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The biology of the organism drives an epidemic

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The biology of the organism drives an epidemic Autoinfection vs. alloinfection Primary spread=by spores Secondary spread=vegetative, clonal spread, same genotype . – PowerPoint PPT presentation

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Title: The biology of the organism drives an epidemic


1
The biology of the organism drives an epidemic
  • Autoinfection vs. alloinfection
  • Primary spreadby spores
  • Secondary spreadvegetative, clonal spread, same
    genotype . Completely different scales (from
    small to gigantic)
  • Coriolus
  • Heterobasidion
  • Armillaria
  • Phellinus

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OUR ABILITY TO
  • Differentiate among different individuals
    (genotypes)
  • Determine gene flow among different areas
  • Determine allelic distribution in an area

4
WILL ALLOW US TO DETERMINE
  • How often primary infection occurs or is disease
    mostly chronic
  • How far can the pathogen move on its own
  • Is the organism reproducing sexually? is the
    source of infection local or does it need input
    from the outside

5
IN ORDER TO UNDERSTAND PATTERNS OF INFECTION
  • If John gave directly Mary an infection, and Mary
    gave it to Tom, they should all have the same
    strain, or GENOTYPE (comparisonsecondary spread
    among forest trees)
  • If the pathogen is airborne and sexually
    reproducing, Mary John and Tom will be infected
    by different genotypes. But if the source is the
    same, the genotypes will be sibs, thus related

6
Recognition of self vs. non self
  • Intersterility genes maintain species gene pool.
    Homogenic system
  • Mating genes recognition of other to allow for
    recombination. Heterogenic system
  • Somatic compatibility protection of the
    individual.

7
INTERSTERILITY
  • If a species has arisen, it must have some
    adaptive advantages that should not be watered
    down by mixing with other species
  • Will allow mating to happen only if individuals
    recognized as belonging to the same species
  • Plus alleles at one of 5 loci (S P V1 V2 V3)

8
MATING
  • Two haploids need to fuse to form nn
  • Sex needs to increase diversity need different
    alleles for mating to occur
  • Selection for equal representation of many
    different mating alleles

9
MATING ALLELES
  • All heterokaryons will have two mating allelels,
    for instance a, b
  • There is an advantage in having more mating
    alleles (easier mating, higher chances of finding
    a mate)
  • Mating allele that is rare, may be of migrant
    just arrived
  • If a parent is important source, genotypes should
    all be of one or two mating types

10
Two scenarios
  • A, A, B, C, D, D, E, H, I, L
  • A, A, A,B, B, A, A

11
Two scenarios
  • A, A, B, C, D, D, E, H, I, L
  • Multiple source of infections (at least 4
    genotypes)
  • A, A, A,B, B, A, A
  • Sible source of infection (1 genotype)

12
SEX
  • Ability to recombine and adapt
  • Definition of population and metapopulation
  • Different evolutionary model
  • Why sex? Clonal reproductive approach can be very
    effective among pathogens

13
Long branches in between groups suggests no sex
is occurring in between groups
Fir-Spruce
Pine Europe
Pine N.Am.
14
Small branches within a clade indicate sexual
reproduction is ongoing within that group of
individuals
NA S
NA P
EU S
890 bp CIgt0.9
EU F
15
Index of association
  • Ia if same alleles are associated too much as
    opposed to random, it means sex is not occurring
  • Association among alleles calculated and compared
    to simulated random distribution

16
SOMATIC COMPATIBILITY
  • Fungi are territorial for two reasons
  • Selfish
  • Do not want to become infected
  • If haploids it is a benefit to mate with other,
    but then the nn wants to keep all other
    genotypes out
  • Only if all alleles are the same there will be
    fusion of hyphae
  • If most alleles are the same, but not all, fusion
    only temporary

17
SOMATIC COMPATIBILITY
  • SC can be used to identify genotypes
  • SC is regulated by multiple loci
  • Individual that are compatible (recognize one
    another as self, are within the same SC group)
  • SC group is used as a proxy for genotype, but in
    reality, you may have some different genotypes
    that by chance fall in the same SC group
  • Happens often among sibs, but can happen by
    chance too among unrelated individuals

18
Recognition of self vs. non self
  • What are the chances two different individuals
    will have the same set of VC alleles?
  • Probability calculation (multiply frequency of
    each allele)
  • More powerful the larger the number of loci
  • and the larger the number of alleles per locus

19
Recognition of self vs. non selfprobability of
identity (PID)
  • 4 loci
  • 3 biallelelic
  • 1 penta-allelic
  • P 0.5x0.5x0.5x0.20.025
  • In humans 99.9, 1000, 1 in one million

20
Evolution and Population genetics
  • Positively selected genes
  • Negatively selected genes
  • Neutral genes normally population genetics
    demands loci used are neutral
  • Loci under balancing selection..

21
Evolution and Population genetics
  • Positively selected genes
  • Negatively selected genes
  • Neutral genes normally population genetics
    demands loci used are neutral
  • Loci under balancing selection..

22
Evolutionary history
  • Darwininan vertical evolutionary models
  • Horizontal, reticulated models..

23
Phylogenetic relationships within the
Heterobasidion complex
Fir-Spruce
Pine Europe
Pine N.Am.
24
Geneaology of S DNA insertion into P ISG
confirms horizontal transfer.Time of
cross-over uncertain
NA S
NA P
EU S
890 bp CIgt0.9
EU F
25
Because of complications such as
  • Reticulation
  • Gene homogeneization(Gene duplication)
  • Need to make inferences based on multiple genes
  • Multilocus analysis also makes it possible to
    differentiate between sex and lack of sex
    (Iaindex of association), and to identify
    genotypes, and to study gene flow

26
Basic definitions again
  • Locus
  • Allele
  • Dominant vs. codominant marker
  • RAPDS
  • AFLPs

27
How to get multiple loci?
  • Random genomic markers
  • RAPDS
  • Total genome RFLPS (mostly dominant)
  • AFLPS
  • Microsatellites
  • SNPs
  • Multiple specific loci
  • SSCP
  • RFLP
  • Sequence information
  • Watch out for linked alleles (basically you are
    looking at the same thing!)

28
Sequence information
  • Codominant
  • Molecules have different rates of mutation,
    different molecules may be more appropriate for
    different questions
  • 3rd base mutation
  • Intron vs. exon
  • Secondary tertiary structure limits
  • Homoplasy

29
Sequence information
  • Multiple gene genealogiesdefinitive phylogeny
  • Need to ensure gene histories are comparable
    partition of homogeneity test
  • Need to use unlinked loci

30
DNA template
Reverse primer
Forward primer
Thermalcycler
31
Gel electrophoresis to visualize PCR product
Ladder (to size DNA product)
32
From DNA to genetic information (alleles are
distinct DNA sequences)
  • Presence or absence of a specific PCR amplicon
    (size based/ specificity of primers)
  • Differerentiate through
  • Sequencing
  • Restriction endonuclease
  • Single strand conformation polymorphism

33
Presence absence of amplicon
  • AAAGGGTTTCCCNNNNNNNNN
  • CCCGGGTTTAAANNNNNNNNN

AAAGGGTTTCCC (primer)
34
Presence absence of amplicon
  • AAAGGGTTTCCCNNNNNNNNN
  • CCCGGGTTTAAANNNNNNNNN

AAAGGGTTTCCC (primer)
35
RAPDS use short primers but not too short
  • Need to scan the genome
  • Need to be readable
  • 10mers do the job (unfortunately annealing
    temperature is pretty low and a lot of priming
    errors cause variability in data)

36
RAPDS use short primers but not too short
  • Need to scan the genome
  • Need to be readable
  • 10mers do the job (unfortunately annealing
    temperature is pretty low and a lot of priming
    errors cause variability in data)

37
RAPDS can also be obtained with Arbitrary Primed
PCR
  • Use longer primers
  • Use less stringent annealing conditions
  • Less variability in results

38
Result series of bands that are present or
absent (1/0)
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Root disease center in true fir caused by H.
annosum
41
Ponderosa pine
Incense cedar
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Yosemite Lodge 1975 Root disease centers
outlined
43
Yosemite Lodge 1997 Root disease centers
outlined
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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

51
RAPD combination1 2
  • 1010101010
  • 1010101010
  • 1010101010
  • 1010101010
  • 1010000000
  • 1011101010
  • 1010111010
  • 1010001010
  • 1011001010
  • 1011110101

52
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

53
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

54
AFLP
  • Amplified Fragment Length Polymorphisms
  • Dominant marker
  • Scans the entire genome like RAPDs
  • More reliable because it uses longer PCR primers
    less likely to mismatch
  • Priming sites are a construct of the sequence in
    the organism and a piece of synthesized DNA

55
How are AFLPs generated?
  • AGGTCGCTAAAATTTT (restriction site in red)
  • AGGTCG CTAAATTT
  • Synthetic DNA piece ligated
  • NNNNNNNNNNNNNNCTAAATTTTT
  • Created a new PCR priming site
  • NNNNNNNNNNNNNNCTAAATTTTT
  • Every time two PCR priming sitea are within
    400-1600 bp you obtain amplification

56
Have we sampled enough?
  • Resampling approaches
  • Saturation curves
  • A total of 30 polymorphic alleles
  • Our sample is either 10 or 20
  • Calculate whether each new sample is
    characterized by new alleles

57
Saturation 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
58
Dealing with dominant anonymous multilocus markers
  • Need to use large numbers (linkage)
  • Repeatability
  • Graph distribution of distances
  • Calculate distance using Jaccards similarity
    index

59
Jaccards
  • Only 1-1 and 1-0 count, 0-0 do not count
  • 1010011
  • 1001011
  • 1001000

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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

61
Now that we have distances.
  • Plot their distribution (clonal vs. sexual)

62
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

63
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

64
AMOVA groupings
  • Individual
  • Population
  • Region
  • AMOVA partitions molecular variance amongst a
    priori defined groupings

65
Results Jaccard similarity coefficients
P. nemorosa
P. pseudosyringae U.S. and E.U.
66
P. pseudosyringae genetic similarity patterns are
different in U.S. and E.U.
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Results P. nemorosa
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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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Distances between study sites
White mangroves Corioloposis caperata
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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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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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Using DNA sequences
  • Testing alternative trees kashino hasegawa
  • Molecular clock
  • Outgroup
  • Spatial correlation (Mantel)
  • Networks and coalescence approaches

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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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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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