Introduction:: The rapid emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in an increased mortality rate across the globe. However, the underlying mechanism of SARS-CoV-2 altering human immune response is still elusive. The existing literature on miRNA mediated pathogenesis of RNA virus viz. Dengue virus, West Nile virus, etc. raises a suspicion that miRNA encoded by SARS-CoV-2 might facilitate virus replication and regulate the host’s gene expression at the post-transcriptional level. Methods:: We investigated this possibility via computational prediction of putative miRNAs encoded by the SARS-CoV-2 genome using a novel systematic pipeline that predicts putative mature-miRNA and their targeted genes transcripts. To trace down if viral-miRNAs targeted the genes critical to the immune pathway, we assessed whether mature miRNA transcripts exhibit effective hybridization with the 3’UTR region of human gene transcripts. Conversely, we also tried to study human miRNA-mediated viral gene regulation to get insight into the miRNA mediated offense and defense mechanism of viruses and their host organisms in toto. Results:: Our analysis led us to shortlist six putative miRNAs that target, majorly, genes related to cell proliferation/differentiation/signaling, and senescence. Nonetheless, they also target immune-related genes that directly/indirectly orchestrate immune pathways like TNF (Tumor Necrosis Factor) signaling and Chemokine signaling pathways putatively serving as the nucleus to cytokine storms. Conclusion:: Besides, these six miRNAs were found to conserved so far across 80 complete genomes of SARS-CoV-2 (NCBI Virus, last assessed 12 April 2020) including Indian strains that are also targeted by 7 human miRNAs and can, therefore, be exploited to develop MicroRNA-Attenuated Vaccines.
Rice, a staple food worldwide, contains varying amount of nutrients in different grain tissues. The underlying molecular mechanism of such distinct nutrient partitioning remains poorly-investigated. Here, an optimized rapid Laser Capture Microdissection (LCM) approach was used to individually collect pericarp, aleurone, embryo and endosperm from 10 Days After Fertilization (DAF) old grains. Subsequent RNA-Seq analysis in these tissues have identified 7760 differentially expressed genes (DEGs). Analysis of promoter sequences of tissue specific genes identified many known and novel cis-elements important for grain filling and seed development. Using identified DEGs, comprehensive spatial gene expression pathways were built for spatial accumulation of starch, proteins, lipids and iron. The extensive transcriptomic analysis has provided many novel insights about nutrient partitioning mechanisms, for instance, it reveals a gradient in Seed Storage Protein accumulation across the analysed four tissue-types. It further reveals that partitioning of various minerals, such as iron, is most likely regulated through transcriptional control of their transporters. In addition, the extensive analysis of this study is presented as an interactive online tool (https://biogeek.shinyapps.io/DEGs/) that provides a much-needed resource for future functional genomics studies aimed to improve grain quality and seed development.
An outbreak of “Pneumonia of Unknown Etiology” occurred in Wuhan, China, in late December 2019. Later, the agent factor was identified and coined as SARS-CoV-2, and the disease was named coronavirus disease 2019 (COVID-19). In a shorter period, this newly emergent infection brought the world to a standstill. On 11 March 2020, the WHO declared COVID-19 as a pandemic. Researchers across the globe have joined their hands to investigate SARS-CoV-2 in terms of pathogenicity, transmissibility, and deduce therapeutics to subjugate this infection. The researchers and scholars practicing different arts of medicine are on an extensive quest to come up with safer ways to curb the pathological implications of this viral infection. A huge number of clinical trials are underway from the branch of allopathy and naturopathy. Besides, a paradigm shift on cellular therapy and nano-medicine protocols has to be optimized for better clinical and functional outcomes of COVID-19-affected individuals. This article unveils a comprehensive review of the pathogenesis mode of spread, and various treatment modalities to combat COVID-19 disease.
Presence of Simple Sequence Repeats (SSRs), both in genic and intergenic regions, have been widely studied in eukaryotes, prokaryotes, and viruses. In the current study, we undertook a survey to analyze the frequency and distribution of microsatellites or SSRs in multiple genomes of Coronaviridae members. We successfully identified 919 SSRs with length≥12 bp across 55 reference genomes majority of which (838 S SRs) were found abundant in genic regions. The in-silico analysis further identified the preferential abundance of hexameric SSRs than any other size-based motif class. Our analysis shows that the genome size and GC content of the genome had a weak influence on SSR frequency and density. However, we find a positive correlation of SSRs GC content with genomic GC content. We also report relatively low abundances of all theoretically possible 501 repeat motif classes in all the genomes of Coronaviridae . The majority of SSRs were AT-rich. Overall, we see an underrepresentation of SSRs across the genomes of Coronaviridae . Besides, our integrative study highlights the presence of SSRs in ORF1ab (nsp3, nsp4, nsp5A_3CLpro and nsp5B_3CLpro, nsp6, nsp10, nsp12, nsp13, & nsp15 domains), S, ORF3a, ORF7a, N & 3′ UTR regions of SARS-CoV-2 and harbours multiple mutations (3′UTR and ORF1ab SSRs serving as major mutational hotspots). This indicates the genic SSRs are under selection pressure against mutations that might alter the reading frame and at the same time responsible for rapid protein evolution. Our preliminary results indicate the significance of the limited repertoire of SSRs in the genomes of Coronaviridae.
The severe acute respiratory syndrome coronavirus 2 that causes coronavirus disease 2019 (COVID-19) disrupted the normal functioning throughout the world since early 2020 and it continues to do so. Nonetheless, the global pandemic was taken up as a challenge by researchers across the globe to discover an effective cure, either in the form of a drug or vaccine. This resulted in an unprecedented surge of experimental and computational data and publications, which often translated their findings in the form of databases (DBs) and tools. Over 160 such DBs and more than 80 software tools were developed, which are uncharacterized, unannotated, deployed at different universal resource locators and are challenging to reach out through a normal web search. Besides, most of the DBs/tools are present on preprints and are either underutilized or unrecognized because of their inability to make it to top Google search hits. Henceforth, there was a need to crawl and characterize these DBs and create a compendium for easy referencing. The current article is one such concerted effort in this direction to create a COVID-19 resource compendium (COVIDium) that would facilitate the researchers to find suitable DBs and tools for their research studies. COVIDium tries to classify the DBs and tools into 11 broad categories for quick navigation. It also provides end-users some generic hit terms to filter the DB entries for quick access to the resources. Additionally, the DB provides Tracker Dashboard, Neuro Resources, references to COVID-19 datasets and protein–protein interactions. This compendium will be periodically updated to accommodate new resources. Database URL: The COVIDium is accessible through http://kraza.in/covidium/
Background Mitochondria are the cell organelles that produce the majority of the chemical energy required to power the biochemical reactions of the cell. Despite being a part of a eukaryotic host cell, the mitochondria contain a separate genome whose origin is linked with the endocytosis of a prokaryotic cell by the eukaryotic host cell and encodes separate genomic information throughout their genomes. Mitochondrial genomes accommodate essential genes and are regularly utilized in biotechnology and phylogenetics. Various assemblers capable of generating full mitochondrial genomes are being continuously developed. These tools often use whole-genome sequencing data as an input containing reads from the mitochondrial genome. Till now no published work has explored the systematic comparison of all the available tools for assembling mitochondrial genome using short-read sequencing data. This evaluation is required in order to identify the best tool that can be well optimized for small-scale projects or even national-level research. Results Here we present a benchmark study of ten mitochondrial assembly tools capable of producing mitochondrial genomes for whole genome paired-end sequencing data. Simulated and real whole genome sequencing data was used as an input for these assemblers. Each of these publicly accessible tools are containerized as docker images to ensure the reproducibility. Our findings demonstrate that the examined assemblers have various computing requirements and degrees of success with the input datasets. Conclusions Based on the overall performance metrics and consistency in assembly quality for all sequencing data, MToolBox performed the best. However, among all the assemblers for simulated datasets, NOVOPlasty consumed the smallest amount of runtime and processing resources. Therefore, NOVOPlasty may be more practical to use when there is a big sample size and a lack of computational resources. Besides, as long read sequencing gains popularity, mitochondrial genome assemblers that can use long read sequencing data must be developed.
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