四川林业科技2024,Vol.45Issue(2) :103-108.DOI:10.12172/202209210002

利用微卫星标记鉴定核桃杂交子代的亲本

Parentage assignment of walnut hybrid offspring by microsatellite markers

郑崇文 王婉尧 白斌 李丕军 吴泞孜 邢文曦 王静 杨金亮
四川林业科技2024,Vol.45Issue(2) :103-108.DOI:10.12172/202209210002

利用微卫星标记鉴定核桃杂交子代的亲本

Parentage assignment of walnut hybrid offspring by microsatellite markers

郑崇文 1王婉尧 2白斌 1李丕军 1吴泞孜 1邢文曦 1王静 1杨金亮1
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作者信息

  • 1. 四川省林业科学研究院,四川成都 610036
  • 2. 四川省林业和草原调查规划院,四川成都 610036
  • 折叠

摘要

杂交育种是目前核桃育种的主要方法,为了快速有效地鉴别杂交子代的真实性,加速杂交育种进程,利用微卫星标记方法辅助进行核桃亲子鉴定.研究从已发表的60对核桃属植物微卫星标记中筛选出12个多态性相对较高且稳定扩增的微卫星位点,对5个杂交组合子代159个个体通过基因型排除法和最大似然法进行亲子关系鉴定.基因型排除法鉴定出121个子代的正确亲本,鉴定率较高,总鉴定率76.10%;最大似然法亲权分析显示,双亲未知情形达到置信区间预测出正确亲本的子代有12个,总鉴定率7.55%.父本未知情形达到置信区间推算出正确亲本的子代有19个,总体鉴定率11.95%.整体鉴定率较低.

Abstract

Cross breeding is the main method of walnut breeding at present.In order to identify the authenticity of cross offspring and accelerate the process of cross breeding quickly and effectively,the microsatellite marker was used to assist walnut paternity identification.In this study,12 microsatellite loci with relatively high polymorphism and stable amplification were selected from 60 published SSR primers of walnut.The 159 offsprings from 5 hybrid combinations were identified by genotype elimination and maximum likelihood method.The correct parents of 121 progeny were identified by genotype elimination,the identification rate was high,and the total identification rate was 76.10%.The maximum likelihood parental analysis showed that 12 offspring with unknown parents reached the confidence interval predicted the correct parents,and the total identification rate was 7.55%.There were 19 progeny whose parents were correct when the confidence interval was reached,and the overall identification rate was 11.95%.The overall identification rate was low.

关键词

核桃/微卫星/亲子鉴定/基因型排除法/最大似然法

Key words

Juglans regia/microsatellites/paternity analysis/genotype elimination method/maximum likelihood method

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基金项目

四川省育种攻关项目(十四五)(2021YFYZ0032-07)

四川省科技厅重点研发项目(2021YFN0005)

出版年

2024
四川林业科技
四川省林学会 四川省林业科学研究院

四川林业科技

影响因子:0.452
ISSN:1003-5508
参考文献量25
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