Construction and analysis of telomere-to-telomere genomes for 2 sweet oranges: Longhuihong and Newhall (<i>Citrus sinensis</i>)
Bibliographic record
Abstract
BACKGROUND: Sweet orange (Citrus sinensis Osbeck) is a fruit crop of high nutritional value that is widely consumed around the world. However, its susceptibility to low-temperature stress limits its cultivation and production in regions prone to frost damage, severely impacting the sustainable development of the sweet orange industry. Therefore, developing cold-resistant sweet orange varieties is of great necessity. Traditional hybrid breeding methods are not feasible due to the polyembryonic phenomenon in sweet oranges, necessitating the enhancement of its germplasm through molecular breeding. High-quality reference genomes are valuable for studying crop resistance to biotic and abiotic stresses. However, the lack of genomic resources for cold-resistant sweet orange varieties has hindered the progress in developing such varieties and researching their molecular mechanisms of cold resistance. FINDINGS: This study integrated PacBio HiFi, ONT, Hi-C, and Illumina sequencing data to assemble telomere-to-telomere (T2T) reference genomes for the cold-resistant sweet orange mutant "Longhuihong" (Citrus sinensis [L.] Osb. cv. LHH) and its wild-type counterpart "Newhall" (C. sinensis [L.] Osb. cv. Newhall). Comprehensive evaluations based on multiple criteria revealed that both genomes exhibit high continuity, completeness, and accuracy. The genome sizes were 340.28 Mb and 346.33 Mb, with contig N50 of 39.31 Mb and 36.77 Mb, respectively. In total, 31,456 and 30,021 gene models were annotated in the respective genomes. Leveraging these assembled genomes, comparative genomics analyses were performed, elucidating the evolutionary history of the sweet orange genome. Moreover, the study identified 2,886 structural variants between the 2 genomes, with several SVs located in the upstream, downstream, or intronic regions of homologous genes known to be associated with cold resistance. CONCLUSIONS: The study de novo assembled 2 T2T reference genomes of sweet orange varieties exhibiting different levels of cold tolerance. These genomes serve as valuable foundational resources for genomic research and molecular breeding aimed at enhancing cold tolerance in sweet oranges. Additionally, they expand the existing repository of reference genomes and sequencing data resources for C. sinensis. Moreover, these genomes provide a critical data foundation for comparative genomics analyses across different plant species.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".