Domestication of Transposable Elements into MicroRNA Genes in Plants
Bibliographic record
Abstract
Transposable elements (TE) usually take up a substantial portion of eukaryotic genome. Activities of TEs can cause genome instability or gene mutations that are harmful or even disastrous to the host. TEs also contribute to gene and genome evolution at many aspects. Part of miRNA genes in mammals have been found to derive from transposons while convincing evidences are absent for plants. We found that a considerable number of previously annotated plant miRNAs are identical or homologous to transposons (TE-MIR), which include a small number of bona fide miRNA genes that conform to generally accepted plant miRNA annotation rules, and hairpin derived siRNAs likely to be pre-evolved miRNAs. Analysis of these TE-MIRs indicate that transitions from the medium to high copy TEs into miRNA genes may undergo steps such as inverted repeat formation, sequence speciation and adaptation to miRNA biogenesis. We also identified initial target genes of the TE-MIRs, which contain homologous sequences in their CDS as consequence of cognate TE insertions. About one-third of the initial target mRNAs are supported by publicly available degradome sequencing data for TE-MIR sRNA induced cleavages. Targets of the TE-MIRs are biased to non-TE related genes indicating their penchant to acquire cellular functions during evolution. Interestingly, most of these TE insertions span boundaries between coding and non-coding sequences indicating their incorporation into CDS through alteration of splicing or translation start or stop signals. Taken together, our findings suggest that TEs in gene rich regions can form foldbacks in non-coding part of transcripts that may eventually evolve into miRNA genes or be integrated into protein coding sequences to form potential targets in a "temperate" manner. Thus, transposons may supply as resources for the evolution of miRNA-target interactions in plants.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".