**3. Impact of omics science and related fields on SARS-CoV-2 research**

With advanced techniques and bioinformatics tools, the scientific landscape has dramatically changed in recent years. The huge data yielding on omics science plays an important role in the steps related to the biology of SARS-CoV-2 infections towards understanding more [22]. These resources are tremendously necessary to scientists studying SARS-CoV-2 infections and provide a map and common reference points to reach the data for describing precisely viral transcripts and ORFs. Comparison of different genomic organizations among all the SARS-CoV-2 isolates forms a starting point to determine the evolutionary relationships in this virus family. The most important point that should not be missed is the instability of the nucleotide sequences in the virus genome, which causes high ratio mutations. Viral genomes data inherently in GenBank involves missing annotated parts that sequence needs to be corrected. Annotations of viral genomes conducted with the best tools are available to test gene prediction with precise algorithms to identify new genes [23]. The annotation process may cause inconsistent findings for different genomes as the terminology used to describe gene function [24]. Viral genomes need to be updated and re-annotated as additional strains are of importance for comparing sequences for the continual annotation process considering analogous by released versions in NCBI [25].

The RNA sequence and structure of the genomes could be easily sequenced, but to predict their role in infection with any certainty seems difficult at the course of an infection. *In vitro* experimentation results should prove the different ORFs identified through algorithms such as codon/pair usage, dinucleotide/junction usage, RNA structure differentiation which are detected by bioinformatics tools on a viral infection [26]. Even microarray using oligonucleotide probes to hybridize with putative exons and splice junctions could be beneficial for following the expression of predicted transcripts and splice variants in virus genome [27], single-cell RNA sequencing analysis of SARS-CoV-2 will help define how the virus integrates into a human as use host cell organization to regulate and code for all the required biologic process [28]. As this knowledge with different biological assays increasingly supports findings on SARS-CoV-2 and its pathogenic behavior, the proteomics data

### *SARS-CoV-2 Origin and COVID-19 Pandemic Across the Globe*

obtained on up/down-regulated expression levels expressed by the virus reflects ongoing RNA transcripts that can be evaluated as biological cases related to posttranslational processing playing role in protein formation complexity. Proteomics methods have also the potential to follow the modification of viral gene products during viral infection, which will help to characterize how post-translation modification that affects viral replication. Since omics technology maybe not sufficient alone to find effective compounds inhibiting viral replication and invasive negative effects that occurred on the human body, we should consider the detection of the genomic parts showing stability without a high mutation ratio to design targeted molecules with inhibitory potential [13]. Genomic screening using specific algorithms to identify conserved motifs and to predict protein structure could be an efficient way to understand protein functions [29]. In immunological studies, model organism, yeast, thanks to its two-hybrid (Bait and Prey) system that can be suggested to prove the protein–protein interactions among viral-cellular proteins and potential gene products cooperating in biological processes can be clarified by the construction of protein–protein interaction maps [30].
