Identification of PP2C gene family and its role in stress and adversity based on T2T flax (Linum usitatissimum L.) genome
Bibliographic record
Abstract
The PP2C gene family plays crucial roles in plant growth, development, and responses to biotic/abiotic stresses. Flax (Linum usitatissimum L.), as an important oilseed and fiber crop, lacks comprehensive characterization of its PP2C genes. In this study, we conducted a genome-wide bioinformatics analysis of the PP2C gene family in flax using the Telomere to Telomere (T2T) genome assembly, identifying 117 LuPP2C genes. Phylogenetic analysis classified these LuPP2C proteins into 11 distinct subclades. Gene structure and motif analyses revealed conserved exon-intron architectures and motif compositions among members within the same phylogenetic branches. Cis-regulatory element analysis of LuPP2C promoters identified abundant stress-responsive elements, including those associated with plant hormones (MeJA and ABA) and abiotic stresses (anaerobic induction, drought responsiveness, and low-temperature adaptation). Genomic duplication events revealed 104 segmental duplication pairs, suggesting expansion through large-scale duplication. miRNA target prediction identified lus-miR395 as the predominant miRNA targeting LuPP2C family members. Expression profiling demonstrated preferential expression of most LuPP2C members in leaf tissues. Quantitative real-time PCR (qRT-PCR) analysis further revealed that subfamily A genes, particularly LuPP2C26 and LuPP2C99, were significantly upregulated under cold, drought, and salt stress conditions. Functional validation through heterologous expression confirmed that overexpression of LuPP2C26 and LuPP2C99 enhances salt tolerance in yeast transformants. These findings systematically characterize the flax PP2C family and provide insights into its potential roles in stress adaptation mechanisms.
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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".