De novo genome assembly of two tomato ancestors, Solanum pimpinellifolium and Solanum lycopersicum var. cerasiforme, by long-read sequencing
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 110Â and 104Â 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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".