4.7 Article

Genomic surveillance of Rift Valley fever virus: from sequencing to lineage assignment

期刊

BMC GENOMICS
卷 23, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s12864-022-08764-6

关键词

RVFV; Rift Valley fever virus; Genotyping; Genomic surveillance; Lineage; L-segment; M-segment; S-segment; Glycoprotein Gn; Sequencing

资金

  1. German government through the Federal Ministry of Economic Cooperation and Development (BMZ)
  2. Rockefeller Foundation
  3. Africa CDC
  4. CGIAR Research Programs on Livestock and Agriculture for Nutrition Health
  5. Department of the Defense, Defense Threat Reduction Agency [HDTRA11910031]
  6. U.S. Department of Defense (DOD) [HDTRA11910031] Funding Source: U.S. Department of Defense (DOD)

向作者/读者索取更多资源

Genetic evolution of Rift Valley fever virus (RVFV) in Africa has been influenced by environmental changes, with 15 lineages circulating in sub-Saharan Africa. International trade and mosquito transmission are responsible for outbreaks, and genomic surveillance is crucial for intervention strategies.
Genetic evolution of Rift Valley fever virus (RVFV) in Africa has been shaped mainly by environmental changes such as abnormal rainfall patterns and climate change that has occurred over the last few decades. These gradual environmental changes are believed to have effected gene migration from macro (geographical) to micro (reassortment) levels. Presently, 15 lineages of RVFV have been identified to be circulating within the Sub-Saharan Africa. International trade in livestock and movement of mosquitoes are thought to be responsible for the outbreaks occurring outside endemic or enzootic regions. Virus spillover events contribute to outbreaks as was demonstrated by the largest epidemic of 1977 in Egypt. Genomic surveillance of the virus evolution is crucial in developing intervention strategies. Therefore, we have developed a computational tool for rapidly classifying and assigning lineages of the RVFV isolates. The computational method is presented both as a command line tool and a web application hosted at https://www. genomedetective.com/app/typingtool/rvfv/. Validation of the tool has been performed on a large dataset using glycoprotein gene (Gn) and whole genome sequences of the Large (L), Medium (M) and Small (S) segments of the RVFV retrieved from the National Center for Biotechnology Information (NCBI) GenBank database. Using the Gn nucleotide sequences, the RVFV typing tool was able to correctly classify all 234 RVFV sequences at species level with 100% specificity, sensitivity and accuracy. All the sequences in lineages A (n = 1 0) , B (n = 1), C (n = 88), D (n = 1), E (n = 3), F (n = 2), G (n = 2), H (n = 105), I (n = 2),J (n = 1), K (n = 4), L (n= 8), M (n = 1), N (n = 5) and 0 (n = 1) were also correctly classified at phylogenetic level. Lineage assignment using whole RVFV genome sequences (L, M and S-segments) did not achieve 100% specificity, sensitivity and accuracy for all the sequences analyzed. We further tested our tool using genomic data that we generated by sequencing 5 samples collected following a recent RVF outbreak in Kenya. All the 5 samples were assigned lineage C by both the partial (Gn) and whole genome sequence classifiers. The tool is useful in tracing the origin of outbreaks and supporting surveillance efforts.

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