Ebola Virus Epidemiology and Evolution in Nigeria

Folarin, Onikepe A.; Ehichioya, Deborah; Schaffner, Stephen F.; Winnicki, Sarah M.; Wohl, Shirlee; Eromon, Philomena; West, Kendra L.; Gladden-Young, Adrianne; Oyejide, Nicholas E.; Matranga, Christian B.; Deme, Awa Bineta; James, Ayorinde; Tomkins-Tinch, Christopher; Onyewurunwa, Kenneth; Ladner, Jason T.; Palacios, Gustavo; Nosamiefan, Iguosadolo; Andersen, Kristian G.; Omilabu, Sunday; Park, Daniel J.; Yozwiak, Nathan L.; Nasidi, Abdusallam; Garry, Robert F.; Tomori, Oyewale; Sabeti, Pardis C.; Happi, Christian T.

Within-host variants (iSNVs) that are shared between patients can provide a more detailed picture of transmission routes, but our data point out some important caveats about their usefulness. First, detection of iSNVs requires deep sequencing of good-quality samples, and that is not always possible: deep enough sequencing could be achieved for only two-thirds of our sequenced samples. Second, even when iSNV data are available, it may not all be meaningful. Some of the iSNVs we observed have previously been documented in unrelated data sets from Sierra Leone and Liberia [2, 13, 18] ; these included all 8 of the shared iSNVs. Most of our iSNVs, including most shared iSNVs, were low-frequency frameshift insertions or deletions. Because they can disrupt protein structure, they are unlikely to be transmitted. More likely, these recurrent iSNVs represent either recurring mutations in highly mutable regions of the EBOV genome or sequencing errors, especially because many of them occur in homopolymer regions. In either case, their value for determining transmission chains is uncertain. More research is necessary to fully make use of within-host genomic data in understanding transmission, including better sequencing coverage for all samples and improved methods to identify false-positives.