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. 1010101010 1010101010 1010101010 1010101010 1010000000 1011101010 1010111010 1010001010 1011001010 1011110101 RAPD combination1 2

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 P1=0.1 • 5 alleles at locus 2 P2=0,2 • Total P= P1*P2=0.02

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 Jaccard’s similarity index

9. Jaccard’s • Only 1-1 and 1-0 count, 0-0 do not count 1010011 1001011 1001000

10. Jaccard’s • Only 1-1 and 1-0 count, 0-0 do not count A: 1010011 AB= 0.6 0.4 (1-AB) B: 1001011 BC=0.5 0.5 C: 1001000 AC=0.2 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. 0.7 0.6 0.5 0.4 Frequency 0.3 0.2 0.1 0 0.90 0.92 0.94 1.00 0.96 0.98 Coefficient 0.7 0.6 0.5 0.4 0.3 Frequency 0.2 0.1 0 0.90 0.92 0.94 0.96 0.98 1.00 Coefficient Results: Jaccard similarity coefficients P. nemorosa P. pseudosyringae: U.S. and E.U.

15. P. ilicis P. pseudosyringae P. nemorosa Results: P. nemorosa

16. Results: P. pseudosyringae P. ilicis P. nemorosa P. pseudosyringae = E.U. isolate

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

18. Example • SPECIES X: 50%blue, 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)---

23. RAPDS> not used often now

24. RAPD DATA W/O COSEGREGATING MARKERS

26. Distances between study sites White mangroves: Corioloposis caperata

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

32. Spatial autocorrelation Moran’s 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 • Nei’s • 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.