PART III. MACROEVOLUTION

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PART III. MACROEVOLUTION We already considered
History of Life and learned a lot about
Macroevolution that occurred in the past - but
only at the shallow level of chronology and
generalizations.
3b) Cladogenesis and extinction are
extremely unfair processes Now, after studying
Microevolution, we are ready to treat the same
subject deeper, and to try to understand hidden
mechanisms of Macroevolution. For some
generalizations simple explanations may be
enough, but Macroevolution is such a complex and
mysterious process that it must be based on
theory, which is so far absent.
GENERALIZATION New genes mostly appear
from pre-existing genes - of course, this is an
easy way. IN NEED OF A DEEP THEORY
Changing lt1 of the genome is enough to turn an
ape into a human - how? We will consider partial
theories of Macroevolution at all levels,
starting from sequences.
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Macroevolution at different levels
At the level of sequences (genomes),
Macroevolution is relatively well-understood. In
contrast, Macroevolution at the next three levels
- molecules, cells and organisms - is understood
very poorly. However, the two upper levels - of
populations and of ecosystems, are simpler again,
and there are many useful partial theories of
their Macroevolution. Sequences are just
genetic texts - they are not doing anything
directly, and are, thus, relatively easy to
study. In contrast, molecules, cells and
organisms are levels where real action occurs.
Not surprisingly, studying them is tough.
However, complexity of adaptations can be ignored
again when we consider Macroevolution of
populations and ecosystems. Macroevolution of
genomes is tightly connected to the evolution of
populations the genome of an organism is just
the record of allele replacements in its
ancestral lineage. In contrast, Macroevolution of
complex phenotypes appears to be mostly
independent of Microevolution.
Organism Individual
ACGATCGACGACGATCGATCGACGATCGA
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Topic 15. Lecture 23-24. Macroevolution of
Genomes What do we know already about the
evolution of sequences? Level-specific
generalizations 1. Sequences a) Mutation
strongly affects sequence evolution, and selfish
segments are common b) Functionally
important segments and sites of genomes usually
evolve slower c) Complex organisms have
larger genomes, mostly due to noncoding
sequences Generalizations concerned with
adaptation and complexity 1. Genetical aspects
of adaptive evolution a) Evolution of both
coding and non-coding sequences is important for
adaptation b) The target for strong positive
selection is narrow at each moment c)
Tightly related genes can perform rather
different functions 3. Origin of novelties
a) New non-coding regulatory sites, but not new
genes, often appear from scratch
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So, what do we want to know, on top of these
generalizations and their simple explanations? It
makes sense to think of two aspects of sequence
evolution. On the one hand, there are properties
of sequence evolution that are mostly dictated by
selection that acts at the upper levels of
organization. We will not consider them
here. On the other hand, there are
properties of sequence evolution that are not
dictated by fitness landscapes in the spaces of
molecules, cells, or multicellular organisms.
MATEGDKLLGGRFVGSTDPIMEILSSSISTEQRLTEVDIQASMAYAK
ALEKASILTKTEL... MAEGDKL GGRF
GSTDPIMELSSI QRLEVDIQ SMAYAKALEKA
ILTKTEL... MASEGDKLWGGRFSGSTDPIMEMLNSSIACDQRL
SEVDIQGSMAYAKALEKAGILTKTEL... Similarity of
delta-crystalline sequence (top) to
argininosuccinate lyase sequence (bottom),
is a sequence-level, and not a molecular-level,
phenomenon. Still, before we can do this, I wish
to briefly address two fundamental concepts of
the theory of sequence evolution that are not
directly concerned with any deep understanding of
evolution, but are necessary to reconstruct its
past course.
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Reconstructing the course of past Macroevolution
of genomes Evolutionary distance. Evolutionary
distance (ED) between two sequences that diverged
from the same ancestral sequence is the number of
accepted nucleotide replacements per site. If two
sequences can be aligned without gaps (simply
placed one above the other), their alignment will
contain the fraction 1-M of matches and the
fraction M of mismatches.
ACACGACACGATGCATACTA
ACACGATACGATGCATGCT
A If two sequences are very similar to each
other, their ED probably equals to M. However,
multiple events per site become important if we
consider more dissimilar sequences. Indeed,
homoplasy can create a match at a site where
multiple substitutions occurred after divergence.
Can we estimate the total number of replacements,
including hidden ones, from the observed
dissimilarity M?
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We observe the fraction of mismatches M, but we
want to know ED, the total number of replacements
that occurred per site. If we know how evolution
occurred, we can derive the function that relates
M (observable) to ED (unobservable). Then, we
invert this function, and estimate unobservable
from observable.
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In the simplest case, known as 1-parameter
Jukes-Cantor model, we assume that all 10
possible nucleotide substitutions (A -gt T, A -gt
G, ...) are equally frequent. If the total
substitution rate per site is a, the rate at
which matches become mismatches is 2a (any
replacement in either sequence will turn a match
into a mismatch), and the rate at which
mismatches become matches is 2a/3 (only one
replacement out of 3 possible ones will turn a
mismatch into a match). Thus,
This equation can be easily integrated
so that
Because, ED2at, our goal has already been
achieved
We can also recover, from the same equation, M as
a function of time
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Reconstructing the course of past Macroevolution
of genomes Sequence alignment. Common ancestry
of individual nucleotides. If divergence of
sequences involved insertions and deletions,
nucleotides derived from the same ancestral
nucleotide can become shifted. Thus, establishing
common ancestry of individual nucleotides from
different species requires sequence
alignment. Let us consider alignment of just 2
sequences, each of length n. They can be aligned,
under reasonable assumptions, in time that is
proportional only to n2. How could this be
done? One option is to construct a "dot-matrix"
that describes matches/mismatches between all the
nucleotides in two sequences (hence n2). After
this, the best path in this matrix can be found,
and this path corresponds to the best alignment.
A x x X G x x X T
x X T x x A x X
x C x X G X x x C X x
A X x x A C G T C A G T
G A
A C G C A T T G A A C G T C
A G T G A
Tricks can be used to find alignments faster, but
the basic idea is to consider a dot-matrix.
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Reconstructing the course of past Macroevolution
of genomes Orthologous segments. In the field
of sequence evolution, homology traditionally
means common ancestry. It is necessary to
distinguish two kinds of common ancestry
("homology") of sequences - orthology and
paralogy. Two segments of different genomes are
orthologous if they originated from the same
segment of the genome of the last common
ancestor. Two segments of the same genome are
paralogous if they originated from the same
segment, by duplication. Two segments of
different genomes are paralogous if they
originated from different paralogous segments of
the genome of the last common ancestor.
The last common ancestor of two modern species, A
and B, had two paralogs in its genome (red and
purple). Red segments of A an B, originated from
ancestral red segment, are each other's
orthologs. The same is true for purple segments,
of course. Red segment of A is a paralog to
purple segments of A and B. Purple segment of A
is a paralog to purple segments of A and B.
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Orthology is established using the bidirectional
best hit test. If for segment a in genome A
segment b in genome B provides the best hit when
a is compared against the whole genome B, and if
a provides the best hit for b, when b is compared
against the whole genome A, we conclude that a
and b are orthologs.
If Nature conspired against us, bidirectional
best hit approach may falsely conclude that
paralogs are orthologs. Thus, genomic contexts
can also be used, when A and B are not too
distant.
A genome may contain two (or more) orthologs to a
segment in some other genome, due to
post-divergence duplication.
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Now, we are ready for theory of Macroevolution at
the sequence level. There are useful partial
theories, describing a variety of phenomena 1)
genes and other functional genome segments often
form families of paralogs. 2) TEs and other junk
genome segments often form families of
paralogs. 3) non-recombining sex chromosomes and
organelle genomes often undergo profound
degeneration. 4) Nucleotide composition
(GC-content) often varies greatly along the
genome. 5) Genome sizes of even not-too-distant
species can differ greatly. 6) at functional
nucleotide sites, the strength of selection is
often s 1/Ne. So, let us try to understand
these 3 sequence-level Macroevolutionary
phenomena
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1) genes and other functional genome segments
often form families of paralogs. First, let us
review the facts. For example, human genome
contains 1434 multigene families of three or more
paralogous genes. Some paralogs form
clusters and are located close to each other, but
many other paralogs are scattered across the
genome.
A sample of clusters of human paralogous genes,
formed by recent duplications.
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A majority of genes within a multigene family
have at least one very close paralog.
KS was estimated for each human gene and its most
closely related human paralog.
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Now, what do we need to understand? Three
things 1) Why some gene duplications are
maintained, and not eliminated by negative
selection? 2) What happens to the paralogs,
after a duplication is fixed? They can either
i) evolve different functions
(neofunctionalization)
or ii) each retain only a part of
the original function (subfunctionalization). 3)
What processes affect the overall properties of
multigene families? The "life history" of a
successful gene duplication consists of 3 phases
i) its origin by a unique mutation, ii) its
fixation within the population, and iii)
divergence of paralogs.
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Mutations that involve a duplication of a long
sequence occur occasionally. A small fraction of
duplications that become successfully fixed are
probably favored by positive selection.
Haploinsufficient genes, such that
heterozygotes carrying a loss-of-function allele
have low fitness, have more paralogs than
haplosufficient genes. If a gene is
haploinsufficient, duplicating it may be a good
idea!
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After a duplication becomes fixed, two things can
happen. One of the two paralogs can be lost,
reversing the duplication. However, if both
paralogs are retained, they will diverge.
There are 2 possibilities subfunctionalization
or neofunctionalization. Only in the second case
the outcome of a duplication is better than the
initial state.
subfunctionalization neofunctionalization
How to explain the distribution of sizes of
families and the excess of similar paralogs?
One possibility is episodes of expansion and
contraction of a multigene family. There are
little data for this scenario. However, paralogs
often "talk to each other" through gene
conversion, which can explain the apparent excess
of "recent" duplications.
So, we at least know what questions to ask
regarding the evolution of multigene families.
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2) TEs and other junk genome segments often form
families of paralogs. First, let us review the
facts. We already know them
1. In many species, families of paralogous
transposable elements (TEs) constitute a large
fraction of the genome. 2. Evolutionary
distances between paralogs within a family
indicate the time when the family has been
formed. 3. In some species (Drosophila)
individual TEs are rare, while in others
(Mammals) they are mostly fixed. We need to
understand factors that control the dynamics of
the families of TEs. The ability of TEs to
cause their own duplications (transpositions) is
the cause of the formation of TE families. But
what regulates the number of TEs in a family?
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Is there an equilibrium number of TEs within a
family? Theoretically, both yes and no answers
are possible.
Paralogous TEs may help each other to propagate.
Thus, an insertion rate grows with the size of a
TE family.
1. Equilibrium insertion rate does not depend
on the TE number, elimination rate increases. 2.
Equilibrium both rates increase, but elimination
rate increases faster. 3. No equilibrium both
rates increase, but elimination rate increases
slower. Unlimited expansion of TEs of a
particular kind in the genome must eventually
lead to extinction of the host lineage. If so,
why did not TEs kill all life?
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Another way to ask this question is what
increases the rate of elimination of TEs when
their number grows? Apparently, the only force
which can eliminate TEs is selection against
those host genotypes that carry many of them.
Still, there are two options
1) Selection against genotypes with many TEs may
be stronger, due to epistasis. 2)
When TEs accumulate, the probability of ectopic
recombination increases. Perhaps both these
effects are responsible for preventing unlimited
expansion of TEs and saving live from extinction.
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3) non-recombining sex chromosomes and organelle
genomes often undergo profound degeneration. Firs
t, let us review the facts. In many clades, sex
chromosomes evolved independently. Often,
the chromosome restricted to the heterogametic
sex (Y or W) never undergoes recombination. Such
non-recombining sex chromosomes have only a small
number of functional genes, contain a lot of
repetitive junk DNA, and encode proteins that
carry multiple mildly deleterious amino acid
replacements.
If males are heterogametic, females are XX, and
males are XY. If females are heterogametic,
females are ZW, and males are ZZ.
Evolutionary degeneration of a non-recombining
sex chromosome.
Why does it happen? Apparently, four processes
contribute to this effect.
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Models (ac) assume that purifying selection
against deleterious mutations is less efficient
on the Y, and model (d) assumes the same about
positive selection for beneficial
mutations. (a) Accumulation of weakly
deleterious mutations by background
selection. (b) Muller's ratchet. (c)
Genetic hitchhiking by favorable
mutations. (d) Lack of adaptation on the
non-recombining Y chromosome.
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In fact, long-term degeneration of
non-recombining Y chromosomes is not the whole
story. Y chromosomes reside only in males, and X
chromosomes reside in females 2/3 of the time.
Thus, genes with a net male benefit can
accumulate on Y chromosome. In contrast, X
chromosome can accumulate genes with female
benefits. The accumulation of sexually
antagonistic alleles on X and Y selects for the
suppression of recombination between the nascent
sex chromosomes, creating a male-specific region
on the Y (MSY). The lack of recombination within
the MSY causes genes in this region to
degenerate, whereas their homologs on the X might
evolve dosage compensation. Next slide shows a
more realistic scenario of the evolution of sex
chromosomes. A number of open questions remain,
but the key process of degeneration of a
non-recombining of sex chromosome appears to be
well-understood.
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Concluding remarks on the evolution of
genomes A genome is a chronicle of past allele
replacements, and Macroevolution of genomes can
be to a large extent explained through
Microevolution of populations. This is good
news. The most interesting facets of the
evolution of genomes are concerned with their
suboptimality - due to mutation-imposed limits on
adaptive evolution (responsible for the origin of
multigene families), mutational pressures
(responsible for proliferation of TEs), and
inefficient selection (responsible for
degeneration of non-recombining chromosomes).
Is accumulation of mildly deleterious junk DNA
essential for adaptive evolution? Functional
sequences often evolve from junk DNA. However, it
is not clear whether availability of junk was
ever a limiting factor for adaptive evolution. If
yes, efficient selection against junk DNA in
unicellular organisms with large populations may
prevent evolution of complexity. Are we
complex because our ancestors somehow accumulated
a lot of junk DNA? OR Do we carry a lot of junk
DNA because we are complex and, thus,
large? Currently, we do not know the answer.
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Quiz So, we know that complex multicellular
organisms have large, "bloated" genomes that
contain a lot of long introns, transposable
elements, and other mostly junk DNA. Two
scenarios can be responsible for this
correlation 1) (Complexity as the cause of
large genomes). Complex multicellular organisms
are physically large. Thus, their populations are
necessarily small - and in small populations weak
selection against new pieces of junk DNA is
inefficient. Thus, genomes became bloated. 2)
(Large genomes as the cause of complexity).
Initially, the genomes of simple unicellular
ancestors of modern complex organisms became
bloated - perhaps, these ancestors had low
population size due to some reason. After this,
complexity and multicellularity evolved, due to
recruitment of some initially junk sequences for
regulation of gene expression. What kinds of
data and analyses could determine, which of the
two scenarios correspond to reality?