsA total of 39 GhGA2ox genes were identified and classified into three subfamilies: C20-GA2ox-I, C19-GA2ox-I, and C19-GA2ox-II. Expression profiling analysis revealed that tissue-specific patterns of GhGA2ox genes, and GhGA2ox6 and GhGA2ox31 were significantly up-regulated in response to MC treatment. VIGS-mediated silencing of GhGA2ox6 resulted in a marked increase in cotton plant height, while silencing GhGA2ox31 had no obvious phenotypic change. Further transcriptomic profiling analysis found that the height-promoting phenotype of GhGA2ox6-silenced plants was driven by a coordinated multi-hormone regulatory network involving gibberllins, auxins, and cytokinins. WGCNA identified 3 gene modules were significantly associated with hormone contents, and 36 Hub genes involved in ethylene, auxin, jasmonate, and gibberenllin pathways.
conclusionsCollectively, our findings indicate that GhGA2ox6 acts as a negative regulator of cotton plant height and is involved in MC-mediated growth regulation. The WGCNA further complemented the multi-hormone coordinated regulatory mechanism underlying GhGA2ox6 function. This study provides novel insights into the molecular mechanisms underlying MC-regulated cotton growth and offers a potential target gene for modulating cotton plant growth via genetic engineering techniques.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.