Download Document

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Hologenome theory of evolution wikipedia , lookup

Natural selection wikipedia , lookup

Gene expression programming wikipedia , lookup

Evolutionary developmental biology wikipedia , lookup

The eclipse of Darwinism wikipedia , lookup

Adaptation wikipedia , lookup

Molecular paleontology wikipedia , lookup

Saltation (biology) wikipedia , lookup

Organisms at high altitude wikipedia , lookup

Evidence of common descent wikipedia , lookup

Genetics and the Origin of Species wikipedia , lookup

Koinophilia wikipedia , lookup

Speciation wikipedia , lookup

Population genetics wikipedia , lookup

Introduction to evolution wikipedia , lookup

Transcript
Chapter 23 - Molecular evolution:
Types of questions:
•
•
How do genomes, DNA, and protein sequences evolve?
•
Dynamics and mode of change.
•
Rates of change.
How are genes and organisms evolutionarily related?
•
Phylogenetic systematics/trees/networks
•
Species concepts (allopatric/sympatric)
Different time scales:
•
Short-term: ‘population genetics’ tends to focus on genetic changes
between generations and within species or between very closely
related species.
•
Long-term: ‘molecular systematics’ tends to focus on genetic
changes over many generations; departures from Hardy-Weinberg
equilibrium can become significant, leading to speciation.
Some basics:
Homology = refers to a structure, behavior, or other character of two
taxa that is derived from the same or equivalent feature of a
common ancestor.
•
Homology applies to nucleotide sequences:
•
Positional vs. character homology
GTACCT
G-ATCT
1.
Four of six nucleotide positions have undergone no change.
2.
A substitution has occurred at position 4.
3.
Insertion/deletion has occurred in one sequence at position 2.
Sequence alignment:
•
Rapid sequence divergence or divergence over many generations
can leave little in common between two sequences and make
alignment difficult or impossible.
•
Indels ~ may be impossible to distinguish between an insertion in
one sequence and a deletion in another sequence.
example: mtDNA 12S rRNA in six different genera
CCACCT-GT---TTCAAAA-CTCAGGCCTT
TCACCTAGC---TCCAAA--C-TAGGCCTT
CTGCCT-AC---TTCCC---C-CAGGCCTT
TCGCCT-AC---T-CAA---C-CAGGCTTT
TCGCCT-ACATTTTCCC---C-CAGGCTTT
•
Many alignment methods exist; all use algorithms that seek to
maximize the number of possible matching nucleotides or amino
acids and minimize the number of indels.
Jukes-Cantor (1969) model of nucleotide substitution:
•
Alignment of sequences with many differences underestimates the
actual number of substitutions.
•
PC(t) = 1/4 + (3/4)e-4t
 = rate of substitution
•
# substitutions/site =
K =-3/4ln(1-4/3p)
p = % difference (raw count)
Fig. 25.1
Saturation of DNA Sequences
Transversions
Transitions
http://www.ccg.unam.mx/~vinuesa/images/Ti_tv_saturation_plot.png
Rates of nucleotide substitution between sequences:
•
Rate = r = K/(2T)
*2T because substitutions accumulate simultaneously and
independently in both sequences (two lineages).
taxon 1
taxon 2
Rates of nucleotide substitution (cont.):
•
Different genes evolve at different rates.
•
Coding regions and non-coding regions differ.
•
Different parts of the coding region differ:
3rd pos. are 2- and 4-fold degenerate  synonymous substitution
•
Synonymous substitution ~5X > than non-synonymous substitution.
•
Substitution ≠ mutation
•
Substitution implies that the mutation has passed through the
filter of selection.
•
Synonymous subsitution ~ mutation rate
•
Non-synonymous substitution ≠ mutation rate.
Rates of nucleotide substitution (cont.):
•
Most substitutions in 3’-flanking regions are tolerated.
•
Rates: 3’ regions > introns > exons
•
5’ regions < 3’ regions due to the presence of promoters and other
regulatory elements.
•
Leader and trailer regions < 5’ regions; important for mRNA
processing and translation.
•
Highest overall rates of substitution occur in non-functional
pseudogenes and other non-functional, non-coding sequence such
as microsatellites.
Codon usage bias:
•
Some synonymous codons are favored over others
e.g., yeast Leu codons: 6 possible codons/80% are UUG
•
Repeated evolution of the same amino acid in hemoglobin subunits
of Andean ducks---all involve the same codon.
Possible explanations:
•
All involve selection.
•
Some tRNAs may be more abundant or efficient; bonding energy
may differ due to differences in base pairs.
•
Selection is expected to be more intense for genes expressed at
higher levels/organisms with short generation times.
•
Codon usage bias permits smaller number of tRNAs (e.g., Wobble
effect).
Variation in evolutionary rates:
Useful for evaluating differences in substitution frequency and action of
natural selection on a locus.
Three types of selection operate on genotypic variation:
Directional selection – natural selection favors one particular genotypic variant
or phenotype over others in one particular environment, causing the allele
frequency to shift.
Purifying selection – removal of deleterious alleles (e.g., elimination of most
non-synonymous substitutions)
Balancing selection – multiple alleles are selected for in the gene pool and
maintained at frequencies above the mutation rate (overdominance is a type
of balancing selection).
http://en.wikipedia.org/wiki/Directional_selection
Michael Bamshad & Stephen P. Wooding - Nature Reviews Genetics 4, 99-111 (February 2003)
Examples of balancing selection:
Light and dark-colored moths in the same population
Major histocompatibility complex (MHC)
•
Genes are important in immune response and are under selective
pressure to diversify (diversifying selection).
•
~90% of humans receive different MHC genes from each parent.
•
Sample of 200 humans will have 15-30 different alleles.
•
Important mechanism for outcrossing in humans.
•
Humans select mates on the basis of their MHC compatibility.
McDonald-Kreitman (1991) test:
•
Compare non-synonymous/synonymous ratios within species to
between species (KNS/KS).
•
If ratios differ, selection may be responsible.
•
KNS/KS typically differs by a factor of 2; but may vary 1,000-fold
between different types of genes.
•
Conservative test.
Rates of evolution in mtDNA and chloroplasts:
•
Organelle genomes (mtDNA, cpDNA) are distinct from nuclear
genomes and show increased rates of substitution.
•
~10X greater than nuclear genes.
•
Possible explanations:
•
Lack proofreading
•
Different DNA repair mechanisms
•
Higher levels of oxidative mutagens due to metabolism
•
Lower selective pressure; most cells contain several dozen
mitochondria.
•
Maternally inherited; smaller effective population size;
increased effects of genetic drift and selective sweeps on
mtDNA/cpDNA variants that are beneficial.
Molecular clocks (fig. 25.3):
•
Zuckerkandl and Pauling (1969): recognized that genes with similar
functions generally show uniform rates over long periods of time.
Molecular clocks (cont.):
•
Can be used to estimate divergence time.
•
“Clocks” tick differently in different proteins.
Relative rate test (Sarich and Wilson 1973):
•
Measure # substitutions between two taxa and an outgroup taxon
that shares a common ancestor.
•
doutgroup-1 > dooutgroup-2
taxon 1
outgroup
taxon 2
Causes of fast/slow molecular substitution rates (cont.):
•
Substitution rates are expected to be related to germ line
replication (or generation time).
•
Metabolic rate also is thought to be an important factor (correlates
with body size and generation time).
example: rodents are small, have a high metabolic rate, and have
short generation time/rodent rates are ~2x humans and apes.
•
In addition to variation between and among genes, rates vary
widely among taxonomic groups.
•
Other sources of variation:
•
DNA repair mechanisms/efficiency
•
Exposure to mutagens
•
Opportunities to adapt to new environments, may lead to
bursts of rapid evolution.
How to build trees - phylogenetic systematics-concepts/definitions:
Taxon
Monophyletic group of organisms recognizable by a set of shared
characters and sufficiently distinct from other such groups to be ranked
in a taxonomic category.
Category
Hierarchical level to which taxa are assigned in a classification (e.g.,
kingdom, phylum, class, order, etc.).
Monophyly
Descent from a common ancestor; every true taxon is monophyletic.
Polyphyly
Descent from more than one ancestral lineage.
Phylogenetic systematics-more concepts/definitions:
Homology
Shared similarity derived from common ancestry.
Homoplasy
Similarity derived from convergence, parallelism, or reversal.
Convergence
Independent acquisition of a similar character by two or more taxa
whose common ancestor lacked that character; generally refers to more
distantly related lineages. Ancestral lineages possessed different
character states.
Parallelism
Independent acquisition of the same or similar characters by more
closely related lineages (i.e., similar to convergence). Ancestral lineages
possessed the same character state.
Reversal
Reappearance of an ancestral character as the result of the loss of a
derived character.
Phylogenetic trees:
•
•
Branching patterns (trees) depict genealogical relationships
•
applies to pedigree analysis and systematics
•
Useful for molecular/non-molecular data
The 3-taxon example:
Fig. 25.5
Phylogenetic trees (cont.):
# of possible rooted trees
= (2n -3)!/(2n-2(n-2))!
# of possible unrooted trees
= (2n -5)!/(2n-3(n-3))!
# taxa
# rooted trees
3
3
4
15
5
105
6
945
7
10,395
8
135,135
9
2,027,025
10
34,459,425
Finding the “best” tree:
•
Long tradition of using characters (morphological and molecular).
•
Ernst Haeckel (1866)
•
1950-1960s
Numerical phenetics
•
Willi Hennig (1966)
Cladistics
Willi Hennig’s cladistic characters:
Synapomorphy: shared derived homologous characters
inferred to have been present in the nearest common ancestor
of two or more taxa, but not in earlier ancestors outside this
group (phylogenetically informative).
Symplesiomorphy: shared ancestral homologous characters
inferred to have been present in the nearest common ancestor
of two or more taxa, and in earlier ancestors outside this group
(phylogenetically non-informative).
Autapomorphy: unique derived character present in only one
of two sister groups (phylogenetically non-informative).
Tree reconstruction methods:
Genetic distance:
•
Create a matrix of genetic distances describing genetic distances
between all pairs of taxa.
•
Select tree that minimizes total genetic distance (distances can be
weight or unweighted).
Parsimony:
•
Minimize number of steps required to evolve shared derived
homologous characters (synapomorphies) on the tree (characters
may be weighted or unweighted).
•
Shortest tree is the best tree by principle of parsimony; i.e., the
explanation that requires the fewest assumptions is preferred to
other more complex explanations.
Maximum likelihood/Bayesian methods:
•
Similar character based approaches but use ‘statistical’ methods
such as maximum likelihood and attempts to model DNA evolution
as we know it (assuming different frequencies of nucleotides,
substitution rates, etc.).
Most parsimonious
taxon 1
taxon 2
outgroup
taxon 1
outgroup
Less parsimonious
taxon 2
Fig. 25.7, All possible trees depicting
nucleotide substitutions at six sites.
Fig. 25.8, Tree of life based
on 16s rRNA sequences
Fig. 25.2, mtDNA lineage relationships in pocket gophers.
Problems with tree reconstruction methods (cont.):
•
One or more (perhaps many) trees may best describe the data.
•
Equally parsimonious/likely trees may not be consistent (character
support can be assed in different ways; e.g., bootstrap resampling).
•
Gene trees and species trees: a gene tree does not necessarily
reflect the species tree.
•
Common ancestor or two gene lineages
can predate species split:
ancestral polymorphism.
•
Trees derived from different genes
or linkage groups may conflict.
Peters, McCracken, et al. (unpubl. data)
Hybridization
•
Gene flow between species or populations also may obscure the
species tree:
The other big problem:
•
Recombination complicates phylogenetic inference.
Speciation and species concepts: Allopatric model
•
If populations become subdivided, allele frequencies naturally
change over time and and populations diverge.
•
If or when populations reunite, they may fail to mate or produce
inviable offspring  allopatric speciation.
•
Or they might introgress and hybridize; the degree of speciation
depends on pre- and post-zygotic barriers:
Biological Species Concept
Systematics and the Origin of Species
Ernst Mayr (1942)
Allopatric Model
Peripatric Model
vicariance
Vicariance results in
subdivision and through
time leads to two
reproductively isolated
species clades evolving on
different trajectories .
Migration event followed by
peripheral isolation (founding
population persists; new
daughter species buds off).
Types of barriers to gene flow:
•
Spatial, temporal, and ecological isolation
•
Post-zygotic barriers
•
•
•
Hybrid sterility/inviability
•
Haldane’s rule: sterility and inviability occurs more often in
the heterogametic sex (e.g., because deleterious alleles are
exposed on the Y chromosome).
•
Hybrid breakdown: inviability occurs some generations later.
Pre-zygotic barriers
•
Behavioral incompatibility
•
Mechanical isolation (genitalia do not fit together)
•
Gametic isolation (gametes fail to fuse)
Reinforcement
•
Pre-zygotic barriers evolve to reinforce post-zygotic barriers
Speciation: Sympatric/Allochronic models
•
In some cases, speciation may be driven in the absence of
allopatry or peripheral isolation.
•
Speciation and reproductive isolation can correlate with ecological
preferences (sympatric) or timing instead of space (allochronic or
heteropatric speciation).
•
Examples of sympatric speciation are though to be driven primarily
by adaptation as opposed to vicariance associated with geography.
•
Several good examples of sympatric speciation documented:
Threespine stickleback
(Gasterosteus aculeatus)
http://fish.dnr.cornell.edu/nyfish/Gasterosteidae/sticklebackpic.html
Sticklebacks inhabit lakes and
streams in recently deglaciated
habitats, evolved from marine
ancestors.
Concluding remarks:
•
No sharp division between phylogenetic systematics and population
genetics.
•
Same forces that give rise to micro-evolutionary patterns we
observe are responsible for macro-evolutionary patterns that play
out over many generations.
•
Successful integrated analysis requires basic knowledge of
population genetics and phylogenetics.