Widespread intron retention in mammals functionally tunes transcriptomes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Alternative splicing (AS) of precursor RNAs is responsible for greatly expanding the regulatory and functional capacity of eukaryotic genomes. Of the different classes of AS, intron retention (IR) is the least well understood. In plants and unicellular eukaryotes, IR is the most common form of AS, whereas in animals, it is thought to represent the least prevalent form. Using high-coverage poly(A)(+) RNA-seq data, we observe that IR is surprisingly frequent in mammals, affecting transcripts from as many as three-quarters of multiexonic genes. A highly correlated set of cis features comprising an "IR code" reliably discriminates retained from constitutively spliced introns. We show that IR acts widely to reduce the levels of transcripts that are less or not required for the physiology of the cell or tissue type in which they are detected. This "transcriptome tuning" function of IR acts through both nonsense-mediated mRNA decay and nuclear sequestration and turnover of IR transcripts. We further show that IR is linked to a cross-talk mechanism involving localized stalling of RNA polymerase II (Pol II) and reduced availability of spliceosomal components. Collectively, the results implicate a global checkpoint-type mechanism whereby reduced recruitment of splicing components coupled to Pol II pausing underlies widespread IR-mediated suppression of inappropriately expressed transcripts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 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