A chromosome-level genome assembly of a model conifer plant, the Japanese cedar, <i>Cryptomeria japonica</i> D. Don
Bibliographic record
Abstract
Abstract Japanese cedar ( Cryptomeria japonica D. Don) is the most important Japanese forest tree, occupying about 44% of artificial forests in Japan, and planted in East Asia, Azores Archipelago, and some islands in the Indian Ocean. Although the huge genome of the species (ca. 11 Gb) with abundant repeat elements might have been an obstacle for genetic analysis, the species is easily propagated by cutting, flowered by plant hormones like gibberellic acid, transformed by agrobacterium, and edited by CRISPR/Cas9. These characteristics of C. japonica are preferable to make the species a model conifer for which reference genome sequences are necessary. In this study, we report the first chromosome-level assembly for C. japonica (2n = 22) using a third generation selfed progeny with an estimated homozygosity of 0.96. Young leaf tissue was used to extract high-molecular-weight DNA (>50 kb) for HiFi PacBio long read sequencing and to construct Hi-C/Omni-C library for Illumina short read sequencing. Using the 29× and 26× genome coverage of HiFi and Illumina reads, respectively, de novo assembly resulted in 2,650 contigs (9.1 Gb in total) with N50 contig size of 12.0 Mb. The Hi-C analysis mapped 97% of the nucleotides on the 11 chromosomes. The assembly was verified by comparing with a consensus linkage map of 7,785 markers. The BUSCO analysis confirmed ~91% of conserved genes. Annotations of genes, repeat elements and synteny with other Cupressaceae and Pinaceae species were performed, providing fundamental resources for genomic research of conifers.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".