Exploring Genetic Diversity within aus Rice Germplasm: Insights into the Variations in Agro-morphological Traits

The aus (Oryza sativa L.) varietal group comprises of aus, boro, ashina and rayada seasonal and/or field ecotypes, and exhibits unique stress tolerance traits, making it valuable for rice breeding. Despite its importance, the agro-morphological diversity and genetic control of yield traits in aus rice remain poorly understood. To address this knowledge gap, we investigated the genetic structure of 181 aus accessions using 399,115 SNP markers and evaluated them for 11 morpho-agronomic traits. Through genome-wide association studies (GWAS), we aimed to identify key loci controlling yield and plant architectural traits.Our population genetic analysis unveiled six subpopulations with strong geographical patterns. Subpopulation-specific differences were observed in most phenotypic traits. Principal component analysis (PCA) of agronomic traits showed that principal component 1 (PC1) was primarily associated with panicle traits, plant height, and heading date, while PC2 and PC3 were linked to primary grain yield traits. GWAS using PC1 identified OsSAC1 on Chromosome 7 as a significant gene influencing multiple agronomic traits. PC2-based GWAS highlighted the importance of OsGLT1 and OsPUP4/ Big Grain 3 in determining grain yield. Haplotype analysis of these genes in the 3,000 Rice Genome Panel revealed distinct genetic variations in aus rice.In summary, this study offers valuable insights into the genetic structure and phenotypic diversity of aus rice accessions. We have identified significant loci associated with essential agronomic traits, with GLT1, PUP4, and SAC1 genes emerging as key players in yield determination.

Timing of oomycete-specific fungicide application impacts the efficacy against fruit rot disease in arecanut

Fungicidal application has been the common and prime option to combat fruit rot disease (FRD) of arecanut (Areca catechu L.) under field conditions. However, the existence of virulent pathotypes, rapid spreading ability, and improper time of fungicide application has become a serious challenge. In the present investigation, we assessed the efficacy of oomycete-specific fungicides under two approaches: (i) three fixed timings of fungicidal applications, i.e., pre-, mid-, and post-monsoon periods (EXPT1), and (ii) predefined different fruit stages, i.e., button, marble, and premature stages (EXPT2). Fungicidal efficacy in managing FRD was determined from evaluations of FRD severity, FRD incidence, and cumulative fallen nut rate (CFNR) by employing generalized linear mixed models (GLMMs). In EXPT1, all the tested fungicides reduced FRD disease levels by >65% when applied at pre- or mid-monsoon compared with untreated control, with statistical differences among fungicides and timings of application relative to infection. In EXPT2, the efficacy of fungicides was comparatively reduced when applied at predefined fruit/nut stages, with statistically non-significant differences among tested fungicides and fruit stages. A comprehensive analysis of both experiments recommends that the fungicidal application can be performed before the onset of monsoon for effective management of arecanut FRD. In conclusion, the timing of fungicidal application based on the monsoon period provides better control of FRD of arecanut than an application based on the developmental stages of fruit under field conditions.

Physicochemical characterization and fatty acid profiles of testa oils from various coconut (Cocos nucifera L.) genotypes

BACKGROUND

Cocos nucifera (L.) is an important plantation crop with immense but untapped nutraceutical potential. Despite its bioactive potential, the biochemical features of testa oils of various coconut genotypes are poorly understood. Hence, in this study, the physicochemical characteristics of testa oils extracted from six coconut genotypes - namely West Coast Tall (WCT), Federated Malay States Tall (FMST), Chowghat Orange Dwarf (COD), Malayan Yellow Dwarf (MYD), and two Dwarf × Dwarf (D × D hybrids) viz., Cameroon Red Dwarf (CRD) × Ganga Bondam Green Dwarf (GBGD) and MYD × Chowghat Green Dwarf (CGD) - were analyzed.

RESULTS

The proportion of testa in the nuts (fruits) (1.29-3.42%), the proportion of oil in the testa (40.97-50.56%), and biochemical components in testa oils - namely proxidant elements Fe (34.17-62.48 ppm) and Cu (1.63-2.77 ppm), and the total phenolic content (6.84-8.67 mg GAE/100 g), and phytosterol content (54.66-137.73 mg CE/100 g) varied depending on the coconut genotypes. The saturated fatty acid content of testa oils (67.75 to 78.78%) was lower in comparison with that of coconut kernel oils. Similarly, the lauric acid (26.66-32.04%), myristic (18.31-19.60%), and palmitic acid (13.43-15.71%,) content of testa oils varied significantly in comparison with the coconut kernel oils (32-51%, 17-21% and 6.9-14%, respectively). Liquid chromatography-mass spectrometry (LC-MS) analysis revealed the presence of 18 phenolic acids in coconut testa oil. Multivariate analysis revealed the biochemical attributes that defined the principal components loadings. Hierarchical clustering analysis of the genotypes showed two distinct clusters.

CONCLUSION

This study reveals the genotypic variations in the nutritionally important biochemical components of coconut testa oils. The relatively high concentration of polyunsaturated fatty acids (PUFA) and polyphenol content in testa oils warrant further investigation to explore their nutraceutical potential. © 2022 Society of Chemical Industry.

Spatial distribution and identification of potential risk regions to rice blast disease in different rice ecosystems of Karnataka

Rice is a globally important crop and highly vulnerable to rice blast disease (RBD). We studied the spatial distribution of RBD by considering the 2-year exploratory data from 120 sampling sites over varied rice ecosystems of Karnataka, India. Point pattern and surface interpolation analyses were performed to identify the spatial distribution of RBD. The spatial clusters of RBD were generated by spatial autocorrelation and Ripley’s K function. Further, inverse distance weighting (IDW), ordinary kriging (OK), and indicator kriging (IK) approaches were utilized to generate spatial maps by predicting the values at unvisited locations using neighboring observations. Hierarchical cluster analysis using the average linkage method identified two main clusters of RBD severity. From the Local Moran’s I, most of the districts were clustered together (at I > 0), except the coastal and interior districts (at I < 0). Positive spatial dependency was observed in the Coastal, Hilly, Bhadra, and Upper Krishna Project ecosystems (p > 0.05), while Tungabhadra and Kaveri ecosystem districts were clustered together at p < 0.05. From the kriging, Hilly ecosystem, middle and southern parts of Karnataka were found vulnerable to RBD. This is the first intensive study in India on understanding the spatial distribution of RBD using geostatistical approaches, and the findings from this study help in setting up ecosystem-specific management strategies against RBD.

Predicting the Potential Suitable Climate for Coconut (Cocos nucifera L.) Cultivation in India under Climate Change Scenarios Using the MaxEnt Model

Climate change and climate variability are projected to alter the geographic suitability of lands for crop cultivation. Early awareness of the future climate of the current cultivation areas for a perennial tree crop like coconut is needed for its adaptation and sustainable cultivation in vulnerable areas. We analyzed coconut's vulnerability to climate change in India, based on climate projections for the 2050s and the 2070s under two Representative Concentration Pathways (RCPs): 4.5 and 8.5. Based on the current cultivation regions and climate change predictions from seven ensembles of Global Circulation Models, we predict changes in relative climatic suitability for coconut cultivation using the MaxEnt model. Bioclimatic variables Bio 4 (temperature seasonality, 34.4%) and Bio 7 (temperature annual range, 28.7%) together contribute 63.1%, which along with Bio 15 (precipitation seasonality, 8.6%) determined 71.7% of the climate suitability for coconuts in India. The model projected that some current coconut cultivation producing areas will become unsuitable (plains of South interior Karnataka and Tamil Nadu) requiring crop change, while other areas will require adaptations in genotypic or agronomic management (east coast and the south interior plains), and yet in others, the climatic suitability for growing coconut will increase (west coast). The findings suggest the need for adaptation strategies so as to ensure sustainable cultivation of coconut at least in presently cultivated areas.

Assessment of the Spatial Distribution and Risk Associated with Fruit Rot Disease in Areca catechu L

Phytophthora meadii (McRae) is a hemibiotrophic oomycete fungus that infects tender nuts, growing buds, and crown regions, resulting in fruit, bud, and crown rot diseases in arecanut (Areca catechu L.), respectively. Among them, fruit rot disease (FRD) causes serious economic losses that are borne by the growers, making it the greatest yield-limiting factor in arecanut crops. FRD has been known to occur in traditional growing areas since 1910, particularly in Malnad and coastal tracts of Karnataka. Systemic surveys were conducted on the disease several decades ago. The design of appropriate management approaches to curtail the impacts of the disease requires information on the spatial distribution of the risks posed by the disease. In this study, we used exploratory survey data to determine areas that are most at risk. Point pattern (spatial autocorrelation and Ripley’s K function) analyses confirmed the existence of moderate clustering across sampling points and optimized hotspots of FRD were determined. Geospatial techniques such as inverse distance weighting (IDW), ordinary kriging (OK), and indicator kriging (IK) were performed to predict the percent severity rates at unsampled sites. IDW and OK generated identical maps, whereby the FRD severity rates were higher in areas adjacent to the Western Ghats and the seashore. Additionally, IK was used to identify both disease-prone and disease-free areas in Karnataka. After fitting the semivariograms with different models, the exponential model showed the best fit with the semivariogram. Using this model information, OK and IK maps were generated. The identified FRD risk areas in our study, which showed higher disease probability rates (>20%) exceeding the threshold level, need to be monitored with the utmost care to contain and reduce the further spread of the disease in Karnataka.

Metagenomic Investigation Uncovers Presence of Probiotic-Type Microbiome in Kalparasa® (Fresh Unfermented Coconut Inflorescence Sap)

The phloem sap tapped from unopened inflorescence (spadix) of coconut palm using a novel collecting device, “coco-sap chiller,” has been branded Kalparasa^® (henceforth as Kalparasa in the text) to distinguish its properties not found in sap harvested by traditional methods. To know its hitherto unidentified microbiome profile, we employed high-throughput sequencing to uncover the bacteriome and mycobiome in fresh and 12-h fermented samples. Fresh Kalparasa had a pH of 7.2, which dropped to 4.5 after 12 h, signifying fermentation of the sap. Diversity analysis indicated fresh Kalparasa having higher bacterial species than the fermented one. Contrary to this, fresh sap had lower fungal/yeast diversity than the fermented sample. Fresh Kalparasa had relatively higher abundance of probiotic-type Leuconostoc genus followed by equal proportions of Gluconobacter, Acetobacter, and Fructobacillus. The 12-h fermented Kalparasa showed a significant increase in Gluconobacter with a sharp decrease in Leuconostoc. Mycobiome data revealed fresh Kalparasa to be preponderant in Saccharomyces and Hanseniaspora genera of yeasts while the fermented sap had higher representation of Hanseniaspora and Cortinarius and lesser Saccharomyces. This suggested that the fermentation of Kalparasa was probably driven by symbiotic culture of bacteria and yeasts (SCOBY), particularly acetic acid bacteria and non-Saccharomyces yeasts. The bacteriome-function predictions highlighted the enrichment of glycerophospholipid, ABC transporters, purine, and pyrimidine metabolisms. Based on our findings, Kalparasa containing large population of Leuconostoc mesenteroides, Fructobacillus fructosus, Saccharomyces cerevisiae, and Hanseniaspora guilliermondii can be promoted as a healthy “unfermented” plant edible food containing live probiotic-type microbiome during its consumption.

Genome-wide association study (GWAS) of major QTLs for bunch and oil yield related traits in Elaeis guineensis L

Oil palm (Elaeis guineensis Jacq.) is a long breeding cycle perennial crop with a genome size of 1.8 Gb. This is the first report of GWAS on large number of 310 African germplasm using 400 SSR markers till date. Highly significant correlation was found between leaf area (LA) and rachis length (RL) (0.75) followed by bunch weight (BW) and bunch index (BI) (0.65), whereas negative correlation was observed between bunch number (BN) and average bunch weight (ABW). First two principal component analysis (PCA) together explained maximum amount of variation (84.5 %). The PCA1 revealed that group 2 (Guinea Bissau and Cameroon) and group 4 (Zambia and Cameroon) genotypes are best suitable for BN, BI and BW traits. GWAS of six bunch yield and seven bunch oil yield traits with SSRs resulted in the identification 43 significant quantitative trait loci (QTLs) by mixed linear model (MLM) approach. Seven SSR loci were found to be linked to oil to dry mesocarp (ODM) on chromosomes 1,4,7,10,12 and 15. The SSR locus mEgCIR1753 for ODM was significantly linked at a p of ≤0.05 which explained 34.6 % of phenotypic variance. The important parameters like ODM, OWM and OB were located on 4, 10, 11 and 15 chromosomes. The leaf area and ODM were associated with candidate genes representing of low-temperature-induced 65 kDa proteins. The identified markers can be effectively used for marker assisted selection of high yielding oil palm genotypes.

Reaction kinetics of physico-chemical attributes in coconut inflorescence sap during fermentation

The study on fermentation kinetics of the coconut inflorescence sap is important to understand its shelf life at different storage conditions and to develop suitable value added products. The coconut inflorescence sap collected by using in-house developed coco-sap chiller device is called Kalparasa. The fermentation characteristics of Kalparasa were investigated at every 1-h interval under ambient (31 ± 2 °C) and refrigerated (5 ± 1 °C) storage conditions. The results reveal that pH of the sap and total sugar content decline rapidly under ambient conditions than under refrigerated conditions. Acidity, turbidity, and reducing sugar content significantly (p < 0.001) increases for the sap stored under ambient conditions. The reaction rate constant (k) of the vitamin C and total sugar degradation increases with the atmospheric fermentation. The degradation kinetics of vitamin C and total sugar in Kalparasa during natural fermentation (ambient condition) follow second-order equation whereas the reducing sugar follows the first-order equation.

Genome wide molecular evolution analysis of begomoviruses reveals unique diversification pattern in coat protein gene of Old World and New World viruses

Begomoviruses (Family-Geminiviridae) are plant infecting single stranded DNA viruses known to evolve very fast. Here, we have analysed the DNA-A sequences of 302 begomoviruses reported as 'type isolates' from different countries following the list of International Committee on Taxonomy of Viruses till 2017. Phylogenetic analysis was performed which revealed two major evolutionarily distinct groups namely Old World (OW) and New World (NW) viruses. Our work present evidence that cp gene has varied degree of diversification among the viruses reported from NW and OW. The NW viruses are more conserved in their cp gene sequences than that of OW viruses irrespective of host plant families. Further analysis reveals that cp gene differs in its recombination pattern among OW and NW viruses whereas rep gene is highly recombination prone in both OW and NW viruses. The sequence conservation in cp gene in NW viruses is a result of meagre recombination and subsequent low substitution rate in comparison to OW viruses. Our results demonstrated that the cp gene in NW viruses is less likely to possess nuclear localisation sequences than OW cp gene. Further we present evidence that the NW-cp is under the influence of strong purifying selection. We propose that the precoat protein (pcp) gene present exclusively in the 5' of cp gene in OW viruses is highly diversified and strong positive selection working on pcp gene might be attributing largely to the diversity of OW-cp gene.

PolyMorphPredict: A Universal Web-Tool for Rapid Polymorphic Microsatellite Marker Discovery From Whole Genome and Transcriptome Data

Microsatellites are ubiquitously distributed, polymorphic repeat sequence valuable for association, selection, population structure and identification. They can be mined by genomic library, probe hybridization and sequencing of selected clones. Such approach has many limitations like biased hybridization and selection of larger repeats. In silico mining of polymorphic markers using data of various genotypes can be rapid and economical. Available tools lack in some or other aspects like: targeted user defined primer generation, polymorphism discovery using multiple sequence, size and number limits of input sequence, no option for primer generation and e-PCR evaluation, transferability, lack of complete automation and user-friendliness. They also lack the provision to evaluate published primers in e-PCR mode to generate additional allelic data using re-sequenced data of various genotypes for judicious utilization of previously generated data. We developed the tool (PolyMorphPredict) using Perl, R, Java and launched at Apache which is available at http://webtom.cabgrid.res.in/polypred/. It mines microsatellite loci and computes primers from genome/transcriptome data of any species. It can perform e-PCR using published primers for polymorphism discovery and across species transferability of microsatellite loci. Present tool has been evaluated using five species of different genome size having 21 genotypes. Though server is equipped with genomic data of three species for test run with gel simulation, but can be used for any species. Further, polymorphism predictability has been validated using in silico and in vitro PCR of four rice genotypes. This tool can accelerate the in silico microsatellite polymorphism discovery in re-sequencing projects of any species of plant and animal for their diversity estimation along with variety/breed identification, population structure, MAS, QTL and gene discovery, traceability, parentage testing, fungal diagnostics and genome finishing.