Genome-wide computational prediction and experimental validation of quinoa (<i>Chenopodium quinoa</i>) microRNAs
Why this work is in the frame
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Bibliographic record
Abstract
MicroRNAs (miRNAs) are highly conserved, endogenous, short (21–24 nucleotides), non-coding RNA molecules that play significant roles in post-transcriptional gene silencing by directing target mRNA cleavage or translational inhibition. Nonetheless, highly nutritious “super grain” quinoa (Chenopodium quinoa) is an extreme abiotic stress tolerant Andean seed crop of many potential uses, with outstanding protein quality and a load of vitamins, minerals, as well as flavonoid antioxidants. In this study, applying genome-wide in silico approaches (referring to the recently published quinoa genome) and following a set of stringent filtering measures, a total of 22 potentially conserved microRNAs belonging to 18 families were characterized from quinoa and 11 randomly selected putative microRNAs (cqu-miR160a, cqu-miR162a, cqu-miR164a, cqu-miR166b, cqu-miR167a, cqu-miR172a, cqu-miR319a, cqu-miR390a, cqu-miR393a, cqu-miR394a, and cqu-miR398b) were validated successfully by RT-PCR. Using the psRNATarget tool, a sum of 59 potential miRNA targets, mostly transcription factors, were identified that are involved in biosynthesis, metabolic processes, and signal transduction. Among the detected targets, six target transcripts (F-Box proteins, TCP, MYB, WD protein, NAC, and CSD) were reported to have specific roles in both flavonoids biosynthesis and stress response signaling in some plants. To the best of our knowledge, this is the first report of quinoa microRNAs and their targets.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it