Histone Deacetylase (HDAC) Gene Family in Allotetraploid Cotton and Its Diploid Progenitors: In Silico Identification, Molecular Characterization, and Gene Expression Analysis under Multiple Abiotic Stresses, DNA Damage and Phytohormone Treatments
Bibliographic record
Abstract
Histone deacetylases (HDACs) play a significant role in a plant’s development and response to various environmental stimuli by regulating the gene transcription. However, HDACs remain unidentified in cotton. In this study, a total of 29 HDACs were identified in allotetraploid Gossypium hirsutum, while 15 and 13 HDACs were identified in Gossypium arboretum and Gossypium raimondii, respectively. Gossypium HDACs were classified into three groups (reduced potassium dependency 3 (RPD3)/HDA1, HD2-like, and Sir2-like (SRT) based on their sequences, and Gossypium HDACs within each subgroup shared a similar gene structure, conserved catalytic domains and motifs. Further analysis revealed that Gossypium HDACs were under a strong purifying selection and were unevenly distributed on their chromosomes. Gene expression data revealed that G. hirsutum HDACs were differentially expressed in various vegetative and reproductive tissues, as well as at different developmental stages of cotton fiber. Furthermore, some G. hirsutum HDACs were co-localized with quantitative trait loci (QTLs) and single-nucleotide polymorphism (SNPs) of fiber-related traits, indicating their function in fiber-related traits. We also showed that G. hirsutum HDACs were differentially regulated in response to plant hormones (abscisic acid (ABA) and auxin), DNA damage agent (methyl methanesulfonate (MMS)), and abiotic stresses (cold, salt, heavy metals and drought), indicating the functional diversity and specification of HDACs in response to developmental and environmental cues. In brief, our results provide fundamental information regarding G. hirsutum HDACs and highlight their potential functions in cotton growth, fiber development and stress adaptations, which will be helpful for devising innovative strategies for the improvement of cotton fiber and stress tolerance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".