Evolution of the SARS-CoV-2 genome based on continuous positive selection

The ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by the rapid outbreak of coronavirus 2 (SARS-CoV-2), has serious implications for the global economy and medical system. I gave it.

study: Ongoing positive selection facilitates the evolution of the SARS-CoV-2 genome.. Image Credit: peterschreiber.media/Shutterstock

SARS-CoV-2 is an RNA virus with a high mutation rate and causes rapid evolution.

Background

Natural selection plays an important role in the pathogenicity and infectivity of SARS-CoV-2, especially through adaptive mutations. Similar conditions have been reported for Zika and Ebola viruses. Since the advent of SARS-CoV-2 in Wuhan Province, China in 2019, many gene mutations have been accumulated.

Researchers have studied and documented the entire genome of the virus and have so far reported substitutions of approximately 29,735 nucleotides.

Scientists have observed that the SARS-CoV-2 strain shows numerous variations in infection and clinical manifestations. Some SARS-CoV-2 mutants show an increased infectivity compared to the original strain.

In addition, certain SARS-CoV-2 mutants can evade immune responses elicited by COVID-19 vaccination or spontaneous infection. Considering these differences in traits, the World Health Organization (WHO) has classified SARS-CoV-2 mutants into Variant of Concern (VOC) and Mutant of Concern (VOI).

Scientists emphasize the importance of predicting epidemic trends, developing effective strategies for controlling disease, and developing efficient COVID-19 vaccines to protect individuals from disease. doing. In addition, they emphasized the importance of understanding how natural selection facilitated the pathogenic and infectious evolution of SARS-CoV-2 during pandemics.

There are gaps in studies related to the identification of functional variants that influence the evolution of epidemiological and pathogenic features of SARS-CoV-2. Previous studies have reported two evolutionary hypotheses associated with the COVID-19 virus. This includes viral evolution within animal hosts and in human populations after zoonotic infections.

To date, the assessment of natural selection with SARS-CoV-2 has focused primarily on the migration phase of the host, the transition from animals to humans. In this case, researchers have studied sequence differences between SARS-CoV-2 and closely related viruses (such as BatCoV-RaTG13). There is a lack of effective methods for assessing uncertain ancestral sequences, assessing SARS-CoV-2 cluster infections, and reducing sampling bias.

Most of the studies available have been based on changes in allelic frequency of individual mutations that may not have occurred due to natural selection. Therefore, researchers have stated that it is important to determine candidate mutation loci for natural selection. So far, screening of the entire SARS-CoV-2 genome to determine the evolutionary perspectives of functional mutations and to understand their impact on epidemiological perspectives remains elusive.

About research

Scientists have recently focused on determining natural selection for the evolution of SARS-CoV-2 based on new methods. They said that the current method is a significant improvement over traditional methods based on founder effects, viral clustering infections, and sampling bias of viral genomic data.

In this study, researchers hypothesized that ongoing positive selections strongly influence the SARS-CoV-2 genome and play an important role in shaping the dynamics of the COVID-19 pandemic. This study Genomics, proteomics, bioinformatics..

In this study, researchers obtained the SARS-CoV-2 sequence from the 2019 Global Initiative on Sharing New Coronavirus Resources and All Influenza Data. They contained 3,328,405 sequences from 169 countries. Scientists used MUSCLE to align these sequences and determine nucleotide mutations by comparing the sequences to the reference sequence, the sequence of the original SARS-CoV-2 strain.

Scientists have divided these viral sequences into clusters according to genomic similarity based on global transmissibility and the development of clustering. They built a temporal and spatial landscape of mutations on top of the cluster. This helped identify mutations that are pathogenic and cause severe or altered clinical symptoms.

Survey results

Researchers compared the relative excesses of non-synonymous and synonymous substitutions as an efficient way to determine the effect of natural selection on SARS-CoV-2. This method is logically similar to the McDonald’s Kleitman test in molecular evolution. The method proposed in the current study is called the NSRF1 method, which compares gene polymorphisms within a species.

NSRF1 is a new way to determine the relative abundance of nucleocapsid and spike (Nm / Sm ratio) proteins between high and low allelic mutations. Researchers investigated the increasing or decreasing trend of Nm / Sm ratios with enhanced mutation allele frequency. In this regard, scientists have assumed that frequent mutations tend to have a longer period of natural selection.

The results of the study show that the ongoing positive selection is responsible for human affinity for improved transmissibility and avoidance of host antiviral immunity.

Closing words

The authors stated that proportionally increasing or decreasing the Nm / Sm ratio is a more efficient indicator of natural selection. Current studies have provided multiple pieces of evidence that the SARS-CoV-2 genome is constrained under purification options during a pandemic.

Importantly, this study provided a list of 556 mutations as presumed target sites for natural selection. Scientists have shown that mutations between cluster divergence or frequency within a cluster increase pathogenicity and infectivity. This list provides the basis for future research related to clinical treatment.