Characterization of <i>Heterobasidion occidentale</i> transcriptomes reveals candidate genes and <scp>DNA</scp> polymorphisms for virulence variations
Why this work is in the frame
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Bibliographic record
Abstract
Characterization of genes involved in differentiation of pathogen species and isolates with variations of virulence traits provides valuable information to control tree diseases for meeting the challenges of sustainable forest health and phytosanitary trade issues. Lack of genetic knowledge and genomic resources hinders novel gene discovery, molecular mechanism studies and development of diagnostic tools in the management of forest pathogens. Here, we report on transcriptome profiling of Heterobasidion occidentale isolates with contrasting virulence levels. Comparative transcriptomic analysis identified orthologous groups exclusive to H. occidentale and its isolates, revealing biological processes involved in the differentiation of isolates. Further bioinformatics analyses identified an H. occidentale secretome, CYPome and other candidate effectors, from which genes with species- and isolate-specific expression were characterized. A large proportion of differentially expressed genes were revealed to have putative activities as cell wall modification enzymes and transcription factors, suggesting their potential roles in virulence and fungal pathogenesis. Next, large numbers of simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs) were detected, including more than 14 000 interisolate non-synonymous SNPs. These polymorphic loci and species/isolate-specific genes may contribute to virulence variations and provide ideal DNA markers for development of diagnostic tools and investigation of genetic diversity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it