Table_6_Genomic Variations in SARS-CoV-2 Genomes From Gujarat: Underlying Role of Variants in Disease Epidemiology.XLSX

Humanity has seen numerous pandemics during its course of evolution. The list includes several incidents from the past, such as measles, Ebola, severe acute respiratory syndrome (SARS), and Middle East respiratory syndrome (MERS), etc. The latest edition to this is coronavirus disease 2019 (COVID-19), caused by the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of August 18, 2020, COVID-19 has affected over 21 million people from 180 + countries with 0.7 million deaths across the globe. Genomic technologies have enabled us to understand the genomic constitution of pathogens, their virulence, evolution, and rate of mutation, etc. To date, more than 83,000 viral genomes have been deposited in public repositories, such as GISAID and NCBI. While we are writing this, India is the third most affected country by COVID-19, with 2.7 million cases and > 53,000 deaths. Gujarat is the 11th highest affected state with a 3.48% death rate compared to the national average of 1.91%. In this study, a total of 502 SARS-CoV-2 genomes from Gujarat were sequenced and analyzed to understand its phylogenetic distribution and variants against global and national sequences. Further variants were analyzed from diseased and recovered patients from Gujarat and the world to understand its role in pathogenesis. Among the missense mutations present in the Gujarat SARS-CoV-2 genomes, C28854T (Ser194Leu) had an allele frequency of 47.62 and 7.25% in deceased patients from the Gujarat and global datasets, respectively. In contrast, the allele frequency of 35.16 and 3.20% was observed in recovered patients from the Gujarat and global datasets, respectively. It is a deleterious mutation present in the nucleocapsid (N) gene and is significantly associated with mortality in Gujarat patients with a p-value of 0.067 and in the global dataset with a p-value of 0.000924. The other deleterious variant identified in deceased patients from Gujarat (p-value of 0.355) and the world (p-value of 2.43E-06) is G25563T, which is located in Orf3a and plays a potential role in viral pathogenesis. SARS-CoV-2 genomes from Gujarat are forming distinct clusters under the GH clade of GISAID. This study will shed light on the viral haplotype in SARS-CoV-2 samples from Gujarat, India.

人类在演化历程中曾遭遇过多次大流行病。既往暴发的疫情包括麻疹、埃博拉、严重急性呼吸综合征（SARS）、中东呼吸综合征（MERS）等。最新暴发的大流行病则是由新型冠状病毒——严重急性呼吸综合征冠状病毒2型（SARS-CoV-2）引发的新型冠状病毒肺炎（COVID-19）。截至2020年8月18日，COVID-19已波及全球180余个国家，累计确诊超2100万例，全球累计死亡达70万例。基因组技术助力我们解析病原体的基因组构成、毒力、演化过程及突变速率等特征。截至目前，已有超过83000条病毒基因组序列被提交至GISAID、NCBI等公共数据库。在本文撰写之际，印度是全球第三大COVID-19疫情影响国，累计确诊270万例，死亡超5.3万例。其中古吉拉特邦为该国第11个受疫情影响最严重的邦，其病死率达3.48%，高于全国1.91%的平均水平。本研究对来自古吉拉特邦的502条SARS-CoV-2基因组进行测序与分析，以解析其相对于全球及本国序列的系统发育分布特征与变异情况。此外，本研究还针对古吉拉特邦及全球范围内的确诊与康复患者样本中的病毒变异株展开分析，以探究其在发病机制中的作用。在古吉拉特邦SARS-CoV-2基因组的错义突变中，C28854T（Ser194Leu）在古吉拉特邦及全球死亡患者数据集中的等位基因频率分别为47.62%与7.25%；与之相对，该突变在古吉拉特邦及全球康复患者数据集中的等位基因频率分别为35.16%与3.20%。该突变位于核衣壳（N）基因中，属于有害突变，在古吉拉特邦患者中与病死率显著相关（p值=0.067），在全球数据集该关联同样具有统计学意义（p值=0.000924）。另一项在古吉拉特邦死亡患者（p值=0.355）及全球死亡患者（p值=2.43×10^-6）中检出的有害突变为G25563T，该突变位于Orf3a基因区域，可能在病毒致病过程中发挥作用。来自古吉拉特邦的SARS-CoV-2基因组在GISAID的GH进化分支下形成了独特的聚类簇。本研究将有助于解析印度古吉拉特邦SARS-CoV-2样本的病毒单倍型特征。