AUTHOR=Liu Hong , Rao Dehua , Guo Tao , Gangurde Sunil S. , Hong Yanbin , Chen Mengqiang , Huang Zhanquan , Jiang Yuan , Xu Zhenjiang , Chen Zhiqiang 

TITLE=Whole Genome Sequencing and Morphological Trait-Based Evaluation of UPOV Option 2 for DUS Testing in Rice

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.945015

DOI=10.3389/fgene.2022.945015

ISSN=1664-8021

ABSTRACT=To evaluate the application potential of high-density SNPs in rice DUS testing, we screened 37,929 SNP loci distributed on 12 rice chromosomes based on whole-genome resequencing of 122 rice accessions. These SNP loci were used to analyze the distinctness, uniformity and stability (DUS) testing of rice varieties based on the correlation of molecular and phenotypic distances of varieties according to UPOV option 2. The results showed that statistical algorithms, the number of phenotypic traits and SNP loci all affected the correlation between molecular and phenotypic distances of rice varieties. Compared with the other 9 algorithms，the Jaccard similarity algorithm had the highest correlation of 0.6587. Both the number of SNPs and the number of phenotypes had a ceiling effect on the correlation between molecular and phenotypic distances of varieties, and the ceiling effect of the number of SNP loci was more obvious. To overcome the correlation bottleneck, we used the genome-wide prediction method to predict 30 phenotypic traits and found that the prediction accuracy of some traits, such as basal sheath anthocyanin color, awn length, and the intensity of green color of leaf blade, was very low. Combined with group comparison analysis, we found that the key to overcoming the ceiling effect of correlation was to improve the resolution of traits with low predictive value. In addition, we also performed distinctness testing on rice varieties using molecular distance and phenotypic distance，and found that there was large differences between the two methods, indicating that UPOV option 2 alone could not replace the traditional phenotypic DUS testing. However, genotype and phenotype analysis together can increase the efficiency of DUS testing.