Cross-validated methods for promoter/transcription start site mapping in SL trans-spliced genes, established using the Ciona intestinalis troponin I gene
Bibliographic record
Abstract
In conventionally-expressed eukaryotic genes, transcription start sites (TSSs) can be identified by mapping the mature mRNA 5'-terminal sequence onto the genome. However, this approach is not applicable to genes that undergo pre-mRNA 5'-leader trans-splicing (SL trans-splicing) because the original 5'-segment of the primary transcript is replaced by the spliced leader sequence during the trans-splicing reaction and is discarded. Thus TSS mapping for trans-spliced genes requires different approaches. We describe two such approaches and show that they generate precisely agreeing results for an SL trans-spliced gene encoding the muscle protein troponin I in the ascidian tunicate chordate Ciona intestinalis. One method is based on experimental deletion of trans-splice acceptor sites and the other is based on high-throughput mRNA 5'-RACE sequence analysis of natural RNA populations in order to detect minor transcripts containing the pre-mRNA's original 5'-end. Both methods identified a single major troponin I TSS located ∼460 nt upstream of the trans-splice acceptor site. Further experimental analysis identified a functionally important TATA element 31 nt upstream of the start site. The two methods employed have complementary strengths and are broadly applicable to mapping promoters/TSSs for trans-spliced genes in tunicates and in trans-splicing organisms from other phyla.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".