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Overlapping genes (OGs) draw the focus of recent day's research. However, the significance of OGs in prokaryotic genomes remained unexplored. As an adaptation to high temperature, thermophiles were shown to eliminate their intergenic regions. Therefore, it could be possible that prokaryotes would increase their OG content to adapt to high temperature. To test this hypothesis, we carried out a comparative study on OG frequency of 256 prokaryotic genomes comprising both thermophiles and non-thermophiles. It was found that thermophiles exhibit higher frequency of overlapping genes than non-thermophiles. Moreover, overlap frequency was found to correlate with optimal growth temperature (OGT) in prokaryotes. Long overlap frequency was found to hold a positive correlation with OGT resulting in an abundance of long overlaps in thermophiles compared to non-thermophiles. On the other hand, short overlap (1-4 nucleotides) frequency (SOF) did not yield any direct correlation with OGT. However, the correlation of SOF with CAIavg (extent of variation of codon usage bias measured as the mean of codon adaptation index of all genes in a given genome) and IG% (proportion of intergenic regions) indicate that they might upregulate the aforementioned factors (CAIavg and IG%) which are already known to be vital forces for thermophilic adaptation. From these evidences, we propose that the OG content bears a strong link to thermophily. Long overlaps are important for their genome compaction and short overlaps are important to uphold high CAIavg. Our findings will surely help in better understanding of the significance of overlapping gene content in prokaryotic genomes.

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More than a decade, overlapping genes in RNA viruses became a subject of research which has explored various effect of gene overlapping on the evolution and function of viral genomes like genome size compaction. Additionally, overlapping regions (OVRs) are also reported to encode elevated degree of protein intrinsic disorder (PID) in unspliced RNA viruses. With the aim to explore the roles of OVRs in HIV-1 pathogenesis, we have carried out an in-depth analysis on the association of gene overlapping with PID in 35 HIV1- M subtypes. Our study reveals an over representation of PID in OVR of HIV-1 genomes. These disordered residues endure several vital, structural features like short linear motifs (SLiMs) and protein phosphorylation (PP) sites which are previously shown to be involved in massive host–virus interaction. Moreover, SLiMs in OVRs are noticed to be more functionally potential as compared to that of non-overlapping region. Although, density of experimentally verified SLiMs, resided in 9 HIV-1 genes, involved in host–virus interaction do not show any bias toward clustering into OVR, tat and rev two important proteins mediates host–pathogen interaction by their experimentally verified SLiMs, which are mostly localized in OVR. Finally, our analysis suggests that the acquisition of SLiMs in OVR is mutually exclusive of the occurrence of disordered residues, while the enrichment of PPs in OVR is solely dependent on PID and not on overlapping coding frames. Thus, OVRs of HIV-1 genomes could be demarcated as potential molecular recognition sites during host–virus interaction.

Viral infections are one of the major causes of human diseases that cause yearly millions of deaths and seriously threaten global health, as we have experienced with the COVID-19 pandemic. Numerous approaches have been adopted to understand viral diseases and develop pharmacological treatments. Among them, the study of virus-host protein-protein interactions is a powerful strategy to comprehend the molecular mechanisms employed by the virus to infect the host cells and to interact with their components. Experimental protein-protein interactions described in the scientific literature have been systematically captured into several molecular interaction databases. These data are organized in structured formats and can be easily downloaded by users to perform further bioinformatic and network studies. Network analysis of available virus-host interactomes allow us to understand how the host interactome is perturbed upon viral infection and what are the key host proteins targeted by the virus and the main cellular pathways that are subverted. In this review, we give an overview of publicly available viral-human protein-protein interactions resources and the community standards, curation rules and adopted ontologies. A description of the main virus-human interactome available is provided, together with the main network analyses that have been performed. We finally discuss the main limitations and future challenges to assess the quality and reliability of protein-protein interaction datasets and resources.