How to use PHYLDOG: a tutorial

PHYLDOG in practiceBastien Boussau

[email protected] @Bastounette

mailto:[email protected]

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

• LBBE collaborators (Lyon):

– Gergely Szöllősi (Budapest),

– Eric Tannier,

– Vincent Daubin,

–Manolo Gouy,

– Sophie Abby,

– Laurent Duret,

– Thomas Bigot, –Magali Semeria

Collaborators

Species: A B C D

TIME

Species: A B C D

Discrete character:Continuous character:

a a b a0.1 0.2 0.2 0.4

TIME

Species: A B C D

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

Species: A B C D

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

D

Species: A B C D

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

D DL

Species: A B C D

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

LGTD DL

Species: A B C D

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

LGT ILSD DL

Species: A B C D

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

LGT ILS

PHYLDOG

D DL

Species: A B C D

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

LGT ILS

DL+LGT: Szollosi et al., PNAS

PHYLDOG

D DL

Species: A B C D

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

Species: A B C D


a a b a0.1 0.2 0.2 0.4

TIME

LGT ILS

DL+LGT: Szollosi et al., PNAS

ILS: Not yet

PHYLDOG

D DL

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.

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 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)

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

PHYLDOG tutorialhttp://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

http://www.prabi.fr/redmine/projects/phyldogtoolt/wiki/Tutorial

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Why our current pipeline can be improved

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•Gene alignments: •Error prone •Short •Point estimates


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•Gene trees: •based on alignments •Point estimates


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•Gene trees: •based on alignments •Point estimates

•Species trees: •based on gene trees


Simulations to test PHYLDOG

rooted organism tree

• 40 species

D1D2

D3D4

D5

D6

L2L1

L4L3

L5

L6


numbers of duplications

and losses

• 40 species • Randomly pick duplication and loss rates per branch


D1D2

D3D4

D5

D6

L2L1

L4L3

L5

L6



and losses

rooted gene trees

• 40 species • Randomly pick duplication and loss rates per branch


D1D2

D3D4

D5

D6

L2L1

L4L3

L5

L6



and losses

rooted gene trees

• 40 species • Randomly pick duplication and loss rates per branch • Complex model of sequence evolution


D1D2

D3D4

D5

D6

L2L1

L4L3

L5

L6

PHYLDOG



and losses

rooted gene trees

? ? ?



D1D2

D3D4

D5

D6

L2L1

L4L3

L5

L6

PHYLDOG



and losses

rooted gene trees

? ? ?


!


Wrong modelPhyML

Wrong modelPHYLDOG

05

1015

20Tr

ee e

rror

Simulations:PHYLDOG builds accurate gene trees

Wrong modelPhyML

Correct modelPhyML

Wrong modelPHYLDOG

05

1015

20Tr

ee e

rror

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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1e−04 1e−03 1e−02 1e−01 1e+00

1e−0

41e−0

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Expected Numbers

Rec

onst

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DuplicationsLosses

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

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 novemcinctusEchinops telfairi

Pteropus vampyrus

Macropus eugenii

Canis familiaris

Sorex araneus

Myotis lucifugus

Laurasiatheria

Afrotheria

Xenarthra

Marsupials

Primates

Glires

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_princepsCavia_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

Bos_taurus

Monodelphis_domestica

Dipodomys_ordii

Myotis_lucifugus

Equus_caballus

Gorilla_gorilla

Mus_musculus

Choloepus_hoffmanni

Echinops_telfairiProcavia_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

• 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

• 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

1) Junk trees generate obesity

• Errors in gene tree reconstruction result in larger ancestral genomes – Better algorithms should yield smaller ancestral genomes

1) PHYLDOG fights genome obesity

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Extant genomes PhyML Ensembl−Compara PHYLDOG

5000

1000

015

000

Num

ber o

f Gen

es

**

TreeBeST

**: Student t-test p-value: 6.61e-06, Wilcoxon test p-value: 2.91e-11

Sus scrofa

Felis catus



Loxodonta africana

Mus musculus

Gorilla gorilla

Dipodomys ordii


Vicugna pacos

Macaca mulatta

Tupaia belangeri

Procavia capensis


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 novemcinctusEchinops telfairi

Pteropus vampyrus

Macropus eugenii

Canis familiaris

Sorex araneus

Myotis lucifugus

Laurasiatheria

Afrotheria

Xenarthra

Marsupials

Primates

Glires

010

000

010

000

010

000

010

000

010

000

010

000

010

000PHYLDOG

TreeBeSTPhyML

1) PHYLDOG fights genome obesity

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

0 1 2 3 4 5 6 7

0.0

0.1

0.2

0.3

0.4

0.5

Number of adjacencies

Prop

ortio

n of

anc

estra

l gen

es PHYLDOGTreeBeSTPhyML

2) Ancestral synteny says PHYLDOG gene trees are better

0.0Pr

opor

tion

of a

nces

tral

gen

es

in s

ynte

ny g

roup

s

Bérard et al., Bioinformatics, 2013

0.1


0.3

Ornithorhynchus anatinusMus musculusMus musculusMus musculusCavia porcellusMus musculus

Oryctolagus cuniculusCanis familiaris

Bos taurusHomo sapiens

Pongo pygmaeusOryctolagus cuniculus

Cavia porcellusEquus caballusEquus caballus

Bos taurusCallithrix jacchusHomo sapiens

Monodelphis domesticaSpermophilus tridecemlineatus

Homo sapiensOrnithorhynchus anatinusOrnithorhynchus anatinusOrnithorhynchus anatinusOrnithorhynchus anatinus

Mus musculusMus musculus

Ornithorhynchus anatinusOrnithorhynchus anatinus

Mus musculusMus musculusMus musculus

Cavia porcellus

Mus musculus


Canis familiaris

Bos taurus

Homo sapiens

Pongo pygmaeus


Cavia porcellus

Equus caballusEquus caballus

Bos taurus

Callithrix jacchusHomo sapiens



Homo sapiens

Ornithorhynchus anatinusOrnithorhynchus anatinusOrnithorhynchus anatinusOrnithorhynchus anatinus

Mus musculusMus musculus

TreeBeST PHYLDOG

An example gene family

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

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

Postdocs wanted!

• LBBE collaborators (Lyon):

– Gergely Szöllősi (Budapest),

– Eric Tannier,

– Vincent Daubin,

–Manolo Gouy,

– Sophie Abby,

– Laurent Duret,

– Thomas Bigot, –Magali Semeria

Postdocs wanted!

Thank you!

How to use PHYLDOG: a tutorial

Science

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