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. RAPD combination 1 2 1010101010 1010000000 1011101010 1010111010 1010001010 1011001010 1011110101

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 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 No Of New alleles

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= 0.60.4 (1-AB) B: 1001011 BC=0.50.5 C: 1001000 AC=0.20.8

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. Results: Jaccard similarity coefficients 0.3 0.900.920.94 0.960.98 1.00 0 0.1 0.2 0.4 0.5 0.6 0.7 Coefficient Frequency P. nemorosa P. pseudosyringae: U.S. and E.U. 0.3 Coefficient 0.900.920.940.960.981.00 0 0.1 0.2 0.4 0.5 0.6 0.7 Frequency

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

16. Results: P. pseudosyringae P. nemorosa P. ilicis 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 v Scenario 1Scenario 2 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. White mangroves: Corioloposis caperata Distances between study sites

29. Coriolopsis caperata on Laguncularia racemosa 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

32. 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

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. 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. 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 Goals of population genetics

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 p 2 + 2pq + q 2 = 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:  p 2 + 2pq + q 2

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.

51. Founder Effects; typical of exotic diseases Establishment of a population by a few individuals can profoundly affect genetic variation –Consequences of Founder effects Fewer alleles Fixed alleles Modified allele frequencies compared to source pop GREATER THAN EXPECTED DIFFERENCES AMONG POPULATIONS BECAUSE POPULATIONS NOT IN EQUILIBRIUM (IF A BLONDE FOUNDS TOWN A AND A BRUNETTE FOUND TOWN B ANDF THERE IS NO MOVEMENT BETWEEN TOWNS, WE WILL ISTANTANEOUSLY OBSERVE POPULATION DIFFERENTIATION)

53. The bottleneck effect occurs when the numbers of individuals in a larger population are drastically reduced By chance, some alleles may be overrepresented and others underrepresented among the survivors Some alleles may be eliminated altogether Genetic drift will continue to impact the gene pool until the population is large enough Bottleneck Effect

54. Founder vs Bottleneck

55. Northern Elephant Seal: Example of Bottleneck Hunted down to 20 individuals in 1890’s Population has recovered to over 30,000 No genetic diversity at 20 loci

56. Hardy Weinberg Equilibrium and F-Stats In general, requires co-dominant marker system Codominant = expression of heterozygote phenotypes that differ from either homozygote phenotype. AA, Aa, aa

57. Hardy-Weinberg Equilibrium Null Model = population is in HW Equilibrium –Useful –Often predicts genotype frequencies well

58. if only random mating occurs, then allele frequencies remain unchanged over time. After one generation of random-mating, genotype frequencies are given by AAAaaa p 2 2pqq 2 p = freq (A) q = freq (a) Hardy-Weinberg Theorem

59. The possible range for an allele frequency or genotype frequency therefore lies between ( 0 – 1) with 0 meaning complete absence of that allele or genotype from the population (no individual in the population carries that allele or genotype) 1 means complete fixation of the allele or genotype (fixation means that every individual in the population is homozygous for the allele -- i.e., has the same genotype at that locus). Expected Genotype Frequencies

60. 1) diploid organism 2) sexual reproduction 3) Discrete generations (no overlap) 4) mating occurs at random 5) large population size (infinite) 6) No migration (closed population) 7) Mutations can be ignored 8) No selection on alleles ASSUMPTIONS

61. If the only force acting on the population is random mating, allele frequencies remain unchanged and genotypic frequencies are constant. Mendelian genetics implies that genetic variability can persist indefinitely, unless other evolutionary forces act to remove it IMPORTANCE OF HW THEOREM

62. Departures from HW Equilibrium Check Gene Diversity = Heterozygosity –If high gene diversity = different genetic sources due to high levels of migration Inbreeding - mating system “leaky” or breaks down allowing mating between siblings Asexual reproduction = check for clones –Risk of over emphasizing particular individuals Restricted dispersal = local differentiation leads to non-random mating

63. Pop 1 Pop 2 Pop 3 Pop 4 F ST = 0.02 F ST = 0.30

64. Pop1Pop2Pop3 Sample size 20 AA1050 Aa4108 aa6512

65. Pop1Pop2Pop3 Freq p(20 + 1/2*8)/40 = 0.60 (10+1/2*20)/40 =.50 (0+1/2*16)/40 = 0.20 q(12 + 1/2*8)/40 = 0.40 (10+1/2*20)/40 =.50 (24+1/2*16)/40 = 0.80

66. Calculate H OBS – Pop1: 4/20 = 0.20 – Pop2: 10/20 = 0.50 – Pop3: 8/20 = 0.40 Calculate H EXP (2pq) – Pop1: 2*0.60*0.40 = 0.48 – Pop2: 2*0.50*0.50 = 0.50 – Pop3: 2*0.20*0.80 = 0.32 Calculate F = (H EXP – H OBS )/ H EXP Pop1 = (0.48 – 0.20)/(0.48) = 0.583 Pop2 = (0.50 – 0.50)/(0.50) = 0.000 Pop3 = (0.32 – 0.40)/(0.32) = -0.250 Local Inbreeding Coefficient

67. F Stats Proportions of Variance F IS = (H S – H I )/(H S ) F ST = (H T – H S )/(H T ) F IT = (H T – H I )/(H T )

68. PopHsHs HIHI pqHTHT F IS F ST F IT 10.480.200.600.40 20.50 30.320.400.200.80 Mea n 0.430.370.430.570.49- 0.14 0.120.24

69. Important point Fst values are significant or not depending on the organism you are studying or reading about: – Fst =0.10 would be outrageous for humans, for fungi means modest substructuring

70. Rhizopogon vulgaris Rhizopogon occidentalis Host islands within the California Northern Channel Islands create fine-scale genetic structure in two sympatric species of the symbiotic ectomycorrhizal fungus Rhizopogon

71. Rhizopogon sampling & study area Santa Rosa, Santa Cruz –R. occidentalis –R. vulgaris Overlapping ranges –Sympatric –Independent evolutionary histories

72. B T NE W Local Scale Population Structure Rhizopogon occidentalis F ST = 0.26 F ST = 0.33 F ST = 0.24 Grubisha LC, Bergemann SE, Bruns TD Molecular Ecology in press. F ST = 0.17 Populations are differentPopulations are similar 8-19 km 5 km