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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]

Cereal cyst nematode (CCN) is a major threat to cereal crop production globally including wheat (Triticum aestivum L.). In the present study, single-locus and multi-locus models of Genome-Wide Association Study (GWAS) were used to find marker trait associations (MTAs) against CCN (Heterodera avenae) in wheat. In total, 180 wheat accessions (100 spring and 80 winter types) were screened against H. avenae in two independent years (2018/2019 "Environment 1" and 2019/2020 "Environment 2") under controlled conditions. A set of 12,908 SNP markers were used to perform the GWAS. Altogether, 11 significant MTAs, with threshold value of −log10 (p-values) ≥ 3.0, were detected using 180 wheat accessions under combined environment (CE). A novel MTA (wsnp_Ex_c53387_56641291) was detected under all environments (E1, E2 and CE) and considered to be stable MTA. Among the identified 11 MTAs, eight were novel and three were co-localized with previously known genes/QTLs/MTAs. In total, 13 putative candidate genes showing differential expression in roots, and known to be involved in plant defense mechanisms were reported. These MTAs could help us to identify resistance alleles from new sources, which could be used to identify wheat varieties with enhanced CCN resistance. [ABSTRACT FROM AUTHOR]

During the last three decades, QTL analysis in wheat has been conducted for a variety of individual traits, so that thousands of QTL along with the linked markers, their genetic positions and contribution to phenotypic variation (PV) for concerned traits are now known. However, no exhaustive database for wheat QTL is currently available at a single platform. Therefore, the present database was prepared which is an exhaustive information resource for wheat QTL data from the published literature till May, 2020. QTL data from both interval mapping and genome-wide association studies (GWAS) have been included for the following classes of traits: (i) morphological traits, (ii) N and P use efficiency, (iii) traits for biofortification (Fe, K, Se, and Zn contents), (iv) tolerance to abiotic stresses including drought, water logging, heat stress, pre-harvest sprouting and salinity, (v) resistance to biotic stresses including those due to bacterial, fungal, nematode and insects, (vi) quality traits, and (vii) a variety of physiological traits, (viii) developmental traits, and (ix) yield and its related traits. For the preparation of the database, literature was searched for data on QTL/marker-trait associations (MTAs), curated and then assembled in the form of WheatQTLdb. The available information on metaQTL, epistatic QTL and candidate genes, wherever available, is also included in the database. Information on QTL in this WheatQTLdb includes QTL names, traits, associated markers, parental genotypes, crosses/mapping populations, association mapping panels and other useful information. To our knowledge, WheatQTLdb prepared by us is the largest collection of QTL (11,552), epistatic QTL (107) and metaQTL (330) data for hexaploid wheat to be used by geneticists and plant breeders for further studies involving fine mapping, cloning, and marker-assisted selection (MAS) during wheat breeding. [ABSTRACT FROM AUTHOR]

Root lesion nematode (RLN; Pratylenchus thornei) causes extensive yield losses in wheat worldwide and thus pose serious threat to global food security. Reliance on fumigants (such as methyl bromide) and nematicides for crop protection has been discouraged due to environmental concerns. Hence, alternative environment friendly control measures like finding and deployment of resistance genes against Pratylenchus thornei are of significant importance. In the present study, genome-wide association study (GWAS) was performed using single-locus and multi-locus methods. In total, 143 wheat genotypes collected from pan-Indian wheat cultivation states were used for nematode screening. Genotypic data consisted of > 7K SNPs with known genetic positions on the high-density consensus map was used for association analysis. Principal component analysis indicated the existence of sub-populations with no major structuring of populations due to the origin. Altogether, 25 significant marker trait associations were detected with − log10 (p value) > 4.0. Three large linkage disequilibrium blocks and the corresponding haplotypes were found to be associated with significant SNPs. In total, 37 candidate genes with nine genes having a putative role in disease resistance (F-box-like domain superfamily, Leucine-rich repeat, cysteine-containing subtype, Cytochrome P450 superfamily, Zinc finger C2H2-type, RING/FYVE/PHD-type, etc.) were identified. Genomic selection was conducted to investigate how well one could predict the phenotype of the nematode count without performing the screening experiments. Prediction value of r = 0.40 to 0.44 was observed when 56 to 70% of the population was used as a training set. This is the first report where GWAS has been conducted to find resistance against root lesion nematode (P. thornei) in Indian wheat germplasm. [ABSTRACT FROM AUTHOR]