Genome-wide association study identifies novel loci and candidate genes for rust resistance in wheat (Triticum aestivum L.).

BACKGROUND: Wheat rusts are important biotic stresses, development of rust resistant cultivars through molecular approaches is both economical and sustainable. Extensive phenotyping of large mapping populations under diverse production conditions and high-density genotyping would be the ideal strategy to identify major genomic regions for rust resistance in wheat. The genome-wide association study (GWAS) population of 280 genotypes was genotyped using a 35 K Axiom single nucleotide polymorphism (SNP) array and phenotyped at eight, 10, and, 10 environments, respectively for stem/black rust (SR), stripe/yellow rust (YR), and leaf/brown rust (LR). RESULTS: Forty-one Bonferroni corrected marker-trait associations (MTAs) were identified, including 17 for SR and 24 for YR. Ten stable MTAs and their best combinations were also identified. For YR, AX-94990952 on 1A + AX-95203560 on 4A + AX-94723806 on 3D + AX-95172478 on 1A showed the best combination with an average co-efficient of infection (ACI) score of 1.36. Similarly, for SR, AX-94883961 on 7B + AX-94843704 on 1B and AX-94883961 on 7B + AX-94580041 on 3D + AX-94843704 on 1B showed the best combination with an ACI score of around 9.0. The genotype PBW827 have the best MTA combinations for both YR and SR resistance. In silico study identifies key prospective candidate genes that are located within MTA regions. Further, the expression analysis revealed that 18 transcripts were upregulated to the tune of more than 1.5 folds including 19.36 folds (TraesCS3D02G519600) and 7.23 folds (TraesCS2D02G038900) under stress conditions compared to the control conditions. Furthermore, highly expressed genes in silico under stress conditions were analyzed to find out the potential links to the rust phenotype, and all four genes were found to be associated with the rust phenotype. CONCLUSION: The identified novel MTAs, particularly stable and highly expressed MTAs are valuable for further validation and subsequent application in wheat rust resistance breeding. The genotypes with favorable MTA combinations can be used as prospective donors to develop elite cultivars with YR and SR resistance.

AMMI and GGE biplot analysis of yield under terminal heat tolerance in wheat.

BACKGROUND: Wheat is an important cereal crop that helps to meet the food grain needs of people all over the world. Heat stress is one of the most significant abiotic stresses that wheat crops face during terminal growth stages in the wheat growing regions like India. It is very important to identify heat tolerant genotypes to be used as donors for breeding tolerant varieties. METHODS: Thirty-six wheat genotypes were evaluated under different sowing dates viz., Timely sown (TS), Late sown (LS) and very late sown (VLS), and the fourth was sown in the Temperature controlled phenotyping facility (TCPF) across two years. Genotypes were planted following lattice square design with two replications. Data was recorded for yield and yield contributing traits and analysed using selection indices as well AMMI and GGE biplot stability models. RESULTS: Heat stress affected all the traits under different heat environments which ranged from 1.6% (Spikelet number) to 37.2% (grain yield). Regression analysis indicated that the thousand grains weight (R2 = 0.50) contributed significantly towards grain yield under heat stress. Stress susceptibility index (SSI) found genotypes GW322, RAJ3765, Raj4037and MACS6145 as heat tolerant whereas, Stress Tolerance Index (STI) identified C306, HD2967, WH1080, WH730, DBW90, HD2932, DBW17, RAJ3765 as heat tolerant and high yielding. AMMI biplot analysis indicated stable genotypes DBW90, WH730, RAJ4083, CBW38, HD2932, NI5439, WR544, whereas GGE biplot analysis revealed stable genotypes NIAW34, NI5439, RAJ4083, DBW90, PBW590, Raj3765, HUW 510, WH730, HD2967 and UP2382. CONCLUSION: Heat stress affects significantly all yield contributing traits. Thousand grain weight was the most important trait that can be used as a selection criterion for selecting tolerant lines. Based on selection indices and both AMMI and GGE analysis, genotype RAJ3765 was identified to be highly heat tolerant with good grain yield.

Unveiling the Wheat Microbiome under Varied Agricultural Field Conditions.

Wheat being the important staple food crop plays a significant role in nutritional security. A wide variety of microbial communities beneficial to plants and contributing to plant health and production are found in the rhizosphere. The wheat microbiome encompasses an extensive variety of microbial species playing a key role in sustaining the physiology of the crop, nutrient uptake, and biotic/abiotic stress resilience. This report presents wheat microbiome analysis under six different farm practices, namely, organic (Org), timely sown (TS), wheat after pulse crop (WAPC), temperature-controlled phenotyping facility (TCPF), maize-wheat cropping system (MW), and residue burnt field (Bur), using 16S rRNA sequencing methodology. The soil samples collected from either side of the wheat row were mixed to get a final sample set for DNA extraction under each condition. After the data preprocessing, microbial community analysis was performed, followed by functional analysis and annotation. An abundance of the phylum Proteobacteria was observed, followed by Acidobacteria, Actinobacteria, and Gemmatimonadetes in the majority of the samples, while relative abundance was found to vary at the genus level. Analysis against the Carbohydrate-Active Enzymes (CAZy) database showed a high number of glycoside hydrolase genes in the TS, TCPF, and WAPC samples, while the Org, MW, and Bur samples predominantly had glycosyltransferase genes and carbohydrate esterase genes were in the lowest numbers. Also, the Org and TCPF samples showed lower diversity, while rare and abundant species ranged from 12 to 25% and 20 to 32% of the total bacterial species in all the sets, respectively. These variations indicate that the different cropping sequence had a significant impact on soil microbial diversity and community composition, which characterizes its economic and environmental value as a sustainable agricultural approach to maintaining food security and ecosystem health. IMPORTANCE This investigation examined the wheat microbiome under six different agricultural field conditions to understand the role of cropping pattern on soil microbial diversity. This study also elaborated the community composition, which has importance in economic (role of beneficial community leading to higher production) and environmental (role of microbial diversity/community in safeguarding the soil health, etc.) arenas. This could lead to a sustainable farming approach for food security and improved ecosystem health. Also, the majority of the microbes are unculturable; hence, technology-based microcultivation will be a potential approach for harnessing other cultured microorganisms, leading to unique species for commercial production. The outcome of this research-accelerated work can provide an idea to the scientists/breeders/agronomists/pathologists under the mentioned field conditions regarding their influence over their crops.

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 identification and expression analysis of sucrose nonfermenting-1-related protein kinase (SnRK) genes in Triticum aestivum in response to abiotic stress.

The SnRK gene family is a key regulator that plays an important role in plant stress response by phosphorylating the target protein to regulate subsequent signaling pathways. This study was aimed to perform a genome-wide analysis of the SnRK gene family in wheat and the expression profiling of SnRKs in response to abiotic stresses. An in silico analysis identified 174 SnRK genes, which were then categorized into three subgroups (SnRK1/2/3) on the basis of phylogenetic analyses and domain types. The gene intron-exon structure and protein-motif composition of SnRKs were similar within each subgroup but different amongst the groups. Gene duplication and synteny between the wheat and Arabidopsis genomes was also investigated in order to get insight into the evolutionary aspects of the TaSnRK family genes. The result of cis-acting element analysis showed that there were abundant stress- and hormone-related cis-elements in the promoter regions of 129 SnRK genes. Furthermore, quantitative real-time PCR data revealed that heat, salt and drought treatments enhanced TaSnRK2.11 expression, suggesting that it might be a candidate gene for abiotic stress tolerance. We also identified eight microRNAs targeting 16 TaSnRK genes which are playing important role across abiotic stresses and regulation in different pathways. These findings will aid in the functional characterization of TaSnRK genes for further research.

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.

GLADS: A gel-less approach for detection of STMS markers in wheat and rice.

Sequence tagged microsatellite site (STMS) are useful PCR based DNA markers. Wide genome coverage, high polymorphic index and co-dominant nature make STMS a preferred choice for marker assisted selection (MAS), genetic diversity analysis, linkage mapping, seed genetic purity analysis etc. Routine STMS analysis involving low-throughput, laborious and time-consuming polyacrylamide/agarose gels often limit their full utility in crop breeding experiments that involve large populations. Therefore, convenient, gel-less marker detection methods are highly desirable for STMS markers. The present study demonstrated the utility of SYBR Green dye based melt-profiling as a simple and convenient gel-less approach for detection of STMS markers (referred to as GLADS) in bread wheat and rice. The method involves use of SYBR Green dye during PCR amplification (or post-PCR) of STMS markers followed by generation of a melt-profile using controlled temperature ramp rate. The STMS amplicons yielded characteristic melt-profiles with differences in melting temperature (Tm) and profile shape. These characteristic features enabled melt-profile based detection and differentiation of STMS markers/alleles in a gel-less manner. The melt-profile approach allowed assessment of the specificity of the PCR assay unlike the end-point signal detection assays. The method also allowed multiplexing of two STMS markers with non-overlapping melt-profiles. In principle, the approach can be effectively used in any crop for STMS marker analysis. This SYBR Green melt-profiling based GLADS approach offers a convenient, low-cost (20-51%) and time-saving alternative for STMS marker detection that can reduce dependence on gel-based detection, and exposure to toxic chemicals.

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.

High Resolution Mapping of QTLs for Heat Tolerance in Rice Using a 5K SNP Array.

BACKGROUND: Heat stress is one of the major abiotic threats to rice production, next to drought and salinity stress. Incidence of heat stress at reproductive phase of the crop results in abnormal pollination leading to floret sterility, low seed set and poor grain quality. Identification of QTLs and causal genes for heat stress tolerance at flowering will facilitate breeding for improved heat tolerance in rice. In the present study, we used 272 F8 recombinant inbred lines derived from a cross between Nagina22, a well-known heat tolerant Aus cultivar and IR64, a heat sensitive popular Indica rice variety to map the QTLs for heat tolerance. RESULTS: To enable precise phenotyping for heat stress tolerance, we used a controlled phenotyping facility available at ICAR-Indian Institute of Wheat and Barley Research, Karnal, India. Based on 'days to 50% flowering' data of the RILs, we followed staggered sowing to synchronize flowering to impose heat stress at uniform stage. Using the Illumina infinium 5K SNP array for genotyping the parents and the RILs, and stress susceptibility and stress tolerance indices (SSI and STI) of percent spikelet sterility and yield per plant (g), we identified five QTLs on chromosomes 3, 5, 9 and 12. The identified QTLs explained phenotypic variation in the range of 6.27 to 21. 29%. Of these five QTLs, two high effect QTLs, one novel (qSTIPSS9.1) and one known (qSTIY5.1/qSSIY5.2), were mapped in less than 400 Kbp genomic regions, comprising of 65 and 54 genes, respectively. CONCLUSIONS: The present study identified two major QTLs for heat tolerance in rice in narrow physical intervals, which can be employed for crop improvement by marker assisted selection (MAS) after development of suitable scorable markers for breeding of high yielding heat tolerant rice varieties. This is the first report of a major QTL for heat tolerance on chromosome 9 of rice. Further, a known QTL for heat tolerance on chromosome 5 was narrowed down from 23 Mb to 331 Kbp in this study.

Draft Genome Sequence of Two Monosporidial Lines of the Karnal Bunt Fungus Tilletia indica Mitra (PSWKBGH-1 and PSWKBGH-2).

Karnal bunt disease caused by the fungus Tilletia indica Mitra is a serious concern due to strict quarantines affecting international trade of wheat. We announce here the first draft assembly of two monosporidial lines, PSWKBGH-1 and -2, of this fungus, having approximate sizes of 37.46 and 37.21 Mbp, respectively.

Mapping of stripe rust resistance QTL in Cappelle-Desprez × PBW343 RIL population effective in northern wheat belt of India.

Stripe rust caused by Puccinia striiformis f. sp. tritici is most important and devastating disease of wheat worldwide, which affects the grain yields, quality and nutrition. To elucidate, the genetic basis of resistance, a mapping population of recombinant inbred lines was developed from a cross between resistant Cappelle-Desprez and susceptible cultivar PBW343 using single-seed descent. Variety PBW343 had been one of the most popular cultivars of North Western Plains Zone, for more than a decade, before succumbing to the stripe rust. Cappelle-Desprez, a source of durable adult plant resistance, has maintained its resistance against stripe rust for a long time in Europe. Map construction and QTL analysis were completed with 1012 polymorphic (DArT and SSR) markers. Screenings for stripe rust disease were carried out in field condition for two consecutive crop seasons (2012-2013 and 2013-2014). Susceptible parent (PBW343) achieved a significant level of disease i.e., 100 % in both the years. In present investigations, resistance in Cappelle-Desprez was found stable and response to the rust ranged from 0 to 1.5 % over the years. The estimated broad-sense heritability (h 2) of stripe rust rAUDPC in the mapping population was 0.82. The relative area under the disease progress curve data showed continuous distributions, indicating that trait was controlled multigenically. Genomic region identified on chromosome 2D, was located within the short arm, with flanking markers (Xgwm484-Xcfd73), explained phenotypic variation (PVE) ranged from 13.9 to 31.8 %. The genomic region identified on chromosome 5B was found with the effect of maximum contribution with flanking DArT markers (1376633|F|0-1207571|F|0), PVE ranged from 24 to 27.0 %. This can, therefore, be utilized for marker assisted selection in developing much needed stripe rust resistant lines for the northern wheat belt of India.

Physiological traits associated with heat tolerance in bread wheat (Triticum aestivum L.).

Field experiments for evaluating heat tolerance-related physiological traits were conducted for two consecutive years using a mapping population of recombinant inbred lines (RILs) from the cross RAJ4014/WH730. Chlorophyll content (Chl) and chlorophyll fluorescence (CFL) were recorded under timely sown (TS) and late sown (LS) conditions. Late sowing exposes the terminal stage of plants to high temperature stress. Pooled analysis showed that CFL and Chl differed significantly under TS and LS conditions. The mean value of CFL (Fv/Fm) and Chl under both timely and late sown conditions were used as physiological traits for association with markers. Regression analysis revealed significant association of microsatellite markers viz., Xpsp3094 and Xgwm131 with coefficients of determination (R (2)) values for CFL (Fv/Fm) and Chl as 12 and 8 %, respectively. The correlation between thousand grain weight (TGW) with Chl and CFL were 14 and 7 % and correlation between grain wt./spike with Chl and CFL were 15 and 8 %, respectively. The genotypes showing tolerance to terminal heat stress as manifested by low heat susceptibility index (HSI = 0.43) for thousand grain weight, were also found having very low Chl, HSI (-0.52). These results suggest that these physiological traits may be used as a secondary character for screening heat-tolerant genotypes.

Deciphering the dynamics of changing proteins of tolerant and intolerant wheat seedlings subjected to heat stress.

Indulgence of heat defense mechanism is crucial to allay undesirable effects by developing significant heat tolerant plants. Translation of heat stress related genes into proteins is a key tolerance strategy tailored by plants. In order to understand the possible mechanisms of heat tolerance in wheat at proteomic level, two wheat genotypes (WH 730-heat tolerant; Raj 4014-heat intolerant) along with their 10 extreme recombinant inbred lines (RILs) were exposed to heat stress (35 °C for 6 h) to identify important stress related proteins. 2-DE coupled with MALDI TOF/TOF of wheat seedlings revealed 14 differentially regulated protein spots. Compared to Raj 4014, 3 proteins viz. Rubisco activase A, Con A and PEP carboxylase 1 were differentially regulated only in WH 730 implying their practical role in heat tolerance. Above and beyond, increased expression of cytochrome b6f complex and catalase in tolerant RIL population signifies their role in accelerated electron flow during heat stress to cope up with the stress. Our results suggests that, compared to intolerant parent and RILs, tolerant parent and RILs might be actively modulating protein involved in photosynthesis, signal transduction and defense which signifies the activation of adaptation mechanism under heat stress.