Agreement among gene trees could be used as evidence of common ancestry ?

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Agreement among gene trees could be used as
evidence of common ancestry ?

• Jessica Clarke and Flor Rodriguez
• March 21st , 2006

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Arguments for common ancestry

• the genetic code is a frozen accident
• when life first arises it alters the environment
  so as to make subsequent start-ups much less
  probable
• species with common ancestor are more likely to
  exhibit congruence in character state patterns
  than species that originated separately

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Hypothesis of common ancestryby Penny et al.
(1982)

• Prediction
• Orthologous genes should lead to similar trees
  because they are expected to share the same
  evolutionary history
• developed an algorithm that guaranteed to find
  all minimal-length trees
• implemented a tree-comparison metric to measure
  closeness
• calculated the expected distribution of this
  metric
• Conclusion
• Theory of evolution leads to quantitative
  predictions that are testable and falsifiable

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Measuring the difference
T1-T11 complete data set T12-T17
cytochrome c T18 fibrinopeptide
A T19-T26 fibrinopeptide B T27-T32
haemoglobin ? T33-T39 haemoglobin ?
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Measuring the difference
The symmetric difference metric on two trees
counts the number of edges that occur in one,
but not both, trees
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Critic by Sober and Steel 2002 Common ancestry
might be untestable
Long ages of time might have erased the pertinent
evidence
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Response from Penny et al. 2003

• Methods of tree construction based on parsimony
• assume common ancestry

Methods other than parsimony can be used, and
should be favored if they give more consistent
results when analyzing and comparing different
data sets
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Response from Penny et al. 2003

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

Some alternatives of the theory of common
ancestry can be formulated, tested and rejected

• The theory of influenza viruses from outer space
• The theory that every species was created
  separately (ID)

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• Influenza viruses continue to arrive
• from outer space via comets
• Hoyle and Wickramasinghe 1984, 1986
• under the theory of descent linear tree is
  expected
• if each epidemic was carried on different comets,
  a correlation between their order of arrival and
  their phylogeny is not expected
• Test 1
• Probability of sequences occurring on a linear
  tree in the same order as the year of appearance
• P lt 10-6 , that the linear tree (observed order)
  occurs by chance
• The theory of descent was not rejected

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Influenza viruses from space

• Test 2
• Steiner tree (Binary tree) was not rejected
• It is not necessary that all possible
  alternatives to a model MUST be rejected
  simultaneously

t1
t3
t2
t4
t1
t2
t3
t4
Binary tree
Star-tree
1 in 1064
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Intelligent design

• Theory of descent vs. theory of individual
  creation
• Example
• Photosynthetic enzymes from plants living in
  hot-dry environments and those living in a
  moist-temperate lawn

correct prediction
Theory of descent leads to testable predictions
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Agreement Between Gene Trees

• Evidence for common descent.. or NOT?

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History of Life

• 3.5byo - oldest prokayotic fossils
• 1.7byo - oldest eukaryotic fossils
• 545-525myo - cambrian explosion
• 475myo - first land plants
• 400myo - origin of vascular tissue
• 300myo - origin of seed plants
• 130myo - origin of flowering plants

Campbell, 1999
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Main Sources

• www.talkorigins.org
• www.trueorigins.org

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Main Arguments

• Trees do not match
• Design not ruled out
• Evolution is not falsifiable
• Molecules do not evolve according to predictions

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Predictions Violated

• Common ancestry predicts agreement among trees.
• Trees do not agree perfectly.
• Therefore, the common ancestry claim is rejected.

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Response

• NR (2n-3)!! (2n-3)!/(2n-2(n-2)!

Theobald, 2006
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Design Not Rejected

• Anatomy and biochemistry are not independent.
• Organisms similar anatomically, are similar
  biochemically- and vise versa.
• Thus, gene agreement could reflect design.

Brand 1997
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Response

• There is no biological reason, besides common
  descent, that similar morphologies should have
  similar biochemestry.
• Besides, we can use neutral genes, and genes with
  vastly different functions to construct trees.

Theobald, 2006
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Not Falsifiable / Not Science

• Evolutionary predictions are shown false
• Evolution is not falsified.
• Thus, evolution is not falsifiable, and is not
  science.
• Possible examples
• horizontal transfer
• hybridization

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Predictions Violated

• Evolution predicts that divergence between
  lineages is proportional to evolutionary distance
  (constant rate of evolution).
• bp changes between lineages does not match
  predictions
• Therefore, claim is false ( molecular data are
  bunk).

Camp, 2001
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Cytochrome C
Turtle
Human
Rattlesnake
22 bp
14 bp
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Cytochrome C
Kangaroo
Human
Horse
12 bp
10 bp
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Response

• Common ancestry does not predict uniform rates.
• Even given uniform rates, events are stochastic,
  and thus should not match predictions exactly.

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

Theobald, 2006
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References

• Brand, Leonard. 1997. Faith, Reason, and Earth
  History. Andrews University Press, Berrien
  Springs, MI.
• Camp, Ashby. 2001. A critique of Douglas
  Theobalds 29 Evidences for Evolution.
• 09 March, 2006. www.trueorigin.org/theobald1a.asp
  
• Campbell, N., Reece J., Mitchell, L. 1999.
  Biology, fifth edition. Benjamin/Cummings,
  Menol Park, CA.
• Kumar, S., and Subramanian, S. 2002. Mutation
  rates in mammalian genomes. Proc Natl Acad Sci.
  99 803-808.
• Penny D., Hendy M., Zimmer E. and R. Hamby. 1990.
  Trees from sequences Panacea or Pandoras box?.
  Aus. Syst. Bot., 3, 21-38.
• Penny D., Hendy M. and M. Steel. 1991.Testing the
  theory of descent. In Phylogenetic analysis of
  DNA sequences. 155-183.
• Penny D., Foulds L. and M. Hendy. 1982. Testing
  the theory of evolution by comparing phylogenetic
  trees constructed from five different protein
  sequences. Nature. 297197-200.
• Penny D., Hendy M. and A. Poole. 2003. Testing
  fundamental evolutionary hypotheses. J. Theor.
  Biol. 223377-385.
• Robinson D. and L. Foulds. 1981.Comparison of
  phylogenetic trees. Math. Biosc. 53131-147.

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References

• 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)1337-1344.
• Rokas A., Williams B., King Nicole and S.
  Carroll. 2003. Genome-scale approaches to
  resolving incongruence in molecular phylogenies.
  Nature. 425798-804
• Sober E. and M. Steel. 2002. Testing the
  hypothesis of common ancestry. J. Theor. Biol.
  218395-408.
• Theobald, Douglas L. "29 Evidences
  Macroevolution The Scientific Case for Common
  Descent." The Talk.Origins Archive. Vers. 2.85. 8
  Jan, 2006 http//www.talkorigins.org/faqs/comdesc/
  
• Theobald, Douglas. 29 Evidences for
  Macroevolution A Response to Ashby Camps
  Critique. 21 March, 2002
• www.talkorigins.org/faqs/comdesc/camp.html

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The competing hypotheses

• Ho CA-1 single ancestral origin
• Ha CA-i, i gt1 separate origination events

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The competing hypotheses
Ho CA-1 single ancestral origin Ha CA-i,
i gt1 separate origination events

• Simplest model
• A , all trait follows the same rules
• B, each trait follows the same rules on all
  branches
• C, all the changes that a single character can
  experience on a given branch must have the same
  probability

Most complex model -A , allow traits to follow
different rules -B, allow a single trait to
follow different rules on different branches -C,
each possible change of a single trait on a
single branch to have its own probability
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The competing hypotheses

• Graph Process model
• Gi Mj
• Gi Mj
• estimate parameters in the model
• L(Gi Mj)
• One can not compare different topologies
• that have different process models
• attached to them

L(Gi Mj) L(Gi Mk)
L(Gi Mj) L(Gk Mj)
LRT does not
apply
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Akaike information criterion (AIC)

• AIC is based on a theorem that describes how the
  predictive accuracy of a model M containing
  adjustable parameter can be estimated
• L(M) is the hypothesis obtained from M by
  assigning values to adjustable parameters that
  maximize the probability of the data
• Good fit-to-data increase predictive accuracy
• Penalty for complexity
• Applies to nested and non-nested models

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Trees from sequences

• Advantages
• scope or domain a character
• range of evolutionary rates
• large number of characters
• mechanism of evolution
• easier data handle
• expectation of useful characters
• cost of obtaining data
• Penny et al. 1990

• Limitations
• Sampling errors
• - sequences too short
• - unrepresentative sequences
• Methodological problems
• - large number of possible trees
• - incomplete use of information
• - converging to an incorrect tree
• - deviations from the standard
• model
• Human error
• - errors in data and programming
• - misreading the tree

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The limits to phylogeny reconstruction depend on
the model

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

fast consistent efficient
robust falsifiable
Results from current methods should be treated
as hypotheses for future testing