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Evolutionary genomics
- 1. LBBE, CNRS, Universitéde Lyon Evolutionary genomics Bastien Boussau boussau@gmail.com @bastounette
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- 3. Chance and necessity …… Evolution …ATCGACATCAGCATCAGCACTAC…
- 4. Chance and necessity …… Evolution Function …ATCGACATCAGCATCAGCACTAC…
- 5. 3 Evolution in ourgenomes 3 Brown, Sanger, Kitai. Biochem. J. 1955.
- 6. 3 Evolution in ourgenomes 3 Brown, Sanger, Kitai. Biochem. J. 1955.
- 7. 3 Evolution in ourgenomes 3 Brown, Sanger, Kitai. Biochem. J. 1955.
- 8. Genomes as Documentsof Evolutionary History 4
- 9. What information canwe extract from genome sequences? 5 1. Species phylogeny! 2. Phylogeography! 3. Diversification history! 4. Ancestral lifestyles! 5. Selective pressures in extant species! 6. Application to cell lineages
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- 11. Genome evolution 6 Genome sequence pointmutations Processes …ACTCGTTCGCATCGACTCCTCCAGC…
- 12. Genome evolution 7 Genome sequence pointmutations Processes …ACTCGATCGCATCGACTCCTCCAGC…
- 13. Genome evolution 7 Genome sequence pointmutations insertions/deletions Processes …ACTCGATCGCATCGAAAACTCCTCCAGC…
- 14. Genome evolution 8 Genome sequence pointmutations insertions/deletions Processes …ACTCGATCGCATCGACTCCTCCAGC…
- 15. Genome evolution 8 Genome sequence pointmutations insertions/deletions duplications/losses Processes …ACTCGATCGCATCGACTCCTTCCTCCAGC…
- 16. Genome evolution 9 Genome sequence pointmutations insertions/deletions duplications/losses Processes …ACTCGATCGCATCGACTCCTCCAGC…
- 17. Genome evolution 9 Genome sequence pointmutations insertions/deletions duplications/losses rearrangements Processes …ACTCGATCGCAAGCTCTCCTCCAGC…
- 18. Genome evolution 10 Genome sequence pointmutations insertions/deletions duplications/losses rearrangements Processes population genetics molecular machinery species phylogeny environment …ACTCGATCGCATCGACTCCTCCAGC…
- 19. Using genomes for statistical inference 11 Genome sequence point mutations insertions/deletions duplications/losses rearrangements Processes population genetics molecular machinery species phylogeny environment …ACTCGATCGCATCGACTCCTCCAGC…
- 20. Inferential statistics 12 Boussau andDaubin, Tree 2010
- 21. Inferential statistics 12 Boussau andDaubin, Tree 2010 • Using computers! • Probabilistic models (e.g. models of sequence evolution)! • “What I cannot create, I do not understand.” (Feynman, 1988)! • What I cannot simulate, I do not understand.”
- 22. What information canwe extract from genome sequences? 13 1. Species phylogeny! 2. Phylogeography! 3. Diversification history! 4. Ancestral lifestyles! 5. Selective pressures in extant species! 6. Application to cell lineages
- 23. 1 Inferring thephylogeny Models:! • Modelling events of substitution! • In some cases, modelling insertions and deletions! • In some cases, modelling allele sorting! • In some cases, modelling gene duplications, losses and transfers! • In some cases, modelling hybridization! • Dates of speciation can also be inferred with a model of rate evolution
- 24. 1 The phylogenyof life Williams et al., Nature 2013
- 25. 1 The phylogenyof life Williams et al., Nature 2013 Improvements in:! • probabilistic models! • data available
- 26. 1 The originof viral strains Boussau, Guéguen, Gouy, Evolutionary Bioinformatics 2009. 1353 first sites ~1200 remaining sites
- 27. 1 The originof viral strains Boussau, Guéguen, Gouy, Evolutionary Bioinformatics 2009. The N HIV strain originated through a recombination between a Human and a Chimp virus 1353 first sites ~1200 remaining sites
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- 30. 1 Forensic analyses Scadutoet al., PNAS 2010 The problem:! • CC01 is a HIV-positive male, accused by several partners of hiding his seropositivity and infecting them in the process ==> trial! • 1 accused male, 6 partners, all seropositive! • HIV sequences available from each of them! • How can we tell whether CC01 likely contaminated his partners?
- 31. 1 Forensic analyses Scadutoet al., PNAS 2010 The problem:! • CC01 is a HIV-positive male, accused by several partners of hiding his seropositivity and infecting them in the process ==> trial! • 1 accused male, 6 partners, all seropositive! • HIV sequences available from each of them! • How can we tell whether CC01 likely contaminated his partners? Use the HIV sequences to build a phylogenetic tree!
- 32. 1 Forensic analyses Scadutoet al., PNAS 2010
- 33. 1 Forensic analyses Scadutoet al., PNAS 2010 Evidence used to establish that CC01 had infected his partners
- 34. 1 Inferring thephylogeny Purposes:! • Inferring the species phylogeny! • Reconstructing the evolutionary history of infectious agents! • Reconstructing transmission histories (e.g. forensic analyses)!
- 35. 2 Phylogeography Question:! • Howdid these organisms get to be where they are?!
- 36. 2 Phylogeography Question:! • Howdid these organisms get to be where they are?! Mus musculus, GBIF database
- 37. 2 Phylogeography Faria etal., Science 2014 Models:! • Add spatial information at the leaves! • Use Discrete models or continuous models to reconstruct ancestral ranges!
- 38. 2 Phylogeography Landis etal., Syst. Biol. 2014
- 39. Landis et al.,Syst. Biol. 2014 2 Phylogeography
- 40. 2 HIV phylogeography Fariaet al., Science 2014
- 41. 2 Phylogeography Purposes:! • Inferringthe species geographical range through time! • Reconstructing the evolutionary spread of infectious agents! • Investigating plate tectonics!
- 42. 3 Diversification history Howdid species diversify? Were there bursts of speciation, or mass extinctions? ! How many species/individuals through time?! Models:! • Modelling events of speciation, and events of extinction! • In some cases, can be dependent on other parameters
- 43. 28 3 Species ofbirds through time Jetz et al., Nature 2012
- 44. 29 3 Speciations ofbirds across the globe Jetz et al., Nature 2012
- 45. 30 3 Phylodynamics ofHCV in Egypt Drummond et al., MBE 2005
- 46. 30 3 Phylodynamics ofHCV in Egypt Drummond et al., MBE 2005 Huge increase in number of viruses coincides with the extensive use of an antischistosomiasis treatment from 1920 to 1980
- 47. 3 Diversification history Purposes:! •Inferring the number of species/individuals through time! • Finding major radiation/extinction events! • Reconstructing past epidemics!
- 48. 4 Ancestral lifestyles Howdid ancestral species live? What temperature did they like most? How long did they live?! Models:! • Correlating molecular evolution with phenotypic traits!
- 49. 4 Inferring growthtemperature across the tree of life
- 50. 4 Inferring growthtemperature across the tree of life Idea: reconstruct ancestral sequences in silico, and predict ancestral growth temperatures
- 51. 4 Inferring growthtemperature across the tree of life Usual model: ! all branches evolve according to the same model Better model: ! different models for different branches
- 52. Boussau et al.,Nature 2008 4 Inferring growth temperature across the tree of life
- 53. Boussau et al.,Nature 2008 4 Inferring growth temperature across the tree of life
- 54. Boussau et al.,Nature 2008 4 Inferring growth temperature across the tree of life Late Heavy Bombardment 3.8 Bya?
- 55. Lartillot and Delsuc,Evolution 2012 4 Joint inference of rates, dates, and traits
- 56. 4 Ancestral lifestyles Purposes:! •Inferring characteristics of ancient organisms! • Inferring characteristics of ancient environments! • Finding/using correlations between phenotype evolution and genotype evolution
- 57. 5 Selective pressuresin extant species What sites in the genome of species X are important?! Models:! • Usual models of sequence evolution! • Models of insertion-deletion! • Hidden Markov Models that run along the genome!
- 58. 40 5 Conservation acrossspecies indicates function 40 Brown, Sanger, Kitai. Biochem. J. 1955.
- 59. 41 5 Conservation acrossspecies indicates function 41 The UCSC genome browser uses conservation across 100 vertebrates to detect functional regions
- 60. Gnad et al.,BMC Genomics 2013 5 How to best predict cancer- causing mutations? Comparison across 12 methods:
- 61. 5 How tobest predict cancer- causing mutations? Gnad et al., BMC Genomics 2013
- 62. 5 Selective pressuresin extant species Purposes:! • Screening a genome for new functional elements! • Evaluating the severity of candidate mutations (e.g. genetic disease, cancer)! • Finding sites to target in a pest that needs controlling
- 63. 6 Application tocell lineages As cells divide by mitosis, mutations accumulate. ! —> phylogenetic approaches can be used to address developmental questions:! • How similar is development across individuals?! • Do the first cells produced during development contribute equally to the adult organism?! • …! Models:! • Usual models of sequence evolution! • Models of microsatellite evolution
- 64. 6 Application tocell lineages Behjati et al., Nature 2014
- 65. 6 Application tocell lineages Behjati et al., Nature 2014 Contributions of early embryonic cells to adult tail cell populations
- 66. 6 Application tocell lineages
- 67. 6 Application tocell lineages Purposes:! • Learning about development! • Learning about cancer evolution (e.g. using phylogeography to understand cancer spread)
- 68. Conclusions • Genomes containa lot of information about their history and about how they work! • The comparative approach is a powerful way to learn about the function of a stretch of sequence! • Thanks to probabilistic models, one can exploit the huge amount of information in genomes to ask a large number of interesting questions Slides available on SlideShare: http://www.slideshare.net/boussau