<i>De novo</i> genome assembly of two tomato ancestors, <i>Solanum pimpinellifolium</i> and <i>Solanum</i> <i> lycopersicum</i> var. <i>cerasiforme</i>, by long-read sequencing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The ancestral tomato species are known to possess genes that are valuable for improving traits in breeding. Here, we aimed to construct high-quality de novo genome assemblies of Solanum pimpinellifolium 'LA1670' and S. lycopersicum var. cerasiforme 'LA1673', originating from Peru. The Pacific Biosciences (PacBio) long-read sequences with 110× and 104× coverages were assembled and polished to generate 244 and 202 contigs spanning 808.8 Mbp for 'LA1670' and 804.5 Mbp for 'LA1673', respectively. After chromosome-level scaffolding with reference guiding, 14 scaffold sequences corresponding to 12 tomato chromosomes and 2 unassigned sequences were constructed. High-quality genome assemblies were confirmed using the Benchmarking Universal Single-Copy Orthologs and long terminal repeat assembly index. The protein-coding sequences were then predicted, and their transcriptomes were confirmed. The de novo assembled genomes of S. pimpinellifolium and S. lycopersicum var. cerasiforme were predicted to have 71,945 and 75,230 protein-coding genes, including 29,629 and 29,185 non-redundant genes, respectively, as supported by the transcriptome analysis results. The chromosome-level genome assemblies coupled with transcriptome data sets of the two accessions would be valuable for gaining insights into tomato domestication and understanding genome-scale breeding.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it