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- Title
茶树叶型性状的全基因组关联分析.
- Authors
王小萍; 王 云; 熊元元; 刘 晓; 李明红; 张 厅; 赖 谦; 李春华
- Abstract
【Objective】This study aims to investigate SNP markers associated with leaf-type related traits in order to provide a reference for molecular marker-assisted breeding of tea plants. 【Method】In this study, simplified genome sequencing (GBS) was conducted on 91 natural tea populations collected in Sichuan. A genome-wide association analysis (GWAS) based on the GLM (Q) model was performed using 863, 468 SNP markers obtained from sequencing. Eight leaf-type related traits, including leaf length (YC), leaf width (YK), leaf length-width ratio (CKB), leaf area (YS), leaf color (YSZ), leaf tip (LD), leaf vein logarithm (YM), and leaf margin (YY), were investigated.【Result】A total of 38 significant SNP markers were detected at a p-value of <0.01, and there were 1 SNP marker associated with YC, 24 SNP markers associated with CKB, 6 SNP markers associated with YSZ, 2 SNP markers associated with YD, 1 SNP marker associated with YM and 4 markers associated with YY. The 38 significant SNP markers could explaine the association traits between 31.37% and 60.70%. Further candidate gene mining within the 50 kbp region upstream and downstream of the significant markers yielded. Additionally, 8 candidate genes were further identified, CSA011953 (Sec11a), CSA027293 (CAD3), CSA020561 (GAE2), CSA008530 (AIM1), CSA008531 (MFP), CSA008532 (AIM1), CSA008763 (CYP72A154), and CSA029592 (RABG3F). Through Go and Ko annotation, CSA027293 (CAD3) and CSA008763 (CYP72A154) could be closely associated with leaf length-width ratio (CKB) and leaf color (YSZ). 【Conclusion】The 38 identification of SNP markers and two candidate genes associated with tea leaf shape traits provide valuable genetic resources and a reference basis for the precise localization of genes regulating tea tree leaf shape and for molecular marker-assisted breeding.
- Subjects
GENOME-wide association studies; SINGLE nucleotide polymorphisms; TEA
- Publication
Southwest China Journal of Agricultural Sciences, 2023, Vol 36, Issue 11, p2339
- ISSN
1001-4829
- Publication type
Article
- DOI
10.16213/j.cnki.scjas.2023.11.005