Comparative Genome-wide Analysis and Expression Profiling of Histone Acetyltransferase (HAT) Gene Family in Response to Hormonal Applications, Metal and Abiotic Stresses in Cotton
Bibliographic record
Abstract
Post-translational modifications are involved in regulating diverse developmental processes. Histone acetyltransferases (HATs) play vital roles in the regulation of chromation structure and activate the gene transcription implicated in various cellular processes. However, HATs in cotton, as well as their regulation in response to developmental and environmental cues, remain unidentified. In this study, 9 HATs were identified from Gossypium raimondi and Gossypium arboretum, while 18 HATs were identified from Gossypium hirsutum. Based on their amino acid sequences, Gossypium HATs were divided into three groups: CPB, GNAT, and TAFII250. Almost all the HATs within each subgroup share similar gene structure and conserved motifs. Gossypium HATs are unevenly distributed on the chromosomes, and duplication analysis suggests that Gossypium HATs are under strong purifying selection. Gene expression analysis showed that Gossypium HATs were differentially expressed in various vegetative tissues and at different stages of fiber development. Furthermore, all the HATs were differentially regulated in response to various stresses (salt, drought, cold, heavy metal and DNA damage) and hormones (abscisic acid (ABA) and auxin (NAA)). Finally, co-localization of HAT genes with reported quantitative trait loci (QTL) of fiber development were reported. Altogether, these results highlight the functional diversification of HATs in cotton growth and fiber development, as well as in response to different environmental cues. This study enhances our understanding of function of histone acetylation in cotton growth, fiber development, and stress adaptation, which will eventually lead to the long-term improvement of stress tolerance and fiber quality in cotton.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".