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

2. 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.

3. 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

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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 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

13. 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

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

15. 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.

16. 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

17. 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)

18. 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)

19. 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)

20. 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)

21. 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

22. 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

23. 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

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

25. 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

26. 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

27. Likelihood disadvantages
Mt sequence analyses
Albumin M’CF
Single nuclear genes
DNA hybridization
Informal-comparative morphology
Algorithmic morphology (MP)
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

28. * 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) 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

29. 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

30. 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 = g
1 = sub-herb
2 = g
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

31. 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

32. 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 = 32 32

33. 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 morphol steps steps
Alg. Morphol. tree “True” tree
b. MP on diet+size: steps steps
c. Ave. over 9% “true” TL steps steps
c. Rev Eng Phylogeny (a-c) steps steps 33 33

34. 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

35. 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

36. >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

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