Decoding the oak genome: public release of sequence data, assembly, annotation and publication strategies
Bibliographic record
Abstract
The 1.5 Gbp/2C genome of pedunculate oak (Quercus robur) has been sequenced. A strategy was established for dealing with the challenges imposed by the sequencing of such a large, complex and highly heterozygous genome by a whole-genome shotgun (WGS) approach, without the use of costly and time-consuming methods, such as fosmid or BAC clone-based hierarchical sequencing methods. The sequencing strategy combined short and long reads. Over 49 million reads provided by Roche 454 GS-FLX technology were assembled into contigs and combined with shorter Illumina sequence reads from paired-end and mate-pair libraries of different insert sizes, to build scaffolds. Errors were corrected and gaps filled with Illumina paired-end reads and contaminants detected, resulting in a total of 17,910 scaffolds (>2 kb) corresponding to 1.34 Gb. Fifty per cent of the assembly was accounted for by 1468 scaffolds (N50 of 260 kb). Initial comparison with the phylogenetically related Prunus persica gene model indicated that genes for 84.6% of the proteins present in peach (mean protein coverage of 90.5%) were present in our assembly. The second and third steps in this project are genome annotation and the assignment of scaffolds to the oak genetic linkage map. In accordance with the Bermuda and Fort Lauderdale agreements and the more recent Toronto Statement, the oak genome data have been released into public sequence repositories in advance of publication. In this presubmission paper, the oak genome consortium describes its principal lines of work and future directions for analyses of the nature, function and evolution of the oak genome.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.049 |
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".