文献类型：期刊文献

英文题名：Decoding hybrid origins and genetic architecture of leaf traits variation in camellia via high-density 21K SNP array for genomic prediction

作者：Li, Jiayu[1,2] Luo, Yixuan[1] Zhang, Rui[1,2] Li, Xinchun[3] Pan, Hongwei[1] Yin, Hengfu[1]

第一作者：李纪元;Li, Jiayu

通信作者：Pan, HW[1];Yin, HF[1]

机构：[1]Chinese Acad Forestry, Res Inst Subtrop Forestry, State Key Lab Tree Genet & Breeding, Zhejiang Key Lab Forest Genet & Breeding, Hangzhou 311400, Zhejiang, Peoples R China;[2]Hebei Agr Univ, Coll Landscape & Tourism, Baoding 071000, Hebei, Peoples R China;[3]Tianjin GenoAgri Co Co Ltd, Tianjin 300385, Peoples R China

年份：2025

卷号：12

期号：11

外文期刊名：HORTICULTURE RESEARCH

收录：;Scopus(收录号：2-s2.0-105020821266);WOS:【SCI-EXPANDED(收录号:WOS:001606086500001)】；

基金：This work was supported by the National Science Foundation of China, grant 32271839 and the Zhejiang Science and Technology Major Program on Agricultural New Variety Breeding (2021C02070-1).

语种：英文

摘要：The domestication of ornamental plants is primarily driven by aesthetic values and usually involves frequent hybridization events. Camellia spp., a globally famous woody flower, exemplifies the complex origins and extensive phenotypic variation. Here, based on the whole genome resequencing 220 germplasms, we developed Camellia21K, a high-density SNP array enabling cost-effective genome-wide genotyping. We demonstrated that Camellia21K accurately resolves 69 cultivars with complex hybridization histories. For molecular identification of closely related varieties, we developed a set of fingerprinting SNPs to support variety discrimination. To dissect the genomic basis of ornamental traits, we performed a genome-wide association study (GWAS) analysis of five leaf shape traits using the Camellia21K array and screened 31 SNP loci significantly associated with the traits. Further, by analyzing the genotypes of the SNP loci and the haplotypes of the surrounding segments, we identified potential genes regulating leaf tip length, thus demonstrating the versatility of the array. To enhance breeding efficiency, we evaluated and optimized four genomic selection (GS) models for leaf trait prediction. We found that the number of SNPs and model selection significantly affected prediction performance, with optimal predictive accuracy (PC) from 0.362 to 0.542, which was positively correlated with heritability. Finally, we integrated fixed-effects SNPs from GWAS and found significant enhancement of PC (24.7%-64.7%), indicating that the combination of GWAS and GS is indispensable for precision breeding applications. We demonstrated that Camellia21K is effective in discriminating the origin of varieties, in genetic analysis of traits and in genomic prediction, and thus informative for crop breeding.