Reappraising plastid markers of the red algae for phylogenetic community ecology in the genomic era
Bibliographic record
Abstract
Abstract Selection of appropriate genetic markers to quantify phylogenetic diversity is crucial for community ecology studies. Yet, systematic evaluation of marker genes for this purpose is scarcely done. Recently, the combined effort of phycologists has produced a rich plastid genome resource with taxonomic representation spanning all of the major lineages of the red algae (Rhodophyta). In this proof‐of‐concept study, we leveraged this resource by developing and applying a phylogenomic strategy to seek candidate plastid markers suitable for phylogenetic community analysis. We ranked the core genes of 107 published plastid genomes based on various sequence‐derived properties and their tree distance to plastid genome phylogenies. The resulting ranking revealed that the most widely used marker, rbcL, is not necessarily the optimal marker, while other promising markers might have been overlooked. We designed and tested PCR primers for several candidate marker genes, and successfully amplified one of them, rpoC1, in a taxonomically broad set of red algal specimens. We suggest that our general marker identification methodology and the rpoC1 primers will be useful to the phycological community for investigating the biodiversity and community ecology of the red algae.
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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".