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Bread wheat (T. aestivum) is one of the world's most widely consumed cereals. Since micronutrient deficiencies are becoming more common among people who primarily depend upon cereal-based diets, a need for better-quality wheat varieties has been felt. An association panel of 154 T. aestivum lines was evaluated for the following quality traits: grain appearance (GA) score, grain hardness (GH), phenol reaction (PR) score, protein percent, sodium dodecyl sulfate (SDS) sedimentation value, and test weight (TWt). In addition, the panel was also phenotyped for grain yield and related traits such as days to heading, days to maturity, plant height, and thousand kernel weight for the year 2017-18 at the Borlaug Institute for South Asia (BISA) Ludhiana and Jabalpur sites. We performed a genome-wide association analysis on this panel using 18,351 genotyping-bysequencing (GBS) markers to find marker-trait associations for quality and grain yield-related traits. We detected 55 single nucleotide polymorphism (SNP) marker trait associations (MTAs) for quality-related traits on chromosomes 7B (10), 1A (9), 2A (8), 3B (6), 2B (5), 7A (4), and 1B (3), with 3A, 4A, and 6D, having two and the rest, 4B, 5A, 5B, and 1D, having one each. Additionally, 20 SNP MTAs were detected for yield-related traits based on a field experiment conducted in Ludhiana on 7D (4) and 4D (3) chromosomes, while 44 SNP MTAs were reported for Jabalpur on chromosomes 2D (6), 7A (5), 2A (4), and 4A (4). Utilizing these loci in marker-assisted selection will benefit from further validation studies for these loci to improve hexaploid wheat for better yield and grain quality [ABSTRACT FROM AUTHOR]

Significant yield losses in major cereal-growing regions around the world have been linked to cereal cyst nematodes (Heterodera spp.). Identifying and deploying natural sources of resistance is of utmost importance due to increasing concerns associated with chemical methods over the years. We screened 141 diverse wheat genotypes collected from pan-Indian wheat cultivation states for nematode resistance over two years, alongside two resistant (Raj MR1, W7984 (M6)) and two susceptible (WH147, Opata M85) checks. We performed genome-wide association analysis using four single-locus models (GLM, MLM, CMLM, and ECMLM) and three multi-locus models (Blink, FarmCPU, and MLMM). Single locus models identified nine significant MTAs (−log10 (P) > 3.0) on chromosomes 2A, 3B, and 4B whereas, multi-locus models identified 11 significant MTAs on chromosomes 1B, 2A, 3B, 3D and 4B. Single and multi-locus models identified nine common significant MTAs. Candidate gene analysis identified 33 genes like F-box-like domain superfamily, Cytochrome P450 superfamily, Leucine-rich repeat, cysteine-containing subtype Zinc finger RING/FYVE/PHD-type, etc., having a putative role in disease resistance. Such genetic resources can help to reduce the impact of this disease on wheat production. Additionally, these results can be used to design new strategies for controlling the spread of H. avenae, such as the development of resistant varieties or the use of resistant cultivars. Finally, the obtained results can also be used to identify new sources of resistance to this pathogen and develop novel control methods. [ABSTRACT FROM AUTHOR]

Background: During the last few decades, the diverse sources of resistance, several genes and QTLs for spot blotch resistance have been identified. However, a large set of germplasm lines are still unexplored that have the potential to develop highly resistant wheat cultivars for the target environments. Therefore, the identification of new sources of resistance to spot blotch is essential for breeding programmes to develop spot blotch resistant cultivars and sustain wheat production. The association mapping panel of 294 diverse bread wheat accessions was used to explore new sources of spot blotch disease resistance and to identify genomic regions using genome wide association analysis (GWAS). The genotypes were tested in replicated trials for spot blotch disease at three major hot spots in India (Varanasi in UP, Pusa in Bihar, and Cooch Behar in West Bengal). The area under the disease progress curve (AUDPC) was calculated to assess the level of resistance in each genotype. Results: A total of 19 highly and 76 moderately resistant lines were identified. Three accessions (EC664204, IC534306 and IC535188) were nearly immune to spot blotch disease. The genotyping of all accessions resulted in a total of 16,787 high-quality polymorphic SNPs. The GWAS was performed using a Compressed Mixed Linear Model (CMLM) and a Mixed Linear Model (MLM). A total of seven significant MTAs, common in both the models and consistent across the environment, were further validated to develop KASP markers. Four MTAs (AX-94710084, AX-94865722, AX-95135556, and AX-94529408) on three chromosomes (2AL, 2BL, and 3BL) have been successfully validated through the KASP marker. Conclusions: The new source of resistance was identified from unexplored germplasm lines. The genomic regions identified through GWAS were validated through KASP markers. The marker information and the highly resistant sources are valuable resources to rapidly develop immune or near immune wheat varieties. [ABSTRACT FROM AUTHOR]

Stripe rust poses a severe menace to wheat cultivation worldwide, occurring as the most devastating disease threatening global wheat industry. The use of resistance genes has been considered as an effective method for management of rust diseases. However, for most of yellow rust (Yr) genes, the molecular mechanisms and pathways responsible for resistance response against Puccinia striiformis (Pst) infection are not well understood. In this study, transcriptome analysis was conducted in two cultivars viz. PBW343 (susceptible) and FLW30 (resistant) to the pathotype 46S119 of Pst in India. The inoculation with Pst pathotype 46S119 was followed by leaf sample collection at different hours per inoculation (hpi) viz. 12, 48, and 72. The transcriptome analysis revealed a total of 18,482 differentially expressed genes (DEGs) across different time points. However, a set of 159 genes were identified to exhibit a genome-wide association with P ≤ 0.05 level of significance, which can be represented as Nominally Significant GWAS Geneset (NSGG). By utilizing Weighted Gene Co-expression Network Analysis (WGCNA), we identified 924 and 79 genes from the DEGs and NSGG dataset belonging to different modules. Functional validation of genes was done to confirm the transcriptional expression of four potential genes, including two hub genes associated with the defence mechanism against rust infection. [ABSTRACT FROM AUTHOR]