Characterization of Pre‐mRNA Splicing and Spliceosomal Machinery in <i>Porphyridium</i><i>purpureum</i> and Evolutionary Implications for Red Algae
Bibliographic record
Abstract
Pre-mRNA splicing is a highly conserved eukaryotic process, but our understanding of it is limited by a historical focus on well-studied organisms such as humans and yeast. There is considerable diversity in mechanisms and components of pre-mRNA splicing, especially in lineages that have evolved under the pressures of genome reduction. The ancestor of red algae is thought to have undergone genome reduction prior to the lineage's radiation, resulting in overall gene and intron loss in extant groups. Previous studies on the extremophilic red alga Cyanidioschyzon merolae revealed an intron-sparse genome with a highly reduced spliceosome. To determine whether these features applied to other red algae, we investigated multiple aspects of pre-mRNA splicing in the mesophilic red alga Porphyridium purpureum. Through strand-specific RNA-Seq, we observed high levels of intron retention across a large number of its introns, and nearly half of the transcripts for these genes are not spliced at all. We also discovered a relationship between variability of 5' splice site sequences and levels of splicing. To further investigate the connections between intron retention and splicing machinery, we bioinformatically assembled the P. purpureum spliceosome, and biochemically verified the presence of snRNAs. While most other core spliceosomal components are present, our results suggest highly divergent or missing U1 snRNP proteins, despite the presence of an uncharacteristically long U1 snRNA. These unusual aspects highlight the diverse nature of pre-mRNA splicing that can be seen in lesser-studied eukaryotes, raising the importance of investigating fundamental eukaryotic processes outside of model organisms.
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.
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".