1. Patterns of divergent selection from combined DNA barcode and phenotypic data Tim Barraclough, Imperial College London

2. Goals: 1)Delimit evolutionary species independent arenas for selection and drift

3. Goals: 1)Delimit evolutionary species independent arenas for selection and drift 2) Identify the processes generating diversity separate demography reproductive isolation divergent selection

4. DNA barcodes DNA sequence data sampled at the individual level across an entire clade sample certain no. individuals per taxonomic species environmental samples irrespective of known species

5. DNA barcodes DNA sequence data sampled at the individual level across an entire clade sample certain no. individuals per taxonomic species environmental samples irrespective of known species new resource linking macro- and population genetic questions

6. DNA barcodes: limitations How to detect evolutionary species? Rely on traditional species Phenetic approaches, e.g. 2% sequence divergence. Population models => prior guess on minimum units (c.f. bacteria) => multilocus, => parameter-rich Sampling?

7. DNA barcodes: limitations Single marker 1)Species tree versus gene tree multilocus approaches 2) Arbitrary or neutral markers No information on adaptive variation niche traits, those involved in R.I.

8. Goals: 1)Delimit independently evolving species 2) Identify the processes generating diversity divergent selection

9. 1) Delimit independently evolving species Prediction: genetic clusters separated by longer internal branches Conservative - miss recent Assumptions Just uses DNA variation

10. Statistical approach Null model: Entire sample derives from single species, i.e. no independently evolving subsets of individuals Single coalescent process Likelihood of waiting times

11. Statistical approach Null model: Entire sample derives from single species, i.e. no independently evolving subsets of individuals Single coalescent process scaling parameter p 1 excess of recent

12. Statistical approach Alternative model: separate independently evolving species Within species branches  coalescence Between species  speciation, extinction Between species branching Within species branching

13. Alternative model: separate populations 1.Label which branches are within v. between species 2.Set of independent coalescent processes in each species 3.Generalized Yule model for between species branching p=1 constant speciation rate model p>1 increasing speciation rate, background extinction p<1 slowdown, incomplete sample of species (Mixed Coalescent Yule model, Pons et al. 2006. Syst Biol. 55:559-609)

14. Alternative model: separate populations Implementation Optimize which nodes define separate species, e.g. sliding threshold or more complex Confidence intervals on delimitation Hypothesis testing

15. Alternative model: separate populations Example Tiger beetles from Australian salt lakes 468 individuals 48 +2/-4 genetic clusters Fitted parameters: Growing populations or selective sweeps Pons et al. 2006. Syst Biol. 55:559-609)

16. Alternative model: separate populations Limitations Current implementation uses sliding threshold Identical individuals Sampling Not exact (but generalized) Conservative, but could focus e.g. multi-locus Correcting for mtDNA rate variation

17. Goals: 1)Delimit independently evolving species 2) Identify the processes generating diversity divergent selection Focus on a trait or traits ecomorphology reproductive morphology behaviour, defensive chemicals etc.

18. Divergent selection Character under divergent selection displays greater ratio of inter-group variation Than neutrally evolving characters Can compare variation in morphological traits to variation of arbitrary DNA markers Qst-FstFontaneto et al. 2007. PLoS Biology 5:e87

21. Divergent selection Compared to clusters identified from mtDNA 1)Coincident with clusters 2)Acting at broader level (uniform selection across entire clade or sub-clades) 3)Acting within clusters - recently formed species or adaptive polymorphism

22. Divergent selection Example: divergent selection on feeding morphology in bdelloid rotifers Fontaneto et al. 2007. PLoS Biology 5:e87

23. Significant pattern of clustering

24. ML solution: 13 clusters COI Pairwise within = 1.5% COI Pairwise between = 16% H0:H1, p<0.0001 Some traditional species contain several clusters

25. Traditional Species are morphological clusters

26. Mapped rate of evolution of trophi size and shape relative to silent mtDNA change Null model: one rate across DNA tree Alternatives: 1) Within versus between species 2) Within versus between clusters 3) Three rates Schluter et al. 1997.

27. Results Significant evidence for divergent selection on trophi size and shape between taxonomic species, not clusters.

28. Sexual organisms? Assumptions Assume additive genetic variation  environmental variation might inflate intra Limited to measurable traits, measurement error will inflate intra Prospects? DNA barcode data as framework to explore selection on morphological traits of voucher specimens