Haplotype‐phased and chromosome‐level genome assembly of <i>Puccinia polysora</i>, a giga‐scale fungal pathogen causing southern corn rust
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Bibliographic record
Abstract
Rust fungi are characterized by large genomes with high repeat content and have two haploid nuclei in most life stages, which makes achieving high-quality genome assemblies challenging. Here, we described a pipeline using HiFi reads and Hi-C data to assemble a gigabase-sized fungal pathogen, Puccinia polysora f.sp. zeae, to haplotype-phased and chromosome-scale. The final assembled genome is 1.71 Gbp, with ~850 Mbp and 18 chromosomes in each haplotype, being currently one of the two giga-scale fungi assembled to chromosome level. Transcript-based annotation identified 47,512 genes for the dikaryotic genome with a similar number for each haplotype. A high level of interhaplotype variation was found with 10% haplotype-specific BUSCO genes, 5.8 SNPs/kbp, and structural variation accounting for 3% of the genome size. The P. polysora genome displayed over 85% repeat contents, with genome-size expansion and copy number increasing of species-specific orthogroups. Interestingly, these features did not affect overall synteny with other Puccinia species having smaller genomes. Fine-time-point transcriptomics revealed seven clusters of coexpressed secreted proteins that are conserved between two haplotypes. The fact that candidate effectors interspersed with all genes indicated the absence of a "two-speed genome" evolution in P. polysora. Genome resequencing of 79 additional isolates revealed a clonal population structure of P. polysora in China with low geographic differentiation. Nevertheless, a minor population differentiated from the major population by having mutations on secreted proteins including AvrRppC, indicating the ongoing virulence to evade recognition by RppC, a major resistance gene in Chinese corn cultivars. The high-quality assembly provides valuable genomic resources for future studies on disease management and the evolution of P. polysora.
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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 | 0.001 |
| 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