Dataset Information

Characterization of Pre-Breeding Wheat (Triticum aestivum L.) Germplasm for Stripe Rust Resistance Using Field Phenotyping and Genotyping.

ABSTRACT: Wheat is highly affected by stripe rust disease, particularly under cooler environments, and the losses can reach up to 100 percent depending on the intensity of infection and the susceptibility of the genotype. The most effective method to manage this disease is the use of resistant varieties. In the present study, 192 wheat genotypes were evaluated for stripe rust resistance under field conditions and also in a laboratory using molecular markers. These lines included pre-breeding germplasm developed for rust resistance and some high-yielding commercially grown wheat varieties. Out of 192 genotypes, 53 were found to be resistant, and 29 showed moderate resistance reaction under field conditions, whereas the remaining genotypes were all either moderately susceptible or susceptible. Under controlled conditions, out of 109 genotypes, only 12 were found to be resistant to all the six virulent/pathogenic pathotypes. Additionally, a selection of 97 genotypes were found resistant in field screening and were subjected to molecular validation using the markers linked to major R-genes, viz., Yr5, Yr10, Yr15 and Yr17. Nine genotypes possessed the Yr5 gene, twelve had the Yr10 gene, fourteen had the Yr15 gene and thirty-two had the Yr17 gene. The resistance genes studied in the current study are effective in conferring resistance against stripe rust disease. The genotypes identified as resistant under both field and controlled conditions can be used as sources in stripe rust resistance breeding programs.

SUBMITTER: Ul Islam B

PROVIDER: S-EPMC10538134 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Characterization of Pre-Breeding Wheat (<i>Triticum aestivum</i> L.) Germplasm for Stripe Rust Resistance Using Field Phenotyping and Genotyping.

Ul Islam Basharat B Mir Saba S Dar Mohammad Saleem MS Khan Gazala H GH Shikari Asif B AB Sofi Najeeb Ul Rehman NUR Mohiddin Fayaz F Ahangar Mohammad Ashraf MA Jehangir Intikhab Aalum IA Kumar Satish S Kumar Satish S Singh Gyanendra G Wani Shabir H SH

Plants (Basel, Switzerland) 20230912 18

Wheat is highly affected by stripe rust disease, particularly under cooler environments, and the losses can reach up to 100 percent depending on the intensity of infection and the susceptibility of the genotype. The most effective method to manage this disease is the use of resistant varieties. In the present study, 192 wheat genotypes were evaluated for stripe rust resistance under field conditions and also in a laboratory using molecular markers. These lines included pre-breeding germplasm dev ...[more]

PMID: 37765402

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Project description:Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a severe disease in wheat worldwide, including Ethiopia, causing up to 100% wheat yield loss in the worst season. The use of resistant cultivars is considered to be the most effective and durable management technique for controlling the disease. Therefore, the present study targeted the genetic architecture of adult plant resistance to yellow rust in 178 wheat association panels. The panel was phenotyped for yellow rust adult-plant resistance at three locations. Phonological, yield, yield-related, and agro-morphological traits were recorded. The association panel was fingerprinted using the genotyping-by-sequencing (GBS) platform, and a total of 6,788 polymorphic single nucleotide polymorphisms (SNPs) were used for genome-wide association analysis to identify effective yellow rust resistance genes. The marker-trait association analysis was conducted using the Genome Association and Prediction Integrated Tool (GAPIT). The broad-sense heritability for the considered traits ranged from 74.52% to 88.64%, implying the presence of promising yellow rust resistance alleles in the association panel that could be deployed to improve wheat resistance to the disease. The overall linkage disequilibrium (LD) declined within an average physical distance of 31.44 Mbp at r2 = 0.2. Marker-trait association (MTA) analysis identified 148 loci significantly (p = 0.001) associated with yellow rust adult-plant resistance. Most of the detected resistance quantitative trait loci (QTLs) were located on the same chromosomes as previously reported QTLs for yellow rust resistance and mapped on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6A, 6B, 7A, and 7D. However, 12 of the discovered MTAs were not previously documented in the wheat literature, suggesting that they could represent novel loci for stripe rust resistance. Zooming into the QTL regions in IWGSC RefSeq Annotation v1 identified crucial disease resistance-associated genes that are key in plants' defense mechanisms against pathogen infections. The detected QTLs will be helpful for marker-assisted breeding of wheat to increase resistance to stripe rust. Generally, the present study identified putative QTLs for field resistance to yellow rust and some important agronomic traits. Most of the discovered QTLs have been reported previously, indicating the potential to improve wheat resistance to yellow rust by deploying the QTLs discovered by marker-assisted selection.

Project description:BackgroundAppropriate information about genetic diversity and population structure of germplasm improves the efficiency of plant breeding. The low productivity of Nepali bread wheat (Triticum aestivum L.) is a major concern particularly since Nepal is ranked the 4th most vulnerable nation globally to climate change. The genetic diversity and population structure of Nepali spring wheat have not been reported. This study aims to improve the exploitation of more diverse and under-utilized genetic resources to contribute to current and future breeding efforts for global food security.ResultsWe used genotyping-by-sequencing (GBS) to characterize a panel of 318 spring wheat accessions from Nepal including 166 landraces, 115 CIMMYT advanced lines, and 34 Nepali released varieties. We identified 95 K high-quality SNPs. The greatest genetic diversity was observed among the landraces, followed by CIMMYT lines, and released varieties. Though we expected only 3 groupings corresponding to these 3 seed origins, the population structure revealed two large, distinct subpopulations along with two smaller and scattered subpopulations in between, with significant admixture. This result was confirmed by principal component analysis (PCA) and UPGMA distance-based clustering. The pattern of LD decay differed between subpopulations, ranging from 60 to 150 Kb. We discuss the possibility that germplasm explorations during the 1970s-1990s may have mistakenly collected exotic germplasm instead of local landraces and/or collected materials that had already cross-hybridized since exotic germplasm was introduced starting in the 1950s.ConclusionWe suggest that only a subset of wheat "landraces" in Nepal are authentic which this study has identified. Targeting these authentic landraces may accelerate local breeding programs to improve the food security of this climate-vulnerable nation. Overall, this study provides a novel understanding of the genetic diversity of wheat in Nepal and this may contribute to global wheat breeding initiatives.

Project description:Stripe rust is one of the most destructive diseases of wheat (Triticum aestivum L.), caused by Puccinia striiformis f. sp. tritici (Pst), and responsible for significant yield losses worldwide. Single-nucleotide polymorphism (SNP) diagnostic markers were used to identify new sources of resistance at adult plant stage to wheat stripe rust (YR) in 141 CIMMYT advanced bread wheat lines over 3 years in replicated trials at Borlaug Institute for South Asia (BISA), Ludhiana. We performed a genome-wide association study and genomic prediction to aid the genetic gain by accumulating disease resistance alleles. The responses to YR in 141 advanced wheat breeding lines at adult plant stage were used to generate G × E (genotype × environment)-dependent rust scores for prediction and genome-wide association study (GWAS), eliminating variation due to climate and disease pressure changes. The lowest mean prediction accuracies were 0.59 for genomic best linear unbiased prediction (GBLUP) and ridge-regression BLUP (RRBLUP), while the highest mean was 0.63 for extended GBLUP (EGBLUP) and random forest (RF), using 14,563 SNPs and the G × E rust score results. RF and EGBLUP predicted higher accuracies (∼3%) than did GBLUP and RRBLUP. Promising genomic prediction demonstrates the viability and efficacy of improving quantitative rust tolerance. The resistance to YR in these lines was attributed to eight quantitative trait loci (QTLs) using the FarmCPU algorithm. Four (Q.Yr.bisa-2A.1, Q.Yr.bisa-2D, Q.Yr.bisa-5B.2, and Q.Yr.bisa-7A) of eight QTLs linked to the diagnostic markers were mapped at unique loci (previously unidentified for Pst resistance) and possibly new loci. The statistical evidence of effectiveness and distribution of the new diagnostic markers for the resistance loci would help to develop new stripe rust resistance sources. These diagnostic markers along with previously established markers would be used to create novel DNA biosensor-based microarrays for rapid detection of the resistance loci on large panels upon functional validation of the candidate genes identified in the present study to aid in rapid genetic gain in the future breeding programs.

Dataset Information

Characterization of Pre-Breeding Wheat (Triticum aestivum L.) Germplasm for Stripe Rust Resistance Using Field Phenotyping and Genotyping.

Publications

Characterization of Pre-Breeding Wheat (<i>Triticum aestivum</i> L.) Germplasm for Stripe Rust Resistance Using Field Phenotyping and Genotyping.

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