African swine fever (ASF) outbreak have caused tremendous economic loss to the pig industry in China since its emergence in August 2018. Previous studies revealed that many published sequences are not suitable for detailed analyses due to the lack of data regarding quality parameters and methodology, and outdated annotations. Thus, high-quality genomes of highly pathogenic strains that can be used as references for early Chinese ASF outbreaks are still lacking, and little is known about the features of intra-host variants of ASF virus (ASFV). In this study, a full genome sequencing of clinical samples from the first ASF outbreak in Guangdong in 2018 was performed using MGI (MGI Tech Co., Ltd., Shenzhen, China) and Nanopore sequencing platforms, followed by Sanger sequencing to verify the variations. With 22 sequencing corrections, we obtained a high-quality genome of one of the earliest virulent isolates, GZ201801_2. After proofreading, we improved (add or modify) the annotations of this isolate using the whole genome alignment with Georgia 2007/1. Based on the complete genome sequence, we constructed the methylation profiles of early ASFV strains in China and predicted the potential 5mC and 6mA methylation sites, which are likely involved in metabolism, transcription, and replication. Additionally, the intra-host single nucleotide variant distribution and mutant allele frequency in the clinical samples of early strain were determined for the first time and found a strong preference for A and T substitution mutation, non-synonymous mutations, and mutations that resulted in amino acid substitutions into Lysine. In conclusion, this study provides a high-quality genome sequence, updated genome annotation, methylation profile, and mutation spectrum of early ASFV strains in China, thereby providing a reference basis for further studies on the evolution, transmission, and virulence of ASFV.
Keywords: African swine fever; annotation; methylation; mutation spectrum; viral genome.
Copyright © 2022 Xu, Gao, Kuang, Xing, Wang, Cao, Xu, Liu, Huang, Zheng, Gong, Wang, Shi, Zhang and Sun.