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There is a significant yield reduction in the wheat crop as a result of different biotic and abiotic stresses, and changing climate, among them moisture deficit stress and leaf rust are the major ones affecting wheat worldwide. HD3086 is a high-yielding wheat variety that has been released for commercial cultivation under timely sown irrigated conditions in the Indo-Gangetic plains of India. Variety HD3086 provides a good, stable yield, and it is the choice of millions of farmers in India. It becomes susceptible to the most prevalent pathotypes 77-5 and 77-9 of Puccinia triticina (causing leaf rust) in the production environment and its potential yield cannot be realized under moisture deficit stress. The present study demonstrates the use of a marker-assisted back cross breeding approach to the successful transfer of leaf rust resistance gene Lr24 and QTLs linked to moisture deficit stress tolerance in the background of HD3086. The genotype HI1500 was used as a donor parent that possesses leaf rust-resistant gene Lr24, which confers resistance against the major pathotypes found in the production environment. It possesses inbuilt tolerance under abiotic stresses with superior quality traits. Foreground selection for gene Lr24 and moisture deficit stress tolerance QTLs linked to Canopy temperature (CT), Normal Differential Vegetation Index (NDVI) and Thousand Kernel Weight (TKW) in different generations of the backcrossing and selection. In BC2F2, foreground selection was carried out to identify homozygous lines based on the linked markers and were advanced following pedigree based phenotypic selection. The selected lines were evaluated against P. triticina pathotypes 77-5 and 77-9 under controlled conditions. Recurrent parent recovery of the selected lines ranged from 78-94%. The identified lines were evaluated for their tolerance to moisture stress under field conditions and their resistance to rust under artificial epiphytotic conditions for two years. In BC2F5 generation, eight positive lines for marker alleles were selected which showed resistance to leaf rust and recorded an improvement in component traits of moisture deficit stress tolerance such as CT, NDVI, TKW and yield compared to the recurrent parent HD3086. The derived line is named HD3471 and is nominated for national trials for testing and further release for commercial cultivation.

Spike fertility and associated traits are key factors in deciding the grain yield potential of wheat. Genome-wide association study (GWAS) interwoven with advanced post-GWAS analysis such as a genotype-phenotype network (geno-pheno network) for spike fertility, grain yield, and associated traits allow to identify of novel genomic regions and represents attractive targets for future marker-assisted wheat improvement programs. In this study, GWAS was performed on 200 diverse wheat genotypes using Breeders’ 35K Axiom array that led to the identification of 255 significant marker-trait associations (MTAs) (–log10P ≥ 3) for 15 metric traits phenotyped over three consecutive years. MTAs detected on chromosomes 3A, 3D, 5B, and 6A were most promising for spike fertility, grain yield, and associated traits. Furthermore, the geno-pheno network prioritised 11 significant MTAs that can be utilised as a minimal marker system for improving spike fertility and yield traits. In total, 119 MTAs were linked to 81 candidate genes encoding different types of functional proteins involved in various key pathways that affect the studied traits either way. Twenty-two novel loci were identified in present GWAS, twelve of which overlapped by candidate genes. These results were further validated by the gene expression analysis, Knetminer, and protein modelling. MTAs identified from this study hold promise for improving yield and related traits in wheat for continued genetic gain and in rapidly evolving artificial intelligence (AI) tools to apply in the breeding program.

Understanding the physiological mechanism of tolerance under stress conditions is an imperative aspect of the crop improvement programme. The role of plant hormones is well-established in abiotic stress tolerance. However, the information on the role of gibberellic acid (GA) in abiotic stress tolerance in late sown wheat is still not thoroughly explored. Thus, we aimed to investigate the role of endogenous GA3 level in stress tolerance in contrasting wheat cultivars, viz., temperature-tolerant (HD 2643 and DBW 14) and susceptible (HD 2189 and HD 2833) cultivars under timely and late sown conditions. We created the variation in endogenous GA3 level by exogenous spray of GA3 and its biosynthesis inhibitor paclobutrazol (PBZ). Tolerant genotypes had higher antioxidant enzyme activity, membrane stability, and photosynthesis rate, lower lipid peroxidase activity, and better growth and yield traits under late sown conditions attributed to H2O2 content. Application of PBZ escalated antioxidant enzymes activity and photosynthesis rate, and reduced the lipid peroxidation and ion leakage in stress, leading to improved thermotolerance. GA3 had a non-significant effect on antioxidant enzyme activity, lipid peroxidation, and membrane stability. However, GA3 application increased the test weight in HD 2643 and HD 2833 under timely and late sown conditions. GA3 upregulated GA biosynthesis and degradation pathway genes, and PBZ downregulated kaurene oxidase and GA2ox gene expression. GA3 also upregulated the expression of the cell expansins gene under both timely and late sown conditions. Exogenous GA3 did not increase thermotolerance but positively affected test weight and cell expansins gene expression. No direct relationship existed between endogenous GA3 content and stress tolerance traits, indicating that PBZ could have conferred thermotolerance through an alternative mechanism instead of inhibiting GA3biosynthesis.

Wheat variety PBW343, released in India in 1995, became the most widely grown cultivar in the country by the year 2000 owing to its wide adaptability and yield potential. It initially succumbed to leaf rust, and resistance genes Lr24 and Lr28 were transferred to PBW343. After an unbroken reign of about 10 years, the virulence against gene Yr27 made PBW343 susceptible to stripe rust. Owing to its wide adaptability and yield potential, PBW343 became the prime target for marker-assisted introgression of stripe rust resistance genes. The leaf rust-resistant versions formed the base for pyramiding stripe rust resistance genes Yr5, Yr10, Yr15, Yr17, and Yr70, in different introgression programs. Advanced breeding lines with different gene combinations, PBW665, PBW683, PBW698, and PBW703 were tested in national trials but could not be released as varieties. The genes from alien segments, Aegilops ventricosa (Lr37/Yr17/Sr38) and Aegilops umbellulata (Lr76/Yr70), were later pyramided in PBW343. Modified marker-assisted backcross breeding was performed, and 81.57% of the genetic background was recovered in one of the selected derivative lines, PBW723. This line was evaluated in coordinated national trials and was released for cultivation under timely sown irrigated conditions in the North Western Plain Zone of India. PBW723 yields an average of 58.0 qtl/ha in Punjab with high potential yields. The genes incorporated are susceptible to stripe rust individually, but PBW723 with both genes showed enhanced resistance. Three years post-release, PBW723 occupies approximately 8–9% of the cultivated area in the Punjab state. A regular inflow of diverse resistant genes, their rapid mobilization to most productive backgrounds, and keeping a close eye on pathogen evolution is essential to protect the overall progress for productivity and resistance in wheat breeding, thus helping breeders to keep pace with pathogen evolution.

Wheat genetic improvement by integration of advanced genomic technologies is one way of improving productivity. To facilitate the breeding of economically important traits in wheat, SNP loci and underlying candidate genes associated with the 36 agro-morphological traits were studied in a diverse panel of 404 genotypes. By using Breeders’ 35K Axiom array in a comprehensive genome-wide association study covering 4364.79 cM of the wheat genome and applying a compressed mixed linear model, a total of 146 SNPs (-log10P ≥ 4) were found associated with 23 traits out of 36 traits studied explaining 3.7–47.0% of phenotypic variance. To reveal this a subset of 260 genotypes was characterized phenotypically for six quantitative traits [days to heading (DTH), days to maturity (DTM), plant height (PH), spike length (SL), awn length (Awn_L), and leaf length (Leaf_L)] under five environments. Gene annotations mined ∼38 putative candidate genes which were confirmed using tissue and stage specific gene expression data from RNA Seq. We observed strong co-localized loci for four traits (glume pubescence, SL, PH, and awn color) on chromosome 1B (24.64 cM) annotated five putative candidate genes. This study led to the discovery of hitherto unreported loci for some less explored traits (such as leaf sheath wax, awn attitude, and glume pubescence) besides the refined chromosomal regions of known loci associated with the traits. This study provides valuable information of the genetic loci and their potential genes underlying the traits such as awn characters which are being considered as important contributors toward yield enhancement.

Wheat fulfills 20% of global caloric requirement. World needs 60% more wheat for 9 billion population by 2050 but climate change with increasing temperature is projected to affect wheat productivity adversely. Trait improvement and management of wheat germplasm requires genomic resource. Simple Sequence Repeats (SSRs) being highly polymorphic and ubiquitously distributed in the genome, can be a marker of choice but there is no structured marker database with options to generate primer pairs for genotyping on desired chromosome/physical location. Previously associated markers with different wheat trait are also not available in any database. Limitations of in vitro SSR discovery can be overcome by genome-wide in silico mining of SSR. Triticum aestivum SSR database (TaSSRDb) is an integrated online database with three-tier architecture, developed using PHP and MySQL and accessible at http://webtom.cabgrid.res.in/wheatssr/. For genotyping, Primer3 standalone code computes primers on user request. Chromosome-wise SSR calling for all the three sub genomes along with choice of motif types is provided in addition to the primer generation for desired marker. We report here a database of highest number of SSRs (476,169) from complex, hexaploid wheat genome (~17 GB) along with previously reported 268 SSR markers associated with 11 traits. Highest (116.93 SSRs/Mb) and lowest (74.57 SSRs/Mb) SSR densities were found on 2D and 3A chromosome, respectively. To obtain homozygous locus, e-PCR was done. Such 30 loci were randomly selected for PCR validation in panel of 18 wheat Advance Varietal Trial (AVT) lines. TaSSRDb can be a valuable genomic resource tool for linkage mapping, gene/QTL (Quantitative trait locus) discovery, diversity analysis, traceability and variety identification. Varietal specific profiling and differentiation can supplement DUS (Distinctiveness, Uniformity, and Stability) testing, EDV (Essentially Derived Variety)/IV (Initial Variety) disputes, seed purity and hybrid wheat testing. All these are required in germplasm management as well as also in the endeavor of wheat productivity.

Understanding the genetic architecture of drought stress tolerance in bread wheat at seedling and reproductive stages is crucial for developing drought-tolerant varieties. In the present study, 192 diverse wheat genotypes, a subset from the Wheat Associated Mapping Initiative (WAMI) panel, were evaluated at the seedling stage in a hydroponics system for chlorophyll content (CL), shoot length (SLT), shoot weight (SWT), root length (RLT), and root weight (RWT) under both drought and optimum conditions. Following that, a genome-wide association study (GWAS) was carried out using the phenotypic data recorded during the hydroponics experiment as well as data available from previously conducted multi-location field trials under optimal and drought stress conditions. The panel had previously been genotyped using the Infinium iSelect 90K SNP array with 26,814 polymorphic markers. Using single as well as multi-locus models, GWAS identified 94 significant marker-trait associations (MTAs) or SNPs associated with traits recorded at the seedling stage and 451 for traits recorded at the reproductive stage. The significant SNPs included several novel, significant, and promising MTAs for different traits. The average LD decay distance for the whole genome was approximately 0.48 Mbp, ranging from 0.07 Mbp (chromosome 6D) to 4.14 Mbp (chromosome 2A). Furthermore, several promising SNPs revealed significant differences among haplotypes for traits such as RLT, RWT, SLT, SWT, and GY under drought stress. Functional annotation and in silico expression analysis revealed important putative candidate genes underlying the identified stable genomic regions such as protein kinases, O-methyltransferases, GroES-like superfamily proteins, NAD-dependent dehydratases, etc. The findings of the present study may be useful for improving yield potential, and stability under drought stress conditions.