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Record W4410703862 · doi:10.1016/j.indcrop.2025.121225

Molecular identification of sugarcane glyceraldehyde-3-phosphate dehydrogenases and their involvement in SCMV infection in sugarcane

2025· article· en· W4410703862 on OpenAlexaff
Zongtao Yang, Kang Zeng, Quanxin Yu, Wendi Jiao, T. Luo, Zhiyuan Cui, Ruikun Chai, Haoming Liu, Yifei Li, Zhang Hai, Heyang Shang, Lu Wang, Guoqiang Huang, Jingsheng Xu

Bibliographic record

VenueIndustrial Crops and Products · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsMinistry of Agriculture
FundersNational Key Research and Development Program of ChinaFujian Agriculture and Forestry UniversityNatural Science Foundation of Fujian Province
KeywordsGlyceraldehyde 3-phosphate dehydrogenaseIdentification (biology)SaccharumBiologyBiotechnologyChemistryBiochemistryEnzymeDehydrogenaseBotany

Abstract

fetched live from OpenAlex

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is one of the key enzymes of glycolysis and plays important roles in plant growth, development and plant–pathogen interactions. However, studies on the characteristics and functions of sugarcane ( Saccharum spp. hybrid) GAPDH family genes are still lacking. In the present study, 24, 75 and 91 GAPDH genes were identified in Saccharum spontaneum and sugarcane cultivars R570 and XTT22 , respectively. A phylogenetic tree revealed that these genes could be divided into four groups, i.e., the GAPC group, the GAPA group, the GAPB group and the GAPCp group. These GAPDH genes contained multiple cis -acting elements related to stress and hormone response. RNA-seq analysis demonstrated that the S. spontaneum GAPDH genes and XTT22-GAPDH genes were constitutively expressed at different developmental stages or in different tissues. ScGAPA , ScGAPB , ScGAPC and ScGAPCp , representatives of each group of the GAPDH family, were isolated from the sugarcane cultivar XTT22 . RT qPCR analysis revealed that the expression levels of ScGAPA and ScGAPB were exponentially greater than those of ScGAPC or ScGAPCp in the leaves; these four genes were differentially expressed upon SCMV infection and after abiotic treatments such as NaCl, salicylic acid, H 2 O 2 or MeJA. DAB staining and detection of ATG8-I and ATG8-II demonstrated that SCMV infection induces bursts of reactive oxygen species and autophagy in sugarcane leaves. ScGAPA, ScGAPB, ScGAPC, and ScGAPCp interacted with ScATG3, thereby suppressing autophagy in Nicotiana benthamiana plants. However, oxidative stress impaired the interaction of ScATG3 with ScGAPA, ScGAPB, ScGAPC and ScGAPCp, indicating that SCMV infection activates autophagy by disrupting ScGAPDH–ScATG3 interactions. The present study reveals the origin and evolution of the GAPDH gene family in sugarcane and the potential roles of this gene family in response to sugarcane mosaic virus (SCMV) infection. Interaction of ScGAPDHs with ScATG3 balances with ROS and autophagy upon SCMV infection. Normally, ScGAPDHs interact with ScATG3, which inhibits the autophagy. ROS was generated upon SCMV infection. Under without SCMV conditions, ScGAPA, ScGAPB, ScGAPC, ScGAPCp interaction with ScATG3. Under SCMV conditions, Intracellular production of ROS in sugarcane leaves, along with upregulated expression levels of ScGAPA, ScGAPC, ScGAPCp and downregulated expression levels of ScGAPB. meanwhile, ROS inhibit the interaction of ScGAPA, ScGAPB, ScGAPC, ScGAPCp interaction with ScATG3 and thereby induce autophagy. • A total of 190 GAPDH genes were identified in S. spontaneum , R570 and XTT22 genome. • ScGAPA , ScGAPB , ScGAPC , and ScGAPCp are differently expressed upon SCMV infection. • Sugarcane GAPDHs interact with ScATG3, thereby suppressing autophagy. • ROS impairs the interaction of Sugarcane GAPDHs with ScATG3 and enhances autophagy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.261
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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