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How to use PHYLDOG: a tutorial
- 1. PHYLDOG in practice Bastien Boussau boussau@gmail.com @Bastounette
- 2. Getting the program • From internet: • http://pbil.univ-lyon1.fr/software/phyldog/#try ! • Using the USB keys in the room: • contain VirtualBox • contain the application along with the data to analyze
- 3. • LBBE collaborators (Lyon): – Gergely Szöllősi (Budapest), – Eric Tannier, – Vincent Daubin, – Manolo Gouy, – Sophie Abby, – Laurent Duret, – Thomas Bigot, – Magali Semeria Collaborators
- 4. Species: A B C D T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E
- 5. Species: A B C D T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E
- 6. Species: A B C D T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E
- 7. Species: A B C D T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E D
- 8. Species: A B C D T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E D DL
- 9. Species: A B C D T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E LGTD DL
- 10. Species: A B C D T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E LGT ILSD DL
- 11. Species: A B C D T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E LGT ILS PHYLDOG D DL
- 12. Species: A B C D T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E LGT ILS DL +LGT: Szollosi et al., PNAS PHYLDOG D DL
- 13. Species: A B C D T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E Species: A B C D Discrete character: Continuous character: a a b a 0.1 0.2 0.2 0.4 T I M E LGT ILS DL +LGT: Szollosi et al., PNAS ILS: Not yet PHYLDOG D DL
- 14. What is PHYLDOG? • Program for the coestimation of species and gene trees at the genome scale • Probabilistic model of sequence evolution + model of gene duplication and loss • Statistical framework • Branch-wise parameters of duplications and losses • Gene families evolve independently of each other • Based on a parallel architecture using MPI Genome-scale coestimation of species and gene trees. Boussau et al., Genome research. 2013 23:323:330.
- 15. Parallel architecture Although it may not look like it, PHYLDOG infers rooted trees
- 16. Structure of the input data
- 17. Option files family_X.option: options specific to gene family X (alignment file, substitution model options, gene tree search options) GeneralOptions.txt: options concerning the species tree search, and options common to all gene families (species tree search options, duplication/loss model options, list of gene families)
- 18. Option files family_X.option: options specific to gene family X (alignment file, substitution model options, gene tree search options) GeneralOptions.txt: options concerning the species tree search, and options common to all gene families (species tree search options, duplication/loss model options, list of gene families) Easy generation of basic option files using the prepareData.py script
- 19. PHYLDOG tutorial http://www.prabi.fr/redmine/projects/phyldogtoolt/wiki/Tutorial • Installing PHYLDOG • Downloading files • Basic input files • Generating all the option files using the prepareData.py script • Running PHYLDOG • Diminishing the number of species considered • Diminishing the number of gene families considered • Running PHYLDOG, at last • Interpreting PHYLDOG's output • Going further
- 20. Why our current pipeline can be improved
- 21. •Gene alignments: •Error prone •Short •Point estimates Why our current pipeline can be improved
- 22. •Gene alignments: •Error prone •Short •Point estimates •Gene trees: •based on alignments •Point estimates Why our current pipeline can be improved
- 23. •Gene alignments: •Error prone •Short •Point estimates •Gene trees: •based on alignments •Point estimates •Species trees: •based on gene trees Why our current pipeline can be improved
- 24. •Gene alignments: •Error prone •Short •Point estimates •Gene trees: •based on alignments •Point estimates •Species trees: •based on gene trees Why our current pipeline can be improved
- 25. Simulations to test PHYLDOG rooted organism tree • 40 species
- 26. D1 D2 D3 D4 D5 D6 L2 L1 L4 L3 L5 L6 rooted organism tree numbers of duplications and losses • 40 species • Randomly pick duplication and loss rates per branch Simulations to test PHYLDOG
- 27. D1 D2 D3 D4 D5 D6 L2 L1 L4 L3 L5 L6 rooted organism tree numbers of duplications and losses rooted gene trees • 40 species • Randomly pick duplication and loss rates per branch Simulations to test PHYLDOG
- 28. D1 D2 D3 D4 D5 D6 L2 L1 L4 L3 L5 L6 rooted organism tree numbers of duplications and losses rooted gene trees • 40 species • Randomly pick duplication and loss rates per branch • Complex model of sequence evolution Simulations to test PHYLDOG
- 29. D1 D2 D3 D4 D5 D6 L2 L1 L4 L3 L5 L6 PHYLDOG rooted organism tree numbers of duplications and losses rooted gene trees ? ? ? • 40 species • Randomly pick duplication and loss rates per branch • Complex model of sequence evolution Simulations to test PHYLDOG
- 30. D1 D2 D3 D4 D5 D6 L2 L1 L4 L3 L5 L6 PHYLDOG rooted organism tree numbers of duplications and losses rooted gene trees ? ? ? • 40 species • Randomly pick duplication and loss rates per branch • Complex model of sequence evolution ! Simulations to test PHYLDOG
- 31. Wrong model PhyML Wrong model PHYLDOG 05101520 Treeerror Simulations:PHYLDOG builds accurate gene trees
- 32. Wrong model PhyML Correct model PhyML Wrong model PHYLDOG 05101520 Treeerror Simulations:PHYLDOG builds accurate gene trees
- 33. Simulations: PHYLDOG accurately recovers numbers of duplications and losses
- 34. Simulations: PHYLDOG accurately recovers numbers of duplications and losses ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 1e−04 1e−03 1e−02 1e−01 1e+00 1e−041e−031e−021e−011e+00 Expected Numbers ReconstructedNumbers ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Duplications Losses
- 35. Study of mammalian genomes • Challenging but well-studied phylogeny • 36 mammalian genomes available in Ensembl v. 57 • About 7000 gene families • Correction for incomplete genomes
- 36. PHYLDOG finds a good species tree Sus scrofa Felis catus Ornithorhynchus anatinus Oryctolagus cuniculus Loxodonta africana Mus musculus Gorilla gorilla Dipodomys ordii Monodelphis domestica Vicugna pacos Macaca mulatta Tupaia belangeri Procavia capensis Spermophilus tridecemlineatus Pongo pygmaeus Tursiops truncatus Microcebus murinus Callithrix jacchus Equus caballus Erinaceus europaeus Tarsius syrichta Choloepus hoffmanni Ochotona princeps Cavia porcellus Pan troglodytes Bos taurus Rattus norvegicus Homo sapiens Otolemur garnettii Dasypus novemcinctus Echinops telfairi Pteropus vampyrus Macropus eugenii Canis familiaris Sorex araneus Myotis lucifugus Laurasiatheria Afrotheria Xenarthra Marsupials Primates Glires
- 37. PHYLDOG finds a good species tree Sus scrofa Felis catus Ornithorhynchus anatinus Oryctolagus cuniculus Loxodonta africana Mus musculus Gorilla gorilla Dipodomys ordii Monodelphis domestica Vicugna pacos Macaca mulatta Tupaia belangeri Procavia capensis Spermophilus tridecemlineatus Pongo pygmaeus Tursiops truncatus Microcebus murinus Callithrix jacchus Equus caballus Erinaceus europaeus Tarsius syrichta Choloepus hoffmanni Ochotona princeps Cavia porcellus Pan troglodytes Bos taurus Rattus norvegicus Homo sapiens Otolemur garnettii Dasypus novemcinctus Echinops telfairi Pteropus vampyrus Macropus eugenii Canis familiaris Sorex araneus Myotis lucifugus Laurasiatheria Afrotheria Xenarthra Marsupials Primates Glires
- 42. • Two approaches: 1. Looking at ancestral genome sizes 2. Assessing how well one can recover ancestral syntenies using reconstructed gene trees (Bérard et al., Bioinformatics) Assessing the quality of gene trees
- 43. • Two approaches: 1. Looking at ancestral genome sizes 2. Assessing how well one can recover ancestral syntenies using reconstructed gene trees (Bérard et al., Bioinformatics) • Comparison between: – PhyML (PhylomeDB and Homolens databases ) – TreeBeST (Ensembl-Compara database) – PHYLDOG Assessing the quality of gene trees
- 44. 1) Junk trees generate obesity • Errors in gene tree reconstruction result in larger ancestral genomes – Better algorithms should yield smaller ancestral genomes
- 45. 1) PHYLDOG fights genome obesity ● ● ● ● ● ● ● ● Extant genomes PhyML Ensembl−Compara PHYLDOG 50001000015000 NumberofGenes ** TreeBeST **: Student t-test p-value: 6.61e-06, Wilcoxon test p-value: 2.91e-11
- 46. Sus scrofa Felis catus Ornithorhynchus anatinus Oryctolagus cuniculus Loxodonta africana Mus musculus Gorilla gorilla Dipodomys ordii Monodelphis domestica Vicugna pacos Macaca mulatta Tupaia belangeri Procavia capensis Spermophilus tridecemlineatus Pongo pygmaeus Tursiops truncatus Microcebus murinus Callithrix jacchus Equus caballus Erinaceus europaeus Tarsius syrichta Choloepus hoffmanni Ochotona princeps Cavia porcellus Pan troglodytes Bos taurus Rattus norvegicus Homo sapiens Otolemur garnettii Dasypus novemcinctus Echinops telfairi Pteropus vampyrus Macropus eugenii Canis familiaris Sorex araneus Myotis lucifugus Laurasiatheria Afrotheria Xenarthra Marsupials Primates Glires 010000 010000 010000 010000 010000 010000 010000 PHYLDOG TreeBeST PhyML 1) PHYLDOG fights genome obesity
- 47. 2) Junk trees break synteny groups • We use Deco (Bérard et al. Bioinformatics 2013) to reconstruct ancestral synteny groups using gene trees • Errors in gene tree reconstruction break synteny groups – Better algorithms should yield more genes in ancestral synteny groups
- 48. 0.00.10.20.30.40.5 Proportionofancestralgenes PHYLDOG TreeBeST PhyML 2) Ancestral synteny says PHYLDOG gene trees are better 0.0 Proportionofancestralgenes insyntenygroups Bérard et al., Bioinformatics, 2013
- 49. 0.1 Ornithorhynchus anatinus 0.3 Ornithorhynchus anatinus Mus musculus Mus musculus Mus musculus Cavia porcellus Mus musculus Oryctolagus cuniculus Canis familiaris Bos taurus Homo sapiens Pongo pygmaeus Oryctolagus cuniculus Cavia porcellus Equus caballus Equus caballus Bos taurus Callithrix jacchus Homo sapiens Monodelphis domestica Spermophilus tridecemlineatus Homo sapiens Ornithorhynchus anatinus Ornithorhynchus anatinus Ornithorhynchus anatinus Ornithorhynchus anatinus Mus musculus Mus musculus Ornithorhynchus anatinus Ornithorhynchus anatinus Mus musculus Mus musculus Mus musculus Cavia porcellus Mus musculus Oryctolagus cuniculus Canis familiaris Bos taurus Homo sapiens Pongo pygmaeus Oryctolagus cuniculus Cavia porcellus Equus caballus Equus caballus Bos taurus Callithrix jacchus Homo sapiens Monodelphis domestica Spermophilus tridecemlineatus Homo sapiens Ornithorhynchus anatinus Ornithorhynchus anatinus Ornithorhynchus anatinus Ornithorhynchus anatinus Mus musculus Mus musculus TreeBeST PHYLDOG An example gene family
- 50. Perspectives ! • Improvement of the algorithms to reconstruct gene trees (e.g. Magali Semeria) • Improvement of the algorithms to reconstruct the species tree • Dealing with ILS • Joint reconstruction of gene trees and gene alignments
- 51. Perspectives ! • Improvement of the algorithms to reconstruct gene trees (e.g. Magali Semeria) • Improvement of the algorithms to reconstruct the species tree • Dealing with ILS • Joint reconstruction of gene trees and gene alignments
- 52. The Ancestrome project • Reconstructing a species tree and gene trees for a large number of species • Reconstructing ancestral gene contents • Inferring ancient metabolisms and lifestyles • Inferring ancient communities New insights into the evolution of life on Earth, and into genomic evolution
- 53. Postdocs wanted!
- 54. • LBBE collaborators (Lyon): – Gergely Szöllősi (Budapest), – Eric Tannier, – Vincent Daubin, – Manolo Gouy, – Sophie Abby, – Laurent Duret, – Thomas Bigot, – Magali Semeria Postdocs wanted! Thank you!