From fragmentation to resolution: high-fidelity genome assembly of <i>zancudomyces culisetae</i> through comparative insights from PacBio, Nanopore, and Illumina sequencing
Bibliographic record
Abstract
Zancudomyces culisetae is an obligate symbiotic fungus inhabiting the digestive tracts of aquatic insect larvae, including black flies, midges, and mosquitoes. With a global distribution and high prevalence in disease-transmitting insects, Z. culisetae serves as a model for studying insect gut fungi. A previous draft genome assembly using Illumina short reads provided insights into its genome composition, such as a low GC ratio and evidence of horizontal gene transfer. However, its fragmented nature has limited deeper exploration of the evolutionary mechanisms shaping these gut symbionts. To address this gap, we generated a wealth of genomic resources for Z. culisetae using multiple sequencing platforms, including Illumina, Oxford Nanopore, PacBio-CLR (Complete Long Reads), and PacBio-HiFi (High Fidelity). This also provides an opportunity to compare these popular sequencing methods to suggest the optimal approach for fungal genome assembly. Our results suggest that PacBio-HiFi produced the most complete assembly, yielding a 27.8 Mb genome size with 26 contigs, representing the highest-quality genome of insect gut fungi to date. Additionally, we generated transcriptomic data to support genome annotation, identifying 8,484 protein-coding genes. Despite the improved genome quality, Z. culisetae lacks ∼20% of Benchmarking Universal Single-Copy Orthologue commonly found in fungi, reflecting adaptations to its obligate symbiotic lifestyle. This study not only provides valuable genomic resources for insect gut fungal research but also evaluates the strengths and limitations of current genome sequencing and assembly approaches, offering best practices for fungal genome analysis and genetic research.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".