Detecting horizontal gene transfers using discrepancies in species and gene classifications Alix Boc Université du Québec à Montréal

Detecting horizontal gene transfers using discrepancies in species and

gene classifications

Alix Boc

Université du Québec à Montréal

Rhodobacter

Hydrogenovibrio L2

Chromatium L

Thiobacillus fe1

Nitrobacter

Xanthobacter

Rhodobacter

Xanthobacter

Nitrobacter

Chromatium L

Thiobacillus fe1

Hydrogenovibrio L2

Problem description

Species tree Gene Tree (rbcL)

Presentation summary

• Some words about phylogeny

• Network models in phylogenetic analysis

• What is a horizontal gene transfer (HGT)?

• Description of the new method

• Examples of application

• HGT-Detection vs LatTrans

• Future works

• T-Rex software

Recontruction of a phylogenetic tree

A: CGTAATB: CGTACGC: CGTCGAD: ACT………E: ………………F: ………………

A B C D E F

A 0 2 3 5 5 4

B 2 0 3 5 5 4

C 3 3 0 4 4 3

D 5 5 4 0 2 3

E 5 5 4 2 0 3

F 4 4 3 3 3 0

A

F

E

D

C

B

DNA Sequences Distance Matrix Phylogenetic Tree


AAATGATCTGCGTCAATATTATAA

GCCTGATCCTCACTACTGTCATCTTAA

ATAGGGCCCGTATTTACCCTATAG

AACTGGTCCACCCTTATACTAAAAGACGCCTCACTAGGAAGCTAA

AACTGATCTGCTTCAATAATTTAA

1 . Align sequences

AAATGATCTGCGTCAATATTA---------------------TAA

GCCTGATCCTCACTA------------------CTGTCATCTTAA

ATA---------------------GGGCCCGTATTTACCCTATAG

AACTGGTCCACCCTTATACTAAAAGACGCCTCACTAGGAAGCTAA

AACTGATCTGCTTCAATAATT---------------------TAA

• Clustal (Higgins, 1994)• Dialign (Morgenstern, 1999)• ….

2 . Apply a model of evolution (distances methods)


0 3 2 4 3

3 0 3 4 2

2 3 0 4 3

4 4 4 0 4

3 2 3 4 0

• Uncorrected Distances• Jukes Cantor• Tajima Nei• Kimura 2 parameters• Tamura• Jin-Nei Gamma• Kimura protein• LogDet• F84• ….

3 . Apply a reconstruction method (distances methods)


• Neighbor Joining• ADDTREE• Unweighted Neighbor Joining• Circular order reconstruction• Weighted Least-squares• BioNJ• ….

Inferring phylogenetic trees

Four main approaches:

• Distance-based methods • UPGMA by Michener and Sokal (1957)

• ADDTREE by Sattath et Tversky (1977)

• Neighbor-joining (NJ) by Saitou and Nei (1988)

• UNJ and BioNJ methods by Gascuel (1997)

• Fitch by Felsenstein (1997)

• Weighted least-squares MW by Makarenkov and Leclerc (1999)

• Maximum Parsimony (Camin and Sokal 1965; Farris 1970; Fitch 1971)

• Maximum Likelihood (Felsenstein 1981)

• Bayesian approach (Rannala and Yang 1996; Huelsenbeck and Ronquist 2001)

Network model

Phylogenetic mechanisms requiring a network representation

• Horizontal gene transfer (i.e. lateral gene transfer)

• Hybridization

• Homoplasy and gene convergence

• Gene duplication and gene loss

1 2 3

4 5

• SplitsTree, Huson and Bryant (2006)

• T-Rex, Makarenkov (2001)

• NeighborNet, Bryant and Moulton (2002)

Software for building phylogenetic networks

Three types of horizontal gene transfer

• Hein (1990) and Hein et al. (1995, 1996)

• Haseler and Churchill (1993)

• Page (1994); Page and Charleston (1998)

• Charleston (1998)

• Hallet and Lagergren (2001)

• Mirkin, Fenner, Galperin and Koonin (2003)

• V’yugin, Gelfand and Lyubetsky (2003)

• Boc and Makarenkov (2003); Makarenkov, Boc and Diallo (2004)

Methods for detecting horizontal gene transfers

The new model

The new model

Basic ideas:

1) Reconcile the species and gene phylogenetic trees using either a topological (Robinson and Foulds topological distance) or a metric (least-squares) criterion

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E

D

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Species Tree Gene Tree

2) Incorporate necessary biological rules into the mathematical model

3) Maintain the algorithmic time complexity polynomial

Partial gene transfer versus complete transfer

A B C D E F

Root

A B C D E F

Root

A B C D E F

Root

Partial Transfer Complete Transfer

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3

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1

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3

2

1

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7

(a) (b)

Biological rules

Partial gene transfer. Incorporating biological rules.

Situations when a new HGT

branch (a,b) can affect the

evolutionary distance between

species i and j,

and cannot affect the distance

between i1 and j.

Root

i

j

x

y

z

wa b

i1

Partial gene transfer. Incorporating biological rules (2).

Three cases when the evolutionary distance between the species i and j is not affected by addition of a new HGT

branch (a,b)

Root

i

jx

y

z

wa b

Root

i

j

x

y

z

wa b

Root

j

x

y

z

wa b

i

(a) (b) (c)

Root

No HGTs can be considered when affected branches are located on the same lineage


Root

Lineage 2Lineage 1

LGT1

LGT2

No HGT can be considered when two HGTs affecting a pair of lineages intersect as shown


i j i j

i j i j

(a) (b)

(c) (d)

b b

b

b1 b

b1

a

a1

a1

a

b1 a1b1 a1

aa

• Cases (a) and (b): path between the leaves i and j is allowed to go through both HGT branches (a,b) and (a1,b1).

• Cases (c) and (d) : path between the leaves i and j is not allowed to go through both HGT branches (a,b) and (a1,b1).


Sub-Tree constraint

Genesub-tree 1

Genesub-tree 2

Genesub-tree 1

x

y

z

w

a b

Genesub-tree 2

x

y

z

wa b

T T1

Timing constraint: the transfer between the branches (z,w) and (x,y) of the species tree T can be allowed if and only if the cluster regrouping both affected sub-trees is present in the gene tree T1. Here and further in the article a single branch is depicted by a plane line and a path is

depicted by a wavy line.

•To arrange the topological conflicts between T and T1 that are due to the

transfers between single species or their close ancestors.

•To identify the transfers that have occurred deeper in the phylogeny.

Optimization

Optimization problem : Least-squares

The least-squares loss function Q to be minimized with the unknown vector of edge lengths l in T and the unknown fraction of the transferred gene α is as follows :

l – the length of the branch k of the path(ij) in T

(i,j) - the given dissimilarity value between i and j

)(

2

)( )(

)),()()1((),(jbpathk

kjb

Sij ijpathk iapathk

kia

kij jilllLQ

Root

i

j

x

y

z

wa b

1-α1-α

1-α

α

α

α

min)),(()(

2 Sij ijpatk

kij jil

Optimization problem : Robinson and Foulds topological distance

The topological distance of Robinson and Foulds (1981)

between two phylogenetic trees is equal to the minimum

number of elementary operations consisting of merging or

splitting vertices necessary to transform one tree into another.

A

B

DC

E

A

B

DE

CT1T

Robinson and Foulds topological distance

Robinson and Foulds distance between T and T1 is 2.

The HGT minimizing the Robinson and Foulds topological distance between the species and gene phylogenetic trees can be considered as the best candidate to reconcile the species and gene phylogenies.

A

B

DC

E

A

B

D

E

CA

B

DC

E

T T1

Algorithm

6A 0 2 3 5 5 4B 2 0 3 5 5 4C 3 3 0 4 4 3D 5 5 4 0 2 3E 5 5 4 2 0 3F 4 4 3 3 3 06A 0 4 4 2 4 4B 4 0 4 4 2 4C 4 4 0 4 4 2 D 2 4 4 0 4 4E 4 2 4 4 0 4F 4 4 2 4 4 0

Input file for our program

Distance matrix or newick string for the species tree

Distance matrix or newick string for the gene tree

Set X of Taxa = {A,B,C,D,E,F}

• Optimization criterion : – Least-Squares – Robinson and Foulds distance.

• Type of scenario : – Unique. – Multiple.

• Maximum number of HGTs.

• Subtree constraint.

• Position of the root.

• Bootstrap (with sequences).

Program options

Algorithm : unique scenario

Begin

Reconstruction of the species tree T and the gene tree T1

Reestimate the length of each branch in T

While Optimization criterion > 0 loop

Test all possible HGTsAdd the best HGTReestimate the length of each branch in TCompute the value of the optimization criterion

End Loop

End

Algorithm : multiple scenario

Begin

Reconstruction of the species tree T and the gene tree T1

Reestimate the length of each branch in T

Test all connections between pairs of branches

Establish a list of HGTs ordered according to the optimization criterion.

End

Algorithm : Step 1

• Reconstruction of the species tree T with Neighbor Joinning

• Set X of n taxa

• Binary tree: internal nodes are all of

degree 3, 2n-3 branches

• T is explicitly rooted (file,prompt,midpoint)

A

F

E

D

C

B

Algorithm : Step 2

• Comparing the gene tree T1 and the species tree T

Criterion 1 :

RF - Robinson and Foulds distance between T and T1

LS - Least-Squares coefficient between distances in T and T1

If RF == 0 or LS == 0 then There is no HGTsElse Step 3End if

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B

F

C

E

D

A

F

E

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B

Species Tree T Gene Tree T1

Algorithm : Step 3

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F

E

D

C

BMultiple Scenario

• Test all connections between pairs of branches.

• Reestimate the length of each branch in T according to the gene distance matrix.

• Establish a list of HGTs ordered according to the least-squares coefficient or the Robinson-Foulds distance.

Algorithm : Step 3

A

F

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A

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D

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Species Tree Upcomming HGT1

Species Tree + HGT1Upcomming HGT2

Species Tree + HGT2Upcomming HGT3

Species Tree + HGT3(Gene Tree)

1

2 3

Unique Scenario

1. The best HGT found is added to the species tree.2. The length of each branch is reestimated according to the gene tree.3. RF distance or LS coefficient are computed.

output**Species tree inferred with NJ (with branch lengths fitted to the gene distance)**

1. 8--B 1.666667 2. 9--C 1.866667 3. 10--D 1.866667 4. 10--11 0.000050 5. 10--E 1.666667 6. 8--A 1.866667 7. 9--8 0.000050 8. 12--Root 0.366687 9. 11--F 1.866667 10. 11--12 0.000050 11. 9--12 0.000050

========================================= = Criteria values before computation ========================================= RF distance = 8 LS criterion = 10.667334 BD criterion = 10.000000 ================ = HGT #1 ============== From branch 8--A to branch D--10 RF = 6 LS = 6.160320 BD = 5.500000 ================ = HGT #2 ============== From branch C--9 to branch F--11 RF = 4 LS = 1.821514 BD = 3.000000 ================ = HGT #3 ============== From branch E--10 to branch B--8 RF = 0 LS = 0.000000 BD = 0.000000

bootstrap

A

F

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.

.

.

.

n replicats(gene trees)

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E

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B

75%

60%

Species Tree Gene Tree

The first gene tree is choosen as the gene tree of reference.

Examples

Horizontal transfer of the Rubisco Large subunit gene

Delwiche, C.F., and J. D. Palmer. 1996. Rampant

Horizontal Transfer and Duplication of Rubisco Genes in

Eubacteria and Plastids. Mol. Biol. Evol. 13:873-882.

Application example 1

rbcL Gene Phylogeny

Mn oxidizing bacterium (S|85-9a1)

Rhodobacter Sphaeroides IXanthobacter

Alcaligenes 17707 chromosomalAlcaligenes H16 plasmidAlcaligenes H16 chromosomal

Cyanidium

PorphyridiumAntithamnion

Ahnfeltia

CryptomonasEctocarpus

OlistodiscusCylindrotheca

ProchlorococcusHydrogenovibrio L2

Chromatium L

Pseudomonas

Thiobacillus ferrooxidans fe1Nitrobacter

Thiobacillus ferr. 19859Thiobacillus denitrificans I

Endosymbiont

AnabaenaSynechococcus

AnacystisProchlorothrix

SynechocystisProchloron

Cyanophora

ChlorellaBryopsis

Chlamidomonas

EuglenaPyramimonas

ColeochaeteMarchantia

PseudotsugaNicotiana

Oryza

Proteobacteria

Proteobacteria

Proteobacteria

Red and Brown Plastids

Cyanobacteria Proteobacteria

Proteobacteria

Proteobacteria

ProteobacteriaProteobacteria

Cyanobacteria

Green Plastids

Glaucophyte Plastid

Green Type(FORM I)

Red Type (FORM I)

Proteobacteria

Proteobacteria

Delwiche and Palmer (1996) - hypotheses of HGTs

1- Cyanobacteria → γ-Proteobacteria

2- α-Proteobacteria → Red and brown algae

3- γ-Proteobacteria → α-Proteobacteria

4- γ-Proteobacteria → β-Proteobacteria

Prochloron

Cyanophora

CyanidiumPorphyridiumAhnfeltiaAnthithamnionCryptomonasEctocarpusOlistodiscusCylindrotheca

CholrellaBryopsisChlamydomonasEuglenaPyramimonasColeochaeteMarchantiaPseudotsugaNicotianaOryza

SynechocystisProchlorothrixAnacystisSynechococcusAnabaenaProchlorococus

NitrobacterMn oxidizing bacteriumXanthobacterRhodobacter Sphaeroïde I

Hydrogenovibrio L2Chromatium L

Thiobacillus ferr. 19859Thiobacillus fe1

PseudomonasEndosymbiontThiobacillus denitificans IAlcaligenes 17707 ChromosomalAlcaligenes H16 ChromosomalAlcaligenes H16 plasmid

Green Plastids

Glaucophyte plastid

Cyanobacteria

-Proteobacteria

-Proteobacteria

-Proteobacteria

Red & Brown algae

6

4

8

7

5

3

1

2

Mn oxidizing bacterium (S|85-9a1)

Rhodobacter Sphaeroides IXanthobacter

Alcaligenes 17707 chromosomalAlcaligenes H16 plasmidAlcaligenes H16 chromosomal

Cyanidium

PorphyridiumAntithamnion

Ahnfeltia

CryptomonasEctocarpus

OlistodiscusCylindrotheca

ProchlorococcusHydrogenovibrio L2

Chromatium L

Pseudomonas

Thiobacillus ferrooxidans fe1Nitrobacter

Thiobacillus ferr. 19859Thiobacillus denitrificans I

Endosymbiont

AnabaenaSynechococcus

AnacystisProchlorothrix

SynechocystisProchloron

Cyanophora

ChlorellaBryopsis

Chlamidomonas

EuglenaPyramimonas

ColeochaeteMarchantia

PseudotsugaNicotiana

Oryza

Proteobacteria

Proteobacteria

Proteobacteria

Red and Brown Plastids

Cyanobacteria Proteobacteria

Proteobacteria

Proteobacteria

ProteobacteriaProteobacteria

Cyanobacteria

Green Plastids

Glaucophyte Plastid

Green Type(FORM I)

Red Type (FORM I)

Proteobacteria

Proteobacteria

Results for hgt-detection

HGTs of the rbcL gene - comparison

Hypotheses by Delwiche and Palmer (1996)

1- Cyanobacteria → -Proteobacteria

2- α-Proteobacteria → Red and brown algae

3- -Proteobacteria → α-Proteobacteria

4- -Proteobacteria → β-Proteobacteria

Solution

1. Cyanobacteria → -Proteobacteria

2. -Proteobacteria → -Proteobacteria


4. -Proteobacteria → Cyanobacteria


6. β-Proteobacteria → -Proteobacteria

7. -Proteobacteria → Red and brown algae


Application example 2

Horizontal transfers of the protein rpl12e

Data taken from:

Matte-Tailliez O., Brochier C., Forterre P. & Philippe H. Archaeal phylogeny based on ribosomal proteins. (2002). Mol. Biol. Evol. 19, 631-639.

Rpl12e HGTs

Pyrobaculum aerophilum

Aeropyrum pernix

Sulfolobus solfataricus

Pyrococcus furiosus

Pyrococcus abyssi

Pyrococcus horikoshii

Methanococcus jannaschii

Methanobacterium thermoautotrophicum

Archaeoglobus fulgidus

Methanosarcina barkeri

Haloarcula marismortui

Halobacterium sp.

Thermoplasma acidophilum

Ferroplasma acidarinanus

Species tree Rpl12e gene tree

Assumed HGTs of the rpl12e gene involved the clusters of Crenarchaeota and Thermoplasmatales (Matte-Tailliez, 2004)


Aeropyrum pernix


Pyrococcus furiosus

Pyrococcus abyssi







Halobacterium sp.



56

100

100

56

51

65

81

61

79

79

74

10

Result for hgt-detection with bootstrap


Aeropyrum pernix


Pyrococcus furiosus

Pyrococcus abyssi







Halobacterium sp.



1

3

4

5

270%

35%

36.3%

48.8%

26.3%

10


Aeropyrum pernix


Pyrococcus furiosus

Pyrococcus abyssi







Halobacterium sp.



56

100

100

56

51

65

81

61

79

79

74

HGT-Detection vs. LatTrans

HGT-Detection vs LatTrans

• LatTrans, Hallett & Lagergren (2001)• time complexity : O(24t n2)

• HGT-Detection•Time complexity : O(n5)

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Number of leaves

Dete

cti

on r

ate

(%

)

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Number of transfers

Dete

cti

on r

ate

(%

)

HGT-Detection vs Lattrans

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Number of leaves

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e s

cenari

o (

%)

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Number of transfers

Runnin

g t

ime

Software

T-REX — Tree and Reticulogram Reconstruction1

Downloadable from http://www.info.uqam.ca/~makarenv/trex.html

Authors: Vladimir Makarenkov

Versions: Windows 9x/NT/2000/XP and Macintosh

With contributions from A. Boc, P. Casgrain, A. B. Diallo, O. Gascuel, A. Guénoche, P.-A. Landry, F.-J. Lapointe, B. Leclerc, and P. Legendre.

________1 Makarenkov, V. 2001. T-REX: reconstructing and visualizing phylogenetic trees and reticulation networks. Bioinformatics 17: 664-668.

T-Rex : Multiple scenario screenshotB

ioin

form

atic

s so

ftw

are

Serveur web (www.trex.uqam.ca)

Internet

Calculateur32 processeurs

de 3.4 Ghz PHP 4.4.1

GeneBase UQAMOracle 10g

UQAM

Chercheurs en bioinformatique de l’ UQAM

Autres utilisateurs

T-Rex Web infrastructure

Future developments

• Partial transfer

• Maximum Likelihood model

• Maximum Parsimony model

• Decreasing the running time

Bibliography

• Boc, A. and Makarenkov, V. (2003), New Efficient Algorithm for Detection of Horizontal Gene Transfer

Events, Algorithms in Bioinformatics, G. Benson and R. Page (Eds.), 3rd Workshop on Algorithms in

Bioinformatics, Springer-Verlag, pp. 190-201.

• Delwiche, C.F., and J. D. Palmer (1996). Rampant Horizontal Transfer and Duplication of Rubisco

Genes in Eubacteria and Plastids. Mol. Biol. Evol. 13:873-882.

• Makarenkov,V. (2001), T-Rex: reconstructing and visualizing phylogenetic trees and reticulation

networks. Bioinformatics, 17, 664-668.

• Makarenkov, V., Boc, A., Delwiche, C.F. and Philippe, H. (2005), A novel approach for detecting

horizontal gene transfers: Modeling partial and complete gene transfer scenarios, submitted Mol. Biol.

Evol.

• Makarenkov, V., Boc, A. and Diallo A.B. (2004), Representing Lateral gene transfer in species

classification. Unique scenario, IFCS’2004 proceedings, Chicago.

• Matte-Tailliez O., Brochier C., Forterre P. & Philippe H. (2002). Archaeal phylogeny based on ribosomal

proteins. Mol. Biol. Evol. 19, 631-639.

• Robinson, D.R. and Foulds L.R. (1981), Comparison of phylogenetic trees, Mathematical Biosciences

53, 131-147.

• Woese, C. R., G. Olsen, M. Ibba, and D. Söll. 2000. Aminoacyl-tRNA synthetases, the genetic code,

and the evolutionary process. Microbiol. Mol. Biol. Rev. 64:202-236.

Documents

Detecting horizontal gene transfers using discrepancies in species and gene classifications Alix Boc Université du Québec à Montréal