Pentatricopeptide Repeat Proteins Constrain Genome Evolution in Chloroplasts
Bibliographic record
Abstract
Higher plants encode hundreds of pentatricopeptide repeat proteins (PPRs) that are involved in several types of RNA processing reactions. Most PPR genes are predicted to be targeted to chloroplasts or mitochondria, and many are known to affect organellar gene expression. In some cases, RNA binding has been directly demonstrated, and the sequences of the cis-elements are known. In this work, we demonstrate that RNA cis-elements recognized by PPRs are constrained in chloroplast genome evolution. Cis-elements for two PPR genes and several RNA editing sites were analyzed for sequence changes by pairwise nucleotide substitution frequency, pairwise indel frequency, and maximum likelihood (ML) phylogenetic distances. All three of these analyses demonstrated that sequences within the cis-element are highly conserved compared with surrounding sequences. In addition, we have compared sequences around chloroplast editing sites and homologous sequences in species that lack an editing site due to the presence of a genomic T. Cis-elements for RNA editing sites are highly conserved in angiosperms; by contrast, comparable sequences around a genomically encoded T exhibit higher rates of nucleotide substitution, higher frequencies of indels, and greater ML distances. The loss in requirement for editing to create the ndhD start codon has resulted in the conversion of the PPR gene responsible for editing that site to a pseudogene. We show that organellar dependence on nuclear-encoded PPR proteins for gene expression has constrained the evolution of cis-elements that are required at the level of RNA processing. Thus, the expansion of the PPR gene family in plants has had a dramatic effect on the evolution of plant organelle genomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".