Using DNA sequences

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Using DNA sequences

• Obtain sequence
• Align sequences, number of parsimony informative
  sites
• Gap handling
• Picking sequences (order)
• Analyze sequences (similarity/parsimony/exhaustive
  /bayesian
• Analyze output CI, HI Bootstrap/decay indices

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Good chromatogram!
Bad chromatogram
Reverse reaction suffers same problems in
opposite direction
Pull-up (too much signal)
Loss of fidelity leads to slips, skips and mixed
signals
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Alignments (Se-Al)
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Using DNA sequences

• Testing alternative trees kashino hasegawa
• Molecular clock
• Outgroup
• Spatial correlation (Mantel)
• Networks and coalescence approaches

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Using DNA sequences

• Bootstrap the presence of a branch separating
  two groups of microbial strains could be real or
  simply one of the possible ways we could
  visualize microbial populations. Bootstrap tests
  whether the branch is real. It does so by trying
  to see through iterations if a similar branch can
  come out by chance for a given dataset
• BS value over 65 ok over 80 good, under 60 bad

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From Garbelotto and Chapela, Evolution and
biogeography of matsutakes
Biodiversity within species as significant as
between species
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Genetic analysis requires variation at loci,
variation of markers (polymorphisms)

• How the variation is structured will tell us
• Does the microbe reproduce sexually or clonally
• Is infection primary or secondary
• Is contagion caused by local infectious spreaders
  or by a long-disance moving spreaders
• How far can individuals move how large are
  populations
• Is there inbreeding or are individuals freely
  outcrossing

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CASE STUDY

• A grou

A stand of adjacent trees is infected by a
disease How can we determine the way trees are
infected?
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CASE STUDY

• A grou

A stand of adjacent trees is infected by a
disease How can we determine the way trees are
infected? BY ANALYSING THE GENOTYPE OF THE
MICROBES if the genotype is the same then we
have local secondary tree-to-tree contagion. If
all genotypes are different then primary
infection caused by airborne spores is the
likely cause of Contagion.
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CASE STUDY

• A grou

WE HAVE DETERMINED AIRBORNE SPORES (PRIMARY
INFECTION ) IS THE MOST COMMON FORM OF
INFECTION QUESTION Are the infectious spores
produced by a local spreader, or is there a
general airborne population of spores that may
come from far away ? HOW CAN WE ANSWER THIS
QUESTION?
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If spores are produced by a local spreader..

• Even if each tree is infected by different
  genotypes (each representing the result of
  meiosis like us here in this class).these
  genotypes will be related
• HOW CAN WE DETERMINE IF THEY ARE RELATED?

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HOW CAN WE DETERMINE IF THEY ARE RELATED?

• By using random genetic markers we find out the
  genetic similarity among these genotypes
  infecting adjacent trees is high
• If all spores are generated by one individual
• They should have the same mitochondrial genome
• They should have one of two mating alleles

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WE DETERMINE INFECTIOUS SPORES ARE NOT RELATED

• QUESTION HOW FAR ARE THEY COMING FROM? .or
• HOW LARGE IS A POPULATION?
• Very important question if we decide we want to
  wipe out an infectious disease we need to wipe
  out at least the areas corresponding to the
  population size, otherwise we will achieve no
  result.

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HOW TO DETERMINE WHETHER DIFFERENT SITES BELONG
TO THE SAME POP OR NOT?

• Sample the sites and run the genetic markers
• If sites are very different
• All individuals from each site will be in their
  own exclusive clade, if two sites are in the same
  clade maybe those two populations actually are
  linked (within reach)
• In AMOVA analysis, amount of genetic variance
  among populations will be significant (if
  organism is sexual portion of variance among
  individuals will also be significant)
• F statistics Fst will be over ) 0.10 (suggesting
  sttong structuring)
• There will be isolation by distance

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Levels of Analyses

• Individual
• identifying parents offspring very important
  in zoological circles identify patterns of
  mating between individuals (polyandry, etc.)
• In fungi, it is important to identify the
  "individual" -- determining clonal individuals
  from unique individuals that resulted from a
  single mating event.

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Levels of Analyses cont

• Families looking at relatedness within colonies
  (ants, bees, etc.)
• Population level of variation within a
  population.
• Dispersal indirectly estimate by calculating
  migration
• Conservation Management looking for founder
  effects (little allelic variation), bottlenecks
  (reduction in population size leads to little
  allelic variation)
• Species variation among species what are the
  relationship between species.
• Family, Order, ETC. higher level phylogenies

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What is Population Genetics?

• About microevolution (evolution of species)
• The study of the change of allele frequencies,
  genotype frequencies, and phenotype frequencies

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Goals of population genetics
Natural selection (adaptation) Chance (random
events) Mutations Climatic changes
(population expansions and contractions) To
provide an explanatory framework to describe the
evolution of species, organisms, and their
genome, due to Assumes that the same
evolutionary forces acting within
species (populations) should enable us to explain
the differences we see between species
evolution leads to change in gene frequencies
within populations
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Pathogen Population Genetics

• must constantly adapt to changing environmental
  conditions to survive
• High genetic diversity easily adapted
• Low genetic diversity difficult to adapt to
  changing environmental conditions
• important for determining evolutionary potential
  of a pathogen
• If we are to control a disease, must target a
  population rather than individual
• Exhibit a diverse array of reproductive
  strategies that impact population biology

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Analytical Techniques

• Hardy-Weinberg Equilibrium
• p2 2pq q2 1
• Departures from non-random mating
• F-Statistics
• measures of genetic differentiation in
  populations
• Genetic Distances degree of similarity between
  OTUs
• Neis
• Reynolds
• Jaccards
• Cavalli-Sforza
• Tree Algorithms visualization of similarity
• UPGMA
• Neighbor Joining

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Allele Frequencies

• Allele frequencies (gene frequencies)
  proportion of all alleles in an all individuals
  in the group in question which are a particular
  type
• Allele frequencies
• p q 1
• Expected genotype frequencies
• p2 2pq q2

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Evolutionary principles Factors causing changes
in genotype frequency

• Selection variation in fitness heritable
• Mutation change in DNA of genes
• Migration movement of genes across populations
• Vectors Pollen, Spores
• Recombination exchange of gene segments
• Non-random Mating mating between neighbors
  rather than by chance
• Random Genetic Drift if populations are small
  enough, by chance, sampling will result in a
  different allele frequency from one generation to
  the next.

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The smaller the sample, the greater the chance of
deviation from an ideal population. Genetic
drift at small population sizes often occurs as a
result of two situations the bottleneck effect
or the founder effect.
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Founder Effects typical of exotic diseases

• Establishment of a population by a few
  individuals can profoundly affect genetic
  variation
• Consequences of Founder effects
• Fewer alleles
• Fixed alleles
• Modified allele frequencies compared to source
  pop
• GREATER THAN EXPECTED DIFFERENCES AMONG
  POPULATIONS BECAUSE POPULATIONS NOT IN
  EQUILIBRIUM (IF A BLONDE FOUNDS TOWN A AND A
  BRUNETTE FOUND TOWN B ANDF THERE IS NO MOVEMENT
  BETWEEN TOWNS, WE WILL ISTANTANEOUSLY OBSERVE
  POPULATION DIFFERENTIATION)

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Bottleneck Effect

• The bottleneck effect occurs when the numbers of
  individuals in a larger population are
  drastically reduced
• By chance, some alleles may be overrepresented
  and others underrepresented among the survivors
• Some alleles may be eliminated altogether
• Genetic drift will continue to impact the gene
  pool until the population is large enough

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Founder vs Bottleneck
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Northern Elephant Seal Example of Bottleneck
Hunted down to 20 individuals in
1890s Population has recovered to over
30,000 No genetic diversity at 20 loci
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Hardy Weinberg Equilibriumand F-Stats

• In general, requires co-dominant marker system
• Codominant expression of heterozygote
  phenotypes that differ from either homozygote
  phenotype.
• AA, Aa, aa

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Hardy-Weinberg Equilibrium

• Null Model population is in HW Equilibrium
• Useful
• Often predicts genotype frequencies well

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Hardy-Weinberg Theorem
if only random mating occurs, then allele
frequencies remain unchanged over time. After one
generation of random-mating, genotype frequencies
are given by AA Aa aa p2 2pq q2 p freq
(A) q freq (a)
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Expected Genotype Frequencies

• The possible range for an allele frequency or
  genotype frequency therefore lies between ( 0
  1)
• with 0 meaning complete absence of that allele
  or genotype from the population (no individual in
  the population carries that allele or genotype)
• 1 means complete fixation of the allele or
  genotype (fixation means that every individual in
  the population is homozygous for the allele --
  i.e., has the same genotype at that locus).

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ASSUMPTIONS
1) diploid organism 2) sexual reproduction 3)
Discrete generations (no overlap) 4) mating
occurs at random 5) large population size
(infinite) 6) No migration (closed population) 7)
Mutations can be ignored 8) No selection on
alleles
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IMPORTANCE OF HW THEOREM
If the only force acting on the population is
random mating, allele frequencies remain
unchanged and genotypic frequencies are
constant. Mendelian genetics implies that
genetic variability can persist indefinitely,
unless other evolutionary forces act to remove it
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Departures from HW Equilibrium

• Check Gene Diversity Heterozygosity
• If high gene diversity different genetic
  sources due to high levels of migration
• Inbreeding - mating system leaky or breaks down
  allowing mating between siblings
• Asexual reproduction check for clones
• Risk of over emphasizing particular individuals
• Restricted dispersal local differentiation
  leads to non-random mating

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Pop 3
Pop 2
Pop 1
Pop 4
FST 0.30
FST 0.02
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Local Inbreeding Coefficient

• Calculate HOBS
• Pop1 4/20 0.20
• Pop2 10/20 0.50
• Pop3 8/20 0.40
• Calculate HEXP (2pq)
• Pop1 20.600.40 0.48
• Pop2 20.500.50 0.50
• Pop3 20.200.80 0.32
• Calculate F (HEXP HOBS)/ HEXP
• Pop1 (0.48 0.20)/(0.48) 0.583
• Pop2 (0.50 0.50)/(0.50) 0.000
• Pop3 (0.32 0.40)/(0.32) -0.250

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F StatsProportions of Variance

• FIS (HS HI)/(HS)
• FST (HT HS)/(HT)
• FIT (HT HI)/(HT)

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Important point

• Fst values are significant or not depending on
  the organism you are studying or reading about
• Fst 0.10 would be outrageous for humans, for
  fungi means modest substructuring

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Microsatellites or SSRs

• AGTTTCATGCGTAGGT CG CG CG CG CG
  AAAATTTTAGGTAAATTT
• Number of CG is variable
• Design primers on FLANKING region, amplify DNA
• Electrophoresis on gel, or capillary
• Size the allele (different by one or more
  repeats if number does not match there may be
  polimorphisms in flanking region)
• Stepwise mutational process (2 to 3 to 4 to 3 to2
  repeats)

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Host islands within the California Northern
Channel Islands create fine-scale genetic
structure in two sympatric species of the
symbiotic ectomycorrhizal fungus Rhizopogon
Rhizopogon occidentalis
Rhizopogon vulgaris
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Rhizopogon sampling study area

• Santa Rosa, Santa Cruz
• R. occidentalis
• R. vulgaris
• Overlapping ranges
• Sympatric
• Independent evolutionary histories

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Sampling
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Bioassay Mycorrhizal pine roots
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Local Scale Population StructureRhizopogon
occidentalis
FST 0.26
8-19 km
N
E
FST 0.33
5 km
FST 0.24
W
B
T
FST 0.17
Populations are different
Populations are similar
Grubisha LC, Bergemann SE, Bruns TD Molecular
Ecology in press.
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Local Scale Population StructureRhizopogon
vulgaris
FST 0.21
N
E
FST 0.25
FST 0.20
W
Populations are different
Grubisha LC, Bergemann SE, Bruns TD Molecular
Ecology in press
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How do we know that we are sampling a population?

• We actually do not know
• Mostly we tend to identify samples from a
  discrete location as a population, obviously
  thats tautological
• Assignment tests will use the data to define
  population, that is what Grubisha et al. did
  using the program STRUCTURE

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Four phases of INVASION

• TRANSPORT
• SURVIVAL AND ESTABLISHMENT (LAG PHASE)
• INVASION
• POST-INVASION

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TRANSPORT

• Biology will determine how
• Normally very few organisms will make it
• Use phylogeographic approach to determine origin
  ( Armillaria, Heterobasidion)
• Use population genetic approach (Cryphonectria,
  Certocystis fimbriata)

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TRANSPORT-2

• Need to sample source pop or a pop that is close
  enough
• Need markers that are polymorphic and will
  differentiate genotypes haplotypes
• Need analysis that will discriminate amongst
  individuals and identify relationships (
  similarity clusterying, parsimony, Fst N,
  coalescent)

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ESTABLISHMENT

• LAG PHASE normally effects not noticed because
  mortality are masked by background normal
  mortality
• By the time the introduction is discovered,
  normally too late to eradicate
• Short lag phase aggressive pathogen
• Long lag phase less aggressive pathogen

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ESTABLISHMENT

• NORMALLY REDUCED GENETIC VARIABILITY

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INVASION

• Because of lack of equilibrium, high Fst values,
  I.e. strong genetic structuring among populations
• Normally dominance of a few genotypes
• Spatial autocorrelation analyses to tell us exten
  of spread

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INVASION-2

• Later phase genetic differentiation
• Higher genetic difference in areas of older
  establishment