Sesame Genomic Web Resource (SesameGWR): a well-annotated data resource for transcriptomic signatures of abiotic and biotic stress responses in sesame (Sesamum indicum L.).

Sesame (Sesamum indicum L.) is a globally cultivated oilseed crop renowned for its historical significance and widespread growth in tropical and subtropical regions. With notable nutritional and medicinal attributes, sesame has shown promising effects in combating malnutrition cancer, diabetes, and other diseases like cardiovascular problems. However, sesame production faces significant challenges from environmental threats such as charcoal rot, drought, salinity, and waterlogging stress, resulting in economic losses for farmers. The scarcity of information on stress-resistance genes and pathways exacerbates these challenges. Despite its immense importance, there is currently no platform available to provide comprehensive information on sesame, which significantly hinders the mining of various stress-associated genes and the molecular breeding of sesame. To address this gap, here a free, web-accessible, and user-friendly genomic web resource (SesameGWR, http://backlin.cabgrid.res.in/sesameGWR/) has been developed This platform provides key insights into differentially expressed genes, transcription factors, miRNAs, and molecular markers like simple sequence repeats, single nucleotide polymorphisms, and insertions and deletions associated with both biotic and abiotic stresses.. The functional genomics information and annotations embedded in this web resource were predicted through RNA-seq data analysis. Considering the impact of climate change and the nutritional and medicinal importance of sesame, this study is of utmost importance in understanding stress responses. SesameGWR will serve as a valuable tool for developing climate-resilient sesame varieties, thereby enhancing the productivity of this ancient oilseed crop.

Development and Validation of Near-Infrared Reflectance Spectroscopy Prediction Modeling for the Rapid Estimation of Biochemical Traits in Potato.

Potato is a globally significant crop, crucial for food security and nutrition. Assessing vital nutritional traits is pivotal for enhancing nutritional value. However, traditional wet lab methods for the screening of large germplasms are time- and resource-intensive. To address this challenge, we used near-infrared reflectance spectroscopy (NIRS) for rapid trait estimation in diverse potato germplasms. It employs molecular absorption principles that use near-infrared sections of the electromagnetic spectrum for the precise and rapid determination of biochemical parameters and is non-destructive, enabling trait monitoring without sample compromise. We focused on modified partial least squares (MPLS)-based NIRS prediction models to assess eight key nutritional traits. Various mathematical treatments were executed by permutation and combinations for model calibration. The external validation prediction accuracy was based on the coefficient of determination (RSQexternal), the ratio of performance to deviation (RPD), and the low standard error of performance (SEP). Higher RSQexternal values of 0.937, 0.892, and 0.759 were obtained for protein, dry matter, and total phenols, respectively. Higher RPD values were found for protein (3.982), followed by dry matter (3.041) and total phenolics (2.000), which indicates the excellent predictability of the models. A paired t-test confirmed that the differences between laboratory and predicted values are non-significant. This study presents the first multi-trait NIRS prediction model for Indian potato germplasm. The developed NIRS model effectively predicted the remaining genotypes in this study, demonstrating its broad applicability. This work highlights the rapid screening potential of NIRS for potato germplasm, a valuable tool for identifying trait variations and refining breeding strategies, to ensure sustainable potato production in the face of climate change.

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.

Characterization of putative calcium-dependent protein kinase-1 (TaCPK-1) gene: hubs in signalling and tolerance network of wheat under terminal heat.

Calcium-dependent protein kinase (CDPK) is member of one of the most important signalling cascades operating inside the plant system due to its peculiar role as thermo-sensor. Here, we identified 28 full length putative CDPKs from wheat designated as TaCDPK (1-28). Based on digital gene expression, we cloned full length TaCPK-1 gene of 1691 nucleotides with open reading frame (ORF) of 548 amino acids (accession number OP125853). The expression of TaCPK-1 was observed maximum (3.1-fold) in leaf of wheat cv. HD2985 (thermotolerant) under T2 (38 ± 3 °C, 2 h), as compared to control. A positive correlation was observed between the expression of TaCPK-1 and other stress-associated genes (MAPK6, CDPK4, HSFA6e, HSF3, HSP17, HSP70, SOD and CAT) involved in thermotolerance. Global protein kinase assay showed maximum activity in leaves, as compared to root, stem and spike under heat stress. Immunoblot analysis showed abundance of CDPK protein in wheat cv. HD2985 (thermotolerant) in response to T2 (38 ± 3 °C, 2 h), as compared to HD2329 (thermosusceptible). Calcium ion (Ca2+), being inducer of CDPK, showed strong Ca-signature in the leaf tissue (Ca-622 ppm) of thermotolerant wheat cv. under heat stress, whereas it was minimum (Ca-201 ppm) in spike tissue. We observed significant variations in the ionome of wheat under HS. To conclude, TaCPK-1 plays important role in triggering signaling network and in modulation of HS-tolerance in wheat. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-024-03989-6.

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.

Prediction of matrilineal specific patatin-like protein governing in-vivo maternal haploid induction in maize using support vector machine and di-peptide composition.

The mutant matrilineal (mtl) gene encoding patatin-like phospholipase activity is involved in in-vivo maternal haploid induction in maize. Doubling of chromosomes in haploids by colchicine treatment leads to complete fixation of inbreds in just one generation compared to 6-7 generations of selfing. Thus, knowledge of patatin-like proteins in other crops assumes great significance for in-vivo haploid induction. So far, no online tool is available that can classify unknown proteins into patatin-like proteins. Here, we aimed to optimize a machine learning-based algorithm to predict the patatin-like phospholipase activity of unknown proteins. Four different kernels [radial basis function (RBF), sigmoid, polynomial, and linear] were used for building support vector machine (SVM) classifiers using six different sequence-based compositional features (AAC, DPC, GDPC, CTDC, CTDT, and GAAC). A total of 1170 protein sequences including both patatin-like (585 sequences) from various monocots, dicots, and microbes; and non-patatin-like proteins (585 sequences) from different subspecies of Zea mays were analyzed. RBF and polynomial kernels were quite promising in the prediction of patatin-like proteins. Among six sequence-based compositional features, di-peptide composition attained > 90% prediction accuracies using RBF and polynomial kernels. Using mutual information, most explaining dipeptides that contributed the highest to the prediction process were identified. The knowledge generated in this study can be utilized in other crops prior to the initiation of any experiment. The developed SVM model opened a new paradigm for scientists working in in-vivo haploid induction in commercial crops. This is the first report of machine learning of the identification of proteins with patatin-like activity.

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.

Changes in microbial community structure and yield responses with the use of nano-fertilizers of nitrogen and zinc in wheat-maize system.

The growing popularity of nano-fertilization around the world for enhancing yield and nutrient use efficiency has been realized, however its influence on soil microbial structure is not fully understood. The purpose of carrying out this study was to assess the combined effect of nano and conventional fertilizers on the soil biological indicators and crop yield in a wheat-maize system. The results indicate that the at par grain yield of wheat and maize was obtained with application of 75% of recommended nitrogen (N) with full dose of phosphorus (P) and potassium (K) through conventional fertilizers along with nano-N (nano-urea) or nano-N plus nano-Zn sprays and N100PK i.e. business as usual (recommended dose of fertilizer). Important soil microbial property like microbial biomass carbon was found statistically similar with nano fertilizer-based management (N75PK + nano-N, and N75PK + nano-N + nano-Zn) and conventional management (N100PK), during both wheat and maize seasons. The experimental data indicated that the application of foliar spray of nano-fertilizers along with 75% N as basal is a sustainable nutrient management approach with respect to growth, yield and rhizosphere biological activity. Furthermore, two foliar sprays of nano-N or nano-N + nano-Zn curtailed N requirement by 25%, furthermore enhanced soil microbial diversity and the microbial community structure. The specific microbial groups, including Actinobacteria, Bacteroidia, and Proteobacteria, were present in abundance and were positively correlated with wheat and maize yield and soil microbial biomass carbon. Thus, one of the best nutrient management approaches for sustaining productivity and maintaining sound microbial diversity in wheat-maize rotation is the combined use of nano-fertilizers and conventional fertilizers.

Genome-wide identification of potassium channels in maize showed evolutionary patterns and variable functional responses to abiotic stresses.

Potassium (K) channels are essential components of plant biology, mediating not only K ion (K+) homeostasis but also regulating several physiological processes and stress tolerance. In the current investigation, we identified 27 K+ channels in maize and deciphered the evolution and divergence pattern with four monocots and five dicot species. Chromosomal localization and expansion of K+ channel genes showed uneven distribution and were independent of genome size. The dispersed duplication is the major force in expanding K+ channels in the target genomes. The mean Ka/Ks ratio of <0.5 in paralogs and orthologs indicates horizontal and vertical expansions of K+ channel genes under strong purifying selection. The one-to-one K+ channel orthologs were prominent among the closely related species, with higher synteny between maize and the rest of the monocots. Comprehensive K+ channels promoter analysis revealed various cis-regulatory elements mediating stress tolerance with the predominance of MYB and STRE binding sites. The regulatory network showed AP2-EREBP TFs, miR164 and miR399 are prominent regulatory elements of K+ channels. The qRT-PCR analysis of K+ channels and regulatory miRNAs showed significant expressions in response to drought and waterlogging stresses. The present study expanded the knowledge on K+ channels in maize and will serve as a basis for an in-depth functional analysis.

Meta-QTL analysis in wheat: progress, challenges and opportunities.

Wheat, an important cereal crop globally, faces major challenges due to increasing global population and changing climates. The production and productivity are challenged by several biotic and abiotic stresses. There is also a pressing demand to enhance grain yield and quality/nutrition to ensure global food and nutritional security. To address these multifaceted concerns, researchers have conducted numerous meta-QTL (MQTL) studies in wheat, resulting in the identification of candidate genes that govern these complex quantitative traits. MQTL analysis has successfully unraveled the complex genetic architecture of polygenic quantitative traits in wheat. Candidate genes associated with stress adaptation have been pinpointed for abiotic and biotic traits, facilitating targeted breeding efforts to enhance stress tolerance. Furthermore, high-confidence candidate genes (CGs) and flanking markers to MQTLs will help in marker-assisted breeding programs aimed at enhancing stress tolerance, yield, quality and nutrition. Functional analysis of these CGs can enhance our understanding of intricate trait-related genetics. The discovery of orthologous MQTLs shared between wheat and other crops sheds light on common evolutionary pathways governing these traits. Breeders can leverage the most promising MQTLs and CGs associated with multiple traits to develop superior next-generation wheat cultivars with improved trait performance. This review provides a comprehensive overview of MQTL analysis in wheat, highlighting progress, challenges, validation methods and future opportunities in wheat genetics and breeding, contributing to global food security and sustainable agriculture.

MethSemble-6mA: an ensemble-based 6mA prediction server and its application on promoter region of LBD gene family in Poaceae.

The Lateral Organ Boundaries Domain (LBD) containing genes are a set of plant-specific transcription factors and are crucial for controlling both organ development and defense mechanisms as well as anthocyanin synthesis and nitrogen metabolism. It is imperative to understand how methylation regulates gene expression, through predicting methylation sites of their promoters particularly in major crop species. In this study, we developed a user-friendly prediction server for accurate prediction of 6mA sites by incorporating a robust feature set, viz., Binary Encoding of Mono-nucleotide DNA. Our model,MethSemble-6mA, outperformed other state-of-the-art tools in terms of accuracy (93.12%). Furthermore, we investigated the pattern of probable 6mA sites at the upstream promoter regions of the LBD-containing genes in Triticum aestivum and its allied species using the developed tool. On average, each selected species had four 6mA sites, and it was found that with speciation and due course of evolution in wheat, the frequency of methylation have reduced, and a few sites remain conserved. This obviously cues gene birth and gene expression alteration through methylation over time in a species and reflects functional conservation throughout evolution. Since DNA methylation is a vital event in almost all plant developmental processes (e.g., genomic imprinting and gametogenesis) along with other life processes, our findings on epigenetic regulation of LBD-containing genes have dynamic implications in basic and applied research. Additionally, MethSemble-6mA (http://cabgrid.res.in:5799/) will serve as a useful resource for a plant breeders who are interested to pursue epigenetic-based crop improvement research.

Transcriptional Regulation of Small Heat Shock Protein 17 (sHSP-17) by Triticum aestivum HSFA2h Transcription Factor Confers Tolerance in Arabidopsis under Heat Stress.

Heat shock transcription factors (HSFs) contribute significantly to thermotolerance acclimation. Here, we identified and cloned a putative HSF gene (HSFA2h) of 1218 nucleotide (acc. no. KP257297.1) from wheat cv. HD2985 using a de novo transcriptomic approach and predicted sHSP as its potential target. The expression of HSFA2h and its target gene (HSP17) was observed at the maximum level in leaf tissue under heat stress (HS), as compared to the control. The HSFA2h-pRI101 binary construct was mobilized in Arabidopsis, and further screening of T3 transgenic lines showed improved tolerance at an HS of 38 °C compared with wild type (WT). The expression of HSFA2h was observed to be 2.9- to 3.7-fold higher in different Arabidopsis transgenic lines under HS. HSFA2h and its target gene transcripts (HSP18.2 in the case of Arabidopsis) were observed to be abundant in transgenic Arabidopsis plants under HS. We observed a positive correlation between the expression of HSFA2h and HSP18.2 under HS. Evaluation of transgenic lines using different physio-biochemical traits linked with thermotolerance showed better performance of HS-treated transgenic Arabidopsis plants compared with WT. There is a need to further characterize the gene regulatory network (GRN) of HSFA2h and sHSP in order to modulate the HS tolerance of wheat and other agriculturally important crops.

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.

Genome-wide identification and characterization of Puccinia striiformis-responsive lncRNAs in Triticum aestivum.

Wheat stripe rust (yellow rust) caused by Puccinia striiformis f. sp. tritici (Pst) is a serious biotic stress factor limiting wheat production worldwide. Emerging evidence demonstrates that long non-coding RNAs (lncRNAs) participate in various developmental processes in plants via post-transcription regulation. In this study, RNA sequencing (RNA-seq) was performed on a pair of near-isogenic lines-rust resistance line FLW29 and rust susceptible line PBW343-which differed only in the rust susceptibility trait. A total of 6,807 lncRNA transcripts were identified using bioinformatics analyses, among which 10 lncRNAs were found to be differentially expressed between resistance and susceptible lines. In order to find the target genes of the identified lncRNAs, their interactions with wheat microRNA (miRNAs) were predicted. A total of 199 lncRNAs showed interactions with 65 miRNAs, which further target 757 distinct mRNA transcripts. Moreover, detailed functional annotations of the target genes were used to identify the candidate genes, pathways, domains, families, and transcription factors that may be related to stripe rust resistance response in wheat plants. The NAC domain protein, disease resistance proteins RPP13 and RPM1, At1g58400, monodehydroascorbate reductase, NBS-LRR-like protein, rust resistance kinase Lr10-like, LRR receptor, serine/threonine-protein kinase, and cysteine proteinase are among the identified targets that are crucial for wheat stripe rust resistance. Semiquantitative PCR analysis of some of the differentially expressed lncRNAs revealed variations in expression profiles of two lncRNAs between the Pst-resistant and Pst-susceptible genotypes at least under one condition. Additionally, simple sequence repeats (SSRs) were also identified from wheat lncRNA sequences, which may be very useful for conducting targeted gene mapping studies of stripe rust resistance in wheat. These findings improved our understanding of the molecular mechanism responsible for the stripe rust disease that can be further utilized to develop wheat varieties with durable resistance to this disease.

Transcriptomics reveals key genes responsible for functional diversity in pectoralis major muscles of native black Kadaknath and broiler chicken.

RNA sequencing-based expression profiles from pectoralis major muscles of black meat (Kadaknath) and white meat (broiler) chicken were compared to identify differentially expressed genes. A total of 156 genes with log2 fold change ≥ ± 2.0 showed higher expression in Kadaknath and 68 genes were expressed at a lower level in comparison to broiler. Significantly enriched biological functions of up-regulated genes in Kadaknath were skeletal muscle cell differentiation, regulation of response to reactive oxygen, positive regulation of fat cell differentiation and melanosome. Significant ontology terms up-regulated in broiler included DNA replication origin binding, G-protein coupled receptor signaling pathway and chemokine activity. Highly inter-connected differentially expressed genes in Kadaknath (ATFs, C/EPDs) were observed to be important regulators of cellular adaptive functions, while in broiler, the hub genes were involved in cell cycle progression and DNA replication. The study is an attempt to get an insight into the transcript diversity of pectoralis major muscles of Kadaknath and broiler chicken. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03682-0.

Revelation of genes associated with energy generating metabolic pathways in the fighter type Aseel chicken of India through skeletal muscle transcriptome sequencing.

In this study, comparative analysis of skeletal muscle transcriptome was carried out for four biological replicates of Aseel, a fighter type breed and Punjab Brown, a meat type breed of India. The profusely expressed genes in both breeds were related to muscle contraction and motor activity. Differential expression analysis identified 961 up-regulated and 979 down-regulated genes in Aseel at a threshold of log2 fold change ≥ ±2.0 (padj<0.05). Significantly enriched KEGG pathways in Aseel included metabolic pathways and oxidative phosphorylation, with higher expression of genes associated with fatty acid beta-oxidation, formation of ATP by chemiosmotic coupling, response to oxidative stress, and muscle contraction. The highly connected hub genes identified through gene network analysis in the Aseel gamecocks were HNF4A, APOA2, APOB, APOC3, AMBP, and ACOT13, which are primarily associated with energy generating metabolic pathways. The up-regulated genes in Punjab Brown chicken were found to be related to muscle growth and differentiation. There was enrichment of pathways such as focal adhesion, insulin signaling pathway and ECM receptor interaction in these birds. The results presented in this study help to improve our understanding of the molecular mechanisms associated with fighting ability and muscle growth in Aseel and Punjab Brown chicken, respectively.

Identification of Novel QTLs/Defense Genes in Spring Wheat Germplasm Panel for Seedling and Adult Plant Resistance to Stem Rust and Their Validation Through KASP Marker Assays.

Stem rust is one of the major diseases threatening wheat production globally. To identify novel resistance quantitative trait loci (QTLs), we performed 35K Axiom Array SNP genotyping assays on an association mapping panel of 400 germplasm accessions, including Indian landraces, in conjunction with phenotyping for stem rust at seedling and adult plant stages. Association analyses using three genome wide association study (GWAS) models (CMLM, MLMM, and FarmCPU) revealed 20 reliable QTLs for seedling and adult plant resistance. Among these 20 QTLs, five QTLs were found consistent with three models, i.e., four QTLs on chromosome 2AL, 2BL, 2DL, and 3BL for seedling resistance and one QTL on chromosome 7DS for adult plant resistance. Further, we identified a total of 21 potential candidate genes underlying QTLs using gene ontology analysis, including a leucine rich repeat receptor (LRR) and P-loop nucleoside triphosphate hydrolase, which have a role in pathogen recognition and disease resistance. Furthermore, four QTLs (Qsr.nbpgr-3B_11, QSr.nbpgr-6AS_11, QSr.nbpgr-2AL_117-6, and QSr.nbpgr-7BS_APR) were validated through KASP located on chromosomes 3B, 6A, 2A, and 7B. Out of these QTLs, QSr.nbpgr-7BS_APR was identified as a novel QTL for stem rust resistance which has been found effective in both seedling as well as the adult plant stages. Identified novel genomic regions and validated QTLs have the potential to be deployed in wheat improvement programs to develop disease resistant varieties for stem rust and can diversify the genetic basis of resistance.

Comparative expression analysis of water buffalo (Bubalus bubalis) to identify genes associated with economically important traits.

The milk, meat, skins, and draft power of domestic water buffalo (Bubalus bubalis) provide substantial contributions to the global agricultural economy. The world's water buffalo population is primarily found in Asia, and the buffalo supports more people per capita than any other livestock species. For evaluating the workflow, output rate, and completeness of transcriptome assemblies within and between reference-free (RF) de novo transcriptome and reference-based (RB) datasets, abundant bioinformatics studies have been carried out to date. However, comprehensive documentation of the degree of consistency and variability of the data produced by comparing gene expression levels using these two separate techniques is lacking. In the present study, we assessed the variations in the number of differentially expressed genes (DEGs) attained with RF and RB approaches. In light of this, we conducted a study to identify, annotate, and analyze the genes associated with four economically important traits of buffalo, viz., milk volume, age at first calving, post-partum cyclicity, and feed conversion efficiency. A total of 14,201 and 279 DEGs were identified in RF and RB assemblies. Gene ontology (GO) terms associated with the identified genes were allocated to traits under study. Identified genes improve the knowledge of the underlying mechanism of trait expression in water buffalo which may support improved breeding plans for higher productivity. The empirical findings of this study using RNA-seq data-based assembly may improve the understanding of genetic diversity in relation to buffalo productivity and provide important contributions to answer biological issues regarding the transcriptome of non-model organisms.

Comparative transcriptome profiling of near isogenic lines PBW343 and FLW29 to unravel defense related genes and pathways contributing to stripe rust resistance in wheat.

Stripe rust (Sr), caused by Puccinia striiformis f. sp. tritici (Pst), is the most devastating disease that poses serious threat to the wheat-growing nations across the globe. Developing resistant cultivars is the most challenging aspect in wheat breeding. The function of resistance genes (R genes) and the mechanisms by which they influence plant-host interactions are poorly understood. In the present investigation, comparative transcriptome analysis was carried out by involving two near-isogenic lines (NILs) PBW343 and FLW29. The seedlings of both the genotypes were inoculated with Pst pathotype 46S119. In total, 1106 differentially expressed genes (DEGs) were identified at early stage of infection (12 hpi), whereas expressions of 877 and 1737 DEGs were observed at later stages (48 and 72 hpi) in FLW29. The identified DEGs were comprised of defense-related genes including putative R genes, 7 WRKY transcriptional factors, calcium, and hormonal signaling associated genes. Moreover, pathways involved in signaling of receptor kinases, G protein, and light showed higher expression in resistant cultivar and were common across different time points. Quantitative real-time PCR was used to further confirm the transcriptional expression of eight critical genes involved in plant defense mechanism against stripe rust. The information about genes are likely to improve our knowledge of the genetic mechanism that controls the stripe rust resistance in wheat, and data on resistance response-linked genes and pathways will be a significant resource for future research.

Regulatory Networks of lncRNAs, miRNAs, and mRNAs in Response to Heat Stress in Wheat (Triticum Aestivum L.): An Integrated Analysis.

Climate change has become a major source of concern, particularly in agriculture, because it has a significant impact on the production of economically important crops such as wheat, rice, and maize. In the present study, an attempt has been made to identify differentially expressed heat stress-responsive long non-coding RNAs (lncRNAs) in the wheat genome using publicly available wheat transcriptome data (24 SRAs) representing two conditions, namely, control and heat-stressed. A total of 10,965 lncRNAs have been identified and, among them, 153, 143, and 211 differentially expressed transcripts have been found under 0 DAT, 1 DAT, and 4 DAT heat-stress conditions, respectively. Target prediction analysis revealed that 4098 lncRNAs were targeted by 119 different miRNA responses to a plethora of environmental stresses, including heat stress. A total of 171 hub genes had 204 SSRs (simple sequence repeats), and a set of target sequences had SNP potential as well. Furthermore, gene ontology analysis revealed that the majority of the discovered lncRNAs are engaged in a variety of cellular and biological processes related to heat stress responses. Furthermore, the modeled three-dimensional (3D) structures of hub genes encoding proteins, which had an appropriate range of similarity with solved structures, provided information on their structural roles. The current study reveals many elements of gene expression regulation in wheat under heat stress, paving the way for the development of improved climate-resilient wheat cultivars.