Host Immune Response Driving SARS-CoV-2 Evolution

Abstract

The transmission and evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are of paramount importance in controlling and combating the coronavirus disease 2019 (COVID-19) pandemic. Currently, over 15,000 SARS-CoV-2 single mutations have been recorded, which have a great impact on the development of diagnostics, vaccines, antibody therapies, and drugs. However, little is known about SARS-CoV-2's evolutionary characteristics and general trend. In this work, we present a comprehensive genotyping analysis of existing SARS-CoV-2 mutations. We reveal that host immune response via APOBEC and ADAR gene editing gives rise to near 65% of recorded mutations. Additionally, we show that children under age five and the elderly may be at high risk from COVID-19 because of their overreaction to the viral infection. Moreover, we uncover that populations of Oceania and Africa react significantly more intensively to SARS-CoV-2 infection than those of Europe and Asia, which may explain why African Americans were shown to be at increased risk of dying from COVID-19, in addition to their high risk of COVID-19 infection caused by systemic health and social inequities. Finally, our study indicates that for two viral genome sequences of the same origin, their evolution order may be determined from the ratio of mutation type, C > T over T > C.

Keywords: ADAR; APOBEC; COVID-19; SARS-CoV-2; gene editing.

Figure 1

The distribution of 12 SNP types among unique mutations in the SARS-CoV-2 genome isolates from different age groups. The text inside each circle represents the total number of records that have age information for different age groups.

Figure 2

The distribution of 12 SNP types among unique mutations in the SARS-CoV-2 genome isolates from two gender groups. The total number of records in the female group is 5762 and the total number of records in the male group is 7012.

Figure 3

The distribution of 12 SNP types among unique mutations in the SARS-CoV-2 genome isolates from different age groups among female patients. The text inside each circle represents the total number of records that have age information for different age groups.

Figure 4

The distribution of 12 SNP types among unique mutations in the SARS-CoV-2 genome isolates from different age groups among male patients. The text inside each circle represents the total number of records that have age information for different age groups.

Figure 5

The distribution of 12 SNP types among unique mutations in the SARS-CoV-2 genome isolates in six continents. The text inside each circle represents the total number of records in each continent.

Figure 6

SNP frequencies on 2-mer motifs. (a) SNP frequencies are at the first position of 2-mer motifs. (b) SNP frequencies are at the second position of 2-mer motifs.

Figure 7

SNP frequency at the first positions of the 3-mer motifs. (a) A or T is at the first position of 3-mer motifs. (b) C or G is at the first position of 3-mer motifs.

Figure 8

SNP frequency at the second position of 3-mer motifs. (a) A or T is at the second position of 3-mer motifs. (b) C or G is at the second position of 3-mer motifs.

Figure 9

SNP frequency at the third position of the 3-mer motifs. (a) A or T is at the third position of 3-mer motifs. (b) C or G is at the third position of 3-mer motifs.

Figure 10

The distribution of 12 SNP types among SARS-CoV, Bat-SL-BM48-31, Bat-SL-CoVZC45, Bat-SL-RaTG13, and SARS-CoV-2. Here, the text at the top represents the reference genome and the text at the bottom represents the mutant sequence.

Figure 11

Comparison of the ratios of 12 SNP types among unique mutations (red) and non-unique mutations (blue) in SARS-CoV-2 genomes globally. Here, if we count the same mutation that appears in different SARS-CoV-2 isolates only once, we call those mutations unique mutations. If we count the same mutation in different SARS-CoV-2 isolates repeatedly according to their frequency, then all of the mutations that are detected in the complete SARS-CoV-2 genome sequences are called non-unique mutations.

Figure 12

Comparison of the ratios of 12 SNP types among unique mutations (red) and non-unique mutations (blue) in MERS-CoV genome isolates. Here, if we count the same mutation that appears in different MERS-CoV isolates only once, we call those mutations unique mutations. If we count the same mutation in different MERS-CoV isolates repeatedly according to their frequency, then all of the mutations that are detected in the complete MERS-CoV genome sequences are called the non-unique mutations.

Figure 13

Genome-wide SARS-CoV-2 mutation distribution. The y-axis represents the natural log frequency for each mutation on a specific position of the complete SARS-CoV-2 genome. While only a few landmark positions are labeled with gene (protein) names, the relative positions of other genes (proteins) can be inferred from Table 5.