Bioinformation and DDBJ Center, National Institute of Genetics.
Department of Molecular Life Science, Tokai University School of Medicine.
Genes Genet Syst. 2023 Nov 21;98(5):221-237. doi: 10.1266/ggs.23-00085. Epub 2023 Oct 14.
Since the early phase of the coronavirus disease 2019 (COVID-19) pandemic, a number of research institutes have been sequencing and sharing high-quality severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes to trace the route of infection in Japan. To provide insight into the spread of COVID-19, we developed a web platform named SARS-CoV-2 HaploGraph to visualize the emergence timing and geographical transmission of SARS-CoV-2 haplotypes. Using data from the GISAID EpiCoV database as of June 4, 2022, we created a haplotype naming system by determining the ancestral haplotype for each epidemic wave and showed prefecture- or region-specific haplotypes in each of four waves in Japan. The SARS-CoV-2 HaploGraph allows for interactive tracking of virus evolution and of geographical prevalence of haplotypes, and aids in developing effective public health control strategies during the global pandemic. The code and the data used for this study are publicly available at: https://github.com/ktym/covid19/.
自 2019 年冠状病毒病(COVID-19)大流行早期以来,许多研究机构一直在对高质量的严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)基因组进行测序和共享,以追踪日本的感染途径。为了深入了解 COVID-19 的传播情况,我们开发了一个名为 SARS-CoV-2 HaploGraph 的网络平台,用于可视化 SARS-CoV-2 单倍型的出现时间和地理传播。利用截至 2022 年 6 月 4 日 GISAID EpiCoV 数据库中的数据,我们通过确定每个流行波的原始单倍型,创建了一个单倍型命名系统,并展示了日本四个流行波中每个地区的特定单倍型。SARS-CoV-2 HaploGraph 允许对病毒进化和单倍型的地理流行情况进行交互式跟踪,有助于在全球大流行期间制定有效的公共卫生控制策略。本研究使用的代码和数据可在以下网址获取:https://github.com/ktym/covid19/。