Phylogenomic analyses of <i>Alternaria</i> section <i>Alternaria</i> : A high-resolution, genome-wide study of lineage sorting and gene tree discordance
Bibliographic record
Abstract
The genus Alternaria contains a diversity of saprobic and pathogenic species that can be found in a wide range of environments. Alternaria is currently divided into 26 subgeneric sections, and the “small-spored” Alternaria section Alternaria includes many species that are economically important agricultural pathogens. Recognizing that a stable framework for systematics and species identification is essential for management and regulation purposes, this section has experienced much taxonomic debate and systematic revision in recent years. Molecular phylogenetic studies have challenged the reliability of using morphological characteristics to differentiate Alternaria species but have also suggested that commonly used molecular markers for fungal phylogenetics may not be sufficiently informative at this taxonomic level. To allow the assessment of molecular variation and evolutionary history at a genome-wide scale, we present an overview and analysis of phylogenomic resources for Alternaria section Alternaria. We review the currently available genomic resources and report five newly sequenced genomes. We then perform multiple comparative genomic analyses, including macrosynteny assessment and inference of phylogenetic relationships using a variety of data sets and analysis methods. Fine-scale, genome-wide phylogenetic reconstruction revealed incomplete lineage sorting and the genomic distribution of gene/species tree discordance. Based on these patterns, we propose a list of candidate genes that may be developed into informative markers that are diagnostic for the main lineages. This overview identifies gaps in knowledge and can guide future genome sequencing efforts for this important group of plant pathogenic fungi.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".