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. 2023 Mar 9:14:1136386.
doi: 10.3389/fmicb.2023.1136386. eCollection 2023.

Variation in synonymous evolutionary rates in the SARS-CoV-2 genome

Qianru Sun  1   2 , Jinfeng Zeng  1   2 , Kang Tang  1   2 , Haoyu Long  1   2 , Chi Zhang  1   2 , Jie Zhang  1   2 , Jing Tang  1   2 , Yuting Xin  1   2 , Jialu Zheng  1   2 , Litao Sun  1   2 , Siyang Liu  1   2 , Xiangjun Du  1   2   3
Affiliations

Variation in synonymous evolutionary rates in the SARS-CoV-2 genome

Qianru Sun et al. Front Microbiol. .

Abstract

Introduction: Coronavirus disease 2019 is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Influential variants and mutants of this virus continue to emerge, and more effective virus-related information is urgently required for identifying and predicting new mutants. According to earlier reports, synonymous substitutions were considered phenotypically silent; thus, such mutations were frequently ignored in studies of viral mutations because they did not directly cause amino acid changes. However, recent studies have shown that synonymous substitutions are not completely silent, and their patterns and potential functional correlations should thus be delineated for better control of the pandemic.

Methods: In this study, we estimated the synonymous evolutionary rate (SER) across the SARS-CoV-2 genome and used it to infer the relationship between the viral RNA and host protein. We also assessed the patterns of characteristic mutations found in different viral lineages.

Results: We found that the SER varies across the genome and that the variation is primarily influenced by codon-related factors. Moreover, the conserved motifs identified based on the SER were found to be related to host RNA transport and regulation. Importantly, the majority of the existing fixed-characteristic mutations for five important virus lineages (Alpha, Beta, Gamma, Delta, and Omicron) were significantly enriched in partially constrained regions.

Discussion: Taken together, our results provide unique information on the evolutionary and functional dynamics of SARS-CoV-2 based on synonymous mutations and offer potentially useful information for better control of the SARS-CoV-2 pandemic.

Keywords: SARS-CoV-2; binding motif; codon usage; dominant variants; synonymous evolutionary rate.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Landscape of synonymous evolutionary rate (SER) of the SARS-CoV-2 genome. (A) SER density distribution in all ORFs of SARS-CoV-2. (B) Violin plot of SER distribution for representative ORF1a, ORF1b, S, and N regions. (C) SER across the whole genomes based on sliding windows. Black dotted lines were 90th, 50th, and 10th percentile levels of SER. (D) Percentiles are used to divide regions. The greater the SER, the more freedom; the smaller the SER, the greater the constraint.
Figure 2
Figure 2
Characteristics for the conserved motifs. Length (A) and Base composition (B) of identified motifs enriched in the constrained regions. The identification indexes are defined by sorting by P-value from the smallest to the largest. (C) Positions of identified motifs on the genome. The location of identified motifs was indicated by short black blocks in the ORFs. The vertical axis represents the credibility of the motif. (D) Motifs and related human RBPs. Motifs are colored in blue, and RBPs are colored in red. (E) GO terms enriched for motif-related human RBPs, including biological process, molecular function, and cellular component.
Figure 3
Figure 3
Feature SHAP value and contribution. (A) SHAP value for the top 20 features. Each point represents a sample. A SHAP value greater than 0 contributes to a higher SER, while a value less than 0 contributes to a lower SER. Feature value represents the value of each sample. (B) Feature importance pie chart. The outer ring represents the grouping, while the inner ring represents each specific feature. Percentage represents the proportion of the total interpretability.
Figure 4
Figure 4
Characteristic mutations in five lineages. (A) Accumulated characteristic mutations in Alpha, Beta, Gamma, and Delta lineages. (B, C) Accumulated characteristic mutations in the Omicron lineage and their specific positions.
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Grants and funding

This study was supported by the National Key Research and Development Projects of the Ministry of Science and Technology of China under grant 2021YFC2301300; the Shenzhen Science and Technology Program under grant KQTD20180411143323605, JSGG20200225152008136, and GXWD20201231165807008; the Guangdong Frontier and Key Tech Innovation Program under grants 2019B020228001, 2019B111103001, 2021A111112007, and 2022B1111020006; and the Natural Science Foundation of Guangdong Province, China, under grant 2021A1515011592.
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