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The novel corona virus disease or COVID-19 caused by a positive strand RNA virus (PRV) called SARS-CoV-2 is plaguing the entire planet as we conduct this study. In this study a multifaceted analysis was carried out employing dinucleotide signature, codon usage and codon context to compare and unravel the genomic as well as genic characteristics of the SARS-CoV-2 isolates and how they compare to other PRVs which represents some of the most pathogenic human viruses. The main emphasis of this study was to comprehend the codon biology of the SARS-CoV-2 in the backdrop of the other PRVs like Poliovirus, Japanese encephalitis virus, Hepatitis C virus, Norovirus , Rubella virus, Semliki Forest virus, Zika virus, Dengue virus, Human rhinoviruses and the Betacoronaviruses since codon usage pattern along with the nucleotide composition prevalent within the viral genome helps to understand the biology and evolution of viruses. Our results suggest discrete genomic dinucleotide signature within the PRVs. Some of the genes from the different SARS-CoV-2 isolates were also found to demonstrate heterogeneity in terms of their dinucleotide signature. The SARS-CoV-2 isolates also demonstrated a codon context trend characteristically dissimilar to the other PRVs. The findings of this study are expected to contribute to the developing global knowledge base in countering COVID-19.

The deluge of sequence information in the recent times provide us with an excellent opportunity to compare organisms on a large genomic scale. In this study we have tried to decipher the variation in the gene organization and structuring of a vital bacterial gene called ftsZ which codes for an integral component of the bacterial cell division, the FtsZ protein. FtsZ is homologous to tubulin protein and has been found to be ubiquitous in eubacteria. FtsZ is showing increasing promise as a target for antibacterial drug discovery. Our study of ftsZ protein from 143 different bacterial species spanning a wider range of morphological and physiological type demonstrates that the ftsZ gene of about ninety three percent of the organisms show relatively biased codon usage profile and significant GC deviation from their genomic GC content. Comparative codon usage analysis of ftsZ and a core housekeeping gene rpoB demonstrated that codon usage pattern of ftsZ CDS is shaped by natural selection to a large extent and mimics that of a housekeeping gene. We have also detected a tendency among the different organisms to utilize a core set of codons in structuring the ftsZ coding sequence. We observed that the compositional frequency of the amino acid serine in the FtsZ protein appears to be a indicator of the bacterial lifestyle. Our meticulous analysis of the ftsZ gene linked with the corresponding FtsZ protein show that there is a bias towards the use of specific synonymous codons particularly in the helix and strand regions of the multi-domain FtsZ protein. Overall our findings suggest that in an indispensable and vital protein such as FtsZ, there is an inherent tendency to maintain form for optimized performance in spite of the extrinsic variability in coding features.

This study involves the assessment of physicochemical and microbiological parameters evaluated from nine sites along the stretch of the Kulik river for one year (during January-December 2020), in and around the town of Raiganj in Uttar Dinajpur district of West Bengal, India. The study was carried out to determine whether the river water can be used for drinking, domestic or household and recreation purposes. The parameters such as water temperature, pH, free carbon dioxide, dissolved oxygen, total alkalinity, total hardness, chlorides and total coliform count were analyzed using standard protocols. Significant differences were observed in the parameters both temporally and spatially. Total coliform count indicated the river water has high faecal contamination. The present study depicts the quality of the river and indicates that the water is non-potable. The result implies that the river needs continuous monitoring and treatment to maintain its aesthetic and hygienic value and to ensure its conservation for the future generation.

Background: Identifying orthologous genes plays a pivotal role in comparative genomics as the orthologous genes remain less diverged in the course of evolution. However, identifying orthologous genes is often difficult, slow, and idiosyncratic, especially in the presence of multiplicity of domains in proteins, evolutionary dynamics, multiple paralogous genes, incomplete genome data, and for distantly related species.Results: We present NORTH, a novel, automated, highly accurate and scalable machine learning based orhtologous gene cluster prediction method. We have utilized the biological basis of orthologous genes and made an effort to incorporate appropriate ideas from machine learning (ML) and natural language processing (NLP). NORTH outperforms the frequently used existing orthologous clustering algorithms on the OrthoBench benchmark, not only just quantitatively with a high margin, but qualitatively under the challenging scenarios as well. Furthermore, we studied 12,55,877 genes in the largest 250 orthologous clusters from the KEGG database, across 3,880 organisms comprising the six major groups of life. NORTH is able to cluster them with 98.48% precision, 98.43% recall and 98.44% F 1 score.Conclusions: This is the first study that maps the orthology identification to the text classification problem, and achieves remarkable accuracy and scalability. NORTH thus advances the state-of-the-art in orthologous gene prediction, and has the potential to be considered as an alternative to the existing phylogenetic tree and BLAST based methods.