SUMMARY Disease and disease triangle Pathogen Native vs

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SUMMARY • • Disease and disease triangle Pathogen Native vs. exotic diseases Type of

SUMMARY • • Disease and disease triangle Pathogen Native vs. exotic diseases Type of diseases Long term effect of disease Density dependence- Janzen Connol Gene for gene- Red queen hypothesis

Evolution and Population genetics • Positively selected genes: …… • Negatively selected genes…… •

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

Evolution and Population genetics • Positively selected genes: …… • Negatively selected genes…… •

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

Evolutionary history • Darwininan vertical evolutionray models • Horizontal, reticulated models. .

Evolutionary history • Darwininan vertical evolutionray models • Horizontal, reticulated models. .

Phylogenetic relationships within the Heterobasidion complex Fir-Spruce Pine Europe Pine N. Am.

Phylogenetic relationships within the Heterobasidion complex Fir-Spruce Pine Europe Pine N. Am.

Geneaology of “S” DNA insertion into P ISG confirms horizontal transfer. NA S Time

Geneaology of “S” DNA insertion into P ISG confirms horizontal transfer. NA S Time of “cross-over” uncertain NA P 890 bp CI>0. 9 EU S EU F

Because of complications such as: • Reticulation • Gene homogeneization…(Gene duplication) • Need to

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 (Ia=index of association)

How to get multiple loci? • Random genomic markers: – RAPDS – Total genome

How to get multiple loci? • Random genomic markers: – RAPDS – Total genome RFLPS (mostly dominant) – AFLPS • Microsatellites • SNPs • Multiple specific loci – SSCP – RFLP – Sequence informat 5 ion

Sequence information • Codominant • Molecules have different rates of mutation, different molecules may

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

Sequence information • Multiple genealogies=definitive phylogeny • Need to ensure gene histories are comparable”

Sequence information • Multiple genealogies=definitive phylogeny • Need to ensure gene histories are comparable” partition of homogeneity test • Need to use unlinked loci

HOST-SPECIFICITY • • • Biological species Reproductively isolated Measurable differential: size of structures Gene-for-gene

HOST-SPECIFICITY • • • Biological species Reproductively isolated Measurable differential: size of structures Gene-for-gene defense model Sympatric speciation: Heterobasidion, Armillaria, Sphaeropsis, Phellinus, Fusarium forma speciales

Phylogenetic relationships within the Heterobasidion complex Fir-Spruce Pine Europe Pine N. Am.

Phylogenetic relationships within the Heterobasidion complex Fir-Spruce Pine Europe Pine N. Am.

SEX • • Ability to recombine and adapt Definition of population and metapopulation Different

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

Recognition of self vs. non self • Intersterility genes: maintain species gene pool. Homogenic

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.

From the population level to the individual • Autoinfection vs. alloinfection • Primary spread=by

From the population level to the individual • Autoinfection vs. alloinfection • Primary spread=by spores • Secondary spread=vegetative, clonal spread, same genotype. Completely different scales Coriolus Heterobasidion Armillaria Phellinus

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

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

Root disease center in true fir caused by H. annosum

Root disease center in true fir caused by H. annosum

Ponderosa pine Incense cedar

Ponderosa pine Incense cedar

Yosemite Lodge 1975 Root disease centers outlined

Yosemite Lodge 1975 Root disease centers outlined

Yosemite Lodge 1997 Root disease centers outlined

Yosemite Lodge 1997 Root disease centers outlined

Are my haplotypes sensitive enough? • To validate power of tool used, one needs

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

RAPD combination 1 2 • 101010 • 1011101010 • 1010111010 • 101010 • 1010001010

RAPD combination 1 2 • 101010 • 1011101010 • 1010111010 • 101010 • 1010001010 • 101010 • 1010000000 • 1011001010 • 1011110101

Conclusions • Only one RAPD combo is sensitive enough to differentiate 4 half-sibs (in

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

Dealing with dominant anonymous multilocus markers • • Need to use large numbers Repeatability

Dealing with dominant anonymous multilocus markers • • Need to use large numbers Repeatability Graph distribution of distances Calculate distance using Jaccard’s similarity index

Jaccard’s • Only 1 -1 and 1 -0 count, 0 -0 do not count

Jaccard’s • Only 1 -1 and 1 -0 count, 0 -0 do not count 1010011 1001000

Jaccard’s • Only 1 -1 and 1 -0 count, 0 -0 do not count

Jaccard’s • Only 1 -1 and 1 -0 count, 0 -0 do not count A: 1010011 B: 1001011 C: 1001000 AB= 0. 6 BC=0. 5 AC=0. 2 0. 4 (1 -AB) 0. 5 0. 8

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

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

Now that we have distances…. • Plot their distribution (clonal vs. sexual) • Analysis:

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

Now that we have distances…. • Plot their distribution (clonal vs. sexual) • Analysis:

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

AMOVA groupings • Individual • Population • Region AMOVA: partitions molecular variance amongst a

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

Now that we have distances…. • Plot their distribution (clonal vs. sexual) • Analysis:

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 – Discriminant, canonical analysis

Now that we have distances…. • Plot their distribution (clonal vs. sexual) • Analysis:

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 – Discriminant, canonical analysis – Frequency: does allele frequency match expected (hardy weinberg), F or Wright’s statistsis

The “scale” of disease • Dispersal gradients dependent on propagule size, resilience, ability to

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)---

S-P ratio in stumps is highly dependent on distance from true fir and hemlock

S-P ratio in stumps is highly dependent on distance from true fir and hemlock stands. . San Diego

Have we sampled enough? • Resampling approaches • Saturation curves

Have we sampled enough? • Resampling approaches • Saturation curves

If we have codominant markers how many do I need • Probability calculation based

If we have codominant markers how many do I need • Probability calculation based on allele frequency.

White mangroves: Corioloposis caperata

White mangroves: Corioloposis caperata

Distances between study sites White mangroves: Corioloposis caperata

Distances between study sites White mangroves: Corioloposis caperata

Forest fragmentation can lead to loss of gene flow among previously contiguous populations. The

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 plantparasitic fungi. AFLP study on single spores Coriolopsis caperata on Laguncularia racemosa

From Garbelotto and Chapela, Evolution and biogeography of matsutakes Biodiversity within species as significant

From Garbelotto and Chapela, Evolution and biogeography of matsutakes Biodiversity within species as significant as between species

Using DNA sequences • Obtain sequence • Align sequences, number of parsimony informative sites

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

Using DNA sequences • • Testing alternative trees: kashino hasegawa Molecular clock Outgroup Spatial

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