A chromosome-level genome assembly of a model conifer plant, the Japanese cedar, Cryptomeria japonica D. Don
Bibliographic record
Abstract
BACKGROUND: The Japanese cedar (Cryptomeria japonica D. Don) is one of the most important Japanese forest trees, occupying approximately 44% of artificial forests and planted in East Asia, the Azores Archipelago, and certain islands in the Indian Ocean. Although the huge genome of the species (ca. 9 Gbp) with abundant repeat elements may have represented an obstacle for genetic analysis, this species is easily propagated by cutting, flowered by gibberellic acid, transformed by Agrobacterium, and edited by CRISPR/Cas9. These characteristics of C. japonica recommend it as a model conifer species for which reference genome sequences are necessary. RESULTS: Herein, we report the first chromosome-level assembly of C. japonica (2n = 22) using third-generation selfed progeny (estimated homozygosity rate = 0.96). Young leaf tissue was used to extract high molecular weight DNA (> 50 kb) for HiFi PacBio long-read sequencing and to construct an Hi-C/Omni-C library for Illumina short-read sequencing. The 29× and 26× genome coverage of HiFi and Illumina reads, respectively, for de novo assembly yielded 2,651 contigs (9.1 Gbp, N50 contig size 12.0 Mbp). Hi-C analysis mapped 97% of the nucleotides on 11 chromosomes. The assembly was verified through comparison with a consensus linkage map comprising 7,781 markers. BUSCO analysis identified ∼ 91% conserved genes. CONCLUSIONS: Annotations of genes and comparisons of repeat elements with other Cupressaceae and Pinaceae species provide a fundamental resource for conifer 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".