Cell wall remodeling confers plant architecture with distinct wall structure in <i>Nelumbo nucifera</i>
Bibliographic record
Abstract
Lotus (Nelumbo nucifera G.) is a perennial aquatic horticultural plant with diverse architectures. Distinct plant architecture (PA) has certain attractive and practical qualities, but its genetic morphogenesis in lotus remains elusive. In this study, we employ genome-wide association analysis (GWAS) for the seven traits of petiole length (PLL), leaf length (LL), leaf width (LW), peduncle length (PLF), flower diameter (FD), petal length (PeL), and petal width (PeW) in 301 lotus accessions. A total of 90 loci are identified to associate with these traits across 4 years of trials. Meanwhile, we perform RNA sequencing (RNA-seq) to analyze the differential expression of the gene (DEG) transcripts between large and small PA (LPA and SPA) of lotus stems (peduncles and petioles). As a result, eight key candidate genes are identified that are all primarily involved in plant cell wall remodeling significantly associated with PA traits by integrating the results of DEGs and GWAS. To verify this result, we compare the cell wall compositions and structures of LPA versus SPA in representative lotus germplasms. Intriguingly, compared with the SPA lotus, the LPA varieties have higher content of cellulose and hemicellulose, but less filling substrates of pectin and lignin. Additionally, we verified longer cellulose chains and higher cellulose crystallinity with less interference in LPA varieties. Taken together, our study illustrates how plant cell wall remodeling affects PA in lotus, shedding light on the genetic architecture of this significant ornamental trait and offering a priceless genetic resource for future genomic-enabled breeding.
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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 | 0.000 | 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".