A Molecular Phylogeny for Bats Illuminates Biogeography...

they were less consistent. Smaller seed mass

was associated with more poleward distribu-

tion in 6 of the 11 dichotomous divergences

and with a more tropical distribution in one

clade. Larger seed mass was associated with

biotic dispersal in 6 of the 11 dichotomous

divergences and with abiotic dispersal in one

divergence. An analysis across all of the

divergences in the tree (based on independent

contrasts) also showed that shifts in seed mass

have been much more closely associated with

shifts in growth form than with shifts in

latitude or dispersal syndrome (35). Thus,

our data are more consistent with Eriksson,

Friis, and Lofgren_s suggestion (29) that

changes in seed mass during angiosperm

evolution resulted primarily from changes in

vegetation structure than with Tiffney_s hy-

pothesis (17) that changes in dispersal fauna

(particularly the radiation of mammals across

the Cretaceous-Tertiary boundary) allowed

angiosperms to radiate into larger seed masses.

Two of the 11 top-ranking dichotomous

divergences in seed mass were not associated

with divergences in plant stature. One was

the divergence between Juglandaceae and

Casuarinaceae/Betulaceae, which was asso-

ciated with a divergence between biotic and

abiotic dispersal. The other was a divergence

within Rhizophoraceae, between a small-

seeded terrestrial habit and a large-seeded

mangrove habit. A shift to a mangrove habit

has generally been associated with increases

in seed mass. The mangrove habit has evolved

in seven families, five of them represented in

our database. In four of these (Acanthaceae,

Myrsinaceae, Meliaceae, and Rhizophoraceae,

but not Combretaceae), mangroves have the

largest seeds in the family.

The most consistent pattern we revealed

was the association between changes in seed

mass and changes in growth form. This

result is in line with Charnov_s life history

theory for mammals (36). In Charnov_streatment, offspring size is coordinated with

size at adulthood, because larger offspring

offset the low survivorship to adulthood that

would otherwise be a consequence of longer

juvenile periods. This result is also consist-

ent with cross-species studies showing that

growth form is the strongest correlate of seed

size (9, 10). A recent compilation of data for

2113 species from around the world (7)

showed a highly significant positive relation-

ship between seed mass and plant height (R2 00.35). Of course, there is still great variation

in seed mass for a given plant size. Some of

this variation can be attributed to differences

in dispersal syndrome, some to biogeography,

and more variation is undoubtedly attributa-

ble to factors that we have not considered

here.

The synthesis of robust phylogenies with

global trait data sets holds great promise for

elucidating the ecological and evolutionary

history of seed plants and of other major

groups of organisms.

References and Notes1. M. L. Henery, M. Westoby, Oikos 92, 479 (2001).2. L. W. Aarssen, C. Y. Jordan, Ecoscience 8, 471 (2001).3. M. R. Leishman, I. J. Wright, A. T. Moles, M. Westoby,

in Seeds: The Ecology of Regeneration in PlantCommunities, M. Fenner, Ed. (CAB International,Wallingford, UK, 2000), pp. 31–57.

4. E. Salisbury, Proc. R. Soc. Lond. Ser. B. 186, 83(1974).

5. S. A. Foster, C. H. Janson, Ecology 66, 773 (1985).6. D. J. Metcalfe, P. J. Grubb, Can. J. Bot. 73, 817 (1995).7. A. T. Moles, D. S. Falster, M. R. Leishman, M. Westoby,

J. Ecol. 92, 384 (2004).8. D. A. Levin, Am. Nat. 108, 193 (1974).9. M. R. Leishman, M. Westoby, Am. Nat. 143, 890

(1994).10. M. R. Leishman, M. Westoby, E. Jurado, J. Ecol. 83,

517 (1995).11. J. Lord et al., J. Biogeogr. 24, 205 (1997).12. K. Thompson, S. R. Band, J. G. Hodgson, Funct. Ecol.

7, 236 (1993).13. D. S. Hammond, V. K. Brown, Ecology 76, 2544 (1995).14. N. Wikstrom, V. Savolainen, M. W. Chase, Proc. R.

Soc. Lond. Ser. B. 268, 2211 (2001).15. P. R. Crane, S. Lidgard, Science 246, 675 (1989).16. D. I. Axelrod, Science 130, 203 (1959).17. B. H. Tiffney, Ann. Mo. Bot. Gard. 71, 551 (1984).18. S. L. Wing, L. D. Boucher, Annu. Rev. Earth Planet. Sci.

26, 379 (1998).19. C. O. Webb, S. Kembel, D. D. Ackerly, Phylocom,

available at www.phylodiversity.net/phylocom/(2004).

20. C. O. Webb, M. J. Donoghue, Mol. Ecol. Notes, in press.21. Percentages were calculated from the Vascular Plant

Families and Genera database, available at www.rbgkew.org.uk/data/vascplnt.html.

22. Materials and methods are available as supportingmaterial on Science Online.

23. M. Schmidt, H. A. W. Schneider-Poetsch, J. Mol. Evol.54, 715 (2002).

24. J. G. Burleigh, S. Mathews, Am. J. Bot. 91, 1599 (2004).

25. D. E. Soltis, P. S. Soltis, M. J. Zanis, Am. J. Bot. 89,1670 (2002).

26. W. S. Judd, C. S. Campbell, E. A. Kellogg, P. F. Stevens,M. J. Donoghue, Plant Systematics: A PhylogeneticApproach (Sinauer, Sunderland, MA, ed. 2, 2002).

27. M. J. Donoghue, J. A. Doyle, Curr. Biol. 10, R106 (2000).28. B. H. Tiffney, Annu. Rev. Ecol. Syst. 35, 1 (2004).29. O. Eriksson, E. M. Friis, P. Lofgren, Am. Nat. 156, 47 (2000).30. D. Haig, M. Westoby, Evol. Ecol. 5, 231 (1991).31. P. F. Stevens, Angiosperm Phylogeny Website, avail-

able at www.mobot.org/MOBOT/Research/APweb/.32. J. A. Raven, Funct. Ecol. 13, 5 (1999).33. D. D. Ackerly, R. Nyffeler, Evol. Ecol. 18, 249 (2004).34. P. Wardle, Vegetation of New Zealand (Cambridge

Univ. Press, Cambridge, 1991).35. A. T. Moles et al., in preparation.36. E. L. Charnov, Life History Invariants: Some Explora-

tions of Symmetry in Evolutionary Ecology (OxfordUniv. Press, Oxford, 1993).

37. We thank R. Condit, S. Diaz, P. Juniper, M. Leishman,J. Lord, M. Mayfield, B. Rice, K. Thompson, I. Wright, andS. J. Wright for access to unpublished data; R. Stevensand J. Alroy for helpful discussion; B. Tiffney andtwo anonymous referees for comments on themanuscript; R. Turner (RBG Kew) for checking thespecies list against the International Plant NamesIndex; and P. Stevens for APweb. Supported by theNational Center for Ecological Analysis and Syn-thesis, the Australian Research Council (M.W.), andan NSF grant (D.D.A., C.O.W., and M. J. Donoghue).The Millennium Seed Bank Project is funded by theUK Millennium Commission, The Wellcome Trust,and Orange Plc. RBG Kew is partially funded by theUK Department of Environment, Food and RuralAffairs.

Supporting Online Materialwww.sciencemag.org/cgi/content/full/307/5709/576/DC1Materials and MethodsFigs. S1 and S2Tables S1 to S3References and Notes

3 September 2004; accepted 2 December 200410.1126/science.1104863

A Molecular Phylogeny for BatsIlluminates Biogeography and the

Fossil RecordEmma C. Teeling,1,2* Mark S. Springer,3* Ole Madsen,4

Paul Bates,5 Stephen J. O’Brien,6* William J. Murphy1,7

Bats make up more than 20% of extant mammals, yet their evolutionaryhistory is largely unknown because of a limited fossil record and conflicting orincomplete phylogenies. Here, we present a highly resolved molecularphylogeny for all extant bat families. Our results support the hypothesis thatmegabats are nested among four major microbat lineages, which originated inthe early Eocene [52 to 50 million years ago (Mya)], coincident with asignificant global rise in temperature, increase in plant diversity andabundance, and the zenith of Tertiary insect diversity. Our data suggest thatbats originated in Laurasia, possibly in North America, and that three of themajor microbat lineages are Laurasian in origin, whereas the fourth isGondwanan. Combining principles of ghost lineage analysis with moleculardivergence dates, we estimate that the bat fossil record underestimates(unrepresented basal branch length, UBBL) first occurrences by, on average,73% and that the sum of missing fossil history is 61%.

Bats are a unique and enigmatic group of

mammals that account for È1,100 species (1).

They are the only mammals to have achieved

true self-powered flight, are found throughout

the globe, and play a major ecological role as

pollinators and insect predators (2). Although

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bats originated in the early Eocene, it has

been difficult to identify bat species from the

fossil record, rendering the chronology of

divergence events and biogeography of this

order intractable from fossils alone (3).

Furthermore, the evolutionary history of this

order has been obscured by controversial

phylogenetic hypotheses. Morphological data

traditionally support the monophyly of the

order and of the two suborders, Mega-

chiroptera (megabats) and Microchiroptera

(microbats), implying a single origin of

laryngeal echolocation and flight in bats (4).

Molecular data support the monophyly of

bats and thus a single origin of flight in mam-

mals. However, molecules reveal a sister-taxon

relationship between the rhinolophoid

microbats and the megabats (Yinpterochi-

roptera), suggesting either multiple origins of

laryngeal echolocation within bats or a

single origin of echolocation with sub-

sequent loss in megabats (5–10). There re-

mains considerable uncertainty in both

subordinal and superfamilial classifications

within bats, where both morphological and

molecular data conflict (4, 7, 10), and

different molecular data sets provide vary-

ing support (8, 10).

To discriminate between the competing

phylogenetic views, we analyzed 13.7 kb of

nuclear sequence data from portions of 17

nuclear genes from representatives of all bat

families and four laurasiatherian outgroups

E30 bat genera, 4 outgroups; (11)^. Phyloge-

netic analyses with diverse methods resulted

in a well-resolved phylogeny, dividing the

order into two suborders and four super-

familial groups, rendering microbats para-

phyletic (Fig. 1). Both the monophyly of the

order Chiroptera and the two suborders

Yinpterochiroptera (Rhinolophoidea þ Ptero-

podidae) and Yangochiroptera received 100%

bootstrap support (BSS) in all maximum

likelihood (ML) analyses and had Bayesian

posterior probabilities (BPP) of 1.000 (Fig. 1;

table S1). Yangochiroptera is further sup-

ported by a 15–base pair (bp) deletion in

BRCA1 and a 7-bp deletion in PLCB4, which

unites all members of Yangochiroptera, and is

absent in all yinpterochiropteran and out-

group taxa (fig. S1). With the inclusion of

representatives from all putative microbat

families and the addition of 6.1 kb of

sequence data from 13 novel nuclear genes,

our results strongly support microbat para-

phyly. Likewise, some of the superfamilial

groupings suggested by previous molecular

data are confirmed and extended by this new

analysis, and many alternative hypotheses

have been refuted (described in table S2).

These data provide a supported resolution

for the phylogenetic placement of two enig-

matic, monotypic families, Craseonycteridae

and Myzopodidae (Fig. 1). Craseonycteris

Fig. 1. The maximum likelihood tree (–ln likelihood 0 92127.3772) forthe concatenated data set under the GTR þ G þ I model of sequenceevolution (11). Numbers at the nodes are the (ML unconstrainedbootstrap values)/(ML constrained bootstrap values)/Bayesian (single-model posterior probabilities shown as percentages)/Bayesian (parti-

tioned model posterior probabilities shown as percentages). 100*signifies clades that received 100% bootstrap support in all analysesand had posterior probabilities of 1.000. The genera are color codedaccording to the superfamilial groups identified by the most recentmorphological phylogenetic study (4).

1Laboratory of Genomic Diversity, Basic ResearchProgram, SAIC-Frederick, Inc., National Cancer Insti-tute, Frederick, MD 21702, USA. 2Department ofZoology, University College Dublin, Belfield, Dublin 4,Ireland. 3Department of Biology, University of Califor-nia, Riverside, CA 92521, USA. 4Department ofBiochemistry, Radboud University of Nijmegen, PostOffice Box 9101, 6500 HB Nijmegen, Netherlands.5Harrison Institute, Centre for Systematics and Biodiver-sity Research, Bowerwood House, 15 St. Botolphs Road,Sevenoaks, Kent TN13 3AQ, UK. 6The Laboratory ofGenomic Diversity, National Cancer Institute, Frederick,MD 21702, USA. 7Department of Veterinary Integra-tive Biosciences, College of Veterinary Medicine andBiomedical Sciences, Texas A&M University, CollegeStation, TX 77843, USA.

*To whom correspondence should be addressed.E-mail: [email protected]; [email protected]; [email protected]

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thonglongai, the smallest mammal in the

world, is confined to the Kanchanaburi

province of western Thailand and southeast

Myanmar (12, 13). Our results convincingly

place Craseonycteridae within the super-

family Rhinolophoidea (100% BSS, 1.000

BPP) and provide robust support for a sister-

group relationship with the megadermatids

(100% ML BSS, 1.000 BPP). Further

support for the inclusion of Craseonycteris

within the Rhinolophoidea derives from the

possession of pubic nipples, a unique and

diagnostic rhinolophoid character (14). The

phylogenetic position of the Myzopodidae

(which consists of the single species Myzop-

oda aurita), endemic to Madagascar (1), is

also controversial (4, 15). Our data support a

basal position for the Myzopodidae within

the superfamily Noctilionoidea (78% ML

BBS, 1.000 BPP).

A time scale for the evolution of the order

Chiroptera based on Bayesian dating analyses

(11) is depicted in Fig. 2. We estimate that

crown group bats last shared a common

ancestor about 64 million years ago (Mya)

at or following the Cretaceous-Tertiary

boundary (fig. S2; table S3) (11). This date

is also corroborated by a comprehensive

eutherian study that primarily used non-

chiropteran fossil calibration points (16).

The four major microbat (echolocating)

lineages ERhinolophoidea, Emballonuroidea,

Noctilionoidea, Vespertilionoidea^ each orig-

inated within a narrow time frame, 52 to 50

Mya, coincident with an approximate 7- rise

in mean annual temperature, a significant

increase in plant diversity, and the peak of

Tertiary insect diversity (17–19). We suggest

that extant microbats diversified in response

to an increase in prey diversity and that the

varied microbat echolocation and flight

strategies may have resulted from differential

niche exploitation at that time.

Using this complete interfamilial phylog-

eny, we examined competing biogeographical

hypotheses regarding the origin of bats. The

oldest definitive bat fossils are early to

middle Eocene, distributed in North Amer-

ica (Icaronycteris), Europe (Hassianycteris,

Archaeonycteris, and Paleochiropteryx),

and Australia (Australonycteris), and they

were already specialized for flight and

echolocation (4, 20–22). They overlapped

in range with the modern extant microbat

lineages, whose oldest fossil record is from

the middle Eocene of Europe (4, 23, 24),

and indeed appear to nest within crown

group Chiroptera (25). We reanalyzed the

morphological data set of Simmons and

Geisler (4) for extant bat families and extinct

Eocene fossils by incorporating the molecular

scaffold from Fig. 1 in parsimony analyses

(Fig. 3) (11). The most parsimonious trees

were used to map both current and past

geographic distributions in a parsimony

framework (Fig. 3) (11).

Geographic ancestral reconstructions (11)

suggest that bats originated in the Laurasian

land masses, possibly in North America

during the early Paleocene, and fail to

support a Gondwanan origin for bats, even

with the inclusion of Australonycteris in the

analyses (Fig. 3; table S4). A Southern

Hemisphere origin of modern bats has been

suggested E(26) and included references^,but it is based mainly on current distribution

of maximum bat diversity and has been

confounded by unreliable phylogenies. Cur-

rently, bats are distributed throughout the

globe, however, at each taxonomic level bat

endemism is high (1). All ancestral recon-

structions support an Asian origin for the

suborder Yinpterochiroptera (Fig. 3; table

S4). Since their diversification in the late

Paleocene, yinpterochiropterans have had an

exclusively Old World distribution (24).

In contrast, the biogeographic history of

Yangochiroptera is more difficult to decipher

because of its panglobal distribution (1). Our

results support a Laurasian, and most likely

Asian/European, origin for Yangochiroptera

(Fig. 3; table S4). Within this suborder, the

emballonurids have an exclusively tropical

Fig. 2. Molecular timescale for the order Chi-roptera based on thedivtime analyses (11),using the ML topologydepicted in Fig. 1, sixfossil constraints, anda mean prior of 65Mya for the base ofthe ingroup root. Num-bers at the nodes arethe molecular dates inmillions of years; valuesin parentheses are the95% credibility inter-vals. Letters along thebranches refer to thefossil constraint age(Mya) imposed on thatparticular node: [a] 0 37;[b] 0 55; [c] 0 37; [d] 034; [e] 0 30; [f] 0 37.Maximum constraint isan arrow pointing up;minimum constraint isan arrow pointing down.Red circles indicate theage of the oldest fossilrepresenting that line-age or ’’off-shoots’’from that lineage (ta-ble S5). Red numbersin brackets to the leftof the slash indicatethe percentage summissing of the fossil record for that clade, (total sum missing perlineage)/(sum age of lineage). Numbers in brackets in red to the right ofthe slash indicate the average percentage missing of that fossil record for

that clade or the average of the percentage missing per lineage (11) (tableS5). A blue square indicates the time of separation between the New WorldRhynchonycteris and the Old World Emballonura.

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distribution on opposite sides of the At-

lantic. The oldest fossils are middle Eocene in

age from the Messel of Germany (21),

whereas the oldest New World fossils are

Oligocene in age (3). Our molecular dates

indicate that the split between African and

South American emballonurids (i.e., Em-

ballonura versus Rhynchonycteris) occurred

about 30 Mya (Fig. 2; fig. S2; table S3). The

arrival of new world monkeys and cavio-

morph rodents into South America from Af-

rica, possibly via a Bvegetational raft[ sailing

from the Gabon to Brazil or Bstepping stones[spanning the Atlantic, is also estimated to

have occurred at least 31 to 25 Mya (27). We

hypothesize that emballonurid bats also

arrived to South America via this dispersal

route and represent another mammalian lin-

eage that made this journey.

Living noctilionoids have a disjunct distri-

bution: phyllostomids, mormoopids, noctil-

ionids, furipterids, and thyropterids are mainly

confined to the Neotropics; mystacinids are

found only in New Zealand; and myzopodids

are restricted to Madagascar (1). Our ances-

tral reconstructions suggest that noctilionoids

originated in Gondwana, perhaps in South

America (Fig. 3; table S4). Their distribution

and center of origin are similar to that of the

flightless ratite birds (28). Molecular dating

suggests that the ratites diversified as a result

of vicariant speciation due to the break up of

Gondwanaland (28), whereas our molecular

dates estimate the origin of noctilionoids at 52

Mya (Fig. 2), too late to be explained by

vicariance. At that time, dispersal was pos-

sible between the Gondwanan land masses

of South America, Antarctica, and Australia.

However, New Zealand, Africa, and Mada-

gascar were already well separated (29).

Our molecular dates suggest that there are

large gaps in the fossil record for most bat

lineages (represented by 58 branches: 30

terminal branches, 28 internal branches;

fig. S3), confirming the long held view that

the bat fossil record is impoverished. By

collating the oldest fossil for every branch

on the tree and comparing it with the

Bayesian estimated molecular divergence

date for that branch, we calculated the

unrepresented basal branch length (UBBL)

for each lineage. Using this value, we quan-

tified the fraction of each branch under-

estimated by the fossil record (11) (table

S5). On average, the fossil record under-

estimates the origin of 58 bat lineages by

73% (Fig. 2). The four major microbat

lineages are missing on average 56 to 86% of

fossil history, with the Gondwanan clade

(noctilionoids) missing the most (Fig. 2).

Megabat lineages are missing a sum total of

98% of their fossil history (table S5). The

terminal and internal branches are missing on

average 58 and 88% of fossil history, respec-

tively (table S5). With well over half of the

Cenozoic history missing for microbat lineages

and nearly all of the fossil history missing for

megabat lineages, it is not surprising that

Paleocene bat ancestors having transitional

morphological adaptations for flight and echo-

location have never been discovered.

Fig. 3. Biogeographic reconstructions. The topology of the chiropteran taxa is the strict consensustopology of the six most parsimonious trees resulting from the reanalysis of the Simmons and Geisler(4) data set with the molecular constraint depicted in Fig. 1. The topology of the outgrouplaurasiatherian orders is taken from Murphy et al. (30). All geographic characters depicted in tableS7 were mapped onto each of the most parsimonious trees using accelerated and delayedtransformations and the consensus results are shown as follows: (A) The earliest occurrences of eachlineage in Laurasia or Gondwana, [polymorphic states indicated by a hatched box at tip of branch (11);table S4, table S7]. (B) Geographic distributions defined by nine character states (11) (table S4, tableS7). Numbers at the branches identify the following clades: 1, Chiroptera; 2, Yangochiroptera; 3,Yinpterochiroptera; 4, Emballonuroidea; 5, Vespertilionoidea; and 6, Noctilionoidea. Results wereconsidered equivocal if the delayed and accelerated transformations conflicted (table S4).

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References and Notes1. N. B. Simmons, in Mammalian Species of the World: A

Taxonomic and Geographic Reference, D. E. Wilson,D. M. Reeder, Eds. (Johns Hopkins Univ. Press, Baltimore,in press).

2. B. D. Patterson, M. R. Willig, R. D. Stevens, in BatEcology, T. H. Kunz, M. B. Fenton, Eds. (Univ. ofChicago Press, Chicago, 2003), pp. 536–579.

3. N. J. Czaplewski, G. S. Morgan, S. A. McLeod, inEvolution of Tertiary Mammals of North America, vol.2, Marine Mammals and Smaller Terrestrial Mammals,C. Janis, G. Gunnell, M. Uhen, Eds. (Cambridge Univ.Press, Cambridge, in press).

4. N. B. Simmons, J. H. Geisler, Bull. Am. Mus. Nat. Hist.235, 1–152 (9 March 1998).

5. J. M. Hutcheon, J. A. W. Kirsh, J. D. Pettigrew, Philos.Trans. R. Soc. London Ser. B 353, 607 (1998).

6. E. C. Teeling et al., Nature 403, 188 (2000).7. E. C. Teeling et al., Proc. Natl. Acad. Sci. U.S.A. 99,

1432 (2002).8. E. C. Teeling, O. Madsen, W. J. Murphy, M. S.

Springer, S. J. O’Brien, Mol. Phylogenet. Evol. 28,308 (2003).

9. R. J. Baker, J. L. Longmire, M. Maltbie, M. J. Hamilton,R. Van Den Bussche, Syst. Biol. 46, 579 (1997).

10. R. A. Van Den Bussche, S. R. Hoofer, J. Mammal. 85,321 (2004).

11. Materials and methods are available as supportingmaterial on Science Online and at the Web site of

the Laboratory of Genomic Diversity, NationalCancer Institute.

12. J. E. Hill, Bull. Br. Mus. (Nat. Hist.) 32, 29 (1974).13. P. J. J. Bates, T. Nwe, K. M. Swe, S. S. H. Bu, Acta

Chiropt. 3, 33 (2001).14. N. B. Simmons, Am. Mus. Novit. 3077, 1 (1993).15. S. R. Hoofer, S. A. Reeder, E. W. Hansen, R. A. Van

Den Bussche, J. Mammal. 84, 809 (2003).16. M. S. Springer, W. J. Murphy, E. Eizirik, S. J. O’Brien,

Proc. Natl. Acad. Sci. U.S.A. 100, 1056 (2003).17. P. Wilf, C. C. Ladanderia, Science 284, 2153 (1999).18. C. C. Labanderia, J. Sepkoski, Science 261, 310 (1993).19. S. L. Wing, H. Sues, in Mesozoic and Early Cenozioc

Terrestrial Ecosystems in Terrestrial Ecosystems ThroughTime, A. K. Behrensmeyer et al. Ed. (Univ. of ChicagoPress, Chicago, 1992), pp. 327–418.

20. G. L. Jepsen, Science 154, 1333 (1966).21. J. Habersetzer, G. Storch, Naturwissenschaften 79,

462 (1992).22. S. Hand, M. Novacek, H. Godthelp, M. Archer, J.

Vertebr. Paleontol. 14, 375 (1994).23. G. Storch, B. Sige, J. Habersetzer, Palaeontol. Z. 76,

189 (2002).24. M. C. McKenna, S. K. Bell, Classifcation of Mammals

above the Species Level (Columbia Univ. Press, NewYork, 1997).

25. M. S. Springer, E. C. Teeling, O. Madsen, M. J.Stanhope, W. W. de Jong, Proc. Natl. Acad. Sci.U.S.A. 98, 6241 (2001).

26. S. J. Hand, J. A. Kirsch, in Bat Biology and Conserva-tion, T. H. Kunz, P. A. Racey, Eds. (Smithsonian Insti-tution Press, Washington, DC, 1998), pp. 72–90.

27. J. J. Flynn, A. R. Wyss, Trends Ecol. Evol. 13, 449(1998).

28. A. Cooper et al., Nature 409, 704 (2001).29. M. O. Woodburne, J. A. Case, J. Mamm. Evol. 3, 121

(1996).30. W. J. Murphy et al., Science 294, 2348 (2001).31. http://home.ncifcrf.gov/ccr/lgd/.32. The research was funded and supported by federal

funds from the National Cancer Institute, NIH, undercontract no. N01-CO-12400, and the Darwin Initia-tive Grant no. 162-11-09. We would like to thank K.Jones, I. Horacek, I. Mackie, C. Mainstone, F. Catzeflis,N. Czaplewski, G. Morgan, Tin Nwe, N. Crumpler,A. Roca, and R. Stanyon for samples, technical sup-port, and advice.

Supporting Online Materialwww.sciencemag.org/cgi/content/full/307/5709/580/DC1Materials and MethodsFigs. S1 to S3Tables S1 to S7References and Notes

10 September 2004; accepted 24 November 200410.1126/science.1105113

Interindividual Variation inPosture Allocation: Possible Role

in Human ObesityJames A. Levine,* Lorraine M. Lanningham-Foster,

Shelly K. McCrady, Alisa C. Krizan, Leslie R. Olson, Paul H. Kane,Michael D. Jensen, Matthew M. Clark

Obesity occurs when energy intake exceeds energy expenditure. Humansexpend energy through purposeful exercise and through changes in postureand movement that are associated with the routines of daily life [called non-exercise activity thermogenesis (NEAT)]. To examine NEAT’s role in obesity,we recruited 10 lean and 10 mildly obese sedentary volunteers and measuredtheir body postures and movements every half-second for 10 days. Obeseindividuals were seated, on average, 2 hours longer per day than leanindividuals. Posture allocation did not change when the obese individuals lostweight or when lean individuals gained weight, suggesting that it isbiologically determined. If obese individuals adopted the NEAT-enhancedbehaviors of their lean counterparts, they might expend an additional 350calories (kcal) per day.

Obesity is epidemic in high-income countries.

In the United States alone poor diet and

physical inactivity are associated with 400,000

deaths per year (1) and obesity-related medical

expenditures in 2003 approximated $75 billion

(2). Obesity is also an emerging problem in

middle- and low-income countries, where the

health and fiscal costs are likely to be dev-

astating (3).

As the impact of obesity on health

escalates, so too does the need to understand

its pathogenesis. Weight gain and obesity

occur when energy intake exceeds energy

expenditure. We are interested in a specific

component of energy expenditure called

NEAT and the role it might play in human

obesity. NEAT is distinct from purposeful

exercise and includes the energy expenditure

of daily activities such as sitting, standing,

walking, and talking.

We have previously shown that when

humans overeat, activation of NEAT helps to

prevent weight gain (4). To better understand

NEAT and its role in obesity, we separated

NEAT into the thermogenesis associated with

posture (standing, sitting, and lying) and that

associated with movement (ambulation).

To investigate whether the obese state has

an effect on NEAT, we first developed and

validated a sensitive and reliable technology

for measuring the postural allocation of

NEAT in human volunteers (5, 6). This

physical activity monitoring system uses

inclinometers and triaxial accelerometers to

capture data on body position and motion

120 times each minute. By combining these

measurements with laboratory measures of

energy expenditure, we can summate NEAT

and define its components (7).

To compare body posture and body

motion in lean and obese people, we re-

cruited 20 healthy volunteers who were self-

proclaimed Bcouch potatoes.[ Ten participants

(five females and five males) were lean Ebody

mass index (BMI) 23 T 2 kg/m2^ and 10

participants (five females and five males)

were mildly obese (BMI 33 T 2 kg/m2) (8)

(table S1). We deliberately selected mildly

obese subjects who were not incapacitated

by their obesity and who had no joint

problems or other medical complications

of obesity. The volunteers agreed to have all

of their movements measured for 10 days

and to have their total NEAT measured with

the use of a stable isotope technique (9).

They were instructed to continue their usual

daily activities and occupations and not

to adopt new exercise practices. Over the

10-day period, we collected È25 million

data points on posture and movement for

each volunteer.

Our analysis revealed that obese partic-

ipants were seated for 164 min longer per

day than were lean participants (Fig. 1A).

Correspondingly, lean participants were

upright for 152 min longer per day than

obese participants. Sleep times (lying) were

almost identical between the groups. Total

Endocrine Research Unit, Mayo Clinic, Rochester, MN55905, USA.

*To whom correspondence should be addressed.E-mail: [email protected]

R E P O R T S


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A Molecular Phylogeny for Bats Illuminates Biogeography and the Fossil RecordEmma C. Teeling, Mark S. Springer, Ole Madsen, Paul Bates, Stephen J. O'Brien and William J. Murphy

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Science Supporting Online Material Teeling, p. 1

Science Supporting Online Material

A Molecular Phylogeny for Bats Illuminates Biogeography and the Fossil Record

Emma C. Teeling, Mark S. Springer, Ole Madsen, Paul J. J. Bates, Stephen J. O’Brien, William J. Murphy

Materials and Methods Genes and taxon sampling We expanded the Teeling et al. (S1) data set by generating 6.1 kb of new nuclear sequence data from 13 gene segments for 30 bat genera, using previous methods (S2, S3). Two new primer pairs spanning two segments of exon 18 of the TITIN gene are described below. Additional sequences are from Murphy et al. (S4), necessitating some chimeric OTUs (table S6). Our data set included four pteropodids (Cynopterus, Nyctimene, Pteropus, Rousettus) two megadermatids (Megaderma, Macroderma), two rhinolophids (Rhinolophus, Hipposideros), one rhinopomatid (Rhinopoma), one craseonycterid (Craseonycteris), one nycterid (Nycteris), three emballonurids (Emballonura, Taphozous, Rhynchonycteris), one natalid (Natalus), two molossids (Tadarida, Eumops), two vespertilionids (Rhogeessa, Myotis), one antrozoid (Antrozous), one myzopodid (Myzopoda), one mystacinid (Mystacina), one furipterid (Furipterus), one thyropterid (Thyroptera), one noctilionid (Noctilio), one mormoopid (Pteronotus), four phyllostomids (Desmodus, Anoura, Tonatia, Artibeus) sensu Simmons and Geisler (S5). We included four laurasiatherians as outgroup taxa. The sequences were aligned using Clustal–X, incorporating default settings (S6), and modified in Se-Al (S7). Regions of alignment ambiguities due to repeats were removed from the noncoding 3´ UTRs APP (313 bp), BMI1 (65 bp), CREM (133 bp), and PLCB4 (156 bp). The repetitive regions were also removed from ADRA2B (87 bp) prior to analyses. This final data set totaled ~13 kb of nuclear sequence data for 18 nuclear genes and includes representative of all bat families. Alignments files that detail regions of ambiguity are posted online at http://home.ncifcrf.gov/ccr/lgd/. GenBank accession numbers for all sequences included in this study are in table S6.

TITIN primer sequence

TTNF1 CACCTCTCTTGTTCTTGACAATG; TTNR2 CCTTTTGGAGGATCAGGTTTATC;

TNNF3 GGATGATGTCACCAGAAACAGTG; TTNR3 GCCTGGTTCTTTGTAGGGATATT;

TTNF6 TGTGATCCTGTGTTCAAACCT; TTNR6 GCATTACAGACTTTGGATTCAGC;

TTNF7 TTCCCCACCAGGAAAGGT; TTNR7 TGGTCCAGGTTCTTTAAATGGAT.

Phylogenetic analyses An evaluation of data set incongruence with a bootstrap support/conflict criterion of 90% (S8) revealed no conflicting nodes, thus we performed phylogenetic analyses on the concatenated data set. Maximum likelihood (ML), minimum evolution (ME) and maximum parsimony (MP) analyses were performed with PAUP 4.0b10 (S9). ML analyses were performed using the GTR (general time reversible) + Γ (gamma


distribution of rates) + I (proportion of invariant sites) sequence evolution with the following parameters settings estimated by Modeltest (S10): R-Matrix = (1.2302 4.6545 0.6304 1.4023 5.5530); base frequencies = (0.2585 0.2592 0.2503 0.2320); proportion of invariant sites = 0.3240; and shape parameter of gamma distribution = 0.7628. In all ML analyses, starting trees were obtained via neighbor-joining (NJ). Owing to computational demands, we used the following taxonomic constraint in ML bootstrap analyses with tree-bisection and reconnection (TBR) branch swapping: (Pteropus, Cynopterus, Rousettus, Nyctimene), (Rhinolophus, Hipposideros), (Megaderma, Macroderma), Nycteris, (Emballonura, Taphozous, Rhynchonycteris), (Tonatia, Artibeus, Desmodus, Anoura), (Tadarida, Eumops), (Antrozous, Rhogeessa, Myotis), Rhinopoma, Noctilio, Myzopoda, Pteronotus, Thyroptera, Mystacina, Furipterus, Natalus, Craseonycteris). All clades constrained received 100% bootstrap support in most other analyses and are highly supported by independent data sets (S1, S4, S11, S12). ML bootstrap analyses were also performed without this molecular constraint using nearest-neighbor interchange branch swapping. ME analyses were performed with ML distances implementing a GTR + Γ + I model of evolution. Starting trees were obtained using NJ. In MP analyses, we used stepwise addition with 1000 randomized input orders. Nucleotide positions were unweighted, and gaps were coded as missing data. Bootstrap analyses included 100 replicates for ML and 500 replicates for ME and MP. We used TBR based heuristic searches in all analyses except unconstrained ML bootstrap replicates.

Bayesian analyses were completed with MrBayes 3.0 (S13). Two kinds of analyses were performed: The first incorporated a single model of sequence evolution for the entire data set (GTR + Γ + I); the second incorporated an independent model of sequence evolution for each data partition. The data set was divided into 17 partitions corresponding to either gene type or genomic linkage: ADRA2B; ADORA3; ADRB2; APP; ATP7A; BDNF; BMI1; BRCA1; CREM; EDG1; PLCB4; PNOC; RAG1+RAG2; TTN; TYR; VWF; ZFX. We used the Akaike Information Criterion incorporated in Modeltest (S10) to assess the optimal model for each partition. GTR + Γ + I was ascertained to be the optimal model for all partitions except APP, BRCA1, and ATP7A where GTR + Γ was the optimal model, HKY85+Γ was optimal for CREM and GTR + I was optimal for BMI1. Flat priors were used, starting trees were random, and phylogenetic constraints were not incorporated. Four simultaneous Markov chains were run for 1,000,000 generations, burn in values were set at 50,000 generations (based on empirical values of stabilizing likelihoods), and trees were sampled every 100 generations. Each Bayesian run was repeated to test for convergence.

Statistical testing We used the Kishino and Hasegawa (S14) test with RELL optimization and 1000 bootstrap replicates to compare the statistical significance of eight a priori hypotheses regarding interfamilial relationships: (a) Yinpterochiroptera (S15); (b) microbat monophyly (5); (c) sistergroup relationship between Noctilionidae and Mystacindae (S16);(d) basal position for Mystacinidae within the noctilionid + mormoopid + phyllostomid clade (S17); (e) monophyly of the superfamily Nataloidea sensu Simmons and Geisler (S5) ; (f) association of thyropterids +furipterids with the exclusion of the natalids (S18); (g) monophyly of the superfamily Rhinolophoidea sensu Koopman (S19); (h) monophyly of the superfamily Rhinolophoidea sensu Teeling et al. (1).


Molecular dating branch length estimation Branch lengths were estimated with ESTBRANCHES for the concatenated data set and for each data partition discussed above (S20). The mole was chosen as the outgroup. The maximum likelihood topology (fig. S2) was incorporated in the analyses. We used Felsenstein’s 1984 model of sequence evolution with an allowance for a gamma distribution of rates with four discrete rate categories (S21). The estimates of the rate categories for the gamma distribution, base frequencies and the transition/transversion parameter were calculated in PAUP 4.0b (S9) for the entire data set and for each data partition.

Divergence time estimations Two programs were used to estimate the divergence times: DIVTIME5B and MULTIDIVTIME (S20, S22). The DIVTIME5B program utilized the estimated branch length for the entire dataset, whereas MULTIDIVTIME utilized the estimated branch lengths for each data partition. PNOC was not incorporated in the MULTIDIVTIME analyses due to missing outgroup data. Both programs incorporated Markov Chain Monte Carlo analyses that were run for 1 million generations and sampled every 100 generations. In the both analyses we incorporated two estimates for the mean ingroup prior: 65 Mya, following a strict interpretation of the Explosive model of placental diversification, placing the root at or near the K-T boundary (S23), and 56 Mya based on the oldest fossil bat (S5). Six fossil constraints were incorporated in the analyses.

(1) A maximum of 34 Mya for the base of the family Phyllostomidae. The oldest verified phyllostomid fossils have been found in the Laventan (13.8-11.8 Mya) deposits of La Venta, Colombia (S24). The oldest suspected, but unconfirmed, and possible stem phyllostomids, are from the Whitneyan (32-30 Mya) I-75 formation from Florida (S25). Therefore we constrained the maximum divergence date for this clade at the Eocene / Oligocene boundary.

(2) A minimum of 30 Mya for the Mormoopidae / Phyllstomidae split. The oldest fossils in this clade are mormoopids found in the Whitneyan (32-30 Mya) land deposits in Florida (S26).

(3) A minimum of 37 Mya for the split between Vespertilionidae / Molossidae. Verified vespertilionid and molossid fossils have been found from the middle Eocene (S27).

(4) A minimum of 37 Mya for the base of Emballonuridae. The oldest crown group emballonurid, Tachypteron franzeni, is found in Germany from middle Eocene deposits (S28).

(5) A minimum of 37 Mya for the base of Rhinolophidae as crown group rhinolophids have been reported from the middle Eocene of Europe (S5, S27).

(6) A maximum of 55 Mya for the base of Rhinolophoidea (S27). There are no early Eocene rhinolophoids so we constrained the maximum age for this split at the Paleocene/Eocene boundary.

To ascertain the sensitivity of our analyses to the fossil constraints each constraint was systematically removed in the DIVTIME5B analyses.

Missing fossil record estimation To estimate the fraction of missing data from the fossil record we collated the oldest definitive fossil for every chiropteran lineage on the tree (fig S3; table S5; S24–S31). We


aimed to identify unequivocal fossils that consisted of more than a single tooth (table S5). A lineage includes any taxon that may fall on that particular branch and any "off-shoots" from that branch (30 terminal branches, 28 internal branches). The date of basal divergence between two sister-lineages was estimated as the first fossil occurrence to represent either lineage, and was assessed for all lineages from tip to root (ghost-lineage). The age of first fossil occurrences for each lineage was compared with the estimated Bayesian molecular dates of first occurrences, (fig. S3, table S5) to identify the "unrepresented basal branch length" or UBBL. When both the molecular and fossil age are in agreement, or when the oldest fossil predated the molecular age (in cases where the either the lineage in question was not taxonomically sampled at its most basal divergence; was a paraphyletic assemblage; or the fossils are incorrectly identified), we concluded that there was no missing data for that lineage. When the oldest fossil was younger than the molecular age we subtracted that the age of the fossil from the molecular date to estimate the UBBL, and hence missing data for that lineage. Where no fossil information was available for the genera sampled, we used the oldest fossil age of the closest relative ("off-shoot" from the branch), and where appropriate, relatedness was based on previous intergeneric phylogenetic analyses (S11, S12, S32–S34). We used the midpoint dates of an epoch or land mammal age to assign an age to a fossil (S24–S31). The percentage of the "total missing" and the average of the "percentage missing" per lineage were calculated. Note the following worked example, see fig. S3, table S5.

Pteropodidae -Branches 1-7 Lineage 1, oldest fossil is Pteropus at 0.89- molecular age = 23, missing = 22.11,

percentage missing = 96% Lineage 2, oldest fossil is Rousettus at 0.13- molecular age = 23, missing = 22.87,

percentage missing = 99% Lineage 3, no fossil available, the time interval for this internal branch is 24-23 = 1,

missing = 1, percentage missing = 100% Lineage 4, oldest fossil is Cynopterus at 0.005-molecular age 22, missing = 21.99,

percentage missing = 100% Lineage 5, oldest fossil is Nyctimene at 0.005-molecular age 22, missing = 21.99.

percentage missing = 100% Lineage 6, no fossil available, the time interval for this internal branch is 24-22 = 2,

missing = 2, percentage missing = 100% Lineage 7, oldest representative is indet. pteropodid. at 26.25, the time interval for this

internal branch is 58-24 = 34, amount of missing data is 58-26.45 = 31.85, percentage missing is 94%

Sum of age of lineages for Pteropodidae: 23+23+1+22+22+2+34 = 127 Sum of missing: 22.11+22.87+1+21.99+21.99+2+31.85 = 123.82 Therefore, percentage total missing: 123.82/127 = 98% Average of percentage missing per lineage: 96 +99+100+100+100+100+94/ 7 = 98% Geographic center of origin reconstruction To assess the evolutionary relationships of the four Eocene fossil taxa, Icaronycteris, Archaeonycteris, Hassianycteris, Paleochiropteryx in light of our molecular phylogeny,


we reanalyzed the data set of Simmons and Geisler [(S5); which includes 195 morphological characters, scored for representatives of every extant bat family and for the four extinct fossil lineages], by incorporating a molecular scaffold that constrained all extant lineages as depicted in figure 1 in a parsimony framework. The fossil taxa were not constrained by the molecular scaffold. We used unweighted MP with 1,000 random input orders. The topology of the outgroup laurasiatherian orders is taken from Murphy et al. (S4). It has been suggested the early Eocene Australian fossil (Australonycteris) is most similar to the Eocene taxa Hassianycteris, Archaeonycteris and Paloechiropteryx (S35), however the exact phylogenetic position of Australonycteris cannot be assessed due to insufficient data. Therefore, we placed Australonycteris as a possible sister-taxon to each of the above lineages, and to Icaronycteris, in each of the most parsimonious trees. Parsimony reconstructions of ancestral character states were obtained using MACCLADE (S36). Both delayed transformations and accelerated transformations were performed. The geographic characters and states are described in table S7. Geographic distributions were mapped onto each of the most parsimonious trees in two ways: (a) The earliest occurrence of each lineage in either the Laurasian or Gondawanan landmasses was assessed and mapped onto the trees (S4, S27, S30); (b) The current global distribution for each lineage was assessed and defined by nine character states (S37); Europe (East of the Ural mountains); Asia (West of the Ural mountains); Africa; Madagascar; Australia; New Zealand; North America; South America (includes central America); West Indies. If any fossils were found outside of the current range, this was also recorded eg. Mystacina is currently found only in New Zealand, however the oldest fossil is found in Australia, therefore the geographic distribution of Mystacina has two states, New Zealand and Australia (S27).

SOM Text Systematically removing each of the fossil constraints had minimal impact on the dates, always being within 1-2 million years of those shown in Fig. 2. Likewise, employing a mean prior of 56 Mya had a negligible effect on the above dates (fig. S2; table S3). When the maximum constraint of 55 Mya at the base of the rhinolophoid radiation was relaxed, the divergence date for the base of Chiroptera increased from ~ 64 Mya to ~72 Mya. Similarly, the date of basal divergence of all clades increased from 1 to 8 million years; however, these older point estimates fell within the credibility intervals of all other analyses (fig. S2; table S3).

Pteropus AGAATAGAACTGAATAAGCAGAAACCTCCATGCTCynopterus AGAATAAAACTGAATAAGCAGAAACCTCCATGCTRousettus AGAATAGAACTAAATAAGCAGAAACCTCCATGCTNyctimene AGAATAGAACTGAATAAGCAGAAACCCTCATGCTRhinolophus AGAAAAGAACTGAATAAGCAGAACCCTCCATGCTHipposideros AGAAAAGAACTGAATAAGCAGAAACCTCCATGCTMegaderma AGAAAAGAACTGAATAATCAGAAACCTCTATGCTMacroderma AGAAAAGAACTGAATAATCAGAAACCTCTATGCTCraseonycteris AGAGAAGAACTGAGTAAGCAGGAACCTCTATGCTRhinopoma AGAAAAGAACTGAGTAAGCATAAACCTGCATGCTNycteris AGACAAGAA---------------CTGCCATGCTEmballonura AGAAGAGAA---------------CCTCCATGCTTaphozous AGAAAAGAA---------------CCTCCATACTRhynchonycteris AGAAAAGAA---------------CCTCCATGCTTonatia AGGGAAGAA---------------TCTCCATCCTArtibeus AGGAGAGAA---------------TCTCCTTCCTDesmodus AGAAGAGAA---------------TCTCCATCCTAnoura AGAAAAGAA---------------TCCCCTTCCTNoctilio AGAAGAGCT---------------TCTCCATGCTAntrozous GGAAAAGAA---------------CTTCCACGCTRhogeessa AGAAAAGAA---------------CTTCCACGCTMyotis GAAAAAGAA---------------CTTCCACGCTMyzopoda AGAAAAGAA---------------CATCCATGCGPteronotus AGAGAAGAA---------------TCTCCATGCTThyroptera AGAAAAGAA---------------TCTCCATGCTMystacina AGAAACGAA---------------TCTCCATGCTFuripterus AGAAAAGAA---------------TCTCCATGCTNatalus AGAAAAGAA---------------CCTCCATGCTTadarida AGAAAAGAA---------------CCTCCAGGCTEumops AGAAAAGAA---------------CCTCCAGGCTcat AGAAAA---CTGAGTAAGCAGAAATCTCCATGCTbovine AGAAAAGAACTGCGTAAGCAGAAACCTGCATGCCmole AGAAAAGAACTGAATAAGCAGAAACCTCCATGCThorse AGAGAAGAACTGAATAAGCAGAAACCTCCACGCT

ACATTATGAATATTGACATTTTGAATATTAACATTTTGAATATTGAGATTTCGAATATTGACATTTTGAATATTGACATTTTGAATATTGACATTTTGAATACTGACATTTTGAATATTGACATTTTGAATATTGACATTTTGAATATTGACAT-------ACTGACAT-------ATTGACAT-------ATTGACAT-------ATTGACAT-------ACTGANGT-------ATTGACAT-------ATTGACAT-------ACTGACAT-------ATTGACAT-------ATTGACAT-------ATTGACAT-------ATTGACAT---------TAACAT-------ACTGACAT-------ATTGACAT-------ATTGACAT-------ATAGACAT-------ACTGACAT-------ATTGACAT-------ATTGACATTTTGAGTATTGACATTCTGAACGCTAATATTTTGAATTTTGACATCTTGAATCTTG

15 base pair deletion BRCA1 7 base pair deletion PLCB4(3’ UTR)

Yinpterochiroptera

Yangochiroptera

Fig S1. Depicts the two deletions found in all members of Yangochiroptera but are not found in any Yinpterochiropteran or outgroup taxa.These deletions were not included in the analyses, but instead are an independent source of support.

Fig. S2. ML tree incorporated in the DIVTIME and MULTIDIVTIME analyses.Numbers at the nodes indicate the nodes referred to in Table S3.

ArtibeusAnoura

TonatiaDesmodus

PteronotusNoctilio

FuripterusThyroptera

MystacinaMyzopoda

AntrozousRhogeessa

MyotisTadarida

EumopsNatalus

EmballonuraRhynchonycteris

TaphozousNycteris

MegadermaMacroderma

CraseonycterisRhinopoma

RhinolophusHipposideros

Pteropus

RousettusCynopterus

3738

39

40

35

36

41

42

43

44 3132

33

34 30

4546

47

48

5849

5051

53

52

56 55

54

57

Nyctimene

Constraints incorporated in the Divtimeand Multidivtime analyses

Nodes Value in MyaU39 34L40 30L33 37L46 37L52 37U53 55

NycterisEmballonuraRhynchonycterisTaphozousTonatiaArtibeusAnouraDesmodusPteronotusNoctilioFuripterusThyropteraMystacinaMyzopodaAntrozousRhogeessaMyotisTadaridaEumopsNatalus

10203040506070 0

K-T boundary Tertiary

Macroderma

PteropusRousettusCynopterusNyctimeneRhinolophusHipposiderosMegaderma

CraseonycterisRhinopoma

64 (71-58)

58 (63-53)

52 (55-48)

49 (53- 45)43 (39-47)

16 (21-12)

39 (43-37)

24 (29-20) 23 (28-18)

22 (27-18)

52 (58-47)42 (47-37)

30 (35-25)

55 (61-50)

54 (60-50)

52 (57-46)46 (51-41)

42 (47-37)36 (41- 31)

40 (46-35)

36 (42-32) 26 (30-21)

22 (26-17)19 (23-15)

10 (13- 7)20 (25-16)

22 (27-17)47 (53-42)

50 (56-45)

Rhinolophoidea

Emballonuroidea

Noctilionoidea

Vespertilionoidea

PteropodidaeY

inpterochiropteraY

angochiroptera

1

23

4

56

7

8

911

10

1213

1415

1617

18

19

202122

2425

26

3028

2729

31

32

33

343637

38

3940

41

42

43

44

45

4647

48

4950

5152

53

55

54

56

58

57

23

35

Fig S3. Molecular timescale for the order Chiroptera based on the divtime analyses, using the ML topology depicted in Fig. 1, six fossilconstraints and a mean prior of 65 Mya for the base of the ingroup root. The values in bold face at the nodes are in millions of years, valuesin parentheses are the 95% credibility intervals. Branch numbers incorporated in table S5 are shown in normal face along each branch.


Table S1. Bootstrap values for the various clades. Bayesian posterior probabilities are shown as percentages. MLNNI, maximum likelihood with nearest neighbor branch swapping; MLTBR, maximum likelihood with tree bisection and reconnection branch swapping; MP, maximum parsimony; ME, minimum evolution; Bayes 1 & 2, Bayesian analyses with a single model of molecular evolution; Bayesian P1 & P2, Bayesian analyses with independent models of sequence evolution per gene partition.

Clade MLNNI MLTBR MP ME BAYES1 BAYES2 BAYESP1 BAYESP2 Pteropodidae 100 100 100 76 100 100 100 100 Pteropus+Rousettus 50 56 20 68 97 98 98 97 Nyctimene+Cynopterus 50 63 63 27 100 100 98 100

Megadermatidae 100 100 100 100 100 100 100 100

Megadermatidae+Craseonycteridae 98 100 100 97 100 100 100 100 Megadermatidae+Craseonycteridae+Rhinopomatidae 90 99 97 5 100 100 100 100

Rhinolophidae 100 100 100 100 100 100 100 100

Rhinolophoidea 100 100 100 100 100 100 100 100

Yinpterochiroptera 100 100 96 76 100 100 100 100 Yangochiroptera 100 100 100 100 100 100 100 100

Emballonuridae 100 100 100 100 100 100 100 100

Emballonura+Rhynchonycteris 100 100 100 100 100 100 100 100

Nycteridae+Emballonuridae 99 97 50 84 100 100 100 100 Vespertilionidae 100 100 100 100 100 100 100 100

Antrozous+Rhogeessa 100 100 100 100 100 100 100 100 Molossidae 100 100 100 100 100 100 100 100

Molossidae+Vespertilionidae 100 99 42 63 100 100 100 100 Vespertilionoidea 100 99 44 91 100 100 100 100

Vespertilionoidea+Noctilionoidea 63 61 21 47 94 95 91 92

Phyllostomidae 100 100 100 100 100 100 100 100 Artibeus+Anoura 84 78 44 76 100 100 100 100 Artibeus+Anoura+Tonatia 100 100 99 82 100 100 100 100

Phyllostomdiae+Mormoopidae 100 100 100 100 100 100 100 100


(Table S1. continued) Noctilionidae+Furipteridae 100 100 81 100 100 100 100 100 Noctilionidae+Furipteridae+Thyropteridae 76 77 18 36 95 96 88 89 Monophyly South American families 100 100 23 61 100 100 100 100

Basal position for Myzopodidae in Noctilionoidea 100 100 74 49 100 100 100 100 Noctilionoidea 78 77 28 50 100 100 100 99


Table S2. Comparison of phylogenetic hypotheses.

Phylogenetic hypotheses Log likelihood score ∆ in –ln likelihood

P values for KH tests

(a) Hutcheon (b) Simmons

1: (a) Yinpterochiroptera (S15) versus (b) Microbat monophyly (S5)

92127.3772 92160.8491 33.47 0.006*

(c) Pierson (d) Kirsch

2: (c) Noctilionidae + Mystacinidae (S16) versus (d) Mystacinidae basal to Noctilionidae + Phyllostomidae+Mormoopidae (S17)

92127.3772 92187.8029 60.43 0.001*

(e) Hoofer (f) Simmons

3: (e) Thyropteridae+Furipteridae with the exclusion of Natalidae and Myzopodidae (S18) versus (f) Nataloidea sensu Simmons and Geisler (S5).

92127.3772 92577.4019 450 < 0.001*

(g) Teeling (h) Koopman

4: (g) Rhinolophoidea sensu Teeling et al. (S1) versus (h) Rhinolophoidea sensu Koopman (S19)

92127.3772 92556.3546 429 < 0.001*

*Indicates hypotheses that were rejected at P < 0.01 in pairwise comparisons


Table S3. Results from the Divtime and Multidivtime analyses. Nodes numbers are depicted in fig. S2. DIVTIME All six constraints

Nodes Point estimate (years × 106)

Standard deviation

95% credibility interval (years × 106)

30 22.01425 2.6303 (17.08512, 27.37454) 31 9.57505 1.42862 (7.05455, 12.62680) 32 20.04225 2.21498 (15.94317, 24.58184) 33 47.2316 2.76193 (41.98074, 52.76308) 34 50.3167 2.77173 (45.05088, 55.81135) 35 35.6822 2.63388 (30.68658, 40.99400) 36 40.1843 2.68585 (35.06333, 45.57177) 37 19.17932 2.02731 (15.36350, 23.28085) 38 21.53562 2.15676 (17.43630, 25.96897) 39 25.54055 2.31106 (21.20864, 30.24902) 40 36.41302 2.57925 (31.57647, 41.57388) 41 41.57746 2.66714 (36.57873, 46.88246) 42 45.82662 2.73156 (40.76129, 51.23790) 43 51.6461 2.81889 (46.37881, 57.30505) 44 54.30112 2.84889 (48.95887, 59.91360) 45 29.84451 2.72846 (24.85206, 35.48524) 46 41.77661 2.60572 (37.42366, 47.17763) 47 51.87178 2.79007 (46.75600, 57.51711) 48 55.17114 2.86814 (49.82219, 60.82810) 49 15.93344 2.18877 (11.96199, 20.51850) 50 43.25103 2.16147 (39.00689, 47.25939) 51 49.40283 1.99472 (45.28458, 52.69085) 52 39.37232 1.65184 (37.11268, 43.04464) 53 52.02211 1.98044 (47.88239, 54.86164) 54 22.12157 2.40312 (17.60806, 27.04482) 55 22.70557 2.34676 (18.25524, 27.55763) 56 24.17959 2.40802 (19.65148, 29.05913) 57 58.3828 2.59157 (53.18106, 63.02626) 58 64.21475 3.28638 (57.96385, 70.71400)


DIVTIME No maximum constraint at node 39


Standard deviation


30 22.05387 2.68459 (17.02026, 27.50882) 31 9.58986 1.451 (7.03161, 12.68661) 32 20.09802 2.24885 (15.97420, 24.75936) 33 47.22963 2.78267 (42.00068, 52.87462) 34 50.28611 2.79476 (45.00059, 55.96544) 35 35.64017 2.63875 (30.66207, 40.99029) 36 40.14065 2.69879 (35.15759, 45.57933) 37 19.14078 2.06503 (15.29690, 23.28943) 38 21.48856 2.2023 (17.38339, 25.95847) 39 25.49 2.36304 (21.04831, 30.29247) 40 36.35162 2.61226 (31.45348, 41.59260) 41 41.52902 2.68391 (36.49644, 46.97722) 42 45.76508 2.73885 (40.61579, 51.27429) 43 51.59512 2.83767 (46.24887, 57.36281) 44 54.25927 2.858 (48.88471, 59.93840) 45 29.8997 2.74889 (24.82261, 35.51594) 46 41.78458 2.62838 (37.40777, 47.26224) 47 51.85021 2.8016 (46.73593, 57.45159) 48 55.13365 2.87842 (49.67935, 60.92174) 49 15.95481 2.18939 (11.97300, 20.53173) 50 43.231 2.17935 (38.80916, 47.19118) 51 49.37014 2.02857 (45.12063, 52.72436) 52 39.37962 1.64337 (37.10863, 43.11389) 53 51.99631 1.99435 (47.72762, 54.87382) 54 22.11442 2.3737 (17.68293, 26.93155) 55 22.70781 2.34987 (18.31995, 27.48823) 56 24.16308 2.38482 (19.71070, 28.96928) 57 58.35715 2.61397 (53.00823, 62.99476) 58 64.15921 3.32034 (57.74125, 70.66890)


DIVTIME No minimum constraint at node 40


Standard deviation


30 21.96768 2.67121 (17.02820, 27.51227) 31 9.56059 1.42973 (7.00342, 12.60015) 32 20.02047 2.2193 (15.80762, 24.57238) 33 47.20002 2.74144 (42.02628, 52.73214) 34 50.28794 2.75161 (45.12864, 55.78763) 35 35.61362 2.6022 (30.58524, 40.90603) 36 40.10992 2.67135 (34.96761, 45.49021) 37 19.15259 2.0567 (15.32373, 23.36773) 38 21.50061 2.18343 (17.38660, 25.92077) 39 25.49139 2.33731 (21.09484, 30.16337) 40 36.34151 2.5689 (31.35613, 41.41163) 41 41.50564 2.64739 (36.43756, 46.78063) 42 45.74839 2.70605 (40.53972, 51.14237) 43 51.59374 2.79857 (46.33165, 57.18599) 44 54.27235 2.82602 (48.96274, 59.95378) 45 29.89776 2.72142 (24.88308, 35.37207) 46 41.79987 2.60051 (37.43305, 47.29352) 47 51.87184 2.7628 (46.78323, 57.41906) 48 55.15021 2.84737 (49.78835, 60.81107) 49 15.89659 2.18704 (11.92900, 20.45956) 50 43.21599 2.18565 (38.76634, 47.24439) 51 49.37496 2.01177 (45.18592, 52.76222) 52 39.37009 1.65095 (37.11242, 43.02544) 53 52.01581 1.97226 (47.78458, 54.87854) 54 22.08963 2.39218 (17.63437, 27.01381) 55 22.67465 2.33874 (18.30441, 27.50438) 56 24.14352 2.40055 (19.64078, 29.03648) 57 58.3792 2.58496 (53.03414, 62.97613) 58 64.20364 3.27871 (57.81929, 70.56990)




Standard deviation


30 22.05953 2.64686 (17.09330, 27.50099) 31 9.58949 1.43179 (7.01481, 12.63746) 32 20.0949 2.205 (15.99053, 24.57445) 33 47.27561 2.74116 (42.11734, 52.71460) 34 50.348 2.75856 (45.17492, 55.83958) 35 35.69369 2.6246 (30.81456, 41.03805) 36 40.19085 2.67831 (35.17772, 45.69075) 37 19.17626 2.06788 (15.37061, 23.46852) 38 21.52786 2.2002 (17.46500, 26.00521) 39 25.54157 2.34053 (21.19091, 30.26960) 40 36.42262 2.58116 (31.58427, 41.73129) 41 41.59007 2.64967 (36.67964, 47.01524) 42 45.83048 2.70298 (40.75674, 51.28142) 43 51.66623 2.793 (46.40025, 57.25894) 44 54.33394 2.82736 (49.05365, 59.91291) 45 29.88566 2.7229 (24.85255, 35.54656) 46 41.81202 2.61022 (37.44085, 47.29870) 47 51.91428 2.78092 (46.77293, 57.52692) 48 55.21529 2.84763 (49.87080, 60.82653) 49 15.94205 2.20251 (11.94084, 20.60110) 50 43.27061 2.20872 (38.78618, 47.35282) 51 49.41393 1.9854 (45.25785, 52.67294) 52 39.41849 1.68439 (37.09856, 43.25004) 53 52.04785 1.95423 (47.86885, 54.86462) 54 22.13918 2.39606 (17.62995, 27.03614) 55 22.74054 2.35102 (18.33962, 27.49763) 56 24.20109 2.40298 (19.75698, 29.04660) 57 58.41379 2.58208 (53.18114, 62.93713) 58 64.24301 3.27896 (57.89010, 70.74010)




Standard deviation


30 21.89526 2.70914 (16.84624, 27.32230) 31 9.52615 1.46359 (6.90475, 12.64161) 32 19.9437 2.28153 (15.64157, 24.60319) 33 46.95011 2.9717 (41.25906, 52.71705) 34 50.02168 2.98091 (44.25967, 55.79341) 35 35.46802 2.73407 (30.31095, 40.88843) 36 39.93492 2.81536 (34.56757, 45.51297) 37 19.05443 2.06554 (15.33637, 23.34260) 38 21.39672 2.20179 (17.40666, 25.92270) 39 25.37224 2.36555 (21.04148, 30.20157) 40 36.18969 2.68617 (31.10991, 41.59280) 41 41.32739 2.80025 (35.99995, 46.87924) 42 45.5418 2.88925 (39.97069, 51.14157) 43 51.33884 3.01824 (45.41655, 57.12372) 44 53.99842 3.06825 (47.92449, 59.88447) 45 29.59994 2.97168 (23.86544, 35.59710) 46 41.42011 3.00028 (35.51467, 47.31390) 47 51.57662 3.03974 (45.56953, 57.40758) 48 54.87521 3.09411 (48.80173, 60.83938) 49 15.92037 2.18765 (11.92578, 20.52479) 50 43.15362 2.23681 (38.60790, 47.21777) 51 49.26455 2.08762 (44.89846, 52.67416) 52 39.34013 1.64064 (37.09397, 43.04125) 53 51.87187 2.0801 (47.41952, 54.85864) 54 22.04246 2.36713 (17.63286, 26.85218) 55 22.62935 2.31954 (18.33014, 27.30460) 56 24.08553 2.37749 (19.63565, 28.87939) 57 58.15873 2.73262 (52.46546, 62.90788) 58 63.91615 3.46616 (56.97773, 70.54494)




Standard deviation


30 21.34773 2.62422 (16.57572, 26.91381) 31 9.28355 1.42667 (6.77623, 12.28983) 32 19.47009 2.23 (15.42916, 24.12170) 33 45.88986 3.02647 (40.49589, 52.03714) 34 48.8658 3.0921 (43.32832, 55.11682) 35 34.64565 2.7 (29.89437, 40.30714) 36 39.02655 2.81465 (34.11684, 44.89747) 37 18.62183 2.03545 (15.01355, 22.89212) 38 20.90855 2.17619 (17.03374, 25.45633) 39 24.78217 2.33768 (20.64410, 29.69183) 40 35.36331 2.64849 (30.73289, 40.82575) 41 40.38715 2.80871 (35.49667, 46.25210) 42 44.50461 2.94528 (39.32615, 50.51663) 43 50.1492 3.16308 (44.53010, 56.47155) 44 52.73374 3.24911 (46.90613, 59.14644) 45 29.19569 2.63059 (24.55965, 34.78426) 46 40.77262 2.58684 (37.17150, 46.48865) 47 50.43056 3.08857 (45.06616, 56.74647) 48 53.5807 3.28535 (47.65011, 60.10672) 49 15.19289 2.29085 (11.02194, 19.98611) 50 41.49529 2.99733 (35.20317, 46.76584) 51 47.52084 3.04977 (41.20802, 52.39643) 52 37.12618 2.97147 (31.12274, 42.62056) 53 50.10261 3.08002 (43.69569, 54.74975) 54 21.13148 2.5245 (16.31511, 26.33119) 55 21.68906 2.50937 (16.95288, 26.81186) 56 23.09232 2.58538 (18.16493, 28.38588) 57 56.47714 3.47449 (49.50979, 62.47537) 58 62.31422 3.97203 (54.86323, 69.91611)


DIVTIME No maximum constraint at node 53


Standard deviation


30 24.58874 3.80255 (17.88082, 32.68125) 31 10.70842 1.9005 (7.45619, 14.85377) 32 22.45833 3.30125 (16.68241, 29.54966) 33 52.94139 5.94649 (43.28798, 65.77811) 34 56.41059 6.25991 (46.33369, 69.80977) 35 39.77139 4.57072 (31.92358, 49.19062) 36 44.82122 4.96776 (36.48208, 54.98004) 37 21.13749 2.60727 (16.21309, 25.96902) 38 23.74269 2.82513 (18.42858, 28.81535) 39 28.19967 3.16955 (22.19247, 33.63725) 40 40.4895 4.43321 (32.79652, 49.18699) 41 46.39168 5.08295 (37.83760, 56.68369) 42 51.21968 5.61047 (41.97662, 63.06672) 43 57.87598 6.36438 (47.61780, 71.60070) 44 60.92267 6.69946 (50.22354, 75.36590) 45 33.35188 4.4166 (26.00772, 42.96111) 46 46.67718 5.39452 (38.08998, 58.37587) 47 58.17114 6.4414 (47.87179, 72.05186) 48 61.91836 6.82066 (51.08204, 76.70061) 49 18.01702 3.16526 (12.72977, 25.08102) 50 48.82393 5.70779 (40.10657, 61.55083) 51 55.79861 6.26195 (46.28352, 69.73844) 52 43.9951 5.05288 (37.31893, 55.64816) 53 58.77446 6.52992 (48.99119, 73.29711) 54 24.97485 3.74898 (18.70666, 33.39214) 55 25.64749 3.75741 (19.45208, 33.88817) 56 27.29468 3.93265 (20.84595, 35.99214) 57 65.85844 7.32158 (54.53148, 82.22862) 58 72.27564 8.08191 (59.54893, 89.94825)


DIVTIME 56 Mya prior, all constraints


Standard deviation


30 21.33793 2.38352 (16.80436, 26.18619) 31 8.97199 1.30926 (6.64177, 11.76023) 32 18.89551 2.00702 (15.12632, 22.96247) 33 45.27094 2.26963 (40.99716, 49.83521) 34 47.97888 2.26165 (43.84005, 52.55103) 35 34.11987 2.21133 (30.02739, 38.68805) 36 38.39314 2.22401 (34.42466, 42.93658) 37 18.27366 1.80159 (14.89963, 21.99316) 38 20.39328 1.89044 (16.86486, 24.21081) 39 24.18118 1.99082 (20.52533, 28.23995) 40 34.54925 2.15141 (30.69293, 38.96936) 41 39.65169 2.19251 (35.77245, 44.19717) 42 43.36807 2.23178 (39.31622, 47.94655) 43 48.79089 2.28972 (44.55795, 53.46509) 44 51.56538 2.29131 (47.35061, 56.18495) 45 28.83172 2.31209 (24.66363, 33.64849) 46 40.26807 2.07337 (37.19502, 44.84675) 47 49.61587 2.25152 (45.59341, 54.33023) 48 52.56092 2.31496 (48.27777, 57.22868) 49 16.20527 2.18034 (12.27157, 20.83883) 50 43.67076 2.04639 (39.52830, 47.44108) 51 49.85248 1.84964 (45.96141, 52.86154) 52 39.43535 1.639 (37.10805, 43.04928) 53 52.31517 1.80433 (48.38404, 54.87443) 54 22.7312 2.36732 (18.30356, 27.62067) 55 22.81523 2.29371 (18.51443, 27.51406) 56 24.65301 2.3556 (20.26165, 29.53995) 57 58.43236 2.3532 (53.60806, 62.62887) 58 62.63056 2.81482 (57.11785, 68.17374)


MULTIDIVTIME 65 Mya prior, all constraints


Standard deviation


30 20.82856 1.98188 (17.17859, 24.93175) 31 12.70627 1.45693 (10.03162, 15.76665) 32 22.08695 1.92884 (18.47736, 26.11053) 33 46.3575 2.65601 (41.52793, 51.73516) 34 47.67065 2.67756 (42.82388, 53.16473) 35 40.65657 2.53756 (35.96456, 45.85757) 36 42.26832 2.55359 (37.64685, 47.49219) 37 23.41805 1.91708 (19.89542, 27.36130) 38 25.11741 1.97373 (21.53462, 29.17009) 39 26.57768 2.01355 (22.89254, 30.72336) 40 37.57782 2.38917 (33.23516, 42.44533) 41 43.10977 2.55345 (38.47039, 48.34105) 42 45.40091 2.63223 (40.60316, 50.75272) 43 51.53168 2.80495 (46.42331, 57.16523) 44 52.17261 2.80773 (47.11479, 57.89156) 45 32.56694 2.61272 (27.79477, 37.97400) 46 42.54776 2.59379 (37.83790, 47.93588) 47 50.96774 2.79501 (45.90431, 56.70255) 48 52.68192 2.81696 (47.61985, 58.40477) 49 15.18104 1.54169 (12.36128, 18.41456) 50 46.54006 2.26323 (42.33212, 51.08670) 51 48.60186 2.20142 (44.59773, 53.04033) 52 38.5572 1.34767 (37.04609, 41.96100) 53 49.8588 2.19226 (45.83383, 54.22694) 54 21.30318 1.78931 (18.04284, 24.95398) 55 20.62245 1.74171 (17.42808, 24.23068) 56 22.0912 1.80105 (18.77040, 25.82280) 57 55.64543 2.60594 (50.91364, 60.90003) 58 60.44898 2.91305 (55.21640, 66.31444)


MULTIDIVTIME 56 Mya prior, all constraints


Standard deviation


30 20.57707 1.94968 (16.94563, 24.54764) 31 12.45105 1.45591 (9.79628, 15.48864) 32 21.68297 1.9046 (18.19148, 25.62239) 33 45.54137 2.57698 (40.95932, 50.92988) 34 46.81998 2.58161 (42.21170, 52.22180) 35 39.94301 2.44261 (35.53363, 45.15050) 36 41.52283 2.4739 (37.08974, 46.76410) 37 23.00935 1.90231 (19.58066, 27.00308) 38 24.67241 1.96195 (21.11943, 28.77793) 39 26.1062 1.97865 (22.44924, 30.23892) 40 36.93487 2.33444 (32.72298, 41.86494) 41 42.35226 2.48569 (37.89967, 47.66580) 42 44.58779 2.57203 (40.05450, 50.04787) 43 50.59176 2.7044 (45.89938, 56.29430) 44 51.2145 2.71444 (46.51985, 56.97779) 45 31.97307 2.53973 (27.30625, 37.30240) 46 41.77479 2.47168 (37.58670, 47.05641) 47 50.01694 2.67861 (45.36714, 55.68119) 48 51.70361 2.7195 (46.99670, 57.42991) 49 15.04461 1.51617 (12.27389, 18.16130) 50 45.90593 2.16002 (41.99399, 50.43169) 51 47.95238 2.13354 (44.12568, 52.42482) 52 38.33258 1.21128 (37.03583, 41.49933) 53 49.1896 2.11897 (45.42244, 53.64849) 54 21.14459 1.75455 (17.87140, 24.72873) 55 20.4743 1.71465 (17.34764, 23.99715) 56 21.92389 1.76718 (18.62578, 25.51721) 57 54.73889 2.50785 (50.25747, 60.01673) 58 59.30108 2.82385 (54.33524, 65.30633)


Table S4. The ancestral reconstructions of geographic origin as mapped onto each of the six most parsimonious trees with both accelerated and delayed transformations for the nine-state and two-state analyses (Fig. 3).

Trees Order

1 2 3 4 5 6

Chiroptera N.America/ N.America/L

N.America/ N.America/L





Yinpterochiroptera Asia/Asia/L Europe/Europe/L Europe/Europe/L Asia/Asia/L Europe/Europe/L Asia/Asia/L

Rhinolophoidea Asia/Asia/L Asia/Asia/L Asia/Asia/L Asia/Asia/L Asia/Asia/L Asia/Asia/L

Pteropodidae Asia/Asia/L Asia/Asia/L Asia/Asia/L Asia/Asia/L Asia/Asia/L Asia/Asia/L

Yangochiroptera Asia/Europe/L Europe/Europe/L Europe/Europe/L Europe/Europe/L Europe/Europe/L Asia/Asia/L

Emballonuroidea Asia/Europe/L NK/Europe/L NK/Europe/L NK/Europe/L NK/Europe/L Asia/Asia/L

Vespertilionoidea† S.America/NK/L S.America/NK/L S.America/NK/L S.America/NK/L S.America/NK/L S.America/ S.America/L

Noctilionoidea S.America/NK/G S.America/NK/ G S.America/NK/G S.America/NK/G S.America/NK/G S.America/ S.America/G

*Acctran/Deltran/G or L; G, Gondwanan; L, Laurasian; NK, not known †Discrepancy in the nine state versus two state analyses


Table S5. Estimation of the missing fossil record per lineage. Values are in millions of years unless specified otherwise.

Branch number Taxon Oldest fossil Molecular

age Time interval of internal branches

Age of lineage

Total missing per lineage

Percent missing per

lineage Pteropodidae*

1 Pteropus 0.89 23 23 22.11 96.13 2 Rousettus 0.13 23 23 22.87 99.43 3 0.89 24 24 – 23 = 1 1 1 100.00 4 Cynopterus 0.005 22 22 21.995 99.98 5 Nyctimene 0.005 22 22 21.995 99.98 6 0.005 24 24 – 22 = 2 2 2 100.00 7 Pteropodidae indet. 26.15 58 58 – 24 = 34 34 31.85 93.68

Rhinolophoidea 8 Rhinolophus 43 39 39 0 0.00 9 Hipposideros 43 39 39 0 0.00 10 Pseudorhinolophus 45.15 52 52 – 39 = 13 13 6.85 52.69 11 Megaderma 28.5 16 16 0 0.00 12 Macroderma 13.8 16 16 2.2 13.75 13 Necromantis 43 43 43 0 0.00 14 Craseonycteris 0.005 43 43 42.995 99.99 15 Necromantis 43 49 49 – 43 = 6 6 6 100.00 16 Rhinopoma 0.005 49 49 48.995 99.99 17 Necromantis 43 52 52 – 49 = 3 3 3 100.00 18 Pseudorhinolophus 45.15 58 58 – 52 = 6 6 6 100.00 19 Pseudorhinolophus 45.15 64 64 – 58 = 6 6 6 100.00

Emballonuroidea 20 Nycteris 26.15 52 52 25.85 49.71 21 Emballonura 0.89 30 30 29.11 97.03 22 Diclidurus 12.4 30 30 17.6 58.67 23 Diclidurus 12.4 30 42 – 30 = 12 12 12 100.00 24 Vespertiliavus 43.8 42 42 0 0.00


Table S5, continued

Branch number Taxon Oldest

fossil Molecular

age Time interval of

internal branches Age of lineage


Percent missing

per lineage 25 Tachypteron† 45.15 52 52 – 42 = 10 10 6.85 68.50 26 Tachypteron 45.15 55 55 – 52 = 3 3 3 100.00

Noctilionoidea 27 Anoura 0.89 19 19 18.11 95.32 28 Artibeus 0.89 19 19 18.11 95.32 29 0.89 22 22 – 19 = 3 3 3 100.00 30 Tonatia 12.5 22 22 9.5 43.18 31 Tonatia 12.5 26 26 – 22 = 4 4 4 100.00 32 Desmodus 1.275 26 26 24.725 95.10 33 Tonatia 12.5 36 36 – 26 = 10 10 10 100.00 34 Mormoopidae indet. 31 36 36 5 13.89 35 Mormoopidae indet. 31 42 42 – 36 = 6 6 6 100.00 36 Noctilio 12.4 36 36 23.6 65.56 37 Furipterus 0.005 36 36 35.995 99.99 38 Noctilio 12.4 40 40 – 36 = 4 4 4 100.00 39 Thyroptera 12.4 40 40 27.6 69.00 40 Noctilio 12.4 42 42 – 40 = 2 2 2 100.00 41 Mormoopidae indet. 31 46 46 – 42 = 4 4 4 100.00 42 Icarops 20.1 46 46 25.9 56.30 43 Mormoopidae indet. 31 52 52 – 46 = 6 6 6 100.00 44 Myzopoda 1.275 52 52 50.725 97.55 45 Mormoopidae indet 31 54 54 – 52 = 2 2 2 100.00

Vespertilionoidea 46 Antrozous 7.5 10 10 2.5 25.00 47 Rhogeessa 0.005 10 10 9.995 99.95 48 Antrozous 7.5 20 20 – 10 = 10 10 10 100.00 49 Myotis‡ 20 20 20 0 0.00 50 Oligomyotis 31.1 47 47 – 20 = 27 27 15.9 58.89


Table S5, continued

Branch number Taxon Oldest fossil Molecular

age Time interval of

internal branches Age of lineage


Percent missing

per lineage 51 Tadarida 35.5 22 22 0 0.00 52 Eumops 12.4 22 22 9.6 43.64 53 Wallia 43.25 47 47 – 22 = 25 25 3.75 15.00 54 Wallia 43.25 50 50 – 47 = 3 3 3 100.00 55 Primonatalus§ 31 50 50 19 38.00 56 Wallia 43.25 54 54 – 50 = 4 4 4 100.00 57 Wallia 43.25 55 55 – 54 = 1 1 1 100.00 58 Tachypteron 45.15 64 64 – 55 = 9 9 9 100.00

*Although it has been suggested that the oldest pteropodid is from the Late Eocene of Thailand (S38), this fossil consists of a single tooth that is considered derived among pteropodids. The validity and assignment of this fossil to crown group pteropdids has been recently questioned (S32); hence, it is considered an equivocal fossil and was not used in our analyses. †Eppsinycteris, originally considered the oldest emballonurid, has recently been questioned as an emballonurid and even as a bat (S28); therefore, it was not used in our analyses. ‡Although it has been suggested that Myotis have been found from the Early Oligocene, these fossils have recently been identified as eptesicoid fossils rather than Myotis fossils (S39). The oldest unequivocal Myotis fossils are from about 20 Mya (S39). §Other Tertiary genera have been considered natalids including the fossils Ageina, Chadronycteris, Chamtwaria, Honrovotis, and Stehlinia; however, these taxa have been questioned as belonging to the Natalidae (S31).

Table S6. GenBank accession numbers

Species ADRA2B ADORA3 ADRB2 APP ATP7A BDNF BMI BRCA1 CREM EDG1 PLCB4 PNOC RAG1 RAG2 TITIN2/3 TITIN6/7 TYR VWF ZFX1 Pteropus rayneri AF337539 AF203751 AF203759 AF203769 AY834670 AY834703 AY012074

Pteropus giganteus AY011233 AY011293 AY011356 AY011420 AY011483 AY011541 AY011666 AY011727 AY011790 AY011847 AY012021Pteropus hypomelanus AF203777

2 Cynopterus sphinx AJ251181 AF203750 AF203758 AF203768 U31605Cynopterus brachyotis AY834412 AY834436 AY834460 AY834484 AY834508 AY834532 AY839080 AY834556 AY835940 AY834580 AY834671 AY834704 AY834605 AY834625

3 Rousettus amplexicadatus AJ315937 AY057829 AF447512 AF447529 AY012022 AF447547Rousettus lanosus AY011234 AY011294 AY011357 AY011421 AY011484 AY011542 AY011667 AY011728 AY011791 AY011848 AY834672 AY834705 AY012075

4 Nyctimene albiventer AJ419805 AY834413 AY834437 AY834461 AY834485 AY834509 AY834533 AF447502 AY839081 AY834557 AY835941 AY834581 AF447514 AF447531 AY834673 AY834706 AY834606 AF447549 AY8346265 Rhinolophus creaghi AJ419806 AY834414 AY834438 AY834462 AY834486 AY834510 AY834534 AF447499 AY839082 AY834558 AY835942 AY834582 AF447511 AF447528 AY834674 AY834707 AY834607 AF447546 AY8346276 Hipposideros commersoni AF337538 AY834415 AY834439 AY834463 AY834487 AY834511 AY834535 AF203752 AY059698 AY834559 AY835943 AY834583 AF203760 AF203770 AY834675 AY834708 AY834608 AF203778 AY8346287 Megaderma lyra AF337537 AY059670 AY059676 AY059680 AY059684 AY059688 AY059692 AF203749 AY839083 AY059701 AY059708 AY059711 AF203757 AF203767 AY834676 AY834709 AY059716 U31616 AY0597198 Macroderma gigas AY834404 AY834416 AY834440 AY834464 AY834488 AY834512 AY834536 AY834645 AY839084 AY834560 AY835944 AY834584 AY834654 AY834661 AY834677 AY834710 AY834609 AY834736 AY834629

Nycteris grandis AJ419807 AF447484 AY834579 AY835945 AY834604 AF447506 AF447523 AY834678 AY834711 AY834610 AF447541 ??????Nycteris thebaica AY011235 AY011295 AY011358 AY011422 AY011485 AY011543 AY011668

10 Rhinopoma hardwicki AJ419809 AY834417 AY834441 AY834465 AY834489 AY834513 AY834537 AF447504 AY839085 AY834561 AY835946 AY834585 AF447535 AF447535 AY834679 AY834712 AY834611 AF447551 AY83463011 Emballonura atrata AJ419810 AY834418 AY834442 AY834466 AY834490 AY834514 AY834538 AF447505 AY839086 AY834562 AY835947 AY834586 AF447519 AF447536 AY834680 AY834713 AY834612 AF203776 ?????12 Taphozous nudiventris AF337543 AY834419 AY834443 AY834467 AY834491 AY834515 AY834539 AF203748 AY839087 AY834563 AY835948 AY834587 AF203756 AF203766 AY834681 AY834714 AY834613 AF447540 AY83463113 Rhynchonycteris naso AY834405 AY834420 AY834444 AY834468 AY834492 AY834516 AY834540 AY834646 AY839088 ????? AY835949 AY834588 ????? AY834662 AY834682 AY834715 AY834614 ????? ?????14 Tonatia bidens AF337541 AF203745 AF203753 AF203763 U31622

Tonatia silvicola/saurophila AY834421 AY834445 AY834469 AY834493 AY834517 AY834541 AY839089 AY834564 AY835950 AY834589 AY834683 AY834716 AY834615 AY83463215 Artibeus jamaicensis AY834406 AY011232 AY011292 AY011355 AY011419 AY011482 AY011540 AY834646 AY011665 AY011726 AY011789 AY011846 AY834655 AY834663 AY834684 AY834717 AY012020 AY834737 AY01207316 Desmodus rotundus AJ419811 AY834422 AY834446 AY834470 AY834494 AY834518 AY834542 AF447503 AY839090 AY834565 AY835951 AY834590 AF447517 AF447534 AY834685 ????? AY834616 AF447550 AY83463317 Anoura geoffroyi AY834407 AY834423 AY834447 AY834471 AY834495 AY834519 AY834543 AY834648 AY839091 AY834566 AY835952 AY834591 AY834656 AY834664 AY834686 AY834718 AY834617 AY834738 AY83463418 Noctilio albiventris AJ419812 AY834424 AY834448 AY834472 AY834496 AY834520 AY834544 AF447497 AY839092 AY834567 AY835953 AY834592 AF447509 AF447526 AY834687 AY834719 ????? AF447544 ?????19 Antrozous pallidus AJ419813 AY834425 AY834449 AY834473 AY834497 AY834521 AY834545 AF447495 AY839093 AY834568 AY835954 AY834593 AF447507 AF447524 AY834688 AY834720 AY834618 AF447542 AY83463520 Rhogeessa tumida AJ419814 AY834426 AY834450 AY834474 AY834498 AY834522 AY834546 AF447496 AY839094 AY834569 AY835955 AY834594 AF447508 AF447525 AY834689 AY834721 AY834619 AF447543 AY83463621 Myotis daubentoni AF337540 AY834427 AY834451 AY834475 AY834499 AY834523 AY834547 AF203746 AY839095 AY834570 AY835956 AY834595 AF203754 AF203764 AY834690 AY834722 AY834620 AF203775 ?????

Myotis velifer22 Myzopoda aurita AY834408 AY834428 AY834452 AY834476 AY834500 AY834524 AY834548 AY834649 AY839096 AY834571 AY835957 AY834596 ????? AY834665 AY834690 AY834723 ????? ????? AY83463723 Pteronotus parnellii AY245422 AY834429 AY834453 AY834477 AY834501 AY834525 AY834549 AY245828 AY839097 AY834572 AY835958 AY834597 AY245418 AY245416 AY834692 AY834724 AY834621 AY245420 AY83463824 Thyroptera tricolor ?????? AY834430 AY834454 AY834478 AY834502 AY834526 AY834550 AY834650 AY839098 AY834573 AY835959 AY834598 AY834657 AY834666 ????? AY834725 ????? AY834739 AY83463925 Mystacina tuberculata AY245423 AY834431 AY834455 AY834479 AY834503 AY834527 AY834551 AY245829 AY839099 AY834574 AY835960 AY834599 AY245419 AY245417 AY834693 AY834726 AY834622 AY245421 AY83464026 Furipterus horrens AY834409 AY834432 AY834456 AY834480 AY834504 AY834528 AY834552 AY834651 AY839100 AY834575 AY835961 AY834600 AY834658 AY834667 AY834694 AY834727 ????? AY834740 AY83464127 Natalus stramineus AJ419815 AY834433 AY834457 AY834481 AY834505 AY834529 AY834553 AF447498 AY839101 AY834576 AY835962 AY834601 AF447510 AF447527 AY834695 AY834728 AY834623 AF447545 AY83464228 Tadarida brasiliensis AF337542 AY059669 AY059675 AY059679 AY059683 AY059687 AY059691 AF203747 AY059697 AY059700 AY059707 AY059710 AF203755 AF203765 AY834696 AY834729 AY059715 AF061061 AY05971829 Eumops auripendulus AY834410 AY834434 AY834458 AY834482 AY834506 AY834530 AY834554 AY834652 AY839102 AY834577 AY835963 AY834602 AY834659 AY834668 AY834697 AY834730 AY834624 AY834741 AY83464330 Craseonycteris thonglongyai AY834411 AY834435 AY834459 AY834483 AY834507 AY834531 AY834555 AY834653 AY839103 AY834578 AY835964 AY834603 AY834660 AY834669 AY834698 AY834731 ????? AY834742 AY83464431 Felis catus AJ251174 AY011246 AY011306 AY011369 AY011433 AY011496 AF284018 AY011679 AY011738 AY011802 AY011858 AF203761 AF203771 AY834699 AY834732 AY012029 AF061062 AY012085

Panthera onca AY01155532 Tragelaphus eurycerus AY011240 AY011300 AY011363 AY011427 AY011490 AY011547 AY011673 AY011732 AY011796 AY011853 AY834700 AY834733 AY012026 AY012079

Bos taurus Y15944 AY077732 AF447520 AF447537 X6382033 Condylura cristata AY011199 AY011260 AY011321 AY011385 AY011449 AY011508 AY011630 AY011693 AY01175 ????? AY834701 AY834734 AY011989 AY012041

Talpa europaea Y12520 AF447515 AF447532Scalopus aquaticus AF284007 AF076479

34 Ceratotherium simum AY011244 AY011304 AY011367 AY011431 AY011494 AY011551 AY057830 AY011677 AY011736 AY011800 AY011856 AY834702 AY834735 AY012028 AY011431 AY012083Equus caballus Y15945 AF447516 AF447533Equus asinus U31610xxxxx=new sequence; ???????=missing

Table S7. Geographic characters and states used in the geographic ancestralreconstructions.

CharactersTaxa

1 2

Pteropodidae L 2&3&4&5Rhinopomatidae L 2&3Megadermatidae L 2&3&5Rhinolophidae L 1&2&3&4&5Craseonycteridae L 3Emballonuridae L 2&3&4&5&8Nycteridae L 2&3&4Myzopodidae G 2&4Mystacinidae G 5&6Furipteridae G 8Thyropteridae G 8Noctilionidae G 8&9Mormoopidae G 8&9Phyllostomidae G 8&9Natalidae G&L 8&9Vespertilionidae L 1&2&3&4&5&6&7&8&9Molossidae G&L 1&2&3&4&5&7&8&9Icaronycteris L 7Archaeonycteris L 1Hassianycteris L 1Paleochiropteryx L 1Carnivora L 1&2&3&4&5&7&8&9Cetartiodactyla L 1&2&3&4&5&6&7&8&9Eulipotyphla L 1&2&3&4&7&8Perissodactyla L 1&2&3&7&8Pholidota L 2&3&7&8

L, Laurasia; G, Gondwana; 1, Europe; 2, Africa; 3, Asia; 4, Madagascar; 5, Australianregion; 6, New Zealand; 7, North America; 8, Central + South America; 9, West Indies


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