Summary

1. Summary • DNA evolves leading to unique sequences that may be used to identify species, biological species, provenences of strains, genotypes, genetic or allelic richness and genetic structure • Mutations and recombinations drive evolution of DNA sequences. Isolation, drift, and selection lead to unique sequences associated with different species or isolated populations • Isolation: allopatric vs. sympatric. In both cases there is no gene flow between species • DNA sequences can be used to identify species. They need to be aligned and compared. If each species is unequivocally found within a statistically supported clade, then that sequence can be used to identify species and provenance for that group of organisms • Diagnostic sequence,narrower concept need to be from a locus that is less variable within species and more variable in between species. Alternatively fixed alleles may be the most powerful. Rare alleles or private alleles are also important in defining populations (individuals that are freely mating): allele frequencies used by assignment tests such as structure

2. Summary • Sequences used to identify species either by comparison of actual sequence or by use of taxon specific PCR primers that will only amplify target organism. Need for control. I.e. primers that will amplify any organism to make sure reaction is working. • If sequences are obtained and compared they can • Aligned with sequences of similar organisms to determine presence of statistically significant clades • Compared with sequences present in public databases such as GenBank. BLAST engine • Beware that a single locus may be deceiving, because history of locus (gene geneaology is not necessarily history of organism)

3. Summary • If more than just species identification is needed, multiple genetic markers will be needed. These should be as much as possible unlinked. These multiple markers can be used to identify genotypes and study their distribution to understand epidemiology of a disease or perform paternity tests; determine allelic richness: this is considered an important issue in conservation biology (normally small or isolated populations tend to loose alleles); study the genetic structure of a species, I.e. Are populations genetically different (are their alleleic frequencies significantly different) and if so at what scale does the difference become significant; finally multiple genetic markers can be used to understand if species is reproducing sexually or not. This is important to understand epidemiology • Genetic information can be supported by other types of information. For fungi for instance the use of somatic compatibility and of mating allele richness can be used to make inferences on genotypic composition, and relatedness of genotypes. • Mitochondrial analysis can also be used to make inferences on genetic relatedness

4. 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.

5. 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

6. Somatic incompatibility

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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)

13. 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

14. 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

15. 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

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

17. Clamp connections

18. 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

19. A, A, B, C, D, D, E, H, I, L A, A, A,B, B, A, A Two scenarios:

20. 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) Two scenarios:

21. 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

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

23. Small branches within a clade indicate sexual reproduction is ongoing within that group of individuals NA S NA P EU S 890 bp CI>0.9 EU F

24. 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

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

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

27. Evolutionary history • Darwininan vertical evolutionary models • Horizontal, reticulated models..

32. 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

33. 1010101010 1010101010 1010101010 1010101010 1010000000 1011101010 1010111010 1010001010 1011001010 1011110101 RAPD combination1 2

34. 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

35. 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

36. 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

37. 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

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

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

40. 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

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

42. 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

43. 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

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

45. Example • SPECIES X: 50%blue, 50% yellow

46. AMOVA: example Scenario 1 Scenario 2 v POP 1 POP 2 v

47. 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

48. Plotting distances • Pairwise genetic distances can be plotted: the distribution of distances can be informative of biology of organism

49. 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.

50. 0.7 0.6 Pp U.S. 0.5 Pp E.U. 0.4 Frequency 0.3 0.2 0.1 0.0 0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 Jaccard coefficient of similarity P. pseudosyringae genetic similarity patterns are different in U.S. and E.U.