RNA‐Seq‐based gene expression analysis of seed protein and sulfur amino acid accumulation in developing pea seeds
Bibliographic record
Abstract
Abstract This research aims at identifying candidate genes associated with the accumulation of seed protein and sulfur amino acids (SAAs) by comparing the expression profile of genes in developing seeds of pea ( Pisum sativum L.) lines. Lines were selected from PR‐25, a recombinant inbred line population, derived from a cross between CDC Amarillo and CDC Limerick. The selected lines were high seed protein concentration (SPC) line PR‐25‐69, high SAA line PR‐25‐53, and low SPC and low SAA line PR‐25‐6. These lines were grown in a phytotron chamber, and developing seeds collected from three biological replicates of each line at 7, 14, 21, and 28 days after anthesis were used for RNA sequencing. By comparison of the gene expression profiles between SPC contrasting lines (PR‐25‐69 vs. PR‐25‐6) and SAAs contrasting lines (PR‐25‐53 vs. PR‐25‐6), 4920 differentially expressed genes (DEGs) were identified over the four time points. Of these, 2798 DEGs were downregulated and 2122 DEGs were upregulated compared to control (PR‐25‐6). The expression levels of the identified DEGs varied from log 2 twofold to log 2 10‐fold. Extensive transmembrane activities, including transportation of amino acids and proteins, were seen in the results of GO analyses. Downregulated DEGs represented 78 significant GO terms, while upregulated DEGs represented 52 significant GO terms. Some distinct biological processes were exclusively present in upregulated DEGs, for instance, reproduction and nutrient reservoir activities. Future studies will involve genetic variant analyses and the development of genetic markers based on the candidate genes.
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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".