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S chool of B iological S ciences

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  1. School of Biological Sciences Clonal diversity mattersHigh levels of functional and genetic diversity occur in the model microzooplankter Oxyrrhis marina Chris Lowe, David Montagnes, Phill Watts

  2. Introduction Microbial food webs are important in aquatic systems Many morphospecies are thought to be ubiquitous Phylogenetic data suggest this may be so (but results are ambiguous) But are we looking at the right aspects? Functional (phenotypic) diversity may be a more appropriate metric to assess distribution

  3. Introduction: Oxyrrhis marina Dujardin 1859 A well characterised morphospecies A commonly used model organism An easy organism to grow Ubiquitous 10 µm

  4. Distribution

  5. Introduction: The BIG question • A specific test case: O. marina • One morphospecies • Phylogenetic markers (different) • Ecophysiological responses (different) • “Everything is everywhere, nature selects” • Are we adequately examining diversity? • Morphology • Genetics • Functional differences (phenotypes)

  6. Phylogeography: Distribution

  7. Phylogeography: Our data

  8. 24s 5.8s 18s Plymouth CAP1133/3 ITS ITS 5` 3` 63 IOM/PSM IOM/P IOM/S Bahrain CAP1133/4 100 Finland CCAP1133/5 Washington CCMP604 These are all Oxyrrhis(18s rDNA) 4 well-supported clades Large genetic differences Do they have a phylogeographic distribution? Lowe et al. 2005 100 100 Caribbean CCMP1788 95 Connecticut CCMP1795 Florida CCMP605 100 Texas CCMP1739 0.05 substitutions/site Phylogeography: (5.8s ITS rDNA)

  9. Phylogeography: (5.8s ITS rDNA) They have no clear phylogeographic distribution

  10. Ecophysiology: Is distribution related to function?

  11. Ecophysiology: Is distribution related to function? Habitat Environment

  12. Oxyrrhis marina Pools vs coastal waters Salinity

  13. Ecophysiology: salinity Salinity numbers Time Nt = N0•et 1 Growth rate () 0 -1 40 30 60 10 Salinity (ppt)

  14. 2 growth rate responses Geographical location Coastal 5.8s ITS sequence data Habitat: coastal, intertidal Growth rate ( d-1) Habitat Salinity (ppt) Location There appears to be a habitat specific response EcophysiologyandrDNA do not agree Lowe et al. 2005

  15. Is everything everywhere? Morphology: inadequate resolution “Neutral” markers: rDNA does not explain observed distribution of clones

  16. Conclusion We need to examine multiple clones to assess differences Ecophysiology: suggests distributional patterns based on habitat Our next step is to examine: Selection/adaptation Population structure/dispersal Neutral andFunctional characteristics Interdisciplinary approach to biodiversity

  17. School of Biological Sciences Breaking boundaries:quantifying the influence of demography and seascape in driving divergence in the protist Oxyrrhis marina Phill Watts, Chris Lowe, David Montagnes

  18. Oxyrrhis marina: “Everything is everywhere, nature selects” This is a hypothesis describing processes of: Dispersal Adaptation It suggested distributions of micro-organisms are fundamentally different from macro-organisms To data there has been no explicit tests of this hypothesis for micro-organisms across landscapes

  19. The marine environment is heterogeneous Distinct oceanographic boundaries (e.g. fronts, gyres, isthmuses, currents) Strong environmental gradients (temperature,salinity)

  20. Oxyrrhis marina: We will quantify relative roles of natural selection and random drift in driving divergence Spatial variation in adaptive traits i.e. salinity and temperature tolerance Demographic parameters e.g. population boundaries, population sizes migration rates Are these processes/parameters different between micro-organisms and macro-organisms?

  21. Oxyrrhis marina and the marine environment The heterogeneous marine environment provides a framework to examine adaptive/neutral variation

  22. Oxyrrhis marina and the marine environment Collect O. marina samples from across Europe 2 scales: Northern Europe Irish and Celtic seas For each site: Isolate & culture replicate O. marina clones Genotype isolates Make phenotypic measurements Growth rate Cell size Gene expression (Na/K ATPase, HSP)

  23. Na/K ATPase expression t1 t2 r1 r2 Salinity Salinity Temperature Population growth rate Nt = N0•et Gene expression Qst Genetic and phenotypic diversity morphology Microsatellite Genotyping Fst

  24. HT = heterozygosity in total population HS = average heterozygosity in subpopulations Fst (dispersal) Measures of the extent of divergence between populations relative to the total diversity within all populations Based on neutral markers (e.g. microsatellites) Provides an indication of geneflow/dispersal between populations

  25. σ2p(b) = phenotypic variance between populations σ2p(w)= average phenotypic variance within populations Qst(adaptive divergence) Measures of the extent of divergence between populations relative to the total diversity within all populations Based on phenotypic traits (e.g. ecophysiological responses, morphometrics) Provides an indication of adaptive divergence

  26. σ2p(b) = phenotypic variance between populations σ2p(w)= average phenotypic variance within populations Qst

  27. No dispersal barriers Fst↓ Identical environments Qst ↓ Fst Qst 0 1 (popns connected, no adaptive divergence) 0 1 Complete dispersal barrier Fst↑ Identical environments Qst ↓ Fst Salinity Qst (popns different, no adaptive divergence) Balancing selection Fst – Qst:comparison Salinity

  28. 0 0 1 1 Complete dispersal barrier Fst↑ Different environments Qst ↑ Fst Qst Salinity (popns different, adaptive divergence) Fst – Qst:comparison No dispersal barriers Fst↓ Different environments Qst ↑ Fst Qst (popns connected, adaptive divergence) Spatially varying selection Salinity

  29. Na/K ATPase expression t1 t2 r1 r2 Salinity Salinity Temperature Population growth rate Nt = N0•et Gene expression Qst Genetic and phenotypic diversity morphology Microsatellite Genotyping Fst

  30. Oxyrrhis marina and the marine environment • So, all we need to do is: • Collect many O. marina • Make measurements on neutral markers and phenotypic traits • Compare Fst-Qst • Apply data to landscapes and boundaries • Test hypothesis that everything is everywhere and nature selects • But it’s expensive to travel all over the place and would make a big carbon footprint • Solution: we need your help to collect O. marina