GWAS reveals the genetic basis and genomic regions underlying four active compounds in chrysanthemum

Chrysanthemum is rich in active compounds such as flavonoids and phenolic acids, and its dried head flowers are commonly used for tea and medicinal purposes. However, the genetic determinism underlying chrysanthemum active compounds remains elusive. In this study, we evaluated a panel of 137 chrysanthemum accessions for total flavonoids, chlorogenic acid, luteolin, and isochlorogenic acid A across two consecutive years. The four active compounds exhibited considerable variation, with a coefficient of variation ranging from 44.96 % to 76.30 %. Significant differences were observed in genotype and environments, and the broad-sense heritability was estimated at 0.5–0.63 for all examined traits. Significant pair-wise correlation was found between the four active compounds. Several accessions showing the highest active compounds were figured out for breeding use by integrating the membership function and hierarchical cluster analysis methods. Based on the 327 042 high-quality SNPs, a genome-wide association study (GWAS) captured 59 significant SNPs for the four active compounds, of which 24 elite alleles exhibited pyramiding effects. A total of 18 potential candidate genes were mined, among which evm.model.scaffold_1149.273 ( QUA1 ) has one linkage disequilibrium (LD) block corresponding to Hap4 with the highest luteolin content. The findings are beneficial to understanding the genetic basis of the active compounds and provide parental materials and valuable markers for the genetic improvement of active compounds in chrysanthemums.

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Publication Details

Journal
Horticultural Plant Journal
Published
2025-02-26
DOI
https://doi.org/10.1016/j.hpj.2024.07.012
Citations
2
Primary Topic
Plant Gene Expression Analysis
Type
article
Field-Weighted Citation Impact
1.61
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article

GWAS reveals the genetic basis and genomic regions underlying four active compounds in chrysanthemum

Weimin Fang, Xinyi Ning, Zhaowen Lu, Jiangshuo Su et al.
2 citations
Horticultural Plant Journal
Plant Gene Expression Analysis
1.61
article

GWAS reveals the genetic basis and genomic regions underlying four active compounds in chrysanthemum

Weimin Fang, Xinyi Ning, Zhaowen Lu, Jiangshuo Su, Fadi Chen, Wei Sun, Xuefeng Zhang, Haibin Wang, Fei Zhang, Zhiyong Guan, Shiyun Wen, Yuhua He
article en
2 citations

Abstract

Chrysanthemum is rich in active compounds such as flavonoids and phenolic acids, and its dried head flowers are commonly used for tea and medicinal purposes. However, the genetic determinism underlying chrysanthemum active compounds remains elusive. In this study, we evaluated a panel of 137 chrysanthemum accessions for total flavonoids, chlorogenic acid, luteolin, and isochlorogenic acid A across two consecutive years. The four active compounds exhibited considerable variation, with a coefficient of variation ranging from 44.96 % to 76.30 %. Significant differences were observed in genotype and environments, and the broad-sense heritability was estimated at 0.5–0.63 for all examined traits. Significant pair-wise correlation was found between the four active compounds. Several accessions showing the highest active compounds were figured out for breeding use by integrating the membership function and hierarchical cluster analysis methods. Based on the 327 042 high-quality SNPs, a genome-wide association study (GWAS) captured 59 significant SNPs for the four active compounds, of which 24 elite alleles exhibited pyramiding effects. A total of 18 potential candidate genes were mined, among which evm.model.scaffold_1149.273 ( QUA1 ) has one linkage disequilibrium (LD) block corresponding to Hap4 with the highest luteolin content. The findings are beneficial to understanding the genetic basis of the active compounds and provide parental materials and valuable markers for the genetic improvement of active compounds in chrysanthemums.

Horticultural Plant JournalVol. 11(6)
Nanjing Agricultural University (CN)
Zero hunger
Openalex Percentile: Top 19%
Plant Gene Expression Analysis
1.61
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