The biology of the organism drives an epidemic

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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

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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

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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

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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.

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Somatic incompatibility
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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

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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

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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

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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

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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)

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INTERSTERILITY

• Basis for speciation
• These alleles are selected for more strongly in
  sympatry
• You can have different species in allopatry that
  have not been selected for different IS alleles

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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

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MATING

• If one individuals is source of inoculum, then
  the same 2 mating alleles will be found in local
  population
• If inoculum is of broad provenance then multiple
  mating alleles should be found

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MATING

• How do you test for mating?
• Place two homokaryons in same plate and check for
  formation of dikaryon (microscopic clamp
  connections at septa)

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Clamp connections
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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

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Two scenarios

• A, A, B, C, D, D, E, H, I, L

• A, A, A,B, B, A, A

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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
• Siblings as source of infection (1 genotype)

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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

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Long branches in between groups suggests no sex
is occurring in between groups
Fir-Spruce
Pine Europe
Pine N.Am.
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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
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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

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If SEX is not happening

• Number of genotypes less than that theorethically
  expected
• E.G. Three biallelic loci should give 8 genotypes

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Basic definitions again

• Locus
• Allele
• Dominant vs. codominant marker
• RAPDS
• AFLPs

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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!)

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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)

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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)

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RAPDS can also be obtained with Arbitrary Primed
PCR

• Use longer primers
• Use less stringent annealing conditions
• Less variability in results

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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
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WORK ON PINES HAD DEMONSTRATED INFECTIONS ARE
MOSTLY ON STUMPS

• Use meticulous field work and genetics
  information to reconstruct disease from infection
  to explosion
• On firs/sequoia if the stump theory were also
  correct we would find a stump within the outline
  of each genotype

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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

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RAPD combination1 2

• 1010101010
• 1010101010
• 1010101010
• 1010101010
• 1010000000

• 1011101010
• 1010111010
• 1010001010
• 1011001010
• 1011110101

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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

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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

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Do the data make sense, based on the known
biology?

• Fungus that disperses through basidiospores
• If we find the same genotype in different
  locations..
• Markers may not be sensitive enough

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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

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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
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Dealing with dominant anonymous multilocus markers

• Need to use large numbers (linkage)
• Repeatability
• Graph distribution of distances
• Calculate distance using Jaccards similarity
  index

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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
• Eliminate markers that are cosegregating
  (probable duplication, from same locus)

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Now that we have distances.

• Plot their distribution (clonal vs. sexual)

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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

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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

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AMOVA groupings

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

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Example

• SPECIES X 50blue, 50 yellow

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AMOVA example
Scenario 1
Scenario 2
v
POP 1
POP 2
v
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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

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Results Jaccard similarity coefficients
P. nemorosa
P. pseudosyringae U.S. and E.U.
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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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RAPDSgt not used often now
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RAPD DATA W/O COSEGREGATING MARKERS
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PCA
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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

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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

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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)