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一种用于苹果(Malus × domestica Borkh.)SSR 基因分型的单管反应试剂盒。

A new one-tube reaction kit for the SSR genotyping of apple (Malus × domestica Borkh.).

机构信息

Research and Breeding Institute of Pomology Holovousy, Ltd., Holovousy 129, 508 01 Horice, Czech Republic.

Research and Breeding Institute of Pomology Holovousy, Ltd., Holovousy 129, 508 01 Horice, Czech Republic.

出版信息

Plant Sci. 2021 Feb;303:110768. doi: 10.1016/j.plantsci.2020.110768. Epub 2020 Nov 25.

Abstract

Though apple genotyping is mainly used for scientific and breeding purposes, it can also be adopted by national authorities to control the authenticity of apple cultivars. To facilitate the introduction of routine apple genotyping into practice, a new apple simple sequence repeat (SSR) genotyping kit was developed (called the Ap17 in. SSR Genotyping Kit). The kit combines 17 SSR markers including those recommended by the Working Group of the European Cooperative Programme for Plant Genetic Resources (ECPGR), covering all apple linkage groups in a one-tube reaction format, using a fragment analysis method to simplify the genotyping procedure. The kit was successfully tested using 880 unique diploid apple germplasm accessions; the kit can also readily discriminate triploid and tetraploid samples. The total probability of identity for the kit and the sample collection used was calculated to be 1.73 × 10. Tables for converting results to enable genotype comparisons between currently-used genotyping systems and the Ap17 in. kit are provided. The kit is ideally suited for validation in laboratories genotyping a large number of apple samples, saving time, costs, and labor, while minimizing technical and human errors.

摘要

虽然苹果基因分型主要用于科学和育种目的,但国家当局也可以采用它来控制苹果品种的真实性。为了促进常规苹果基因分型在实践中的应用,开发了一种新的苹果简单重复序列(SSR)基因分型试剂盒(称为 Ap17 in. SSR 基因分型试剂盒)。该试剂盒结合了 17 个 SSR 标记物,包括欧洲合作植物遗传资源计划(ECPGR)工作组推荐的标记物,涵盖了所有苹果连锁群,采用片段分析方法简化了基因分型程序。该试剂盒已成功用于 880 个独特的二倍体苹果种质资源进行测试;该试剂盒还可以轻松区分三倍体和四倍体样本。试剂盒和使用的样本集的总身份概率计算为 1.73 × 10。提供了用于将结果转换为当前使用的基因分型系统和 Ap17 in. 之间进行基因型比较的表格。试剂盒非常适合在大量苹果样本进行基因分型的实验室中进行验证,节省时间、成本和劳动力,同时最大限度地减少技术和人为错误。

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