Title: Quiz
1Quiz
- What were the two most significant consequences
of geographic isolation of some mangrove stand in
Panama? - In the Hogberg et al paper on Fomitopsis what
were the two most significant findings? - -------
- Why is there a Somatic Compatibility system in
fungi and whay it is a good proxy for genotyping? - Why do we talk of balancing selection with
regards to mating alleles and how would you use
mating allele analysis to prove the relatedness
of fungal genotypes
2Are my haplotypes sensitive enough?
- To validate power of tool used, one needs to be
able to differentiate among closely related
individual - Generate progeny
- Make sure each meiospore has different haplotype
- Calculate P
3RAPD combination1 2
- 1010101010
- 1010101010
- 1010101010
- 1010101010
- 1010000000
- 1011101010
- 1010111010
- 1010001010
- 1011001010
- 1011110101
4Conclusions
- Only one RAPD combo is sensitive enough to
differentiate 4 half-sibs (in white) - Mendelian inheritance?
- By analysis of all haplotypes it is apparent that
two markers are always cosegregating, one of the
two should be removed
5If we have codominant markers how many do I need
- IDENTITY tests probability calculation based
on allele frequency Multiplication of
frequencies of alleles - 10 alleles at locus 1 P10.1
- 5 alleles at locus 2 P20,2
- Total P P1P20.02
6Have we sampled enough?
- Resampling approaches
- Raraefaction curves
- A total of 30 polymorphic alleles
- Our sample is either 10 or 20
- Calculate whether each new sample is
characterized by new alleles
7Saturation (rarefaction) curves
No Of New alleles
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
8Dealing with dominant anonymous multilocus markers
- Need to use large numbers (linkage)
- Repeatability
- Graph distribution of distances
- Calculate distance using Jaccards similarity
index
9Jaccards
- Only 1-1 and 1-0 count, 0-0 do not count
- 1010011
- 1001011
- 1001000
10Jaccards
- Only 1-1 and 1-0 count, 0-0 do not count
- A 1010011 AB 0.6 0.4 (1-AB)
- B 1001011 BC0.5 0.5
- C 1001000 AC0.2 0.8
11Now that we have distances.
- Plot their distribution (clonal vs. sexual)
12Now that we have distances.
- Plot their distribution (clonal vs. sexual)
- Analysis
- Similarity (cluster analysis) a variety of
algorithms. Most common are NJ and UPGMA
13Now that we have distances.
- Plot their distribution (clonal vs. sexual)
- Analysis
- Similarity (cluster analysis) a variety of
algorithms. Most common are NJ and UPGMA - AMOVA requires a priori grouping
14Results Jaccard similarity coefficients
P. nemorosa
P. pseudosyringae U.S. and E.U.
15Results P. nemorosa
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17AMOVA groupings
- Individual
- Population
- Region
- AMOVA partitions molecular variance amongst a
priori defined groupings
18Example
- SPECIES X 50blue, 50 yellow
19AMOVA example
Scenario 1
Scenario 2
v
POP 1
POP 2
v
20Expectations for fungi
- Sexually reproducing fungi characterized by high
percentage of variance explained by individual
populations - Amount of variance between populations and
regions will depend on ability of organism to
move, availability of host, and - NOTE if genotypes are not sensitive enough so
you are calling the same things that are
different you may get unreliable results like 100
variance within pops, none among pops
21The scale of disease
- Dispersal gradients dependent on propagule size,
resilience, ability to dessicate, NOTE not
linear - Important interaction with environment, habitat,
and niche availability. Examples Heterobasidion
in Western Alps, Matsutake mushrooms that offer
example of habitat tracking - Scale of dispersal (implicitely correlated to
metapopulation structure)---
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23RAPDSgt not used often now
24RAPD DATA W/O COSEGREGATING MARKERS
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26Distances between study sites
White mangroves Corioloposis caperata
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29Forest fragmentation can lead to loss of gene
flow among previously contiguous populations.
The negative repercussions of such genetic
isolation should most severely affect highly
specialized organisms such as some
plant-parasitic fungi.
AFLP study on single spores
Coriolopsis caperata on Laguncularia racemosa
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32Spatial autocorrelation
Morans I (coefficient of departure from spatial
randomness) correlates with distance up to
Distribution of genotypes (6 microsatellite
markers) in different populations of P.ramorum
in California
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33Genetic 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
34CASE STUDY
A stand of adjacent trees is infected by a
disease How can we determine the way trees are
infected?
35CASE STUDY
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.
36CASE STUDY
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?
37If 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?
38HOW 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
39WE 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.
40HOW 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
41Levels 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.
42Levels 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
43What is Population Genetics?
- About microevolution (evolution of species)
- The study of the change of allele frequencies,
genotype frequencies, and phenotype frequencies
44Goals 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
45Pathogen 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
46Analytical 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
47Allele 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
48Evolutionary 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.
49The 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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51Founder 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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53Bottleneck 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
54Founder vs Bottleneck
55Northern 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
56Hardy 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
57Hardy-Weinberg Equilibrium
- Null Model population is in HW Equilibrium
- Useful
- Often predicts genotype frequencies well
58Hardy-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)
59Expected 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).
60ASSUMPTIONS
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
61IMPORTANCE 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
62Departures 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
63Pop 3
Pop 2
Pop 1
Pop 4
FST 0.30
FST 0.02
64Pop1 Pop2 Pop3
Sample size 20 20 20
AA 10 5 0
Aa 4 10 8
aa 6 5 12
65Pop1 Pop2 Pop3
Freq
p (20 1/28)/40 0.60 (101/220)/40 .50 (01/216)/40 0.20
q (12 1/28)/40 0.40 (101/220)/40 .50 (241/216)/40 0.80
66Local 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
67F StatsProportions of Variance
- FIS (HS HI)/(HS)
- FST (HT HS)/(HT)
- FIT (HT HI)/(HT)
68Pop Hs HI p q HT FIS FST FIT
1 0.48 0.20 0.60 0.40
2 0.50 0.50 0.50 0.50
3 0.32 0.40 0.20 0.80
Mean 0.43 0.37 0.43 0.57 0.49 -0.14 0.12 0.24
69Important 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
70Host 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
71Rhizopogon sampling study area
- Santa Rosa, Santa Cruz
- R. occidentalis
- R. vulgaris
- Overlapping ranges
- Sympatric
- Independent evolutionary histories
72Local 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.