Identification of Genomic Regions and Sources for Wheat Blast Resistance through GWAS in Indian Wheat Genotypes.

Wheat blast (WB) is a devastating fungal disease that has recently spread to Bangladesh and poses a threat to the wheat production in India, which is the second-largest wheat producing country in the world. In this study, 350 Indian wheat genotypes were evaluated for WB resistance in 12 field experiments in three different locations, namely Jashore in Bangladesh and Quirusillas and Okinawa in Bolivia. Single nucleotide polymorphisms (SNPs) across the genome were obtained using DArTseq® technology, and 7554 filtered SNP markers were selected for a genome-wide association study (GWAS). All the three GWAS approaches used identified the 2NS translocation as the only major source of resistance, explaining up to 32% of the phenotypic variation. Additional marker-trait associations were located on chromosomes 2B, 3B, 4D, 5A and 7A, and the combined effect of three SNPs (2B_180938790, 7A_752501634 and 5A_618682953) showed better resistance, indicating their additive effects on WB resistance. Among the 298 bread wheat genotypes, 89 (29.9%) carried the 2NS translocation, the majority of which (60 genotypes) were CIMMYT introductions, and 29 were from India. The 2NS carriers with a grand mean WB index of 6.6 showed higher blast resistance compared to the non-2NS genotypes with a mean index of 46.5. Of the 52 durum wheats, only one genotype, HI 8819, had the 2NS translocation and was the most resistant, with a grand mean WB index of 0.93. Our study suggests that the 2NS translocation is the only major resistance source in the Indian wheat panel analysed and emphasizes the urgent need to identify novel non-2NS resistance sources and genomic regions.

Genetic dissection for head blast resistance in wheat using two mapping populations.

Wheat head blast is a dangerous fungal disease in South America and has recently spread to Bangladesh and Zambia, threatening wheat production in those regions. Host resistance as an economical and environment-friendly management strategy has been heavily relied on, and understanding the resistance loci in the wheat genome is very helpful to resistance breeding. In the current study, two recombinant inbred line (RIL) populations, Alondra/Milan (with 296 RILs) and Caninde#2/Milan-S (with 254 RILs and Milan-S being a susceptible variant of Milan), were used for mapping QTL associated with head blast resistance in field experiments. Phenotyping was conducted in Quirusillas and Okinawa, Bolivia, and in Jashore, Bangladesh, during the 2017-18 and 2018-19 cropping cycles. The DArTseq® technology was employed to genotype the lines, along with four STS markers in the 2NS region. A QTL with consistent major effects was mapped on the 2NS/2AS translocation region in both populations, explaining phenotypic variation from 16.7 to 79.4% across experiments. Additional QTL were detected on chromosomes 2DL, 7AL, and 7DS in the Alondra/Milan population, and 2BS, 4AL, 5AS, 5DL, 7AS, and 7AL in the Caninde#2/Milan-S population, all showing phenotypic effects <10%. The results corroborated the important role of the 2NS/2AS translocation on WB resistance and identified a few novel QTL for possible deployment in wheat breeding. The low phenotypic effects of the non-2NS QTL warrantee further investigation for novel QTL with higher and more stable effects against WB, to alleviate the heavy reliance on 2NS-based resistance.

New Genotypes and Genomic Regions for Resistance to Wheat Blast in South Asian Germplasm.

Wheat blast (WB) disease, since its first identification in Bangladesh in 2016, is now an established serious threat to wheat production in South Asia. There is a need for sound knowledge about resistance sources and associated genomic regions to assist breeding programs. Hence, a panel of genotypes from India and Bangladesh was evaluated for wheat blast resistance and a genome-wide association study (GWAS) was performed. Disease evaluation was done during five crop seasons-at precision phenotyping platform (PPPs) for wheat blast disease at Jashore (2018-19), Quirusillas (2018-19 and 2019-20) and Okinawa (2019 and 2020). Single nucleotide polymorphisms (SNP) across the genome were obtained using DArTseq genotyping-by-sequencing platform, and in total 5713 filtered markers were used. GWAS revealed 40 significant markers associated with WB resistance, of which 33 (82.5%) were in the 2NS/2AS chromosome segment and one each on seven chromosomes (3B, 3D, 4A, 5A, 5D, 6A and 6B). The 2NS markers contributed significantly in most of the environments, explaining an average of 33.4% of the phenotypic variation. Overall, 22.4% of the germplasm carried 2NS/2AS segment. So far, 2NS translocation is the only effective WB resistance source being used in the breeding programs of South Asia. Nevertheless, the identification of non-2NS/2AS genomic regions for WB resistance provides a hope to broaden and diversify resistance for this disease in years to come.

Screening and Mapping for Head Blast Resistance in a Panel of CIMMYT and South Asian Bread Wheat Germplasm.

Wheat blast (WB) is a destructive disease in South America and its first outbreak in Bangladesh in 2016 posed a great risk to food security of South Asian countries. A genome wide association study (GWAS) was conducted on a diverse panel of 184 wheat genotypes from South Asia and CIMMYT. Phenotyping was conducted in eight field experiments in Bolivia and Bangladesh and a greenhouse experiment in the United States. Genotypic data included 11,401 SNP markers of the Illumina Infinium 15K BeadChip and four additional STS markers on the 2NS/2AS translocation region. Accessions with stable WB resistance across experiments were identified, which were all 2NS carriers. Nevertheless, a dozen moderately resistant 2AS lines were identified, exhibiting big variation among experiments. Significant marker-trait associations (MTA) were detected on chromosomes 1BS, 2AS, 6BS, and 7BL; but only MTAs on 2AS at the 2NS/2AS translocation region were consistently significant across experiments. The resistant accessions identified in this study could be used in production in South Asian countries as a preemptive strategy to prevent WB outbreak.

Genomic Selection for Wheat Blast in a Diversity Panel, Breeding Panel and Full-Sibs Panel.

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.

Genome-wide association mapping for wheat blast resistance in CIMMYT's international screening nurseries evaluated in Bolivia and Bangladesh.

Wheat blast caused by the fungus Magnaporthe oryzae pathotype Triticum (MoT) is an emerging threat to wheat production. To identify genomic regions associated with blast resistance against MoT isolates in Bolivia and Bangladesh, we performed a large genome-wide association mapping study using 8607 observations on 1106 lines from the International Maize and Wheat Improvement Centre's International Bread Wheat Screening Nurseries (IBWSNs) and Semi-Arid Wheat Screening Nurseries (SAWSNs). We identified 36 significant markers on chromosomes 2AS, 3BL, 4AL and 7BL with consistent effects across panels or site-years, including 20 markers that were significant in all the 49 datasets and tagged the 2NS translocation from Aegilops ventricosa. The mean blast index of lines with and without the 2NS translocation was 2.7 ± 4.5 and 53.3 ± 15.9, respectively, that substantiates its strong effect on blast resistance. Furthermore, we fingerprinted a large panel of 4143 lines for the 2NS translocation that provided excellent insights into its frequency over years and indicated its presence in 94.1 and 93.7% of lines in the 2019 IBWSN and SAWSN, respectively. Overall, this study reinforces the effectiveness of the 2NS translocation for blast resistance and emphasizes the urgent need to identify novel non-2NS sources of blast resistance.

QTL mapping for field resistance to wheat blast in the Caninde#1/Alondra population.

KEY MESSAGE: Wheat blast resistance in Caninde#1 is controlled by a major QTL on 2NS/2AS translocation and multiple minor QTL in an additive mode. Wheat blast (WB) is a devastating disease in South America, and it recently also emerged in Bangladesh. Host resistance to WB has relied heavily on the 2NS/2AS translocation, but the responsible QTL has not been mapped and its phenotypic effects in different environments have not been reported. In the current study, a recombinant inbred line population with 298 progenies was generated, with the female and male parents being Caninde#1 (with 2NS) and Alondra (without 2NS), respectively. Phenotyping was carried out in two locations in Bolivia, namely Quirusillas and Okinawa, and one location in Bangladesh, Jashore, with two sowing dates in each of the two cropping seasons in each location, during the years 2017-2019. Genotyping was performed with the DArTseq® technology along with five previously reported STS markers in the 2NS region. QTL mapping identified a major and consistent QTL on 2NS/2AS region, explaining between 22.4 and 50.1% of the phenotypic variation in different environments. Additional QTL were detected on chromosomes 1AS, 2BL, 3AL, 4BS, 4DL and 7BS, all additive to the 2NS QTL and showing phenotypic effects less than 10%. Two codominant STS markers, WGGB156 and WGGB159, were linked proximally to the 2NS/2AS QTL with a genetic distance of 0.9 cM, being potentially useful in marker-assisted selection.

Improving grain yield, stress resilience and quality of bread wheat using large-scale genomics.

Bread wheat improvement using genomic tools is essential for accelerating trait genetic gains. Here we report the genomic predictabilities of 35 key traits and demonstrate the potential of genomic selection for wheat end-use quality. We also performed a large genome-wide association study that identified several significant marker-trait associations for 50 traits evaluated in South Asia, Africa and the Americas. Furthermore, we built a reference wheat genotype-phenotype map, explored allele frequency dynamics over time and fingerprinted 44,624 wheat lines for trait-associated markers, generating over 7.6 million data points, which together will provide a valuable resource to the wheat community for enhancing productivity and stress resilience.

Mapping quantitative trait loci for quality factors in an inter-class cross of US and Chinese wheat.

Wheat quality factors are critical in determining the suitability of wheat (Triticum aestivum L.) for end-use product and economic value, and they are prime targets for marker-assisted selection. Objectives of this study were to identify quantitative trait loci (QTLs) that ultimately influence wheat market class and milling quality. A population of 132 F(12) recombinant inbred lines (RILs) was derived by single-seed descent from a cross between the Chinese hard wheat line Ning7840 and the soft wheat cultivar Clark and grown at three Oklahoma locations from 2001 to 2003. Milling factors such as test weight (volumetric grain weight, TW), kernel weight (KW), and kernel diameter (KD) and market class factors such as wheat grain protein content (GPC) and kernel hardness index (HI) were characterized on the basis of a genetic map constructed from 367 SSR and 241 AFLP markers covering all 21 chromosomes. Composite interval mapping identified eight QTLs for TW, seven for KW, six for KD, two each for GPC and HI measured by near-infrared reflectance (NIR) spectroscopy, and four for HI measured by single kernel characterization system. Positive phenotypic correlations were found among milling factors. Consistent co-localized QTLs were identified for TW, KW, and KD on the short arms of chromosomes 5A and 6A. A common QTL was identified for TW and KD on the long arm of chromosome 5A. A consistent major QTL for HI peaked at the Pinb-D1 locus on the short arm of chromosome 5D and explained up to 85% of the phenotypic variation for hardness. We identified QTLs for GPC on 4B and the short arm of 3A chromosomes. The consistency of quality factor QTLs across environments reveals their potential for marker-assisted selection.