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中国农学通报 ›› 2026, Vol. 42 ›› Issue (1): 37-42.doi: 10.11924/j.issn.1000-6850.casb2024-0350

• 生物科学 • 上一篇    下一篇

混池样本数量对辣椒果色基因定位的影响

黄汕1,2(), 盘祥2, 陈潇1, 常静静1, 张白鸽1, 宋钊1()   

  1. 1 广东省农业科学院蔬菜研究所/广东省蔬菜新技术研究重点实验室,广州 510640
    2 清远市巨劲科技有限公司,广东清远 511520
  • 收稿日期:2024-05-29 修回日期:2025-06-15 出版日期:2026-01-15 发布日期:2026-01-15
  • 通讯作者:
    宋钊,男,1982年出生,湖南张家界人,副研究员,博士研究生,研究方向:辣椒果色遗传与简约化栽培研究。通信地址:510640 广东省广州市天河区五山街道金颖路66号蔬菜研究所,Tel:020-38801740,E-mail:
  • 作者简介:

    黄汕,男,1986年出生,清远连州人,工程师,硕士,研究方向:生物与农业应用技术研发。通信地址:511518 广东清远高新技术产业开发区天安智谷T1-102,Tel:0763-3787565,E-mail:

  • 基金资助:
    广州市基础与应用基础研究项目“辣椒青熟期黄果色基因精细定位”(202201010706); 广东省自然科学基金面上项目“辣椒黄果色重要候选基因的筛选与功能分析”(2023A1515012694)

Effect of Sample Number of DNA Bulks on Mapping of Fruit Color Genes in Capsicum

HUANG Shan1,2(), PAN Xiang2, CHEN Xiao1, CHANG Jingjing1, ZHANG Baige1, SONG Zhao1()   

  1. 1 Vegetable Research Institute/ Guangdong Key Lab for New Technology Research of Vegetables,Guangdong Academy of Agricultural Sciences, Guangzhou 510640
    2 Qingyuan Jujin Technology Co., Ltd., Qingyuan, Guangdong 511520
  • Received:2024-05-29 Revised:2025-06-15 Published:2026-01-15 Online:2026-01-15

摘要: 为明确辣椒BSA分析中适宜的DNA混池样本数量及可靠关联算法,本研究以青熟期淡黄果色(CSJ009)和绿果色(CSJ010)辣椒自交系构建的F2分离群体为材料,分别选取30株(2019年群体,220株)和50株(2021年群体,788株)极端表型单株构建DNA混池,进行全基因组重测序(WGRS)及BSA分析,比较SNP-index与ED 2种算法的定位效果。结果表明,50样本混池测序深度(平均50.92×)高于30样本混池(35×以上),Q30质量值(94.71%以上)更优,SNP与InDel标记检测错误率更低,但定位结果更复杂;SNP-index算法在50样本混池的99%置信水平下检测到235个峰值区(126个为负峰值区),难以锁定核心候选区间,而30样本混池仅检测到21个峰值区,且主要集中于9号染色体;ED算法在50样本混池的99%置信水平下检测到22个峰值区(均位于9号染色体),30样本混池检测到13个峰值区(集中于9号染色体29.5 Mbp区间)。结合遗传连锁分析验证结果,SNP-index算法比ED算法更可靠。综上,辣椒果色基因BSA定位中,30株极端表型单株构建混池的效果优于50株,SNP-index算法更适合目标基因初定位,研究结果可为辣椒及同类作物BSA基因定位的实验设计提供参考。

关键词: DNA混池, 辣椒果色, 集群分离分析, SNP-index算法, 欧氏距离算法

Abstract:

To determine the appropriate number of DNA pooled samples and reliable association algorithms for bulked segregant analysis (BSA) in pepper, this study used F2 segregating populations constructed from inbred lines with light-yellow (CSJ009) and green (CSJ010) immature fruit color. 30 (from a population of 220 F2 individuals in 2019) and 50 (from a population of 788 F2 individuals in 2021) extreme phenotype individuals were selected to construct DNA bulks, respectively, for whole-genome resequencing (WGRS) and BSA analysis. The mapping effects of SNP-index and ED algorithms were compared. The results showed that the sequencing depth of the 50-sample pool (average 50.92×) was higher than that of the 30-sample pool (above 35×), and the Q30 quality value was better (above 94.71%). The error rates of SNP and InDel marker detection were lower, but the mapping results were more complex. The SNP-index algorithm detected 235 peak regions (126 of which were negative peak regions) at the 99% confidence level in the 50-sample pool, making it difficult to lock onto the core candidate regions, while the 30-sample pool only detected 21 peak regions, mainly concentrated on chromosome 9. The ED algorithm detected 22 peak regions (all on chromosome 9) at the 99% confidence level in the 50-sample pool, and 13 peak regions (concentrated in the 29.5 Mbp interval on chromosome 9) in the 30-sample pool. Combined with the results of genetic linkage analysis verification, the SNP-index algorithm was more reliable than the ED algorithm. In conclusion, in the BSA mapping of pepper fruit color genes, the effect of constructing pools with 30 extreme phenotype plants is better than that with 50, and the SNP-index algorithm is more suitable for the initial mapping of target genes. The results provide a scientific reference for the experimental design of BSA gene mapping in pepper and similar crops.

Key words: DNA bulk, fruit color, bulked segregant analysis, SNP-index, Euclidean distance