Testing for Rapid Radiation Over Clade History Using the Gamma Statistic

Testing for Rapid Radiation Over Clade History Using the Gamma Statistic

Testing for Rapid Radiation Over Clade History Using the Gamma Statistic Did a clade ‘adaptively radiate’? Expect initial diversification to be fast Pybus and Harvey (2001)* proposed a test for rate shift across the tree Pybus, O. G., and P. H. Harvey. 2000. Testing macro-evolutionary models using incomplete molecular phylogenies. Phil. Trans. Roy. Soc. (Lond.) B 267:2267-2272. The gamma statistic Midpoint of BLs a tree branching under a constant-rates model should have a balance of node depths around the midpoint of the tree γ describes this distance γ~0 Early branching rapid, early diversification will create an imbalance of young nodes this will be reflected by a -γ evidence for adaptive radiation γ<0 Late branching recent accelerated net diversification will concentrate nodes towards the tips could be due to increase in birth rate or decrease in death rate γ>0 γ-statistic Elevated early rate Constant rate Elevated late rate Midpoint of BLs Keypoint: Negative γ-statistic consistent with early elevation of diversification rate (this is the CR test) γ<0 γ~0 γ>0 if gamma is less than 2 std. deviations from mean (γ ≤ -1.645), reject constant rate of diversification What about incomplete sampling? 3 with random 1 sampling of four 4 taxa, what nodes would be expected to miss? 5 2 how would this affect gamma? 6 0 0 5 MCCR: The constant rates1 A. test for 0 0 0 1 area = 2.27 incompletely sampledfrequency trees* 0 0 5 Complete sampling: γ ≤ -1.645 0 !4 !2 0 2 4 Incomplete sampling means that old nodes more likely to be area recovered, biasing CR test 0 Solution: MCCR test* 0 0 4 B. Simulate tree with n taxa 0 0 0 3 RANDOMLY prune missing taxa 0 frequency 0 0 2 ! = -3.24 Calculate the γ-statistic on pruned tree 0 0 0 Repeat 1 0 Calculate corrected p-value !4 !2 0 2 4 ! * Pybus and Harvey (2000) Example of Gamma Statistic: Diversification of Homalopsid Snakes 34 species distributed across S.E. Asia Aquatic to semi-aquatic Alfaro et al. 2007 A timetree for homalopsid diversification Enhydris matannensis Lake Towuti, Sulawesi A Enhydris plumbea A Enhydris plumbea B Enhydris chinensis Bayesian timetree Enhydris subtaeniata Enhydris enhydris B using BEAST Enhydris innominata Enhydris longicauda 4 genes (12S, 16S, cytB, Enhydris punctata Bitia hydroides 0 0 C-Mos 5 1 A. Cantoria violacea C 0 0 0 Gerarda prevostiana 1 area = 2.27 frequency Fordonia leucobalia A 9 of 10 genera, 20 of 0 0 5 Fordonia leucobalia B 34 species 0 Enhydris polylepis !4 !2 0 2 4 Myron richardsonii area MCCR test suggests Enhydris bocourti Erpeton tentactulatus 0 0 0 rapid initial 4 B. Homalopsis buccata 0 0 0 D diversification ( P < 3 Cerberus australis 0 frequency 0 Cerberus rynchops A 0 0.001) 2 ! = -3.24 Cerberus microlepis 0 0 0 1 Cerberus rynchops B 0 30 28 26 24 22 20 18 16 14 12 10 8 6 4 2 0 !4 !2 0 2 4 ! OLIGO MIOCENE Pi Ps Alfaro et al. 2007 Log-Lineages Through Time 3.0 2.5 2.0 Log Lineages 1.5 1.0 0 5 10 15 20 Time From Basal Divergence Models of diversification: Constant-rate models Pure birth (PB) Pure Birth Model Death = 0 0.7 0.6 Birth Rate 0.5 0.4 0.3 0 20 40 60 80 100 Time Models of diversification: Constant-rate models Birth-Death (BD) Birth-Death Model Birth & Death constant 0.7 0.6 Birth 0.5 Rate 0.4 Death 0.3 0 20 40 60 80 100 Time Rate-variable models: Density-dependent Exponential Density-Dependent Model Density-dependent: Exponential 1.0 -x R(t) = R0 *(N(t)) 0.8 0.6 Birth Rate 0.4 0.2 0.0 0 20 40 60 80 100 Time Rate-variable models: Density-dependent Logistic Density-Dependent Model Density-dependent: Logistic 1.00 R(t) = R0 *(1- N(t)/K) 0.95 Birth 0.90 Rate res[, 1] 0.85 0.80 0 20 40 60 80 100 as.numeric(rownames(res))Time Models of diversification: Variable-rate models Yule-2-RateYule-2-Rate Model Model Yule-2-Rate (Y2R) Death = 0 Birth-2 0.805 Shift Time Rate 0.800 Rate Birth-1 0.795 0 20 40 60 80 100 TimeTime Models of diversification: Variable-rate models Rate-variable BD (RVBD) Rate-VariableRate-Variable Birth-Death BD Model Model Death/Birth is constant Rate-2 0.805 Shift Time Rate 0.800 Rate Rate-1 D/B 0.795 0 20 40 60 80 100 TimeTime Model scores Model LH dAIC Rate 1 Rate 2 Shift Time PB 75.73 12.07 0.153 NA NA BD 75.73 14.07 0.153 NA NA DDL 79.07 7.4 0.236 NA NA DDX 77.58 10.37 0.352 NA NA Y2R 83.77 0 0.177 0.036 1.127 RVBD 83.77 2.0 0.177 0.036 1.127 density-dependent models rejected for rockfish How can we test for unequal rates of diversification? Construct a timetree Calculate rates Test for significant differences using comparative methods Step1: molecular phylogeny Molecular sequence data from three loci Rag1, 12S, 16S (Holcroft, 2005, plus additional data) Sampled 86 ingroup taxa including members of all extant families Bayesian analysis using MrBayes, 1 X 107 generations, multiple independent runs v Ranzania laevis v Masturus lanceolatus MOLIDAE # v Mola mola 1 # Mola mola 2 Triodon macropterus TRIODONTIDAE v Anoplocaparos inermis Aracana ornata ARACANIDAE v # Tetrosomus concatenatus v Lactophrys bicaudalis v Lactophrys triqueter OSTRACIIDAE Lactophrys polygonia Lactophrys quadricornis v Allomycterus pilatus v v Chilomycterus antennatus # Chilomycterus schoepfii v Diodon holacanthus DIODONTIDAE v Diodon hystrix v Diodon liturosus # Lagocephalus laevigatus Marilyna darwinii v v v Takifugu rubripes # v Torquigener pleurogramma v Tetractenos glaber Tetractenos hamiltoni v Sphoeroides dorsalis Sphoeroides spengleri Monotreta leiurus v # Tetraodon fluviatillis TETRAODONTIDAE v Arothron hispidus v v Arothron nigropunctatus Canthigaster bennetti v Canthigaster rostrata Canthigaster amboinensis v Canthigaster valentini v Canthigaster solandri v Canthigaster jactator Canthigaster janthinoptera v Trixiphicthys weberi Pseudotriacanthus strigilifer TRIACANTHIDAE Triacanthodes anomalus TRIACANTHODIDAE v Aluterus scriptus # v Brachaluteres jacksonianus v Paraluterus prionurus v v Monacanthus ciliatus # Monacanthus hispidus Oxymonacanthus longirostris MONACANTHIDAE v Meuschenia trachylepis Nelusetta ayraudi v v Cantherhines pullus # Amanses scopas Cantherhines dumerilii Balistoides conspicillum Melicthys niger v v Balistoides virdescens Xanthichthys auromarginatus Abalistes stellatus BP > 85% v Rhinecanthus aculeatus v Rhinecanthus assasi v v Sufflamen bursa BALISTIDAE PP > 95% Sufflamen chrysopterus v Canthidermis maculatus v Pseudobalistes fuscus v # Balistes vetula v v Balistes capriscus Balistes polylepis Alfaro, Brock, and Santini 2007, Evolution Step 4: Compare Diversification Rates 1. Estimate mean Age Extant Taxon Faster? diversification rate of (MY) # predominately reef tetraodontiformes (λG) Balistidae 22.9 43 ** λG = [ln(n) - ln(2)]/t Diodontidae 10.9 22 ** = ln(350)-ln(2)/70MY Monacanthidae 24.6 108 ** = 0.07 species/MY Ostraciidae 20.8 25 * Tetraodontidae 38.3 185 ** pelagic, benthic, temperate 2. Test whether family Aracanidae 6.7 13 ** species richness Molidae 25.9 5 NS keyplausible point: given species λG * Triacanthidae 21.0 7 NS richness exceptionally Triacanthodidae 55.7 22 NS Triodontidae 54.0 1 NS high in reef groups 10 substitutions/site PALEOGENE NEOGENE PALEO EOCENE OLIGO MIOCENE Pi Ps *Magallon and Sanderson, 2001 66.5 55.8 33.9 23.0 5.3 1.9 Sharks Polypteriformes Chondrostei Amiiformes Elopomorpha Osteoglossomorpha Ostariophysi Clupeomorpha Stomiiformes A Timetree for Osmeriformes Esociformes Salmoniformes Myctophiformes Aulopiformes Jawed Vertebrates Percopsiformes+Gadiiformes Polymixiiformes+Zeiforms Lampriformes Beryciformes+Stephanoberyciformes Ophidiiformes •~ 60,000 species total Percomorpha Scombridae Latimeridae •Molecular Phylogeny Dipnoi Gymnophiona •RAG-1 genbank data Caudata Anura Monotremes •221 tip species Marsupials Afrotheria+Xenarthra •Relaxed molecular clock Boreoeutheria Taxa Sphenodon 42 fossil calibrations 1 NongekkoSquamates • 5 Gekkos 10 Pleurodira •major gnathostome 50 Cryptodira 100 Gavialidae lineages represented 500 Crocodylinae 1000 Camininae 5000 Alligatorinae Tinamiformes 10000 Struthioniformes 20000 Neoaves Galliformes Anseriformes 500 400 300 200 100 0 MYA Sharks Polypteriformes Chondrostei Amiiformes Elopomorpha Osteoglossomorpha Ostariophysi 1. λG = [log(n) - log 2]/t Clupeomorpha Stomiiformes Osmeriformes Esociformes n = 57,859 species Salmoniformes Myctophiformes Aulopiformes t = 549 mya Percopsiformes+Gadiiformes Polymixiiformes+Zeiforms Lampriformes Beryciformes+Stephanoberyciformes Ophidiiformes Percomorpha λG = ln(n) - ln(2) Scombridae Latimeridae Dipnoi t Gymnophiona Caudata Anura Monotremes λG = ln(57859) - ln(2) Marsupials Afrotheria+Xenarthra Boreoeutheria 549 Taxa Sphenodon 1 NongekkoSquamates 5 Gekkos 10 Pleurodira 50 Cryptodira 100 Gavialidae 500 Crocodylinae λG = 0.019 1000 Camininae 5000 Alligatorinae Tinamiformes 10000 Struthioniformes 20000 Neoaves Galliformes Anseriformes 500 400 300 200 100 0 MYA 9 j 10000 2 f d s e z a 5 4 ! u 1 l 7 # $h 0 k 8 t 100 3 i % Extant Species Richness n @ x 6 w q m & p Species Richness v b r o g c 1 y 100 200 300 400 500 Stem AgeStem Age (MY) Pure Birth λ = 0.019 9 j 10000 2 f d s e z a 5 4 ! u 1 l 7 # $h 0 k 8 t 100 3 i % Extant Species Richness n @ x 6 w q m & p Species Richness v b r o g c 1 y 100 200 300 400 500 Stem AgeStem Age (MY) Thanks!!! • we will send course materials out--make sure you gave us your email • please send comments and feedback with ‘FEEDBACK’ in the header to [email protected] Sharks Polypteriformes Chondrostei Amiiformes Elopomorpha Osteoglossomorpha Ostariophysi Clupeomorpha Stomiiformes A Timetree for Osmeriformes Esociformes Salmoniformes Myctophiformes Aulopiformes Jawed Vertebrates

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