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Phylogenetic Networks - DIMACS

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Phylogenetic Phylogenetic Networks Networks Daniel H. Huson Daniel H. Huson www www - - ab.informatik.uni ab.informatik.uni - - tuebingen.de tuebingen.de
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Page 1: Phylogenetic Networks - DIMACS

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PhylogeneticPhylogenetic NetworksNetworks

Daniel H. HusonDaniel H. Huson

wwwwww--ab.informatik.uniab.informatik.uni--tuebingen.detuebingen.de

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PhylogeneticPhylogenetic NetworksNetworksAs a data representation As a data representation techniquetechnique

Splits graphs and othersSplits graphs and others

As a more complex As a more complex model of evolutionmodel of evolution

Reticulation graphs: Reticulation graphs: such as hybridization such as hybridization graphs or ancestor graphs or ancestor recombination graphsrecombination graphs

xx11 xx33 xx44 xx99 xx1010xx22

xx55

xx88xx66

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PhylogeneticPhylogenetic NetworksNetworks

Rooted splits graphRooted splits graph UnrootedUnrootedreticulation graphreticulation graph

Either type of graph can be Either type of graph can be unrootedunrooted or rootedor rooted

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What is a Splits Graph?What is a Splits Graph?

The The split encodingsplit encoding ΣΣ(T) of a tree T:(T) of a tree T:

GG11

GG88

GG77

GG66

GG55

GG44

GG33GG22

GG11,G,G33,G,G44,G,G66,G,G77 vsvs GG22,G,G55,G,G88

eeGG88

GG55GG22

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What is a Splits Graph?What is a Splits Graph?

CutCut--set of parallel edges defines split {set of parallel edges defines split {A,BA,B} } vsvs restrest

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GlossaryGlossarySplits system Splits system ΣΣ: a set of splits : a set of splits ((bipartitioningsbipartitionings) of a given ) of a given taxontaxon set Xset XSplits graph GSplits graph G: graph representing : graph representing ΣΣ(includes trees, not necessarily planar!)(includes trees, not necessarily planar!)SplitsTreeSplitsTree: a program providing various : a program providing various algorithms for computing splits graphsalgorithms for computing splits graphsSplit decompositionSplit decomposition: an algorithm for : an algorithm for computing splits from distancescomputing splits from distances(other: (other: NeighborNeighbor--Net, consensus networks, Net, consensus networks, or Zor Z--super networks)super networks)

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Example: Consensus NetworksExample: Consensus NetworksSix input trees:Six input trees:

ΣΣ((1/6):1/6): ΣΣ((0):0):ΣΣ((1/2):1/2):

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SplitsTree4 SplitsTree4

Provides many Provides many algorithms for algorithms for

phylogeneticphylogenetic analysis analysis using trees and using trees and

networksnetworks

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The The SplitsTreeSplitsTree ProgramProgram

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The The SplitsTreeSplitsTree ProgramProgram

TaxaTaxaUnalignedUnalignedCharactersCharactersDistancesDistancesQuartetsQuartetsTreesTreesSplitsSplits

Main WindowMain Window

Method WindowMethod Window

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Example: ZExample: Z--Super NetworkSuper NetworkFive trees fungal trees from Five trees fungal trees from (Pryor 2000) and (Pryor 2003)(Pryor 2000) and (Pryor 2003)Trees:Trees:

ITS (two trees)ITS (two trees)SSU (two trees)SSU (two trees)GpdGpd (one tree)(one tree)

Numbers of Numbers of taxataxa differ: “partial trees”differ: “partial trees”Trees from Trees from TreeBaseTreeBase

Unfortunately, no edge lengthsUnfortunately, no edge lengths

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Individual Gene TreesIndividual Gene Trees

ITS00ITS00

46 46 taxataxa

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Individual Gene TreesIndividual Gene Trees

ITS03ITS03

40 40 taxataxa

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Individual Gene TreesIndividual Gene Trees

SSU00SSU00

29 29 taxataxa

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Individual Gene TreesIndividual Gene Trees

SSU03SSU03

40 40 taxataxa

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Individual Gene TreesIndividual Gene Trees

Gpd03Gpd03

40 40 taxataxa

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Gene Trees as Super NetworkGene Trees as Super Network

ZZ--closure: a fast superclosure: a fast super--network method (WABI 2004)network method (WABI 2004)

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Gene Trees as Super NetworkGene Trees as Super Network

ITS00+ITS00+ITS03ITS03

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Gene Trees as Super NetworkGene Trees as Super Network

ITS03+ITS03+SSU00SSU00

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Gene Trees as Super NetworkGene Trees as Super Network

ITS00+ITS00+ITS00+ITS00+SSU03SSU03

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Gene Trees as Super NetworkGene Trees as Super Network

ITS00+ITS00+ITS03+ITS03+SSU03+SSU03+Gpd03Gpd03

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Gene Trees as Super NetworkGene Trees as Super Network

ITS00+ITS00+ITS03+ITS03+SSU00+SSU00+SSU03+SSU03+Gpd03Gpd03

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ZZ--Super NetworkSuper Network

AA22

BB22

Idea: Idea: ExtendExtend partial splits.partial splits.

ZZ--rule:rule:

Repeatedly apply to completion. Repeatedly apply to completion. Return all full splits.Return all full splits.

AA11

BB11

AA22

BB22

AA11

BB11∪ ∪ BB22

AA11 ∪ ∪ AA22

BB22

∩∩

,,

AA11

BB11

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Reticulation NetworksReticulation Networks

aabb11 cc bb33

bb22

hh

PP QQ

Ancestral genomeAncestral genomegg11

Build gene treesBuild gene trees

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Reticulation NetworksReticulation Networks

PP

gg11PP--treetree

QQ

hhbb1 aa cc bb331

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Reticulation NetworksReticulation Networks

PP

gg22

QQ

hhaabb11 cc bb33

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Reticulation NetworksReticulation Networks

PP

gg22QQ--treetree

QQ

hhaabb11 cc bb33

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From Gene Trees to Reticulation GraphsFrom Gene Trees to Reticulation Graphs

gene tree1gene tree1 gene tree2gene tree2 combinedcombinedsplits

reticulationreticulationgraphsplits graph

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Multiple Independent ReticulationsMultiple Independent Reticulations

Two hybridizations Two hybridizations ⇒⇒four different gene trees

reconstructedreconstructedreticulationsall splitsall splits reticulations

four different gene trees

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NonNon--Independent Reticulation EventsIndependent Reticulation Events

base treebase tree

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Splits GraphSplits Graph

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Reticulation GraphReticulation Graph

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Reticulation GraphReticulation Graph

Ambiguous,Ambiguous,unless root in unless root in

{t{t55,t,t66} or {b} or {b11,…,b,…,b44}}

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Application to Real Data: ButtercupsApplication to Real Data: Buttercups

ITS (nuclear genome)ITS (nuclear genome) JSA (chloroplast genome)JSA (chloroplast genome)

jointly with Pete Lockhartjointly with Pete Lockhart

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Application to Real Data: ButtercupsApplication to Real Data: Buttercups

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Application to Real Data: ButtercupsApplication to Real Data: Buttercups

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Algorithm to Detect Reticulation Algorithm to Detect Reticulation •• Input: set of splits Input: set of splits ΣΣ•• Process each component of the Process each component of the

incompatibility graph IG(incompatibility graph IG(ΣΣ) separately) separately•• Generate all possible “linear” Generate all possible “linear”

reticulation scenariosreticulation scenarios•• Check necessary conditions on splitsCheck necessary conditions on splits•• Check sufficient conditions on splitsCheck sufficient conditions on splits•• Modify splits graph to display Modify splits graph to display

detected reticulationsdetected reticulations

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Splits Graphs and ReticulationsSplits Graphs and Reticulations

XXAA

BB11 BB22 BB33 BB44

XXCC

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Recognizing an Isolated ReticulationRecognizing an Isolated Reticulation

XX

BB11 BB22 BB33 BB44

uu1 uu3uu2 uu41 32 4

AA CC

AABB11 BB22 BB33 BB44

XX

dd2dd1 dd3 dd421 3 4

CC

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Recognizing an Isolated ReticulationRecognizing an Isolated Reticulation

The associated splits graph…The associated splits graph…

BB11 BB22 BB33 BB44

XX

uu11 uu22 uu33 uu44dd11 dd22 dd33 dd44

uu11

dd33 uu22

uu33

uu44

dd44

dd22

dd11

AA CC

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Splits Graph to Reticulation GraphSplits Graph to Reticulation Graph

The associated splits graph…

BB22 BB33

AA CC

BB44BB11

The associated splits graph…

Delete all Delete all internal edgesinternal edges

XX

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Splits Graph to Reticulation GraphSplits Graph to Reticulation Graph

& the reticulation graph

AA

XX

Delete all Delete all internal edgesinternal edges

CC

BB44BB33BB11 BB22

The associated splits graph…The associated splits graph… & the reticulation graph

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Reconstruction From Mosaic SequencesReconstruction From Mosaic Sequences

Mosaic sequences evolvingMosaic sequences evolvingalong two different treesalong two different trees

Splits graph containingSplits graph containingthe splits of both treesthe splits of both trees

NeighborNeighbor--netnet

As sequences grow longerAs sequences grow longer

AA

BB

CCDD

EEff

eeAA

BB

CC

DDEE

AABB

CC DDEE

ee

ff

NeighborNeighbor--net consistentnet consistenton circular distanceson circular distancesGalled trees always circularGalled trees always circularBryant, Huson, Bryant, Huson, KloepperKloepper and and NieseltNieselt, WABI 2003, WABI 2003

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SummarySummarySplits graphs and reticulation networks Splits graphs and reticulation networks are different, but related types of are different, but related types of phylogeneticphylogenetic networksnetworksBased on this, algorithms for detecting Based on this, algorithms for detecting and visualizing “linear” reticulation and visualizing “linear” reticulation scenarios can be developedscenarios can be developedImplementations exist and will be made Implementations exist and will be made available in available in SplitsTreeSplitsTree

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AcknowledgementsAcknowledgementsTobias Tobias KloepperKloepper and Mike Steel and Mike Steel (hybridization detection algorithms)(hybridization detection algorithms)Pete Lockhart (application to plants)Pete Lockhart (application to plants)Dave Bryant (SplitsTree4)Dave Bryant (SplitsTree4)

Software: wwwSoftware: www--ab.informatik.uniab.informatik.uni--tuebingen.detuebingen.de


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