A. R. Rao

Genome-wide association mapping of salinity tolerance in rice (Oryza sativa)

Salinity tolerance in rice is highly desirable to sustain production in areas rendered saline due to various reasons. It is a complex quantitative trait having different components, which can be dissected effectively by genome-wide association study (GWAS). Here, we implemented GWAS to identify loci controlling salinity tolerance in rice. A custom-designed array based on 6,000 single nucleotide polymorphisms (SNPs) in as many stress-responsive genes, distributed at an average physical interval of <100 kb on 12 rice chromosomes, was used to genotype 220 rice accessions using Infinium high-throughput assay. Genetic association was analysed with 12 different traits recorded on these accessions under field conditions at reproductive stage. We identified 20 SNPs (loci) significantly associated with Na+/K+ ratio, and 44 SNPs with other traits observed under stress condition. The loci identified for various salinity indices through GWAS explained 5–18% of the phenotypic variance. The region harbouring Saltol, a major quantitative trait loci (QTLs) on chromosome 1 in rice, which is known to control salinity tolerance at seedling stage, was detected as a major association with Na+/K+ ratio measured at reproductive stage in our study. In addition to Saltol, we also found GWAS peaks representing new QTLs on chromosomes 4, 6 and 7. The current association mapping panel contained mostly indica accessions that can serve as source of novel salt tolerance genes and alleles. The gene-based SNP array used in this study was found cost-effective and efficient in unveiling genomic regions/candidate genes regulating salinity stress tolerance in rice.

Predicting antimicrobial peptides with improved accuracy by incorporating the compositional, physico-chemical and structural features into Chou’s general PseAAC

Antimicrobial peptides (AMPs) are important components of the innate immune system that have been found to be effective against disease causing pathogens. Identification of AMPs through wet-lab experiment is expensive. Therefore, development of efficient computational tool is essential to identify the best candidate AMP prior to the in vitro experimentation. In this study, we made an attempt to develop a support vector machine (SVM) based computational approach for prediction of AMPs with improved accuracy. Initially, compositional, physico-chemical and structural features of the peptides were generated that were subsequently used as input in SVM for prediction of AMPs. The proposed approach achieved higher accuracy than several existing approaches, while compared using benchmark dataset. Based on the proposed approach, an online prediction server iAMPpred has also been developed to help the scientific community in predicting AMPs, which is freely accessible at http://cabgrid.res.in:8080/amppred/. The proposed approach is believed to supplement the tools and techniques that have been developed in the past for prediction of AMPs.

Modulatory potential of Spirulina fusiformis on carcinogen metabolizing enzymes in Swiss albino mice

The modulatory potential of Spirulina fusiformis was observed on the hepatic and extrahepatic carcinogen metabolizing enzymes in Swiss albino mice at a dose of 800 mg/kg b.w. given orally. A significant reduction in the hepatic cytochrome P450 content was observed in the group treated with Spirulina in comparison with the control group. The hepatic glutathione S‐transferase activity was induced significantly by Spirulina treatment. There was no change in the extrahepatic glutathione S‐transferase activity after the animals were fed with Spirulina. Copyright

Exploration of new drug-like inhibitors for serine/threonine protein phosphatase 5 of Plasmodium falciparum: a docking and simulation study

Protein phosphorylation is an important mechanism that implicates in physiology of any organism including parasitic protozoa. Metallic protein Ser/Thr protein phosphatase 5 (PP5) controls various cellular signaling pathways of Plasmodium falciparum. The structure and inhibitory mechanism of PP5 in P. falciparum is not known. In fact, no experimental structural data are available for P. falciparum Ser/Thr protein phosphatase 5 (PfPP5) till date. Hence, we have proposed computer-generated model of catalytic subunit of PfPP5 and its inhibitory mechanism was analyzed. A set of 42 known natural inhibitors of protein phosphate family were docked against metal-binding catalytic site of PfPP5 and we found that cantharidin and its derivatives shows better binding energy among them. Similarity search was performed by taking these compounds as lead compounds against PubChem and ChemBank. The search result provides 3703 similar compounds; out of which 2245 qualified the Lipinski rule of five. Further, virtual screening of these compounds was performed and selected top 25 were selected on the basis of binding energy. In continuation, rigid and flexible docking of these screened compounds was performed to get the insight of interactions. Finally, top 5 compounds were verified for ADMET properties, and then, all are subjected to MD simulations for 25 ns in order to validate their stability. Compounds CBI: 3554182, CID: 23561913, and CID: 21168680 showed most stable binding, although some of hydrogen bonds pairing varied throughout simulation. These finding would be helpful to the medicinal chemists for the development of antimalarial drugs to combat this deadly disease.

Genomic Selection for Drought Tolerance Using Genome-Wide SNPs in Maize

Traditional breeding strategies for selecting superior genotypes depending on phenotypic traits have proven to be of limited success, as this direct selection is hindered by low heritability, genetic interactions such as epistasis, environmental-genotype interactions, and polygenic effects. With the advent of new genomic tools, breeders have paved a way for selecting superior breeds. Genomic selection (GS) has emerged as one of the most important approaches for predicting genotype performance. Here, we tested the breeding values of 240 maize subtropical lines phenotyped for drought at different environments using 29,619 cured SNPs. Prediction accuracies of seven genomic selection models (ridge regression, LASSO, elastic net, random forest, reproducing kernel Hilbert space, Bayes A and Bayes B) were tested for their agronomic traits. Though prediction accuracies of Bayes B, Bayes A and RKHS were comparable, Bayes B outperformed the other models by predicting highest Pearson correlation coefficient in all three environments. From Bayes B, a set of the top 1053 significant SNPs with higher marker effects was selected across all datasets to validate the genes and QTLs. Out of these 1053 SNPs, 77 SNPs associated with 10 drought-responsive transcription factors. These transcription factors were associated with different physiological and molecular functions (stomatal closure, root development, hormonal signaling and photosynthesis). Of several models, Bayes B has been shown to have the highest level of prediction accuracy for our data sets. Our experiments also highlighted several SNPs based on their performance and relative importance to drought tolerance. The result of our experiments is important for the selection of superior genotypes and candidate genes for breeding drought-tolerant maize hybrids.

Identification, Characterization, and Functional Validation of Drought-responsive MicroRNAs in Subtropical Maize Inbreds

MicroRNA-mediated gene regulation plays a crucial role in controlling drought tolerance. In the present investigation, 13 drought-associated miRNA families consisting of 65 members and regulating 42 unique target mRNAs were identified from drought-associated microarray expression data in maize and were subjected to structural and functional characterization. The largest number of members (14) was found in the zma-miR166 and zma-miR395 families, with several targets. However, zma-miR160, zma-miR390, zma-miR393, and zma-miR2275 each showed a single target. Twenty-three major drought-responsive cis-regulatory elements were found in the upstream regions of miRNAs. Many drought-related transcription factors, such as GAMYB, HD-Zip III, and NAC, were associated with the target mRNAs. Furthermore, two contrasting subtropical maize genotypes (tolerant: HKI-1532 and sensitive: V-372) were used to understand the miRNA-assisted regulation of target mRNA under drought stress. Approximately 35 and 31% of miRNAs were up-regulated in HKI-1532 and V-372, respectively. The up-regulation of target mRNAs was as high as 14.2% in HKI-1532 but was only 2.38% in V-372. The expression patterns of miRNA-target mRNA pairs were classified into four different types: Type I- up-regulation, Type II- down-regulation, Type III- neutral regulation, and Type IV- opposite regulation. HKI-1532 displayed 46 Type I, 13 Type II, and 23 Type III patterns, whereas V-372 had mostly Type IV interactions (151). A low level of negative regulations of miRNA associated with a higher level of mRNA activity in the tolerant genotype helped to maintain crucial biological functions such as ABA signaling, the auxin response pathway, the light-responsive pathway and endosperm expression under stress conditions, thereby leading to drought tolerance. Our study identified candidate miRNAs and mRNAs operating in important pathways under drought stress conditions, and these candidates will be useful in the development of drought-tolerant maize hybrids.

Genome Wide Single Locus Single Trait, Multi-Locus and Multi-Trait Association Mapping for Some Important Agronomic Traits in Common Wheat (T. aestivum L.)

Genome wide association study (GWAS) was conducted for 14 agronomic traits in wheat following widely used single locus single trait (SLST) approach, and two recent approaches viz. multi locus mixed model (MLMM), and multi-trait mixed model (MTMM). Association panel consisted of 230 diverse Indian bread wheat cultivars (released during 1910–2006 for commercial cultivation in different agro-climatic regions in India). Three years phenotypic data for 14 traits and genotyping data for 250 SSR markers (distributed across all the 21 wheat chromosomes) was utilized for GWAS. Using SLST, as many as 213 MTAs (p ≤ 0.05, 129 SSRs) were identified for 14 traits, however, only 10 MTAs (~9%; 10 out of 123 MTAs) qualified FDR criteria; these MTAs did not show any linkage drag. Interestingly, these genomic regions were coincident with the genomic regions that were already known to harbor QTLs for same or related agronomic traits. Using MLMM and MTMM, many more QTLs and markers were identified; 22 MTAs (19 QTLs, 21 markers) using MLMM, and 58 MTAs (29 QTLs, 40 markers) using MTMM were identified. In addition, 63 epistatic QTLs were also identified for 13 of the 14 traits, flag leaf length (FLL) being the only exception. Clearly, the power of association mapping improved due to MLMM and MTMM analyses. The epistatic interactions detected during the present study also provided better insight into genetic architecture of the 14 traits that were examined during the present study. Following eight wheat genotypes carried desirable alleles of QTLs for one or more traits, WH542, NI345, NI170, Sharbati Sonora, A90, HW1085, HYB11, and DWR39 (Pragati). These genotypes and the markers associated with important QTLs for major traits can be used in wheat improvement programs either using marker-assisted recurrent selection (MARS) or pseudo-backcrossing method.

Genome-wide generation and use of informative intron-spanning and intron-length polymorphism markers for high-throughput genetic analysis in rice

We developed genome-wide 84634 ISM (intron-spanning marker) and 16510 InDel-fragment length polymorphism-based ILP (intron-length polymorphism) markers from genes physically mapped on 12 rice chromosomes. These genic markers revealed much higher amplification-efficiency (80%) and polymorphic-potential (66%) among rice accessions even by a cost-effective agarose gel-based assay. A wider level of functional molecular diversity (17–79%) and well-defined precise admixed genetic structure was assayed by 3052 genome-wide markers in a structured population of indica, japonica, aromatic and wild rice. Six major grain weight QTLs (11.9–21.6% phenotypic variation explained) were mapped on five rice chromosomes of a high-density (inter-marker distance: 0.98 cM) genetic linkage map (IR 64 x Sonasal) anchored with 2785 known/candidate gene-derived ISM and ILP markers. The designing of multiple ISM and ILP markers (2 to 4 markers/gene) in an individual gene will broaden the user-preference to select suitable primer combination for efficient assaying of functional allelic variation/diversity and realistic estimation of differential gene expression profiles among rice accessions. The genomic information generated in our study is made publicly accessible through a user-friendly web-resource, “Oryza ISM-ILP marker” database. The known/candidate gene-derived ISM and ILP markers can be enormously deployed to identify functionally relevant trait-associated molecular tags by optimal-resource expenses, leading towards genomics-assisted crop improvement in rice.

Identification of Novel Abiotic Stress Proteins in Triticum aestivum Through Functional Annotation of Hypothetical Proteins

Cereal grain bread wheat (T. aestivum) is an important source of food and belongs to Poaceae family. Hypothetical proteins (HPs), i.e., proteins with unknown functions, share a substantial portion of wheat proteomes and play important roles in growth and physiology of plant system. Several functional annotations studies utilizing the protein sequences for characterization of role of individual protein in physiology of plant systems were being reported in recent past. In this study, an integrated pipeline of software/servers has been used for the identification and functional annotation of 124 unique HPs of T. aestivum considering available data in NCBI till date. All HPs were broadly annotated, out of which functions of 77 HPs were successfully assigned with high confidence level. Precisely functional annotation of remaining 47 HPs is also characterized with low confidence. Several latest versions of protein family databases, pathways information, genomics context methods and in silico tools were utilized to identify and assign function for individual HPs. Annotation result of several HPs mainly belongs to cellular protein, metabolic enzymes, binding proteins, transmembrane proteins, transcription factors and photosystem regulator proteins. Subsequently, functional analysis has revealed the role of few HPs in abiotic stress, which were further verified by phylogenetic analysis. The functionally associated proteins with each of above-mentioned abiotic stress-related proteins were identified through protein–protein interaction network analysis. The outcome of this study may be helpful for formulating general set pipeline/protocols for a better understanding of the role of HPs in physiological development of various plant systems.

Genomewide Expression and Functional Interactions of Genes under Drought Stress in Maize

A genomewide transcriptome assay of two subtropical genotypes of maize was used to observe the expression of genes at seedling stage of drought stress. The number of genes expressed differentially was greater in HKI1532 (a drought tolerant genotype) than in PC3 (a drought sensitive genotype), indicating primary differences at the transcriptional level in stress tolerance. The global coexpression networks of the two genotypes differed significantly with respect to the number of modules and the coexpression pattern within the modules. A total of 174 drought-responsive genes were selected from HKI1532, and their coexpression network revealed key correlations between different adaptive pathways, each cluster of the network representing a specific biological function. Transcription factors related to ABA-dependent stomatal closure, signalling, and phosphoprotein cascades work in concert to compensate for reduced photosynthesis. Under stress, water balance was maintained by coexpression of the genes involved in osmotic adjustments and transporter proteins. Metabolism was maintained by the coexpression of genes involved in cell wall modification and protein and lipid metabolism. The interaction of genes involved in crucial biological functions during stress was identified and the results will be useful in targeting important gene interactions to understand drought tolerance in greater detail.