利用KASP标记鉴定'吉美8号'大白菜种子纯度
Identification of Chinese Cabbage Seed Purity of'Jimei No.8'by KASP Markers
唐昊 1杨双娟 2张晓伟 2魏小春 2赵艳艳 2王志勇 2苏贺楠 2原玉香 2李庆飞3
作者信息
- 1. 河南科技学院园艺园林学院,新乡,453003;河南省农业科学院园艺研究所,郑州,450002
- 2. 河南省农业科学院园艺研究所,郑州,450002
- 3. 河南科技学院园艺园林学院,新乡,453003
- 折叠
摘要
种子纯度是种子质量的核心指标,是保障优良品种增产的关键因素.本研究以大白菜品种'吉美8号'及其亲本为实验材料,用KASP标记技术研究杂交种与双亲之间的多态性引物以甄别真假杂交种.结果发现,从26个KASP标记中筛选到6个在亲本间差异明显的标记,分别为KBr98、KBr100、KBr106、KBr109、KBr135和KBr143.选取其中的3个标记(KBr100,KBr106和KBr143)对136株'吉美8号'杂交种进行纯度分析,结果表明,3个KASP标记对'吉美8号'种子纯度鉴定结果完全一致,杂交种纯度均为96.32％.进一步利用InDe1标记BrID90039对136株'吉美8号'杂交种进行纯度分析,其鉴定结果与3个KASP标记的结果也完全一致,证明了 KASP标记鉴定结果的准确性.因此,本研究筛选的6个KASP标记可以低成本、高通量的用于大白菜杂交种'吉美8号'种子纯度的快速鉴定.
Abstract
Seed purity is the core index of seed quality and the key factor to ensure the yield increase of excellent varieties.In this study,the Chinese Cabbage variety'Jimei No.8'and its parents were used as experimental materi-als,and the polymorphic primers between the hybrids and their parents were studied by KASP marker technology to identify the true and false hybrids.The results showed that six KASP markers with significant differences be-tween parents were selected from 26 KASP markers,namely KBr98,KBr100,KBr106,KBr109,KBr135 and KBr143.Three of them(KBr100,KBr106 and KBr143)were selected to analyze the purity of 136'Jimei 8'hybrids.The results showed that the three pairs of KASP markers identified the purity of'Jimei No.8'seeds were identical,and the purity of the hybrids was 96.32％.The purity of 136'Jimei No.8'hybrids was further analyzed by using In-Del marker BrID90039.The identification results were also consistent with the results of three KASP markers,which proved the accuracy of the identification results of KASP markers.Therefore,the six KASP markers select-ed in this study can be used for rapid identification of seed purity of Chinese cabbage hybrid'Jimei No.8'with low cost and high throughput.
关键词
大白菜/吉美8号/KASP标记/纯度鉴定Key words
Chinese cabbage/Jimei No.8/KASP marker/Purity identification引用本文复制引用
基金项目
河南省农业良种联合攻关项目(2022010504)
国家大宗蔬菜产业技术体系项目(CARS-23-G15)
河南省农业科学院优秀创新团队项目(2023TD06)
出版年
2024
NETL
NSTL
万方数据