https://www.ahs.ac.cn/images/0513-353X/images/top-banner1.jpg|#|苹果
https://www.ahs.ac.cn/images/0513-353X/images/top-banner2.jpg|#|甘蓝
https://www.ahs.ac.cn/images/0513-353X/images/top-banner3.jpg|#|菊花
https://www.ahs.ac.cn/images/0513-353X/images/top-banner4.jpg|#|灵芝
https://www.ahs.ac.cn/images/0513-353X/images/top-banner5.jpg|#|桃
https://www.ahs.ac.cn/images/0513-353X/images/top-banner6.jpg|#|黄瓜
https://www.ahs.ac.cn/images/0513-353X/images/top-banner7.jpg|#|蝴蝶兰
https://www.ahs.ac.cn/images/0513-353X/images/top-banner8.jpg|#|樱桃
https://www.ahs.ac.cn/images/0513-353X/images/top-banner9.jpg|#|观赏荷花
https://www.ahs.ac.cn/images/0513-353X/images/top-banner10.jpg|#|菊花
https://www.ahs.ac.cn/images/0513-353X/images/top-banner11.jpg|#|月季
https://www.ahs.ac.cn/images/0513-353X/images/top-banner12.jpg|#|菊花

园艺学报 ›› 2012, Vol. 39 ›› Issue (5): 879-887.

• 蔬菜 • 上一篇    下一篇

黄瓜苗期主要农艺性状相关 QTL 定位分析

 苗晗, 顾兴芳, 张圣平, 张忠华, 黄三文, 王烨, 方智远   

  1. (中国农业科学院蔬菜花卉研究所,北京 100081)
  • 出版日期:2012-05-25 发布日期:2012-05-25

Mapping QTLs for Seedling-associated Traits in Cucumber

MIAO  Han, GU  Xing-Fang, ZHANG  Sheng-Ping, ZHANG  Zhong-Hua, HUANG  San-Wen, WANG  Ye, FANG  Zhi-Yuan   

  1. (Institute of Vegetables and Flowers,Chinese Academy of Agricultural Sciences,Beijing 100081,China)
  • Online:2012-05-25 Published:2012-05-25

摘要: 利用以华北保护地类型黄瓜9930和欧洲温室类型黄瓜9110Gt为亲本构建的含148株系的F9代RILs群体遗传图谱,结合春秋两季4次黄瓜苗期相关性状的表型鉴定数据,使用MapQTL4.0软件采用多座位QTL模型(MQM)进行QTL定位分析?在RIL群体中检测到与子叶长、子叶宽、下胚轴长、第一雌花节位、始花期等5个性状相关的QTL共19个,分布在1、3、5、6号染色体上,其中主效QTL(贡献率≥10.0%)17个,占总数的89.5%,可在不同季节重复检出的QTL 3个;检测到的QTL的LOD值在3.28 ~ 15.25之间,可解释的表型变异在6% ~ 37.8%之间。结合基因组序列信息对主效QTL定位区域进行了基因预测。

关键词: 黄瓜, 苗期相关性状, QTL, 重组自交系, SSR 标记

Abstract: Phenotypic data of cotyledon length(Cl),cotyledon width(Cw),hypocotyl length(Hl),the first pistillate flower bearing node(Fpfn),days to anthesis(Da)in 148 F9 recombinant inbred lines (RILs)which originated from a narrow-cross between 9110Gt and 9930 were investigated four times in different seasons. The multiple QTL model(MQM)method of software package MapQTL version 4.0 was used to map and analyze QTLs. Nineteen QTLs were detected for 5 traits. These QTLs were mapped on chromosome 1,3,5 and 6,respectively. 17 QTLs(89.5%)were major QTLs which explained more than 10% of the phenotypic variation. Three QTLs were repeatedly detected in different seasons in greenhouse cultivation. Their LOD values varied between 3.28 and 15.25,which explained 6%–37.8% of the phenotypic variation. Based on the whole genome sequence,the genomic regions harboring major QTLs were analyzed using BLAST software.

Key words:

cucumber, seedling-associated traits, quantitative trait locus(QTL), recombinant inbred lines(RILs), SSR marker