Comprehensive genomic and phenotypic analyses reveal the genetic basis of fruit quality in litchi
Bibliographic record
Abstract
BACKGROUND: Litchi, an economically important fruit crop in Southeast Asia, is renowned for its distinctive flavor and nutrient value, but its genetic diversity and genetic basis underlying fruit quality regulation remain largely unexplored. RESULTS: We re-sequence 276 litchi accessions collected globally and identify 54 million high-quality biallelic SNPs. We then analyze the population structure and reveal four main subgroups within the population. By phenotypic profiling of 21 fruit-quality-related traits, followed with genome-wide association study, we identify a plethora of candidate genes and genomic loci that are responsible for regulating seed and fruit quality traits. In particular, we characterize and experimentally validate an invertase gene, LcSAI, encoding an enzyme catalyzing the conversion of sucrose into reducing sugars, as a key regulator of sugar composition in litchi fruit, affecting the sweetness of litchi fruits. CONCLUSIONS: Our study demonstrates the genetic diversity and population structure of litchi. We delineate the genetic basis of fruit quality through comprehensive genomic analyses and phenotypic profiling. These findings provide valuable resources and knowledge for understanding the genetic basis of fruit quality in litchi, which contribute to the theoretical basis for further genetic improvement.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".