Uncovering DNA methylation landscapes to decipher evolutionary footprints of phenotypic diversity in chickpea.

Genetic diversity and environmental factors are long believed to be the dominant contributors to phenotypic diversity in crop plants. However, it has been recently established that, besides genetic variation, epigenetic variation, especially variation in DNA methylation, plays a significant role in determining phenotypic diversity in crop plants. Therefore, assessing DNA methylation diversity in crop plants becomes vital, especially in the case of crops like chickpea, which has a narrow genetic base. Thus, in the present study, we employed whole-genome bisulfite sequencing to assess DNA methylation diversity in wild and cultivated (desi and kabuli) chickpea. This revealed extensive DNA methylation diversity in both wild and cultivated chickpea. Interestingly, the methylation diversity was found to be significantly higher than genetic diversity, suggesting its potential role in providing vital phenotypic diversity for the evolution and domestication of the Cicer gene pool. The phylogeny based on DNA methylation variation also indicates a potential complementary role of DNA methylation variation in addition to DNA sequence variation in shaping chickpea evolution. Besides, the study also identified diverse epi-alleles of many previously known genes of agronomic importance. The Cicer MethVarMap database developed in this study enables researchers to readily visualize methylation variation within the genes and genomic regions of their interest (http://223.31.159.7/cicer/public/). Therefore, epigenetic variation like DNA methylation variation can potentially explain the paradox of high phenotypic diversity despite the narrow genetic base in chickpea and can potentially be employed for crop improvement.

Transcriptome-wide association mapping provides insights into the genetic basis and candidate genes governing flowering, maturity and seed weight in rice bean (Vigna umbellata).

BACKGROUND: Rice bean (Vigna umbellata), an underrated legume, adapts to diverse climatic conditions with the potential to support food and nutritional security worldwide. It is used as a vegetable, minor food crop and a fodder crop, being a rich source of proteins, minerals, and essential fatty acids. However, little effort has been made to decipher the genetic and molecular basis of various useful traits in this crop. Therefore, we considered three economically important traits i.e., flowering, maturity and seed weight of rice bean and identified the associated candidate genes employing an associative transcriptomics approach on 100 diverse genotypes out of 1800 evaluated rice bean accessions from the Indian National Genebank. RESULTS: The transcriptomics-based genotyping of one-hundred diverse rice bean cultivars followed by pre-processing of genotypic data resulted in 49,271 filtered markers. The STRUCTURE, PCA and Neighbor-Joining clustering of 100 genotypes revealed three putative sub-populations. The marker-trait association analysis involving various genome-wide association study (GWAS) models revealed significant association of 82 markers on 48 transcripts for flowering, 26 markers on 22 transcripts for maturity and 22 markers on 21 transcripts for seed weight. The transcript annotation provided information on the putative candidate genes for the considered traits. The candidate genes identified for flowering include HSC80, P-II PsbX, phospholipid-transporting-ATPase-9, pectin-acetylesterase-8 and E3-ubiquitin-protein-ligase-RHG1A. Further, the WRKY1 and DEAD-box-RH27 were found to be associated with seed weight. Furthermore, the associations of PIF3 and pentatricopeptide-repeat-containing-gene with maturity and seed weight, and aldo-keto-reductase with flowering and maturity were revealed. CONCLUSION: This study offers insights into the genetic basis of key agronomic traits in rice bean, including flowering, maturity, and seed weight. The identified markers and associated candidate genes provide valuable resources for future exploration and targeted breeding, aiming to enhance the agronomic performance of rice bean cultivars. Notably, this research represents the first transcriptome-wide association study in pulse crop, uncovering the candidate genes for agronomically useful traits.

The chickpea WIP2 gene underlying a major QTL contributes to lateral root development.

Lateral roots are a major component of root system architecture, and lateral root count (LRC) positively contributes to yield under drought in chickpea. To understand the genetic regulation of LRC, a biparental mapping population derived from two chickpea accessions having contrasting LRCs was genotyped by sequencing, and phenotyped to map four major quantitative trait loci (QTLs) contributing to 13-32% of the LRC trait variation. A single- nucleotide polymorphism tightly linked to the locus contributing to highest trait variation was located on the coding region of a gene (CaWIP2), orthologous to NO TRANSMITTING TRACT/WIP domain protein 2 (NTT/WIP2) gene of Arabidopsis thaliana. A polymorphic simple sequence repeat (SSR) in the CaWIP2 promoter showed differentiation between low versus high LRC parents and mapping individuals, suggesting its utility for marker-assisted selection. CaWIP2 promoter showed strong expression in chickpea apical root meristem and lateral root primordia. Expression of CaWIP2 under its native promoter in the Arabidopsis wip2wip4wip5 mutant rescued its rootless phenotype to produce more lateral roots than the wild-type plants, and led to formation of amyloplasts in the columella. CaWIP2 expression also induced the expression of genes that regulate lateral root emergence. Our study identified a gene-based marker for LRC which will be useful for developing drought-tolerant, high-yielding chickpea varieties.

Evolution of pathogenicity-associated genes in Rhizoctonia solani AG1-IA by genome duplication and transposon-mediated gene function alterations.

BACKGROUND: Rhizoctonia solani is a polyphagous fungal pathogen that causes diseases in crops. The fungal strains are classified into anastomosis groups (AGs); however, genomic complexity, diversification into the AGs and the evolution of pathogenicity-associated genes remain poorly understood. RESULTS: We report a recent whole-genome duplication and sequential segmental duplications in AG1-IA strains of R. solani. Transposable element (TE) clusters have caused loss of synteny in the duplicated blocks and introduced differential structural alterations in the functional domains of several pathogenicity-associated paralogous gene pairs. We demonstrate that the TE-mediated structural variations in a glycosyl hydrolase domain and a GMC oxidoreductase domain in two paralogous pairs affect the pathogenicity of R. solani. Furthermore, to investigate the association of TEs with the natural selection and evolution of pathogenicity, we sequenced the genomes of forty-two rice field isolates of R. solani AG1-IA. The genomic regions with high population mutation rates and with the lowest nucleotide diversity are enriched with TEs. Genetic diversity analysis predicted the genes that are most likely under diversifying and purifying selections. We present evidence that a smaller variant of a glucosamine phosphate N-acetyltransferase (GNAT) protein, predicted to be under purifying selection, and an LPMP_AA9 domain-containing protein, predicted to be under diversifying selection, are important for the successful pathogenesis of R. solani in rice as well as tomato. CONCLUSIONS: Our study has unravelled whole-genome duplication, TE-mediated neofunctionalization of genes and evolution of pathogenicity traits in R. solani AG1-IA. The pathogenicity-associated genes identified during the study can serve as novel targets for disease control.

An efficient registration-based approach for retinal blood vessel segmentation using generalized Pareto and fatigue pdf.

Segmentation of Retinal Blood Vessel (RBV) extraction in the retina images and Registration of segmented RBV structure is implemented to identify changes in vessel structure by ophthalmologists in diagnosis of various illnesses like Glaucoma, Diabetes, and Hypertension's. The Retinal Blood Vessel provides blood to the inner retinal neurons, RBV are located mainly in internal retina but it may partly in the ganglion cell layer, following network failure haven't been identified with past methods. Classifications of accurate RBV and Registration of segmented blood vessels are challenging tasks in the low intensity background of Retinal Image. So, we projected a novel approach of segmentation of RBV extraction used matched filter of Generalized Pareto Probability Distribution Function (pdf) and Registration approach on feature-based segmented retinal blood vessel of Binary Robust Invariant Scalable Key point (BRISK). The BRISK provides the predefined sampling pattern as compared to Pdf. The BRISK feature is implemented for attention point recognition & matching approach for change in vessel structure. The proposed approaches contain 3 levels: pre-processing, matched filter-based Generalized Pareto pdf as a source along with the novel approach of fatigue pdf as a target, and BRISK framework is used for Registration on segmented retinal images of supply & intention images. This implemented system's performance is estimated in experimental analysis by the Average accuracy, Normalized Cross-Correlation (NCC), and computation time process of the segmented retinal source and target image. The NCC is main element to give more statistical information about retinal image segmentation. The proposed approach of Generalized Pareto value pdf has Average Accuracy of 95.21%, NCC of both image pairs is 93%, and Average accuracy of Registration of segmented source images and the target image is 98.51% respectively. The proposed approach of average computational time taken is around 1.4 s, which has been identified on boundary condition of Pdf function.

Mutation in the Endo-ß-1,4-glucanase (KORRIGAN) Is Responsible for Thick Leaf Phenotype in Sorghum.

Sorghum [Sorghum bicolor (L.) Moench] is an important crop for food, feed, and fuel production. Particularly, sorghum is targeted for cellulosic ethanol production. Extraction of cellulose from cell walls is a key process in cellulosic ethanol production, and understanding the components involved in cellulose synthesis is important for both fundamental and applied research. Despite the significance in the biofuel industry, the genes involved in sorghum cell wall biosynthesis, modification, and degradation have not been characterized. In this study, we have identified and characterized three allelic thick leaf mutants (thl1, thl2, and thl3). Bulked Segregant Analysis sequencing (BSAseq) showed that the causal mutation for the thl phenotype is in endo-1,4-ß-glucanase gene (SbKOR1). Consistent with the causal gene function, the thl mutants showed decreased crystalline cellulose content in the stem tissues. The SbKOR1 function was characterized using Arabidopsis endo-1,4-ß-glucanase gene mutant (rsw2-1). Complementation of Arabidopsis with SbKOR1 (native Arabidopsis promoter and overexpression by 35S promoter) restored the radial swelling phenotype of rsw2-1 mutant, proving that SbKOR1 functions as endo-1,4-ß-glucanase. Overall, the present study has identified and characterized sorghum endo-1,4-ß-glucanase gene function, laying the foundation for future research on cell wall biosynthesis and engineering of sorghum for biofuel production.

Cysteine-rich antimicrobial peptides from plants: The future of antimicrobial therapy.

There has been a spurt in the spread of microbial resistance to antibiotics due to indiscriminate use of antimicrobial agents in human medicine, agriculture, and animal husbandry. It has been realized that conventional antibiotic therapy would be less effective in the coming decades and more emphasis should be given for the development of novel antiinfective therapies. Cysteine rich peptides (CRPs) are broad-spectrum antimicrobial agents that modulate the innate immune system of different life forms such as bacteria, protozoans, fungi, plants, insects, and animals. These are also expressed in several plant tissues in response to invasion by pathogens, and play a crucial role in the regulation of plant growth and development. The present work explores the importance of CRPs as potent antimicrobial agents, which can supplement and/or replace the conventional antibiotics. Different plant parts of diverse plant species showed the presence of antimicrobial peptides (AMPs), which had significant structural and functional diversity. The plant-derived AMPs exhibited potent activity toward a range of plant and animal pathogens, protozoans, insects, and even against cancer cells. The cysteine-rich AMPs have opened new avenues for the use of plants as biofactories for the production of antimicrobials and can be considered as promising antimicrobial drugs in biotherapeutics.

Biological Nanofactories: Using Living Forms for Metal Nanoparticle Synthesis.

Metal nanoparticles are nanosized entities with dimensions of 1-100 nm that are increasingly in demand due to applications in diverse fields like electronics, sensing, environmental remediation, oil recovery and drug delivery. Metal nanoparticles possess large surface energy and properties different from bulk materials due to their small size, large surface area with free dangling bonds and higher reactivity. High cost and pernicious effects associated with the chemical and physical methods of nanoparticle synthesis are gradually paving the way for biological methods due to their eco-friendly nature. Considering the vast potentiality of microbes and plants as sources, biological synthesis can serve as a green technique for the synthesis of nanoparticles as an alternative to conventional methods. A number of reviews are available on green synthesis of nanoparticles but few have focused on covering the entire biological agents in this process. Therefore present paper describes the use of various living organisms like bacteria, fungi, algae, bryophytes and tracheophytes in the biological synthesis of metal nanoparticles, the mechanisms involved and the advantages associated therein.

Fréchet PDF based Matched Filter Approach for Retinal Blood Vessels Segmentation.

BACKGROUND AND OBJECTIVE: Retinal pathology diseases such as glaucoma, obesity, diabetes, hypertension etc. have deadliest impact on life of human being today. Retinal blood vessels consist of various significant information which are helpful in detection and treatment of these diseases. Therefore, it is essential to segment these retinal vessels. Various matched filter approaches for segmentation of retinal blood vessels are reported in the literature but their kernel templates are not appropriate to vessel profile resulting poor performance. To overcome this, a novel matched filter approach based on Fréchet probability distribution function has been proposed. METHODS: Image processing operations which we have used in the proposed approach are basically divided into three major stages viz; pre processing, Fréchet matched filter and post processing. In pre processing, principle component analysis (PCA) method is used to convert color image into grayscale image thereafter contrast limited adaptive histogram equalization (CLAHE) is applied on obtained grayscale to get enhanced grayscale image. In Fréchet matched filter, exhaustive experimental tests are conducted to choose optimal values for both Fréchet function parameters and matched filter parameters to design new matched filter. In post processing, entropy based optimal thresholding technique is applied on obtained MFR image to get binary image followed by length filtering and masking methods are applied to generate to a clear and whole vascular tree. RESULTS: For evaluation of the proposed approach, quantitative performance metrics such as average specificity, average sensitivity and average accuracy and root mean square deviation (RMSD) are computed in the literature. We found the average specificity 97.24%, average sensitivity 72.78%, average accuracy 95.09% for STARE dataset while average specificity 97.61%, average sensitivity 73.07%, average accuracy 95.44% for DRIVE dataset. Average RMSD values are found 0.07 and 0.04 for STARE and DRIVE databases respectively. CONCLUSIONS: From experimental results, it can be observed that our proposed approach outperforms over latest and prominent works reported in the literature. The cause of improved performance is due to better matching between vessel profile and Fréchet template.

Root-specific expression of chickpea cytokinin oxidase/dehydrogenase 6 leads to enhanced root growth, drought tolerance and yield without compromising nodulation.

Cytokinin group of phytohormones regulate root elongation and branching during post-embryonic development. Cytokinin-degrading enzymes cytokinin oxidases/dehydrogenases (CKXs) have been deployed to investigate biological activities of cytokinin and to engineer root growth. We expressed chickpea cytokinin oxidase 6 (CaCKX6) under the control of a chickpea root-specific promoter of CaWRKY31 in Arabidopsis thaliana and chickpea having determinate and indeterminate growth patterns, respectively, to study the effect of cytokinin depletion on root growth and drought tolerance. Root-specific expression of CaCKX6 led to a significant increase in lateral root number and root biomass in Arabidopsis and chickpea without any penalty to vegetative and reproductive growth of shoot. Transgenic chickpea lines showed increased CKX activity in root. Soil-grown advanced chickpea transgenic lines exhibited higher root-to-shoot biomass ratio and enhanced long-term drought tolerance. These chickpea lines were not compromised in root nodulation and nitrogen fixation. The seed yield in some lines was up to 25% higher with no penalty in protein content. Transgenic chickpea seeds possessed higher levels of zinc, iron, potassium and copper. Our results demonstrated the potential of cytokinin level manipulation in increasing lateral root number and root biomass for agronomic trait improvement in an edible legume crop with indeterminate growth habit.

Retinal blood vessels segmentation by using Gumbel probability distribution function based matched filter.

BACKGROUND AND OBJECTIVE: Retinal blood vessel segmentation is a prominent task for the diagnosis of various retinal pathology such as hypertension, diabetes, glaucoma, etc. In this paper, a novel matched filter approach with the Gumbel probability distribution function as its kernel is introduced to improve the performance of retinal blood vessel segmentation. METHODS: Before applying the proposed matched filter, the input retinal images are pre-processed. During pre-processing stage principal component analysis (PCA) based gray scale conversion followed by contrast limited adaptive histogram equalization (CLAHE) are applied for better enhancement of retinal image. After that an exhaustive experiments have been conducted for selecting the appropriate value of parameters to design a new matched filter. The post-processing steps after applying the proposed matched filter include the entropy based optimal thresholding and length filtering to obtain the segmented image. RESULTS: For evaluating the performance of proposed approach, the quantitative performance measures, an average accuracy, average true positive rate (ATPR), and average false positive rate (AFPR) are calculated. The respective values of the quantitative performance measures are 0.9522, 0.7594, 0.0292 for DRIVE data set and 0.9270, 0.7939, 0.0624 for STARE data set. To justify the effectiveness of proposed approach, receiver operating characteristic (ROC) curve is plotted and the average area under the curve (AUC) is calculated. The average AUC for DRIVE and STARE data sets are 0.9287 and 0.9140 respectively. CONCLUSIONS: The obtained experimental results confirm that the proposed approach performance better with respect to other prominent Gaussian distribution function and Cauchy PDF based matched filter approaches.