A multi-cell model for the C4 photosynthetic pathway in developing wheat grains based upon tissue-specific transcriptome data.

A non-Kranz C4 photosynthesis of the NAD-ME subtype, specifically in developing wheat grains (14 dpa, days post-anthesis) was originally demonstrated using transcriptome-based RNA-seq. Here we present a re-examination of evidence for C4 photosynthesis in the developing grains of wheat and, more broadly, the Pooideae and an investigation of the evolutionary processes and implications. The expression profiles for the genes associated with C4 photosynthesis (C4- and C3-specific) were evaluated using published transcriptome data for the outer pericarp, inner pericarp, and endosperm tissues of the developing wheat grains. The expression of the C4-specific genes across these three tissues revealed the involvement of all three tissues in an orderly fashion to accomplish the non-Kranz NAD-ME-dependent C4 photosynthesis. Based on their expression levels in RPKM (reads per kilobase per million mapped reads) values, a model involving multiple cell- and tissue-types is proposed for C4 photosynthesis involved in the refixation of the respired CO2 from the endosperm tissues in the developing wheat grains. This multi-cell C4 model, proposed to involve more than two cell types, requires further biochemical validation.

Rhizobacteria Bacillus spp. mitigate osmotic stress and improve seed germination in mustard by regulating osmolyte and plant hormone signaling.

Drought, a widespread abiotic stressor, exerts a profound impact on agriculture, impeding germination and plant growth, and reducing crop yields. In the present investigation, the osmotolerant rhizobacteria Bacillus casamancensis strain MKS-6 and Bacillus sp. strain MRD-17 were assessed for their effects on molecular processes involved in mustard germination under osmotic stress conditions. Enhancement in germination was evidenced by improved germination percentages, plumule and radicle lengths, and seedling vigor upon rhizobacterial inoculation under no stress and osmotic stress conditions. Under osmotic stress, rhizobacteria stimulated the production of gibberellins and reserve hydrolytic enzymes (lipases, isocitrate lyase, and malate synthase), bolstering germination. Furthermore, these rhizobacteria influenced the plant hormones such as gibberellins and abscisic acid (ABA), as well as signalling pathways, thereby promoting germination under osmotic stress. Reduced proline and glycine betaine accumulation, and down-regulation of transcription factors BjDREB1_2 and BjDREB2 (linked to ABA-independent signalling) in rhizobacteria-inoculated seedlings indicated that bacterial treatment mitigated water deficit stress during germination, independently of these pathways. Hence, the advantageous attributes exhibited by these rhizobacterial strains can be effectively harnessed to alleviate drought-induced stress in mustard crops, potentially through the development of targeted bio-formulations.

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.

A Versatile Protocol for Efficient Transformation and Regeneration in Mega Indica Rice Cultivar MTU1010: Optimization through Hormonal Variables.

Rice is one of the apex food crops in terms of meeting the daily calorific and dietary requirement of the majority of the world population. However, rice productivity is severely limited by various biotic and abiotic attributes, causing a severe threat to global food security. In the use of functional genomics and genome editing for the generation of trait-enhanced genotypes, it is necessary to have an efficient genetic transformation and regeneration protocol. The recalcitrant nature and paucity of efficient and versatile genetic transformation and regeneration protocols for indica cultivars remains a constraint. In the present study, we have optimized a tissue culture method for MTU1010, a mega indica rice variety. We conducted a combinatorial analysis of different plant growth regulators on embryogenic callus induction efficiency, and it was observed that MSB5 medium supplemented with 2.5 mg/L 2-4D and 0.25 mg/L 6-BAP results in maximum embryogenic callus induction, i.e., 92%. The regeneration efficiency of a transformed callus can be enhanced by up to 50% with the supplementation of 1 mg/L kinetin alongside 2.5 mg/L BAP and 0.5 mg/L NAA in the shooting medium. Furthermore, our results unveiled that the pre-activation of Agrobacterium culture for 30 min with 150 µM acetosyringone significantly increased the transformation efficiency of calli. Additionally, descaling the salt concentration to half strength in resuspension and co-cultivation increased the efficiency of transformation up to 33%. Thus, the protocol developed in this study will be instrumental for the genome editing and genetic engineering of indica rice cultivars for functional genomics studies and crop improvement.

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.

Image-based phenotyping of seed architectural traits and prediction of seed weight using machine learning models in soybean.

Among seed attributes, weight is one of the main factors determining the soybean harvest index. Recently, the focus of soybean breeding has shifted to improving seed size and weight for crop optimization in terms of seed and oil yield. With recent technological advancements, there is an increasing application of imaging sensors that provide simple, real-time, non-destructive, and inexpensive image data for rapid image-based prediction of seed traits in plant breeding programs. The present work is related to digital image analysis of seed traits for the prediction of hundred-seed weight (HSW) in soybean. The image-based seed architectural traits (i-traits) measured were area size (AS), perimeter length (PL), length (L), width (W), length-to-width ratio (LWR), intersection of length and width (IS), seed circularity (CS), and distance between IS and CG (DS). The phenotypic investigation revealed significant genetic variability among 164 soybean genotypes for both i-traits and manually measured seed weight. Seven popular machine learning (ML) algorithms, namely Simple Linear Regression (SLR), Multiple Linear Regression (MLR), Random Forest (RF), Support Vector Regression (SVR), LASSO Regression (LR), Ridge Regression (RR), and Elastic Net Regression (EN), were used to create models that can predict the weight of soybean seeds based on the image-based novel features derived from the Red-Green-Blue (RGB)/visual image. Among the models, random forest and multiple linear regression models that use multiple explanatory variables related to seed size traits (AS, L, W, and DS) were identified as the best models for predicting seed weight with the highest prediction accuracy (coefficient of determination, R2=0.98 and 0.94, respectively) and the lowest prediction error, i.e., root mean square error (RMSE) and mean absolute error (MAE). Finally, principal components analysis (PCA) and a hierarchical clustering approach were used to identify IC538070 as a superior genotype with a larger seed size and weight. The identified donors/traits can potentially be used in soybean improvement programs.

Functional analysis of a susceptibility gene (HIPP27) in the Arabidopsis thaliana-Meloidogyne incognita pathosystem by using a genome editing strategy.

BACKGROUND: Plant-parasitic root-knot nematodes cause immense yield declines in crop plants that ultimately obviate global food security. They maintain an intimate relationship with their host plants and hijack the host metabolic machinery to their own advantage. The existing resistance breeding strategies utilizing RNAi and resistance (R) genes might not be particularly effective. Alternatively, knocking out the susceptibility (S) genes in crop plants appears to be a feasible approach, as the induced mutations in S genes are likely to be long-lasting and may confer broad-spectrum resistance. This could be facilitated by the use of CRISPR/Cas9-based genome editing technology that precisely edits the gene of interest using customizable guide RNAs (gRNAs) and Cas9 endonuclease. RESULTS: Initially, we characterized the nematode-responsive S gene HIPP27 from Arabidopsis thaliana by generating HIPP27 overexpression lines, which were inoculated with Meloidogyne incognita. Next, two gRNAs (corresponding to the HIPP27 gene) were artificially synthesized using laboratory protocols, sequentially cloned into a Cas9 editor plasmid, mobilized into Agrobacterium tumefaciens strain GV3101, and transformed into Arabidopsis plants using the floral dip method. Apart from 1-3 bp deletions and 1 bp insertions adjacent to the PAM site, a long deletion of approximately 161 bp was documented in the T0 generation. Phenotypic analysis of homozygous, 'transgene-free' T2 plants revealed reduced nematode infection compared to wild-type plants. Additionally, no growth impairment was observed in gene-edited plants. CONCLUSION: Our results suggest that the loss of function of HIPP27 in A. thaliana by CRISPR/Cas9-induced mutagenesis can improve host resistance to M. incognita.

Phenomics based prediction of plant biomass and leaf area in wheat using machine learning approaches.

Introduction: Phenomics has emerged as important tool to bridge the genotype-phenotype gap. To dissect complex traits such as highly dynamic plant growth, and quantification of its component traits over a different growth phase of plant will immensely help dissect genetic basis of biomass production. Based on RGB images, models have been developed to predict biomass recently. However, it is very challenging to find a model performing stable across experiments. In this study, we recorded RGB and NIR images of wheat germplasm and Recombinant Inbred Lines (RILs) of Raj3765xHD2329, and examined the use of multimodal images from RGB, NIR sensors and machine learning models to predict biomass and leaf area non-invasively. Results: The image-based traits (i-Traits) containing geometric features, RGB based indices, RGB colour classes and NIR features were categorized into architectural traits and physiological traits. Total 77 i-Traits were selected for prediction of biomass and leaf area consisting of 35 architectural and 42 physiological traits. We have shown that different biomass related traits such as fresh weight, dry weight and shoot area can be predicted accurately from RGB and NIR images using 16 machine learning models. We applied the models on two consecutive years of experiments and found that measurement accuracies were similar suggesting the generalized nature of models. Results showed that all biomass-related traits could be estimated with about 90% accuracy but the performance of model BLASSO was relatively stable and high in all the traits and experiments. The R2 of BLASSO for fresh weight prediction was 0.96 (both year experiments), for dry weight prediction was 0.90 (Experiment 1) and 0.93 (Experiment 2) and for shoot area prediction 0.96 (Experiment 1) and 0.93 (Experiment 2). Also, the RMSRE of BLASSO for fresh weight prediction was 0.53 (Experiment 1) and 0.24 (Experiment 2), for dry weight prediction was 0.85 (Experiment 1) and 0.25 (Experiment 2) and for shoot area prediction 0.59 (Experiment 1) and 0.53 (Experiment 2). Discussion: Based on the quantification power analysis of i-Traits, the determinants of biomass accumulation were found which contains both architectural and physiological traits. The best predictor i-Trait for fresh weight and dry weight prediction was Area_SV and for shoot area prediction was projected shoot area. These results will be helpful for identification and genetic basis dissection of major determinants of biomass accumulation and also non-invasive high throughput estimation of plant growth during different phenological stages can identify hitherto uncovered genes for biomass production and its deployment in crop improvement for breaking the yield plateau.

Targeting Induced Local Lesions in Genomes (TILLING): advances and opportunities for fast tracking crop breeding.

The intensification of food production via conventional crop breeding alone is inadequate to cater for global hunger. The development of precise and expeditious high throughput reverse genetics approaches has hugely benefited modern plant breeding programs. Targeting Induced Local Lesions in Genomes (TILLING) is one such reverse genetics approach which employs chemical/physical mutagenesis to create new genetic sources and identifies superior/novel alleles. Owing to technical limitations and sectional applicability of the original TILLING protocol, it has been timely modified. Successions include: EcoTILLING, Double stranded EcoTILLING (DEcoTILLING), Self-EcoTILLING, Individualized TILLING (iTILLING), Deletion-TILLING (De-TILLING), PolyTILLING, and VeggieTILLING. This has widened its application to a variety of crops and needs. They can characterize mutations in coding as well as non-coding regions and can overcome complexities associated with the large genomes. Combining next generation sequencing tools with the existing TILLING protocols has enabled screening of huge germplasm collections and mutant populations for the target genes. In silico TILLING platforms have transformed TILLING into an exciting breeding approach. The present review outlines these multifarious TILLING modifications for precise mutation detection and their application in advance breeding programmes together with relevant case studies. Appropriate use of these protocols will open up new avenues for crop improvement in the twenty first century.

Nitrate supply regulates tissue calcium abundance and transcript level of Calcineurin B-like (CBL) gene family in wheat.

Calcium ion (Ca2+) is the most ubiquitous signalling molecule and is sensed by different classes of Ca2+ sensor proteins. Recent evidences underscore the role of calcium signalling in plant response to nitrogen/nitrate supply. Recently we found that under nitrate deficiency, a short-term supply of calcium could improve the plant biomass, nitrate assimilation, anthocyanin accumulation and expression of nitrate uptake and signalling genes. Long-term calcium supply, on the other hand, was not beneficial. Calcineurin B-like (CBL) proteins are one of the vital plant Ca2+ sensory protein family which is essential for stress perception and signaling. To understand the dynamics of CBL-mediated stress signalling in bread wheat, we identified CBL genes in bread wheat (Triticum aestivum) and its progenitors, namely Triticum dicoccoides, Triticum urartu and Aegilops tauschii with the aid of newly available whole-genome sequence. The expression of different CBLs and the changes in root Ca2+ localization in response to nitrate provision or deficiency were analysed. Expression of the CBLs were studied in two bread wheat genotypes with comparatively higher (B.T. Schomburgk, BTS) and lower (Gluyas early, GE) nitrate responsiveness and nitrogen use efficiency. High N promoted the expression of CBLs in seedling leaves while in roots the expression was promoted by N deficiency. At the 5 days after anthesis stage, nitrate starvation downregulated the expression of CBLs while nitrate supply enhanced the expression. At anthesis stage, expression of CBL6 was significantly promoted by HN in panicles of both the genotypes, the highest expression was recorded in BTS. Expression of CBL6 was significantly upregulated by short term nitrate treatment also suggesting its role in Primary nitrate response (PNR) in wheat. There was a significant down regulation of CBL6 expression post nitrate starvation, making it a probable regulator of nitrogen starvation response (NSR) as well. In seedling roots, the tissue localization of Ca2+ was increased both by high and low nitrate treatments, albeit at different magnitudes. Our results suggest that calcium signalling might be a major signalling pathway governing nitrogen responsiveness and CBL6 might be playing pivotal role in NSR and PNR in wheat.

Influence of Thermotolerant Rhizobacteria Bacillus spp. on Biochemical Attributes and Antioxidant Status of Mustard Under High Temperature Stress.

Due to global warming, increasing incidences of higher-than-normal temperatures have been observed, which adversely affect seed germination, crop growth, and productivity. Several reports are available on the effect of inoculation with rhizobacteria on plant growth and biochemical attributes; however, information on their influence on seed germination and plant stress levels is lacking. In the present study, under heat stress, we studied the effect of three thermotolerant rhizobacterial strains on mustard seed germination, seedling vigor, and plant growth. Effect of inoculation with the rhizobacterial strains on the plant stress levels, biochemical attributes and antioxidant activity was also determined. Under heat stress, inoculation with the rhizobacterial strains improved seed germination and seedling fresh weight and plumule length; while only Bacillus licheniformis SSA 61 inoculated plants showed better radicle length. There was a concomitant decrease in the plant ethylene levels in the inoculated treatments. Inoculated plants showed higher shoot fresh weight, however, Bacillus sp. MRD-17 inoculated plants only improved root growth. There was significant increase in most of the plant biochemical parameters and activities of antioxidant enzymes superoxide dismutase, catalase, and ascorbate peroxidase. Significant reduction in proline and total sugar content was noted in the inoculated treatments; while increase in the amino acid and phenolics content was observed. A further increase in the antioxidant enzyme activity was recorded in most of the inoculated treatments compared with no stress. Thus, our study indicated that thermotolerant rhizobacterial strains reduced plant stress levels; enhanced seed germination, seedling vigor, plant biomass, and thermotolerance of mustard.

Elucidating the role of key physio-biochemical traits and molecular network conferring heat stress tolerance in cucumber.

Cucumber is an important vegetable crop grown worldwide and highly sensitive to prevailing temperature condition. The physiological, biochemical and molecular basis of high temperature stress tolerance is poorly understood in this model vegetable crop. In the present study, a set of genotypes with contrasting response under two different temperature stress (35/30°C and 40/35°C) were evaluated for important physiological and biochemical traits. Besides, expression of the important heat shock proteins (HSPs), aquaporins (AQPs), photosynthesis related genes was conducted in two selected contrasting genotypes at different stress conditions. It was established that tolerant genotypes were able to maintain high chlorophyll retention, stable membrane stability index, higher retention of water content, stability in net photosynthesis, high stomatal conductance and transpiration in combination with less canopy temperatures under high temperature stress conditions compared to susceptible genotypes and were considered as the key physiological traits associated with heat tolerance in cucumber. Accumulation of biochemicals like proline, protein and antioxidants like SOD, catalase and peroxidase was the underlying biochemical mechanisms for high temperature tolerance. Upregulation of photosynthesis related genes, signal transduction genes and heat responsive genes (HSPs) in tolerant genotypes indicate the molecular network associated with heat tolerance in cucumber. Among the HSPs, higher accumulation of HSP70 and HSP90 were recorded in the tolerant genotype, WBC-13 under heat stress condition indicating their critical role. Besides, Rubisco S, Rubisco L and CsTIP1b were upregulated in the tolerant genotypes under heat stress condition. Therefore, the HSPs in combination with photosynthetic and aquaporin genes were the underlying important molecular network associated with heat stress tolerance in cucumber. The findings of the present study also indicated negative feedback of G-protein alpha unit and oxygen evolving complex in relation to heat stress tolerance in cucumber. These results indicate that the thermotolerant cucumber genotypes enhanced physio-biochemical and molecular adaptation under high-temperature stress condition. This study provides foundation to design climate smart genotypes in cucumber through integration of favorable physio-biochemical traits and understanding the detailed molecular network associated with heat stress tolerance in cucumber.

Long term nitrogen deficiency alters expression of miRNAs and alters nitrogen metabolism and root architecture in Indian dwarf wheat (Triticum sphaerococcum Perc.) genotypes.

The important roles of plant microRNAs (miRNAs) in adaptation to nitrogen (N) deficiency in different crop species especially cereals (rice, wheat, maize) have been under discussion since last decade with little focus on potential wild relatives and landraces. Indian dwarf wheat (Triticum sphaerococcum Percival) is an important landrace native to the Indian subcontinent. Several unique features, especially high protein content and resistance to drought and yellow rust, make it a very potent landrace for breeding. Our aim in this study is to identify the contrasting Indian dwarf wheat genotypes based on nitrogen use efficiency (NUE) and nitrogen deficiency tolerance (NDT) traits and the associated miRNAs differentially expressed under N deficiency in selected genotypes. Eleven Indian dwarf wheat genotypes and a high NUE bread wheat genotype (for comparison) were evaluated for NUE under control and N deficit field conditions. Based on NUE, selected genotypes were further evaluated under hydroponics and miRNome was compared by miRNAseq under control and N deficit conditions. Among the identified, differentially expressed miRNAs in control and N starved seedlings, the target gene functions were associated with N metabolism, root development, secondary metabolism and cell-cycle associated pathways. The key findings on miRNA expression, changes in root architecture, root auxin abundance and changes in N metabolism reveal new information on the N deficiency response of Indian dwarf wheat and targets for genetic improvement of NUE.

Spectral characterization and severity assessment of rice blast disease using univariate and multivariate models.

Rice is the staple food of more than half of the population of the world and India as well. One of the major constraints in rice production is frequent occurrence of pests and diseases and one of them is rice blast which often causes yield loss varying from 10 to 30%. Conventional approaches for disease assessment are time-consuming, expensive, and not real-time; alternately, sensor-based approach is rapid, non-invasive and can be scaled up in large areas with minimum time and effort.  In the present study, hyperspectral remote sensing for the characterization and severity assessment of rice blast disease was exploited. Field experiments were conducted with 20 genotypes of rice having sensitive and resistant cultivars grown under upland and lowland conditions at Almora, Uttarakhand, India. The severity of the rice blast was graded from 0 to 9 in accordance to International Rice Research Institute (IRRI).  Spectral observations in field were taken using a hand-held portable spectroradiometer in range of 350-2500 nm followed by spectral discrimination of different disease severity levels using Jeffires-Matusita (J-M) distance. Then, evaluation of 26 existing spectral indices (r≥0.8) was done corresponding to blast severity levels and linear regression prediction models were also developed. Further, the proposed ratio blast index (RBI) and normalized difference blast index (NDBI) were developed using all possible combinations of their correlations with severity level followed by their quantification to identify the best indices. Thereafter, multivariate models like support vector machine regression (SVM), partial least squares (PLS), random forest (RF), and multivariate adaptive regression spline (MARS) were also used to estimate blast severity. Jeffires-Matusita distance was separating almost all severity levels having values >1.92 except levels 4 and 5. The 26 prediction models were effective at predicting blast severity with R2 values from 0.48 to 0.85. The best developed spectral indices for rice blast were RBI (R1148, R1301) and NDBI (R1148, R1301) with R2 of 0.85 and 0.86, respectively. Among multivariate models, SVM was the best model with calibration R2=0.99; validation R2=0.94, RMSE=0.7, and RPD=4.10. The methodology developed paves way for early detection and large-scale monitoring and mapping using satellite remote sensors at farmers' fields for developing better disease management options.

Variation in nitrogen partitioning and reproductive stage nitrogen remobilization determines nitrogen grain production efficiency (NUEg) in diverse rice genotypes under varying nitrogen supply.

Nitrogen (N) is an important macronutrient needed for grain yield, grain N and grain protein content in rice. Grain yield and quality are significantly determined by N availability. In this study, to understand the mechanisms associated with reproductive stage N remobilization and N partitioning to grain 2 years of field experiments were conducted with 30 diverse rice genotypes during 2019-Kharif and 2020-Kharif seasons. The experiments were conducted with two different N treatments; N deficient (N0-no external N application, available soil N; 2019-234.15 kgha-1, 2020-225.79 kgha-1) and N sufficient (N120-120 kgha-1 external N application, available soil N; 2019-363.77 kgha-1, 2020-367.95 kgha-1). N application increased the NDVI value, biomass accumulation, grain yield, harvest index and grain N accumulation. Post-anthesis N uptake and N remobilization from vegetative tissues to grain are critical for grain yield and N harvest index. Rice genotypes, Kalinga-1, BAM-4234, IR-8384-B-B102-3, Sahbhagi Dhan, BVD-109 and Nerica-L-42 showed a higher rate of N remobilization under N sufficient conditions. But, under N deficiency, rice genotypes-83929-B-B-291-3-1-1, BVD-109, IR-8384-B-B102-3 and BAM-4234 performed well showing higher N remobilization efficiency. The total amount of N remobilization was recorded to be high in the N120 treatment. The harvest index was higher in N120 during both the cropping seasons. RANBIR BASMATI, BAM-832, APO, BAM-247, IR-64, Vandana, and Nerica-L-44 were more efficient in N grain production efficiency under N deficient conditions. From this study, it is evident that higher grain N accumulation is not always associated with higher yield. IR-83929-B-B-291-3-1-1, Kalinga-1, APO, Pusa Basmati-1, and Nerica-L-44 performed well for different N use efficiency component traits under both N deficient (N0) and N sufficient (N120) conditions. Identifying genotypes/donors for N use efficiency-component traits is crucial in improving the fertilizer N recovery rate and site specific N management.

Molecular mapping of genomic regions and identification of possible candidate genes associated with gynoecious sex expression in bitter gourd.

Bitter gourd is an important vegetable crop grown throughout the tropics mainly because of its high nutritional value. Sex expression and identification of gynoecious trait in cucurbitaceous vegetable crops has facilitated the hybrid breeding programme in a great way to improve productivity. In bitter gourd, gynoecious sex expression is poorly reported and detailed molecular pathways involve yet to be studied. The present experiment was conducted to study the inheritance, identify the genomic regions associated with gynoecious sex expression and to reveal possible candidate genes through QTL-seq. Segregation for the gynoecious and monoecious sex forms in the F2 progenies indicated single recessive gene controlling gynoecious sex expression in the genotype, PVGy-201. Gynoecious parent, PVGy-201, Monoecious parent, Pusa Do Mausami (PDM), and two contrasting bulks were constituted for deep-sequencing. A total of 10.56, 23.11, 15.07, and 19.38 Gb of clean reads from PVGy-201, PDM, gynoecious bulk and monoecious bulks were generated. Based on the ΔSNP index, 1.31 Mb regions on the chromosome 1 was identified to be associated with gynoecious sex expression in bitter gourd. In the QTL region 293,467 PVGy-201 unique variants, including SNPs and indels, were identified. In the identified QTL region, a total of 1019 homozygous variants were identified between PVGy1 and PDM genomes and 71 among them were non-synonymous variants (SNPS and INDELs), out of which 11 variants (7 INDELs, 4 SNPs) were classified as high impact variants with frame shift/stop gain effect. In total twelve genes associated with male and female gametophyte development were identified in the QTL-region. Ethylene-responsive transcription factor 12, Auxin response factor 6, Copper-transporting ATPase RAN1, CBL-interacting serine/threonine-protein kinase 23, ABC transporter C family member 2, DEAD-box ATP-dependent RNA helicase 1 isoform X2, Polygalacturonase QRT3-like isoform X2, Protein CHROMATIN REMODELING 4 were identified with possible role in gynoecious sex expression. Promoter region variation in 8 among the 12 genes indicated their role in determining gynoecious sex expression in bitter gourd genotype, DBGy-1. The findings in the study provides insight about sex expression in bitter gourd and will facilitate fine mapping and more precise identification of candidate genes through their functional validation.

Disentangling the Roles of Plant Water Status and Stem Carbohydrate Remobilization on Rice Harvest Index Under Drought.

BACKGROUND: Harvest index is an important component of grain yield and is typically reduced by reproductive stage drought stress in rice. Multiple drought response mechanisms can affect harvest index including plant water status and the degree of stem carbohydrate mobilization during grain filling. In this study, we aimed to dissect the contributions of plant water status and stem carbohydrate mobilization to harvest index. Pairs of genotypes selected for contrasting harvest index but similar biomass and days to flowering were characterized at ICAR-RCER, Patna, India and at IRRI, Philippines. RESULTS: Multiple traits were related with harvest index across experiments, including mobilization efficiency at both sites as indicated by groupings in principal component analysis, and plant water status as indicated by direct correlations. Biomass-related traits were positively correlated with harvest index at IRRI but biomass was negatively correlated with harvest index at ICER-RCER, Patna. We observed that some pairs of genotypes showed differences in harvest index across environments, whereas other showed differences in harvest index only under drought. Of all time points measured when all genotypes were considered together, the stem carbohydrate levels at maturity were most consistently (negatively) correlated with harvest index under drought, but not under well-watered conditions. However, in the pairs of genotypes grouped as those whose differences in harvest index were stable across environments, improved plant water status resulted in a greater ability to both accumulate and remobilize stored carbohydrate, i.e. starch. CONCLUSION: By distinguishing between genotypes whose harvest index was improved across conditions as opposed to specifically under drought, we can attribute the mechanisms behind the stable high-harvest index genotypes to be more related to stem carbohydrate remobilization than to plant water status. The stable high-harvest index lines in this study (Aus 257 and Wanni Dahanala) may confer mechanisms to improve harvest index that are independent of drought response and therefore may be useful for breeding improved rice varieties.

Hydrogen Peroxide and GA3 Levels Regulate the High Night Temperature Response in Pistils of Wheat (Triticum aestivum L.).

High night temperature (HNT) impairs crop productivity through the reproductive failure of gametes (pollen and pistil). Though female gametophyte (pistil) is an equal partner in the seed-set, the knowledge of the antioxidant system(s) and hormonal control of HNT tolerance or susceptibility of pistils is limited and lacking. The objectives of this study were to determine the antioxidant mechanism for homeostatic control of free radicals, and the involvement of abscisic acid (ABA) and gibberellic acid (GA3) in HNT stress protection in the wheat pistils of contrasting wheat genotypes. We hypothesized that HNT tolerance is attributed to the homeostatic control of reactive oxygen species (ROS) and hormonal readjustment in pistils of the tolerant genotype. The ears of two contrasting wheat genotypes-HD 2329 (susceptible) and Raj 3765 (tolerant) were subjected to two HNTs (+5 °C and +8 °C) over ambient, in the absence and presence of dimethylthiourea (DMTU), a chemical trap of hydrogen peroxide (H2O2). Results showed that HNTs significantly increased ROS in pistils of susceptible genotype HD 2329 to a relatively greater extent compared to tolerant genotype Raj 3765. The response was similar in the presence or absence of DMTU, but the H2O2 values were lower in the presence of DMTU. The ROS levels were balanced by increased activity of peroxidase under HNT to a greater extent in the tolerant genotype. Cytosolic glyceraldehyde-3-phosphate dehydrogenase (GAPC) activity was inversely related to H2O2 production within a critical range in Raj 3765, indicating its modulation by H2O2 levels as no change was observed at the transcriptional level. The hormonal status showed increased ABA and decreased GA3 contents with increasing temperature. Our study elucidates the role of H2O2 and GA3 in stress tolerance of pistils of tolerant genotype where GAPC acts as a ROS sensor due to H2O2-mediated decrease in its activity.

Unravelling structural, functional, evolutionary and genetic basis of SWEET transporters regulating abiotic stress tolerance in maize.

Sugars Will Eventually be Exported Transporters (SWEETs) are the novel sugar transporters widely distributed among living systems. SWEETs play a crucial role in various bio-physiological processes, viz., plant developmental, nectar secretion, pollen development, and regulation of biotic and abiotic stresses, in addition to their prime sugar-transporting activity. Thus, in-depth structural, evolutionary, and functional characterization of maize SWEET transporters was performed for their utility in maize improvement. The mining of SWEET genes in the latest maize genome release (v.5) showed an uneven distribution of 20 ZmSWEETs. The comprehensive structural analyses and docking of ZmSWEETs with four sugars, viz., fructose, galactose, glucose, and sucrose, revealed frequent amino acid residues forming hydrogen (asparagine, valine, serine) and hydrophobic (tryptophan, glycine, and phenylalanine) interactions. Evolutionary analyses of SWEETs showed a mixed lineage with 50-100 % commonality of ortho-groups and -sequences evolved under strong purifying selection (Ka/Ks < 0.5). The duplication analysis showed non-functionalization (ZmSWEET18 in B73) and neo- and sub-functionalization (ZmSWEET3, ZmSWEET6, ZmSWEET9, ZmSWEET19, and ZmSWEET20) events in maize. Functional analyses of ZmSWEET genes through co-expression, in silico expression and qRT-PCR assays showed the relevance of ZmSWEETs expression in regulating drought, heat, and waterlogging stress tolerances in maize. The first ever ZmSWEET-regulatory network revealed 286 direct (ZmSWEET-TF: 140 ZmSWEET-miRNA: 146) and 1226 indirect (TF-TF: 597; TF-miRNA: 629) edges. The present investigation has given new insights into the complex transcriptional and post-transcriptional regulation and the regulatory and functional relevance of ZmSWEETs in assigning stress tolerance in maize.