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Welcome to EEB 390 - Evolutionary Biology
Topic 1. Lectures 1-2. Basic Concepts of Evolutionary
Biology
We will start by considering 30 basic concepts of Evolutionary Biology. There will
be no hard facts to remember today or in the next lecture.
So, relax - but pay attention!
Naturally, the first question we need to address is this:
What is Evolutionary Biology?
You may expect Evolutionary Biology to study evolution of life, and this is correct,
as a first approximation.
Thus, the very first concept we need to introduce is evolution of life.
What is Evolution of life?
Evolutio = unrolling (Latin).
As time flows, organisms which currently
represent a lineage, a succession of organisms
connected to each other by ancestor-descendent
relationships, keep changing and deviate more
and more from the original ancestors.
Darwin called this phenomenon descent with
modification, now we call it evolution.
Why is time flowing upwards on this picture?
Strictly speaking, individual organisms do not evolve - only long-lasting lineages
of organisms could evolve.
Of course, natural changes of organisms in a lineage could only be evolutionary
(slow and gradual): a daughter must always be very similar to her mother.
Evolutionary Biology is a science that studies origin of living beings with new
qualities.
Any substantial changes of life is a fair game for evolutionary biology.
Modern life is complex and diverse.
The central claim of Evolutionary Biology is that modern life is a product of long
evolution in the past.
Thus, Evolutionary Biology has two basic tasks - to explain diversity and
complexity of life.
30 Basic Concepts of Evolutionary Biology
1. Anagenesis, Cladogenesis.
2. Phase space, Determinism, Space of genotypes.
3. Levels of organization, Phenotype, Trait, Fitness, Adaptation.
4. Mutation, Variation, Population, Selection, Allele replacement.
5. Fitness landscape.
6. Similarity, Relatedness, Compatibility, Connectedness.
7. Clade, Species.
8. Complexity, Optimality, Evolvability, Designability.
9. Stochasticity, Random drift.
10. Microevolution, Macroevolution.
Bad news: you really need to understand all these difficult concepts.
Good news: you probably understand most of them already.
1. Anagenesis, Cladogenesis.
To explain the origin of modern biodiversity, Evolutionary biology makes two
claims - Weak Claim and Strong Claim - about life in the past.
Weak Claim: if we take a modern species (form of life), and trace its lineage back
in time, we will encounter organisms that deviate more and more from this
species.
This claim may seem weird - elephants do not produce bears.
Strong Claim: if we take several modern species, and trace their lineages back in
time, we will see them merging one-by-one until, at some remote moment, the
only one lineage remains. Thus, all modern species have Common ancestry.
This may seem even more weird - there are no intermediate forms between
humans and flies.
We need to understand why biologists universally accept these weird claims.
Thus, in lectures 3-6 we will consider indirect evidence for past evolution.
In other words, the Weak Claim asserts that
Anagenesis (changes in one lineage) happened,
and the Strong Claim asserts that
Cladogenesis (splitting of an evolving lineage) happened.
These two evolutionary processes are responsible for the origin of complexity
and diversity of life.
2. Phase space, Determinism, Space of genotypes.
When an object can exist in many different states, it helps to think of its Phase
space which consists of all these states .
Phase, state, and configurational space are synonyms.
The concept of phase space permeates all natural sciences.
Changes of the object correspond to movements of the point which represents its
current state within the phase space.
If these changes are gradual (evolution), the
movement does not include any instant leaps.
Let us consider four examples of phase spaces.
Phases of water in the two-dimensional
Euclidian temperature-pressure phase space.
Solid, liquid, and gaseous are three phases of matter.
Can you think of a one-dimensional phase space?
What is the phase space of a pendulum?
Shapes of fly wings reside in an infinite-dimensional phase space of continuous
functions.
Still, a wing can be, as a good approximation, described by a finite number of
parameters: length, width, and, say, two parameters characterizing its shape.
Who needs more dimensions to describe a human being - a tailor or a surgeon?
Natural sciences is a struggle to describe complex objects in a manageable way.
Phase space of chess
Initial position
All possible moves
by white
Q: How many positions and how many games
are possible?
A: Way more than the number of electrons in the
Universe.
Impossible position
The numbers of positions and games are about
as large as the numbers of sequences and of
evolutionary trajectories of a short protein.
Phase space of English texts
We cannot convert Hamlet into Pride and Prejudice by small editorial changes, in
such a way that all the intermediate texts are meaningful. Or can we?
So, how can a prokaryote genome be transformed into a human genome, by
accumulating a lot of (mostly) small mutations one-by-one, and without becoming
meaningless along the way?
The ultimate goal of Evolutionary Biology is to answer this question - and we are
still a very long way from acheiving it.
In some simple cases, we may assume that movements with the phase space are
deterministic.
Determinism: assumption that the current state of an object predetermines its
changes in the future. A deterministic process is predictable and reproducible.
Example: radioactive decay is a (macroscopically) deterministic process: knowing
the current number of radioactive atoms, we can predict (approximately!) this
number for any moment in the future, and infer it for any moment in the past.
One-dimensional phase space of the
number N of radioactive atoms. Rate
of N as a function of N (l is the
constant of decay): dN/dt = -lN.
Because N declines at rate proportional
to it current value, N is an exponential
function of time t: N(t) = N0e-lt.
Some aspects of evolution can also be viewed as a deterministic process.
Thus, the key equation of evolution theory is also a differential equation!
One-dimensional phase space of the
frequency [A] of an advantageous allele
A. Rate of [A] as a function of [A] (s is
selection coefficient):
Red lines: [A] as function
of time t:
[A](t) = 1/(1+((1-[A]0)/[A]0)e-st)
d[A]/dt = s[A](1-[A]) (blue line).
Natural selection is a macroscopically deterministic process, due to the same
reasons as in the case of radioactive decay.
Evolution of life unfolds within the Space of genotypes - because an organism is,
first of all, characterized by its genotype.
Space of genotypes
is L-dimensional,
where L is the length
of the longest genotype.
How long is the
human genome?
Genome =
consensus
of genotypes
To call the number of all possible genotypes that are not longer than ours,
43,000,000,000 = 101,600,000,000 astronomical is a huge understatement. Of course, the
vast majority of these sequences are garbage - and still evolution must somehow
navigate its way through the space of genotypes.
3. Levels of organization, Phenotype, Trait, Fitness, Adaptation.
Levels of organization: sequences, molecules, cells, organisms, populations,
ecosystems.
The idea is simple:
This is an interaction between organisms (individuals) - not between cells or
molecules.
When possible, we will try to consider evolution at different levels of organization
independently. Still, evolution of genotypes is behind it all.
Phenotype: any description of life at any level (usually, the term is not applied to
sequences, populations, or ecosystems).
Life has to rebuild itself from the ground up every generation.
Genotype -> phenotype maps are a key subject in biology:
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Trait is a part of description of the phenotype. How to subdivide a phenotype into
traits? Informally, we want traits to:
1) Work within the organism as independently as possible,
2) Vary between the organisms as independently as possible,
3) Provide the most compact possible description of variation,
4) Make sure that descriptions of parents and offspring are similar.
This common-sense approach will be sufficient. For example:
Hs
Pt
Cf
Ss
Bt
1
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MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAED
MALWMRLLPLLVLLALWGPDPASAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAED
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MALWTRLLPLLALLALWAPAPAQAFVNQHLCGSHLVEALYLVCGERGFFYTPKARREAEN
MALWTRLRPLLALLALWPPPPARAFVNQHLCGSHLVEALYLVCGERGFFYTPKARREVEG
Hs
Pt
Cf
Ss
Ss
Bt
Bt
61
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LQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN
LQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN
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PQAGAVELGGGLGGLQALALEGPPQKRGIVEQCCTSICSLYQLENYCNOO
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60
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110
110
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105
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Alignment of preproinsulin sequences from 5 mammals.
Before we define sequence traits, sequences should be aligned. Then, the i-th trait
describes the amino acid (including "-") which occupies the i-th position within
the alignment.
Fitness: a trait of the complete phenotype of an organism which describes the
efficiency of its reproduction.
Simplistically, (absolute) fitness is the total number of offspring.
Function (biological): any process, within the organism, which contributes to its
reproduction.
Adaptation (noun): any part of the phenotype which performs a function.
What are the functions
of human heart, and what
adaptations are responsible
for performing them?
An adaptation can be general, being useful under a wide range of environments
(like heart).
Alternatively, an adaptation may work only under a very specific environment.
Mullerian mimicry, mutualistic resemblance between unpalatable species,
involving Heliconius melpomene, Heliconius erato, and their comimics in Eastern
Peru. On the top line are H. melpomene (left) and H. erato (right) from the upper
Huallaga. Their pattern switches to join a "rayed" mimicry ring in the lower
Huallaga, where a similar rayed pattern was adopted by 10 different unpalatable
species. Thus, the rayed pattern is adaptive only in one locality.
4. Mutation, Variation, Population, Selection, Allele replacement.
Mutation: any change in the DNA sequence due to unavoidable errors in its
replication and in the repair of its damages.
TCATAGA > TCAGAGA (substitution, transversion)
TCATAGA > TCAAGA
(deletion of 1 nucleotide)
Variation: any differences, genotypic or phenotypic, between organisms from
some set.
Dominant allele with
incomplete penetrance?
Population: a set of organisms that represent competing lineages, such that
expansion of one lineage would lead to decline of others. Members of the same
population live together (more or less) and usually can interbreed (if sexual).
Every organism belongs to a population. Why?
There are at least two reasons:
1) organisms are smaller than their environments,
2) a lone lineage would soon go extinct.
Selection (natural selection): differential reproduction of individuals within a
population - an unavoidable consequence of variation in fitness.
It is convenient to reserve the term "selection" only for those situations when
different genotypes (or phenotypes) confer different (average) fitnesses.
The outcome of selection depends only on relative fitnesses of genotypes.
If we think in terms of populations,
the concept of selection is
obvious: the winner is the one
who runs faster.
Allele replacement: changes of frequencies of alleles (genes) within the
population, resulting in one allele replacing all other alleles at the locus.
Selection-driven allele replacement is the key process in Darwinian evolution.
Increase, with time, of the frequency of the fittest allele.
How many selection-driven allele replacements did it take to convert apes into
humans? Definitely less than 30,000,000 - and may be just 300?
The Darwinian mechanism of evolution, by mutation and selection, is very
wasteful. Lamarckian evolution would be more efficient .
Also, selection is greedy - it cannot have any foresight.
So, how could it possibly produce any good outcomes?
Apparently, a greedy algorithm can work! Still, it seems likely that many
potentially nice phenotypes can never be produced by Darwinian evolution.
Important notes about this course:
1) STUDY POSTED MATERIALS BEFORE EACH LECTURE. I HAVE NO CHOICE
BUT TO GO FAST - I WANT TO TEACH YOU SOMETHING.
2) In the Syllabus, you will find a list of 40 questions, which cover the whole
course. All tests will be based only on these questions.
3) There will be a one-question quiz at the end of each lecture, due before the
beginning of the following lecture. You are ENCOURAGED to discuss answers
with your peers, but please write them independently!
4) I WANT to see you in my office hours (or contact me if you need to talk at a
different time - [email protected]).
Disclaimer:
You may have religious beliefs that make it impossible to accept past evolution of
life as a fact. Relax and fear not - my job is to teach you biology, and not to
indoctrinate you in the matters of faith. I will try to make sure that you understand
and remember scientific concepts, data, and reasoning. If you succed in this, but
still believe that the Earth was created 6,000 years ago (and, perhaps, that Prof.
Kondrashov, as an "evolutionist", will end up in Hell), this is none of my business.
Personally, I think that denying wellestablished facts for the sake of religion or anything else - is ridiculous and sad.
However, I grew up under Communism
and absolutely hate it when an authority
imposes its views by coercion.
Quiz - due when you enter the room for the next lecture:
What are the differences between Lamarckian and Darwinian mechanisms of
evolution? Why the superior Lamarckian mechanism is not working in nature? Do
you think it would be possible to distinguish the outcomes of Lamarckian and
Darwinian evolution?
Hint: these are open-ended questions. Show your reasoning, give some examples,
and everything will be OK.
5. Fitness landscape.
Fitness is a function (mathematical) in the space of genotypes. Fitness landscape
is a graph of this function. In other words, fitness landscape (= adaptive
topography), is a genotype > fitness map.
Fitness landscapes is the best "mental language" for thinking about evolution.
Still, it is a difficult concept!
The "ultimate" fitness landscape exists over the >3,000,000,000-dimensional
space of complete genotypes. Obviously, it cannot be drawn! Thus, it helps to
consider fitness landscapes over spaces of partial genotypes or phenotypes. Let
us first assume that fitness depends only on 1 or 2 traits.
Fitness of the majority of
possible genotypes is 0.
If fitness is below 1, the
lineage will go extinct.
There are fitness maxima
(peaks) separated by valleys.
Fitness landscape over two-dimensional phase space.
Because selection tries to increase fitness, maxima on the fitness landscape are
of particular importance. Nothing new appears with more than two dimensions.
A local maximum (peak) on the fitness landscape is surrounded by its slopes,
which constitute its domain of attraction. A lineage under selection will climb the
peak in whose domain of attraction it was located initially, and stay on it forever.
Thus, any fitness maximum is a trap for an evolving lineage.
Thus, key properties of fitness landscapes
imply that greedy Darwinian evolution must
be subject to historical constraints. Indeed,
such constraints are everywhere. For
example, superficially similar sharks,
ichthyosaurs, and dolphins retain a lot of
features that define them as fishes, reptiles,
and mammals, respectively.
Still, this simple analysis is definitely not
the whole story, because of 3 paradoxes:
1) peaks on a generic fitness landscape are
all of different heights, but the mean
absolute fitness of any lineage must be very
close to 1.
2) evolution keeps going on for over 3.5
billion years, without settling on any peak.
3) A lineage sometimes splits into two,
instead of always climbing up as a unit.
These paradoxes can be resolved if we remember that fitness landscapes are not
invariant, but depend on the environment. In other words, we have to consider not
just one fitness landscape, but a family of them, each corresponding to one of
many possible sets of environmental conditions.
Resolution of paradox 1:
If the height of an occupied
fitness peak exceeds one,
the size of the population
which occupies it
increases, eventually
causing the peak to reach
the equilibrium height of
one - the fitness landscape
bends locally under the
weight of the population.
Resolution of paradox 2:
The environment may affect not only
the heights, but also the locations of
peaks. This can lead to never-ending
evolution if the peak occupied by a
population keeps moving. The
population will follow, with some lag.
Resolution of paradox 3:
If two populations occupying the
same position within the space of
genotypes experience different
fitness landscapes, their evolution
can proceed along completely
different paths. This can happen, for
example, if the two populations live
in different locations and under
different environments.
Instead of the family of all possible fitness landscapes, we may consider only
fitness peaks, and plot their locations under all possible environments. When the
environment, and the fitness landscape, changes slightly, a peak usually
responds by moving a little. However, occasionally a peak can disappear or
appear out of nothing. Still rarer, one peak splits into two, or two peaks merge into
one. Thus, all possible locations of fitness peaks form a system of connected and
branching ridges.
Or we can draw a more
inclusive picture, and show
not just peaks but all genotype
which possess non-zero
fitnesses under some
environments. Such genotypes
are a small minority, as most
of possible genotypes are
garbage. Still, evolution can
occur only if fit genotypes
form long enough continuous
paths within the space of
genotypes.
Try to master the language of
fitness landscapes - it is the
key to understanding
evolution.
Complete fitness landscapes are unknown. Think of immense, highly complex
fitness landscapes mostly hidden in the darkness of non-existence, with only tiny
spots on them visible, each illuminated by a population.
6. Similarity, Relatedness, Compatibility, Connectedness.
To comprehend the enormous diversity of life, the following 4 concepts, each
applicable to just a pair of individuals, are very useful.
Similarity of two individuals can refer to their genotypes or phenotypes.
Genotypes of a human (Homo sapiens) and a chimpanzee (Pan troglodytes) are
98.7% similar, if we count only nucleotide substitutions, or ~95% similar,
if we also count gaps with their lengths:
ATACGATCGATACGATCGATCGAAGCATGC---GTGTGATC
ACACGA----------CGATCGATGCATGCACAGTGTGATC
Relatedness of two individuals is the time (or a number of generations) which
lapsed since their last common ancestor.
The last common ancestor of a human and a chimpanzee lived ~6 million years, or
~300,000 generations, ago.
Connectedness of two individuals describes whether their genotypes and
phenotypes are connected by a continuous chain of genotypes and phenotypes of
other currently existing individuals.
Aquilegia formosa
Aquilegia pubescens
Two "species", A. formosa and A.
pubescens, are connected by a
wide variety of intermediate
individuals.
Common ancestry implies that
any two individuals, however
dissimilar, are connected if we
take past life into account.
Compatibility of two individuals describes whether genotypes consisting of
assortments of corresponding segments from their genotypes would be OK.
Two fit organisms may, nevertheless, be
incompatible to each other, like horses
and donkeys.
In contrast, Africans and
Europeans are compatible.
Two very similar individuals must also be closely related, compatible, and
connected. Still, there is no 1:1 correspondence between these four
characteristics of pairs of individuals.
The hippopotamus is more similar, at least at the level of phenotypes, to the pig,
but is more closely related to the dolphin.
A ring of forms of
greenish warbler,
Phylloscopus
trochiloides. The two
extreme forms, blue
and red, live together
in Central Siberia
without much
interbreeding. Still,
these two forms are
connected, in the
space of genotypes,
by a continuum of
intermediate forms,
whose ranges go
around the Tibetan
Plateau.
Sometimes, rather different genotypes are, nevertheless, connected to each other
by a continuous chain of currently-living genotypes.
The opposite pattern: disconnected forms may yet be compatible. Rhododendron
catawbiense (Eastern North America, left) and R. fortunei (China, right) are distinct
"species", with no natural intermediates. Nevertheless, they are fully compatible,
and produce fertile hybrids (center).
Concepts of similarity, relatedness, connectedness, and compatibility provide us
with the language that is necessary to think about the structure of biodiversity.
7. Clade, Species.
Now we are ready to address the structure of biodiversity. Here, the two most
important concepts are clade, which is relevant to relatedness, and species,
which is relevant to compatibility.
Clade: any complete branch of a phylogenetic tree, a set of all descendants of a
particular common ancestor. Every two members of a clade are more tightly
related to each other than any one of them to any non-member.
Examples of clades
Species: a set of individuals that are all compatible to each other.
All modern humans belong to the same species, Homo sapiens, perhaps to the
exclusion of Pan troglodytus.
Life is not always that simple, and we will encounter many gray areas later.
8. Complexity, Optimality, Evolvability, Designability.
Complexity is another general property - and wonder - of life. To understand the
origin of complex phenotypes is another great goal of Evolutionary Biology. This
goal is even more elusive than understanding the origin of biodiversity.
Both goals were clear to Darwin. The title of his most famous book refers to the
origin of biodiversity, but he explicitly described the origin of complexity as the
most mysterious facet of evolution.
"To suppose that the eye, with all its inimitable contrivances for adjusting the
focus to different distances, for admitting different amounts of light, and for the
correction of spherical and chromatic aberration, could have been formed by
natural selection, seems, I freely confess, absurd in the highest possible degree."
(Darwin, "The Origin of Species", 1859, Chapter 6).
Complexity is not easy to define. Still, a phenotype is complex if it:
1) consists of many interacting parts,
2) requires a long description, so that its phase space has many dimensions,
3) is fragile, so that even a small change can alter its properties radically.
We encounter staggering
complexity at all levels of
organization of life. Still,
sequences and populations
are simpler than molecules,
cells, and organisms.
In order to think about evolution of complex phenotypes, the following 3 concepts
are of great help.
Optimality: a phenotype is optimal if it performs its function better than any other
feasible phenotype. Greedy evolution can hardly produce optimal complex
phenotypes - it does not permit radical redesigning. Human eye, although
marvelous, is a striking example of suboptimality.
Evolvability: a phenotype is evolvable if it can be changed a little, without losing
its function. Currently, experimental studies of evolvability are possible only at a
very limited scale.
A: Five amino acids of isopropylmalate dehydrogenase that cause it to
preferentially bound NAD (ignore anomalous Arg341).
B: Five amino acid replacements which convert NAD-binding enzyme into NADPbinding enzyme.
Designability: a phenotype is designable if greedy evolution can arrive to it from a
wide range of other phenotypes.
How designable are natural adaptations?
Somehow, evolution managed to arrive to the human eye, starting from very
simple photoreceptors and gradually perfecting them.
Euglena is a protist with a
distinct eyespot. Euglena
displays phototaxis - a
reaction to light.
The "cross-eyed" flatworm Dugesia has
two eyespots composed of cells full of
photosensitive pigments. These
eyespots allow Dugesia to react to light.
9. Stochasticity, Random drift.
Determinism is simple and neat, but it is not the whole story.
Stochasticity: a process is stochastic if it is unpredictable and irreproducible.
Is Nature inherently deterministic or stochastic? Einstein believed in determinism
("God does not play dice"), but, apparently, he was wrong.
if a population simply climbs on the fitness landscape, it will always arrive to the
same peak, starting from a particular initial state. However, in reality evolution is a
stochastic process, due to several reasons:
1) mutation is a quantum phenomenon and, thus, is inherently stochastic,
2) environments and initial conditions are irreproducible.
3) reproduction of an individual is unpredictable, for all practical purposes,
4) populations are too small to mask this elementary stochasticity.
Random drift refers to stochastic fluctuations of allele frequencies in the
population, due to reasons 3) and 4).
Because the number of individuals
in any population is smaller than
the number of atoms in any sample,
determinism is a poorer (but still
often useful) approximation for
population processes than for
radioactive decay.
Because of its stochasticity, evolution, facing essentially the same situation on
several occasions, usually takes a different course each time.
Rock pocket mice, are
generally light-colored
and live on light-colored
rocks. However, some of
their populations live on
dark lava, and they
acquire dark coat color.
In different places, dark
coat colors evolved by
completely different
genetic mechanisms.
10. Microevolution, Macroevolution.
The most important pattern in biodiversity is that in the space of genotypes (or
phenotypes) it consists of clumps of similar individuals. This is rather similar to
stars, most of which are parts of galaxies, within the physical space.
Two-scale structure of visible
matter: a majority of stars are
organized in galaxies.
Two-scale structure of biodiversity:
every organism belongs to a more or
less distinct group (cluster, population,
form of life) of very similar organisms.
This two-scale structure of biodiversity leads to two distinct scales in the
evolution of life.
Macroevolution profound changes, at
the scale of differences
between different
forms of life.
Microevolution - small
changes, at the scale of
differences between
members of the same
population.
Time scales of Micro- and
Macroevolution.
Macroevolution is obviously important - it describes origin of novel organisms.
Why do we care about Microevolution? Because Macroevolution occurs through
natural selection of advantageous variants within populations. In other words,
Microevolution drives Macroevolution.
An allele replacement is an interface between Microevolution and Macroevolution.
We just reviewed
30 Basic Concepts of Evolutionary Biology
1. Anagenesis, Cladogenesis.
2. Phase space, Determinism, Space of genotypes.
3. Levels of organization, Phenotype, Trait, Fitness, Adaptation.
4. Mutation, Variation, Population, Selection, Allele replacement.
5. Fitness landscape.
6. Similarity, Relatedness, Compatibility, Connectedness.
7. Clade, Species.
8. Complexity, Optimality, Evolvability, Designability.
9. Stochasticity, Random drift.
10. Microevolution, Macroevolution.
Are they really that difficult?
Q: What motivates the overall structure of this course?
A: The structure of modern evolutionary biology, which consists of 3 parts:
I) Studies of past evolution. Successful since XIX century.
Data on past evolution remain our key
source of information on how
Macroevolution works and, moreover,
the main reason to believe that
Macroevolution is, indeed, possible.
II) Studies of Microevolution. Successful since XX century.
Microevolution can be understood by
combining Darwinian selection with
Mendelian genetics ("evolutionary
synthesis").
III) Studies of Macroevolution. Still in their infancy, will flourish in XXI century.
We still do not understand
Macroevolution well. There are many
useful generalizations, but only very
fragmented theory.
?
Structure of this course in more detail
(see posted Syllabus for even more detail)
1-2.
Basic concepts of evolutionary biology
I) PAST EVOLUTION
3-6.
Evidence for past evolution of life
7.
Reconstructing the course of past evolution
8.
Earth and fossils
9-10. History of life on Earth
11.
Recent history of the Homo sapiens lineage
12-13. Generalizations emerging from past evolution
14.
Evolution while you are watching
15-16.
17.
18.
19.
20.
21.
22.
23.
II) MICROEVOLUTION
Populations and tools for studying them
Within-population variation
Mutation
Natural selection
Sex, population structure, and random drift
Actions of positive, negative, and balancing selection
Microevolutionary mechanisms of Macroevolution
Species and speciation
24.
25
26.
27.
III) MACROEVOLUTION
Macroevolution of genomes
Macroevolution of complex phenotypes
Macroevolution of populations
Macroevolution of ecosystems
28.
IV) EPILOGUE
Implications of evolutionary biology outside natural sciences
I hope that you will find this structure sensible.
Quiz - due when you enter the room for the next lecture:
What fundamental properties of nature make evolution unpredictable, and to what
extent can we ignore this unpredictability?