Predicting evolution from the shape of genealogical trees

By Richard A. Neher, C. Russell, Boris I. Shraiman. 2014

202 citations recorded by the source corpus.

Given a sample of genome sequences from an asexual population, can one predict its evolutionary future? Here we demonstrate that the branching patterns of reconstructed genealogical trees contains information about the relative fitness of the sampled sequences and that this information can be used to predict successful strains. Our approach is based on the assumption that evolution proceeds by accumulation of small effect mutations, does not require species specific input and can be applied to any asexual population under persistent selection pressure. We demonstrate its performance using historical data on seasonal influenza A/H3N2 virus. We predict the progenitor lineage of the upcoming influenza season with near optimal performance in 30% of cases and make informative predictions in 16 out of 19 years. Beyond providing a tool for prediction, our ability to make informative predictions implies persistent fitness variation among circulating influenza A/H3N2 viruses. DOI: http://dx.doi.org/10.7554/eLife.03568.001

Subfields: Epidemiology, Genetics, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Epidemiology

1. Aleksandra M. Walczak
2. Ville Mustonen
3. Michael Lässig

In Genetics

1. Aleksandra M. Walczak
2. Michael Lässig
3. Ville Mustonen

In Molecular Biology

1. Ville Mustonen
2. Aleksandra M. Walczak
3. Michael Lässig

Citations in the corpus

• Predicting evolution (2017, methodology): “Alternatively, we can infer selection on genetic clades and build predictive models from the local shape of sequence-based coalescent trees 15 .”