Abstract
Wheat blast is an emerging threat to wheat production, due to its recent migration to South Asia and Sub-Saharan Africa. Because genomic selection (GS) has emerged as a promising breeding strategy, the key objective of this study was to evaluate it for wheat blast phenotyped at precision phenotyping platforms in Quirusillas (Bolivia), Okinawa (Bolivia) and Jashore (Bangladesh) using three panels: (i) a diversity panel comprising 172 diverse spring wheat genotypes, (ii) a breeding panel comprising 248 elite breeding lines, and (iii) a full-sibs panel comprising 298 full-sibs. We evaluated two genomic prediction models (the genomic best linear unbiased prediction or GBLUP model and the Bayes B model) and compared the genomic prediction accuracies with accuracies from a fixed effects model (with selected blast-associated markers as fixed effects), a GBLUP + fixed effects model and a pedigree relationships-based model (ABLUP). On average, across all the panels and environments analyzed, the GBLUP + fixed effects model (0.63 ± 0.13) and the fixed effects model (0.62 ± 0.13) gave the highest prediction accuracies, followed by the Bayes B (0.59 ± 0.11), GBLUP (0.55 ± 0.1), and ABLUP (0.48 ± 0.06) models. The high prediction accuracies from the fixed effects model resulted from the markers tagging the 2NS translocation that had a large effect on blast in all the panels. This implies that in environments where the 2NS translocation-based blast resistance is effective, genotyping one to few markers tagging the translocation is sufficient to predict the blast response and genome-wide markers may not be needed. We also observed that marker-assisted selection (MAS) based on a few blast-associated markers outperformed GS as it selected the highest mean percentage (88.5%) of lines also selected by phenotypic selection and discarded the highest mean percentage of lines (91.8%) also discarded by phenotypic selection, across all panels. In conclusion, while this study demonstrates that MAS might be a powerful strategy to select for the 2NS translocation-based blast resistance, we emphasize that further efforts to use genomic tools to identify non-2NS translocation-based blast resistance are critical.
Highlights
IntroductionAn emerging threat to wheat production that has the potential to cause substantial yield losses is the disease blast (Kohli et al, 2011; Islam et al, 2016; Chowdhury et al, 2017; Cruz and Valent, 2017; Sadat and Choi, 2017; Singh et al, 2021), caused by the fungus Magnaporthe oryzae pathotype Triticum Catt. (MoT) (anamorph Pyricularia oryzae Cavara) (Couch and Kohn, 2002; Tosa and Chuma, 2014; Zhang et al, 2016)
The diversity panel was phenotyped for blast in two planting dates that were about 14 days apart, indicated as first planting (FP) and second planting (SP) in the following blast precision phenotyping platforms and crop cycles: (i) Quirusillas, Bolivia (18◦20 S 63◦57 W) during the 2017– 2018 and 2018–2019 crop cycles (December to April) in two different planting dates and the datasets are referred to by the site followed by the harvest year and planting time as: Quirusillas 2018 FP, Quirusillas 2018 SP, Quirusillas 2019 FP and Quirusillas 2019 SP
Statistical Analysis of Blast Indices in the Diversity Panel Statistical analysis of blast indices in the diversity panel (Supplementary Data 1 and Table 1) indicated that the mean blast indices were relatively higher in the Quirusillas 2019 FP (38.5 ± 35.1), Quirusillas 2018 FP (32 ± 25.5) and Okinawa 2018 SP (31.4 ± 22.9) datasets
Summary
An emerging threat to wheat production that has the potential to cause substantial yield losses is the disease blast (Kohli et al, 2011; Islam et al, 2016; Chowdhury et al, 2017; Cruz and Valent, 2017; Sadat and Choi, 2017; Singh et al, 2021), caused by the fungus Magnaporthe oryzae pathotype Triticum Catt. (MoT) (anamorph Pyricularia oryzae Cavara) (Couch and Kohn, 2002; Tosa and Chuma, 2014; Zhang et al, 2016). The warm and humid climate at heading time during that year was a significant driver of the epidemic, as both high temperatures (between 25 and 30◦C) and long wetting periods favor blast development (Cardoso et al, 2008; Islam et al, 2019). Another major intercontinental jump of the MoT pathogen to Africa was recently reported, when blast was observed in the Muchinga province of Zambia during the 2017–2018 rainy season (Tembo et al, 2020). About seven million hectares of wheat growing regions in India, Pakistan and Bangladesh and some states in the United States (Louisiana, Mississippi and Florida) were identified to be vulnerable to blast outbreaks, given their similar favorable environmental conditions (Cruz et al, 2016a; Mottaleb et al, 2018; Valent et al, 2021), indicating that further spread of the disease is possible
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