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Summary of last lesson • Excellent review of techniques for pop gen • Methods of analysis • Previous lesson: density dependence/janzen connel/red queen hypothesis/type of markers • humnogous fungus • Testing the marker/testing sample size Frequency-, or density dependent, or balancing selection • New alleles, if beneficial because linked to a trait linked to fitness will be positively selected for. – Example: two races of pathogen are present, but only one resistant host variety, suggests second pathogen race has arrived recently • Rapid generation time of pathogens. Reticulated evolution very likely. Pathogens will be selected for INCREASED virulence • In the short/medium term with long lived trees a pathogen is likely to increase its virulence • In long term, selection pressure should result in widespread resistance among the host Overview Armillaria bulbosa (gallica) • Known as the Humungous Fungus, or honey mushroom • Form rhizomorphs, which make up much of the “humungous” part • Basidiocarp: cap 6 cm in diameter, stem is 5-10 cm tall • Facultative tree root pathogen Life cycle: Reproduction • Sexual – Basidiocarps release spores (n) after karyogamy and meiosis – 2 mating-type loci, each with multiple alleles in the population – Isolates (n) must have different alleles at two mating type loci to be sexually compatible • Asexual – vegetative spreading of rhizomorph • The large mass of rhizomorph that is genetically isolated is called a clone Building up the question… • “By extending the areas sampled in subsequent years, we were finally able to delimit the large area occupied by this genotype and then go on to show that this genotype likely represents and ‘individual’” - Myron Smith Researcher’s Question • The clonal “individual” is especially difficult to define because the network of hyphae is underground • How do you unambiguously identify an individual fungi within a local population? Approach 1. Collect samples 2. Check mating type - Somatic compatibility test - Distrubution of mating-type alleles 3. Molecular testing - RFLP - RAPD 4. Statistics 5. More testing Methods and Materials 1 1. Collecting samples • Researcher collected samples over a 30 hectare area by baiting Armillaria with poplar stakes and taking tissues and spores • They then grew the successfully colonized stakes in soil taken from the study site • Each fungal colony cultured was called an isolate. Methods and Materials 2 Example (not Armillaria) 2. Checking mating type - Somatic incompatibility For two fungal isolates to fuse, all somatic compatibility loci must be the same. Fusion means they’re clones Methods and Materials 2 • 2. Checking mating type - Distrubution of mating alleles - Mating occurs only when coupled isolates have different alleles at two unlinked, multiallelic loci: A and B. (They have an incompatibility system) - If fruit bodies had the same alleles at A and B, and were collected from the same area, they were assumed to be from the same clone Result 1 • Somatic compatilbilty: – isolates from vegetative mycelium from a large sampling area fused • Mating alleles – They had the same mating type Result 1 • “Clone 1” was found to exceed 500 m in diameter – Used previously collected mtDNA restriction fragment patterns Sensitivity of Approach • Problem: These tests alone are not enough to distinguish a clone from closely related individuals Why? • Q: The first two tests were not sensitive enough to tell a clone from a close relative…Why? • A: Spores from same point source have the same mating-type alleles, but the offspring they produce after inbreeding are genetically distinct. Methods and Materials 3 3. Molecular Testing - RFLP analysis at 5 polymorphic, heterozyg. loci of mtDNA from “Clone 1” - RAPD analysis at 11 loci RAPDS vs. RFLPs • Use 1 short PCR primer • When it finds match on template at a distance that can be amplified (primer binds twice within 50 to 2000 bp) RAPD amplicon • Dominant, annoymous • Total genomic, vs single locus • Use endonuclease to digest DNA at specific restriction site • Run digest and see how amplicon was cut • Single locus is codominant • RFLP Result 2 – All 5 loci from Clone 1 were heterozygous and identical (both alleles present at loci: 1,1) • RAPD – All 11 RAPD products were present in all vegetative isolates” Statistical Analysis • The probability of retaining heterozygosity at each parental locus in an individual produced by mating of sibling monospore isolates… = 0.0013 • So they were pretty confident that cloning was responsible for their results, not inbreeding More testing, just in case • To be completely confident, they tested: – 1) that nearby Clone 2 was different and lacked 5 of the Clone 1 heterozyg. RAPD fragments, – 2) more loci, totaling • 20 RAPD fragments • 27 nuclear DNA RFLP fragments ** all were identical in Clone 1 Sensitivity of RAPDs • Tested on subset of spores from same basidiocarp • RAPDs differentiated among full sibs Conclusions • Somatic compatibility, mating allele loci, mtDNA, RFLP, and RAPD tests all indicate that a single organism could indeed occupy a 15 hectare area Conclusions • The larger individual, Clone 1 was estimated to weigh 9700 kg and be over 1500 years old Implications • ????? • Fungi are one of the oldest and largest organisms on the planet • Recycle nutrients…very important! • Armillaria bulbosa also a pathogen; its effects on forest above may be huge as well. 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 NJ Phylogenetic relationships within the Heterobasidion complex Het INSULARE Fir-Spruce True Fir EUROPE Spruce EUROPE True Fir NAMERICA Pine Europe Pine EUROPE Pine N.Am. Pine NAMERICA 0.05 substitutions/site The biology of the organism drives an epidemic • Autoinfection vs. alloinfection • Primary spread=by spores • Secondary spread=vegetative, clonal spread, same genotype . Completely different scales (from small to gigantic) Coriolus Heterobasidion Armillaria Phellinus OUR ABILITY TO: • Differentiate among different individuals (genotypes) • Determine gene flow among different areas • Determine allelic distribution in an area 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 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 (comparison=secondary 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 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. 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 Recognition of self vs. non self • It is possible to have different genotypes with the same vc alleles • VC grouping and genotyping is not the same • It allows for genotyping without genetic tests • Reasons behing VC system: protection of resources/avoidance of viral contagion Somatic incompatibility Quic kTime™ and a TIFF (Unc ompres sed) decompress or are needed to see this picture. Quic kTime™ and a TIFF (Unc ompres sed) decompress or are needed to see this picture. More on somatic compatibility • Perform calculation on power of approach • Temporary compatibility allows for cytoplasmic contact that then is interrupted: this temporary contact may be enough for viral contagion 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 n+n 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 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 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 Recognition of self vs. non self: probability of identity (PID) • 4 loci • 3 biallelelic • 1 penta-allelic • P= 0.5x0.5x0.5x0.2=0.025 • In humans 99.9%, 1000, 1 in one million 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) 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 MATING • Two haploids need to fuse to form n+n • Sex needs to increase diversity: need different alleles for mating to occur • Selection for equal representation of many different mating alleles 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 MATING • How do you test for mating? • Place two homokaryons in same plate and check for formation of dikaryon (microscopic clamp connections at septa) Clamp connections QuickTi me™ and a TIFF ( Uncompressed) decompr essor are needed to see thi s p icture. QuickTi me™ and a T IFF (Uncom pressed) decom pressor are needed to see t his pict ure. QuickTime™ and a TIFF (U ncompressed) decompressor are needed to see t his picture. 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 Two scenarios: • A, A, B, C, D, D, E, H, I, L • A, A, A,B, B, A, A Two scenarios: • A, A, B, C, D, D, E, H, I, L • A, A, A,B, B, A, A • Multiple source of infections (at least 4 genotypes) • Siblings as source of infection (1 genotype) 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 Long branches in between groups suggests no sex is occurring in between groups NJ Het INSULARE Fir-Spruce True Fir EUROPE Spruce EUROPE True Fir NAMERICA Pine Europe Pine EUROPE Pine N.Am. Pine NAMERICA 0.05 substitutions/site NJ 11.10 SISG CA 2.42 SISG CA Small branches within a clade indicate sexual reproduction is ongoing within that group of individuals BBd SISG WA F2 SISG MEX NA S BBg SISG WA 14a2y SISG CA 15a5y M6 SISG CA 6.11 SISG CA 9.4 SISG CA AWR400 SPISG CA 9b4y SISG CA 15a1x M6 PISG CA 1M PISG MEX 9b2x PISG CA A152R FISG EU A62R SISG EU A90R SISG EU 890 bp CI>0.9 EU S A93R SISG EU J113 FISG EU J14 SISG EU J27 SISG EU J29 SISG EU 0.0005 substitutions/site EU F NA P 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 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…… • Neutral genes: normally population genetics demands loci used are neutral • Loci under balancing selection….. Evolutionary history • Darwininan vertical evolutionary models • Horizontal, reticulated models.. NJ Phylogenetic relationships within the Heterobasidion complex Het INSULARE Fir-Spruce True Fir EUROPE Spruce EUROPE True Fir NAMERICA Pine Europe Pine EUROPE Pine N.Am. Pine NAMERICA 0.05 substitutions/site NJ 11.10 SISG CA Geneaology of “S” DNA insertion into P ISG confirms horizontal transfer. 2.42 SISG CA BBd SISG WA F2 SISG MEX Time of “cross-over” uncertain NA S BBg SISG WA 14a2y SISG CA 15a5y M6 SISG CA 6.11 SISG CA 9.4 SISG CA AWR400 SPISG CA 9b4y SISG CA 15a1x M6 PISG CA 1M PISG MEX 9b2x PISG CA A152R FISG EU A62R SISG EU 890 bp CI>0.9 A90R SISG EU EU S A93R SISG EU J113 FISG EU J14 SISG EU J27 SISG EU J29 SISG EU 0.0005 substitutions/site EU F NA P 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), and to identify genotypes, and to study gene flow Basic definitions again • Locus • Allele • Dominant vs. codominant marker – RAPDS – AFLPs 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!) 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) 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) RAPDS can also be obtained with Arbitrary Primed PCR • Use longer primers • Use less stringent annealing conditions • Less variability in results Result: series of bands that are present or absent (1/0) Root disease center in true fir caused by H. annosum Ponderosa pine Incense cedar Yosemite Lodge 1975 Root disease centers outlined Yosemite Lodge 1997 Root disease centers outlined 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 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 RAPD combination 1 2 • 1010101010 • 1011101010 • 1010101010 • 1010111010 • 1010101010 • 1010001010 • 1010101010 • 1010000000 • 1011001010 • 1011110101 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 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 P1=0.1 • 5 alleles at locus 2 P2=0,2 • Total P= P1*P2=0.02 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 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 Dealing with dominant anonymous multilocus markers • • • • Need to use large numbers (linkage) 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 1010011 1001011 1001000 Jaccard’s • Only 1-1 and 1-0 count, 0-0 do not count A: 1010011 AB= 0.6 B: 1001011 BC=0.5 C: 1001000 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) • 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: – 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 priori defined groupings Example • SPECIES X: 50%blue, 50% yellow AMOVA: example Scenario 1 v v Scenario 2 POP 1 POP 2 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 Results: Jaccard similarity coefficients Frequency P. nemorosa 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0.90 0.92 0.94 0.96 Coefficient 1.00 0.98 Frequency P. pseudosyringae: U.S. and E.U. 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0.90 0.92 0.94 0.96 Coefficient 0.98 1.00 P. pseudosyringae genetic similarity patterns are different in U.S. and E.U. 0.7 Frequency 0.6 0.5 Pp U.S. 0.4 Pp E.U. 0.3 0.2 0.1 0.0 0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 Jaccard coefficient of similarity 0.98 0.99 Results: P. nemorosa 4175A p72 p39 p91 1050 P. ilicis P. pseudosyringae p7 2502 p51 2055.2 2146.1 5104 4083.1 2512 2510 2501 2500 2204 2201 2162.1 2155.3 2140.2 2140.1 2134.1 2059.2 2052.2 HCT4 MWT5 p114 p113 p61 p59 p52 p44 p38 p37 p13 p16 2059.4 p115 2156.1 HCT7 p106 0.1 P. nemorosa Results: P. pseudosyringae P. ilicis P. nemorosa 4175A 2055.2 p44 = E.U. isolate 0.1 FC2D FC2E GEROR4 FC1B FCHHD FCHHC FC1A p80 FAGGIO 2 FAGGIO 1 FCHHB FCHHA FC2F FC2C FC1F FC1D FC1C p83 p40 BU9715 p50 p94 p92 p88 p90 p56B p45 p41 p72 p84 p85 p86 p87 p93 p96 p39 p118 p97 p81 p76 p73 p70 p69 p62 p55 p54 HELA2 HELA 1 P. pseudosyringae 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)--- QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. RAPDS> not used often now QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. RAPD DATA W/O COSEGREGATING MARKERS QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. PCA QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. 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 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 4001600 bp you obtain amplification Coco Solo Mananti Ponsok David Coco Solo 0 237 273 307 Mananti Ponsok David 0 60 89 0 113 0 Distances between study sites White mangroves: Corioloposis caperata 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 Site # of isolates # of loci % fixed alleles Coco Solo 11 113 2.6 David 14 104 3.7 Bocas 18 92 15.04 Coco Solo Coco Solo Bocas David 0.000 0.000 0.000 Bocas 0.2083 0.000 0.000 David 0.1109 0.2533 0.000 Distances =PhiST between pairs of populations. Above diagonal is the Probability Random d istance > Observed distance (1000 iterations). 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 correlation (Mantel) • Networks and coalescence approaches From Garbelotto and Chapela, Evolution and biogeography of matsutakes Biodiversity within species as significant as between species 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)