Felix Marza

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.

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.

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.

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.

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.

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.

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 F₁₂ 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.

Grain yield and associated agronomic traits are important factors in wheat (Triticum aestivum L.) improvement. Knowledge regarding the number, genomic location, and effect of quantitative trait loci (QTL) would facilitate marker-assisted selection and the development of cultivars with desirable characteristics. Our objectives were to identify QTLs directly and indirectly affecting grain yield expression. A population of 132 F₁₂ recombinant inbred lines (RILs) was derived by single-seed descent from a cross between the Chinese facultative wheat Ning7840 and the US soft red winter wheat Clark. Phenotypic data were collected for 15 yield and other agronomic traits in the RILs and parental lines from three locations in Oklahoma from 2001 to 2003. Twenty-nine linkage groups, consisting of 363 AFLP and 47 SSR markers, were identified. Using composite interval mapping (CIM) analysis, 10, 16, 30, and 14 QTLs were detected for yield, yield components, plant adaptation (shattering and lodging resistance, heading date, and plant height), and spike morphology traits, respectively. The QTL effects ranged from 7 to 23%. Marker alleles from Clark were associated with a positive effect for the majority of QTLs for yield and yield components, but gene dispersion was the rule rather than the exception for this RIL population. Often, QTLs were detected in proximal positions for different traits. Consistent, co-localized QTLs were identified in linkage groups 1AL, 1B, 4B, 5A, 6A, and 7A, and less consistent but unique QTLs were identified on 2BL, 2BS, 2DL, and 6B. Results of this study provide a benchmark for future efforts on QTL identification for yield traits.