International travelers and genomics uncover a ‘hidden’ Zika outbreak

Nathan D. Grubaugh; Sharada Saraf; Karthik Gangavarapu; Alexander Watts; Amanda L. Tan; Rachel J. Oidtman; Jason T. Ladner; Glenn Oliveira; Nathaniel L. Matteson; Moritz U.G. Kraemer; Chantal B.F. Vogels; Aaron Hentoff; Deepit Bhatia; Danielle Stanek; Blake Scott; Vanessa Landis; Ian Stryker; Marshall R. Cone; Edgar W. Kopp; Andrew C. Cannons; Lea Heberlein-Larson; Stephen White; Leah D. Gillis; Michael J. Ricciardi; Jaclyn Kwal; Paola K. Lichtenberger; Diogo M. Magnani; David I. Watkins; Gustavo Palacios; Davidson H. Hamer; Lauren M. Gardner; T. Alex Perkins; Guy Baele; Kamran Khan; Andrea Morrison; Sharon Isern; Scott F. Michael; Kristian G. Andersen

Our open source software package, iVar (Grubaugh et al., 2018b) , was used to process the Zika virus sequencing data and call the consensus sequences. Source code and detailed documentation for iVar can be found at https://github.com/andersen-lab/ivar. In brief, BWA (Li and Durbin, 2009 ) was used to align the paired-end reads to a reference genome (GenBank KX087101). The primer sequences were trimmed from the reads using a BED file, with the primer positions, followed by quality trimming. The consensus sequence was called by the majority nucleotide at each position with >10x coverage. All alignments and consensus sequences were visually inspected using Geneious v9.1.5 (Kearse et al., 2012) . The Zika virus sequences generated here can be found using the NCBI Bioproject PRJNA438510.