Linkage of SSR markers with rice blast resistance and development of partial resistant advanced lines of rice (Oryza sativa) through marker-assisted selection

Nihad, Sheikh Arafat Islam; Hasan, MJ; Kabir, Amirul; Bhuiyan, Md. Rejwan; Yusop, Mohd Rafii; Latif, Abdul

doi:10.1007/s12298-022-01141-3

Cited by 15 publications

(13 citation statements)

References 66 publications

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“…Microsatellite markers have been extensively used for molecular variability assessment, mapping of genes/QTLs, marker‐assisted selection, marker‐assisted recurrent selection, and allele mining (Ganie et al., 2014; M. Kumar et al., 2022; Nihad et al., 2022; Park et al., 2020; A. K. Singh et al., 2011). We used 48 HvSSR markers for molecular analysis of 96 aromatic rices and detected 528 alleles with 11.0 alleles per SSR locus.…”

Section: Discussionmentioning

confidence: 99%

Aromatic rice (Oryza sativa L.) landraces of Indo‐Gangetic Plains of India harbor rich genetic diversity

Bairwa,

Yadav,

Tiwari

et al. 2024

Crop Science

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Aromatic rice (Oryza sativa L.) germplasm conserved in global genebanks needs intensive characterization to assess genetic diversity and population structure for crop improvement. We analyzed a panel of 92 accessions of non‐Basmati aromatic rice landrace germplasm with 23 phenotypic traits and 48 microsatellite markers. The landrace accessions displayed a huge phenotypic diversity for traits, namely, culm length, flag‐leaf length, panicle‐bearing tillers (PBT), plant height, panicle length, peduncle length, panicle exsertion, grain length, grain width, hull color, and 1000‐grain weight (TGW). Phenotypic clustering revealed three major clusters and five principal components explained 81.24% of the variance. TGW was associated positively with grain length, grain width, peduncle length, and grain yield but negatively with culm length and PBT. A total of 528 microsatellite alleles were detected, with 11.0 alleles per locus, revealing the presence of high polymorphism. Genetically, four subpopulations were detected based on structure analysis. In the germplasm, high levels of gene flow (Nm = 1.51) and gene diversity (HE = 0.83) were found. Among the subpopulations, we discovered high levels of inbreeding (FIS = 0.92) and moderate genetic differentiation (FST = 0.14). High polymorphism information content (0.806) along with a high level of molecular variance among genotypes (79%) was detected. A large number of multiple alleles were detected in numerous landrace accessions, revealing the presence of heterogeneity and heterozygotes in the landrace germplasm. The results of the present study are vital for the utilization of landrace diversity in the genetic improvement programs designed for rice quality improvement and consumer preference.

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Section: Discussionmentioning

confidence: 99%

Aromatic rice (Oryza sativa L.) landraces of Indo‐Gangetic Plains of India harbor rich genetic diversity

Bairwa,

Yadav,

Tiwari

et al. 2024

Crop Science

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“…To improve the blast resistance of Chinese restorer line R 175, Xiao et al ( 2019 ) followed two step MABC strategy using foreground selection for the target R gene(s) using gene-based or linked markers and stringent phenotypic selection for agronomic traits to accelerate recurrent parent genome recovery without background selection till BC 3 F 3 generation. The blast susceptible rice variety MR 263 was improved for blast resistance through MABC approach based on only foreground and phenotypic selection by Nihad et al ( 2022 ). The PCR-based DNA marker RM527 is tightly linked with Pi2 gene (Usatov et al 2016 ), was able to identify positive plants precisely without any false positive detection at any stage of MAS.…”

Section: Discussionmentioning

confidence: 99%

Improving blast resistance of maintainer line DRR 9B by transferring broad spectrum resistance gene Pi2 by marker assisted selection in rice

Singh

Ponnuswamy

Prasad

et al. 2023

Physiol Mol Biol Plants

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“…Initially, breeders utilized marker-trait associations revealed by linkage mapping and genome-wide association mapping for MAS in breeding programs to enhance efficiency and genetic gain 12 . To date, MAS has been successfully used to improve monogenic or oligogenic traits in many major crops such as rice 13 , 14 , wheat 15 – 17 , maize 18 – 20 , etc. However, the improvement of quantitative traits controlled by multiple QTLs with minor effects is challenging.…”

Section: Introductionmentioning

confidence: 99%

Genomic prediction for agronomic traits in a diverse Flax (Linum usitatissimum L.) germplasm collection

Hoque,

Anderson,

Rahman

2024

Sci Rep

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Breeding programs require exhaustive phenotyping of germplasms, which is time-demanding and expensive. Genomic prediction helps breeders harness the diversity of any collection to bypass phenotyping. Here, we examined the genomic prediction’s potential for seed yield and nine agronomic traits using 26,171 single nucleotide polymorphism (SNP) markers in a set of 337 flax (Linum usitatissimum L.) germplasm, phenotyped in five environments. We evaluated 14 prediction models and several factors affecting predictive ability based on cross-validation schemes. Models yielded significant variation among predictive ability values across traits for the whole marker set. The ridge regression (RR) model covering additive gene action yielded better predictive ability for most of the traits, whereas it was higher for low heritable traits by models capturing epistatic gene action. Marker subsets based on linkage disequilibrium decay distance gave significantly higher predictive abilities to the whole marker set, but for randomly selected markers, it reached a plateau above 3000 markers. Markers having significant association with traits improved predictive abilities compared to the whole marker set when marker selection was made on the whole population instead of the training set indicating a clear overfitting. The correction for population structure did not increase predictive abilities compared to the whole collection. However, stratified sampling by picking representative genotypes from each cluster improved predictive abilities. The indirect predictive ability for a trait was proportionate to its correlation with other traits. These results will help breeders to select the best models, optimum marker set, and suitable genotype set to perform an indirect selection for quantitative traits in this diverse flax germplasm collection.

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Linkage of SSR markers with rice blast resistance and development of partial resistant advanced lines of rice (Oryza sativa) through marker-assisted selection

Cited by 15 publications

References 66 publications

Aromatic rice (Oryza sativa L.) landraces of Indo‐Gangetic Plains of India harbor rich genetic diversity

Aromatic rice (Oryza sativa L.) landraces of Indo‐Gangetic Plains of India harbor rich genetic diversity

Improving blast resistance of maintainer line DRR 9B by transferring broad spectrum resistance gene Pi2 by marker assisted selection in rice

Genomic prediction for agronomic traits in a diverse Flax (Linum usitatissimum L.) germplasm collection

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