CLASS REVIEW 2010 Lectures

Understanding of nature, an essential part of culture Forests essential for life on the planet Fungi essential for survival of forests

DNA mutates, evolves, and different DNA sequences can be assigned to different individuals, populations from different provenances, closely related species, different species, different microbial pathovars DNA-based phylogeography allowed to discover pine pathogen in Italy was of North American origin DNA based genealogies allowed to identify hybridization between native and exotic pathogen DNA allows to identify new species and to determine whether they are exotic or not

Definitions Propagule= structure used by an organism to spread or survive Locus= a physical portion of a chromosome,a gene Intron= a portion of DNA, a locus that does not code for a protein Exon= a coding gene

Definitions-2 Alleles= different DNA sequences at the same locus If a locus has variation in sequence it is polymorphic (many forms) Polymorphisms are differences in DNA among organisms, the more polymorphisms the easier it is to differentiate organisms There are more polymorphisms in introns

Definitions-3 Invasive organisms: exotic organism that reproduces and occupies progressively a larger area: –Fast reproductive cycle –Vectored –Hardy –Occupy unoccupied niches –Different drain on natural resources –Make environment favorable for itself and other invaders –Linked to disturbances –If pathogen, more changes because top of pyramid –May hybridize with native species: new taxon is created

New host pathogen combinations Pathogen stays/Plant moves: invasive plant Pathogen moves/Plant stays: exotic epidemic Pathogen moves/Plant moves: biological control

Success. The “1:10” rule Can exotic withstand new environment Can it withstand attacks of predators Can it outcompete similar native organisms by accessing resources –Can a pathogen be pathogenic –Can a pathogen be sufficiently virulent

Functions of avr/R genes Avr genes may help detoxify plant enzymes, secure necessary aminoacids or proteins, plant toxins, promoting pathogen growth. Normally they are mobile, wall-bound products R genes normally recognize multiple avr genes and start hypersensitive response (programmed cell death)

Can be R genes accumulated? There is a cost associated with R genes Mostly R genes initiate costly defense processed, often even when challenged by innocuous microbes Some evidence that in absence of specific avr, R are lost

CAN WE PREDICT: Success of an exotic microbe? –Survival structures such as cysts, spores, etc –Saprotrophic ability (ability to feed on dead matter) –Degree of host specialization, the more specialized the harder it may be to establish –Phylogenetic distance of hosts (the closertive and new hosts are, the easier the establishment) –Similar ecology

CAN WE PREDICT: Levels of the epidemic? –Density dependance: abundance of susceptible hosts –Genetic variation in host. In general it is assumed that genetic variation in host populations slows down epidemics, however backing data from natural ecosystems is missing. It could be that low genetic diversity associated with widespread presence of resistance may be more beneficial that genetic variability

DNA polymorphisms can be diagnostic –Mutations/Sex/Barriers to mating Plant Diseases can be biotic (interaction between host and causal agent ), or abiotic Many organisms can cause plant diseases, but fungi are the No.1 cause Diversity of fungi, but all have ideal structure for plant infection: –hypha/cord/rhizomorph/infection peg/appressorium –Sexual vs. asexual reproduction: can do both

Definitions Alternatively fixed alleles Dominant vs. co-dominant markers Genotype

Dominant vs. codominant genetic markers Concept of “genotype” Alternatively fixed allele vs.difference in frequencies PLANT HOST INTERACTION: timing, physical/chemical interaction, basic genetic compatibility leads to virulence, gene for gene hypothesis, pathogenicity

Categories of wild plant diseases Seed decay Seedling diseases Foliage diseases Systemic infections Parasitic plants Cankers, wilts, and diebacks Root and butt rots Floral diseases

Janzen-Connol hypothesis; explanation of why diseases lead to spatial heterogeneity Diseases also lead to heterogeneity or changes through time –Driving succession –The Red Queen Hypothesis: selection pressure will increase number of resistant plant genotypes Co-evolution: pathogen increase virulence in short term, but in long term balance between host and pathogen Density dependance

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

Important fungal genetic systems: Intersterility genes Somatic (vegetative) compatibility Mating system

Summary AFLP, RAPDs, RFLPs, microsatellites Repeatability Test for power (PID and test progeny) Have we sampled enough? Rarefaction curves, resampling, need to be ob flat portion of curve

Summary From raw data to genetic distance Distance distribution AMOVA PHIst Distance based trees Number of polymorphic alleles

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)---

The scale of disease Curves of spore dispersal (rapid dilution effect, e.g most spores fall near source, but a long low tail, a few spores will travel long distances Genetic structure of species: the more structure the more fragmented the less dispersal Mantel tests, spatial autocorrelation: plot the genetic distance against the geographic distance

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

Population genetics concepts Gene flow, migration Lack of gene flow, genetic substructuring=differentiation Hardy Weinberg= for diploid or dikaryotic organims predicts levels of heterozygosity Inbreeding coefficient Fst

How do we know that we are sampling a population? We actually do not know Mostly we tend to identify samples from a discrete location as a population, obviously that’s tautological Assignment tests will use the data to define population, that is what Grubisha et al. did using the program STRUCTURE

CLASS REVIEW 2010 Research papers

Hayden et al paper describes how PCR assay is designed: 1- primers only match target species and not relatives: PCR product = pathogen is there 2-nested approach 3-control primers amplify all plants

Molecular Ecology (2008) doi: /j X x Blackwell Publishing Ltd Reconstruction of the Sudden Oak Death epidemic in California through microsatellite analysis of the pathogen Phytophthora ramorum S. MASCHERETTI,* P. J. P. CROUCHER,* A. VETTRAINO, † S. PROSPERO ‡ and M. GARBELOTTO* * Department of Environmental Science, Policy and Management, 137 Mulford Hall, University of California, Berkeley, CA , USA, †Department of Plant Protection, University of Tuscia, I Viterbo, Italy, ‡INRA, UMR 1202 Biodiversité Gènes et communités, Equipe de pathologie Forestiere, BP 81, Villenave d′ Omon Cedex, Fra nc e Abstract The genetic structure of the clonally reproducing Sudden Oak Death (SOD) pathogen in California was investigated using seven variable microsatellites. A total of 35 multilocus genotypes were identified among 292 samples representative of populations from 14 forest sites and of the nursery trade. AMOVA indicated significant genetic variability both within (44.34%) and among populations (55.66%). Spatial autocorrelation analyses indicated that Moran ’ s index of similarity reached a minimum of 0.1 at 350m, increased to 0.4 at 1500 m and then decreased to zero at 10km. These results suggest a bimodal pattern of spread, with medium range dispersal (1500 – 10000m) putatively attributed to the presence of strong winds. Lack of genetic structure was identified for three groups of populations. One group notably included the nurseries ’ population and two forest populations, both linked to early reports of the pathogen. A neighbour-joining analysis based on pairwi s e ΦST values indicated that the clade inclusive of the nurseries ’ populations is basal to all California populations. A network analysis identified three common genotypes as the likely founders of the California infestation and proposes a stepwise model for local evolution of novel genotypes. This was supported by the identification in the same locations of novel genotypes and of their 1- or 2-step parents. We hypothesize that the few undifferentiated population groups indicate historical human spread of the pathogen, while the general presence of genetically structured populations indicates that new infestations are currently generated by rare medium or long-range natural movement of the pathogen, followed by local generatio

Key points Organism is exotic, why? How does it kill oaks? How far does it spread? Is it in equilibrium, How does it attain diversity? What ecological conditions are necessary? What can be done?

Key points Pine mortality near Rome, never reported before suggesting something new Heterobasidion root rot basidiocarps found at base of trees Multiple loci analysis indicates pathogen is from North America Likely to have been brought into Europe by US Army with untreated lumber

Nature 394, (1998) © Macmillan Publishers Ltd. Cause of sea fan death in the West Indies

Humongous fungus The Fungus Armillaria bulbosa is among the largest and oldest living organisms

Key points Armillaria does not reproduce via asexual spores Same genotype found in a large area RAPDs and RFLP of mitochondrion and mating alleles Tested sensitivity of RAPDs on full sibs Age estimated by dividing maximum distance within clone by annual growth rate

Key points Native fungus, host specialized How does it infest stands? Does it need stumps? How was research done? Sampling and analysis What type of forests will enhance secondary spread? Is source of inoculum local or not? How was it shown that nuclei can rearrange themselves

Key points Wood decay fungus, generalist Sexually reproducing hence lots of local diversity Easily airborne, easy to find hosts, no genetic structure within Sweden Structure between Sweden and Finland Methods: RAPDS and AMOVA

Key points Pathogen, very host-specific Infection is mostly primary by airborne meiospores Method: AFLP analysis on haploid meiospores AMOVA indicated significant genetic diversity both within and among populations Lack of host= barrier to migration

Key points Mycorrhizal fungus, obligate symbiont Symbiont with most conifers, air dispersed Japanese market buys some species, rejects others Species accepted by market are monophyletic At least 3 species: circumboreal, mexican, and west coast North America= center of diversity Oldest species is in North America Methods: DNA sequencing and AFLPs Isolation by distance: distant populations more different genetically

Isolation by landscape in populations of a prized edible mushroom Tricholoma matsutake

Key points Specific mycorrhizal symbiont, underground mushrooms, animal dispersed Islands in islands Compare genetics of fruitbodies and of seed banks Genetic structure indicate low gene flow among sites, but similar genetic structure between two islands