Viral genomes reveal patterns of the SARS-CoV-2 outbreak in Washington State
Nicola F. Müller*†1, Cassia Wagner†1,2, Chris D. Frazar†2, Pavitra Roychoudhury†1,2, Jover Lee1, Louise H. Moncla1, Benjamin Pelle2, Matthew Richardson2, Erica Ryke2, Hong Xie3, Lasata Shrestha3, Amin Addetia3, Victoria M. Rachleff1,3, Nicole A. P. Lieberman3, Meei-Li Huang3, Romesh Gautom4, Geoff Melly4, Brian Hiatt4, Philip Dykema4, Amanda Adler5, Elisabeth Brandstetter6, Peter D. Han2, Kairsten Fay1, Misja Ilcisin1, Kirsten Lacombe5, Thomas R. Sibley1, Melissa Truong2, Caitlin R. Wolf6, Michael Boeckh1,6,7, Janet A. Englund5,8, Michael Famulare9, Barry R. Lutz7,10, Mark J. Rieder7, Matthew Thompson11, Jeffrey S. Duchin12,13, Lea M. Starita2,7, Helen Y. Chu12,7, Jay Shendure2,7,14, Keith R. Jerome1,3, Scott Lindquist4, Alexander L. Greninger‡1,3, Deborah A. Nickerson‡2,7, Trevor Bedford*‡1,2,7
1Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
2Department of Genome Sciences, University of Washington, Seattle, WA, USA
3Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
4Washington State Department of Health, Shoreline, WA, USA
5Seattle Children’s Research Institute, Seattle, WA, USA
6Department of Medicine, Division of Allergy and Infectious Diseases, University of Washington, Seattle, WA, USA
7Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
8Department of Pediatrics, University of Washington, Seattle, WA, USA.
9Institute for Disease Modeling, Bellevue, WA, USA
10Department of Bioengineering, University of Washington, Seattle, WA, USA.
11Department of Global Health, University of Washington, Seattle, WA, USA.
12Department of Medicine, Division of Allergy and Infectious Diseases, University of Washington, Seattle, WA, USA.
13Public Health - Seattle & King County, Seattle, WA, USA
14Howard Hughes Medical Institute, Seattle, WA, USA
†These authors contributed equally.
*To whom correspondence should be addressed.
Abstract: The rapid spread of SARS-CoV-2 has gravely impacted societies around the world. Outbreaks in different parts of the globe are shaped by repeated introductions of new lineages and subsequent local transmission of those lineages. Here, we sequenced 3940 SARS-CoV-2 viral genomes from Washington State to characterize how the spread of SARS-CoV-2 in Washington State (USA) was shaped by differences in timing of mitigation strategies across counties, as well as by repeated introductions of viral lineages into the state. Additionally, we show that the increase in frequency of a potentially more transmissible viral variant (614G) over time can potentially be explained by regional mobility differences and multiple introductions of 614G, but not the other variant (614D) into the state. At an individual level, we see evidence of higher viral loads in patients infected with the 614G variant. However, using clinical records data, we do not find any evidence that the 614G variant impacts clinical severity or patient outcomes. Overall, this suggests that with regards to D614G, the behavior of individuals has been more important in shaping the course of the pandemic than changes in the virus.
Software contains the NAB.jar file, which is a compiled BEAST2 jar file that includes the multitree coalescent. It can be run just like any other BEAST2 jar file from the command line.
scripts contains all the matlab and R scripts that are needed to build xml files, to get clusters and to plot the figures in the manuscript
xmls contains xml files to run the multitree coalescent analyses. The xml files are given for rep0 whereas the runs for the manuscript were in triplets (with rep1 and rep2 files, while not given, being exactly the same as the rep0 files).