Population genetics of rapid adaptation and the predictability of evolution

Richard Neher
Biozentrum, University of Basel

slides at neherlab.org/201706_facmtg.html

  • Evolution of HIV
  • Theory of evolution
  • Tracking and prediction of RNA virus evolution

Evolution of HIV

  • Chimp → human transmission ~1900 gave rise to HIV-1 group M
  • Diversified into subtypes that are ~20% different
  • evolves at a rate of about 0.1% per year
image: Sharp and Hahn, CSH Persp. Med.

HIV-1 sequencing before and after therapy

Zanini et al, eLife, 2015; Brodin et al, eLife, 2016. Collaboration with the group of Jan Albert

Population sequencing to track all mutations above 1%

  • diverge at 0.1-1% per year
  • almost full genomes coverage in 10 patients
  • full data set at hiv.tuebingen.mpg.de
Zanini et al, eLife, 2015; antibody data from Richman et al, 2003

Rapid evolution before therapy, no evolution on therapy

Brodin et al, eLife, 2016

Population genetics models

evolutionary processes ↔ trees ↔ genetic diversity

Kingman coalescent

strong selection

Bolthausen-Sznitman Coalescent

RN, Hallatschek, PNAS, 2013; see also Brunet and Derrida, PRE, 2007

Bursts in a tree ↔ high fitness genotypes

Can we read fitness of a tree?

  • Influenza virus evolves to avoid human immunity
  • Vaccines need frequent updates

Fitness inference from trees

$$P(\mathbf{x}|T) = \frac{1}{Z(T)} p_0(x_0) \prod_{i=0}^{n_{int}} g(x_{i_1}, t_{i_1}| x_i, t_i)g(x_{i_2}, t_{i_2}| x_i, t_i)$$
RN, Russell, Shraiman, eLife, 2014

Prediction of the dominating H3N2 influenza strain

RN, Russell, Shraiman, eLife, 2014



HIV acknowledgments

  • Fabio Zanini
  • Jan Albert
  • Johanna Brodin
  • Christa Lanz
  • Göran Bratt
  • Lina Thebo
  • Vadim Puller

Influenza and Theory acknowledgments

  • Boris Shraiman
  • Colin Russell
  • Trevor Bedford