Crp/fnr family protein binds to promoters of atxA and sodmn genes that regulate the expression of exotoxins in Bacillus anthracis.

Bacillus anthracis produces a tripartite exotoxin, which is regulated by AtxA. Sodmn is constitutively expressed during invasion. Crp/Fnr family transcriptional regulators are known to bind promoters of toxin regulators as well as constitutively expressed genes during pathogenesis. B. anthracis fnr gene was cloned, over-expressed in E. coli and recombinant protein was purified. Oligomeric nature of recombinant rFnr protein was studied by diamide treatment and DTT reduction. DNA binding of rFnr protein was studied by EMSA. We observed that rFnr exists in both monomeric and oligomeric forms. It was found that rFnr was able to oligomerize after diamide treatment which was reversible through DTT reduction. Promoter regions of atxA and sodmn show binding to monomeric form of rFnr, however, dimeric form was unable to bind. Fnr might be playing a role in regulation of toxin gene expression via regulation of atxA gene. It can also be involved in regulation of pathogenesis by regulating the sodmn expression. Oligomerization can act as an ON/OFF switch for the Fnr mediated regulation.

Bacterial community structure analysis of a hot spring soil by next generation sequencing of ribosomal RNA.

In the present study the whole bacterial community structure of Tapovan hot spring soil located in the state of Uttarakhand, India was analysed through next generation sequencing. The hot spring soil is slightly alkaline in nature with abundance of sulphur. The spring soil was rich in various metallic and non-metallic elements required for bacterial survival. The community was found to comprise of 14 bacterial phyla with representation of members belonging to Firmicutes, Proteobacteria, Thermi, Bacteroidetes, Aquificae, Actinobacteria, chloroflexi, TM7, Fusobacteria etc. At the genus level Bacillus, Pseudomonas, Symbiobacterium, Thermus, Geobacillus, Anoxybacillus were found in abundance as compared to other genera like Flavobacterium, Ureibacillus, Clostridium, Meiothermus, Acinetobacter, Desulfotomaculum and Rheinheimera.

Physicochemical and microbiological assessment of spring water in central Himalayan region.

In the present study, water quality of 16 springs, located along National Highway-58 from Rishikesh to Badrinath in India, was assessed by determining various physicochemical and microbiological parameters in three different seasons, i.e., pre-monsoon, monsoon, and post-monsoon. For majority of the springs, the pH was slightly alkaline with temperature ranging between 10 and 27 °C. All other parameters such as total hardness (TH), total alkalinity (TA), chloride, phosphate, nitrate, total dissolved solids (TDS), electrical conductivity (EC), dissolved oxygen (DO), and biochemical oxygen demand (BOD) were found to lie within the acceptable limit prescribed by various standard national and international agencies. The principal component analysis reveals that water quality of springs mainly depends on mineral contents of water, as there is a loading of TH, TA, EC, TDS, and other mineral components during one or other season of a year. The positive correlation coefficients determined among mineral components of spring water further substantiate this fact. No loading of DO, BOD, nitrate, and phosphate indicates an absence of anthropogenic pollution in the studied area. No trace metals were detected in any of the springs. Most probable number (MPN) index for coliforms was found to be above the acceptable limit for all the springs in one or more seasons of a year, except the one in Pandukeshwar. Plate-based assay revealed the presence of pathogens like Salmonella, Shigella, Vibrio, and Pseudomonas in some spring water. The findings of the present work reveal that due to high MPN index and presence of other pathogenic bacteria, water from most of the springs cannot be considered completely safe for direct human consumption in its raw form.

Global insights into high temperature and drought stress regulated genes by RNA-Seq in economically important oilseed crop Brassica juncea.

BACKGROUND: Brassica juncea var. Varuna is an economically important oilseed crop of family Brassicaceae which is vulnerable to abiotic stresses at specific stages in its life cycle. Till date no attempts have been made to elucidate genome-wide changes in its transcriptome against high temperature or drought stress. To gain global insights into genes, transcription factors and kinases regulated by these stresses and to explore information on coding transcripts that are associated with traits of agronomic importance, we utilized a combinatorial approach of next generation sequencing and de-novo assembly to discover B. juncea transcriptome associated with high temperature and drought stresses. RESULTS: We constructed and sequenced three transcriptome libraries namely Brassica control (BC), Brassica high temperature stress (BHS) and Brassica drought stress (BDS). More than 180 million purity filtered reads were generated which were processed through quality parameters and high quality reads were assembled de-novo using SOAPdenovo assembler. A total of 77750 unique transcripts were identified out of which 69,245 (89%) were annotated with high confidence. We established a subset of 19110 transcripts, which were differentially regulated by either high temperature and/or drought stress. Furthermore, 886 and 2834 transcripts that code for transcription factors and kinases, respectively, were also identified. Many of these were responsive to high temperature, drought or both stresses. Maximum number of up-regulated transcription factors in high temperature and drought stress belonged to heat shock factors (HSFs) and dehydration responsive element-binding (DREB) families, respectively. We also identified 239 metabolic pathways, which were perturbed during high temperature and drought treatments. Analysis of gene ontologies associated with differentially regulated genes forecasted their involvement in diverse biological processes. CONCLUSIONS: Our study provides first comprehensive discovery of B. juncea transcriptome under high temperature and drought stress conditions. Transcriptome resource generated in this study will enhance our understanding on the molecular mechanisms involved in defining the response of B. juncea against two important abiotic stresses. Furthermore this information would benefit designing of efficient crop improvement strategies for tolerance against conditions of high temperature regimes and water scarcity.

Identification and characterization of miRNAome in root, stem, leaf and tuber developmental stages of potato (Solanum tuberosum L.) by high-throughput sequencing.

BACKGROUND: MicroRNAs (miRNAs) are ubiquitous components of endogenous plant transcriptome. miRNAs are small, single-stranded and ~21 nt long RNAs which regulate gene expression at the post-transcriptional level and are known to play essential roles in various aspects of plant development and growth. Previously, a number of miRNAs have been identified in potato through in silico analysis and deep sequencing approach. However, identification of miRNAs through deep sequencing approach was limited to a few tissue types and developmental stages. This study reports the identification and characterization of potato miRNAs in three different vegetative tissues and four stages of tuber development by high throughput sequencing. RESULTS: Small RNA libraries were constructed from leaf, stem, root and four early developmental stages of tuberization and subjected to deep sequencing, followed by bioinformatics analysis. A total of 89 conserved miRNAs (belonging to 33 families), 147 potato-specific miRNAs (with star sequence) and 112 candidate potato-specific miRNAs (without star sequence) were identified. The digital expression profiling based on TPM (Transcripts Per Million) and qRT-PCR analysis of conserved and potato-specific miRNAs revealed that some of the miRNAs showed tissue specific expression (leaf, stem and root) while a few demonstrated tuberization stage-specific expressions. Targets were predicted for identified conserved and potato-specific miRNAs, and predicted targets of four conserved miRNAs, miR160, miR164, miR172 and miR171, which are ARF16 (Auxin Response Factor 16), NAM (NO APICAL MERISTEM), RAP1 (Relative to APETALA2 1) and HAM (HAIRY MERISTEM) respectively, were experimentally validated using 5' RLM-RACE (RNA ligase mediated rapid amplification of cDNA ends). Gene ontology (GO) analysis for potato-specific miRNAs was also performed to predict their potential biological functions. CONCLUSIONS: We report a comprehensive study of potato miRNAs at genome-wide level by high-throughput sequencing and demonstrate that these miRNAs have tissue and/or developmental stage-specific expression profile. Also, predicted targets of conserved miRNAs were experimentally confirmed for the first time in potato. Our findings indicate the existence of extensive and complex small RNA population in this crop and suggest their important role in pathways involved in diverse biological processes, including tuber development.

Unveiling the microbial communities and metabolic pathways of Keem, a traditional starter culture, through whole-genome sequencing.

Traditional alcoholic beverages have played a significant role in the cultural, social, and culinary fabric of societies worldwide for centuries. Studying the microbial community structure and their metabolic potential in such beverages is necessary to define product quality, safety, and consistency, as well as to explore associated biotechnological applications. In the present investigation, Illumina-based (MiSeq system) whole-genome shotgun sequencing was utilized to characterize the microbial diversity and conduct predictive gene function analysis of keem, a starter culture employed by the Jaunsari tribal community in India for producing various traditional alcoholic beverages. A total of 8,665,213 sequences, with an average base length of 151 bps, were analyzed using MG-RAST. The analysis revealed the dominance of bacteria (95.81%), followed by eukaryotes (4.11%), archaea (0.05%), and viruses (0.03%). At the phylum level, Actinobacteria (81.18%) was the most abundant, followed by Firmicutes (10.56%), Proteobacteria (4.00%), and Ascomycota (3.02%). The most predominant genera were Saccharopolyspora (36.31%), followed by Brevibacterium (15.49%), Streptomyces (9.52%), Staphylococcus (8.75%), Bacillus (4.59%), and Brachybacterium (3.42%). At the species level, the bacterial, fungal, and viral populations of the keem sample could be categorized into 3347, 57, and 106 species, respectively. Various functional attributes to the sequenced data were assigned using Cluster of Orthologous Groups (COG), Non-supervised Orthologous Groups (NOG), subsystem, and KEGG Orthology (KO) annotations. The most prevalent metabolic pathways included carbohydrate, lipid, and amino acid metabolism, as well as the biosynthesis of glycans, secondary metabolites, and xenobiotic biodegradation. Given the rich microbial diversity and its associated metabolic potential, investigating the transition of keem from a traditional starter culture to an industrial one presents a compelling avenue for future research.

Design and development of efficient and compact 20 kW 325 MHz solid-state amplifier for superconducting accelerator applications.

An efficient and compact, 20 kW solid-state power amplifier (SSA) at 325 MHz has been designed and developed in-house, using single stage combining. It comprises of 24 nos. of 1 kW power amplifier (PA) modules, a 24-way Wilkinson power combiner and divider, and other peripheral systems. The typical gain and conversion efficiency of the PA modules at 1.0 kW output is 21.7 dB and 66.6%, respectively. It is demonstrated that overall power gain and AC to RF efficiency of this SSA at 20 kW is 88.5 dB and 54.8%, respectively, which matches closely with the design estimates. The harmonic content in the RF output is < -40 dBc for all the harmonics. The results of the Monte Carlo simulation are also presented, showing lower bound on combining efficiency with a degree of confidence if magnitude and phase data for 24 inputs are randomly chosen from a normal distribution's pre-defined interval. The salient features of this SSA include power density of 12.7 kW/m3, AC to RF efficiency of 54.8% at 20 kW, and guaranteed output of 20 kW with one failed PA module and 18.1 kW under two failed PA modules condition.

Genetic and functional diversity among root-associated psychrotrophic Pseudomonad's isolated from the Himalayan plants.

Out of 534 psychrotrophic bacteria, 12 bacteria were selected on the basis of plant growth promoting activities at 4 °C and identified as Pseudomonas genus. These strains showed high level of genetic polymorphisms based on RAPD and rep-PCR fingerprinting. This genetic variability revealed that isolates belonging to same species were as high as the variability among different species. Further inoculation of these Pseudomonas strains significantly improves root/shoot biomass and nutrients uptake of lentil plant as compared to non-bacterized control after 40 days of seed showing. Agglomerative hierarchical clustering analysis of pot assay results revealed that genetically diverse strains showing the same prototype in functional parameter and representing diverse blueprint of plant growth promoting attributes. Results of present findings explain the huge beneficial microbial resources from root zone of hilly crops of Himalayan region that could be effectively exploited as bio-inoculums for cold climatic condition.

Alleviation of cold stress in inoculated wheat (Triticum aestivum L.) seedlings with psychrotolerant Pseudomonads from NW Himalayas.

Twelve psychrotolerant Pseudomonad strains were selected on the basis of various plant growth-promoting (PGP) activities at cold temperature (4°C). The effect of inoculation with Pseudomonad strains on cold alleviation and growth of wheat seedling at cold temperature (8°C) was investigated under greenhouse condition. Inoculation with Pseudomonad strains significantly enhanced root/shoot biomass and nutrients uptake as compared to non-bacterized control at 60 days of plant growth. Bacterization significantly improved the level of cellular metabolites like chlorophyll, anthocyanin, free proline, total phenolics, starch content, physiologically available iron, proteins, and amino acids that are sign of alleviation of cold stress in wheat plants. Increased relative water content, reduced membrane injury (electrolyte leakage), and Na(+)/K(+) ratio were also recorded in bacterized wheat plants. Electrolyte leakage and Na(+)/K(+) were found inversely proportional to plant growth at cold temperature. Statistical analysis of twenty-three measured parameters revealed that uninoculated control was under cold stress while eight bacterial strains were positively alleviating cold stress in wheat plants. Thus, the psychrotrophic Pseudomonad strains could effectively provide a promising solution to overcome cold stress, which is major factor hindering wheat productivity under cold climatic condition.

Lung nodule malignancy classification with weakly supervised explanation generation.

Purpose: Explainable AI aims to build systems that not only give high performance but also are able to provide insights that drive the decision making. However, deriving this explanation is often dependent on fully annotated (class label and local annotation) data, which are not readily available in the medical domain. Approach: This paper addresses the above-mentioned aspects and presents an innovative approach to classifying a lung nodule in a CT volume as malignant or benign, and generating a morphologically meaningful explanation for the decision in the form of attributes such as nodule margin, sphericity, and spiculation. A deep learning architecture that is trained using a multi-phase training regime is proposed. The nodule class label (benign/malignant) is learned with full supervision and is guided by semantic attributes that are learned in a weakly supervised manner. Results: Results of an extensive evaluation of the proposed system on the LIDC-IDRI dataset show good performance compared with state-of-the-art, fully supervised methods. The proposed model is able to label nodules (after full supervision) with an accuracy of 89.1% and an area under curve of 0.91 and to provide eight attributes scores as an explanation, which is learned from a much smaller training set. The proposed system's potential to be integrated with a sub-optimal nodule detection system was also tested, and our system handled 95% of false positive or random regions in the input well by labeling them as benign, which underscores its robustness. Conclusions: The proposed approach offers a way to address computer-aided diagnosis system design under the constraint of sparse availability of fully annotated images.

A Saliva-Based RNA Extraction-Free Workflow Integrated With Cas13a for SARS-CoV-2 Detection.

A major bottleneck in scaling-up COVID-19 testing is the need for sophisticated instruments and well-trained healthcare professionals, which are already overwhelmed due to the pandemic. Moreover, the high-sensitive SARS-CoV-2 diagnostics are contingent on an RNA extraction step, which, in turn, is restricted by constraints in the supply chain. Here, we present CASSPIT (Cas13 Assisted Saliva-based & Smartphone Integrated Testing), which will allow direct use of saliva samples without the need for an extra RNA extraction step for SARS-CoV-2 detection. CASSPIT utilizes CRISPR-Cas13a based SARS-CoV-2 RNA detection, and lateral-flow assay (LFA) readout of the test results. The sample preparation workflow includes an optimized chemical treatment and heat inactivation method, which, when applied to COVID-19 clinical samples, showed a 97% positive agreement with the RNA extraction method. With CASSPIT, LFA based visual limit of detection (LoD) for a given SARS-CoV-2 RNA spiked into the saliva samples was ~200 copies; image analysis-based quantification further improved the analytical sensitivity to ~100 copies. Upon validation of clinical sensitivity on RNA extraction-free saliva samples (n = 76), a 98% agreement between the lateral-flow readout and RT-qPCR data was found (Ct<35). To enable user-friendly test results with provision for data storage and online consultation, we subsequently integrated lateral-flow strips with a smartphone application. We believe CASSPIT will eliminate our reliance on RT-qPCR by providing comparable sensitivity and will be a step toward establishing nucleic acid-based point-of-care (POC) testing for COVID-19.

An efficient ORF selection system for DNA fragment libraries based on split beta-lactamase complementation.

PCR-based amplification of annotated genes has allowed construction of expression clones at genome-scale using classical and recombination-based cloning technologies. However, genome-scale expression and purification of proteins for down-stream applications is often limited by challenges such as poor expression, low solubility, large size of multi-domain proteins, etc. Alternatively, DNA fragment libraries in expression vectors can serve as the source of protein fragments with each fragment encompassing a function of its whole protein counterpart. However, the random DNA fragmentation and cloning result in only 1 out of 18 clones being in the correct open-reading frame (ORF), thus, reducing the overall efficiency of the system. This necessitates the selection of correct ORF before expressing the protein fragments. This paper describes a highly efficient ORF selection system for DNA fragment libraries, which is based on split beta-lactamase protein fragment complementation. The system has been designed to allow seamless transfer of selected DNA fragment libraries into any downstream vector systems using a restriction enzyme-free cloning strategy. The strategy has been applied for the selection of ORF using model constructs to show near 100% selection of the clone encoding correct ORF. The system has been further validated by construction of an ORF-selected DNA fragment library of 30 genes of M. tuberculosis. Further, we have successfully demonstrated the cytosolic expression of ORF-selected protein fragments in E. coli.

In silico study of chikungunya polymerase, a potential target for inhibitors.

Non-structural protein 4 (nsP4) polymerase of chikungunya virus (CHIKV) has a crucial role in genome replication and hence could act as a promising target for novel therapeutics. Though, nsP4 is important in viral life cycle, but it is less explored as therapeutic target. The catalytic core of nsP4 Polymerase includes conserved GDD motif which is present not only across different CHIKV strains but also across other Alphaviruses. This emphasizes the uniqueness and importance of this motif in the functioning of nsP4 polymerase and hence, we focused on GDD motif for docking of drug molecules. Herein, a model of nsP4 polymerase was developed using Swiss Model, validated by Ramachandran plot and molecular dynamic simulation. Molecular docking was performed using LeadIT FlexX flexible docking module with FDA approved drug molecule library. On the basis of flexX score, top 5 leads with flexX scores - 33.7588, - 30.2555, - 29.6043, - 28.916 and - 28.5042 were selected. The bonding pattern of these leads were analysed in discovery studio and were further screened on the basis of molecular dynamic simulation studies. Simulation analysis revealed that only the top lead, Mitoxantrone Hydrochloride which is an anticancer drug and is currently indicated in leukemias and lymphomas interacted favourably and stably with nsP4. Our findings suggest that Mitoxantrone Hydrochloride can be a potential novel inhibitor of CHIKV polymerase and should be further validated by in vitro assays.

Genome-wide identification and characterization of miRNAome from tomato (Solanum lycopersicum) roots and root-knot nematode (Meloidogyne incognita) during susceptible interaction.

Root-knot nematodes (RKNs, Meloidogyne spp.) are the most damaging plant parasites causing severe losses to crop production. The present study reports genome-wide identification and characterization of both tomato and RKN miRNAs simultaneously from RKN-infected susceptible tomato roots using high-throughput sequencing technique. RNAseq data from 11 small RNA libraries derived from 5 disease development stages identified 281 novel miRNAs of tomato in addition to 52 conserved and 4 variants of conserved miRNAs. Additionally, the same set of RNAseq data identified 38 conserved and 290 novel RKN miRNAs. Both tomato and RKN miRNAs showed differential expression at 5 stages of disease development based on digital expression profiles. In tomato, further validation through qRT-PCR confirmed that majority of miRNAs were significantly upregulated during susceptible response whereas downregulated during resistance response. The predicted targets of 8 conserved and 1 novel miRNAs were validated through 5'RLM-RACE. A negative correlation between expression profiles of a few conserved miRNAs (miR156, miR159, miR164 and miR396) and their targets (SBP, GAMYB-like, NAC and GRF1 transcription factor) was confirmed. A novel Sly_miRNA996 also showed a negative correlation with its target MYB-like transcription factor. These results indicate that the conserved and novel tomato miRNAs are involved in regulating developmental changes in host root during RKN infection. In RKN, the targets of conserved miRNAs were also predicted and a few of their predicted target genes are known to be involved in nematode parasitism. Further, the potential roles of both tomato and RKN miRNAs have been discussed.

Automated Detection of Glaucoma From Topographic Features of the Optic Nerve Head in Color Fundus Photographs.

OBJECTIVE: To describe and evaluate the performance of an automated CAD system for detection of glaucoma from color fundus photographs. DESIGN AND SETTING: Color fundus photographs of 2252 eyes from 1126 subjects were collected from 2 centers: Aravind Eye Hospital, Madurai and Coimbatore, India. The images of 1926 eyes (963 subjects) were used to train an automated image analysis-based system, which was developed to provide a decision on a given fundus image. A total of 163 subjects were clinically examined by 2 ophthalmologists independently and their diagnostic decisions were recorded. The consensus decision was defined to be the clinical reference (gold standard). Fundus images of eyes with disagreement in diagnosis were excluded from the study. The fundus images of the remaining 314 eyes (157 subjects) were presented to 4 graders and their diagnostic decisions on the same were collected. The performance of the system was evaluated on the 314 images, using the reference standard. The sensitivity and specificity of the system and 4 independent graders were determined against the clinical reference standard. RESULTS: The system achieved an area under receiver operating characteristic curve of 0.792 with a sensitivity of 0.716 and specificity of 0.717 at a selected threshold for the detection of glaucoma. The agreement with the clinical reference standard as determined by Cohen κ is 0.45 for the proposed system. This is comparable to that of the image-based decisions of 4 ophthalmologists. CONCLUSIONS AND RELEVANCE: An automated system was presented for glaucoma detection from color fundus photographs. The overall evaluation results indicated that the presented system was comparable in performance to glaucoma classification by a manual grader solely based on fundus image examination.

Development of Genomic Microsatellite Markers in Carthamus tinctorius L. (Safflower) Using Next Generation Sequencing and Assessment of Their Cross-Species Transferability and Utility for Diversity Analysis.

BACKGROUND: Safflower (Carthamus tinctorius L.), an Asteraceae member, yields high quality edible oil rich in unsaturated fatty acids and is resilient to dry conditions. The crop holds tremendous potential for improvement through concerted molecular breeding programs due to the availability of significant genetic and phenotypic diversity. Genomic resources that could facilitate such breeding programs remain largely underdeveloped in the crop. The present study was initiated to develop a large set of novel microsatellite markers for safflower using next generation sequencing. PRINCIPAL FINDINGS: Low throughput genome sequencing of safflower was performed using Illumina paired end technology providing ~3.5X coverage of the genome. Analysis of sequencing data allowed identification of 23,067 regions harboring perfect microsatellite loci. The safflower genome was found to be rich in dinucleotide repeats followed by tri-, tetra-, penta- and hexa-nucleotides. Primer pairs were designed for 5,716 novel microsatellite sequences with repeat length ≥ 20 bases and optimal flanking regions. A subset of 325 microsatellite loci was tested for amplification, of which 294 loci produced robust amplification. The validated primers were used for assessment of 23 safflower accessions belonging to diverse agro-climatic zones of the world leading to identification of 93 polymorphic primers (31.6%). The numbers of observed alleles at each locus ranged from two to four and mean polymorphism information content was found to be 0.3075. The polymorphic primers were tested for cross-species transferability on nine wild relatives of cultivated safflower. All primers except one showed amplification in at least two wild species while 25 primers amplified across all the nine species. The UPGMA dendrogram clustered C. tinctorius accessions and wild species separately into two major groups. The proposed progenitor species of safflower, C. oxyacantha and C. palaestinus were genetically closer to cultivated safflower and formed a distinct cluster. The cluster analysis also distinguished diploid and tetraploid wild species of safflower. CONCLUSION: Next generation sequencing of safflower genome generated a large set of microsatellite markers. The novel markers developed in this study will add to the existing repertoire of markers and can be used for diversity analysis, synteny studies, construction of linkage maps and marker-assisted selection.

Note: electronic damping of microphonics in superconducting resonators of a continuous wave linac.

The paper presents an implementation technique to damp the microphonics in superconducting resonators utilizing the coupling between the electromagnetic and the mechanical modes of a resonator. In the technique used the resonant frequency variations are fed back to modulate the field amplitude through a suitable transfer function. Of the two transfer functions used in the experiments, one emulates a derivative action and is placed in a negative feedback configuration. The other transfer function is essentially a parallel combination of second order low pass filters and is used in a positive feedback configuration. Experiments with the Quarter Wave resonators of IUAC, New Delhi linac demonstrate that the damping of some of the modes increases significantly with the introduction of this feedback leading to a reduction in power required for field stabilization and quieter operation of the RF control system.

CspA encodes a major cold shock protein in Himalayan psychrotolerant Pseudomonas strains.

The major cold-shock protein (CspA) encoding gene cspA were detected in three Himalayan psychrotrophic Pseudomonad strains, by PCR amplification. Partial sequencing of three Pseudomonas strains cspA gene and BLAST search confirmed the high similarity with putative bacterial cspA gene and bacterial CspA protein. Bioinformatics analysis of these partial CspA amino acid sequences showed presence of putative conserved region for DNA/RNA-binding motifs RNP-1 and RNP-2. Protein homologies of all three bacterial CspA proteins belong to S1 like protein (Ribosomal protein S1-like RNA-binding domain). Presence of cspA gene and its high similarity with Bacillus cereus group demonstrating uniqueness of cspA gene in these Pseudomonas strains and suggesting strong evolutionary relationship between these two groups to survive in cold environments. Probable CspA protein expression levels were checked after cold shock (28°C to 4°C) and cold acclimation (4°C and 15°C) experiment. SDS-PAGE analysis revealed a small protein of approximate size of 7.5 kDa was expressed after cold shock (28°C to 4°C) and continuously over-expressed with the incubation time at cold temperature (4°C). Therefore it was predicted this protein would be product of cspA gene and suggesting this protein aids survival in Himalayan environments.

A comprehensive genome-wide study on tissue-specific and abiotic stress-specific miRNAs in Triticum aestivum.

Productivity of wheat crop is largely dependent on its growth and development that, in turn, is mainly regulated by environmental conditions, including abiotic stress factors. miRNAs are key regulators of gene expression networks involved in diverse aspects of development and stress responses in plants. Using high-throughput sequencing of eight small RNA libraries prepared from diverse abiotic stresses and tissues, we identified 47 known miRNAs belonging to 20 families, 49 true novel and 1030 candidate novel miRNAs. Digital gene expression analysis revealed that 257 miRNAs exhibited tissue-specific expression and 74 were associated with abiotic stresses. Putative target genes were predicted for miRNAs identified in this study and their grouping into functional categories indicated that the putative targets were involved in diverse biological processes. RLM-RACE of predicted targets of three known miRNAs (miR156, miR160 and miR164) confirmed their mRNA cleavage, thus indicating their regulation at post-transcriptional level by the corresponding miRNAs. Mapping of the sequenced data onto the wheat progenitors and closely related monocots revealed a large number of evolutionary conserved miRNAs. Additional expression profiling of some of these miRNAs in other abiotic stresses underline their involvement in multiple stresses. Our findings provide valuable resource for an improved understanding of the role of miRNAs in stress tolerance as well as plant development.

A genome-wide perspective of miRNAome in response to high temperature, salinity and drought stresses in Brassica juncea (Czern) L.

Micro RNAs (miRNAs) are involved in diverse biological processes including adaptive response towards abiotic stresses. To unravel small RNAs and more specifically miRNAs that can potentially regulate determinants of abiotic stress tolerance, next generation sequencing of B. juncea seedlings subjected to high temperature, high salt and drought conditions was carried out. With the help of UEA sRNA workbench software package, 51 conserved miRNAs belonging to 30 miRNA families were identified. As there was limited genomic information available for B. juncea, we generated and assembled its genome sequence at a low coverage. Using the generated sequence and other publically available Brassica genomic/transcriptomic resources as mapping reference, 126 novel (not reported in any plant species) were discovered for the first time in B. juncea. Further analysis also revealed existence of 32 and 37 star sequences for conserved and novel miRNAs, respectively. The expression of selected conserved and novel miRNAs under conditions of different abiotic stresses was revalidated through universal TaqMan based real time PCR. Putative targets of identified conserved and novel miRNAs were predicted in B. rapa to gain insights into functional roles manifested by B. juncea miRNAs. Furthermore, SPL2-like, ARF17-like and a NAC domain containing protein were experimentally validated as targets of miR156, miR160 and miR164 respectively. Investigation of gene ontologies linked with targets of known and novel miRNAs forecasted their involvement in various biological functions.