The Mathematics of Biological Evolutionpks/Presentation/innsbruck-13.pdf · 2013-09-25 · The...
Transcript of The Mathematics of Biological Evolutionpks/Presentation/innsbruck-13.pdf · 2013-09-25 · The...
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The Mathematics of Biological Evolution
Peter Schuster
Institut für Theoretische Chemie, Universität Wien, Austria and
The Santa Fe Institute, Santa Fe, New Mexico, USA
ÖMG-DMV Congress 2013 Minisymposium: Mathematics of the Planet Earth
Innsbruck, 23.– 24.09.2013
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Web-Page for further information:
http://www.tbi.univie.ac.at/~pks
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1. Prologue
2. Mathematics of Darwin‘s natural selection
3. Mendel, Fisher and population genetics
4. Mutations and selection
5. What means neutrality in evolution?
6. Evolution in simple systems
7. Some origins of complexity in biology
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1. Prologue
2. Mathematics of Darwin‘s natural selection
3. Mendel, Fisher and population genetics
4. Mutations and selection
5. What means neutrality in evolution?
6. Evolution in simple systems
7. Some origins of complexity in biology
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A + X 2 X …… asexual reproduction
A + X + Y X + Y + Z {X,Y} …… sexual reproduction
Two modes of reproduction in biology
viruses, bacteria, some higher organisms (eukaryotes)
most higher organisms (eukaryotes) …… obligatory with mammals
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Leonardo da Pisa „Fibonacci“
~1180 – ~1240
1,0 10
11
==
+= −+
FFFFF nnn
The history of exponential growth
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1, 2 , 4 , 8 ,16 , 32 , 64, 128 , ...
geometric progression
The history of exponential growth
Thomas Robert Malthus 1766 – 1834
Leonhard Euler, 1717 - 1783
nn n
xx )1(lim)(exp +≡ ∞→
exponential function
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The history of exponential growth
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A + X 2 X …… asexual reproduction
growthlexponentia)(exp)0()( tfxtxxfdtdx
=⇒=
[ ] fitnessconst 00 fakaxakdtdx
=⇒==⇒= A
[A] = a ; [X] = x
Reproduction and exponential growth
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Comparison of curves for unlimited growth
1and1)0(tonormalized0
====tdt
dxxxkdtdx α
α
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1. Prologue
2. Mathematics of Darwin‘s natural selection
3. Mendel, Fisher and population genetics
4. Mutations and selection
5. What means neutrality in evolution?
6. Evolution in simple systems
7. Some origins of complexity in biology
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Three necessary conditions for Darwinian evolution are:
1. Multiplication,
2. Variation, and
3. Selection.
Darwin discovered the principle of natural selection from empirical observations in nature.
No attempt has been made to cast the principle into theorems.
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Pierre-François Verhulst, 1804-1849
The logistic equation, 1828
( ) tfeyCyCyty
Cyyf
dtdy
−−+=
−=
)0()0()0()(,1
C …… carrying capacity of the ecosystem
Was known 30 years before the
‘Origin of Species’
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Generalization of the logistic equation to n variables yields selection
( )ΦfxxCΦxf
xfCxxfx
Cxxfx
−==≡
−=⇒
−=
dtd:1,)t(
dtd1
dtd
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Darwin
Generalization of the logistic equation to n variables yields selection
[ ]
( ) ( ) ∑∑
∑
==
=
=−=−=
====
n
i iijjn
i iijjj
iin
i iiin
xfΦΦfxxffxx
ffCxx
11
121
;dt
d
)X(;1;X:X,,X,X
{ } 0vardtd 22 ≥=><−><= fffΦ
A + Xi 2 Xi ; i = 1, 2 , … , n
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Evolutionary optimization
{ }
0lim1lim
,max
)(lim
,
1
max
==
=
=Φ=Φ
≠∞→
∞→
∞→
mjjt
mt
nm
mt
xx
fff
ft
fftft jjj −=Φ−= )()(δφ
f1 = 0.99, f2 = 1.00, f3 = 1.01
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fxfxfxf
kxfdt
dxkk
k
=++=Φ
=Φ−=
332211
3,2,1;)(
simplex S3 is an invariant set e3 …… “corner equilibrium”
Phase diagram of Darwinian selection
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f1 = 1 , f2 = 2 , f3 = 3 , f4 = 7
Before the development of molecular biology mutation was treated as a “deus ex machina”
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1. Prologue
2. Mathematics of Darwin‘s natural selection
3. Mendel, Fisher and population genetics
4. Mutations and selection
5. What means neutrality in evolution?
6. Evolution in simple systems
7. Some origins of complexity in biology
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Recombination in Mendelian genetics
Gregor Mendel 1822 - 1884
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Mendelian genetics
The 1:3 rule
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The results of the individual experiments Gregor Mendel did with the garden pea pisum sativum.
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Darwin
Ronald Fisher‘s selection equation: The genetical theory of natural selection. Oxford, UK, Clarendon Press, 1930.
Ronald Fisher (1890-1962)
( ) { } 0var22dtd 22 ≥=><−><= aaaΦ
Mendel
alleles: A1, A2, ..... , An frequencies: xi = [Ai] ; genotypes: Ai·Aj fitness values: aij = f (Ai·Aj), aij = aji
( )
∑∑ ∑
∑∑
== =
==
==
=−=−=
n
j jjin
j
n
i ji
in
i jijjjin
i jij
xxxaΦ
njΦxaxxΦxxax
11 1
11
1und(t)mit
,,2,1,td
d
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Fitness in Fisher’s selection equation
jifa
xaxxaxa
ij XX
22222112
2111 2)(
fitnessmean
=++=Φ x
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1. Prologue
2. Mathematics of Darwin‘s natural selection
3. Mendel, Fisher and population genetics
4. Mutations and selection
5. What means neutrality in evolution?
6. Evolution in simple systems
7. Some origins of complexity in biology
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organism mutation rate per genome
reproduction event
RNA virus 1 replication retroviruses 0.1 replication bacteria 0.003 replication eukaryotes 0.003 cell division eukaryotes 0.01 – 0.1 sexual reproduction
John W. Drake, Brian Charlesworth, Deborah Charlesworth and James F. Crow. 1998. Rates of spontaneous mutation. Genetics 148:1667-1686.
Hermann J. Muller 1890 - 1967
Thomas H. Morgan 1866 - 1945
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The logic of DNA (or RNA) replication and mutation
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The logic of DNA (or RNA) replication and mutation
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The logic of DNA (or RNA) replication and mutation
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Manfred Eigen 1927 -
∑∑
∑
==
=
==⋅=
=−=
n
i iin
i iijiji
jin
i jij
xfΦxfQW
njΦxxWx
11
1
,1,
,,2,1;dt
d
Mutation and (correct) replication as parallel chemical reactions
M. Eigen. 1971. Naturwissenschaften 58:465, M. Eigen & P. Schuster.1977. Naturwissenschaften 64:541, 65:7 und 65:341
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Mutation-selection equation: [Ii] = xi 0, fi > 0, Qij 0
Solutions are obtained after integrating factor transformation by means
of an eigenvalue problem
fxfxnixxQfdtdx n
j jjn
i iijn
j jiji ==Φ==Φ−= ∑∑∑ === 111
;1;,,2,1,
( ) ( ) ( )( ) ( )
)0()0(;,,2,1;exp0
exp01
1
1
0
1
0 ∑∑ ∑∑
=
=
−
=
−
= ==⋅⋅
⋅⋅=
n
i ikikn
j kkn
k jk
kkn
k iki xhcni
tcb
tcbtx
λ
λ
{ } { } { }njihHBnjibBnjiQfW ijijiji ,,1,;;,,1,;;,,1,; 1 ======÷ −
{ }1,,1,0;1 −==Λ=⋅⋅− nkBWB k λ
1,,1,0;)( −=Φ−= nkdt
dkk
k λbb
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( ) ( )( )
)0()0(;,,2,1;0
0lim1 00
1 00
00 ∑∑ =
=
∞→ ====n
i iin
j j
iiit xhcni
cbcbxtx
The quasispecies is the long-time solution of the mutation-selection equation.
Definition of quasispecies
3210:theoremFrobeniusPerron λλλλ ≥≥>−
=⇔
0
20
10
00
nb
bb
bλ
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Phase diagram of the mutation-selection system
)( 000 Φ−= λbb
dtd
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Selection Selection-recombination Selection-mutation
Method of solution
integrating factor qualitative analysis integrating factor, eigenvalue problem
Linearity yes no yes
Optimization of yes yes no
Unique optimum yes no no optimum
Invariance of Sn yes yes no
Uniqueness of solution
yes no yes
Selection of fittest fittest/coexistence quasispecies
Comparison of mathematical models of evolution
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1. Prologue
2. Mathematics of Darwin‘s natural selection
3. Mendel, Fisher and population genetics
4. Mutations and selection
5. What means neutrality in evolution?
6. Evolution in simple systems
7. Some origins of complexity in biology
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Motoo Kimura’s population genetics of neutral evolution.
Evolutionary rate at the molecular level. Nature 217: 624-626, 1955.
The Neutral Theory of Molecular Evolution. Cambridge University Press. Cambridge, UK, 1983.
Motoo Kimura, 1924 - 1994
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Motoo Kimura
mean time of fixation: 4 Ne … effective population size
mean time of replacement: -1 … reciprocal mutation rate
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mk
mk
k
kk
,,1;
,,1;2
=→
=→+
BXXXA
λ
λ
( ))()()(
)(,,)(,)()(
21
21 2211,,,
tPtPtP
ntntntPtP
m
m
nnn
mmnnn
⋅⋅⋅=
=====
XXX
neutrality: all probabilities are equivalent and the densities identical
( ) ( )ntPtPtPntPntPndt
dPnnnn
n ==−++−= +− )()(;)(2)()1()()1( 11 Xλ
knn
k
nn
n tt
kn
knknn
tttP
−
−
−−+
+
= ∑=
+
22
220
),(min
0
0 111
)(00
λλ
λλ
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BXXXA
→
→+λ
λ 2
( ) ( )ntPtPtPntPntPndt
dPnnnn
n ==−++−= +− )()(;)(2)()1()()1( 11 Xλ
knn
k
nn
n tt
kn
knknn
tttP
−
−
−−+
+
= ∑=
+
22
220
),(min
0
0 111
)(00
λλ
λλ
( ) ( )0
1)(,2)(,)( 00
20
n
tttPtntntE
+
===λλλσ XX
1)(lim 0 =∞→ tPt
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( )m
kk tttPtHtPtH
+
==<=λ
λ1
)()(,)( 0,,0,00 T
m
jmk
jk tt
jm
tH)1(
)()(0 λ
λ+
=
−
=∑
Sequential extinction times Tk
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Sequential extinction times Tk
λλ
λ
mmE
kkmE k
≈−
=
⋅−
=
1)(
1)(
1T
T
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Sewall Wrights fitness landscape as metaphor for Darwinian evolution
Sewall Wright. 1932. The roles of mutation, inbreeding, crossbreeding and selection in evolution. In: D.F.Jones, ed. Int. Proceedings of the Sixth International Congress on Genetics. Vol.1, 356-366. Ithaca, NY.
Sewall Wright, 1889 - 1988
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Evolution as a global phenomenon in genotype space
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many genotypes one phenotype
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Complexity in molecular evolution
W = G F
0 , 0 largest eigenvalue and eigenvector
diagonalization of matrix W
„ complicated but not complex “
fitness landscape mutation matrix
„ complex “ ( complex )
sequence structure
„ complex “
mutation selection
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1. Prologue
2. Mathematics of Darwin‘s natural selection
3. Mendel, Fisher and population genetics
4. Mutations and selection
5. What means neutrality in evolution?
6. Evolution in simple systems
7. Some origins of complexity in biology
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Selma Gago, Santiago F. Elena, Ricardo Flores, Rafael Sanjuán. 2009. Extremely high mutation rate of a hammerhead viroid. Science 323:1308.
Mutation rate and genome size
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Replicating molecules
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RNA replication by Q-replicase
C. Weissmann, The making of a phage. FEBS Letters 40 (1974), S10-S18
Charles Weissmann 1931-
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Kinetics of RNA replication
C.K. Biebricher, M. Eigen, W.C. Gardiner, Jr. Biochemistry 22:2544-2559, 1983
Christof K. Biebricher, 1941-2009
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Paul E. Phillipson, Peter Schuster. 2009. Modeling by nonlinear differential equations. Dissipative and conservative processes. World Scientific Publishing, Hackensack, NJ.
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Paul E. Phillipson, Peter Schuster. 2009. Modeling by nonlinear differential equations. Dissipative and conservative processes. World Scientific Publishing, Hackensack, NJ.
replicase e(t)
plus strand x+(t) minus strand x-(t)
total RNA concentration
xtot(t) = x+(t) + x-(t)
complemetary replication
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Application of molecular evolution to problems in biotechnology
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Viruses
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The error threshold in replication
quasispecies
driving virus populations through threshold
leth
al m
utag
enes
is
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Application of quasispecies theory to the fight against viruses
Esteban Domingo 1943 -
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Molecular evolution of viruses
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1. Prologue
2. Mathematics of Darwin‘s natural selection
3. Mendel, Fisher and population genetics
4. Mutations and selection
5. What means neutrality in evolution?
6. Evolution in simple systems
7. Some origins of complexity in biology
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The bacterial cell as an example for the simplest form of autonomous life
Escherichia coli genome: 4 million nucleotides
4460 genes
The spatial structure of the bacterium Escherichia coli
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Evolution does not design with the eyes of an engineer, evolution works like a tinkerer.
François Jacob. The Possible and the Actual. Pantheon Books, New York, 1982, and
Evolutionary tinkering. Science 196 (1977), 1161-1166.
François Jacob, 1920-2013
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Sketch of a genetic and metabolic network
1 2 3 4 5 6 7 8 9 10 11 12
Regulatory protein or RNA
Enzyme
Metabolite
Regulatory gene
Structural gene
A model genome with 12 genes
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The reaction network of cellular metabolism published by Boehringer-Ingelheim.
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ENCyclopedia Of DNA Elements
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Coworkers
Walter Fontana, Harvard Medical School, MA
Josef Hofbauer, Universität Wien, AT
Martin Nowak, Harvard University, MA
Christian Reidys, University of Southern Denmark, Odense, DK
Karl Sigmund, Universität Wien, AT
Peter Stadler, Bärbel M. Stadler, Universität Leipzig, DE
Thomas Wiehe, Universität Köln, DE
Ivo L.Hofacker, Christoph Flamm, Universität Wien, AT
Paul Phillipson, University of Boulder at Colorado, CO
Christian Forst, University of Texas, Southwestern Medical School, TX
Erich Bornberg-Bauer, Universität Münster, DE
Universität Wien
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Thank you for your attention!
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Web-Page for further information:
http://www.tbi.univie.ac.at/~pks
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