No abstract

Long non-coding RNAs (lncRNAs) are the transcripts of length longer than 200 nucleotides. They are involved in the regulation of various biological activities. Leghorn and Fayoumi breeds of Gallus gallus were known to be having differential resistance against Newcastle Disease Virus (NDV) infection. Differentially expressed genes which were thought to be involved in this pattern of resistance were already studied. Here we report the analysis of the transcriptomic data of Harderian gland of Gallus gallus for studying the lncRNAs involved in regulation of these genes. Using bioinformatics approaches, a total of 37,411 lncRNAs were extracted and 359 lncRNAs were differentially expressing. Functional annotation using co-expression analysis revealed the involvement of lncRNAs in the regulation of various pathways. We also identified 1232 quantitative trait loci (QTLs) associated with the genes interacting with lncRNA. Additionally, we identified the role of lncRNAs as putative micro RNA precursors, and the interaction of differentially expressed Genes with transcription factors and micro RNAs. Our study revealed the role of lncRNAs during host response against NDV infection which would facilitate future experiments in unravelling regulatory mechanisms of development in the genetic improvement of the susceptible breeds of Gallus gallus.

No abstract

COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. It has six open reading frames (orf1ab, orf3a, orf6, orf7a, orf8, and orf10), a spike protein, a membrane protein, an envelope small membrane protein, and a nucleocapsid protein, out of which, orf1ab is the largest ORF coding different important non-structural proteins. In this study, an effort was made to evaluate the susceptibility of different animals against SARS-CoV-2 by analyzing the interactions of Spike and ACE2 proteins of the animals and propose a list of potential natural compounds binding to orf1ab of SARS-CoV-2. Here, we analyzed structural interactions between spike proteins of SARS-CoV-2 and the ACE2 receptor of 16 different hosts. A simulation for 50 ns was performed on these complexes. Based on post-simulation analysis, Chelonia mydas was found to have a more stable complex, while Bubalus bubalis, Aquila chrysaetos chrysaetos, Crocodylus porosus, and Loxodonta africana were found to have the least stable complexes with more fluctuations than all other organisms. Apart from that, we performed domain assignment of orf1ab of SARS-CoV-2 and identified 14 distinct domains. Out of these, Domain 3 (DNA/RNA polymerases) was selected as a target, as it showed no similarities with host proteomes and was validated in silico. Then, the top 10 molecules were selected from the virtual screening of ∼1.8 lakh molecules from the ZINC database, based on binding energy, and validated for ADME and toxicological properties. Three molecules were selected and analyzed further. The structural analysis showed that these molecules were residing within the pocket of the receptor. Finally, a simulation for 200 ns was performed on complexes with three selected molecules. Based on post-simulation analysis (RMSD, RMSF, Rg, SASA, and energies), the molecule ZINC000103666966 was found as the most suitable inhibitory compound against Domain 3. As this is an in silico prediction, further experimental studies could unravel the potential of the proposed molecule against SARS-CoV-2.