Systematically fragmented genes in a multipartite mitochondrial genome
Bibliographic record
Abstract
Arguably, the most bizarre mitochondrial DNA (mtDNA) is that of the euglenozoan eukaryote Diplonema papillatum. The genome consists of numerous small circular chromosomes none of which appears to encode a complete gene. For instance, the cox1 coding sequence is spread out over nine different chromosomes in non-overlapping pieces (modules), which are transcribed separately and joined to a contiguous mRNA by trans-splicing. Here, we examine how many genes are encoded by Diplonema mtDNA and whether all are fragmented and their transcripts trans-spliced. Module identification is challenging due to the sequence divergence of Diplonema mitochondrial genes. By employing most sensitive protein profile search algorithms and comparing genomic with cDNA sequence, we recognize a total of 11 typical mitochondrial genes. The 10 protein-coding genes are systematically chopped up into three to 12 modules of 60-350 bp length. The corresponding mRNAs are all trans-spliced. Identification of ribosomal RNAs is most difficult. So far, we only detect the 3'-module of the large subunit ribosomal RNA (rRNA); it does not trans-splice with other pieces. The small subunit rRNA gene remains elusive. Our results open new intriguing questions about the biochemistry and evolution of mitochondrial trans-splicing in Diplonema.
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 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 | 0.000 |
| 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 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".