The Complete Genome Sequence of the Phytopathogenic Fungus Sclerotinia sclerotiorum Reveals Insights into the Genome Architecture of Broad Host Range Pathogens
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sclerotinia sclerotiorum is a phytopathogenic fungus with over 400 hosts including numerous economically important cultivated species. This contrasts many economically destructive pathogens that only exhibit a single or very few hosts. Many plant pathogens exhibit a “two-speed” genome. So described because their genomes contain alternating gene rich, repeat sparse and gene poor, repeat-rich regions. In fungi, the repeat-rich regions may be subjected to a process termed repeat-induced point mutation (RIP). Both repeat activity and RIP are thought to play a significant role in evolution of secreted virulence proteins, termed effectors. We present a complete genome sequence of S. sclerotiorum generated using Single Molecule Real-Time Sequencing technology with highly accurate annotations produced using an extensive RNA sequencing data set. We identified 70 effector candidates and have highlighted their in planta expression profiles. Furthermore, we characterized the genome architecture of S. sclerotiorum in comparison to plant pathogens that exhibit “two-speed” genomes. We show that there is a significant association between positions of secreted proteins and regions with a high RIP index in S. sclerotiorum but we did not detect a correlation between secreted protein proportion and GC content. Neither did we detect a negative correlation between CDS content and secreted protein proportion across the S. sclerotiorum genome. We conclude that S. sclerotiorum exhibits subtle signatures of enhanced mutation of secreted proteins in specific genomic compartments as a result of transposition and RIP activity. However, these signatures are not observable at the whole-genome scale.
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.
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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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