five

Table_2_Characterising Foot-and-Mouth Disease Virus in Clinical Samples Using Nanopore Sequencing.DOCX

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://figshare.com/articles/dataset/Table_2_Characterising_Foot-and-Mouth_Disease_Virus_in_Clinical_Samples_Using_Nanopore_Sequencing_DOCX/14603211
下载链接
链接失效反馈
官方服务:
资源简介:
The sequencing of viral genomes provides important data for the prevention and control of foot-and-mouth disease (FMD) outbreaks. Sequence data can be used for strain identification, outbreak tracing, and aiding the selection of the most appropriate vaccine for the circulating strains. At present, sequencing of FMD virus (FMDV) relies upon the time-consuming transport of samples to well-resourced laboratories. The Oxford Nanopore Technologies' MinION portable sequencer has the potential to allow sequencing in remote, decentralised laboratories closer to the outbreak location. In this study, we investigated the utility of the MinION to generate sequence data of sufficient quantity and quality for the characterisation of FMDV serotypes O, A, Asia 1. Prior to sequencing, a universal two-step RT-PCR was used to amplify parts of the 5′UTR, as well as the leader, capsid and parts of the 2A encoding regions of FMDV RNA extracted from three sample matrices: cell culture supernatant, tongue epithelial suspension and oral swabs. The resulting consensus sequences were compared with reference sequences generated on the Illumina MiSeq platform. Consensus sequences with an accuracy of 100% were achieved within 10 and 30 min from the start of the sequencing run when using RNA extracted from cell culture supernatants and tongue epithelial suspensions, respectively. In contrast, sequencing from swabs required up to 2.5 h. Together these results demonstrated that the MinION sequencer can be used to accurately and rapidly characterise serotypes A, O, and Asia 1 of FMDV using amplicons amplified from a variety of different sample matrices.
创建时间:
2021-05-17
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作