Delineation of loci governing an extra-earliness trait in lentil (Lens culinaris Medik.) using the QTL-Seq approach.

Developing early maturing lentil has the potential to minimize yield losses, mainly during terminal drought. Whole-genome resequencing (WGRS) based QTL-seq identified the loci governing earliness in lentil. The genetic analysis for maturity duration provided a good fit to 3:1 segregation (F2), indicating earliness as a recessive trait. WGRS of Globe Mutant (late parent), late-flowering, and early-flowering bulks (from RILs) has generated 1124.57, 1052.24 million raw and clean reads, respectively. The QTL-Seq identified three QTLs (LcqDTF3.1, LcqDTF3.2, and LcqDTF3.3) on chromosome 3 having 246244 SNPs and 15577 insertions/deletions (InDels) and 13 flowering pathway genes. Of these, 11 exhibited sequence variations between bulks and validation (qPCR) revealed a significant difference in the expression of nine candidate genes (LcGA20oxG, LcFRI, LcLFY, LcSPL13a, Lcu.2RBY.3g060720, Lcu.2RBY.3g062540, Lcu.2RBY.3g062760, LcELF3a, and LcEMF1). Interestingly, the LcELF3a gene showed significantly higher expression in late-flowering genotype and exhibited substantial involvement in promoting lateness. Subsequently, an InDel marker (I-SP-383.9; LcELF3a gene) developed from LcqDTF3.2 QTL region showed 82.35% PVE (phenotypic variation explained) for earliness. The cloning, sequencing, and comparative analysis of the LcELF3a gene from both parents revealed 23 SNPs and InDels. Interestingly, a 52 bp deletion was recorded in the LcELF3a gene of L4775, predicted to cause premature termination of protein synthesis after 4 missense amino acids beyond the 351st amino acid due to the frameshift during translation. The identified InDel marker holds significant potential for breeding early maturing lentil varieties.

Genome-wide discovery of InDels and validation of PCR-Based InDel markers for earliness in a RIL population and genotypes of lentil (Lens culinaris Medik.).

The systematic identification of insertion/deletion (InDel) length polymorphisms from the entire lentil genome can be used to map the quantitative trait loci (QTL) and also for the marker-assisted selection (MAS) for various linked traits. The InDels were identified by comparing the whole-genome resequencing (WGRS) data of two extreme bulks (early- and late-flowering bulk) and a parental genotype (Globe Mutant) of lentil. The bulks were made by pooling 20 extreme recombinant inbred lines (RILs) each, derived by crossing Globe Mutant (late flowering parent) with L4775 (early flowering parent). Finally, 734,716 novel InDels were identified, which is nearly one InDel per 5,096 bp of lentil genome. Furthermore, 74.94% of InDels were within the intergenic region and 99.45% displayed modifier effects. Of these, 15,732 had insertions or deletions of 20 bp or more, making them amenable to the development of PCR-based markers. An InDel marker I-SP-356.6 (chr. 3; position 356,687,623; positioned 174.5 Kb from the LcFRI gene) was identified as having a phenotypic variance explained (PVE) value of 47.7% for earliness when validated in a RIL population. Thus, I-SP-356.6 marker can be deployed in MAS to facilitate the transfer of the earliness trait to other elite late-maturing cultivars. Two InDel markers viz., I-SP-356.6 and I-SP-383.9 (chr. 3; linked to LcELF3a gene) when tested in 9 lentil genotypes differing for maturity duration, clearly distinguished three early (L4775, ILL7663, Precoz) and four late genotypes (Globe Mutant, MFX, L4602, L830). However, these InDels could not be validated in two genotypes (L4717, L4727), suggesting either absence of polymorphism and/or presence of other loci causing earliness. The identified InDel markers can act as valuable tools for MAS for the development of early maturing lentil varieties.

Identification of quantitative trait loci (QTLs) regulating leaf SPAD value and trichome density in mungbean (Vigna radiata L.) using genotyping-by-sequencing (GBS) approach.

Quantitative trait loci (QTL) mapping is used for the precise localization of genomic regions regulating various traits in plants. Two major QTLs regulating Soil Plant Analysis Development (SPAD) value (qSPAD-7-1) and trichome density (qTric-7-2) in mungbean were identified using recombinant inbred line (RIL) populations (PMR-1×Pusa Baisakhi) on chromosome 7. Functional analysis of QTL region identified 35 candidate genes for SPAD value (16 No) and trichome (19 No) traits. The candidate genes regulating trichome density on the dorsal leaf surface of the mungbean include VRADI07G24840, VRADI07G17780, and VRADI07G15650, which encodes for ZFP6, TFs bHLH DNA-binding superfamily protein, and MYB102, respectively. Also, candidate genes having vital roles in chlorophyll biosynthesis are VRADIO7G29860, VRADIO7G29450, and VRADIO7G28520, which encodes for s-adenosyl-L-methionine, FTSHI1 protein, and CRS2-associated factor, respectively. The findings unfolded the opportunity for the development of customized genotypes having high SPAD value and high trichome density having a possible role in yield and mungbean yellow vein mosaic India virus (MYMIV) resistance in mungbean.

Integration of miRNA dynamics and drought tolerant QTLs in rice reveals the role of miR2919 in drought stress response.

To combat drought stress in rice, a major threat to global food security, three major quantitative trait loci for 'yield under drought stress' (qDTYs) were successfully exploited in the last decade. However, their molecular basis still remains unknown. To understand the role of secondary regulation by miRNA in drought stress response and their relation, if any, with the three qDTYs, the miRNA dynamics under drought stress was studied at booting stage in two drought tolerant (Sahbaghi Dhan and Vandana) and one drought sensitive (IR 20) cultivars. In total, 53 known and 40 novel differentially expressed (DE) miRNAs were identified. The primary drought responsive miRNAs were Osa-MIR2919, Osa-MIR3979, Osa-MIR159f, Osa-MIR156k, Osa-MIR528, Osa-MIR530, Osa-MIR2091, Osa-MIR531a, Osa-MIR531b as well as three novel ones. Sixty-one target genes that corresponded to 11 known and 4 novel DE miRNAs were found to be co-localized with the three qDTYs, out of the 1746 target genes identified. We could validate miRNA-mRNA expression under drought for nine known and three novel miRNAs in eight different rice genotypes showing varying degree of tolerance. From our study, Osa-MIR2919, Osa-MIR3979, Osa-MIR528, Osa-MIR2091-5p and Chr01_11911S14Astr and their target genes LOC_Os01g72000, LOC_Os01g66890, LOC_Os01g57990, LOC_Os01g56780, LOC_Os01g72834, LOC_Os01g61880 and LOC_Os01g72780 were identified as the most promising candidates for drought tolerance at booting stage. Of these, Osa-MIR2919 with 19 target genes in the qDTYs is being reported for the first time. It acts as a negative regulator of drought stress tolerance by modulating the cytokinin and brassinosteroid signalling pathway.

Morpho-biochemical characterization of a RIL population for seed parameters and identification of candidate genes regulating seed size trait in lentil (Lens culinaris Medik.).

The seed size and shape in lentil (Lens culinaris Medik.) are important quality traits as these influences the milled grain yield, cooking time, and market class of the grains. Linkage analysis was done for seed size in a RIL (F5:6) population derived by crossing L830 (20.9 g/1000 seeds) with L4602 (42.13 g/1000 seeds) which consisted of 188 lines (15.0 to 40.5 g/1000 seeds). Parental polymorphism survey using 394 SSRs identified 31 polymorphic primers, which were used for the bulked segregant analysis (BSA). Marker PBALC449 differentiated the parents and small seed size bulk only, whereas large seeded bulk or the individual plants constituting the large-seeded bulk could not be differentiated. Single plant analysis identified only six recombinant and 13 heterozygotes, of 93 small-seeded RILs (<24.0 g/1000 seed). This clearly showed that the small seed size trait is very strongly regulated by the locus near PBLAC449; whereas, large seed size trait seems governed by more than one locus. The PCR amplified products from the PBLAC449 marker (149bp from L4602 and 131bp from L830) were cloned, sequenced and BLAST searched using the lentil reference genome and was found amplified from chromosome 03. Afterward, the nearby region on chromosome 3 was searched, and a few candidate genes like ubiquitin carboxyl-terminal hydrolase, E3 ubiquitin ligase, TIFY-like protein, and hexosyltransferase having a role in seed size determination were identified. Validation study in another RIL mapping population which is differing for seed size, showed a number of SNPs and InDels among these genes when studied using whole genome resequencing (WGRS) approach. Biochemical parameters like cellulose, lignin, and xylose content showed no significant differences between parents and the extreme RILs, at maturity. Various seed morphological traits like area, length, width, compactness, volume, perimeter, etc., when measured using VideometerLab 4.0 showed significant differences for the parents and RILs. The results have ultimately helped in better understanding the region regulating the seed size trait in genomically less explored crops like lentils.

Draft genome sequencing and secretome profiling of Sclerotinia sclerotiorum revealed effector repertoire diversity and allied broad-host range necrotrophy.

White mold commonly known as Sclerotinia sclerotiorum causes stem rot disease and has emerged as one of the major fungal pathogens of oilseed Brassica across the world. In the present study, consistently virulent S. sclerotiorum isolate "ESR-01" was sequenced and an assembly size of ~ 41 Mb with 328 scaffolds having N50 of 447,128 was obtained. Additionally, 27,450 single nucleotide polymorphisms (SNPs) were identified from 155 scaffolds against S. sclerotiorum 1980 isolate, with an average SNP density of ~ 1.5 per kb genome. 667 repetitive elements were identified and approximately comprised 7% of the total annotated genes. The DDE_1 with 454 in numbers was found to be the most abundant and accounts for 68% of the total predicted repetitive elements. In total, 3844 simple sequence repeats are identified in the 328 scaffolds. A total of 9469 protein-coding genes were predicted from the whole genome assembly with an average gene length of 1587 bp and their distribution as 230.95 genes per Mb in the genome. Out of 9469 predicted protein-coding genes, 529 genes were observed encoding the CAZymes (Carbohydrate-Active enzymes) capable of degradation of the complex polysaccharides. Glycosyltransferase (GT) families were most abundant (49.71%) among the predicted CAZymes and GT2 (23%), GT4 (20%), and glycoside hydrolase (GH) 23% with GH18 (11%) were the prominent cell wall degrading enzyme families in the ESR-01 secretome. Besides this, 156 genes essential for the pathogen-host interactions were also identified. The effector analysis in the whole genome proteomics dataset revealed a total of 57 effector candidates (ECs) and 27 of them were having their analogs whereas the remaining 30 were novel ones. Eleven selected ECs were validated experimentally by analyzing the expression profile of the ESR-01 isolate of S. sclerotiorum. Together, the present investigation offers a better understanding of the S. sclerotiorum genome, secretome, and its effector repertoire which will help in refining the present knowledge on S. sclerotiorum-Brassica interactions and necrotrophic lifestyle of the phytopathogen in general.

Multigroup prediction in lung cancer patients and comparative controls using signature of volatile organic compounds in breath samples.

Early detection of lung cancer is a crucial factor for increasing its survival rates among the detected patients. The presence of carbonyl volatile organic compounds (VOCs) in exhaled breath can play a vital role in early detection of lung cancer. Identifying these VOC markers in breath samples through innovative statistical and machine learning techniques is an important task in lung cancer research. Therefore, we proposed an experimental approach for generation of VOC molecular concentration data using unique silicon microreactor technology and further identification and characterization of key relevant VOCs important for lung cancer detection through statistical and machine learning algorithms. We reported several informative VOCs and tested their effectiveness in multi-group classification of patients. Our analytical results indicated that seven key VOCs, including C4H8O2, C13H22O, C11H22O, C2H4O2, C7H14O, C6H12O, and C5H8O, are sufficient to detect the lung cancer patients with higher mean classification accuracy (92%) and lower standard error (0.03) compared to other combinations. In other words, the molecular concentrations of these VOCs in exhaled breath samples were able to discriminate the patients with lung cancer (n = 156) from the healthy smoker and nonsmoker controls (n = 193) and patients with benign pulmonary nodules (n = 65). The quantification of carbonyl VOC profiles from breath samples and identification of crucial VOCs through our experimental approach paves the way forward for non-invasive lung cancer detection. Further, our experimental and analytical approach of VOC quantitative analysis in breath samples may be extended to other diseases, including COVID-19 detection.

Comparative transcriptome analysis, unfolding the pathways regulating the seed-size trait in cultivated lentil (Lens culinaris Medik.).

Market class, cooking time, quality, and milled grain yield are largely influenced by the seed size and shape of the lentil (Lens culinaris Medik.); thus, they are considered to be important quality traits. To unfold the pathways regulating seed size in lentils, a transcriptomic approach was performed using large-seeded (L4602) and small-seeded (L830) genotypes. The study has generated nearly 375 million high-quality reads, of which 98.70% were properly aligned to the reference genome. Among biological replicates, very high similarity in fragments per kilobase of exon per million mapped fragments values (R > 0.9) showed the consistency of RNA-seq results. Various differentially expressed genes associated mainly with the hormone signaling and cell division pathways, transcription factors, kinases, etc. were identified as having a role in cell expansion and seed growth. A total of 106,996 unigenes were used for differential expression (DE) analysis. String analysis identified various modules having certain key proteins like Ser/Thr protein kinase, seed storage protein, DNA-binding protein, microtubule-associated protein, etc. In addition, some growth and cell division-related micro-RNAs like miR3457 (cell wall formation), miR1440 (cell proliferation and cell cycles), and miR1533 (biosynthesis of plant hormones) were identified as having a role in seed size determination. Using RNA-seq data, 5254 EST-SSR primers were generated as a source for future studies aiming for the identification of linked markers. In silico validation using Genevestigator® was done for the Ser/Thr protein kinase, ethylene response factor, and Myb transcription factor genes. It is of interest that the xyloglucan endotransglucosylase gene was found differentially regulated, suggesting their role during seed development; however, at maturity, no significant differences were recorded for various cell wall parameters including cellulose, lignin, and xylose content. This is the first report on lentils that has unfolded the key seed size regulating pathways and unveiled a theoretical way for the development of lentil genotypes having customized seed sizes.

Sequencing and de novo transcriptome assembly for discovering regulators of gene expression in Jack (Artocarpus heterophyllus).

Jack (Artocarpus heterophyllus) is a multipurpose fruit-tree species with minimal genomic resources. The study reports developing comprehensive transcriptome data containing 80,411 unigenes with an N50 value of 1265 bp. We predicted 64,215 CDSs from the unigenes and annotated and functionally categorized them into the biological process (23,230), molecular function (27,149), and cellular components (17,284). From 80,411 unigenes, we discovered 16,853 perfect SSRs with 192 distinct repeat motif types reiterating 4 to 22 times. Besides, we identified 2741 TFs from 69 TF families, 53 miRNAs from 19 conserved miRNA families, 25,953 potential lncRNAs, and placed three functional eTMs in different lncRNA-miRNA pairs. The regulatory networks involving genes, TFs, and miRNAs identified several regulatory and regulated nodes providing insight into miRNAs' gene associations and transcription factor-mediated regulation. The comparison of expression patterns of some selected miRNAs vis-à-vis their corresponding target genes showed an inverse relationship indicating the possible miRNA-mediated regulation of the genes.

A Web Tool for Consensus Gene Regulatory Network Construction.

Gene regulatory network (GRN) construction involves various steps of complex computational steps. This step-by-step procedure requires prior knowledge of programming languages such as R. Development of a web tool may reduce this complexity in the analysis steps which can be easy accessible for the user. In this study, a web tool for constructing consensus GRN by combining the outcomes obtained from four methods, namely, correlation, principal component regression, partial least square, and ridge regression, has been developed. We have designed the web tool with an interactive and user-friendly web page using the php programming language. We have used R script for the analysis steps which run in the background of the user interface. Users can upload gene expression data for constructing consensus GRN. The output obtained from analysis will be available in downloadable form in the result window of the web tool.

Comparative RNA-Seq analysis unfolds a complex regulatory network imparting yellow mosaic disease resistance in mungbean [Vigna radiata (L.) R. Wilczek].

Yellow Mosaic Disease (YMD) in mungbean [Vigna radiata (L.) R. Wilczek] is one of the most damaging diseases in Asia. In the northern part of India, the YMD is caused by Mungbean Yellow Mosaic India Virus (MYMIV), while in southern India this is caused by Mungbean Yellow Mosaic Virus (MYMV). The molecular mechanism of YMD resistance in mungbean remains largely unknown. In this study, RNA-seq analysis was conducted between a resistant (PMR-1) and a susceptible (Pusa Vishal) mungbean genotype under infected and control conditions to understand the regulatory network operating between mungbean-YMV. Overall, 76.8 million raw reads could be generated in different treatment combinations, while mapping rate per library to the reference genome varied from 86.78% to 93.35%. The resistance to MYMIV showed a very complicated gene network, which begins with the production of general PAMPs (pathogen-associated molecular patterns), then activation of various signaling cascades like kinases, jasmonic acid (JA) and brassinosteroid (BR), and finally the expression of specific genes (like PR-proteins, virus resistance and R-gene proteins) leading to resistance response. The function of WRKY, NAC and MYB transcription factors in imparting the resistance against MYMIV could be established. The string analysis also revealed the role of proteins involved in kinase, viral movement and phytoene synthase activity in imparting YMD resistance. A set of novel stress-related EST-SSRs are also identified from the RNA-Seq data which may be used to find the linked genes/QTLs with the YMD resistance. Also, 11 defence-related transcripts could be validated through quantitative real-time PCR analysis. The identified gene networks have led to an insight about the defence mechanism operating against MYMIV infection in mungbean which will be of immense use to manage the YMD resistance in mungbean.

Agro-Morphological Characterization of Lentil Germplasm of Indian National Genebank and Development of a Core Set for Efficient Utilization in Lentil Improvement Programs.

Lentil (Lens culinaris Medik.) is one of the major cool-season pulse crops worldwide. Its increasing demand as a staple pulse has led to the unlocking of diverse germplasm collections conserved in the genebanks to develop its superior varieties. The Indian National Genebank, housed at the Indian Council of Agricultural Research (ICAR)-National Bureau of Plant Genetic Resources, New Delhi, India, currently has 2,324 accessions comprising 1,796 indigenous and 528 exotic collections. This study was conducted to unveil the potential of lentil germplasm by assessing its agro-morphological characteristics and diversity, identifying trait-specific germplasm, and developing a core set. The complete germplasm set was characterized for two years, i.e., 2017-2018 and 2018-2019, and data were recorded on 26 agro-morphological traits. High phenotypic variability was observed for nine quantitative and 17 qualitative traits. A core set comprising 170 accessions (137 Indian and 33 exotic) was derived based on the characterization data as well as geographical origin using a heuristic method and PowerCore software. This core set was found to be sufficiently diverse and representative of the entire collection based on the comparison made using Shannon-Weaver diversity indices and χ2 test. These results were further validated by summary statistics. The core set displayed high genetic diversity as evident from a higher coefficient of variance in comparison to the entire set for individual traits and overall Shannon-Weaver diversity indices (entire: 1.054; core: 1.361). In addition, the total variation explained by the first three principal components was higher in the core set (70.69%) than in the entire collection (68.03%). Further, the conservation of pairwise correlation values among descriptors in the entire and core set reflected the maintenance of the structure of the whole set. Based on the results, this core set is believed to represent the entire collection, completely. Therefore, it constitutes a potential set of germplasm that can be used in the genetic enhancement of lentils.

Identification of QTLs/Defense Genes Effective at Seedling Stage Against Prevailing Races of Wheat Stripe Rust in India.

Resistance in modern wheat cultivars for stripe rust is not long lasting due to the narrow genetic base and periodical evolution of new pathogenic races. Though nearly 83 Yr genes conferring resistance to stripe rust have been cataloged so far, few of them have been mapped and utilized in breeding programs. Characterization of wheat germplasm for novel sources of resistance and their incorporation into elite cultivars is required to achieve durable resistance and thus to minimize the yield losses. Here, a genome-wide association study (GWAS) was performed on a set of 391 germplasm lines with the aim to identify quantitative trait loci (QTL) using 35K Axiom® array. Phenotypic evaluation disease severity against four stripe rust pathotypes, i.e., 46S119, 110S119, 238S119, and 47S103 (T) at the seedling stage in a greenhouse providing optimal conditions was carried out consecutively for 2 years (2018 and 2019 winter season). We identified, a total of 17 promising QTl which passed FDR criteria. Moreover these 17 QTL identified in the current study were mapped at different genomic locations i.e. 1B, 2A, 2B, 2D, 3A, 3B, 3D, 4B, 5B and 6B. These 17 QTLs identified in the present study might play a key role in marker-assisted breeding for developing stripe rust resistant wheat cultivars.

Integrated Framework for Selection of Additive and Nonadditive Genetic Markers for Genomic Selection.

Genomic selection is a modified form of marker-assisted selection in which the markers from the whole genome are used to estimate the genomic-estimated breeding value (GEBV). Several estimators are available to estimate GEBV. These estimators are able to capture either additive genetic effects or nonadditive genetic effects. However, there is hardly any procedure available that could capture both the effects simultaneously. Therefore, this study has been conducted to develop an integrated framework that is able to capture both additive and nonadditive effects efficiently. This integrated framework has been developed after evaluating existing additive and nonadditive models for marker selection. Furthermore, two efficient additive and nonadditive methods, that is, sparse additive models (SpAM) and Hilbert-Schmidt independence criterion least absolute shrinkage and selection operator (HSIC LASSO), have been combined to select both additive and nonadditive genetic markers for estimation of GEBV. The performance of the proposed framework has been evaluated on the basis of prediction accuracy, fraction of correctly selected features, and redundancy rate, along with standard error of mean for estimation of GEBV, compared with the individual performances of SpAM and HSIC LASSO separately. The newly developed framework is found to be satisfactory in terms of its performance and found to be robust for estimation of GEBV.

RiceMetaSysB: a database of blast and bacterial blight responsive genes in rice and its utilization in identifying key blast-resistant WRKY genes.

Nearly two decades of revolution in the area of genomics serves as the basis of present-day molecular breeding in major food crops such as rice. Here we report an open source database on two major biotic stresses of rice, named RiceMetaSysB, which provides detailed information about rice blast and bacterial blight (BB) responsive genes (RGs). Meta-analysis of microarray data from different blast- and BB-related experiments across 241 and 186 samples identified 15135 unique genes for blast and 7475 for BB. A total of 9365 and 5375 simple sequence repeats (SSRs) in blast and BB RGs were identified for marker development. Retrieval of candidate genes using different search options like genotypes, tissue, developmental stage of the host, strain, hours/days post-inoculation, physical position and SSR marker information is facilitated in the database. Search options like 'common genes among varieties' and 'strains' have been enabled to identify robust candidate genes. A 2D representation of the data can be used to compare expression profiles across genes, genotypes and strains. To demonstrate the utility of this database, we queried for blast-responsive WRKY genes (fold change ≥5) using their gene IDs. The structural variations in the 12 WRKY genes so identified and their promoter regions were explored in two rice genotypes contrasting for their reaction to blast infection. Expression analysis of these genes in panicle tissue infected with a virulent and an avirulent strain of Magnaporthe oryzae could identify WRKY7, WRKY58, WRKY62, WRKY64 and WRKY76 as potential candidate genes for resistance to panicle blast, as they showed higher expression only in the resistant genotype against the virulent strain. Thus, we demonstrated that RiceMetaSysB can play an important role in providing robust candidate genes for rice blast and BB.

Genetic Diversity Studies Based on Morphological Variability, Pathogenicity and Molecular Phylogeny of the Sclerotinia sclerotiorum Population From Indian Mustard (Brassica juncea).

White mold or stem rot disease are ubiquitously distributed throughout the world and the causal organism of this disease Sclerotinia sclerotiorum (Lib.) de Bary, is known to infect over 400 plant species. Sclerotinia stem rot is one of the most devastating fungal diseases and poses a serious threat to the worldwide cultivation of oilseed Brassica including India. S. sclerotiorum pathogen usually infects the stem but in severe cases leaves and pods also affected at different developmental stages that deteriorate not only the oil quality but also causing the seed and oil yield losses up to 90% depending on the severity of the disease infestation. This study investigated the morphological and molecular characterization of pathogenic S. sclerotiorum (Lib) de Bary geographical isolates from oilseed Brassica including Brassica juncea (Indian mustard). The aim of this study was to compare isolates of S. sclerotiorum originated from different agro-climatic conditions and to analyse similarity or differences between them as well as to examine the virulence of this pathogen specifically in Brassica for the first time. The collection of S. sclerotiorum isolates from symptomatic Brassica plants was done and analyzed for morphological features, and molecular characterization. The virulence evaluation test of 65 isolates on four Brassica cultivars has shown 5 of them were highly virulent, 46 were virulent and 14 were moderately virulent. Phylogenetic analysis encompassing all the morphological features, SSR polymorphism, and ITS sequencing has shown the existence of high genetic diversity among the isolates that categorized all the isolates in three evolutionary lineages in the derived dendrogram. Further, genetic variability analysis based on sequences variation in ITS region of all the isolates has shown the existence of either insertions or deletions of the nucleotides in the ITS region has led to the interspecies variability and observed the variation were in a clade-specific manner. Together this analysis observed the existence of higher heterogeneity and genetic variability in S. sclerotiorum isolates collection and indicates the presence of clonal and sexual progenies of the pathogen in the mustard growing regions of India surveyed in this study. With a higher level of genetic variability and diversity among the S. sclerotiorum population needs robust screening approaches to identify the donor parent and utilize them in resistance breeding program for effectively counter the menace of stem rot disease in Brassica.

Abiotic Stress Responsive miRNA-Target Network and Related Markers (SNP, SSR) in Brassica juncea.

Abiotic stress is one of the major factors responsible for huge yield loss in crop plants. MicroRNAs play a key role in adaptive responses of plants under abiotic stress conditions through post-transcriptional gene regulations. In present study, 95 potential miRNAs were predicted in Brassica juncea using comparative genomics approach. It was noted that these miRNAs, target several transcription factors (TFs), transporter family proteins, signaling related genes, and protease encoding genes. Nineteen distinct miRNA-target regulatory networks were observed with significant involvement in regulation of transcription, response to stimulus, hormone and auxin mediated signaling pathway related gene ontology (GO) term. The sucrose-starch metabolism and pentose-gluconate interconversion pathways were found significantly enriched for these target genes. Molecular markers such as Simple Sequence Repeats (SSR) and Single Nucleotide Polymorphism (SNPs) were identified on miRNAs (miR-SSRs and miR-SNPs) and their target genes in B. juncea. Notably, one of the miR-SNP (C/T) was found at the 5th position on mature region of miR2926. This C/T transition led to the distorted and unstable hairpin structure of miR2926, consequently complete loss of target function. Hence, findings from this study will lay a foundation for marker assisted breeding for abiotic stress tolerant varieties of B. juncea.

SSH Analysis of Endosperm Transcripts and Characterization of Heat Stress Regulated Expressed Sequence Tags in Bread Wheat.

Heat stress is one of the major problems in agriculturally important cereal crops, especially wheat. Here, we have constructed a subtracted cDNA library from the endosperm of HS-treated (42°C for 2 h) wheat cv. HD2985 by suppression subtractive hybridization (SSH). We identified ~550 recombinant clones ranging from 200 to 500 bp with an average size of 300 bp. Sanger's sequencing was performed with 205 positive clones to generate the differentially expressed sequence tags (ESTs). Most of the ESTs were observed to be localized on the long arm of chromosome 2A and associated with heat stress tolerance and metabolic pathways. Identified ESTs were BLAST search using Ensemble, TriFLD, and TIGR databases and the predicted CDS were translated and aligned with the protein sequences available in pfam and InterProScan 5 databases to predict the differentially expressed proteins (DEPs). We observed eight different types of post-translational modifications (PTMs) in the DEPs corresponds to the cloned ESTs-147 sites with phosphorylation, 21 sites with sumoylation, 237 with palmitoylation, 96 sites with S-nitrosylation, 3066 calpain cleavage sites, and 103 tyrosine nitration sites, predicted to sense the heat stress and regulate the expression of stress genes. Twelve DEPs were observed to have transmembrane helixes (TMH) in their structure, predicted to play the role of sensors of HS. Quantitative Real-Time PCR of randomly selected ESTs showed very high relative expression of HSP17 under HS; up-regulation was observed more in wheat cv. HD2985 (thermotolerant), as compared to HD2329 (thermosusceptible) during grain-filling. The abundance of transcripts was further validated through northern blot analysis. The ESTs and their corresponding DEPs can be used as molecular marker for screening or targeted precision breeding program. PTMs identified in the DEPs can be used to elucidate the thermotolerance mechanism of wheat-a novel step toward the development of "climate-smart" wheat.

Identification of Putative RuBisCo Activase (TaRca1)-The Catalytic Chaperone Regulating Carbon Assimilatory Pathway in Wheat (Triticum aestivum) under the Heat Stress.

RuBisCo activase (Rca) is a catalytic chaperone involved in modulating the activity of RuBisCo (key enzyme of photosynthetic pathway). Here, we identified eight novel transcripts from wheat through data mining predicted to be Rca and cloned a transcript of 1.4 kb from cv. HD2985, named as TaRca1 (GenBank acc. no. KC776912). Single copy number of TaRca1 was observed in wheat genome. Expression analysis in diverse wheat genotypes (HD2985, Halna, PBW621, and HD2329) showed very high relative expression of TaRca1 in Halna under control and HS-treated, as compared to other cultivars at different stages of growth. TaRca1 protein was predicted to be chloroplast-localized with numerous potential phosphorylation sites. Northern blot analysis showed maximum accumulation of TaRca1 transcript in thermotolerant cv. during mealy-ripe stage, as compared to thermosusceptible. Decrease in the photosynthetic parameters was observed in all the cultivars, except PBW621 in response to HS. We observed significant increase in the Rca activity in all the cultivars under HS at different stages of growth. HS causes decrease in the RuBisCo activity; maximum reduction was observed during pollination stage in thermosusceptible cvs. as validated through immunoblotting. We observed uniform carbon distribution in different tissues of thermotolerant cvs., as compared to thermosusceptible. Similarly, tolerance level of leaf was observed maximum in Halna having high Rca activity under HS. A positive correlation was observed between the transcript and activity of TaRca1 in HS-treated Halna. Similarly, TaRca1 enzyme showed positive correlation with the activity of RuBisCo. There is, however, need to manipulate the thermal stability of TaRca1 enzyme through protein engineering for sustaining the photosynthetic rate under HS-a novel approach toward development of "climate-smart" crop.

Harnessing Next Generation Sequencing in Climate Change: RNA-Seq Analysis of Heat Stress-Responsive Genes in Wheat (Triticum aestivum L.).

Wheat is a staple food worldwide and provides 40% of the calories in the diet. Climate change and global warming pose a threat to wheat production, however, and demand a deeper understanding of how heat stress might impact wheat production and wheat biology. However, it is difficult to identify novel heat stress associated genes when the genomic information is not available. Wheat has a very large and complex genome that is about 37 times the size of the rice genome. The present study sequenced the whole transcriptome of the wheat cv. HD2329 at the flowering stage, under control (22°±3°C) and heat stress (42°C, 2 h) conditions using Illumina HiSeq and Roche GS-FLX 454 platforms. We assembled more than 26.3 and 25.6 million high-quality reads from the control and HS-treated tissues transcriptome sequences respectively. About 76,556 (control) and 54,033 (HS-treated) contigs were assembled and annotated de novo using different assemblers and a total of 21,529 unigenes were obtained. Gene expression profile showed significant differential expression of 1525 transcripts under heat stress, of which 27 transcripts showed very high (>10) fold upregulation. Cellular processes such as metabolic processes, protein phosphorylation, oxidations-reductions, among others were highly influenced by heat stress. In summary, these observations significantly enrich the transcript dataset of wheat available on public domain and show a de novo approach to discover the heat-responsive transcripts of wheat, which can accelerate the progress of wheat stress-genomics as well as the course of wheat breeding programs in the era of climate change.