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Title: Quiz


1
Quiz
  • 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

2
Are 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

3
RAPD combination1 2
  • 1010101010
  • 1010101010
  • 1010101010
  • 1010101010
  • 1010000000
  • 1011101010
  • 1010111010
  • 1010001010
  • 1011001010
  • 1011110101

4
Conclusions
  • 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

5
If 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

6
Have 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

7
Saturation (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
8
Dealing with dominant anonymous multilocus markers
  • Need to use large numbers (linkage)
  • Repeatability
  • Graph distribution of distances
  • Calculate distance using Jaccards similarity
    index

9
Jaccards
  • Only 1-1 and 1-0 count, 0-0 do not count
  • 1010011
  • 1001011
  • 1001000

10
Jaccards
  • 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

11
Now that we have distances.
  • Plot their distribution (clonal vs. sexual)

12
Now that we have distances.
  • Plot their distribution (clonal vs. sexual)
  • Analysis
  • Similarity (cluster analysis) a variety of
    algorithms. Most common are NJ and UPGMA

13
Now 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

14
Results Jaccard similarity coefficients
P. nemorosa
P. pseudosyringae U.S. and E.U.
15
Results P. nemorosa
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17
AMOVA groupings
  • Individual
  • Population
  • Region
  • AMOVA partitions molecular variance amongst a
    priori defined groupings

18
Example
  • SPECIES X 50blue, 50 yellow

19
AMOVA example
Scenario 1
Scenario 2
v
POP 1
POP 2
v
20
Expectations 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

21
The 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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23
RAPDSgt not used often now
24
RAPD DATA W/O COSEGREGATING MARKERS
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26
Distances between study sites
White mangroves Corioloposis caperata
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29
Forest 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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32
Spatial 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
32
33
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

34
CASE STUDY
A stand of adjacent trees is infected by a
disease How can we determine the way trees are
infected?
35
CASE 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.
36
CASE 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?
37
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?

38
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

39
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.

40
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

41
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.

42
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

43
What is Population Genetics?
  • About microevolution (evolution of species)
  • The study of the change of allele frequencies,
    genotype frequencies, and phenotype frequencies

44
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
45
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

46
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

47
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

48
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.

49
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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51
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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53
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

54
Founder vs Bottleneck
55
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
56
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

57
Hardy-Weinberg Equilibrium
  • Null Model population is in HW Equilibrium
  • Useful
  • Often predicts genotype frequencies well

58
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)
59
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).

60
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
61
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
62
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

63
Pop 3
Pop 2
Pop 1
Pop 4
FST 0.30
FST 0.02
64
Pop1 Pop2 Pop3
Sample size 20 20 20
AA 10 5 0
Aa 4 10 8
aa 6 5 12
65
Pop1 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
66
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

67
F StatsProportions of Variance
  • FIS (HS HI)/(HS)
  • FST (HT HS)/(HT)
  • FIT (HT HI)/(HT)

68
Pop 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

69
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

70
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
71
Rhizopogon sampling study area
  • Santa Rosa, Santa Cruz
  • R. occidentalis
  • R. vulgaris
  • Overlapping ranges
  • Sympatric
  • Independent evolutionary histories

72
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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