Genetic diversity and distinctness based on morphological and SSR markers in peanut

Hong, Yanbin; Pandey, Manish K.; Lu, Qing; Líu, Hao; Gangurde, Sunil S.; Li, Shaoxiong; Liu, Haiyan; Li, Haifen; Liang, Xuanqiang; Varshney, Rajeev K.; Chen, Xiaoping

doi:10.1002/agj2.20671

Cited by 14 publications

(9 citation statements)

References 62 publications

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“…In this study, only five groups could not be distinguished by the 23 core markers, and the field growing comparison test showed that varieties in each of the five groups were very similar but were still distinguishable by some visually observed or measured characteristic. Molecular markers correlated to a medium extent ( r = 0.53) with morphological characteristics, which was higher than that in a previous study on peanuts (0.347) ( Hong et al., 2021 ), but no functional molecular markers associated with morphological characteristics in non-heading Chinese cabbage were found in this study. Therefore, without enough functional markers, molecular markers cannot completely replace morphological markers, but a combination of both types of markers would be more accurate and efficient in variety identification and in similar variety screening for the distinctness test.…”

Section: Discussioncontrasting

confidence: 95%

SSR marker based analysis for identification and of genetic diversity of non-heading Chinese cabbage varieties

Yin

Zhao

et al. 2023

Front. Plant Sci.

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As a widely cultivated vegetable in China and Southeast Asia, the breeding of non-heading Chinese cabbage (Brassica campestris ssp. chinensis Makino) is widespread; more than 400 varieties have been granted new plant variety rights (PVRs) in China. Distinctness is one of the key requirements for the granting of PVRs, and molecular markers are widely used as a robust supplementary method for similar variety selection in the distinctness test. Although many genome-wide molecular markers have been developed, they have not all been well used in variety identification and tests of distinctness of non-heading Chinese cabbage. In this study, by using 423 non-heading Chinese cabbage varieties collected from different regions of China, 287 simple sequence repeat (SSR) markers were screened for polymorphisms, and 23 core markers were finally selected. The polymorphic information content (PIC) values of the 23 SSR markers ranged from 0.555 to 0.911, with an average of 0.693, and the average number of alleles per marker was 13.65. Using these 23 SSR markers, 418 out of 423 varieties could be distinguished, with a discrimination rate of 99.994%. Field tests indicated that those undistinguished varieties were very similar and could be further distinguished by a few morphological characteristics. According to the clustering results, the 423 varieties could be divided into three groups: pak-choi, caitai, and tacai. The similarity coefficient between the SSR markers and morphological characteristics was moderate (0.53), and the efficiency of variety identification was significantly improved by using a combination of SSR markers and morphological characteristics.

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Section: Discussioncontrasting

confidence: 95%

SSR marker based analysis for identification and of genetic diversity of non-heading Chinese cabbage varieties

Yin

Zhao

et al. 2023

Front. Plant Sci.

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“…DUS testing is an important scientific basis for the authorization of new plant varieties. In order to improve the testing efficiency and quality, researchers have conducted in-depth studies on the correlation between molecular distances and phenotypic distances of varieties (Jones et al, 2013;Hong et al, 2021). Earlier reports showed that there was low correlation between phenotypic and molecular distances (Gupta et al, 2018;Guan et al, 2020), which might be related to the low number of Correlation between the molecular and phenotypic distances of varieties based on the Jaccard algorithm.…”

Section: Discussionmentioning

confidence: 99%

“…However, in comparison with morphological characteristics, molecular markers can be used at various developmental stages and they are not affected by the environment. Moreover, molecular markers are abundant and genetically stable, and they are most widely used for genetic diversity analyses in almost all crops (Hayward et al, 2015;Hong et al, 2021). Molecular markers have diverse applications in breeding programs, such as F1 confirmation, cultivar/hybrid purity testing, DNA finger printing (Gangurde et al, 2017), foreground and background selection (Shasidhar et al, 2020), marker-assisted selection (Cockram et al, 2012;Wagh et al, 2021), and genetic mapping (Dodia et al, 2019;Jadhav et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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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.

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“…Cultivated peanut ( Arachis hypogaea L.) is one of the most important leguminous oilseeds and food crops used for high-quality eatable oil and protein [ 1 ]. To date, ~54 million tons of peanuts are produced annually around the world [ 2 , 3 ], but peanut bacterial wilt (PBW) a soil-borne vascular disease caused by Ralstonia solanacearum , severely damages worldwide peanut production due to its widespread distribution and high pathogenicity [ 4 , 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Silicon Application for the Modulation of Rhizosphere Soil Bacterial Community Structures and Metabolite Profiles in Peanut under Ralstonia solanacearum Inoculation

Deng

Líu

et al. 2023

IJMS

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Silicon (Si) has been shown to promote peanut growth and yield, but whether Si can enhance the resistance against peanut bacterial wilt (PBW) caused by Ralstonia solanacearum, identified as a soil-borne pathogen, is still unclear. A question regarding whether Si enhances the resistance of PBW is still unclear. Here, an in vitro R. solanacearum inoculation experiment was conducted to study the effects of Si application on the disease severity and phenotype of peanuts, as well as the microbial ecology of the rhizosphere. Results revealed that Si treatment significantly reduced the disease rate, with a decrement PBW severity of 37.50% as compared to non-Si treatment. The soil available Si (ASi) significantly increased by 13.62–44.87%, and catalase activity improved by 3.01–3.10%, which displayed obvious discrimination between non-Si and Si treatments. Furthermore, the rhizosphere soil bacterial community structures and metabolite profiles dramatically changed under Si treatment. Three significantly changed bacterial taxa were observed, which showed significant abundance under Si treatment, whereas the genus Ralstonia genus was significantly suppressed by Si. Similarly, nine differential metabolites were identified to involve into unsaturated fatty acids via a biosynthesis pathway. Significant correlations were also displayed between soil physiochemical properties and enzymes, the bacterial community, and the differential metabolites by pairwise comparisons. Overall, this study reports that Si application mediated the evolution of soil physicochemical properties, the bacterial community, and metabolite profiles in the soil rhizosphere, which significantly affects the colonization of the Ralstonia genus and provides a new theoretical basis for Si application in PBW prevention.

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Genetic diversity and distinctness based on morphological and SSR markers in peanut

Cited by 14 publications

References 62 publications

SSR marker based analysis for identification and of genetic diversity of non-heading Chinese cabbage varieties

SSR marker based analysis for identification and of genetic diversity of non-heading Chinese cabbage varieties

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

Silicon Application for the Modulation of Rhizosphere Soil Bacterial Community Structures and Metabolite Profiles in Peanut under Ralstonia solanacearum Inoculation

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