Tracking and predicting the evolution of human RNA viruses

Richard Neher
Biozentrum & SIB, University of Basel

slides at

Human seasonal influenza viruses

slide by Trevor Bedford

Positive tests for influenza in the USA by week

Data by the US CDC

Sequences record the spread of pathogens

Mutations accumulate at a rate of $10^{-5}$ per site and day!
images by Trevor Bedford

  • Influenza viruses evolve to avoid human immunity
  • Vaccines need frequent updates

Influenza B viruses have split into two lineages

Le Yan, RN, Shraiman, bioRxiv, 2018

GISRS and GISAID -- Influenza virus surveillance

  • comprehensive coverage of the world
  • timely sharing of data through GISAID -- often within 2-3 weeks of sampling
  • hundreds of sequences per week (in peak months)
→ requires continuous analysis and easy dissemination
→ interpretable and intuitive visualization

joint project with Trevor Bedford & his lab

by Trevor Bedford
by Trevor Bedford

Tracking diversity and spread of SARS-CoV-2 in Nextstrain

Available data on Jan 26

Early genomes differed by only a few mutations, suggesting very recent emergence

Interactive part on Nextstrain

VoCs have more mutations than expected...


VoCs and VoIs: rapid converging evolution by Emma Hodcroft

Reduced neutralization of VoCs by convalescent serum (B.1.351)

Cele et al, 2021, Wibmer et al 2021

Deep mutational scanning approaches

  • Library of pseudo-typed virus with mutations at every position
  • Propagate in cell culture with and without selection (serum, ABs)
  • Measure which variants are selected for
  • → assess mutations before they are observed
  • → screen for potentially important variants
  • → follow-up with virological/serological studies
Greaney et al 2021

Summary and Conclusions

  • Enormous amounts of data provide unprecedented real time picture of a pandemic
  • Several highly evolved variants of SARS-CoV-2 emerged in a short time
  • The current VoCs are likely just the tip of the iceberg
  • Processing, analyzing, and interpreting data is a major challenge
  • Integration of genomic and experimental data is key to generate insight


Trevor Bedford and his lab -- terrific collaboration since 2014

especially James Hadfield, Emma Hodcroft, Ivan Aksamentov, Moira Zuber, and Tom Sibley

Data we analyze are contributed by scientists from all over the world

Data are shared and curated by GISAID

Influenza and Theory acknowledgments

  • Boris Shraiman
  • Colin Russell
  • Trevor Bedford
  • Pierre Barrat
  • Oskar Hallatschek

  • All the NICs and WHO CCs that provide influenza sequence data
  • The WHO CCs in London and Atlanta for providing titer data