Identification of marker trait association is a prerequisite for marker-assisted breeding. To find markers linked with traits under heat and drought stress in bread wheat (Triticum aestivum L.), we performed a genome-wide association study (GWAS). GWAS mapping panel used in this study consists of advanced breeding lines from the IARI stress breeding programme produced by pairwise and complex crosses. Phenotyping was done at multi locations namely New Delhi, Karnal, Indore, Jharkhand and Pune with augmented-RCBD design under different moisture and heat stress regimes, namely timely sown irrigated (IR), timely sown restricted irrigated (RI) and late sown (LS) conditions. Yield and its component traits, viz., Days to Heading (DH), Days to Maturity (DM), Normalized Difference Vegetation Index (NDVI), Chlorophyll Content (SPAD), Canopy temperature (CT), Plant Height (PH), Thousand grain weight (TGW), Grain weight per spike (GWPS), Plot Yield (PLTY) and Biomass (BMS) were phenotyped. Analysis of variance and descriptive statistics revealed significant differences among the studied traits. Genotyping was done using the 35k SNP Wheat Breeder's Genotyping Array. Population structure and diversity analysis using filtered 10,546 markers revealed two subpopulations with sufficient diversity. A large whole genome LD block size of 7.15 MB was obtained at half LD decay value. Genome-wide association search identified 57 unique markers associated with various traits across the locations. Twenty-three markers were identified to be stable, among them nine pleiotropic markers were also identified. In silico search of the identified markers against the IWGSC ref genome revealed the presence of a majority of the SNPs at or near the gene coding region. These SNPs can be used for marker-assisted transfer of genes/QTLs after validation to develop climate-resilient cultivars.

Genetic biofortification is recognized as a cost-effective and sustainable strategy to reduce micronutrient malnutrition. Genomic regions governing grain iron concentration (GFeC), grain zinc concentration (GZnC), and thousand kernel weight (TKW) were investigated in a set of 280 diverse bread wheat genotypes. The genome-wide association (GWAS) panel was genotyped using 35 K Axiom Array and phenotyped in five environments. The GWAS analysis showed a total of 17 Bonferroni-corrected marker-trait associations (MTAs) in nine chromosomes representing all the three wheat subgenomes. The TKW showed the highest MTAs (7), followed by GZnC (5) and GFeC (5). Furthermore, 14 MTAs were identified with more than 10% phenotypic variation. One stable MTA i.e. AX-95025823 was identified for TKW in both E4 and E5 environments along with pooled data, which is located at 68.9 Mb on 6A chromosome. In silico analysis revealed that the SNPs were located on important putative candidate genes such as Multi antimicrobial extrusion protein, F-box domain, Late embryogenesis abundant protein, LEA-18, Leucine-rich repeat domain superfamily, and C3H4 type zinc finger protein, involved in iron translocation, iron and zinc homeostasis, and grain size modifications. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection. The identified SNPs will be valuable in the rapid development of biofortified wheat varieties to ameliorate the malnutrition problems.

Genomic regions governing days to heading (DH), grain filling duration (GFD), grain number per spike (GNPS), grain weight per spike (GWPS), plant height (PH), and grain yield (GY) were investigated in a set of 280 diverse bread wheat genotypes. The genome-wide association studies (GWAS) panel was genotyped using a 35K Axiom Array and phenotyped in five environments. The GWAS analysis showed a total of 27 Bonferroni-corrected marker-trait associations (MTAs) on 15 chromosomes representing all three wheat subgenomes. The GFD showed the highest MTAs (8), followed by GWPS (7), GY (4), GNPS (3), PH (3), and DH (2). Furthermore, 20 MTAs were identified with more than 10% phenotypic variation. A total of five stable MTAs (AX-95024590, AX-94425015, AX-95210025 AX-94539354, and AX-94978133) were identified in more than one environment and associated with the expression of DH, GFD, GNPS, and GY. Similarly, two novel pleiotropic genomic regions with associated MTAs i.e. AX-94978133 (4D) and AX-94539354 (6A) harboring co-localized QTLs governing two or more traits were also identified. In silico analysis revealed that the SNPs were located on important putative candidate genes such as F-box-like domain superfamily, Lateral organ boundaries, LOB, Thioredoxin-like superfamily Glutathione S-transferase, RNA-binding domain superfamily, UDP-glycosyltransferase family, Serine/threonine-protein kinase, Expansin, Patatin, Exocyst complex component Exo70, DUF1618 domain, Protein kinase domain involved in the regulation of grain size, grain number, growth and development, grain filling duration, and abiotic stress tolerance. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection (MAS).

IntroductionWheat is grown and consumed worldwide, making it an important staple food crop for both its calorific and nutritional content. In places where wheat is used as a staple food, suboptimal micronutrient content levels, especially of grain iron (Fe) and zinc (Zn), can lead to malnutrition. Grain nutrient content is influenced by abiotic stresses, such as drought and heat stress. The best method for addressing micronutrient deficiencies is the biofortification of food crops. The prerequisites for marker-assisted varietal development are the identification of the genomic region responsible for high grain iron and zinc contents and an understanding of their genetics.MethodsA total of 193 diverse wheat genotypes were evaluated under drought and heat stress conditions across the years at the Indian Agricultural Research Institute (IARI), New Delhi, under timely sown irrigated (IR), restricted irrigated (RI) and late sown (LS) conditions. Grain iron content (GFeC) and grain zinc content (GZnC) were estimated from both the control and treatment groups. Genotyping of all the lines under study was carried out with the single nucleotide polymorphisms (SNPs) from Breeder’s 35K Axiom Array.Result and DiscussionThree subgroups were observed in the association panel based on both principal component analysis (PCA) and dendrogram analysis. A large whole-genome linkage disequilibrium (LD) block size of 3.49 Mb was observed. A genome-wide association study identified 16 unique stringent marker trait associations for GFeC, GZnC, and 1000-grain weight (TGW). In silico analysis demonstrated the presence of 28 potential candidate genes in the flanking region of 16 linked SNPs, such as synaptotagmin-like mitochondrial-lipid-binding domain, HAUS augmin-like complex, di-copper center-containing domain, protein kinase, chaperonin Cpn60, zinc finger, NUDIX hydrolase, etc. Expression levels of these genes in vegetative tissues and grain were also found. Utilization of identified markers in marker-assisted breeding may lead to the rapid development of biofortified wheat genotypes to combat malnutrition.

Biofortification is gaining importance globally to improve human nutrition through enhancing the micronutrient content, such as vitamin A, iron, and zinc, in staple food crops. The present study aims to identify the chromosomal regions governing the grain iron concentration (GFeC), grain zinc concentration (GZnC), and thousand kernel weight (TKW) using recombinant inbred lines (RILs) in wheat, developed from a cross between HD3086 and HI1500. The experiment was conducted in four different production conditions at Delhi viz., control, drought, heat, and combined heat and drought stress and at Indore under drought stress. Grain iron and zinc content increased under heat and combined stress conditions, while thousand kernel weight decreased. Medium to high heritability with a moderate correlation between grain iron and zinc was observed. Out of 4,106 polymorphic markers between the parents, 3,407 SNP markers were used for linkage map construction which spanned over a length of 14791.18 cm. QTL analysis identified a total of 32 chromosomal regions governing the traits under study, which includes 9, 11, and 12 QTLs for GFeC, GZnC, and TKW, respectively. A QTL hotspot was identified on chromosome 4B which is associated with grain iron, grain zinc, and thousand kernel weight explaining the phenotypic variance of 29.28, 10.98, and 17.53%, respectively. Similarly, common loci were identified on chromosomes 4B and 4D for grain iron, zinc, and thousand kernel weight. In silico analysis of these chromosomal regions identified putative candidate genes that code for proteins such as Inositol 1,3,4-trisphosphate 5/6-kinase, P-loop containing nucleoside triphosphate hydrolase, Pleckstrin homology (PH) domains, Serine-threonine/tyrosine-protein kinase and F-box-like domain superfamily proteins which play role in many important biochemical or physiological process. The identified markers linked to QTLs can be used in MAS once successfully validated.