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Record W6886007505 · doi:10.13925/j.cnki.gsxb.20240644

Genetic diversity and GWAS analysis of flesh hardness trait in Xinjiang melon germplasm resources

2025· article· en· W6886007505 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvances in Cucurbitaceae Research
Canadian institutionsnot available
Fundersnot available
KeywordsGermplasmFleshGenetic diversityMelonPopulationTraitHybridGenetic variation

Abstract

fetched live from OpenAlex

[Objective] Melon, as an important global fruit and vegetable crop, is highly influenced by fruit flesh hardness and other quality traits, which directly affect its market competitiveness. Melon is widely cultivated worldwide and holds significant economic value, especially in Xinjiang, China, which serves as a major production hub. Xinjiang is the home to a diverse array of melon varieties, with key cultivation areas including Hami, Turpan, Korla and Changji. In recent years, the melon planting area has continued to expand, with Xinjiang accounting for one-third of the national production. However, the Xinjiang melon industry faces challenges such as severe homogenization, a reliance on a limited number of parental lines for breeding, and low breeding efficiency. Conducting genetic diversity analyses of melon germplasm and identifying key trait-associated genes and loci can provide critical information for developing genetic improvement strategies. This, in turn, can promote varietal diversity and enhance the industry's market competitiveness. Flesh hardness is a key quality characteristic, however, and little research has been reported on the genetic basis of fruit flesh hardness in melon. This study aims to analyze the genetic diversity and population structure of melon germplasm and to locate genes associated to flesh hardness. [Methods] High-throughput sequencing technology was used to analyze the genomes of 292 melon accessions from around the world, constructing a large-scale genetic variation map. The Neighbor-Joining Method was applied to calculate the genetic distance matrix, and a phylogenetic tree was built. Genome-wide association analysis (GWAS) and haplotype analysis were performed in conjunction with the flesh hardness trait. [Results] The melon germplasm population was divided into two distinct branches: BranchⅠ (Pop1) and BranchⅡ (Pop2). Pop1 predominantly clustered local varieties from Xinjiang of China, Japan and the former Soviet Union, with Xinjiang varieties making up the majority (90.84%). Pop2 was mainly composed of cultivated varieties, widely distributed across various regions, including multiple provinces of China (Xinjiang, Shaanxi, Taiwan, Gansu, Inner Mongolia and Liaoning), Japan, the former Soviet Union, the United States, Canada, Iran, Turkey, Hungary, South Africa and India, with Xinjiang varieties constituting 67.5%. Genome-wide linkage disequilibrium (LD) analysis confirmed significant differences in genetic diversity and population structure between the two groups. LD analysis revealed that the LD decay distance for the entire melon germplasm population was 49.2 kb when r2 decreased to half (r2=0.33). However, when analyzed separately, the LD decay distances for landraces and cultivated varieties were 57 kb and 45.9 kb, respectively, indicating that cultivated varieties exhibited a faster LD decay rate than landraces. This suggests that cultivated varieties have undergone stronger selective pressures and genetic drift. Furthermore, nucleotide diversity analysis showed that the nucleotide diversity of cultivated varieties (2.537 × 10-3) was significantly (p<0.01) higher than that of landraces (1.989 × 10-3), further supporting the idea of rapid evolution in genetic diversity among cultivated varieties. Through GWAS, we explored the variation of flesh traits, especially the important agronomic trait of flesh hardness. Based on phenotypic and genotypic data, we identified a significant association signal on chromosome 8 of the melon genome (Chr08: 2815957_2831112; P=2.36e-07). This region contained 11 significant associated SNPs, which explained 9.04% of the phenotypic variation. Functional annotation revealed that this region harbored candidate genes related to cell wall biosynthesis and remodeling, like inositol monophosphatase (MELO3C007440.2) and nucleotide-sugar transporter (MELO3C007449.2). These genes may influence flesh hardness by regulating the synthesis and remodeling of pectin and cell wall polysaccharides. Five SNPs were found in the coding region of MELO3C007451.2, which were in strong linkage disequilibrium, allowing the population to be divided into four haplotypes. The 98.05% of local varieties carried the hap001 haplotype. Hap004 haplotype materials exhibited soft and brittle characteristics, while hard materials carried hap001, hap002 and hap003 haplotypes. [Conclusion] The high geographical and cultivation environment differentiation of melon germplasm reflects significant genetic differences between local and cultivated varieties, especially the diversified geographical origins of Xinjiang melons. The study identified candidate genes associated with melon flesh hardness, including MELO3C007434, MELO3C007435, MELO3C007436, MELO3C007437, MELO3C007438, MELO3C007439, MELO3C007440 and MELO3C007441, which were confirmed as selection genes related to the differentiation between wild and cultivated species. We speculate that these genes may play a key role in the domestication process of flesh hardness from wild to cultivated species. In addition, candidate genes like inositol monophosphatase (MELO3C007440.2) and nucleotide-sugar transporter (MELO3C007449.2), involved in pectin and cell wall polysaccharide synthesis, may be important regulatory factors influencing flesh hardness. Furthermore, we discovered several haplotypes associated with flesh hardness in the population, and the differences in these haplotypes were closely related to phenotypic variation in flesh texture. Notably, haplotype differentiation showed a clear association between hard and soft flesh samples, highlighting the connection between genotype and phenotype. This study provides new molecular markers for the genetic improvement of melon flesh hardness and other quality traits, laying the foundation for marker-assisted selection in melon breeding.

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How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.872

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.004
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.144
GPT teacher head0.538
Teacher spread0.394 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
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