Predicting evolution from the shape of genealogical trees
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 t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2014-11-01
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| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/03568 |
| _version_ | 1811236997649399808 |
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| author | Richard A Neher Colin A Russell Boris I Shraiman |
| author_facet | Richard A Neher Colin A Russell Boris I Shraiman |
| author_sort | Richard A Neher |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T12:18:25Z |
| format | Article |
| id | doaj.art-fa4a2ff954b144ccb898ac615fa78d46 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-12T12:18:25Z |
| publishDate | 2014-11-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-fa4a2ff954b144ccb898ac615fa78d462022-12-22T03:33:23ZengeLife Sciences Publications LtdeLife2050-084X2014-11-01310.7554/eLife.03568Predicting evolution from the shape of genealogical treesRichard A Neher0https://orcid.org/0000-0003-2525-1407Colin A Russell1Boris I Shraiman2Evolutionary Dynamics and Biophysics, Max Planck Institute for Developmental Biology, Tübingen, GermanyDepartment of Veterinary Medicine, University of Cambridge, Cambridge, United KingdomKavli Institute for Theoretical Physics, University of California, Santa Barbara, Santa Barbara, United StatesGiven 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.https://elifesciences.org/articles/03568vaccine strain selectionadaptive evolutionpopulation genetics |
| spellingShingle | Richard A Neher Colin A Russell Boris I Shraiman Predicting evolution from the shape of genealogical trees eLife vaccine strain selection adaptive evolution population genetics |
| title | Predicting evolution from the shape of genealogical trees |
| title_full | Predicting evolution from the shape of genealogical trees |
| title_fullStr | Predicting evolution from the shape of genealogical trees |
| title_full_unstemmed | Predicting evolution from the shape of genealogical trees |
| title_short | Predicting evolution from the shape of genealogical trees |
| title_sort | predicting evolution from the shape of genealogical trees |
| topic | vaccine strain selection adaptive evolution population genetics |
| url | https://elifesciences.org/articles/03568 |
| work_keys_str_mv | AT richardaneher predictingevolutionfromtheshapeofgenealogicaltrees AT colinarussell predictingevolutionfromtheshapeofgenealogicaltrees AT borisishraiman predictingevolutionfromtheshapeofgenealogicaltrees |