Marsupial herbivore evolution and the failure of morphological algorithmic phylogenetics New Guinea forest wallaby matt.phillips@anu.edu.au Centre for Macroevolution & Macroecology, Research School of Biology, Australian National University 1

Horse evolution & Macroevolutionary theory, e.g. Cope’s rule “Phylogenetics is concerned with the problem of reconstructing the past evolutionary history of extant organisms from present day molecular data” – Phylomania 2010 website Darwin’s (the 1st ?) phylogenetic tree It’s not surprising though, that we’ve got to the point of thinking of phylogeny as an application of molecular data.

Molecular data: Invaluable for phylogenetic inference Morphological studies had left us with 1.99  1021 possible relationships among the 29 orders Molecular studies now leave us with ≈405 possible relationships Phillips & Penny (2010) 3

Molecular data: Is molecular phylogeny above the species level a pursuit of diminishing returns (for theoreticians)? Remaining uncertainty involves lineage sorting: genomic retroposons better than species-tree methods for assigning ancestry Clearly it’s the most efficacious data source for phylogeny reconstruction. But the big applied gains have been made, or are ready to be made with available methods. Better models for non-stationarity and selection are desirable, but unlikely to provide the required assistance – goes beyond mammals In either case, the interesting question of individual gene ancestry is defeated by stochastic error 4

21kb of nuclear genes for 57 marsupial&placental mammals BEAST relaxed clock (lognormal dist. branch rates), 13 FR calibration priors – unconstrained, 20 lineages originate in the Cretaceous 99 mya (83-116HPD) To relax the clock we need to make assumptions, like autocorrelation among branches or some distribution of rates among branches - not particularly biologically realistic. Attempts to employ biological factors (such as body size) to inform rate change are limited by poor correlation – e.g. despite general trend for large size/low rate, on these data, the ½ ton cow is evolving faster than the 25g tree shrew. Cretaceous Period Work with Kate Loynes 5

Rates of DNA substitution (subs/site/Ma) on individual branches Dark blue: unconstrained Light blue: 4 placental lineages in Cretaceous Red: no placentals cross into Cretaceous Another way to look at the data is to see what constraining the number of lineages originating in the Cretaceous implies for rates of evolution. All placentals originating in the Tertiary requires biologically unrealistic rates early in their evolution – but neither the unconstrained (20 lineage) nor 4 lineage analyses provide implausible rates. Cretaceous Tertiary Loynes & Phillips (in prep) 6

21kb nuclear genes for 57 marsupial & placentals mammals BEAST relaxed clock (as previous) – now constraining ≤4 placental lineages to originate in the Cretaceous 82 mya (73-93HPD) So the situation with just a few lineages originating in the Cretaceous cannot be rejected (so I don’t think molecular dating can help beyond saying 4-25 lineages) Cretaceous Period 7

Cut-out section of the placental mammal tree, with putative relationships of fossils from close to or before the K/T boundary More fossils confidently assigned to branches on the modern tree could immediately solve the K/T boundary problem 67 86 All these fossils may be stem placentals Kulbeckia 86 The surest way to solve the problem would be to resolve the relationships of more fossil taxa – but this relies on morphological data 92 And for the overall evolutionary timescale , reduces reliance on assumptions for how rates vary among branches 65 8

Ancestral state reconstruction Meredith et al (MPE, 2009) Foraging height Arboreality inferred at all deep nodes But megafaunal extinction was biased towards large/terrestrial Palorchestes ancestral state recon typically assumes change probability is proportional to time, or molecular branch-length. Would often be more sensible for ecological/morphological change probability to be proportional to morphological branch-length. Include 5 extinct sub-families 9

Lineage through time analysis Null hypothesis of constant net diversification (speciation-extinction) is linear Marsupial divergence times “Pull of the recent” peaks Ln (accumulated branching events) Again, incorporating fossils would help to reduce this bias, while the signal among the extant taxa helps to ameliorate biases in the fossil record. Penny & Phillips (Nature, 2006) Million years ago Turnover associated with recent biotic/aboitic events overwrites more ancient signals 10

Hurdles for morphological phylogenetics: progress is being made in some areas Long branch attraction – A serious problem when MP is standard ML models (e.g. Mk or Mkv of Lewis (Syst Biol, 2001) outperform MP 11

Other problems include: Developmental correlations (e.g. upper/lower molars) Outgroup attraction of ecological long branches (e.g. turtles) Objectivity in character state discrimination frequency Trait score State 1 State 2 Another problem is which characters to include – usually those that support your hypothesis – objective discretization can also help decide on character inclusion If no clear pattern or unimodal, exclude or score as constant 12

Functional/ecological correlations Babies cute/ugly Wing development slow/rapid Leg development rapid/slow Pigeon Emu Chicken I’ll concentrate on Functional/ecological correlations. Parenting strategy - bring them with me (common to ground feeders) versus leave them in a nest (common to tree/aerial) feeders Ducks Galah Not really three characters providing a strong phylogenetic signal Evolutionarily non-independent, associated with parenting strategy 13

Marsupials arrived in Australasia 55-70 mya from S Marsupials arrived in Australasia 55-70 mya from S.America, via Antarctica Microbiotheria Diprotodontia “Polyprotodontia”

The remainder of the talk revolves around diprotodontian marsupials The remainder of the talk revolves around diprotodontian marsupials. Diprotodont = “2 front teeth” - specifically 2 procumbent lower incisors. Other traits associated with herbivorous ancestry (diastema, horizontal shear teath, little or no canines, high mandibular condyle) - compare with polyprotodont carnivores/insectivores.

Diprotodontia: The most ecologically diverse mammal order Diprotodon opatum ~2500kg Thylacoleo carnifex 110kg So they are ideal for examining the influence of ecology on phylogeny reconstruction. Terrestrial herbivores, arboreal insectivores and a multitude of niches in between 16

Diprotodontia: 10 extant families (≈ 120 species) Vombatidae = wombats (Burrowing grazers) Phascolarctidae = koala (Arboreal folivores) Burramyidae = pygmy possums (Mostly-terrestrial to mostly arboreal gramnivores and generalized omnivores)

Macropodidae = kangaroos and potoroos (Bipedal hopping browsers/grazers and semi-fossorial root/fungi feeders) Tarsipedidae = honey possum (Arboreal nectivore) Hypsiprymnodontidae = musky rat-kangaroo (Terrestrial, bounding frugivore-omnivore)

Acrobatidae = feathertail possums (Gliding/arboreal omnivores) Pseudocheiridae = Ringtail possums (Arboreal folivores) Petauridae = gliders and trioks (Gliding gumnivores and arboreal insectivores) Phalangeridae = Brushtail possums and cuscuces (Scansorial to arboreal frugivores-folivores)

Diprotodontian consensus phylogeny: Cardillo et al. (J. Zool, 2004) Vombatidae (wombats) Vombatiformes Phascolarctidae (koala) Burramyidae (pygmy possums) Tarsipedidae (honey possum) Petauridae (gliders, stripped possums) “Core” Petauroidea Pseudocheiridae (ringtail possums) Cardillo et al used an MRP supertree to summarize the results of all earlier molecular and morphological studies on Diprotodontia Acrobatidae (feathertail possums) Phalangeridae (cuscuses and brushtail possums) Macropodidae (kangaroos and potoroos) Macropodoidea Hypsiprymnodontidae (musky rat-kangaroo)

Phillips and Pratt (MPE, 2008): mitochondrial (mt) genomes Beck (J. Mammalogy, 2008): several mt & nuclear genes Meredith et al. (MPE, 2009): 5-nuclear genes Vombatidae Phascolarctidae Acrobatidae Tarsipedidae Petauridae The family-level phylogeny of Diprotodontia has since become very clear. Pseudocheiridae Macropodidae Hypsiprymnodontidae Phalangeridae Burramyidae

Molecular “supermatrix”: 26 marsupials  20,654 nucleotides Complete mt genome protein/RNA coding sequences & 5 nuclear genes (RAG1, BRCA1, IRBP, vWF, APOB) Analysed as 13 separately modelled process partitions Mitochondrial protein 3rd codons RY-coded to reduce saturation and compositional non-stationarity

All nodes MrBayes BPP = 1. 00 and RAxML BP >95%, All nodes MrBayes BPP = 1.00 and RAxML BP >95%, (except where noted) wombats koala musky rat-kangaroo kangaroos Diprotodontia pygmy possums cuscuses feathertail possums honey possum gliders ringtail possums bandicoots “Polyprotodontia” marsupial mole 0.97 / 72 dasyurids

Previous work on the family-level phylogeny of Diprotodontia Mt sequence analyses MRP supertree summary Albumin M’CF Baverstock et al. 1990 (review) Single nuclear genes MRP supertree summary DNA hybridization Kirsch et al. 1997 (review) Informal-comparative morphology MRP supertree Algorithmic morphology (MP) MRP supertree summary Algorithmic morphology morphol352 (MP) Algorithmic morphology morphol352 (ML, Bayesian)

Differences between informal-comparative and algorithmic morphology MP, ML etc. Homology, otherwise biology-free Many and varied (inc. bootstrap) Informal-comparative vague Homology, untangling funct/dev correlation form phylogenetic signal Non-statistical Selection criterion Character analysis Informal-comp like the wily old policemen who draws on common sense and gut instinct Algorithmic morphology is the new recruit with the fancy computer (garbage in, garbage out) Hypothesis testing 25 25

How do these data / methods perform? One test would be whether or not they reject the molecular consensus - not helpful … Hypothesis testing is difficult with distance methods like DNA hybridization and impossible with informal-comparative morphology Alternative: Likelihood disadvantage on the 20,654 nucleotide molecular matrix for a fairer comparison of data / methods Example: –lnL(consensus) = 121,316.3 –lnL(DNA hybridization tree) = 121,438.2 lnL disadvantage = 121.9 26

Likelihood disadvantages Mt sequence analyses 84.4 Albumin M’CF 182.4 Single nuclear genes 96.0 DNA hybridization 121.9 Informal-comparative morphology 71.7 Algorithmic morphology (MP) 690.1 In the present case likelihood and Bayesian methods are not providing improvements on parsimony. Informal-comparative provides hope Algorithmic morphology morphol352 (MP/ML) 594.6 Algorithmic morphology morphol352 (Bayes) 617.5 27

* Do the algorithmic analyses just suffer from stochastic blindness? Scaled the molecular-dated marsupial tree to the treelength of the morphol352 ML tree Simulated 60,000 character “pseudomorphological” dataset, Sim352 in Seq-gen (JC, equivalent to Mk4). 1000 boots, 352 chs Vombatidae Phascolarctidae Pseudocheiridae Burramyidae Phalangeridae Macropodidae Acrobatidae Tarsipedidae Petauridae Hypsiprymnodontidae 95 100 87 73 61 53 74 * 5 outgroup taxa 28 28

Algorithmic morphology Vombatidae Molecular consensus Phascolarctidae Acrobatidae Tarsipedidae Phascolarctidae Pseudoch’idae Phalangeridae Acrobatidae Tarsipedidae Vombatidae Burramyidae Macropodidae Petauridae Algorithmic morphology Petauridae Pseudocheiridae Macropodidae Phalangeridae Burramyidae 29 29

Can we mimic the real morphological data by combining molecular phylogenetic and ecological signals ? 60,000 characters 5 outgroup taxa Vombatidae Size Diet Phascolarctidae Sim352 phylogenetic signal as per the molecular dated tree, scaled to morphol352 treelength Acrobatidae 0 = <50g 0 = herb Tarsipedidae 1 = 50-200g 1 = sub-herb 2 = 200-800g 2 = omniv Petauridae 3 = 800g-3kg 3 = sub-carn Pseudocheiridae Start with just the the phylogenetic signal, then progressively multiply out the contribution from the size and diet character 4 = 3-12kg 4 = carn Macropodidae 5 = >12kg Phalangeridae Burramyidae ordered states 30 30

Optimum fit to the algorithmic morphology tree (9% ecol. cont.) Optimum fit to the molecular consensus tree (0% ecological contribution) Optimum fit to the algorithmic morphology tree (9% ecol. cont.) 2 4 % MP tree length disadvantage 6 8 10 8 16 24 32 % ecological contribution to MP tree length 31 31

Algorithmic morphology Vombatidae Molecular consensus Phascolarctidae Acrobatidae Phylo-ecol sim Tarsipedidae Phascolarctidae Pseudoch’idae Phalangeridae Acrobatidae Tarsipedidae Vombatidae Burramyidae Macropodidae Petauridae Algorithmic morphology Petauridae Pseudocheiridae Macropodidae Phalangeridae Burramyidae Phylogenetic randomization test P-value = 0.00016 32 32

Tempting next move: Reverse engineered phylogeny If the algorithmic morphology (morphol352) data is effectively 91% phylogenetic signal, 9% ecological signal … what if we subtract the 9% ecological signal from the observed signal? a. MP on morphol352 741 steps 782 steps Alg. Morphol. tree “True” tree b. MP on diet+size: 14 steps 26 steps c. Ave. over 9% “true” TL 61.8 steps 114.7 steps c. Rev Eng Phylogeny (a-c) 679.2 steps 667.3 steps 33 33

Improvements Co-inferring the relative weightings of the ecological correlates simultaneously with the relative apparent contributions of phylogenetic and ecological signal Searching tree space for the reverse engineered phylogeny - current phylogenetic programs are well set up for addition of log-likelihoods (e.g. for partitioned data), but not for subtraction Size and diet were equally weighted in this study 34 34

Molecular tree is employed in the discrimination of apparent phylogenetic and ecological signals - so has some influence on the reverse engineered phylogeny. Microraptor However, the ultimate aim here is the placement of fossils. The correction for ecological signal (inferred with extant taxa) can be employed for fossil taxa, independent of their DNA the ultimate aim here…is assistance with marcoevolutionary questions, like Whether flight in birds involve a 4-winnged phase? And what role did competition play in the early history of our mammalian lineage? Morphological phylogeny is critical here. Eomaia 35 35

>99% of all species are extinct Their fossils provide the only direct evidence for answering many key questions in macroecology and macroevolution and for calibrating molecular timescales 36 36

Acknowledgements Kate Loynes (ANU, PhD student) Emily Lake (ANU, Honours student) Australian Research Council 37 37