PHYLDOG in practice
Bastien Boussau
boussau@gmail.com
@Bastounette
Getting the program
• From internet:
• http://pbil.univ-lyon1.fr/software/phyldog/#try
!
• Using the USB keys in the room:...
• LBBE collaborators (Lyon):
– Gergely Szöllősi (Budapest),
– Eric Tannier,
– Vincent Daubin,
– Manolo Gouy,
– Sophie Abby...
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
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
Specie...
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
Specie...
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
Specie...
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
Specie...
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
Specie...
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
Specie...
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
Specie...
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
Specie...
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
Specie...
What is PHYLDOG?
• Program for the coestimation of species and gene trees at the
genome scale
• Probabilistic model of seq...
Parallel architecture
Although it may not look like it, PHYLDOG infers rooted trees
Structure of the input data
Option files
family_X.option: options specific to gene family X (alignment
file, substitution model options, gene tree sea...
Option files
family_X.option: options specific to gene family X (alignment
file, substitution model options, gene tree sea...
PHYLDOG tutorial
http://www.prabi.fr/redmine/projects/phyldogtoolt/wiki/Tutorial
• Installing PHYLDOG
• Downloading files
...
Why our current pipeline can be improved
•Gene alignments:
•Error prone
•Short
•Point estimates
Why our current pipeline can be improved
•Gene alignments:
•Error prone
•Short
•Point estimates
•Gene trees:
•based on alignments
•Point estimates
Why our current ...
•Gene alignments:
•Error prone
•Short
•Point estimates
•Gene trees:
•based on alignments
•Point estimates
•Species trees:
...
•Gene alignments:
•Error prone
•Short
•Point estimates
•Gene trees:
•based on alignments
•Point estimates
•Species trees:
...
Simulations to test PHYLDOG
rooted
organism tree
• 40 species
D1
D2
D3
D4
D5
D6
L2
L1
L4
L3
L5
L6
rooted
organism tree
numbers of
duplications
and losses
• 40 species
• Randomly pick d...
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...
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...
D1
D2
D3
D4
D5
D6
L2
L1
L4
L3
L5
L6
PHYLDOG
rooted
organism tree
numbers of
duplications
and losses
rooted
gene trees
? ? ...
D1
D2
D3
D4
D5
D6
L2
L1
L4
L3
L5
L6
PHYLDOG
rooted
organism tree
numbers of
duplications
and losses
rooted
gene trees
? ? ...
Wrong model
PhyML
Wrong model
PHYLDOG
05101520
Treeerror
Simulations:PHYLDOG builds accurate gene trees
Wrong model
PhyML
Correct model
PhyML
Wrong model
PHYLDOG
05101520
Treeerror
Simulations:PHYLDOG builds accurate gene trees
Simulations: PHYLDOG accurately recovers numbers of
duplications and losses
Simulations: PHYLDOG accurately recovers numbers of
duplications and losses
●
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●
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●...
Study of mammalian genomes
• Challenging but well-studied phylogeny
• 36 mammalian genomes available in Ensembl v. 57
• Ab...
PHYLDOG
finds a good
species tree
Sus scrofa
Felis catus
Ornithorhynchus anatinus
Oryctolagus cuniculus
Loxodonta africana...
PHYLDOG
finds a good
species tree
Sus scrofa
Felis catus
Ornithorhynchus anatinus
Oryctolagus cuniculus
Loxodonta africana...
Sorex_araneus
Callithrix_jacchus
Dasypus_novemcinctus
Pongo_pygmaeus
Canis_familiaris
Vicugna_pacos
Otolemur_garnettii
Myo...
Sorex_araneus
Callithrix_jacchus
Dasypus_novemcinctus
Pongo_pygmaeus
Canis_familiaris
Vicugna_pacos
Otolemur_garnettii
Myo...
Bos_taurus
Monodelphis_domestica
Dipodomys_ordii
Myotis_lucifugus
Equus_caballus
Gorilla_gorilla
Mus_musculus
Choloepus_ho...
Bos_taurus
Monodelphis_domestica
Dipodomys_ordii
Myotis_lucifugus
Equus_caballus
Gorilla_gorilla
Mus_musculus
Choloepus_ho...
• Two approaches:
1. Looking at ancestral genome sizes
2. Assessing how well one can recover ancestral syntenies using
rec...
• Two approaches:
1. Looking at ancestral genome sizes
2. Assessing how well one can recover ancestral syntenies using
rec...
1) Junk trees generate obesity
• Errors in gene tree reconstruction result in larger
ancestral genomes
– Better algorithms...
1) PHYLDOG fights genome obesity
●
●
●
●
●
●
●
●
Extant genomes PhyML Ensembl−Compara PHYLDOG
50001000015000
NumberofGenes...
Sus scrofa
Felis catus
Ornithorhynchus anatinus
Oryctolagus cuniculus
Loxodonta africana
Mus musculus
Gorilla gorilla
Dipo...
2) Junk trees break synteny groups
• We use Deco (Bérard et al. Bioinformatics 2013) to
reconstruct ancestral synteny grou...
0.00.10.20.30.40.5
Proportionofancestralgenes
PHYLDOG
TreeBeST
PhyML
2) Ancestral synteny says 

PHYLDOG gene trees are be...
0.1
Ornithorhynchus anatinus
0.3
Ornithorhynchus anatinus
Mus musculus
Mus musculus
Mus musculus
Cavia porcellus
Mus muscu...
Perspectives
!
• Improvement of the algorithms to reconstruct gene
trees (e.g. Magali Semeria)
• Improvement of the algori...
Perspectives
!
• Improvement of the algorithms to reconstruct gene
trees (e.g. Magali Semeria)
• Improvement of the algori...
The Ancestrome project
• Reconstructing a species tree and gene trees for a large
number of species
• Reconstructing ances...
Postdocs wanted!
• LBBE collaborators (Lyon):
– Gergely Szöllősi (Budapest),
– Eric Tannier,
– Vincent Daubin,
– Manolo Gouy,
– Sophie Abby...
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How to use PHYLDOG: a tutorial

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Presentation of PHYLDOG, a piece of software for reconstructing gene and species phylogenies, with a focus on the practical side of things and pointers to a tutorial.

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How to use PHYLDOG: a tutorial

  1. 1. PHYLDOG in practice Bastien Boussau boussau@gmail.com @Bastounette
  2. 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. 3. • LBBE collaborators (Lyon): – Gergely Szöllősi (Budapest), – Eric Tannier, – Vincent Daubin, – Manolo Gouy, – Sophie Abby, – Laurent Duret, – Thomas Bigot, – Magali Semeria Collaborators
  4. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 15. Parallel architecture Although it may not look like it, PHYLDOG infers rooted trees
  16. 16. Structure of the input data
  17. 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. 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. 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. 20. Why our current pipeline can be improved
  21. 21. •Gene alignments: •Error prone •Short •Point estimates Why our current pipeline can be improved
  22. 22. •Gene alignments: •Error prone •Short •Point estimates •Gene trees: •based on alignments •Point estimates Why our current pipeline can be improved
  23. 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. 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. 25. Simulations to test PHYLDOG rooted organism tree • 40 species
  26. 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. 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. 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. 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. 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. 31. Wrong model PhyML Wrong model PHYLDOG 05101520 Treeerror Simulations:PHYLDOG builds accurate gene trees
  32. 32. Wrong model PhyML Correct model PhyML Wrong model PHYLDOG 05101520 Treeerror Simulations:PHYLDOG builds accurate gene trees
  33. 33. Simulations: PHYLDOG accurately recovers numbers of duplications and losses
  34. 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. 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. 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. 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
  38. 38. Sorex_araneus Callithrix_jacchus Dasypus_novemcinctus Pongo_pygmaeus Canis_familiaris Vicugna_pacos Otolemur_garnettii Myotis_lucifugus Microcebus_murinus Sus_scrofa Ornithorhynchus_anatinus Dipodomys_ordii Gorilla_gorilla Tupaia_belangeri Ochotona_princeps Cavia_porcellus Mus_musculus Erinaceus_europaeus Pteropus_vampyrus Felis_catus Homo_sapiens Loxodonta_africana Monodelphis_domestica Tursiops_truncatus Echinops_telfairi Macaca_mulatta Pan_troglodytes Rattus_norvegicus Choloepus_hoffmanni Oryctolagus_cuniculus Equus_caballus Bos_taurus Procavia_capensis Macropus_eugenii Spermophilus_tridecemlineatus Tarsius_syrichta Marsupials Afrotheria Xenarthra Laurasiatheria Primates Glires Duptree finds a pretty good species tree
  39. 39. Sorex_araneus Callithrix_jacchus Dasypus_novemcinctus Pongo_pygmaeus Canis_familiaris Vicugna_pacos Otolemur_garnettii Myotis_lucifugus Microcebus_murinus Sus_scrofa Ornithorhynchus_anatinus Dipodomys_ordii Gorilla_gorilla Tupaia_belangeri Ochotona_princeps Cavia_porcellus Mus_musculus Erinaceus_europaeus Pteropus_vampyrus Felis_catus Homo_sapiens Loxodonta_africana Monodelphis_domestica Tursiops_truncatus Echinops_telfairi Macaca_mulatta Pan_troglodytes Rattus_norvegicus Choloepus_hoffmanni Oryctolagus_cuniculus Equus_caballus Bos_taurus Procavia_capensis Macropus_eugenii Spermophilus_tridecemlineatus Tarsius_syrichta Marsupials Afrotheria Xenarthra Laurasiatheria Primates Glires Duptree finds a pretty good species tree
  40. 40. Bos_taurus Monodelphis_domestica Dipodomys_ordii Myotis_lucifugus Equus_caballus Gorilla_gorilla Mus_musculus Choloepus_hoffmanni Echinops_telfairi Procavia_capensis Vicugna_pacos Tursiops_truncatus Spermophilus_tridecemlineatus Callithrix_jacchus Ornithorhynchus_anatinus Canis_familiaris Sus_scrofa Cavia_porcellus Rattus_norvegicus Pan_troglodytes Erinaceus_europaeus Microcebus_murinus Felis_catus Pteropus_vampyrus Loxodonta_africana Ochotona_princeps Sorex_araneus Dasypus_novemcinctus Tupaia_belangeri Pongo_pygmaeus Otolemur_garnettii Homo_sapiens Macropus_eugenii Macaca_mulatta Oryctolagus_cuniculus Tarsius_syrichta Marsupials Afrotheria Xenarthra Laurasiatheria Primates Glires iGTP finds a different species tree
  41. 41. Bos_taurus Monodelphis_domestica Dipodomys_ordii Myotis_lucifugus Equus_caballus Gorilla_gorilla Mus_musculus Choloepus_hoffmanni Echinops_telfairi Procavia_capensis Vicugna_pacos Tursiops_truncatus Spermophilus_tridecemlineatus Callithrix_jacchus Ornithorhynchus_anatinus Canis_familiaris Sus_scrofa Cavia_porcellus Rattus_norvegicus Pan_troglodytes Erinaceus_europaeus Microcebus_murinus Felis_catus Pteropus_vampyrus Loxodonta_africana Ochotona_princeps Sorex_araneus Dasypus_novemcinctus Tupaia_belangeri Pongo_pygmaeus Otolemur_garnettii Homo_sapiens Macropus_eugenii Macaca_mulatta Oryctolagus_cuniculus Tarsius_syrichta Marsupials Afrotheria Xenarthra Laurasiatheria Primates Glires iGTP finds a different species tree
  42. 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. 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. 44. 1) Junk trees generate obesity • Errors in gene tree reconstruction result in larger ancestral genomes – Better algorithms should yield smaller ancestral genomes
  45. 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. 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. 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. 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. 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. 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. 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. 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. 53. Postdocs wanted!
  54. 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!

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