Supporting Information

Steiper and Seiffert 10.1073/pnas.1119506109 SI Text trices using Mesquite version 2.72 (11), and supertrees were Phylogeny Reconstruction. Comprehensive, taxon-rich calculated using the heuristic search option in PAUP* 4.0b10 molecular phylogenies are available for extant [e.g., across 5,000 replicates. Perelman et al. (1)], but phylogenetic estimates for extinct pri- Tests of trait also require that the phylogeny be time- mates tend to be much more restricted in their taxonomic scaled. A time-scaled phylogeny is easily generated for extant taxa sampling [e.g., living and extinct platyrrhine anthropoids (2) and from molecular clock analyses; however, for this analysis, living and extinct catarrhine anthropoids (3)]. Because a com- taxa were also required to be part of this time-scaled phylogeny. prehensive morphological phylogenetic analysis of the entire Although most have at least an approximate date associ- primate radiation is not available, we used a supertree approach ated with them, there is no simple method for generating the age [using matrix representation with parsimony (MRP) (4)] to ob- for the last common ancestors of fossil taxa. For example, whereas tain a broad estimate of relationships among living and extinct africanus has a last common ancestor with hu- primates. We combined results from four different studies into mans at some point along the hominin branch (12), it is not a composite taxon-rich phylogeny that included 62 extant pri- currently possible to determine precisely when this last common mate genera and 123 extinct primate . We placed par- ancestor existed, despite having a date for A. africanus fossils. ticular emphasis on sampling members of the early phases of Acknowledging these difficulties and uncertainties, we re- primate evolution, because it is the deepest nodes of primate constructed a time-calibrated phylogeny that included fossil and phylogeny that exhibit the greatest disagreement between mo- extant primates using the following rules: lecular and fossil evidence for divergence times. The molecular i) Divergence dates among extant genera are based on Perel- dating analysis also required that relationships among extant – taxa be the same as those recovered by Perelman et al. (1), so the man et al. (1) from their tables 1 3. only morphology-based trees that could be used in the MRP ii) Internodes along stem lineages were distributed by equally analysis were those that were congruent with their study. Rossie dividing stem-lineage lengths by the number of extinct and MacLatchy’s (3) analysis of -to-Recent catarrhines clades that branch off from that stem lineage. Similarly, for terminal branches, branch lengths were equally divided (i.e., the tree in their figure 8) recovered relationships among for each extinct clade that connects to it. For example, to extant catarrhines that are consistent with the Perelman et al. (1) connect A. africanus to the Homo lineage, we divided the phylogeny, and so did not require modification. In the remaining Homo lineage (6.6 Ma) into two equal-length branches (3.3 two cases, the trees we included were based on morphological Ma) and connected the A. africanus branch to this midpoint. phylogenetic analyses that were constrained by a molecular iii) Fossil species were placed at their currently estimated age “scaffold” (5). For living and extinct platyrrhines, we included on the geological timescale, with ages rounded to the near- Kay et al.’s (2) analysis that was constrained to fit a molecular est 1 Ma. For example, A. africanus is dated to ∼2 Ma (13). scaffold (i.e., the tree in their figure 20A). For both the Rossie Because A. africanus connects to the Homo stem lineage at and MacLatchy (3) and Kay et al. (2) trees, we used results that 3.3 Ma, this requires a 1.3-Ma–long terminal branch to were derived from runs that included some ordered multistate connect A. africanus to the Homo branch. characters to maintain as much methodological consistency as iv) For extinct clades and extinct species, branch lengths were possible across these disparate datasets. For the remaining living distributed in such a way that terminal species branches and extinct primates (plesiadapiforms, strepsirrhines, adapi- and internodes were assigned, at minimum, a length of 2 forms, omomyiforms, tarsiids, and stem and early crown an- Ma [unless extinct taxa were too ancient, based on the thropoids), we used the matrix of Boyer et al. (6), which was divergence dates calculated for extant taxa by Perelman reanalyzed with a backbone constraint of extant taxa based on et al. (1)] to allow for 2-Ma internodes. One such case is the relationships recovered by Perelman et al. (1). The matrix the parapithecoid-proteopithecid clade, within which some was analyzed with some multistate characters ordered and internodes were assigned lengths shorter than 2 Ma early scaled, and with reacquisition not allowed [see also in their phylogeny to accommodate their placement within Boyer et al. (6)]. The matrix was analyzed with the heuristic crown Anthropoidea as sister taxa of Platyrrhini; another is search option in PAUP* 4.0b10 (7) across 5,000 replicates, with Saharagalago, which is too old for internodes along the a random addition sequence and tree bisection and reconnection galagid stem lineage to be distributed equally. branch swapping. Three highly fragmentary taxa (Loveina min- v) Polytomies were broken up by resolving them with very uta, L. sheai, and L. wapiteinsis) and two more complete taxa short branch lengths (0.01 Ma). (Rooneyia viejaensis and Plesiopithecus teras) were excluded be- cause these species have proven to be particularly unstable given This method generated a time-calibrated phylogeny of extant different assumptions about character evolution and the rela- genera and extinct species (Fig. S2A). tionships of extant taxa [see Boyer et al. (6) and Seiffert et al. (8– This phylogeny was used in the analyses of body size (BS) 10), which are based on the same core character-taxon matrix, evolution. The analyses of absolute endocranial volume (EV) and with minor modifications], and we considered it preferable for relative endocranial volume (REV) required a different tree for these unstable taxa to not have a major influence on the phy- two reasons. First, most primate fossil species do not preserve logeny used for ancestral body mass calculation. The Eocene crania. Second, there are some extinct primates for which EV can sivaladapids Hoanghonius and Wailekia were included in the be reconstructed that have not been placed in a phylogeny using phylogenetic analysis but could not be used in the reconstruction parsimony analysis of character data (e.g., Chilecebus). Because of ancestral states for body mass because m1 measurements are so few fossil primate crania are available, it was nevertheless either not available (Wailekia) or unpublished (Hoanghonius). critical to include as many of these specimens as possible into the Finally, the -level phylogeny of Perelman et al. (1) (their time-scaled phylogeny. To generate a time-scaled phylogeny for figure 1) was integrated into the supertree. Strict consensus trees these analyses, the BS tree was pruned of fossil taxa that do not from each of these four studies were converted into MRP ma- preserve crania. Subsequently, the following specimens were

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 1of15 added to the pruned supertree as follows: A. africanus was linked 29.745, κ; 26.446, λ; 26.534, δλ; 30.008, δκ; 26.885, κλ; 27.935, to the Homo branch (12); Oreopithecus was linked to the great δλκ. A model with no scaling factors was compared with each stem (14); Chilecebus was placed halfway along the platyr- scaling factor individually (none vs. λ, none vs. κ, none vs. δ); the rhine stem lineage, based in part on its small relative , BFs showed that both the λ and κ parameters improved the which apparently falls outside the range of all extant platyrrhines model, especially κ, which had the highest harmonic mean (15); Mioeuoticus was placed in a polytomy at the base of crown likelihood and a BF of 10.24 (Table S9). Comparing the κ model Lorisiformes using a very small branch to approximate a tri- with models in which two and three parameters were used (κ vs. chotomy (16) (our method requires bifurcating trees); the no- δλ, κ vs. δκ, κ vs. κλ, κ vs. δκλ) showed that the κ-only model still tharctid adapiforms Smilodectes and Notharctus were linked to had the best fit. Given this analysis of BFs, the preferred model the notharctid Cantius as a sister taxon to Pronycticebus (17). for the regression analysis was a model that included the κ pa- Ignacius was alternatively placed as a sister taxon to Plesiadapis rameter (posterior mean = 0.31). The average values for the (18) or as the most basal taxon in a paraphyletic plesiadapiform phylogenetically corrected regression slope and intercept yielded group (19). The monophyletic plesiadapiform phylogram the equation EV = 0.670 × BS − 1.274. is presented in Fig. S2B, and both tree files are presented in The within-directional model BFs were compared for these SI Appendix. REV data. The directional model with no scaling factors was compared with each scaling factor individually (none vs. λ, none Computation of Bayes Factors. Models were compared using Bayes vs. κ, none vs. δ). Here the BFs showed that the κ and λ pa- factors (BFs) as described in the main text. Note that in our rameters improved the model, with BFs of 11.28 and 11.30, re- reporting of the Bayes factors, for consistency we are reporting spectively (Table S6). Comparing the κ and λ models with negative values where more complex models have lower like- models where two or three parameters were used (κ vs. δλ, κ vs. lihoods, effectively 2 × (log[harmonic mean(more complex δκ, κ vs. κλ, κ vs. δκλ) showed that the κλ model had the best fit, model)] − log[harmonic mean(less complex model)]). Harmonic with a BF of ∼3.7 over the model with only κ or λ. Given this mean likelihoods are in Table 1 in the main text. analysis of BFs, the preferred model for the REV data was Brownian versus directional model. First, the Bayes factors between a directional model that included the κ and λ parameters the Brownian and directional models were compared. In 23 of the (κ posterior mean = 0.69 and λ posterior mean = 0.84). 24 permutations of scaling parameters, the directional model was a better fit (Table S3). In the EV model that incorporated scaling Analysis of Molecular Rates. DNA-sequence alignments. Four large parameters δ and κ, the directional and Brownian models were DNA-sequence datasets were compiled to use in molecular rate equivalent, but these models making up this comparison did not analyses: codon third positions from 1,078 genome-wide tran- have very high overall likelihoods relative to all of the other scripts (22); a genome-wide sampling of regions (1); the CYP7A1 models and therefore were not in contention for one of the region (23); and the CFTR region (24). preferred overall models. Given these BFs, we conclude that the The alignment from Jameson et al. (22) was 422,687-bp long directional model is the preferred model for the BS, EV, and and included eight primate genera and it was reduced to include REV datasets. only a rabbit outgroup. The alignment from Perelman et al. (1) Body-size Bayes factors. The within-directional model BFs were was trimmed to only include autosomal regions. Within each compared for BS data using the directional model. The di- genus one sequence was chosen, the one with the most base pairs rectional model with no scaling factors was compared with each of coverage. The resulting alignment was 27,436 bp long and in- scaling factor individually (none vs. λ, none vs. κ, none vs. δ) for cluded 61 primate genera and a rabbit outgroup. The CYP7A1 the BS data. Here, the BFs showed that both the λ and κ pa- region is based on an alignment analyzed by Wilkinson et al. (23). rameters improved the model, especially κ, which had the A number of primate sequences were added to this dataset to highest harmonic mean likelihood and a BF of 34.12 (Table S4). generate a more taxon-rich alignment. The same sequences were Comparing the κ model to models where two or three parame- used for , Macaca, Pongo, Saimiri, Callithrix, Colobus, Papio, ters were used (κ vs. δλ, κ vs. δκ, κ vs. κλ, κ vs. δκλ) showed that Lemur, and Aotus. The sequence was updated to reflect the κ model still had the best fit because its likelihood was ab- the new genome release (hg19, chromosome 8:59363188– solutely higher. Given this analysis of BFs, the preferred model 59442859). Subsequently, the human sequence was used to obtain for the BS data was a directional model that included the κ sequences from the Ensembl database (25) via the alignment tool parameter (posterior mean = 0.32). for Tarsius, Otolemur, Gorilla, and Microcebus. The rabbit se- Endocranial volume Bayes factors. The within-directional model BFs quence was obtained as an outgroup (oryCun2, chromosome were compared for EV data using the directional model. The 3:73890431–74009250) from the University of California, Santa directional model with no scaling factors was compared with each Cruz Genome Browser (26). All of the Ns, gaps, and unknown scaling factor individually (none vs. λ, none vs. κ, none vs. δ). regions were removed from the Ensembl sequences. All se- Here the BFs showed that only the κ parameter improved the quences were masked to lowercase using RepeatMasker (27). An model, with a BF of 11.12 (Table S5). Comparing the κ model alignment was conducted with TBA (28), using the tree based on with models where two or three parameters were used (κ vs. δλ, κ the phylogeny above and the specifications Y = 3,400, H = 2,000, vs. δκ, κ vs. κλ, κ vs. δκλ) showed that the κ model still had the B = 2, C = 0. The resulting MAF file was converted to a FASTA best fit because its likelihood was absolutely higher. Given this file using the Galaxy web server (29, 30). The final alignment analysis of BFs, the preferred model for the EV data was a included 14 primate genera and was 21,478 bp long. The align- directional model that included the κ parameter (posterior ment of the CFTR region is based on primate data and the rabbit mean = 0.32). outgroup from Prasad et al. (24). These sequences were aligned Relative endocranial volume Bayes factors. To generate the REV with TBA (28), using the tree based on the phylogeny above and dataset, we used residuals from a phylogenetically corrected the specifications Y = 3,400, H = 2,000, B = 2, C = 0. The re- least-squares regression of EV on BS following the approach of sulting MAF file was converted to a FASTA file using Galaxy (29, Montgomery et al. (20). To generate a regression formula in 30). The final CFTR alignment included 16 primate genera and BayesTraits (21), we needed to use the best model of trait evo- was 5,573,099 bp long. lution. To do this, we compared BFs from the Brownian model Molecular clock analysis. To generate molecular rates for these (the only available model for regression analysis) incorporating datasets, a molecular clock analyss using “soft-bounded calibra- all permutations of the δ, λ, and κ parameters. The final har- tions” was conducted on each of the datasets individually using monic mean likelihoods were 24.623, no parameters; 23.591, δ; the relaxed clock mcmctree program (31–33) with the approxi-

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 2of15 mate-likelihood implementation (due to the large size of the rich Perelman et al. (1) analysis, the crown Lorisiformes node DNA-sequence datasets). Branch lengths were estimated using was constrained to be older than 20 Ma (16). To generate a weak the HKY+Γ5 model (34, 35). In the analyses, substitution rates upper bound, this calibration was a truncated Cauchy distribu- were assumed to drift among lineages, that is, a relaxed molec- tion (39) with P = 0.1 and c = 0.5. The roots of the phylogenies ular clock using a geometric Brownian-motion model for rate were constrained to be less than 80 Ma. Each run had a 100,000- change (31). The prior for the rate at the root was assigned the step burnin followed by a 25 million-step run, sampled every − gamma prior G(0.05, 0.5), which corresponds to a rate of 10 9 500th step. Acceptance rates were tuned to between 15% and − and an SD of 2 × 10 9. A model of correlated rate change among 40%. Convergence of these analyses was assessed by examining lineages was used. The rate-drift parameter (σ2) was assigned the the effective sample size values (40) and the concordance be- gamma prior G(1, 10). The prior for times is generated from the tween two independent runs. These analyses generated an “un- birth–death process with sampling, given parameters λ = μ =1 corrected” molecular clock rate for each lineage for each gene and ρ = 0 (31). The time unit used was 100 Ma. For all four and a dated molecular phylogeny (Fig. S1 and SI Appendix). analyses, trees were calibrated at the Homo/Pan and Papio/ The time dependency of molecular rates (41–43) is not an issue Macaca divergences using bounds from 6 to 8 Ma ago based on for these rate estimates for two reasons. First, this effect has only dates for the earliest hominins (36, 37) and macaques (38). been shown to occur in mitochondrial data, which we do not These bounds had a hard lower bound at 6 Ma and a “soft” analyze here. Second, this effect only occurs over recent esti- upper bound at 8 Ma, where there was a limited probability mates, that is, <2 Ma. All of our divergences are >2 Ma, mostly (2.5%) that the age estimate was older than 8 Ma. In the taxon- substantially.

1. Perelman P, et al. (2011) A molecular phylogeny of living primates. PLoS Genet 7: 26. Kent WJ, et al. (2002) The human genome browser at UCSC. Genome Res 12: e1001342. 996–1006. 2. Kay RF, et al. (2008) The anatomy of Dolichocebus gaimanensis, a stem platyrrhine 27. Smit AFA, Green P, Hubley R (1996–2004) RepeatMasker Open-3.0 (http://www. from Argentina. J Hum Evol 54:323–382. repeatmasker.org). 3. Rossie JB, MacLatchy L (2006) A new pliopithecoid genus from the early of 28. Blanchette M, et al. (2004) Aligning multiple genomic sequences with the threaded Uganda. J Hum Evol 50:568–586. blockset aligner. Genome Res 14:708–715. 4. Bininda-Emonds OR, Bryant HN (1998) Properties of matrix representation with 29. Blankenberg D, et al. (2010) Galaxy: A web-based genome analysis tool for parsimony analyses. Syst Biol 47:497–508. experimentalists. Curr Protoc Mol Biol 89:19.10.1–19.10.21. 5. Springer MS, Teeling EC, Madsen O, Stanhope MJ, de Jong WW (2001) Integrated fossil 30. Goecks J, Nekrutenko A, Taylor J; Galaxy Team (2010) Galaxy: A comprehensive and molecular data reconstruct bat echolocation. Proc Natl Acad Sci USA 98:6241–6246. approach for supporting accessible, reproducible, and transparent computational 6. Boyer DM, Seiffert ER, Simons EL (2010) Astragalar morphology of Afradapis, a large research in the life sciences. Genome Biol 11:R86. adapiform primate from the earliest late Eocene of Egypt. Am J Phys Anthropol 143: 31. Rannala B, Yang Z (2007) Inferring speciation times under an episodic molecular clock. 383–402. Syst Biol 56:453–466. 7. Swofford DL (2001) PAUP*. Phylogenetic Analysis Using Parsimony (* and Other 32. Yang Z (2007) PAML 4: Phylogenetic analysis by maximum likelihood. Mol Biol Evol Methods) (Sinauer Associates, Sunderland, MA), Version 4. 24:1586–1591. 8. Seiffert ER, Perry JM, Simons EL, Boyer DM (2009) Convergent evolution of 33. Yang Z, Rannala B (2006) Bayesian estimation of species divergence times under anthropoid-like adaptations in Eocene adapiform primates. Nature 461:1118–1121. a molecular clock using multiple fossil calibrations with soft bounds. Mol Biol Evol 23: 9. Seiffert ER, et al. (2010) A fossil primate of uncertain affinities from the earliest late 212–226. Eocene of Egypt. Proc Natl Acad Sci USA 107:9712–9717. 34. Hasegawa M, Kishino H, Yano T (1985) Dating of the human-ape splitting by 10. Seiffert ER, et al. (2005) Basal anthropoids from Egypt and the antiquity of Africa’s a molecular clock of mitochondrial DNA. J Mol Evol 22(2):160–174. higher primate radiation. Science 310:300–304. 35. Yang Z (1994) Maximum likelihood phylogenetic estimation from DNA sequences 11. Maddison WP, Maddison DR (2010) Mesquite: A modular system for evolutionary with variable rates over sites: Approximate methods. J Mol Evol 39:306–314. analysis (http://mesquiteproject.org), Version 2.73. 36. Lebatard AE, et al. (2008) Cosmogenic nuclide dating of Sahelanthropus tchadensis 12. Strait DS, Grine FE, Moniz MA (1997) A reappraisal of early hominid phylogeny. J Hum and Australopithecus bahrelghazali: Mio-Pliocene hominids from Chad. Proc Natl Evol 32(1):17–82. Acad Sci USA 105:3226–3231. 13. Herries AI, Shaw J (2011) Palaeomagnetic analysis of the Sterkfontein palaeocave 37. Vignaud P, et al. (2002) Geology and palaeontology of the Upper Miocene Toros- deposits: Implications for the age of the hominin fossils and stone tool industries. J Menalla hominid locality, Chad. Nature 418(6894):152–155. Hum Evol 60:523–539. 38. Moyà-Solà S, Köhler M, Alba DM, Casanovas-Vilar I, Galindo J (2004) Pierolapithecus 14. Begun DR, Ward CV, Rose MD (1997) Events in hominoid evolution. Function, catalaunicus, a new Middle Miocene great ape from Spain. Science 306:1339–1344. Phylogeny, and Fossils: Miocene Hominoid Evolution and Adaptations, eds Begun DR, 39. Inoue J, Donoghue PC, Yang Z (2010) The impact of the representation of fossil Ward CV, Rose MD (Plenum, New York), pp 389–415. calibrations on Bayesian estimation of species divergence times. Syst Biol 59(1):74–89. 15. Sears KE, Finarelli JA, Flynn JJ, Wyss AR (2008) Estimating body mass in New World 40. Rambaut A, Drummond AJ (2007) Tracer (http://beast.bio.ed.ac.uk/Tracer), Version “monkeys” (Platyrrhini, Primates), with a consideration of the Miocene platyrrhine, 1.4. Chilecebus carrascoensis. Am Mus Novit 3617:1–29. 41. Ho SY, Phillips MJ, Cooper A, Drummond AJ (2005) Time dependency of molecular 16. Seiffert ER (2007) Early evolution and biogeography of lorisiform strepsirrhines. Am J rate estimates and systematic overestimation of recent divergence times. Mol Biol Primatol 69(1):27–35. Evol 22:1561–1568. 17. Gunnell GF (2002) Notharctine primates () from the early to middle 42. Ho SY, Shapiro B, Phillips MJ, Cooper A, Drummond AJ (2007) Evidence for time Eocene (Wasatchian-Bridgerian) of Wyoming: Transitional species and the origins of dependency of molecular rate estimates. Syst Biol 56:515–522. Notharctus and Smilodectes. J Hum Evol 43:353–380. 43. Emerson BC (2007) Alarm bells for the molecular clock? No support for Ho et al.’s 18. Silcox MT (2001) A phylogenetic analysis of Plesiadapiformes and their relationship to model of time-dependent molecular rate estimates. Syst Biol 56:337–345. Euprimates and other Archontans. PhD dissertation (Johns Hopkins Univ School of 44. Steiper ME, Young NM (2006) Primate molecular divergence dates. Mol Phylogenet Medicine, Baltimore). Evol 41:384–394. 19. Bloch JI, Silcox MT, Boyer DM, Sargis EJ (2007) New Paleocene skeletons and the 45. Fabre PH, Rodrigues A, Douzery EJ (2009) Patterns of macroevolution among relationship of plesiadapiforms to crown-clade primates. Proc Natl Acad Sci USA 104: primates inferred from a supermatrix of mitochondrial and nuclear DNA. Mol 1159–1164. Phylogenet Evol 53:808–825. 20. Pagel M, Meade A (2011) BayesTraits (Univ of Reading, Reading, UK) Version 1.0. 46. Bininda-Emonds OR, et al. (2007) The delayed rise of present-day . Nature 21. Montgomery SH, Capellini I, Barton RA, Mundy NI (2010) Reconstructing the ups and 446:507–512. downs of primate brain evolution: Implications for adaptive hypotheses and Homo 47. Conroy GC (1987) Problems of body-weight estimation in fossil primates. Int J floresiensis. BMC Biol 8:9. Primatol 8(2):115–137. 22. Jameson NM, et al. (2011) Genomic data reject the hypothesis of a prosimian primate 48. Smith RJ, Jungers WL (1997) Body mass in comparative primatology. J Hum Evol 32: clade. J Hum Evol 61:295–305. 523–559. 23. Wilkinson RD, et al. (2011) Dating primate divergences through an integrated analysis 49. Kirk EC (2006) Visual influences on primate encephalization. J Hum Evol 51(1):76–90. of palaeontological and molecular data. Syst Biol 60(1):16–31. 50. Silcox MT, Dalmyn CK, Bloch JI (2009) Virtual endocast of Ignacius graybullianus 24. Prasad AB, Allard MW, Green ED; NISC Comparative Sequencing Program (2008) (Paromomyidae, Primates) and brain evolution in early primates. Proc Natl Acad Sci Confirming the phylogeny of mammals by use of large comparative sequence data USA 106:10987–10992. sets. Mol Biol Evol 25:1795–1808. 51. Wood B, Collard M (1999) The human genus. Science 284(5411):65–71. 25. Flicek P, et al. (2011) Ensembl 2011. Nucleic Acids Res 39(Database issue):D800– 52. Benefit BR, McCrossin ML (1997) Earliest known . Nature 388: D806. 368–371.

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 3of15 Fig. S1. Final ultrametric corrected trees. CYP, CYP7A1 (1); JAM, Jameson et al. (2); PER, Perelman et al. (3); PRA, CFTR alignment of data from Prasad et al. (22).

1. Wilkinson RD, et al. (2011) Dating primate divergences through an integrated analysis of palaeontological and molecular data. Syst Biol 60(1):16–31. 2. Pagel M, Meade A (2011) BayesTraits (Univ of Reading, Reading, UK) Version 1.0 3. Perelman P, et al. (2011) A molecular phylogeny of living primates. PLoS Genet 7:e1001342.

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 4of15 A

o

m

o

s

r

u

u

c

p

e

i

t

h

h

t

i

e

p

c

o

u

i

l

s

ropithecus

ur

B

Fig. S2. Phylogenetic supertrees used in BS analysis (A) and EV and REV analysis (B). Extant taxa are indicated by red text. Tree scaled to Ma.

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 5of15 to (node 30) 86 Cercopithecus l’hoesti group Donrussellia gallica 85 Erythrocebus 3 to (node 4) 84 Parapithecus grangeri 1 Panobius russelli Chlorocebus Afradapis longicristatus 82 Allenopithecus Chilecebus 31 Caenopithecus lemuroides 83 Cercopithecus 36 Cacajao 2 Aframonius dieides 81 Miopithecus 35 Chiropotes masillae Macaca 32 34 Pithecia Cercocebus Mahgarita stevensi 87 89 Callicebus Mandrillus Europolemur klatti 88 40 Lagothrix 74 Theropithecus Godinotia neglecta 90 33 39 Brachyteles 3 91 Lophocebus Microadapis sciureus 38 Ateles Papio 2 Adapis parisiensis 76 Colobus Alouatta Leptadapis magnus 37 75 Piliocolobus 42 Cebus Protoadapis curvicuspidens 73 Presbytis Saimiri 77 41 Cantius abditus Trachypithecus/Semnopithecus Aotus 78 43 Pronycticebus gaudryi 79 Rhinopithecus Saguinus Nasalis 44 Rencunius zhoui 80 Leontopithecus Pygathrix 45 4 Asiadapis cambayensis Callimico Marcgodinotius indicus Victoriapithecus 46 heseloni 47 Cebuella Anchomomys gaillardi Callithrix Anchomomys milleri Limnopithecus evansi Tarsius 5 Djebelemur martinezi 1 48 Kalepithecus songhorensis Necrolemur Galago senegalensis group 18 Limnopithecus legetet Tetonius 6 17 Otolemur clarki Smilodectes gracilis 16 Galagoides Simiolus Notharctus tenebrosus 15 Komba robustus 67¶ macinessi Pronycticebus gaudryi 7 14 Wadilemur elegans Equatorius africanus Leptadapis magnus Saharagalago misrensis 9 69§ Adapis parisiensis 11 Arctocebus Symphalangus Nomascus Nycticebus Perodicticus 68 53 10 Pongo 52 Nycticebus 70 12 Gorilla 49 Perodicticus 8 Loris 71 54 13 72 Homo Arctocebus Nycticeboides simpsoni 51¥ 66 Pan Galagoides Karanisia clarki Rangwapithecus gordoni 55 56 Otolemur Daubentonia Nyanzapithecus vancouveringorum 19 Galago senegalensis group 24 Hapalemur Nyanzapithecus harrisoni 50 Mioeuoticus 20 23 Lemur Nyanzapithecus pick fordi Daubentonia 22 Eulemur Proconsul africanus Hapalemur Varecia 65 Proconsul major 61 21 Dionysopithecus 60 Lemur 26 Avahi 57 Laccopithecus 59 Propithecus Eulemur 25 Lepilemur Varecia 27 Epipliopithecus 58 Cheirogaleus 63 Avahi 28 Lomorupithecus Microcebus Propithecus 29 64 Moeripithecus markgrafi 62 Lepilemur Mirza Taqah propliopithecid 64 Cheirogaleus to Catarrhini (node 64) haeck eli 65 Apidium moustafai zeuxis 66 Microcebus Apidium phiomense Propliopithecus chirobates Mirza Parapithecus fraasi Catopithecus browni Parapithecus grangeri Oligopithecus rogeri 13 Papio Qatrania wingi Oligopithecus savagei 12 Lophocebus 44 Abuqatrania basiodontos Biretia fayumensis 11 Theropithecus Biretia megalopsis to Anthropoidea (node 38) 10 14 Cercocebus Arsinoea kallimos Teilhardina asiatica Mandrillus Serapia eocaena Teilhardina belgica Proteopithecus sylviae 9 Macaca Loveina zephryi 45 Branisella boliviana 30 16 Miopithecus Carlocebus carmenensis Shoshonius cooperi 15 Cercopithecus Dolichocebus gaimanensis Washak ius insignis 46 Soriacebus ameghinorum Allenopithecus Dyseolemur pacificus 8 17 51 Cacajao 36 18 Erythrocebus 50 Tarsius Chiropotes 31 Chlorocebus 47 Pithecia 37* Phileosimias kamali 49† 35 Piliocolobus Proteropithecia Xanthorhysis tabrumi 20 Callicebus 43 Hemiacodon gracilis Colobus Brachyteles 34 19 48 55 7 Presbytis 54 Lagothrix 33 Macrotarsius montanus 21 53 Ateles Omomys sp. 22 Trachypithecus/Semnopithecus Alouatta Steinius vespertinus 23 Nasalis 52 Cebus 57 32 Teilhardina americana Pygathrix Saimiri 56 Aotus Absarokius sp. Victoriapithecus 58 Saguinus Anaptomorphus sp. 42 25 Symphalangus 59 Leontopithecus Aycrossia lovei Hylobates 60 Callimico 24 61 Strigorhysis sp. Callithrix Oreopithecus bambolii 62 Tetonius sp. 26 63 Cebuella 6£ Pongo 41 Mico Arapahovius gazini 27 Gorilla Siamopithecus eocaenus Tetonoides sp. 28 Amphipithecus mogaungensis Pan Anemorhysis savagei 5 29 Pondaungia cotteri Australopithecus africanus 40 Bugtipithecus inexpectans Trogolemur myodes 30 Homo Bahinia pondaungensis Pseudoloris parvulus 4 Phenacopithecus xueshii Proconsul africanus 39 Microchoerus erinaceus Eosimias centennicus Aegyptopithecus zeuxis Eosimias sinensis Necrolemur spp. 38 Afrotarsius spp. Nannopithex abderhaldeni Catopithecus browni Altiatlasius k oulchii Nannopithex raabi Uintanius ameghini

Fig. S3. Key to ancestral reconstructions in Tables S7 and S8. The numbers at the nodes of the four trees to the left of the divider correspond to the first column of Table S7 (Reconstructed ancestral trait values for BS). The numbers at the nodes of the two trees to the right of the divider correspond to the first column of Table S8 (Reconstructed ancestral trait values for EV and REV). Trees are not to scale. Scaled trees are found in Fig. S2.

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 6of15 Table S1. Divergence dates from recent molecular clock studies Jameson Steiper and Fabre Wilkinson Perelman Bininda-Emonds † ‡ Node et al. (20)* Young (44) et al. (45) et al. (23)§ et al. (1) et al. (46) Average

Crown Primate Estimate 72.6 77.5 82.2 84.5 87.2 87.7 81.9 Low 69.6 65.9 — 69.2 75.9 85.2 73.2 High 76.9 93.2 — 103.5 98.6 90.4 92.5 Crown Haplorhini Estimate 68.6 — 74.5 — 81.3 85 77.3 Low 65.6 ———69.5 81.8 72.3 High 72.7 ———95.8 88.3 85.6 Crown Estimate 52.4 57.1 71.9 49.8 68.7 75.5 62.6 Low 47 48 — 35.9 58.8 71.4 52.2 High 57.2 68.7 — 72 76.6 79.6 70.8 Crown Anthropoidea Estimate 40 42.9 39.8 47.2 43.5 54.1 44.6 Low 37.3 36.1 — 38.9 38.6 49.8 40.1 High 43.1 51.1 — 56.5 48.4 58.6 51.5 Crown Catarrhini Estimate 25.4 30.5 25 31 31.6 36.6 30 Low 23.7 25.9 — 25.1 25.7 33.9 26.9 High 27.6 35.8 — 37.7 37.9 39.5 35.7 Crown Platyrrhini Estimate — 20.8 15.9 25.1 24.8 24.5 22.2 Low — 16.5 — 20.1 20.6 21.5 19.7 High — 26 — 31 29.3 28.3 28.6 Aotus/Cebus/Saimiri/ Estimate — 17.1 12.8 20.5 20 21 18.3 Callithrix Low — 13.3 — 16.3 15.7 17.7 15.7 High — 21.8 — 25.3 24 24.5 23.9 Crown Estimate ——14.5 14.1 17.6 21.6 16.9 Cercopithecoidea Low ———11 13.9 18.7 14.5 High ———17.7 21.5 24.6 21.3 Homo/Pongo Estimate 18 18.3 15.4 19.2 16.5 19.7 17.9 Low 16.8 16.1 — 15.1 13.5 18.5 16 High 19.6 20.8 — 24.1 19.7 21 21

—, not determined. *Traditional estimates. † Calibration interval estimates. ‡ Tree 4. §Poisson estimates.

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 7of15 Table S2. BS, EV, and REV data for living and extinct species

BS: log10 log10 body-size EV: log10 endocranial log10 endocranial REV: endocranial Taxon body size (g) (g) source volume (cm3) volume (cm3) source volume residual

Absarokius sp. 2.32015 1 ——— Abuqatrania basiodontos 2.53275 1 ——— Adapis parisiensis 3.37107 4 0.94448 4 −0.03596 Aegyptopithecus zeuxis 3.82672 4 1.53656 4 0.25362 Afradapis longicristatus 3.51348 1 ——— Aframonius dieides 3.10551 1 ——— Afrotarsius spp. 2.33445 1 ——— Allenopithecus 3.66792 3 1.77137 3 0.59386 Alouatta 3.78533 3 1.74386 3 0.48841 Altanius orlovi 1.32222 1 ——— Altiatlasius koulchii 1.97313 1 ——— Amphipithecus mogaungensis 3.90784 1 ——— Anaptomorphus sp. 2.06446 1 ——— Anchomomys gaillardi 1.69897 1 ——— Anchomomys milleri 1.88649 1 ——— Anemorhysis savagei 1.76343 1 ——— Aotus 2.99564 3 1.28240 3 0.55119 Apidium moustafai 2.76864 1 ——— Apidium phiomense 3.10209 1 ——— Arapahovius gazini 2.34242 1 ——— Arctocebus 2.41414 3 0.79692 3 0.45175 Arsinoea kallimos 2.55023 1 ——— Asiadapis cambayensis 2.45179 1 ——— Ateles 3.91803 3 2.05327 3 0.70972 Australopithecus africanus 4.55630 5 2.65992 5 0.89264 Avahi 3.07004 3 0.98900 3 0.20840 Aycrossia lovei 2.25042 1 ——— Bahinia pondaungensis 2.63246 1 ——— Biretia fayumensis 2.20412 1 ——— Biretia megalopsis 2.37475 1 ——— Brachyteles 3.94645 3 2.07700 3 0.71459 Branisella boliviana 2.67761 1 ——— Bugtipithecus inexpectans 2.54777 1 ——— Cacajao 3.46761 3 1.83715 3 0.79261 Caenopithecus lemuroides 3.56478 1 ——— Callicebus 3.09517 3 1.28981 3 0.49253 Callimico 2.68485 3 1.06333 3 0.53845 Callithrix 2.52244 3 0.90064 3 0.48357 Cantius abditus 3.43521 1 ——— Carlocebus carmenensis 3.52724 1 ——— Catopithecus browni 2.45003 4 0.49136 4 0.12236 Cebuella 2.06446 3 0.64048 3 0.52745 Cebus 3.46575 3 1.84267 3 0.79937 Cercocebus 3.87274 3 2.04395 3 0.73047 Cercopithecus 3.64755 3 1.81783 3 0.65384 Cercopithecus lhoesti group 2.36860 2 ——— Cheirogaleus 2.53339 3 0.65658 3 0.23224 Chilecebus 2.76567 3 0.87274 3 0.29420 Chiropotes 3.43775 3 1.75427 3 0.72956 Chlorocebus 3.55871 3 1.84367 3 0.73866 Colobus 3.95412 3 1.90798 3 0.54047 Darwinius masillae 3.11193 1 ——— Daubentonia 3.40739 3 1.65196 3 0.64740 Dendropithecus macinessi 3.92330 1 ——— Dionysopithecus 3.69188 1 ——— Djebelemur martinezi 1.80618 1 ——— Dolichocebus gaimanensis 3.11694 1 ——— Donrussellia gallica 2.14301 1 ——— Donrussellia provincialis 2.25768 1 ——— Dyseolemur pacificus 2.08636 1 ——— Eosimias centennicus 1.81757 1 ——— Eosimias sinensis 1.84073 1 ———

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 8of15 Table S2. Cont.

BS: log10 log10 body-size EV: log10 endocranial log10 endocranial REV: endocranial Taxon body size (g) (g) source volume (cm3) volume (cm3) source volume residual

Epipliopithecus 3.78383 1 ——— Equatorius africanus 4.48673 1 ——— Erythrocebus 3.97543 3 1.97488 3 0.59322 Eulemur 3.29623 3 1.36925 3 0.43850 Euoticus 2.43775 3 0.76716 3 0.40631 Europolemur klatti 3.09412 1 ——— Galago senegalensis group 2.34044 4 0.67806 3 0.38181 Galagoides 2.01072 3 0.49415 3 0.41679 Godinotia neglecta 3.17026 1 ——— Gorilla 5.08279 3 2.69135 3 0.57456 Hapalemur 3.12548 3 1.33846 3 0.52105 Hemiacodon gracilis 2.92376 1 ——— Homo 4.76366 2 3.13194 5 1.22701 Hylobates 3.75645 3 1.97850 3 0.74222 Ignacius 2.57403 4 0.33041 4 −0.12091 Indri 3.80175 3 1.56324 3 0.29689 Kalepithecus songhorensis 3.81211 1 ——— Karanisia clarki 2.51587 1 ——— Komba robustus 2.48287 1 ——— Laccopithecus 4.06930 1 ——— Lagothrix 3.85431 3 2.00389 3 0.70265 Lemur 3.34439 3 1.37639 3 0.41366 Leontopithecus 2.77342 3 1.09726 3 0.51357 Lepilemur 2.83979 3 0.91408 3 0.28633 Leptadapis magnus 3.97772 4 1.33646 4 −0.04672 Limnopithecus evansi 3.69364 1 ——— Limnopithecus legetet 3.73823 1 ——— Lomorupithecus 3.56277 1 ——— Lophocebus 3.84308 3 2.00089 3 0.70710 Loris 2.28556 3 0.75511 3 0.49530 Loveina zephryi 2.15534 1 ——— Macaca 3.82364 3 1.94890 3 0.66802 Macrotarsius montanus 3.35005 1 ——— Mahgarita stevensi 2.84634 1 ——— Mandrillus 4.34733 3 2.20978 3 0.58124 Marcgodinotius indicus 1.99883 1 ——— Mico 2.52593 1 ——— Microadapis sciureus 2.45025 1 ——— Microcebus 1.71600 3 0.21617 3 0.33446 Microchoerus erinaceus 3.18724 1 ——— Micropithecus clarki 3.45071 1 ——— Mioeuoticus sp. 3.10721 4 0.89209 4 0.08682 Miopithecus 3.09691 3 1.61637 3 0.81793 Mirza 2.49831 3 0.76418 3 0.36312 Moeripithecus markgrafi 3.51746 1 ——— Nannopithex abderhaldeni 2.00000 1 ——— Nannopithex raabi 2.10380 1 ——— Nasalis 4.17926 3 1.98250 3 0.46552 Necrolemur spp. 2.36736 4 0.57978 4 0.26567 Nomascus 3.88397 1 ——— Notharctus tenebrosus 3.29885 4 1.01703 4 0.08453 Nyanzapithecus harrisoni 3.74858 1 ——— Nyanzapithecus pickfordi 4.06811 1 ——— Nyanzapithecus vancouveringorum 3.97804 1 ——— Nycticeboides simpsoni 2.43297 1 ——— Nycticebus 2.68124 3 0.94201 3 0.41952 Oligopithecus rogeri 3.11860 1 ——— Oligopithecus savagei 3.04021 1 ——— Omomys sp. 2.37291 1 ——— Oreopithecus bambolii 4.24405 4 2.30103 4 0.74105 Otolemur 2.98091 3 1.03523 3 0.31380

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 9of15 Table S2. Cont.

BS: log10 log10 body-size EV: log10 endocranial log10 endocranial REV: endocranial Taxon body size (g) (g) source volume (cm3) volume (cm3) source volume residual

Pan 4.58206 3 2.60304 3 0.81866 Panobius russelli 1.95775 1 ——— Papio 4.25828 3 2.25249 3 0.68306 Parapithecus fraasi 3.12516 1 ——— Parapithecus grangeri 2.98290 4 1.05690 4 0.33415 Perodicticus 3.08991 3 1.10312 3 0.30933 Phaner 2.66276 3 0.81090 3 0.30068 Phenacopithecus xueshii 2.26717 1 ——— Phileosimias kamali 2.37107 1 ——— Piliocolobus 3.91829 3 1.84936 3 0.50563 Pithecia 3.24551 3 1.54370 3 0.64660 Plesiadapis cookei 3.34242 4 0.69897 4 −0.26246 Plesiadapis tricuspidens 3.25696 1 ——— Plesiolestes problematicus 2.18184 1 ——— Pliopithecus 3.78197 1 ——— Pondaungia cotteri 3.94226 1 ——— Pongo 4.75702 3 2.58444 3 0.68392 Presbytis 3.86034 3 1.90026 3 0.59501 Proconsul africanus 4.02119 4 2.22272 4 0.81068 Proconsul heseloni 4.25998 1 ——— Proconsul major 4.71773 1 ——— Proconsul nyanzae 4.42225 1 ——— Pronycticebus gaudryi 3.08636 4 0.68124 4 −0.11019 Propithecus 3.70286 3 1.52414 3 0.32343 Propliopithecus chirobates 3.55919 1 ——— Propliopithecus haeckeli 3.53593 1 ——— Proteopithecus sylviae 2.73400 1 ——— Proteropithecia 3.01755 1 ——— Protoadapis curvicuspidens 3.10755 1 ——— Pseudoloris parvulus 1.50515 1 ——— Purgatorius unio 1.91381 1 ——— Pygathrix 4.08760 3 2.00561 3 0.54949 Qatrania wingi 2.14301 1 ——— Rangwapithecus gordoni 4.16349 1 ——— Rencunius zhoui 3.00860 1 ——— Rhinopithecus 4.11444 1 ——— Saguinus 2.66527 3 0.95118 3 0.43929 Saharagalago misrensis 2.08636 1 ——— Saimiri 2.87795 3 1.42700 3 0.77392 Serapia eocaena 2.85794 1 ——— Shoshonius cooperi 2.04922 1 ——— Siamopithecus eocaenus 3.94126 1 ——— Simias 3.90173 3 1.77151 3 0.43879 Simiolus 3.83065 1 ——— Smilodectes gracilis 3.29226 4 0.97772 4 0.04960 Soriacebus ameghinorum 2.98000 1 ——— Steinius vespertinus 2.38202 1 ——— Strigorhysis sp. 2.24304 1 ——— Symphalangus 4.05308 3 2.10857 3 0.67536 Taqah propliopithecid 3.69992 1 ——— Tarsius 2.08636 3 0.50965 3 0.38208 Teilhardina americana 1.93450 1 ——— Teilhardina asiatica 1.81291 1 ——— Teilhardina belgica 1.80618 1 ——— Tetonius sp. 1.86923 4 0.17609 4 0.19266 Tetonoides sp. 1.86923 1 ——— Theropithecus 4.18611 3 2.11992 3 0.59840 Trachypithecus + Semnopithecus 3.94535 3 1.92578 3 0.56409 Trogolemur myodes 1.72428 1 ——— Uintanius ameghini 2.00000 1 ——— Varecia 3.54283 3 1.50853 3 0.41406

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 10 of 15 Table S2. Cont.

BS: log10 log10 body-size EV: log10 endocranial log10 endocranial REV: endocranial Taxon body size (g) (g) source volume (cm3) volume (cm3) source volume residual

Victoriapithecus 3.68314 1 1.73239 6 0.54478 Wadilemur elegans 2.03342 1 ——— Washakius insignis 2.08636 1 ——— Xanthorhysis tabrumi 2.20683 1 ———

1, estimated using Conroy’s (47) “all primate” equation for estimating BS from lower first molar area; 2, from Smith and Jungers (48); 3, from Kirk (49); 4, from Silcox et al. (50); 5, from Wood and Collard (51); 6, from Benefit and McCrossin (52); —, no data.

Table S3. Brownian versus directional model Bayes factors BS Bayes factor Brownian EV Bayes factor Brownian REV Bayes factor Brownian Scaling parameters vs. directional model vs. directional model vs. directional model

– 9.20 9.90 15.72 δ 3.51 3.50 5.01 κ 8.58 7.67 16.77 λ 12.99 10.15 24.81 δλ 10.41 9.19 19.55 δκ 4.17 −0.55 5.59 κλ 10.22 6.09 27.88 δλκ 9.14 3.26 19.43

Table S4. BS Bayes factors, directional model Comparison Bayes factor

None vs. δ −9.96 None vs. κ 34.12 None vs. λ 14.28 κ vs. δλ −22.26 κ vs. δκ −7.00 κ vs. κλ −1.32 κ vs. δκλ −1.75

Table S5. EV Bayes factors, directional model Comparison Bayes factor

None vs. δ −7.72 None vs. κ 11.12 None vs. λ −0.89 κ vs. δλ −14.66 κ vs. δκ −4.86 κ vs. κλ −4.48 κ vs. δκλ −6.04

Table S6. REV Bayes factors, directional model Comparison Bayes factor

None vs. δ −12.84 None vs. κ 11.28 None vs. λ 11.30 κ vs. δλ −5.31 κ vs. δκ −9.58 κ vs. κλ 3.75 κ vs. δκλ −1.69 λ vs. δλ −5.34 λ vs. δκ −9.61 λ vs. κλ 3.72 λ vs. δκλ −1.72

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 11 of 15 Table S7. Reconstructed ancestral trait values for BS Node from BS trees in Fig. S3 (left of divider) BS mean 95% HPD lower 95% HPD upper

1 1.7493 1.3281 2.2283 2 1.8192 1.3669 2.2397 3 1.8403 1.4262 2.3035 4 1.8962 1.4401 2.3539 5 1.7847 1.3126 2.2036 6 1.7944 1.3594 2.2234 7 1.8575 1.419 2.2656 8 2.0354 1.5848 2.5183 9 2.0766 1.658 2.5055 10 2.2305 1.7612 2.6899 11 2.513 2.0609 2.9262 12 2.3507 1.921 2.7971 13 2.3292 1.9692 2.7053 14 2.0481 1.6945 2.3846 15 2.0515 1.7025 2.3896 16 2.2067 1.8184 2.5872 17 2.2048 1.8115 2.6191 18 2.4218 2.03 2.7988 19 2.3387 1.8482 2.7833 20 2.6553 2.144 3.1561 21 2.7802 2.3086 3.275 22 3.0738 2.6088 3.5283 23 3.1109 2.6777 3.5387 24 3.1485 2.7587 3.5184 25 2.757 2.2596 3.2103 26 3.1273 2.7121 3.5322 27 2.5935 2.1603 3.0709 28 2.3746 1.9228 2.8052 29 2.1605 1.7562 2.5585 30 1.7372 1.2779 2.1742 31 1.7532 1.3359 2.2222 32 1.8525 1.394 2.2641 33 2.0668 1.6625 2.4798 34 2.1938 1.7867 2.6121 35 2.3042 1.8866 2.7231 36 2.1283 1.7093 2.5398 37* 2.1275 1.7808 2.4752 38 1.8078 1.3798 2.2707 39 1.873 1.4219 2.2964 40 1.9624 1.5971 2.3448 41 2.303 1.8816 2.7142 42 2.5403 2.1169 2.9723 43 2.8919 2.4657 3.3199 44 2.7639 2.3623 3.1749 45 2.6687 2.2837 3.054 46 2.6777 2.2853 3.0926 47 2.8222 2.4093 3.2543 48 2.917 2.4995 3.3554 49a† 2.9764 2.6386 3.3574 † 49b 2.9638 2.6268 3.343 50 3.1293 2.7412 3.5424 51 3.3015 2.9199 3.6458 52 3.009 2.5995 3.4241 53 3.4212 3.0066 3.8213 54 3.6559 3.2507 4.0236 55 3.7552 3.3896 4.1 56 2.3112 1.9841 2.6212 57 2.7663 2.3549 3.17 58 2.816 2.4217 3.1949 59 2.656 2.2598 3.0434 60 2.6027 2.2292 2.9897 61 2.5179 2.1315 2.8953

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 12 of 15 Table S7. Cont. Node from BS trees in Fig. S3 (left of divider) BS mean 95% HPD lower 95% HPD upper

62 2.3983 2.0732 2.7628 63 2.3124 2.0033 2.6473 64 1.7476 1.2936 2.1859 65 3.2392 2.8422 3.6046 66 3.4812 3.1068 3.8879 ‡ 67a 3.7309 3.4067 4.082 ‡ 67b 3.7276 3.4019 4.0327 68 3.9886 3.5661 4.4182 69a§ 3.8522 3.5275 4.1872 69b§ 3.8568 3.5091 4.1953 70 4.3582 3.9422 4.7483 71 4.6439 4.2723 5.0321 72 4.6293 4.2837 4.9755 73 3.6272 3.2374 4.0214 74 3.5829 3.1474 4.0138 75 3.6962 3.29 4.0802 76 3.8 3.4278 4.169 77 3.783 3.4267 4.1569 78 3.8473 3.5112 4.209 79 3.9572 3.6298 4.3014 80 4.0165 3.6933 4.3402 81 3.5254 3.1123 3.9257 82 3.3994 3.052 3.7556 83 3.353 3.017 3.707 84 3.4103 3.074 3.7777 85 3.3322 3.011 3.6739 86 3.2302 2.9289 3.5504 87 3.7092 3.3488 4.0735 88 3.8496 3.4881 4.2062 89 3.9754 3.6505 4.3031 90 3.9761 3.6513 4.3095 91 3.9904 3.6809 4.2901

HPD, highest posterior densities. *This node was a trichotomy that was resolved randomly with Phileosimias kamali and Xanthorhysis tabrumi as sister taxa using a 0.01-Ma branch length. † This node was a trichotomy that was resolved randomly with Callicebus as sister to the other two taxa using a 0.01-Ma branch length. The more recent node is 51a and the deeper node is 51b. ‡This node was a polytomy that was resolved with and monkeys as sister taxa and a sister group of Miocene catarrhines. All polytomy branches were resolved with 0.01-Ma branch lengths. The more recent node was 69a and the deeper node was 69b. §This node was a trichotomy that was resolved randomly with Nomascus as sister to the other two taxa using a 0.01-Ma branch length. The more recent node is 71a and the deeper node is 71b.

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 13 of 15 Table S8. Reconstructed ancestral trait values for EV and REV Node from EV/REV EV REV trees in Fig. S3 (right of divider) Mean 95% HPD lower 95% HPD upper Mean 95% HPD lower 95% HPD upper

1 0.3471 −0.1149 0.8064 −0.3484 0.0942 −0.0885 2 0.4102 −0.0226 0.8227 −0.2304 −0.4138 −0.0547 3 0.7414 0.4349 1.0667 0.11 −0.0486 0.2639 4 0.8382 0.5517 1.1116 0.1532 0.0001 0.309 5 1.2729 1.0008 1.5655 0.2266 0.0677 0.3855 6a* 1.7112 1.4052 2.0081 0.3727 0.2042 0.5358 6b* 1.6901 1.4147 1.9901 0.3722 0.2042 0.5376 7 1.6743 1.3778 1.9717 0.4072 0.2271 0.5787 8 1.6729 1.3632 1.9813 0.4279 0.2543 0.6099 9 1.7059 1.4107 2.0042 0.5067 0.3247 0.6846 10 1.8421 1.5642 2.1065 0.5508 0.368 0.7352 11 1.9342 1.6675 2.198 0.5709 0.3911 0.7581 12 2.0148 1.7846 2.2644 0.607 0.4213 0.7991 13 2.0627 1.8346 2.2902 0.6285 0.4397 0.8217 14 2.0242 1.7668 2.2524 0.6 0.4102 0.7854 15 1.684 1.4153 1.9561 0.5616 0.389 0.7456 16 1.6736 1.4301 1.9342 0.5938 0.3994 0.7688 17 1.715 1.4618 1.9706 0.5704 0.3865 0.7553 18 1.8126 1.5633 2.0514 0.6128 0.4186 0.7996 19 1.7279 1.4389 2.0394 0.4422 0.2595 0.6245 20 1.7882 1.5251 2.055 0.4718 0.286 0.6656 21 1.7972 1.5442 2.0773 0.4708 0.2839 0.6558 22 1.8406 1.5833 2.0978 0.4772 0.2941 0.6614 23 1.9058 1.6683 2.1581 0.4937 0.3038 0.6868 24 1.9574 1.6672 2.2811 0.5145 0.3395 0.7011 25 1.9821 1.7091 2.2469 0.6222 0.4268 0.8151 26 2.148 1.8576 2.4277 0.5558 0.3864 0.7335 27 2.3336 2.0253 2.6152 0.5903 0.4019 0.7627 28 2.5252 2.2509 2.7955 0.7078 0.5266 0.9049 29 2.5963 2.3341 2.8453 0.7704 0.5777 0.954 30 2.7588 2.5334 2.976 0.8815 0.6835 1.0723 31 0.8293 0.5406 1.1331 0.1313 −0.031 0.2818 32 0.9136 0.6082 1.2143 0.2205 0.0498 0.392 33 1.1344 0.8195 1.4618 0.3297 0.1546 0.4992 34 1.2391 0.9349 1.5501 0.3971 0.2249 0.5787 35 1.4392 1.1465 1.7242 0.5129 0.325 0.7022 36 1.6394 1.3944 1.9088 0.6199 0.4343 0.8152 37 1.2528 0.9082 1.5793 0.3624 0.1923 0.5354 38 1.5559 1.2457 1.8429 0.4457 0.2602 0.624 39 1.801 1.5236 2.0847 0.5387 0.3654 0.7365 40 1.9033 1.6302 2.1668 0.5748 0.378 0.7632 41 1.2286 0.9089 1.5602 0.4002 0.2233 0.5712 42 1.2285 0.9111 1.5502 0.3985 0.2269 0.5714 43 1.146 0.8471 1.4477 0.3987 0.2288 0.58 44 0.9923 0.7039 1.2694 0.4048 0.2289 0.5903 45 0.9551 0.6677 1.226 0.4161 0.2328 0.5974 46 0.9 0.6253 1.1759 0.4428 0.2535 0.63 47 0.7902 0.541 1.0487 0.4787 0.2884 0.6799 48 0.3498 −0.0318 0.7192 −0.1152 −0.2985 0.0718 49 0.5157 0.0486 0.9679 −0.2892 0.1559 −0.0527 50 0.6573 0.1773 1.1069 −0.1848 0.2423 0.0018 51a† 0.6459 0.2912 0.9816 0.005 −0.1736 0.184 † 51b 0.6666 0.3118 1.0443 0.0037 −0.1779 0.1799 52 0.6744 0.3076 1.0101 0.0603 −0.1254 0.2521 53 0.7432 0.4351 1.0651 0.2398 0.0412 0.4382 54 0.8122 0.5001 1.1057 0.2109 0.0096 0.4098 55 0.5937 0.2758 0.9111 0.1822 −0.011 0.3699 56 0.7062 0.4026 0.9831 0.2313 0.0343 0.4198 57 0.9289 0.4293 1.3825 −0.0624 −0.0706 0.0753 58 0.9274 0.4867 1.3675 0.0201 0.0241 0.1041 59 1.1671 0.8193 1.513 0.1667 −0.0291 0.3575

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 14 of 15 Table S8. Cont. Node from EV/REV EV REV trees in Fig. S3 (right of divider) Mean 95% HPD lower 95% HPD upper Mean 95% HPD lower 95% HPD upper

60 1.2148 0.8998 1.5532 0.2351 0.0435 0.4355 61 1.2787 1.0077 1.5657 0.3573 0.1595 0.5581 62 0.8861 0.4977 1.2654 0.0263 −0.1646 0.2169 63 1.087 0.7719 1.3865 0.1518 −0.0449 0.3575 64 0.7497 0.4005 1.0965 0.0619 −0.1365 0.2527 65 0.5954 0.277 0.9269 0.1213 −0.0704 0.3253 66 0.4888 0.2095 0.779 0.2229 0.0189 0.426

HPD, highest posterior densities. *This node was a polytomy that was resolved with apes and monkeys forming sister taxa and a Proconsul outgroup, resolved with 0.01- Ma branch lengths. The more recent node was 6a and the deeper node was 6b. †This node was a trichotomy that was resolved with Mioeuoticus as sister group to the other two taxa using a 0.01-Ma branch length. The more recent node is 51a and the deeper node is 51b.

Table S9. Regression model Bayes factors, Brownian model Comparison Bayes factor

None vs. δ −2.06 None vs. κ 10.24 None vs. λ 3.65 κ vs. δλ −6.42 κ vs. δκ 0.53 κ vs. κλ −5.72 κ vs. δκλ −3.62

Other Supporting Information Files

SI Appendix (PDF)

Steiper and Seiffert www.pnas.org/cgi/content/short/1119506109 15 of 15