Quantifying uncertainty in species discovery with approximate Bayesian computation (ABC): single samples and re

Quantifying uncertainty in species discovery with approximate Bayesian computation (ABC): single samples and re

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## Quantifying uncertainty in species discovery with approximate Bayesian computation (ABC): single samples and re

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**Quantifying uncertainty in species discovery**with approximate Bayesian computation (ABC): single samples and recent radiations Mike Hickerson University of California, Berkeley Chris Meyer Museum of Vertebrate Zoology Craig Moritz**Outline**Introduction - Species Discovery Potential problems - Simulations Potential problems - Empirical data Potential statistical solutions**Match new specimen’s DNA “barcode” to voucher**specimens with barcodes in database**Proposed genetic thresholds for discovery**Comparing sample to closest sister taxon in reference database 1.Hebert’s 10X rule between species divergence must be > 10 times the average within species divergence 2. Reciprocal Monophyly**Noisy Problem**Species Tree ≠ Gene Tree Usually a “near miss” Species A Species B Species C 4 Sampled Individuals Species C**Doubly Noisy Problem**(mtDNA Barcode locus) Genetic Threshold Equal? Species Delimitation Criteria Moving Target (Mental Construct?)**Doubly Noisy Problem**Not sensitive enough (mtDNA Barcode locus) Under-Discovery Genetic Threshold too sensitive Over-Discovery Equal? Species Delimitation Criteria Moving Target**Joint Simulation**Exploration DNA-barcode gene (mtDNA, CO1 690 bp) Simple BDM Model of Reproductive isolation: (Bateson-Dobzhansky-Muller) Coalescent model Problematic parameter space? Potential statistical solutions?**BDM Model**(Bateson-Dobzhansky-Muller) Genotype A , b OK a , b A, B a, B Bad Neutral and divergent selection (Gavrilets 2004) Speciation events - Poisson process**BDM loci**Barcode locus (mtDNA) Divergence Time (generations) Island/Continent (peripatric)**Reciprocal monophyly**Threshold Hickerson et al. 2006 (in press; Systematic Biology)**Coyne and Orr 1997**10X Not Species**Coyne and Orr 1997**Not Species**Coyne and Orr 1997**Presgraves 2002 Mendelson 2003 Bolnick and Near 2005 Zigler et al. 2005 Sasa et al. 1998**Move beyond “Yes/No” answers:**Nielsen and Metz 2005 Bayesian posterior probabilities w/ ABC -answers with quantified uncertainty -very fast (< 30 seconds per query) -flexible (parameter threshold, model and prior changes according to taxonomic group) = moderate support for new species Migration Isolation time**Prior, parameter threshold and operative model is**adjustable as appropriate for particular taxonomic group ? Mymarommatid wasps (10 rare living fossil species) African Cichlids (recent radiation)**Ongoing Work**Extension of msBayes software pipeline Determining appropriate priors, thresholds and models Testing: Simulated data -Yule model (stochastic speciation/extinction) Empirical data - Chris Meyer (marine taxa)**Simulated data -Yule model**Speciation and extinction follows a random birth/death process Time Speciation Extinction**Test = what % of sisters and orphans are detected as**new species “discoveries? Test Data 1.Closest Divergence times - Sister’s and Orphans 2. Population sizes - Gamma distributed 50K-2.5M 3. Single specimens from “new” species 3,5,10,20, and 40 specimens from reference species Orphan Sister-pair**Yule model**Empirical Data (Cowries) 100 lineages per clade 135 lineages Is it a new species? Function of Posterior Probability of divergence Time and gene flow Discovery? Reference Species**msBayes Software pipeline**SIMULATE 1,000,000 \ draws from model Flexible Pre-simulated prior ABC observed data Accept 0.2% Posterior probability surface ~< 1 minute**Approximate Bayesian**Computation (ABC) Posterior Prior**Parameter threshold?**Posterior Prior**M1= yes, new species**M2= no, same old species f (M1given Data) f (M2given Data) Bayes Factor = prior (M1) prior (M2) A way to compare evidence for these 2 discrete models**Very Near Future**1. Better priors Species divergence time AND intra-species coalescence 2. Incorporate Migration • Hierarchical Model New species status Hyper-Parameter Yes No Hyper-Prior Prior(T,N) Prior(N, T=0)**ACKNOWLEDGEMENTS**Discussion C. Moritz C. Meyer T. Mendelson K. Zigler N. Rosenberg J. Degnan Coauthors C. Meyer C. Moritz cpu resources J. McGuire Museum of Vertebrate Zoology Funding NSF DIMACS