Comparative Analysis of Sequences Preceding Protein-Coding Mitochondrial Genes in Flowering Plants
Bibliographic record
Abstract
We examined the nucleotide sequences preceding 23 mitochondrial protein-coding genes held in common by maize, rice, wheat, sugar beet, tobacco, Arabidopsis, and Brassica to look for features related to translation initiation and to assess the degree of conservation in mitochondrial mRNA leaders among these plants. We observed broad variation in sequence similarity as illustrated by dot plot analysis, ranging from a level rivaling that of coding sequences to complete absence of homology due to lineage-specific DNA rearrangements. Genes encoding ATP synthase subunits predominated in the latter category, whereas ones encoding cytochrome c biogenesis proteins and NADH dehydrogenase subunits were primarily of the highly conserved type. Within the region immediately preceding initiation codons, in most cases we did not observe motifs consistent with a bacterial-type Shine-Dalgarno interaction to assist in ribosome binding, nor was any other consensus sequence evident. In fact, indels in the form of tandem repeats were seen among homologues from different plants. We did, however, observe a bias for high adenosine and low cytosine in the proximal approximately 30 nt compared with further upstream. Duplicates of some sequences in our data set were found to be associated with more than one gene within a genome. Indeed, 3 such families of upstream cassettes were identified, and they exhibit a lineage-specific distribution among plants. Moreover, the presence of related sequences at genomic sites distant from known genes raises the possibility of future recruitment as regulatory elements. Our observations point to a dynamic nature in the makeup of the 5' leaders of plant mitochondrial mRNAs and an apparent plasticity in translational control elements.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".