Nanopore sequencing of <i>Giardia</i> reveals widespread intra-isolate structural variation
Bibliographic record
Abstract
Abstract Background Genomes of the parasite Giardia duodenalis are relatively small for eukaryotic genomes, yet there are only six publicly available. Difficulties in assembling the tetraploid G. duodenalis genome from short read sequencing data likely contribute to this lack of genomic information. We sequenced three isolates of G. duodenalis (AWB, BGS, and beaver) on the Oxford Nanopore Technologies MinION whose long reads have the potential to address genomic areas that are problematic for short reads. Results Using a hybrid approach that combines MinION long reads and Illumina short reads to take advantage of the continuity of the long reads and the accuracy of the short reads we generated reference quality genomes for each isolate. The genomes for two of the isolates were evaluated against the available reference genomes for comparison. The third genome for which there is no previous data was then assembled. The long reads were used to find structural variants in each isolate to examine heterozygosity. Consistent with previous findings based on SNPs, Giardia BGS was found to be considerably more heterozygous than the other isolates that are from Assemblage A. We also find an enrichment of variant-specific surface proteins in some of the structural variant regions. Conclusions Our results show that the MinION can be used to generate reference quality genomes in Giardia and further be used to identify structural variant regions that are an important source of genetic variation not previously examined in these parasites.
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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 | 0.000 |
| 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) | 0.001 | 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".