De novo transcriptomic data of salt tolerant halophytes Dichnathium annulatum (Forssk.) stapf and Urochondra setulosa (Trin.) C.E.Hubb.

Two halophytes, Dichanthium annulatum (moderately salt tolerant) and Urochondra setulosa (highly salt tolerant) were selected to generate transcriptome at different salinity levels. Sequencing of RNA samples was done on Illumina-Hi-Seq platform for de novo transcriptome assembly from the leaf tissues of D. annulatum at salinity of ECe ∼30 dS/m and of U. setulosa at three salt levels (i.e. ECe ∼30, ∼40 and ∼50 dS/m). DESeq was used for identification of differentially expressed transcripts and a total of 267,196 and 384,442 transcripts were assembled through Trinity in both the plants respectively. A total of 32,246 and 25,479 SSRs were identified respectively in both the plants using MISA perl script with mono and tri-nucleotide repeats as most common motif.

de novo transcriptomic profiling of differentially expressed genes in grass halophyte Urochondra setulosa under high salinity.

Soil salinity is one of the major limiting factors for crop productivity across the world. Halophytes have recently been a source of attraction for exploring the survival and tolerance mechanisms at extreme saline conditions. Urochondra setulosa is one of the obligate grass halophyte that can survive in up to 1000 mM NaCl. The de novo transcriptome of Urochondra leaves at different salt concentrations of 300-500 mM NaCl was generated on Illumina HiSeq. Approximately 352.78 million high quality reads with an average contig length of 1259 bp were assembled de novo. A total of 120,231 unigenes were identified. On an average, 65% unigenes were functionally annotated to known proteins. Approximately 35% unigenes were specific to Urochondra. Differential expression revealed significant enrichment (P < 0.05) of transcription factors, transporters and metabolites suggesting the transcriptional regulation of ion homeostasis and signalling at high salt concentrations in this grass. Also, about 143 unigenes were biologically related to salt stress responsive genes. Randomly selected genes of important pathways were validated for functional characterization. This study provides useful information to understand the gene regulation at extremely saline levels. The study offers the first comprehensive evaluation of Urochondra setulosa leaf transcriptome. Examining non-model organisms that can survive in harsh environment can provide novel insights into the stress coping mechanisms which can be useful to develop improved agricultural crops.

Pan-genome analysis and ancestral state reconstruction of class halobacteria: probability of a new super-order.

Halobacteria, a class of Euryarchaeota are extremely halophilic archaea that can adapt to a wide range of salt concentration generally from 10% NaCl to saturated salt concentration of 32% NaCl. It consists of the orders: Halobacteriales, Haloferaciales and Natriabales. Pan-genome analysis of class Halobacteria was done to explore the core (300) and variable components (Softcore: 998, Cloud:36531, Shell:11784). The core component revealed genes of replication, transcription, translation and repair, whereas the variable component had a major portion of environmental information processing. The pan-gene matrix was mapped onto the core-gene tree to find the ancestral (44.8%) and derived genes (55.1%) of the Last Common Ancestor of Halobacteria. A High percentage of derived genes along with presence of transformation and conjugation genes indicate the occurrence of horizontal gene transfer during the evolution of Halobacteria. A Core and pan-gene tree were also constructed to infer a phylogeny which implicated on the new super-order comprising of Natrialbales and Halobacteriales.

Identification and evolutionary analysis of polycistronic miRNA clusters in domesticated and wild wheat.

MicroRNAs are ~22 nucleotide long non-coding RNAs that regulate gene expression at posttranscriptional level. Genome-wide analysis was performed to identify polycistronic miRNAs from wheat. Total 89 polycistronic miRNAs were identified in bread wheat which were distributed on three component sub-genomes (A = 26, B = 33 and D = 30). Except some, most of the identified polycistronic miRNAs were also present in other cultivated and wild wheat species. Expression of 11 identified polycistronic miRNAs could be validated using previously assembled transcriptomes, RNA-seq/s-RNA seq data of cultivated and wild wheats and RT-PCR. Polycistronic miRNAs orthologs were also localized on rice and Brachypodium genomes. As a case study, we also analyzed molecular evolution of miR395 family polycistrons in wheat. Both tandem and segmental duplications contributed to expansion of miR395 family polycistrons. Our findings provide a comprehensive view on wheat polycitronic miRNAs that will enable their in-depth functional analysis in the future.

Identification, analysis and development of salt responsive candidate gene based SSR markers in wheat.

BACKGROUND: Salinity severely limits wheat production in many parts of the world. Development of salt tolerant varieties represents the most practical option for enhancing wheat production from these areas. Application of marker assisted selection may assist in fast tracking development of salt tolerant wheat varieties. However, SSR markers available in the public domain are not specifically targeted to functional regions of wheat genome, therefore large numbers of these need to be analysed for identification of markers associated with traits of interest. With the availability of a fully annotated wheat genome assembly, it is possible to develop SSR markers specifically targeted to genic regions. We performed extensive analysis to identify candidate gene based SSRs and assessed their utility in characterizing molecular diversity in a panel of wheat genotypes. RESULTS: Our analysis revealed, 161 SSR motifs in 94 salt tolerance candidate genes of wheat. These SSR motifs were nearly equally distributed on the three wheat sub-genomes; 29.8% in A, 35.7% in B and 34.4% in D sub-genome. The maximum number of SSR motifs was present in exons (31.1%) followed by promoters (29.8%), 5'UTRs (21.1%), introns (14.3%) and 3'UTRs (3.7%). Out of the 65 candidate gene based SSR markers selected for validation, 30 were found polymorphic based on initial screening and employed for characterizing genetic diversity in a panel of wheat genotypes including salt tolerant and susceptible lines. These markers generated an average of 2.83 alleles/locus. Phylogenetic analysis revealed four clusters. Salt susceptible genotypes were mainly represented in clusters I and III, whereas high and moderate salt tolerant genotypes were distributed in the remaining two clusters. Population structure analysis revealed two sub-populations, sub-population 1 contained the majority of salt tolerant whereas sub-population 2 contained majority of susceptible genotypes. Moreover, we observed reasonably higher transferability of SSR markers to related wheat species. CONCLUSION: We have developed salt responsive gene based SSRs in wheat for the first time. These were highly useful in unravelling functional diversity among wheat genotypes with varying responses to salt stress. The identified gene based SSR markers will be valuable genomic resources for genetic/association mapping of salinity tolerance in wheat.

Draft Genome Sequence of Halolamina pelagica CDK2 Isolated from Natural Salterns from Rann of Kutch, Gujarat, India.

Halolamina pelagica strain CDK2, a halophilic archaeon (growth range 1.36 to 5.12 M NaCl), was isolated from rhizosphere of wild grasses of hypersaline soil of the Rann of Kutch, Gujarat, India. Its draft genome contains 2,972,542 bp and 3,485 coding sequences, depicting genes for halophilic serine proteases and trehalose synthesis.

First high quality draft genome sequence of a plant growth promoting and cold active enzyme producing psychrotrophic Arthrobacter agilis strain L77.

Arthrobacter agilis strain L77, is a plant growth promoting and cold active hydrolytic enzymes producing psychrotrophic bacterium, isolated from Pangong Lake, a subglacial lake in north western Himalayas, India. Genome analysis revealed metabolic versatility with genes involved in metabolism and cold shock adaptation, utilization and biosynthesis of diverse structural and storage polysaccharides such as plant based carbon polymers. The genome of Arthrobacter agilis strain L77 consists of 3,608,439 bp (3.60 Mb) of a circular chromosome. The genome comprises of 3316 protein coding genes and 74 RNA genes, 725 hypothetical proteins, 25 pseudo-genes and 1404 unique genes.

Cheminformatics models for inhibitors of Schistosoma mansoni thioredoxin glutathione reductase.

Schistosomiasis is a neglected tropical disease caused by a parasite Schistosoma mansoni and affects over 200 million annually. There is an urgent need to discover novel therapeutic options to control the disease with the recent emergence of drug resistance. The multifunctional protein, thioredoxin glutathione reductase (TGR), an essential enzyme for the survival of the pathogen in the redox environment has been actively explored as a potential drug target. The recent availability of small-molecule screening datasets against this target provides a unique opportunity to learn molecular properties and apply computational models for discovery of activities in large molecular libraries. Such a prioritisation approach could have the potential to reduce the cost of failures in lead discovery. A supervised learning approach was employed to develop a cost sensitive classification model to evaluate the biological activity of the molecules. Random forest was identified to be the best classifier among all the classifiers with an accuracy of around 80 percent. Independent analysis using a maximally occurring substructure analysis revealed 10 highly enriched scaffolds in the actives dataset and their docking against was also performed. We show that a combined approach of machine learning and other cheminformatics approaches such as substructure comparison and molecular docking is efficient to prioritise molecules from large molecular datasets.