<i>Alternaria</i> sections <i>Infectoriae and Pseudoalternaria</i> : New genomic resources, phylogenomic analyses, and biodiversity
Bibliographic record
Abstract
Species in Alternaria sections Infectoriae and Pseudoalternaria are commonly isolated from agricultural crops and a variety of other plant hosts. With the increasing appreciation that species from these two sections are often the dominant taxa recovered from important cereal crops, the need for improved understanding of their biodiversity and taxonomy has grown. Given that morphological characteristics and existing molecular markers are not sufficient for distinguishing among species, we expanded the genomic resources for these sections to support research in biosystematics and species diagnostics. Whole genome assemblies for 22 strains were generated, including the first genomes from section Infectoriae or Pseudoalternaria strains sampled from Canada, which significantly increases the number of publicly released genomes, particularly for section Pseudoalternaria. We performed comprehensive phylogenomic analyses of all available genomes (n = 39) and present the first robust phylogeny for these taxa. The segregation of the two sections was strongly supported by genomewide data, and multiple lineages were detected within each section. We then provide an overview of the biosystematics of these groups by analyzing two standard molecular markers from the largest sample of section Infectoriae and Pseudoalternaria strains studied to date. The patterns of relative diversity suggest that, in many cases, multiple species described based on minor morphological differences may actually represent different strains of the same species. A list of candidate loci for development into new informative molecular markers, which are diagnostic for sections and lineages, was created from analyses of phylogenetic signals from individual genes across the entire genome.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".