Genome‐Wide Identification and Evolution of Core Cell Cycle Genes in <scp> <i>Marchantia polymorpha</i> </scp> : Insights Into Redundancy, Stress, and Functional Evolution
Bibliographic record
Abstract
The cell cycle is a fundamental process of plant growth, development, and reproduction, in which cyclin-dependent kinases (CDKs) and cyclins (CYCs) play central roles in regulating the progression through various stages. These proteins are coordinated with multiple interacting partners to ensure the accurate execution of essential biological events such as DNA replication, chromosome segregation, and cell division. Marchantia polymorpha, one of the earliest diverging land plant species, has emerged as a key model for exploring fundamental mechanisms in plant biology and evolution. However, compared with other model plants, such as Arabidopsis thaliana and Oryza sativa, the core cell cycle genes in M. polymorpha remain relatively uncharacterized. In this study, we identified 31 core cell cycle genes in M. polymorpha through genome-wide analysis, including 13 CDKs, 8 CYCs, 5 E2F/DPs, 1 ICK, 1 RB, 1 CKS, and 2 Wee1 genes. We further analyzed their physicochemical properties, gene structures, and conserved domains, along with evolutionary pressures assessed via Ka/Ks and 4DTv analyses. Comparative genomic analysis revealed patterns of gene contraction and expansion. Additionally, we predicted cis-acting regulatory elements and performed differential expression analysis under various stress conditions to explore their potential functions and expression profiles. Finally, a protein-protein interaction (PPI) network was constructed, and key genes were experimentally validated. These findings provide valuable insights into the core cell cycle gene family in M. polymorpha, contributing to an enhanced understanding of cell cycle regulation and its evolutionary significance in plants.
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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".