Agreement among gene trees Agreement among gene trees could be used as evidence of could be used as evidence of

common ancestry ?common ancestry ?

Jessica Clarke and Flor RodriguezJessica Clarke and Flor RodriguezMarch 21March 21stst , 2006 , 2006

Arguments for common ancestryArguments for common ancestry

the genetic code is a “frozen accident”the genetic code is a “frozen accident”

when life first arises it alters the environment so when life first arises it alters the environment so as to make subsequent start-ups much less as to make subsequent start-ups much less probableprobable

species with common ancestor are more likely to species with common ancestor are more likely to exhibit congruence in character state patterns exhibit congruence in character state patterns than species that originated separatelythan species that originated separately

Hypothesis of common ancestryHypothesis of common ancestryby Penny by Penny et alet al. (1982). (1982)

Prediction:Prediction:Orthologous genes should lead to similar trees Orthologous genes should lead to similar trees because they are expected to share the same because they are expected to share the same evolutionary historyevolutionary history

developed an algorithm that guaranteed to find all developed an algorithm that guaranteed to find all minimal-length treesminimal-length trees

implemented a tree-comparison metric to measure implemented a tree-comparison metric to measure closenesscloseness

calculated the expected distribution of this metriccalculated the expected distribution of this metric

Conclusion:Conclusion:Theory of evolution leads to quantitative predictions Theory of evolution leads to quantitative predictions that are testable and falsifiablethat are testable and falsifiable

Measuring the differenceMeasuring the difference

T1-T11 complete data set

T12-T17 cytochrome c

T18 fibrinopeptide A

T19-T26 fibrinopeptide B

T27-T32 haemoglobin T33-T39 haemoglobin

Measuring the differenceMeasuring the difference

* * ***

*

The symmetric difference metric on two trees counts The symmetric difference metric on two trees counts the number of edges that occur in one, but not both, treesthe number of edges that occur in one, but not both, trees

Critic by Sober and Steel 2002Critic by Sober and Steel 2002 Common ancestry might be untestableCommon ancestry might be untestable

I(X,Z) I(X,Z) ≤ 4k max≤ 4k maxi i {n{niiee-4rti-4rti}} I(X, Y) ≤ neI(X, Y) ≤ ne-4rt-4rt

n = 1000n = 1000t = 20 million yearst = 20 million yearsr = 1 in 2million yearsr = 1 in 2million years

n = 100n = 100t = 20 million yearst = 20 million yearsr = 1 in 100 million yearsr = 1 in 100 million years

K = 10 000K = 10 000

No method can infer X from YNo method can infer X from Ywith a probability that is any with a probability that is any better than simply ignoring Y better than simply ignoring Y and blindly guessing Xand blindly guessing X

No method can reliably No method can reliably determine from this data determine from this data how these four groups are how these four groups are related historicallyrelated historically

Long ages of time might have erased the pertinent evidenceLong ages of time might have erased the pertinent evidence

Response from Penny Response from Penny et al.et al. 2003 2003

Methods of tree construction based on parsimony Methods of tree construction based on parsimony

assume common ancestryassume common ancestry

Methods other than parsimony can be used, and Methods other than parsimony can be used, and should be favored if they give more consistent results should be favored if they give more consistent results

when analyzing and comparing different data setswhen analyzing and comparing different data sets

Response from Penny Response from Penny et al.et al. 2003 2003

The hypothesis of common ancestry (CA)The hypothesis of common ancestry (CA)might be untestablemight be untestable

Some alternatives of the Some alternatives of the theory of common ancestrytheory of common ancestry

can be formulated, tested and rejectedcan be formulated, tested and rejected

The theory of influenza viruses from outer spaceThe theory of influenza viruses from outer space The theory that every species was created separately The theory that every species was created separately

(ID)(ID)

Influenza viruses continue to arrive Influenza viruses continue to arrive from outer space via cometsfrom outer space via comets

Hoyle and Wickramasinghe 1984, 1986Hoyle and Wickramasinghe 1984, 1986

under the theory of descent linear tree is expectedunder the theory of descent linear tree is expected if each epidemic was carried on different comets, a if each epidemic was carried on different comets, a

correlation between their order of arrival and their correlation between their order of arrival and their phylogeny is not expectedphylogeny is not expected

Test 1:Test 1: Probability of sequences occurring on a linear tree in the Probability of sequences occurring on a linear tree in the

same order as the year of appearance same order as the year of appearance P < 10P < 10-6 -6 , that the linear tree (observed order) occurs by , that the linear tree (observed order) occurs by

chancechance

The theory of descent was not rejectedThe theory of descent was not rejected

Influenza viruses from spaceInfluenza viruses from space

Test 2:Test 2:

Steiner tree (Binary tree) was not rejectedSteiner tree (Binary tree) was not rejected It is not necessary that all possible alternatives to a It is not necessary that all possible alternatives to a

model MUST be rejected simultaneouslymodel MUST be rejected simultaneously

t1

t2

t3

t4

Binary treet1 t2 t3 t4

Star-tree

1 in 1064

Intelligent designIntelligent designTheory of descent vs. theory of individual creationTheory of descent vs. theory of individual creation

Example:Example: Photosynthetic enzymes from plants living in hot-dry Photosynthetic enzymes from plants living in hot-dry

environments and those living in a moist-temperate lawnenvironments and those living in a moist-temperate lawn

correct prediction correct prediction

Theory of descent leads to testable predictionsTheory of descent leads to testable predictions

Agreement Between Agreement Between Gene TreesGene Trees

Evidence for common descent….. Evidence for common descent….. or NOT?or NOT?

History of LifeHistory of Life

3.5byo - oldest prokayotic fossils3.5byo - oldest prokayotic fossils 1.7byo - oldest eukaryotic fossils1.7byo - oldest eukaryotic fossils 545-525myo - cambrian explosion545-525myo - cambrian explosion 475myo - first land plants475myo - first land plants 400myo - origin of vascular tissue400myo - origin of vascular tissue 300myo - origin of seed plants300myo - origin of seed plants 130myo - origin of flowering plants130myo - origin of flowering plants

Campbell, 1999

Main SourcesMain Sources

www.talkorigins.orgwww.talkorigins.org

www.trueorigins.orgwww.trueorigins.org

Main ArgumentsMain Arguments

Trees do not match Trees do not match Design not ruled outDesign not ruled out Evolution is not falsifiableEvolution is not falsifiable Molecules do not evolve according to Molecules do not evolve according to

predictionspredictions

Predictions ViolatedPredictions Violated

Common ancestry predicts agreement Common ancestry predicts agreement among trees.among trees.

Trees do not agree perfectly.Trees do not agree perfectly. Therefore, the common ancestry claim is Therefore, the common ancestry claim is

rejected.rejected.

ResponseResponse

NR = (2n-3)!! = (2n-3)!/(2n-2(n-2)!

Rooted Unrooted Number of Possible Trees2 3 13 4 34 5 155 6 1056 7 9457 8 10,3958 9 135,1359 10 2,027,025

10 11 654,729,075

20 21 8,200,794,532,637,890,000,000

Number of Taxa

Theobald, 2006

Design Not RejectedDesign Not Rejected

Anatomy and biochemistry are not independent.Anatomy and biochemistry are not independent. Organisms similar anatomically, are similar Organisms similar anatomically, are similar

biochemically- and vise versa.biochemically- and vise versa. Thus, gene agreement could reflect design.Thus, gene agreement could reflect design.

Brand 1997

ResponseResponse

There is no biological reason, besides There is no biological reason, besides common descent, that similar common descent, that similar morphologies should have similar morphologies should have similar biochemestry.biochemestry.

Besides, we can use neutral genes, and Besides, we can use neutral genes, and genes with vastly different functions to genes with vastly different functions to construct trees.construct trees.

Theobald, 2006

Not Falsifiable / Not ScienceNot Falsifiable / Not Science

Evolutionary predictions are shown falseEvolutionary predictions are shown false Evolution is not falsified.Evolution is not falsified. Thus, evolution is not falsifiable, and is not science.Thus, evolution is not falsifiable, and is not science.

Possible examplesPossible examples horizontal transferhorizontal transfer hybridizationhybridization

Predictions ViolatedPredictions Violated

Evolution predicts that divergence between Evolution predicts that divergence between lineages is proportional to evolutionary distance lineages is proportional to evolutionary distance (constant rate of evolution).(constant rate of evolution).

# bp changes between lineages does not match # bp changes between lineages does not match predictionspredictions

Therefore, claim is false (& molecular data are Therefore, claim is false (& molecular data are bunk).bunk).

Camp, 2001

14 bp

22 bp

Turtle HumanRattlesnake

Cytochrome CCytochrome C

10 bp

12 bp

Kangaroo HumanHorse

Cytochrome CCytochrome C

Response Response

Common ancestry does not predict Common ancestry does not predict uniform rates.uniform rates.

Even given uniform rates, events are Even given uniform rates, events are stochastic, and thus should not match stochastic, and thus should not match predictions exactly.predictions exactly.

Distribution of genetic distances between human and mouse Distribution of genetic distances between human and mouse genes. genes. The histogram is the actual data from 2,019 human and mouse The histogram is the actual data from 2,019 human and mouse genes. The solid curve shows the expected distribution of genetic genes. The solid curve shows the expected distribution of genetic distances assuming only a constant rate of background mutation (~10distances assuming only a constant rate of background mutation (~10-9-9 substitutions per site per year) (reproduced from Figure 3a in Kumar and substitutions per site per year) (reproduced from Figure 3a in Kumar and Subramanian 2002).Subramanian 2002).

Theobald, 2006

ReferencesReferences Brand, Leonard. 1997. Brand, Leonard. 1997. Faith, Reason, and Earth HistoryFaith, Reason, and Earth History. Andrews University Press, . Andrews University Press,

Berrien Springs, MI.Berrien Springs, MI. Camp, Ashby. 2001. A critique of Douglas Theobald’s “29 Evidences for Evolution”. Camp, Ashby. 2001. A critique of Douglas Theobald’s “29 Evidences for Evolution”.

09 March, 2006. 09 March, 2006. www.trueorigin.org/theobald1a.aspwww.trueorigin.org/theobald1a.asp Campbell, N., Reece J., Mitchell, L. 1999. Biology, fifth edition. Campbell, N., Reece J., Mitchell, L. 1999. Biology, fifth edition.

Benjamin/Cummings, Menol Park, CA.Benjamin/Cummings, Menol Park, CA. Kumar, S., and Subramanian, S. 2002. Mutation rates in mammalian genomes. Proc Kumar, S., and Subramanian, S. 2002. Mutation rates in mammalian genomes. Proc

Natl Acad Sci. 99: 803-808.Natl Acad Sci. 99: 803-808. Penny D., Hendy M., Zimmer E. and R. Hamby. 1990. Trees from sequences: Penny D., Hendy M., Zimmer E. and R. Hamby. 1990. Trees from sequences:

Panacea or Pandora’s box?. Aus. Syst. Bot., 3, 21-38.Panacea or Pandora’s box?. Aus. Syst. Bot., 3, 21-38. Penny D., Hendy M. and M. Steel. 1991.Testing the theory of descent. In: Penny D., Hendy M. and M. Steel. 1991.Testing the theory of descent. In:

Phylogenetic analysis of DNA sequences. 155-183.Phylogenetic analysis of DNA sequences. 155-183. Penny D., Foulds L. and M. Hendy. 1982. Testing the theory of evolution by Penny D., Foulds L. and M. Hendy. 1982. Testing the theory of evolution by

comparing phylogenetic trees constructed from five different protein sequences. comparing phylogenetic trees constructed from five different protein sequences. Nature. 297:197-200.Nature. 297:197-200.

Penny D., Hendy M. and A. Poole. 2003. Testing fundamental evolutionary Penny D., Hendy M. and A. Poole. 2003. Testing fundamental evolutionary hypotheses. J. Theor. Biol. 223:377-385.hypotheses. J. Theor. Biol. 223:377-385.

Robinson D. and L. Foulds. 1981.Comparison of phylogenetic trees. Math. Biosc. Robinson D. and L. Foulds. 1981.Comparison of phylogenetic trees. Math. Biosc. 53:131-147.53:131-147.

ReferencesReferences Rokas A. and S. Carroll. 2005. More genes or more taxa?. The relative contribution of Rokas A. and S. Carroll. 2005. More genes or more taxa?. The relative contribution of

gene number and taxon number to phylogenetic accuracy. Mol. Biol. Evol. 22(5):1337-gene number and taxon number to phylogenetic accuracy. Mol. Biol. Evol. 22(5):1337-1344.1344.

Rokas A., Williams B., King Nicole and S. Carroll. 2003. Genome-scale approaches to Rokas A., Williams B., King Nicole and S. Carroll. 2003. Genome-scale approaches to resolving incongruence in molecular phylogenies. Nature. 425:798-804resolving incongruence in molecular phylogenies. Nature. 425:798-804

Sober E. and M. Steel. 2002. Testing the hypothesis of common ancestry. J. Theor. Sober E. and M. Steel. 2002. Testing the hypothesis of common ancestry. J. Theor. Biol. 218:395-408.Biol. 218:395-408.

Theobald, Douglas L. "29+ Evidences Macroevolution: The Scientific Case for Common Theobald, Douglas L. "29+ Evidences Macroevolution: The Scientific Case for Common Descent." Descent." The Talk.Origins ArchiveThe Talk.Origins Archive. Vers. 2.85. 8 Jan, 2006. Vers. 2.85. 8 Jan, 2006 http://www.talkorigins.org/faqs/comdesc/

Theobald, Douglas. “29+ Evidences for Macroevolution: A Response to Ashby Camp’s Theobald, Douglas. “29+ Evidences for Macroevolution: A Response to Ashby Camp’s “Critique”. 21 March, 2002“Critique”. 21 March, 2002

www.www.talkoriginstalkorigins..org/faqs/comdesc/camporg/faqs/comdesc/camp.html.html

The competing hypothesesThe competing hypotheses

Ho: CA-1 single ancestral origin

Ha: CA-i, i >1 separate origination events

The competing hypothesesThe competing hypotheses

Simplest modelSimplest model

A , all trait follows the same rulesA , all trait follows the same rulesB, each trait follows the same rules B, each trait follows the same rules

on all brancheson all branchesC, all the changes that a single C, all the changes that a single

character can experience on a character can experience on a given branch must have the given branch must have the same probabilitysame probability

Most complex modelMost complex model

-A , allow traits to follow different -A , allow traits to follow different rulesrules

-B, -B, allow a single trait to follow allow a single trait to follow different rules on different different rules on different branchesbranches

-C, -C, each possible change of a each possible change of a single trait on a single single trait on a single branch to have its own branch to have its own probabilityprobability

Ho: CA-1Ho: CA-1 single ancestral originsingle ancestral origin

Ha: CA-Ha: CA-ii,, i i >1>1 separate origination separate origination eventsevents

The competing hypothesesThe competing hypotheses

GraphGraph Process modelProcess model GGii MMjj

GGii & MMjjestimate parameters in the model estimate parameters in the model

L(L(GGii && MMjj))

One can not compare different topologiesOne can not compare different topologiesthat have different process modelsthat have different process models

attached to themattached to them

L(L(GGii && MMjj))

L(L(GGii && MMkk))L(L(GGii && MMjj))

L(L(GGkk&& MMjj)) LRT does not applyLRT does not apply

Akaike information criterion (AIC)Akaike information criterion (AIC)

AIC is based on a theorem that describes how the AIC is based on a theorem that describes how the predictive accuracy of a model predictive accuracy of a model M M containing adjustable containing adjustable parameter can be estimatedparameter can be estimated

L(M)L(M) is the hypothesis obtained from is the hypothesis obtained from MM by assigning by assigning values to adjustable parameters that maximize the values to adjustable parameters that maximize the probability of the dataprobability of the data

Good fit-to-data increase predictive accuracy Good fit-to-data increase predictive accuracy

Penalty for complexityPenalty for complexity

Applies to nested and non-nested modelsApplies to nested and non-nested models

AdvantagesAdvantages scope or domain a characterscope or domain a character range of evolutionary ratesrange of evolutionary rates large number of characterslarge number of characters mechanism of evolutionmechanism of evolution easier data handleeasier data handle expectation of useful charactersexpectation of useful characters cost of obtaining datacost of obtaining data

Penny et al. 1990Penny et al. 1990

LimitationsLimitations Sampling errors:Sampling errors:

- sequences too short- sequences too short- unrepresentative sequences- unrepresentative sequences

Methodological problems:Methodological problems:- large number of possible trees- large number of possible trees- incomplete use of information- incomplete use of information- converging to an incorrect tree- converging to an incorrect tree- deviations from the standard - deviations from the standard

modelmodel Human error:Human error:

- errors in data and programming- errors in data and programming- misreading the tree- misreading the tree

Trees from sequencesTrees from sequences

The limits to phylogeny reconstruction The limits to phylogeny reconstruction depend on the modeldepend on the model

A good method for reconstructing trees should A good method for reconstructing trees should have the properties of beinghave the properties of being

fastfast consistent consistent

efficientefficient robust robust

falsifiablefalsifiable

Results from current methods should be treated Results from current methods should be treated as hypotheses for future testingas hypotheses for future testing