Departamento de Ciencias Agrarias y del Medio Natural, Universidad de Zaragoza, Escuela Politécnica Superior, Huesca, Spain.
Departamento del Arroz, Instituto Valenciano de Investigaciones Agrarias, Moncada, Spain.
PLoS One. 2023 Jun 23;18(6):e0286839. doi: 10.1371/journal.pone.0286839. eCollection 2023.
The use of molecular markers for plant variety identification and protection is increasing. For this purpose, SNP markers have provided a reliable and stable tool for plant genotyping. The availability of small and low-cost SNP panels to accelerate the identification of the cultivated rice varieties should be beneficial for breeders, seed certification entities and rice industry. With the intention of providing of such a facility, we first developed a simple and easy-handle bioinformatics tool based on the widely used and freely available software R to generate small sets of SNPs that can discriminate varieties, by selecting markers from a larger genotyping dataset. By applying this algorithm to data from a previously genotyped collection of temperate japonica varieties from different countries, we identified a minimal set of 31 SNPs markers to distinguish 210 varieties. In addition, we used this algorithm to discriminate the 43 most cultivated in Spain rice varieties with minimal sets of 8 SNPs. We then developed and tested 22 Kompetitive Allele-Specific PCR (KASP) assays for the markers included in these panels, and obtained reliable genotype patterns for rice varieties identification. The complete 22 markers panel and the rice genotypes data could offer a useful and low-cost tool for rice breeders and industry to identify varieties and therefore to guarantee the quality of rice. The provided R-based algorithm can be applied to other genomic resources to develop core sets of discriminating markers.
利用分子标记进行植物品种鉴定和保护的方法正在不断增加。为此,SNP 标记为植物基因型分析提供了可靠且稳定的工具。小型且廉价的 SNP 面板的可用性可以加速栽培稻品种的鉴定,这将对育种者、种子认证实体和稻米行业有益。为了提供这样的工具,我们首先基于广泛使用且免费的 R 软件开发了一个简单易用的生物信息学工具,通过从更大的基因分型数据集选择标记,生成可以区分品种的 SNP 小集。通过将此算法应用于来自不同国家的温带粳稻品种的先前基因分型数据集,我们确定了一个最小的 31 个 SNP 标记集,可区分 210 个品种。此外,我们还使用此算法区分了西班牙种植的 43 个主要水稻品种,最小集为 8 个 SNP。然后,我们为这些面板中的标记开发并测试了 22 个竞争性等位基因特异性 PCR(KASP)测定,以获得可靠的水稻品种基因型模式。完整的 22 个标记面板和水稻基因型数据可以为水稻育种者和行业提供一个有用且低成本的工具,用于识别品种,从而保证大米的质量。所提供的基于 R 的算法可以应用于其他基因组资源,以开发区分标记的核心集。