A High-Quality Phased Genome Assembly of Stinging Nettle (Urtica dioica ssp. dioica)
Bibliographic record
Abstract
Stinging nettles (Urtica dioica) have a long history of association with human civilization, having been used as a source of textile fibers, food and medicine. Here, we present a chromosome-level, phased genome assembly for a diploid female clone of Urtica dioica from Romania. Using a combination of PacBio HiFi, Oxford Nanopore, and Illumina sequencing, as well as Hi-C long-range interaction data (using a novel Hi-C protocol presented here), we assembled two haplotypes of 574.9 Mbp (contig N50 = 10.9 Mbp, scaffold N50 = 44.0 Mbp) and 521.2 Mbp (contig N50 = 13.5 Mbp, scaffold N50 = 48.0 Mbp), with assembly BUSCO scores of 92.6% and 92.2%. We annotated 20,333 and 20,140 genes for each haplotype, covering over 90% of the complete BUSCO genes and including two copies of a gene putatively encoding the neurotoxic peptide urthionin, which could contribute to nettle’s characteristic sting. Despite its relatively small size, the nettle genome displays very high levels of repetitiveness, with transposable elements comprising more than 60% of the genome, as well as considerable structural variation. This genome assembly represents an important resource for the nettle community and will enable the investigation of the genetic basis of the many interesting characteristics of this species.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".