GWAS elucidated grain yield genetics in Indian spring wheat under diverse water conditions.

KEY MESSAGE: Underpinned natural variations and key genes associated with yield under different water regimes, and identified genomic signatures of genetic gain in the Indian wheat breeding program. A novel KASP marker for TKW under water stress was developed and validated. A comprehensive genome-wide association study was conducted on 300 spring wheat genotypes to elucidate the natural variations associated with grain yield and its eleven contributing traits under fully irrigated, restricted water, and simulated no water conditions. Utilizing the 35K Wheat Breeders' Array, we identified 1155 quantitative trait nucleotides (QTNs), with 207 QTNs exhibiting stability across diverse conditions. These QTNs were further delimited into 539 genomic regions using a genome-wide LD value of 3.0 Mbp, revealing pleiotropic control across traits and conditions. Sub-genome A was significantly associated with traits under irrigated conditions, while sub-genome B showed more QTNs under water stressed conditions. Favourable alleles with significantly associated QTNs were delineated, with a notable pyramiding effect for enhancing trait performance. Additionally, allele of only 921 QTNs significantly affected the population mean. Allele profiling highlighted C-306 as a most potential source of drought tolerance. Moreover, 762 genes overlapping significant QTNs were identified, narrowing down to 27 putative candidate genes overlapping 29 novel and functional SNPs expressing (≥ 0.5 tpm) relevance across various growth conditions. A new KASP assay was developed, targeting a gene TraesCS2A03G1123700 regulating thousand kernel weight under severe drought condition. Genomic selection models (GBLUP, BayesB, MxE, and R-Norm) demonstrated an average prediction accuracy of 0.06-0.58 across environments, indicating potential for trait selection. Retrospective analysis of the Indian wheat breeding program supported a genetic gain in GY at the rate of ca. 0.56% per breeding cycle, since 1960, supporting the identification of genomic signatures driving trait selection and genetic gain. These findings offer insight into improving the rate of genetic gain in wheat breeding programs globally.

Utilization of Grain Physical and Biochemical Traits to Predict Malting Quality of Barley (Hordeum vulgare L.) under Sub-Tropical Climate.

Barley is the most popular raw material for malting, and recently, the demand for malt-based products has increased several folds in India and other South Asian countries. The barley growing season is peculiar in the sub-tropical plains region compared to European or Northern American conditions, characterized by a total crop duration of 130-145 days with a maximum grain filling duration of around only 35-40 days. A total of 19 barley genotypes were grown for three years to assess the comparative performance in relation to different quality traits, including grain physical traits and biochemical and malt quality parameters. Analysis of variance, Pearson correlation, and principal component analysis were performed to determine the correlation among different traits. The results showed significant genotypic variation among genotypes for individual grain and malt traits. Despite the shorter window for grain filling, several good malting genotypes have been developed for the sub-tropical climates. The genotypes DWRUB52, DWRB101, RD2849, DWRUB64, and DWRB91 were found suitable for malting. Based on correlation studies, a few grain parameters have been identified which can be used to predict the malting potential of a barley genotype. The hot water extract was found to be positively correlated with the grain test weight, thousand-grain weight, and malt friability but was negatively correlated with the husk content. Beta-glucan content varied from 3.4 to 6.1% (dwb); reducing the grain beta-glucan content and increasing the amylase could be priorities to address in future malt barley improvement programs under sub-tropical climatic conditions.

RNA-Seq Analysis of Developing Grains of Wheat to Intrigue Into the Complex Molecular Mechanism of the Heat Stress Response.

Heat stress is one of the significant constraints affecting wheat production worldwide. To ensure food security for ever-increasing world population, improving wheat for heat stress tolerance is needed in the presently drifting climatic conditions. At the molecular level, heat stress tolerance in wheat is governed by a complex interplay of various heat stress-associated genes. We used a comparative transcriptome sequencing approach to study the effect of heat stress (5°C above ambient threshold temperature of 20°C) during grain filling stages in wheat genotype K7903 (Halna). At 7 DPA (days post-anthesis), heat stress treatment was given at four stages: 0, 24, 48, and 120 h. In total, 115,656 wheat genes were identified, including 309 differentially expressed genes (DEGs) involved in many critical processes, such as signal transduction, starch synthetic pathway, antioxidant pathway, and heat stress-responsive conserved and uncharacterized putative genes that play an essential role in maintaining the grain filling rate at the high temperature. A total of 98,412 Simple Sequences Repeats (SSR) were identified from de novo transcriptome assembly of wheat and validated. The miRNA target prediction from differential expressed genes was performed by psRNATarget server against 119 mature miRNA. Further, 107,107 variants including 80,936 Single nucleotide polymorphism (SNPs) and 26,171 insertion/deletion (Indels) were also identified in de novo transcriptome assembly of wheat and wheat genome Ensembl version 31. The present study enriches our understanding of known heat response mechanisms during the grain filling stage supported by discovery of novel transcripts, microsatellite markers, putative miRNA targets, and genetic variant. This enhances gene functions and regulators, paving the way for improved heat tolerance in wheat varieties, making them more suitable for production in the current climate change scenario.

GWAS to Identify Novel QTNs for WSCs Accumulation in Wheat Peduncle Under Different Water Regimes.

Water-soluble carbohydrates (WSCs) play a vital role in water stress avoidance and buffering wheat grain yield. However, the genetic architecture of stem WSCs' accumulation is partially understood, and few candidate genes are known. This study utilizes the compressed mixed linear model-based genome wide association study (GWAS) and heuristic post GWAS analyses to identify causative quantitative trait nucleotides (QTNs) and candidate genes for stem WSCs' content at 15 days after anthesis under different water regimes (irrigated, rainfed, and drought). Glucose, fructose, sucrose, fructans, total non-structural carbohydrates (the sum of individual sugars), total WSCs (anthrone based) quantified in the peduncle of 301 bread wheat genotypes under multiple environments (E01-E08) pertaining different water regimes, and 14,571 SNPs from "35K Axiom Wheat Breeders" Array were used for analysis. As a result, 570 significant nucleotide trait associations were identified on all chromosomes except for 4D, of which 163 were considered stable. A total of 112 quantitative trait nucleotide regions (QNRs) were identified of which 47 were presumable novel. QNRs qWSC-3B.2 and qWSC-7A.2 were identified as the hotspots. Post GWAS integration of multiple data resources prioritized 208 putative candidate genes delimited into 64 QNRs, which can be critical in understanding the genetic architecture of stem WSCs accumulation in wheat under optimum and water-stressed environments. At least 19 stable QTNs were found associated with 24 prioritized candidate genes. Clusters of fructans metabolic genes reported in the QNRs qWSC-4A.2 and qWSC-7A.2. These genes can be utilized to bring an optimum combination of various fructans metabolic genes to improve the accumulation and remobilization of stem WSCs and water stress tolerance. These results will further strengthen wheat breeding programs targeting sustainable wheat production under limited water conditions.

Genome-Wide Association Studies in Diverse Spring Wheat Panel for Stripe, Stem, and Leaf Rust Resistance.

Among several important wheat foliar diseases, Stripe rust (YR), Leaf rust (LR), and Stem rust (SR) have always been an issue of concern to the farmers and wheat breeders. Evolution of virulent pathotypes of these rusts has posed frequent threats to an epidemic. Pyramiding rust-resistant genes are the most economical and environment-friendly approach in postponing this inevitable threat. To achieve durable long term resistance against the three rusts, an attempt in this study was made searching for novel sources of resistant alleles in a panel of 483 spring wheat genotypes. This is a unique and comprehensive study where evaluation of a diverse panel comprising wheat germplasm from various categories and adapted to different wheat agro-climatic zones was challenged with 18 pathotypes of the three rusts with simultaneous screening in field conditions. The panel was genotyped using 35K SNP array and evaluated for each rust at two locations for two consecutive crop seasons. High heritability estimates of disease response were observed between environments for each rust type. A significant effect of population structure in the panel was visible in the disease response. Using a compressed mixed linear model approach, 25 genomic regions were found associated with resistance for at least two rusts. Out of these, seven were associated with all the three rusts on chromosome groups 1 and 6 along with 2B. For resistance against YR, LR, and SR, there were 16, 18, and 27 QTL (quantitative trait loci) identified respectively, associated at least in two out of four environments. Several of these regions got annotated with resistance associated genes viz. NB-LRR, E3-ubiquitin protein ligase, ABC transporter protein, etc. Alien introgressed (on 1B and 3D) and pleiotropic (on 7D) resistance genes were captured in seedling and adult plant disease responses, respectively. The present study demonstrates the use of genome-wide association for identification of a large number of favorable alleles for leaf, stripe, and stem rust resistance for broadening the genetic base. Quick conversion of these QTL into user-friendly markers will accelerate the deployment of these resistance loci in wheat breeding programs.

Characterization of genetic diversity and population structure in wheat using array based SNP markers.

Genetic diversity is crucial for successful adaptation and sustained improvement in crops. India is bestowed with diverse agro-climatic conditions which makes it rich in wheat germplasm adapted to various niches. Germplasm repository consists of local landraces, trait specific genetic stocks including introgressions from wild relatives, exotic collections, released varieties, and improved germplasm. Characterization of genetic diversity is done using morpho-physiological characters as well as by analyzing variations at DNA level. However, there are not many reports on array based high throughput SNP markers having characteristics of genome wide coverage employed in Indian spring wheat germplasm. Amongst wheat SNP arrays, 35K Axiom Wheat Breeder's Array has the highest SNP polymorphism efficiency suitable for genetic mapping and genetic diversity characterization. Therefore, genotyping was done using 35K in 483 wheat genotypes resulting in 14,650 quality filtered SNPs, that were distributed across the B (~ 50%), A (~ 39%), and D (~ 10%) genomes. The total genetic distance coverage was 4477.85 cM with 3.27 SNP/cM and 0.49 cM/SNP as average marker density and average inter-marker distance, respectively. The PIC ranged from 0.09 to 0.38 with an average of 0.29 across genomes. Population structure and Principal Coordinate Analysis resulted in two subpopulations (SP1 and SP2). The analysis of molecular variance revealed the genetic variation of 2% among and 98% within subpopulations indicating high gene flow between SP1 and SP2. The subpopulation SP2 showed high level of genetic diversity based on genetic diversity indices viz. Shannon's information index (I) = 0.648, expected heterozygosity (He) = 0.456 and unbiased expected heterozygosity (uHe) = 0.456. To the best of our knowledge, this study is the first to include the largest set of Indian wheat genotypes studied exclusively for genetic diversity. These findings may serve as a potential source for the identification of uncharacterized QTL/gene using genome wide association studies and marker assisted selection in wheat breeding programs.

RNAseq analysis reveals drought-responsive molecular pathways with candidate genes and putative molecular markers in root tissue of wheat.

Drought is one of the major impediments in wheat productivity. Traditional breeding and marker assisted QTL introgression had limited success. Available wheat genomic and RNA-seq data can decipher novel drought tolerance mechanisms with putative candidate gene and marker discovery. Drought is first sensed by root tissue but limited information is available about how roots respond to drought stress. In this view, two contrasting genotypes, namely, NI5439 41 (drought tolerant) and WL711 (drought susceptible) were used to generate ~78.2 GB data for the responses of wheat roots to drought. A total of 45139 DEGs, 13820 TF, 288 miRNAs, 640 pathways and 435829 putative markers were obtained. Study reveals use of such data in QTL to QTN refinement by analysis on two model drought-responsive QTLs on chromosome 3B in wheat roots possessing 18 differentially regulated genes with 190 sequence variants (173 SNPs and 17 InDels). Gene regulatory networks showed 69 hub-genes integrating ABA dependent and independent pathways controlling sensing of drought, root growth, uptake regulation, purine metabolism, thiamine metabolism and antibiotics pathways, stomatal closure and senescence. Eleven SSR markers were validated in a panel of 18 diverse wheat varieties. For effective future use of findings, web genomic resources were developed. We report RNA-Seq approach on wheat roots describing the drought response mechanisms under field drought conditions along with genomic resources, warranted in endeavour of wheat productivity.

Uncovering Genomic Regions Associated With 36 Agro-Morphological Traits in Indian Spring Wheat Using GWAS.

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 (-log10 P ≥ 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.

Development of species specific putative miRNA and its target prediction tool in wheat (Triticum aestivum L.).

MicroRNA are 20-24 nt, non-coding, single stranded molecule regulating traits and stress response. Tissue and time specific expression limits its detection, thus is major challenge in their discovery. Wheat has limited 119 miRNAs in MiRBase due to limitation of conservation based methodology where old and new miRNA genes gets excluded. This is due to origin of hexaploid wheat by three successive hybridization, older AA, BB and younger DD subgenome. Species specific miRNA prediction (SMIRP concept) based on 152 thermodynamic features of training dataset using support vector machine learning approach has improved prediction accuracy to 97.7%. This has been implemented in TamiRPred ( http://webtom.cabgrid.res.in/tamirpred ). We also report highest number of putative miRNA genes (4464) of wheat from whole genome sequence populated in database developed in PHP and MySQL. TamiRPred has predicted 2092 (>45.10%) additional miRNA which was not predicted by miRLocator. Predicted miRNAs have been validated by miRBase, small RNA libraries, secondary structure, degradome dataset, star miRNA and binding sites in wheat coding region. This tool can accelerate miRNA polymorphism discovery to be used in wheat trait improvement. Since it predicts chromosome-wise miRNA genes with their respective physical location thus can be transferred using linked SSR markers. This prediction approach can be used as model even in other polyploid crops.

Development of model web-server for crop variety identification using throughput SNP genotyping data.

Crop varieties or genotypes of a given species are pivotal for agricultural production and ownership, management and improvement of their germplasm is a great challenge. Its morphological identification requires time, cost and descriptors are often compromised statistically due to phenotypic plasticity. Development of DNA based signature of varieties can overcome these limitations. There is a global need to implement world trade organization (WTO) and intellectual property rights (IPR) guidelines of Plant Breeders Rights (PBR) where DUS (distinctness, uniformity and stability) testing can be supplemented by DNA profile. Universalization and minimization of SNP number without compromising identification accuracy is the major challenge in development of varietal profile by rapid genotype assay. Besides this, there is no server-based approach reducing computational skill with global accessibility of referral phenotypic and genotypic data. We report world's first model web server for crop variety identification using >350 Indian wheat varieties and Axiom 35 K SNP chip data. Standard filtering and linkage disequilibrium approach were used to develop varietal signature in Linux using HTML, Java, PHP and MySQL with provision of QR code generator to facilitate bar-coding. Phylogenetic tree constructed by selected SNPs confirms six major trait based clusters of varieties and their pedigree. Our user friendly server based tool, VISTa (Variety Identification System of Triticum aestivum) ( http://webtom.cabgrid.res.in/vista ) can be used in DUS testing having dispute resolution of sovereignty and access benefit sharing (ABS) issues. This model approach can be used in other crops with pan-global level management of crop germplasm in endeavour of crop productivity.

Putative Microsatellite DNA Marker-Based Wheat Genomic Resource for Varietal Improvement and Management.

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.

Hulless barley as a promising source to improve the nutritional quality of wheat products.

In this study, efforts were made to utilize hulless barley (variety BHS352) to enhance the nutritive value of chapatti and biscuit made from wheat flour. Barley flour was added to wheat flour in different ratios (5 to 30%). Antioxidant activity, total phenolic content and ß-glucan content were determined both in flour blends and their products. Changes in physical quality and taste of chapatti and biscuits after blending of hulless barley flour with wheat flour were measured. The chapatti quality score decreased by 15% and biscuit spread factor by 33% after 30% barley flour blending. Significant increase in ß-glucan content and antioxidant activity of flour blends and their products was observed at 30% blending level. The phenolic content increased from 63 to 135 µg for biscuits and 237 to 287 ug GAE/g for chapatti with blending of 30% barley flour.

Phenotyping at hot spots and tagging of QTLs conferring spot blotch resistance in bread wheat.

Spot blotch is a major foliar disease of wheat caused by Bipolaris sorokiniana in warm and humid environments of the world including South Asian countries. In India, it has a larger impact in Indo-Gangetic plains of the country. Therefore, the present study was undertaken to phenotype a mapping population at different hot spots of India and to detect quantitative trait loci (QTL) for resistance to spot blotch in wheat. For this study, 209 single seed descent (SSD) derived F8, F9, F10 recombinant inbred lines (RILs) of the cross 'Sonalika' (an Indian susceptible cultivar)/'BH 1146' (a Brazilian resistant cultivar) were assessed for spot blotch resistance at two hot spot locations (Coochbehar and Kalyani) for three years and for two years under controlled conditions in the polyhouse (Karnal). The population showed large variation in spot blotch reaction for disease severity in all the environments indicating polygenic nature of the disease. Microsatellite markers were used to create the linkage maps. Joint and/or individual year analysis by composite interval mapping (CIM) and likelihood of odds ratio (LOD) >2.1, detected two consistent QTLs mapped on chromosome 7BL and 7DL and these explained phenotypic variation of 11.4 percent and 9.5 percent over the years and locations, respectively. The resistance at these loci was contributed by the parent 'BH 1146' and shown to be independent of plant height and earliness. Besides, association of some agro-morphological traits has also been observed with percent disease severity. These identified genomic regions may be used in future wheat breeding programs through marker assisted selection for developing spot blotch resistant cultivars.

Differential Activity and Expression Profile of Antioxidant Enzymes and Physiological Changes in Wheat (Triticum aestivum L.) Under Drought.

Wheat crop may experience water deficit at crucial stages during its life cycle, which induces oxidative stress in the plants. The antioxidant status of the plant plays an important role in providing tolerance against the water stress. The objective of this study was to investigate the impact of water stress on physiological traits, antioxidant activity and transcript profile of antioxidant enzyme related genes in four wheat genotypes (C306, AKAW3717, HD2687, PBW343) at three crucial stages of plants under medium (75% of field capacity) and severe stress (45% of field capacity) in pots. Drought was applied by withholding water for 10 days at a particular growth stage viz. tillering, anthesis and 15 days after anthesis (15DAA). For physiological traits, a highly significant effect of water stress at a particular stage and genotypic variations for resistance to drought tolerance was observed. Under severe water stress, the malondialdehyde (MDA) content increased while the relative water content (RWC) and chlorophyll index decreased significantly in all the genotypes. The drought susceptibility index (DSI) of the genotypes varied from 0.18 to 1.9. The drought treatment at the tillering and anthesis stages was found more sensitive in terms of reduction in thousand grain weight (TGW) and grain yield. Antioxidant enzyme activities [superoxide dismutase (SOD) and peroxidase (POX)] increased with the decrease in osmotic potential in drought tolerant genotypes C306 and AKAW3717. Moreover, the transcript profile of Mn-SOD upregulated significantly and was consistent with the trend of the variation in SOD activity, which suggests that Mn-SOD might play an important role in drought tolerance.

Modeling and phylogeny analysis of bread wheat MnSOD.

Superoxide dismutase (SOD) acts as first line of defense against oxidative and genetic stress. Manganese superoxide dismutase (MnSOD), found in mitochondria or peroxisomes, contains Mn(III) at the active site. Therefore, it is of interest to study MnSOD from bread wheat (a grain crop). However, a structure model is not yet solved for bread wheat MnSOD. Hence, we describe the structure model of bread wheat MnSOD developed using homology model. The model provides molecular insight to metal binding molecular function towards the understanding of oxidative stress resistance in plants. The distinction of bread wheat (a monocot) MnSOD from dicots is also shown using phylogenetic analysis.

Analysis of simple sequence repeats (SSRs)dynamics in fungus Fusarium graminearum.

The abundance and inherent potential for variations in simple sequence repeats (SSRs) or microsatellites resulted in valuable source for genetic markers in eukaryotes. We describe the organization and abundance of SSRs in fungus Fusarium graminearum (causative agent for Fusarium head blight or head scab of wheat). We identified 1705 SSRs of various nucleotide repeat motifs in the sequence database of F. graminearum. It is observed that mononucleotide repeats (62%) were most abundant followed by di- (20%) and trinucleotide repeats (14%). It is noted that tetra-, penta- and hexanucleotide repeats accounted for only 4% of SSRs. The estimated frequency of Class I SSRs (perfect repeats ≥20 nucleotides) was one SSR per 124.5 kb, whereas the frequency of Class II (perfect repeats >10 nucleotides and ≫20 nucleotides) was one SSR per 25.6 kb. The dynamics of SSRs will be a powerful tool for taxonomic, phylogenetic, genome mapping and population genetic studies as SSR based markers show high levels of allelic variation, codominant inheritance and ease of analysis.

Mining and survey of simple sequence repeats in wheat rust Puccinia sp.

The abundance and inherent potential for extensive allelic variations in simple sequence repeats (SSRs) or microsatellites resulted in valuable source for genetic markers in eukaryotes. In this study, we analyzed and compared the abundance and organisation of SSR in the genome of two important fungal pathogens of wheat, brown or leaf rust (Puccinia triticina) and black or stem rust (Puccinia graminis f. sp. tritici). P. triticina genome with two fold genome size as compared to P. graminis tritici has lower relative abundance and SSR density. The distribution pattern of different SSR motifs provides the evidence of greater accumulation of dinucleotide followed by trinucleotide repeats. More than two-hundred different types of repeat motifs were observed in the genomes. The longest SSR motifs varied in both genomes and some of the repeat motifs are found in higher frequency. The information about survey of relative abundance, relative density, length and frequency of different repeat motifs in Puccinia sp. will be useful for developing SSR markers that could find several applications in analysis of fungal genome such as genetic diversity, population genetics, race identification and acquisition of new virulence.