Identification of Novel miRNAs and miRNA Dependent Developmental Shifts of Gene Expression in Arabidopsis thaliana
Bibliographic record
Abstract
microRNAs (miRNAs) are small, endogenous RNAs of 20 approximately 25 nucleotides, processed from stem-loop regions of longer RNA precursors. Plant miRNAs act as negative regulators of target mRNAs predominately by slicing target transcripts, and a number of miRNAs play important roles in development. We analyzed a number of published datasets from Arabidopsis thaliana to characterize novel miRNAs, novel miRNA targets, and miRNA-regulated developmental changes in gene expression. These data include microarray profiling data and small RNA (sRNA) deep sequencing data derived from miRNA biogenesis/transport mutants, microarray profiling data of mRNAs in a developmental series, and computational predictions of conserved genomic stem-loop structures. Our conservative analyses identified five novel mature miRNAs and seven miRNA targets, including one novel target gene. Two complementary miRNAs that target distinct mRNAs were encoded by one gene. We found that genes targeted by known miRNAs, and genes up-regulated or down-regulated in miRNA mutant inflorescences, are highly expressed in the wild type inflorescence. In addition, transcripts upregulated within the mutant inflorescences were abundant in wild type leaves and shoot meristems and low in pollen and seed. Downregulated transcripts were abundant in wild type pollen and seed and low in shoot meristems, roots and leaves. Thus, disrupting miRNA function causes the inflorescence transcriptome to resemble the leaf and meristem and to differ from pollen and seed. Applications of our computational approach to other species and the use of more liberal criteria than reported here will further expand the number of identified miRNAs and miRNA targets. Our findings suggest that miRNAs have a global role in promoting vegetative to reproductive transitions in A. thaliana.
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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 | 0.001 |
| 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".