Phenotypic data were recorded for 30 morphological traits ( Table 2 ; Supplementary Table S2 ).
Open resource ↗Supplementary Table S2 · lines:702-772Unverified paper record
Whole Genome Sequencing and Morphological Trait-Based Evaluation of UPOV Option 2 for DUS Testing in Rice.
Frontiers in genetics · 26 Aug 2022 · 10.3389/fgene.2022.945015
Abstract
To evaluate the application potential of high-density SNPs in rice distinctness, uniformity, and stability (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 DUS testing of rice varieties based on the correlation between the molecular and phenotypic distances of varieties according to UPOV option 2. The results showed that statistical algorithms and the number of phenotypic traits and SNP loci all affected the correlation between the molecular and phenotypic distances of rice varieties. Relative to the other nine 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 the 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 the basal sheath anthocyanin color, glume length, and intensity of the green color of the leaf blade, was very low. In combination 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 values. In addition, we also performed distinctness testing on rice varieties by using the molecular distance and phenotypic distance, and we found that there were large differences between the two methods, indicating that UPOV option 2 alone cannot replace the traditional phenotypic DUS testing. However, genotype and phenotype analysis together can increase the efficiency of DUS testing.
Plant phenotyping relevance
イネのDUS試験における分子距離・表現型距離、統計アルゴリズム、ゲノムワイド予測を比較評価しており、表現型評価手法の技術的検証が研究の中心です。
abstractTo evaluate the application potential of high-density SNPs in rice distinctness, uniformity, and stability (DUS) testing
abstractThese SNP loci were used to analyze the DUS testing of rice varieties based on the correlation between the molecular and phenotypic distances of varieties according to UPOV option 2.
abstractTo overcome the correlation bottleneck, we used the genome-wide prediction method to predict 30 phenotypic traits
abstractgenotype and phenotype analysis together can increase the efficiency of DUS testing.
Code and data availability
保存済みの本文根拠を更新済みルールで再検証し、公開資産1件を確認しました。
This is an automatically classified, unverified record. Curator approval is required before any resource enters the Catalog.