Landscape of fluid sets of hairpin-derived 21-/24-nt-long small RNAs at seed set uncovers special epigenetic features in <i>Picea glauca</i>
Bibliographic record
Abstract
Conifers' exceptionally large genome (20-30 Gb) is scattered with 60% retrotransposon (RT) components and we have little knowledge on their origin and evolutionary implications. RTs may impede the expression of flanking genes and provide sources of the formation of novel small RNA (sRNAs) populations to constrain events of transposon (TE) proliferation/transposition. Here we show a declining expression of 24-nt-long sRNAs and low expression levels of their key processing gene, pgRTL2 (RNASE THREE LIKE 2) at seed set in Picea glauca. The sRNAs in 24-nt size class are significantly less enriched in type and read number than 21-nt sRNAs and have not been documented in other species. The architecture of MIR loci generating highly expressed 24-/21-nt sRNAs is featured by long terminal repeat-retrotransposons (LTR-RTs) in families of Ty3/Gypsy and Ty1/Copia elements. This implies that the production of sRNAs may be predominantly originated from TE fragments on chromosomes. Furthermore, a large proportion of highly expressed 24-nt sRNAs does not have predictable targets against unique genes in Picea, suggestive of their potential pathway in DNA methylation modifications on, for instance, TEs. Additionally, the classification of computationally predicted sRNAs suggests that 24-nt sRNA targets may bear particular functions in metabolic processes while 21-nt sRNAs target genes involved in many different biological processes. This study, therefore, directs our attention to a possible extrapolation that lacking of 24-nt sRNAs at the late conifer seed developmental phase may result in less constraints in TE activities, thus contributing to the massive expansion of genome size.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".