RNA-Seq Analysis of Plant Maturity in Crested Wheatgrass (Agropyron cristatum L.)
Bibliographic record
Abstract
Crested wheatgrass (Agropyron cristatum L.) breeding programs aim to develop later maturing cultivars for extending early spring grazing in Western Canada. Plant maturity is a complex genetic trait, and little is known about genes associated with late maturity in this species. An attempt was made using RNA-Seq to profile the transcriptome of crested wheatgrass maturity and to analyze differentially expressed genes (DEGs) between early and late maturing lines. Three cDNA libraries for each line were generated by sampling leaves at the stem elongation stage, spikes at the boot and anthesis stages. A total of 75,218,230 and 74,015,092 clean sequence reads were obtained for early and late maturing lines, respectively. De novo assembly of all sequence reads generated 401,587 transcripts with a mean length of 546 bp and N50 length of 691 bp. Out of 13,133 DEGs detected, 22, 17, and eight flowering related DEGs were identified for the three stages, respectively. Twelve DEGs, including nine flowering related DEGs at the stem elongation stage were further confirmed by qRT-PCR. The analysis of homologous genes of the photoperiod pathway revealed their lower expression in the late maturing line at the stem elongation stage, suggesting that their differential expression contributed to late maturity in crested wheatgrass.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".