ABSTRACT
The pandemic spread of African swine fever (ASF) has caused serious effects on the global pig industry. Virus genome sequencing and genomic epidemiology analysis play an important role in tracking the outbreaks of the disease and tracing the transmission of the virus. Here we obtained the full-length genome sequence of African swine fever virus (ASFV) in the first outbreak of ASF in China on August 3rd, 2018 and compared it with other published genotype II ASFV genomes including 9 genomes collected in China from September 2018 to October 2020. Phylogenetic analysis on genomic sequences revealed that genotype II ASFV has evolved into different genetic clusters with temporal and spatial correlation since being introduced into Europe and then Asia. There was a strong support for the monophyletic grouping of all the ASFV genome sequences from China and other Asian countries, which shared a common ancestor with those from the Central or Eastern Europe. An evolutionary rate of 1.312 × 10−5 nucleotide substitutions per site per year was estimated for genotype II ASFV genomes. Eight single nucleotide variations which located in MGF110-1L, MGF110-7L, MGF360-10L, MGF505-5R, MGF505-9R, K145R, NP419L, and I267L were identified as anchor mutations that defined genetic clusters of genotype II ASFV in Europe and Asia. This study expanded our knowledge of the molecular epidemiology of ASFV and provided valuable information for effective control of the disease.
ABSTRACT
BACKGROUND: Mitochondria have been shown to play vital roles during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) development. Currently, it is unclear whether mitochondrial DNA (mtDNA) variants, which define mtDNA haplogroups and determine oxidative phosphorylation performance and reactive oxygen species production, are associated with COVID-19 risk. METHODS: A population-based case-control study was conducted to compare the distribution of mtDNA variations defining mtDNA haplogroups between healthy controls (n = 615) and COVID-19 patients (n = 536). COVID-19 patients were diagnosed based on molecular diagnostics of the viral genome by qPCR and chest X-ray or computed tomography scanning. The exclusion criteria for the healthy controls were any history of disease in the month preceding the study assessment. MtDNA variants defining mtDNA haplogroups were identified by PCR-RFLPs and HVS-I sequencing and determined based on mtDNA phylogenetic analysis using Mitomap Phylogeny. Student's t-test was used for continuous variables, and Pearson's chi-squared test or Fisher's exact test was used for categorical variables. To assess the independent effect of each mtDNA variant defining mtDNA haplogroups, multivariate logistic regression analyses were performed to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) with adjustments for possible confounding factors of age, sex, smoking and diseases (including cardiopulmonary diseases, diabetes, obesity and hypertension) as determined through clinical and radiographic examinations. RESULTS: Multivariate logistic regression analyses revealed that the most common investigated mtDNA variations (> 10% in the control population) at C5178a (in NADH dehydrogenase subunit 2 gene, ND2) and A249d (in the displacement loop region, D-loop)/T6392C (in cytochrome c oxidase I gene, CO1)/G10310A (in ND3) were associated with a reduced risk of severe COVID-19 (OR = 0.590, 95% CI 0.428-0.814, P = 0.001; and OR = 0.654, 95% CI 0.457-0.936, P = 0.020, respectively), while A4833G (ND2), A4715G (ND2), T3394C (ND1) and G5417A (ND2)/C16257a (D-loop)/C16261T (D-loop) were related to an increased risk of severe COVID-19 (OR = 2.336, 95% CI 1.179-4.608, P = 0.015; OR = 2.033, 95% CI 1.242-3.322, P = 0.005; OR = 3.040, 95% CI 1.522-6.061, P = 0.002; and OR = 2.890, 95% CI 1.199-6.993, P = 0.018, respectively). CONCLUSIONS: This is the first study to explore the association of mtDNA variants with individual's risk of developing severe COVID-19. Based on the case-control study, we concluded that the common mtDNA variants at C5178a and A249d/T6392C/G10310A might contribute to an individual's resistance to developing severe COVID-19, whereas A4833G, A4715G, T3394C and G5417A/C16257a/C16261T might increase an individual's risk of developing severe COVID-19.