RESEARCH ARTICLE Open Access
Evolutionary history of endemic Sulawesi
squirrels constructed from UCEs and
mitogenomes sequenced from museum
specimens
Melissa T. R. Hawkins1,2,3*, Jennifer A. Leonard4, Kristofer M. Helgen2, Molly M. McDonough1,2,
Larry L. Rockwood5 and Jesus E. Maldonado1,2
Abstract
Background: The Indonesian island of Sulawesi has a complex geological history. It is composed of several
landmasses that have arrived at a near modern configuration only in the past few million years. It is the largest
island in the biodiversity hotspot of Wallacea—an area demarcated by the biogeographic breaks between Wallace’s
and Lydekker’s lines. The mammal fauna of Sulawesi is transitional between Asian and Australian faunas. Sulawesi’s
three genera of squirrels, all endemic (subfamily Nannosciurinae: Hyosciurus, Rubrisciurus and Prosciurillus), are of
Asian origin and have evolved a variety of phenotypes that allow a range of ecological niche specializations. Here
we present a molecular phylogeny of this radiation using data from museum specimens. High throughput
sequencing technology was used to generate whole mitochondrial genomes and a panel of nuclear ultraconserved
elements providing a large genome-wide dataset for inferring phylogenetic relationships.
Results: Our analysis confirmed monophyly of the Sulawesi taxa with deep divergences between the three endemic
genera, which predate the amalgamation of the current island of Sulawesi. This suggests lineages may have evolved in
allopatry after crossing Wallace’s line. Nuclear and mitochondrial analyses were largely congruent and well supported,
except for the placement of Prosciurillus murinus. Mitochondrial analysis revealed paraphyly for Prosciurillus, with P. murinus
between or outside of Hyosciurus and Rubrisciurus, separate from other species of Prosciurillus. A deep but monophyletic
history for the four included species of Prosciurillus was recovered with the nuclear data.
Conclusions: The divergence of the Sulawesi squirrels from their closest relatives dated to ~9.7–12.5 million years ago
(MYA), pushing back the age estimate of this ancient adaptive radiation prior to the formation of the current conformation
of Sulawesi. Generic level diversification took place around 9.7 MYA, opening the possibility that the genera represent
allopatric lineages that evolved in isolation in an ancient proto-Sulawesian archipelago. We propose that incongruence
between phylogenies based on nuclear and mitochondrial sequences may have resulted from biogeographic
discordance, when two allopatric lineages come into secondary contact, with complete replacement of the mitochondria
in one species.
Keywords: Wallacea, Ultraconserved elements, Species tree, Sciuridae, Ancient introgression
* Correspondence: mtroberts2@gmail.com
1Center for Conservation and Evolutionary Genetics, Smithsonian
Conservation Biology Institute, National Zoological Park, Washington, DC
20008, USA
2Division of Mammals, National Museum of Natural History, MRC 108,
Smithsonian Institution, P.O. Box 37012, Washington, DC 20013-7012, USA
Full list of author information is available at the end of the article
© 2016 Hawkins et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 
DOI 10.1186/s12862-016-0650-z
Background
The Indonesian island of Sulawesi has a complex geo-
logical history. The current ‘k’ shaped landmass consists
of four peninsulas and a central core [1]. Geologists have
estimated the movement and extent for each fragment
of the island complex [2, 3], and determined that the
present conformation is relatively recent (limited to the
past ~5 million years). The four major peninsulas cor-
respond to landmasses from at least three tectonic prov-
inces, and two smaller continental fragments [4, 5].
Throughout geologic history, Sulawesi has dramatically
changed in configuration, area, and elevation [2, 6, 7].
The first appearance of what we presently consider
Sulawesi was the western peninsula, or west Sulawesi,
during Eocene sea level changes (~40 MYA) [8]. In the
mid Oligocene (~30 MYA) west Sulawesi was sur-
rounded by ocean, but terrestrial habitats were present.
At this time, east Java and south Sulawesi were still sub-
merged in shallow marine environments (as determined
by carbonate deposits) [8]. Rapid geologic changes ~23
MYA (in the Cenozoic) resulted in the collision of the
Australian plate (specifically the Sula spur) and the
Sunda Shelf, which led to some degree of mountain for-
mation in Sulawesi and modified the elevation of eastern
Sulawesi. The southern peninsula continued to be at
least partially submerged at this time, and west Sulawesi
was relatively flat. The nature of the connection between
eastern and western Sulawesi is unknown. The geo-
logical record is scarce for this period of time, but the
few poorly dated marine sediments available indicate
that the area may have been largely subaerial [8].
During the mid Miocene a process known as ‘rollback’
was likely ongoing near the subduction zone around the
north peninsula of Sulawesi [8]. Essentially this process
involves the expansion of terrestrial environments sur-
rounding a subduction zone when the inflow of heated
mantle pushes to the surface, elevates, and expands the
terrestrial environment in the opposite direction of the
plate movement (see Figures 11 and 12 in [8]). This
rollback process likely caused a long-lived terrestrial
environment in Sulawesi [8]. Additional evidence for
extended terrestrial habitat comes from central and
southeastern Sulawesi, where a significant amount of
erosion and prolonged weathering has been docu-
mented. Much of Sulawesi was exposed land during the
Miocene, but few additional details are available regard-
ing the extent of land and elevation through time [5, 8].
The present topography of Sulawesi dates to the Late
Miocene, approximately 5 MYA, when tectonic move-
ments affected the amount of exposed land and extent
of mountains across Sulawesi [8]. Although sea level
changes during the Pleistocene had an extreme effect on
the exposed land area and therefore mobility of species
across the Sunda Shelf, the effect on Sulawesi was minor
[5, 9–12]. The combined isolation and steep edges of
tectonic shelves on Sulawesi likely prevented a terrestrial
connection between islands in Wallacea [8]. The com-
plex geology of this biodiverse island has confounded
many studies trying to determine the age of endemic lin-
eages, which is where phylogenetic reconstruction can
aid in understanding [5, 13].
Mammals on Sulawesi are primarily of Asian descent,
except for the phalangerid marsupials and pteropodine
bats, which have Australian or Pacific origin [14, 15].
The earliest estimated mammalian colonization of
Sulawesi was by phalangerid marsupials approximately
21–23 MYA [14]. Squirrels are estimated as the second
oldest arrivals, around 11 MYA [16]. Subsequent mam-
malian colonization events (all of which occurred from
Asia, and have been dated) occurred during the Pliocene
(2.6–5.3 MYA) and include the first colonization events
for both macaques and shrews [17–19]. Interestingly,
macaques and shrews both colonized Sulawesi a second
time in the Pleistocene (0.01–2.6 MYA). Other mamma-
lian colonization events occurred primarily during the
Pleistocene, including bovids and suids [20–24], al-
though recent re-dating recovered vastly different esti-
mates with a trend towards much older colonization
events [5]. The estimated date of arrival of the squirrels,
however, remained largely unchanged.
With the exception of a recent morphological and eco-
logical analysis that detailed the distribution and
characterization of each species [25], squirrels are some
of the least studied taxa on Sulawesi. Three genera of
endemic squirrels (subfamily Nannosciurinae/Callosciur-
inae, referred to hereafter as Nannosciurinae) occur on
Sulawesi: Hyosciurus, the long-nosed squirrels; Rubris-
ciurus, the giant ground squirrels; and Prosciurillus, the
relatively small-bodied tree squirrels. The genus Hyos-
ciurus contains two named species, H. ileile and H. hein-
richi. These terrestrial species have extremely elongate
rostra, possibly for a specialized invertebrate diet [26].
Both species of Hyosciurus have fairly restricted ranges,
and H. ileile has two disjunct recorded populations, one
in the northern peninsula and the second in the central
core, although the species is probably more widespread
[25, 26]. Hyosciurus heinrichi is distributed through the
highlands of the central core. The genus Rubrisciurus
contains a single species, R. rubriventer, which is distrib-
uted across the entire island. Finally, Prosciurillus is the
most diverse genus, containing seven recognized species
(P. abstrusus, P. alstoni, P. leucomus, P. murinus, P.
weberi, P. topapuensis, and P. rosenbergii- located north
of Sulawesi, on four small islands), all of which (except
P. murinus) have restricted ranges (Fig. 1). Several Pros-
ciurillus species are found in specific habitat types, for
example, P. weberi occurs in mangrove forests, and P.
topapuensis and P. abstrusus in montane forests [25, 27].
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 Page 2 of 16
The three genera are easily distinguished morphologically.
Hyosciurus has a very long rostrum, Rubrisciurus is very
large and bright red, while the species of Prosciurillus, the
most diverse and variable genus, are brownish or olivaceous
in general coloration. Members of this latter genus usually
have ear tufts of various colors and banding along the tail,
and some have either patches of coloration along the nape
(P. leucomus) or dorsal stripes (P. weberi) [25, 26, 28]. The
smallest and most plain squirrel, Prosciurillus murinus,
lacks ear tufts and tail banding.
To date, only one sciurid-wide phylogeny has included
three of these species, one representative per genus (Pros-
ciurillus murinus, Rubrisciurus rubriventer and Hyosciurus
heinrichi) [16]. Mercer and Roth [16] analyzed two mito-
chondrial genes (12S and 16S rRNA) and one nuclear
gene (IRBP), based on which they suggested that a single
squirrel lineage crossed Wallace’s Line to give rise to these
three genera of squirrels on Sulawesi. Here we estimated
the phylogeny of endemic Sulawesi squirrels using rela-
tively dense taxonomic sampling across Sulawesi and sev-
eral Sundaland outgroup taxa in order to test the
hypothesis that there was a single colonization event for
Sulawesi squirrels. We compared divergence time esti-
mates to what is known of the geological history of
Sulawesi in order to determine which geological events
may have been important in the history of the group. We
sequenced whole mitochondrial genomes (mitogenomes
hereafter), which provide much greater resolution than
single mitochondrial genes for evaluating phylogenetic
relationships, especially over short time scales [29, 30].
Here we analyze all non-saturated coding genes of the se-
quenced mitogenomes. Given that mitochondrial DNA is
inherited as a single unit, species tree estimates require
additional independently inherited markers [31]. There-
fore, we enriched for a panel of nuclear markers, ultracon-
served elements (UCEs), to derive sequences from the
variable flanking regions [32, 33], which have proven
useful for resolving rapid radiations in a variety of taxa
[32, 34]. Fresh tissue samples for most of the species are
not available; therefore, we obtained our molecular data
from historic museum skins, mostly collected
approximately a century ago. Since rates of nucleotide
Fig. 1 Map of Sulawesi with biogeographic barriers shown, as well as the approximate distribution of each species plotted within the inlaid maps. Species
distributions estimated from [27, 28]. Individual samples are placed in the same color, and on the representative map of each sampled species. Species not
included are in grey text in the center inlaid map, and P. rosenbergii is distributed on the islands north of the northern peninsula (Sangihe Islands). Base
maps modified from Wikimedia Commons
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 Page 3 of 16
substitution are greater in flanking regions of UCEs and
degradation has an effect on DNA fragment length, this
study provides empirical evidence for the utility of UCEs
in degraded DNA studies. We also report the enrichment
success and the assembled length for the recovered UCEs
to build our phylogenies.
Results
Mitogenomes
Whole mitochondrial genomes were successfully con-
structed from 14 individuals from seven of the 10 recog-
nized species (Table 1). Average mitogenome coverage
was 232.2× and ranged from 46.5 to 880.8× (Table 2).
Evidence of contamination was detected in two Pros-
ciurillus murinus samples (MZB 5973 and 5977), and one
sample of Prosciurillus weberi (MZB 6256) had low cover-
age (16X); these were therefore excluded from phyloge-
nomic analysis. Contamination was deduced based on
damage which occurred during transport of samples (tube
seals were damaged for both samples MZB 5973 and
5977), which was later combined with the recovery of a
large number of herterozygosities within these two speci-
mens. In order to assure that submitted sequences were of
the species intended; these samples were removed from
further analysis. All samples were checked for contamin-
ation by repeating library preparation, replicate sequen-
cing, translation of coding genes, and by evaluating
heterozygous sites in the mitochondrion. Nuclear copies
of mitochondrial sequences have been shown to be an
issue when using historic material as a genetic source [35].
In order to ensure that our sequences represented mito-
chondrial sequences as opposed to nuclear copies, we
followed the standard protocols for high throughput se-
quencing (HTS hereafter) generated mitogenomes and de-
termined the mitochondrial sequence by consensus of
high coverage fragments (as in [36]).
Several mitochondrial genes were found to have near-
saturated third codon positions; therefore, only non-
saturated genes (cytochrome oxidase subunit 1–3, and
ND1-5) coding genes were included in phylogenetic in-
ference. Phylogenetic trees generated from the whole
mitochondrial genome, without including gene or codon
partitioning, were used for comparison to the topology
when data partitions were applied (data not shown,
complete mitogenomes are available on GenBank, acces-
sion numbers presented in Table 1). Both maximum
Table 1 All samples included in this study, with museum catalog #, geographic location, Genbank # (for mitogenomes), whether
mtDNA or UCEs were extracted for each sample, and the number of UCEs enriched
Species Catalog # Location Genbank accession # mtDNA UCEs # Loci
1 Hyosciurus heinrichi MZB 34908 Sulawesi KR911797 x 258
2 Hyosciurus ileile ANMH 225461 Gunung Kanino, Sulawesi KR911796 x x 2608
3 Prosciurillus abstrusus AMNH 101360 Menkoka Mts., Tanke Salokko KR911793 x x 3748
4 Prosciurillus leucomus occidentalis 1 AMNH 196571 Roeroekan, Sulawesi KR911786 x x 3248
5 Prosciurillus leucomus leucomus 2 USNM 200274 Sulawesi, Toli Toli KR911785 x x 1262
6 Prosciurillus leucomus leucomus 3 USNM 216771 Sulawesi, Teteamoel KR911784 x
7 Prosciurillus murinus 1 USNM 217817 Sulawesi, Temboan KR911795 x x 1067
8 Prosciurillus murinus 2 USNM 218713 Sulawesi, Koelawi KR911794 x
9 Prosciurillus weberi 1 MZB 6252 Mosamba, Celebes KR911789 x
10 Prosciurillus weberi 2 MZB 6254 Mohari, Sulawesi KR911787 x
11 Prosciurillus weberi 3 MZB 6255 N. Celebes, Meuado KR911788 x
12 Rubrisciurus rubriventer 1 USNM 218710 Sulawesi, Koelawi KR911791 x x 1359
13 Rubrisciurus rubriventer 2 USNM 218711 Sulawesi, Rano Lindoe KR911790 x
14 Rubrisciurus rubriventer 3 ANMH 101313 Mengkoka Mts., Tanke Salokko, Sulawesi KR911792 x
15 Exilisciurus exilis ROM 102254 East Kalimantan, Indonesia KR911801 x x 3706
16 Callosciurus adamsi NZP95-322 Sabah, Malaysia KR911800 x x 3834
17 Nannosciurus melanotis USNM 123098 Sumatra, Indonesia KT001463 x x 3800
18 Lariscus insignis MVZ192194 Sumatra, Indonesia KR911799 x x 3838
19 Sundasciurus everetti MTRB 3/16 Mount Kinabalu, Sabah, Malaysia KR911798 x x 3863
20 Callosciurus erythraeus KM502568 China KM502568 x
Museum abbreviations: MZB; Museum Zoologicum Bogoriense, Bogor, Java, Indonesia; AMNH; American Museum of Natural History, New York, New York, USA;
USNM; National Museum of Natural History, Smithsonian Institution, Washington D.C, USA; NZP; National Zoological Park, Washington D.C., USA; MTRB; M.Hawkins
Field Samples, see Hawkins et al. [41] for details
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 Page 4 of 16
likelihood (ML) and Bayesian inference (BI) estimates
supported the monophyly of Sulawesi squirrels (Fig. 2;
BS ≥75 and BPP ≥ 0.95). Ingroup nodes were well-
supported (BS >90 and BPP >0.98) and the topology was
consistent with Mercer and Roth [16], indicating that
the genus Hyosciurus was the earliest diverging lineage
of Sulawesi squirrels. Interestingly, Prosciurillus was
found to be paraphyletic, with Prosciurillus murinus fall-
ing out sister to Rubrisciurus + Prosciurillus (Figs. 2 and
3). Divergence dating replicates implemented in BEAST
[37] were found to converge and had high ESS values
(>200). The empty alignment was significantly different
from the mitogenome alignment and recovered poor
ESS values, indicating the priors did not strongly influ-
ence the results. Coalescent modeling recovered a
slightly different topology than the BI and ML analyses,
with Prosciurillus murinus the most divergent species
within the radiation of Sulawesi squirrels, followed by
the Hyosciurus, Rubrisciurus, and finally the remaining
Prosciurillus species (Fig. 3). All Sulawesi squirrels
shared a common ancestor almost 10 MYA (HPDs =
5.89 – 13.75). Intraspecific divergence times varied be-
tween taxa (1.5–2.3 MYA). Interestingly, the two Hyos-
ciurus species were deeply divergent, sharing a common
ancestor ~5.8 MYA (Fig. 3).
UCEs
UCE loci were successfully sequenced (range 1035 to
3748; Table 1) for all but one Sulawesi species (258 re-
covered UCE loci, Hyosciurus heinrichi MZB 34908);
therefore, this sample was excluded from subsequent
analyses. Outgroup specimens from high quality tissues
samples yielded more loci (3706 to 3863 loci; Table 1)
than degraded DNA samples. Twenty-eight loci were
successfully characterized in all taxa (total length
8824 bps). The incomplete matrix contained 4046 loci
(1,743,442 bps), in which 2646 loci contained at least
one parsimony informative site per locus. The average
length of loci in the full dataset was 434 bps, ranging
from 150 (minimum length acceptable) to 2863 bps.
This dataset was reduced to include only loci with at
least three informative sites (1137 loci) and then for
alignments that contained at least 9 of the 11 included
taxa (362 loci). This partition of the dataset averaged
435 bps, and ranged from 192–918 bps. This resulted in
a concatenated alignment of 157,353 bps. In order to see
if the length and compositions of various loci had an ef-
fect on topology, an incomplete matrix containing UCEs
with at least 8 of 11 taxa was generated, consisting of
2410 loci (956,549 bps long). To mirror the complete
dataset of 28 loci, another subset of the 28 ‘most
Table 2 Results of mitochondrial genome enrichment for Sulawesi samples (modern outgroup samples were generated from Long
Range PCR), read merging (PEAR), and read mapping (with BWA); average coverage of mitogenome also detailed
Catalog # Species Location # merged
reads
# reads mapped
w/Sulawesi reference
Average
coverage
1 MZB 34908 Hyosciurus heinrichi Sulawesi 745249 80370 775.8
2 ANMH
225461
Hyosciurus ileile Gunung Kanino, Sulawesi 428430 76952 367.4
3 AMNH
101360
Prosciurillus abstrusus Menkoka Mts., Tanke Salokko 147485 35982 152.7
4 AMNH
196571
Prosciurillus leucomus
occidentalis 1
Roeroekan, Sulawesi 348234 69856 513.3
5 USNM
216771
Prosciurillus leucomus leucomus 3 Sulawesi, Teteamoel 140615 35892 111.5
6 USNM
200274
Prosciurillus leucomus leucomus 2 Sulawesi, Toli Toli 123089 21723 64.9
7 USNM
218713
Prosciurillus murinus 2 Sulawesi, Koelawi 145631 36348 105.6
8 USNM
217817
Prosciurillus murinus 1 Sulawesi, Temboan 113550 25655 75.3
9 MZB 6254 Prosciurillus weberi 2 Mohari, Sulawesi 9706968 27230 174.7
10 MZB 6255 Prosciurillus weberi 3 N. Celebes, Meuado 2296646 166994 1082.6
11 MZB 6252 Prosciurillus weberi 1 Mosamba, Celebes 177965 9705 59.9
12 ANMH
101313
Rubrisciurus rubriventer 3 Mengkoka Mts., Tanke Salokko,
Sulawesi
106941 12385 66.4
13 USNM
218711
Rubrisciurus rubriventer 2 Sulawesi, Rano Lindoe 70224 24618 178.1
14 USNM
218710
Rubrisciurus rubriventer 1 Sulawesi, Koelawi 25633 19029 84.2
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 Page 5 of 16
informative’ loci was constructed, which contained the
28 loci with the highest number of parsimony inform-
ative sites (13,578 bps in length). A comparison of the
complete dataset with the ‘most informative’ loci recov-
ered overall mean genetic distance of 0.005 % in the
complete dataset, and from 0.030 % in the ‘most inform-
ative’ dataset (Additional file 1: Table S1).
Prosciurillus murinus (USNM 217817) had the fewest
number of enriched UCE loci within Prosciurillus (1067),
with data missing for a large percentage of loci in the in-
complete dataset analyses. The placement of Prosciurillus
abstrusus varied depending on the amount of information
per included locus. To provide better resolution for the
placement of these two species, and to reduce the effects
of missing data on topology and branch lengths, another
analysis was done including 34 loci (12,860 bps) in which
P. murinus and P. abstrusus were always included. In
order to evaluate these various data partitions, PHyML
[38] runs were performed (all with HKY substitution
models) on each of the above data partitions, as well as a
species tree inference via ASTRAL [39] (Fig. 4) and NJst
[40] (Additional file 2: Figure S1).
The topological relationships for ingroup taxa remained
the same regardless of how the data were parsed. Length,
number of informative sites, and number of differences per
UCE locus were plotted to visualize the effects of reducing
the dataset (Additional file 3: Figure S2). Relationships be-
tween outgroup taxa varied, but in five of the six trees
(from Fig. 4a-f) the genus Sundasciurus (represented by S.
everetti [41]) was recovered as the sister lineage to the radi-
ation of Sulawesi squirrels. Similar to the mitochondrial re-
sults, within the Sulawesi radiation Hyosciurus was the
earliest diverging lineage with Rubrisciurus and Prosciuril-
lus recovered as sister genera. Within Prosciurillus, P. mur-
inus was the most divergent lineage. Branch lengths were
variable, especially for Prosciurillus leucomus 2 (USNM
200274), which was due to missing data.
Both the concatenated (using PHyML [38] and MrBayes
[42]) and the species tree inference methods (using AS-
TRAL [39] and NJst [40]), which consider the loci inde-
pendently, yielded the same topology (ASTRAL, Fig. 4f;
NJst, Additional file 2: Figure S1). The 362 loci dataset
was dated with various partitioning schemes and substitu-
tion models. Each of the four replicates for the BEAST
analysis converged and had robust ESS values (>200). Esti-
mated divergence times were relatively consistent across
datasets, with an estimated most recent common ancestor
at 12.5 MYA for the 362 loci analysis (HKY substitution
model), and 12.7 MYA (HKY+G), and 12.6 MYA for the
partitioned analysis (Fig. 5, Table 3).
Fig. 2 Whole mitochondrial genome phylogenetic tree. Support values are provided for both Maximum Likelihood and Bayesian Inference (ML/BI). Colors
correspond to range maps in Fig. 1. Species with multiple individuals are detailed in Table 1
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 Page 6 of 16
Discussion
UCE characterization in mammals
As the number of reported cases of incongruence be-
tween gene trees and species trees increases, it is im-
perative to consider species level phylogenetic analyses
based on evidence from multiple, independently inher-
ited markers [43]. In early reports of incongruence it
was unclear which of the small number of gene trees
best reflected the species tree [43, 44]. However, now
that a large number of independent nuclear loci can be
analyzed, highly accurate species trees can be con-
structed and the vagaries of lineage sorting in individual
genes ceases to be an issue [45]. UCEs are a large panel
of nuclear markers developed across vertebrates that can
be used to overcome the limitations imposed by small
numbers of genes and have been shown to be useful in
reconstructing species trees at various evolutionary
scales [32, 34, 46, 47]. Here we used the same loci to
demonstrate their power for resolving intergeneric rela-
tionships among Sulawesi squirrels. Our data suggest
that these loci may be useful in a wide variety of animals
at a similar evolutionary scale (i.e., diversification within
and between mammalian genera) [33, 34, 48].
In this study, a large portion of our results was gener-
ated from degraded DNA extracted from museum speci-
mens. Amplifying the entire mitochondrial genome and
minimally 1000 nuclear loci in small overlapping frag-
ments followed by Sanger sequencing would have been
technically challenging and cost prohibitive. We have
demonstrated the effectiveness of enrichment protocols,
such as for the UCEs and mitogenomes, in degraded
samples. Our lower quality museum samples enriched
fewer loci than the high quality frozen tissue samples,
but despite this, over 1000 UCE loci per sample (with an
average length of 432 bp per locus) were recovered in all
but one case. We observed high variability in the num-
ber of recovered UCE loci from the museum specimens,
from 286 (Hyosciurus heinrichi) loci to 3800 (Nannos-
ciurus melanotis), with an average of 810 loci per mu-
seum specimen (which is significantly lowered due to
the low number of loci captured in Hyosciurus heinrichi;
the average without this sample was 2939 loci).
Since most UCE loci represent DNA fragments of un-
known function, here we implemented the k-means al-
gorithm shown to produce better partitioning schemes
than traditional methods (e.g. by locus, codon position,
Fig. 3 Divergence dated whole mitochondrial genome phylogeny. Bayesian inference support values are shown and dates are provided in
millions of years. Blue bars indicate the 95 % HPD for each dated node. The split from Sundaland to Sulawesi taxa is the node dated to
11.03 MYA
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 Page 7 of 16
etc.) [49]. Robust phylogenies were generated from both
coalescent and non-coalescent approaches, yet individual
loci recovered a variety of topologies, dependent on the
included taxa, number of informative sites per locus,
amount of missing data and of course, lineage sorting.
Evolutionary history of the Sulawesi squirrels
Sulawesi was never connected by land to Borneo, so an
overwater ‘sweepstakes’ crossing is the most likely mech-
anism by which squirrels arrived on Sulawesi. Our esti-
mated time of divergence between Sulawesi and
Sundaland squirrels ranged from ~9.7–12.5 MYA on aver-
age including both the mitogenome and UCE datasets re-
spectively, compared to divergence estimates of 10.5–11.4
MYA reported by Mercer and Roth [16]. All of our diver-
gence time estimates from UCEs (using a strict molecular
clock) resulted in 95 % HPD outside of, and older than
the estimates from Mercer and Roth [16] (~12.5 MYA
average, 11.65–15.2 MYA 95 % HPD from the UCE data-
set), whereas our mitogenome dataset yielded a younger
estimate of 9.71 MYA (95 % HPD: 5.89–13.76 MYA). The
difference is likely due to the use of a relaxed molecular
clock with the mitogenome dataset. Our results suggest
that squirrels colonized Sulawesi during the Miocene,
likely to west Sulawesi, which was located further south
and west of its present location. The east and central pen-
insulas may have been partially connected at this time, but
the other peninsulas were not [6, 50]. Based on the ob-
served topology and monophyly, our results also support
a single colonization event, as proposed by Mercer and
Roth [16].
The deep divergence times between the three gen-
era predate the modern configuration of Sulawesi by
several million years. The three extant Sulawesi gen-
era diverged from the outgroup taxa about ~9.7–12.5
MYA—a divergence that may potentially be linked to
sea level changes during this timeframe [5, 16, 51].
Low sea level may have facilitated a scenario of initial
rafting to Sulawesi, followed by allopatric diversifica-
tion with squirrel lineages diversifying on different
islands/areas that subsequently came together to form
Sulawesi.
A) B)
C)
E) F)
D)
Fig. 4 Comparative analysis of UCEs, with several trees provided based on various partitioning schemes. All trees were generated with Maximum
Likelihood via PHyML except F. a the complete matrix of 28 loci, (b) a tree of the 28 ‘most informative’ loci, including loci with the highest number of
informative sites per locus. c a tree of 34 loci where Prosciurillus murinus and P. abstrusus were always present, (d) the tree containing 362 loci, which
included at least 9 of the 11 taxa, and at least three informative sites per locus. e A tree of 2410 loci containing at least 9 of 11 taxa and at least a
single informative site per locus. f ASTRAL species tree estimation, generated from the 362 loci dataset. Additional details about partitioning are found
in the Methods
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 Page 8 of 16
A few million years after the original crossing to Sulawesi,
mountain uplift created the first highlands in the region [8],
and potentially allowed for additional niche specialization
in Sulawesi squirrel species. Hall [8] suggests the inclusion
of biological and molecular evidence to deduce the precise
timing of evolution in Sulawesi, as the geologic record is in-
complete. The endemic squirrels represent a group of com-
pletely terrestrial, forest-dependent mammals, which are
known as poor over-water dispersers. We propose that the
divergence dates observed in endemic squirrels are likely
closely tied to the geologic events − as originally
described by Merecer and Roth [16] − because several
species are restricted to specialized habitats (including
montane, mangrove, and peninsula restricted species).
Specifically, our divergence estimates based on
mtDNA for Hyosciurus heinrichi and H. ileile are dated
at approximately 5.76 MYA, coinciding approximately
with the timing of uplift in the central core of Sulawesi.
Within Prosciurillus, P. abstrusus (a montane endemic)
was dated as splitting from other Prosciurillus species
between 5.09 and 5.14 MYA (mitogenomes and UCEs
respectively), which is also likely tied to the uplifting
Fig. 5 Divergence dated UCE dataset with two independent analyses (see methods) shaded (95 % CI) in different colors (although almost entirely
overlapping). The inlaid maps are geological reconstructions from [8], reprinted with permission, highlighting the approximate conformation and
extent of subaerial land at 10 and 5 MYA. The green indicates land, yellow indicates highland habitat, red triangles represent volcanoes, and the
shades of blue represent shallow-deep sea (light–dark blue)
Table 3 Comparison of BEAST divergence date estimates between both the mitogenome and UCE datasets. Several analyses of the
UCE dataset are shown. Various dates from UCE partitions are shown, with the associated columns shaded in grey. The split
between extant Bornean and Sulawesi taxa is in bold (Split 3)
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 Page 9 of 16
and/or isolation of this species in the mountains of the
south peninsula [8]. Prosciurillus leucomus was esti-
mated to have diverged between 2.3 and 4.6 MYA (mito-
genomes and UCEs respectively), which is likely near the
time when the northern peninsula connected to the cen-
tral core of Sulawesi [8]. Finally, Prosciurillus weberi, a
species currently restricted to mangrove forests in the
southernmost extent of the central core of Sulawesi, was
estimated to have diverged 3.79 MYA, with over two
million years of history within the species, and may pro-
vide an indication of the formation or expansion of man-
groves in Sulawesi around this time.
We note that our dating estimates should be taken
with caution because they were recovered from fossil
calibration points far outside of the Sulawesi taxa, and
we did not use geological data to constrain divergence
dates. By combining the known geological record with
carefully dated phylogenetic trees, we can begin to reveal
finer scale patterns of speciation and movement across
this biodiversity hotspot. The inclusion of additional spe-
cies and large datasets can provide an independent
source of information regarding the estimated conver-
gence of all land fragments in Sulawesi, and provide fur-
ther evidence for a better resolution of the evolutionary
history of this endemic radiation within Sulawesi.
Discordance between mitochondrial and nuclear datasets
The well-supported monophyletic groups resulting from
the species tree analysis are consistent with previous
generic level designations based on morphology. Dis-
cordance between mitochondrial and nuclear datasets
has been well-documented in animals [52]. Since mito-
chondrial DNA is inherited as a single unit, it reflects
only the genealogical history of a single locus and hence
phylogenies derived from mtDNA result in gene trees,
which may or may not be congruent with the species
tree. However, examination of this marker (when com-
pared with multiple unlinked loci) can provide insight
into evolutionary processes (e.g. introgression, selection,
drift) that have influenced phylogenetic patterns.
Considering the estimated age of this group, the para-
phyletic relationships in Prosciurillus observed in the
mitochondrial dataset are likely the result of an ancient
mitochondrial introgression event. Mitochondrial intro-
gression has been reported in a variety of animals and
occurs more frequently in mtDNA compared to nDNA
(see Ballard and Whitlock [53] and citations within).
Mitochondrial introgression into the Prosciurillus muri-
nus lineage is best explained by ancient introgression
when a population of ancestral P. murinus expanded its
range into the range of another lineage not sampled
here. Some of the oldest events of ancient introgression
of mtDNA have been reported in squirrels [54–56].
Simulations suggest that introgression almost exclusively
occurs in the direction from the native to the invading
species [52], as also empirically illustrated by some late
Quaternary expansions [57, 58]. That implies that when
a proto- Prosciurillus murinus lineage colonized a new
island/region up to 7 MYA (which corresponds to the
most recent age estimate based on UCE’s of P. murinus
from other Sulawesi species, after splitting from other
species), it encountered and reproduced with squirrels
already present there. The other lineage of squirrels was
not sampled in this study, possibly because it went ex-
tinct after the arrival of Prosciurillus, but their mito-
chondrial lineage became fixed in the expanding species.
The review of mito-nuclear discordance presented by
Toews and Brelsford [44] found that 97 % of surveyed
studies detailed situations where isolation had occurred,
followed by secondary contact leading to the introgres-
sion events, which may be the most likely scenario for
the patterns observed in Prosciurillus.
Relatively short internodes in the deeper parts of the
phylogeny can be problematic for species tree construc-
tion (i.e. between Hyosciurus, Prosciurillus and Rubris-
ciurus). Studies of adaptive radiations that occurred over
short evolutionary time scales (e.g. African cichlid fishes)
have reported difficulty in resolving nodes deep at the base
of the radiation [59]. As demonstrated here and elsewhere,
large genomic datasets provide enough power to resolve
these difficult nodes. However; these results need to
be taken with caution as large datasets can also potentially
inflate support values when gene sequences are
concatenated, leading to higher confidence in incorrect
phylogenetic trees [45, 60–63]. The initial rapid diversifi-
cation rates (combined with short branches between line-
ages) of adaptive radiations likely make the deep nodes
very difficult to resolve, and by increasing data with HTS,
branch support could be misleading [63, 64]. In this sys-
tem, the different topologies observed between coalescent
and non-coalescent analyses of our mitogenome dataset
(placement of Rubrisciurus and Hyosciurus with respect to
P. murinus) may be linked to the short internodes be-
tween genera with fewer informative sites to properly
place these lineages or violations of model assumptions.
Our results provide further justification for using many
unlinked loci for resolving phylogenies. In this study, the
results based on mitochondrial data alone would have
questioned the monophyly of the genus Prosciurillus.
While contamination is a major concern when working
with degraded DNA from historical specimens [65–67],
the observed discordance between mitochondrial and nu-
clear datasets in this study is clearly due to evolutionary
processes rather than to problems with contamination. If
the result were due to contamination, we would expect to
see issues with both the mitochondrial and nuclear datasets
because DNA samples for both marker analyses were
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 Page 10 of 16
conducted on the same extraction aliquots. Second, we
replicated library preparation and in-solution hybridization
protocols, which resulted in confirmation of the results
presented here. We also followed steps to identify and en-
sure removal of nuclear copies of mitochondrial DNA in
our samples [35, 68]. Finally, cross-contamination would
have resulted in heterozygosities in the mitochondrial data-
set, and either admixed placement of the samples in the
UCE analyses, or poor support for these nodes. The only
cases where we detected evidence of contamination in-
volved samples from two museum specimens from tubes
that were damaged during transport. These samples were
excluded from all analyses.
Conservation implications
The data presented here unveil deep divergences within
species, from 1.28 million years within Rubrisciurus
rubriventer, to 2.33 million years between subspecies of
Prosciurillus leucomus. Even the mangrove-restricted
species Prosciurillus weberi showed over 2 million years
of divergence between individuals, indicating significant
genetic diversity in a limited geographic range. These re-
sults highlight the evolutionary distinctiveness of the iso-
lated populations of squirrels found in this highly
threatened landscape. More exhaustive sampling across
the range of individual species could reveal additional
ancient lineages, and perhaps allow us to determine the
level of divergence within and between all species.
Evans et al. [69] suggested conservation priorities for
seven areas across Sulawesi for which macaques and
toads had similar species distributions. The squirrels are
not tightly correlated to the same seven regions, and
seem more habitat specific (with mangrove and montane
specialists), which may, for example, instead explain the
similarity to patterns revealed in species of viviparous
freshwater snails [50]. An ecosystem approach might be
a better method of determining conservation priorities
to encompass the differences observed in faunal distri-
bution across Sulawesi, but more research, ideally in-
volving well-sampled phylogenies across a much wider
diversity of Sulawesi biodiversity, is needed to address
this question and ultimately to provide the best-
informed conservation plan and practices.
Conclusion
The additional taxonomic sampling of Sulawesi squirrels
and outgroup taxa from Sundaland obtained from museum
specimens coupled with sequence capture of a large num-
ber of unlinked UCE loci and mitogenomes resulted in a
well-resolved phylogeny that dates the divergence of
endemic Sulawesi squirrels from their closest relatives
to ~9.7–12.5 MYA. Our results confirm the monophyly of
Sulawesi squirrels with deep divergences between the
three endemic genera and support a single colonization
event that likely occurred during the Miocene and repre-
sents an old adaptive radiation that predates the amalgam-
ation of the current island of Sulawesi. The incorporation
of novel HTS technologies and newer geological models
are leading to new biogeographic insights and further un-
derstanding of the evolutionary processes driving adaptive
radiations in this region. These biogeographic insights and
the patterns of faunal exchange in and out of Sulawesi
make this island an extremely interesting place for future
research. Also, we found incongruent evolutionary rela-
tionships derived from mitochondrial and nuclear markers
which we hypothesize are due to an ancient introgression
event. Future research that incorporates dense taxon sam-
pling and all nominal species is needed to completely
understand the evolutionary history and allow us to test
more fine-scale hypotheses concerning dispersal and di-
versification within this unique group of squirrels. Finally,
as deforestation has reached unprecedented rates in this
region, it will be important to implement an ecosystem
approach to better determine conservation priorities that
encompass the differences observed in faunal distribution
across Sulawesi. Future research with well-sampled and
well-resolved phylogenies from a large set of representa-
tive taxa from Sulawesi is needed to address this question
and ultimately to provide the best-informed conservation
plan and practices.
Methods
Samples
A total of 17 ingroup samples from the three target gen-
era and 5 outgroup taxa were included in this study. All
ingroup samples were derived from degraded museum
specimens, obtained from bone fragments, skin clips, or
adherent osteological material from specimen skulls
(Table 1). Sampling of specimens followed strict proto-
cols including changing gloves between each sample, as
well as bleaching all work surfaces and utensils prior to
each use. Three species of Prosciurillus were not in-
cluded in this study (Prosciurillus alstoni, P. topapuensis,
and P. rosenbergii) because it was not possible to obtain
samples. All outgroup taxa were high quality tissue sam-
ples (except Nannosciurus melanotis, which was also
from a degraded museum specimen, and was included
to represent an additional extant Bornean genus).
Specimens were collected following ethical guidelines,
detailed in [41], and approved from institutional animal
care and use committees (Smithsonian Institution, Na-
tional Museum of Natural History, Proposal Number
2012–04, and Estación Biológica de Doñana Proposal
Number CGL2010-21524). Research permits from Sabah
Parks were approved under permit number TS/PTD/5/4
Jld. 47 (25), and exported with permissions from the
Sabah Biodiversity Council (Ref: TK/PP:8/8Jld.2). DNA
extractions of museum specimens were performed by
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 Page 11 of 16
phenol/chloroform isolation in a specifically dedicated
laboratory (for low quality ancient DNA) that is physic-
ally separated from the main laboratory. To monitor for
contamination, negative extractions were included in
every batch of extractions, library preparation was repli-
cated, and sequencing was performed in multiple labora-
tories. Samples were subsequently concentrated via
centrifugation [70]. Tissue samples for the outgroups were
extracted with Qiagen DNeasy Blood and Tissue Kits
(Valencia, CA) and eluted in 200 μl of Qiagen elution buf-
fer. All samples were subsequently stored at −20 °C.
Library preparation
Several library preparation methods were used, including
a modification of Roche 454 library preparation for Illu-
mina sequencing, which is detailed in the supplemental
materials. Commercial kits were used for both museum
and tissue samples, as detailed in [71]. After successful
library preparation, amplification of indexed libraries
was performed with a high fidelity Taq (either Phusion
HF Taq or Kapa HF Taq) for 18 cycles on museum spec-
imens, and 14 cycles on modern tissue samples.
Mitochondrial genome generation
Museum samples
Due to the degraded nature of the samples and variation
in copy number of mtDNA versus nDNA, separate en-
richments were performed for each type of DNA and
museum versus frozen tissue samples. For mitogenomes
generated from museum specimens, two to four samples
were multiplexed and enriched following the protocol
described in [71, 72].
Tissue samples
As the frozen tissue samples were high molecular weight
samples, enrichment of mitogenomes was not required,
and instead long-range PCR (LR PCR) amplified the en-
tire mitogenome in two fragments with universal primers
[73, 74]. Takara LA Taq (Clonetech) was used for LR PCR,
and amplified for 35 cycles with a 68 °C anneal. PCR prod-
ucts were then sonicated to randomly shear the PCR prod-
ucts. A QSonica Q800RS was used for sonication using
25 % amplitude with an on/off pulse for 5 min. Products
were subsequently visualized on an agarose gel to evaluate
the resulting fragment size. After magnetic bead purifica-
tion (MagNA) following Rohland and Reich [75], Kapa li-
brary preparation kits were used for library preparation of
approximately 500 ng of template DNA.
Ultraconserved elements
Museum and tissue samples were enriched for UCEs in
multiplexed pools of eight samples (combined with sam-
ples from other unrelated projects). Reduced subsets of in-
dividuals were enriched for UCEs due to the cost to enrich
and sequence these samples. No museum samples were
multiplexed with modern tissue samples to prevent biased
enrichment of the samples. Reduced sets of specimens
were enriched for UCEs due to the anticipated allelic drop-
out with museum samples and deeper sequencing require-
ments. The UCE enrichments were performed with DNA
based probes using the NimbleGen SeqCap EZ (Roche) kit.
The probe set contained approximately 4000 UCE loci de-
signed for tetrapods [46]. After enrichment, amplification
was performed (following the manufacturer’s protocol).
Enrichments were visualized after MagNA purification on
both an agarose gel and on the Bioanalyzer (Agilent, High
Sensitivity Kit). Problems with removal of adapter dimer
were common with the museum samples, as the target
DNA and the adapter dimer were fairly close in size; so
complete removal of adapter dimer was rarely possible. To
compensate for this, enrichments with dimer were se-
quenced at higher coverage.
Quantification and sequencing
Following visualization of the enrichments, quantitative
PCR (qPCR) was performed using SYBR green florescence
(Kapa Biosystems Illumina Library Quantification Kit).
Equimolar pooling of samples was based on the values
generated from qPCR. Illumina sequencing was done on
either the Illumina MiSeq or HiSeq 2000 with either 2 ×
250 bp or 2 × 150 bp paired end sequencing, respectively.
Since the coverage requirements were substantially differ-
ent for the mitogenomes versus the UCEs, the two types
of enrichments were sequenced on separate runs. Sequen-
cing was performed at the Semel Institute of Neurosciences
(UCLA), National High-throughput DNA Sequencing
Centre (University of Copenhagen, Denmark), and the Cen-
ter for Conservation and Evolutionary Genetics (Smithson-
ian Institution, National Zoological Park).
Data analysis
Raw fastq files were generated from sequencing cores
for both mitogenomes and UCEs. The processing of the
two molecule types (mtDNA versus nDNA) was done
separately. For the mitogenome analysis, an average of
1,041,190 merged reads were recovered for each sample,
with individuals ranging from 25,633 to 9,706,968 per
individual (see Table 2). The samples screened for UCEs
recovered an average of 3,571,092 paired end reads, ran-
ging from 771,645 to 9,891,988 (see Additional file 4:
Table S2).
Mitogenome analysis
Both museum and tissue samples were analyzed with the
same pipeline, with the modern samples skipping read
merging. Paired-end reads for each museum sample were
merged together using the program PEAR v.0.9.4 [76] to
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 Page 12 of 16
allow for better downstream read mapping. Residual
adapter fragments were removed with the program Cuta-
dapt v1.4.2 [77]. Reads with a mean quality score below 20
and exact PCR duplicates (three or more identical mole-
cules) from the 5′ direction were removed with Prinseq
v.0.20.4 [78]. The high quality reads were then mapped to
a reference sequence. There are no previously published
mitogenome sequences for any of the endemic Sulawesi
squirrels, so a consensus of three Sundaland squirrels was
used as a reference: Callosciurus erythraeus (Accession #
NC_025550.1), Sundasciurus everetti (Accession #
KR911798; [41]), and Lariscus insignis (generated here,
Accession # KR911799). This reference is referred to in
Table 2 as 'Sulawesi Reference'. The cleaned reads were
mapped to the consensus sequence with bwa v.0.7.10,
using the ‘bwa mem’ command [79]. The resulting SAM file
was imported to Geneious v.7.1.7, visually inspected,
aligned to other mitogenomes, and subsequently annotated.
UCE analysis
A total of 12 samples were included in the UCE analysis.
These contained eight endemic Sulawesi taxa and five
outgroup taxa. The complete bioinformatic analysis of
the UCE dataset followed the published pipeline phyluce
[48], available at http://phyluce.readthedocs.org/en/lat-
est/. The phyluce pipeline has options for generation
and analysis of both complete and incomplete UCE
matrices, and both were generated here. In order to de-
termine which loci informed phylogenetic relationships,
a script from the phyluce pipeline was run to determine
the number of informative loci from both the complete
and incomplete dataset. A number of comparisons were
made between the complete, and subsets of the incom-
plete, matrix. In addition to the standard phyluce pipe-
line, MARE [80] was used to test for biases in matrix
reduction, and FASconCat-G [81] was used to concaten-
ate the loci for phylogenetic analysis, where appropriate.
Phylogenetic analysis
Mitogenomes
MEGA v.5.2.2 was used to test for the molecular clock on
both the ingroup, and the entire dataset including out-
groups, for which a strict clock was rejected in both in-
stances [82]. In order to determine the amount of
saturation, all protein coding genes were extracted from the
mitogenomes, and transversions were plotted against tran-
sitions between codon positions 1,2 versus 3. PartitionFin-
der was used to determine the codon partitioning and
substitution model for each mitochondrial gene [83].
Phylogenetic trees were generated with both maximum
likelihood (ML) and Bayesian inference (BI) approaches.
PhyML [38] was run with the Geneious v.7.1.7 plugin for
the ML tree; 100 bootstrap replicates were run with the
non-partitioned concatenated dataset. The substitution
model used was HKY and the topology was optimized for
tree topology, branch lengths, and substitution rates.
MrBayes v3.2.3 [42] was used to generate the BI tree, and
three independent runs were completed for 2 million
chains, with a subsample frequency of 1000, and four
heated chains at a temperature of 0.2. Independent runs
were evaluated for convergence. Unconstrained branch
lengths were allowed, and the first 100,000 trees were dis-
carded as burnin. The average standard deviation of split
frequencies (ASDSF) was evaluated to determine the con-
vergence between runs. The non-saturated mitochondrial
genes (CO1-3, ND1-5) were included in a divergence dat-
ing analysis using BEAST v.1.8.1. [37] PartitionFinder [83]
was used to determine the codon partitioning and substi-
tution model for each non-saturated gene. A lognormal
(uncorrelated) relaxed clock was used under a Yule speci-
ation tree, with operator left to default. A single fossil cali-
bration was used for the Callosciurus + Sundasciurus +
Nannosciurus + Lariscus + Exilisciurus clade of squirrels,
which here included only the outgroup sequences (Sun-
dasciurus everetti, Callosciurus adamsi, Nannosciurus
melanotis, Lariscus insignis, and Exilisciurus exilis) based
on first observance of Callosciurus as well as fossils of
Dremomys and Tamiops [84]. The specific range for the
Callosciurus fossil (focused on here as there is evidence
for earlier Dremomys and Tamiops, which are not in-
cluded in this dataset) is from 14.3–13.2 MYA, which was
recovered from the lower part of the Chinji formation
(Lawrence Flynn, pers. comm.). Older fossils representing
Dremomys and Tamiops are available at this same site, and
an ancestor to Tamiops has been recovered from around
20 MYA [84]. Due to the paucity of the fossil record,
obtaining the best fossils for divergence dating can be dif-
ficult, and sometimes requires incorporation of fossils and
inferred dates in combination, as done in [41]. A lognor-
mal distribution was centered at 14.0 MYA and the 5 and
95 % quantiles were 13.19 and 18.18 MYA respectively.
We allowed for additional depth past the 14.3 MYA to ac-
count for some degree of discrepancies in the fossil rec-
ord, and to coincide with the topology and date ranges
found in the two previous sciurid phylogenies, particularly
to incorporate the placement of Exilisciurus [16, 85]. Four
independent runs were performed to assess run conver-
gence using Tracer v.1.5 and TreeAnnotator was used to
combine individual runs [86].
UCEs
In order to determine the number of effective partitions, we
ran the program PartitionFinder [83] on the Smithsonian
Institution High Performance Cluster (SI/HPC). MEGA
v.5.2.2 was used to test for the molecular clock, for which a
strict clock could not be rejected [82]. Both Maximum
Likelihood (ML) and Bayesian Inference (BI) trees were
produced. PhyML [38] was run with the Geneious v.7.1.7
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 Page 13 of 16
plugin, and MrBayes v. 3.2.3 [42] was run on XSEDE
via the Cipres Science Gateway [87]. The BI analysis
was run three times with 10,000,000 generations
along four chains with two replicates at a temperature
of 0.05. The ASDSF was evaluated to determine the
convergence between runs. Sample frequency was set
to 100 with a burnin of 10,000. Tree topologies were
visualized with FigTree v.1.4 [88].
Species tree inference
In order to evaluate the effects of different species tree
methods, we ran the 362 UCE loci dataset with AS-
TRAL4.7.7 [39] and NJst [40] on the STRAW webserver
[89]. ASTRAL employs a statistical binning approach to
generate consensus trees for multiple genes, then com-
bining them for a species tree [39]. NJst uses a distance
method for inferring species trees from unrooted gene
trees by neighbor-joining methods built from a distance
matrix [40].
Divergence dating
BEAST v.1.8.1 [37] was used to estimate the age of the
endemic Sulawesi squirrels. The 362 UCE loci dataset
was concatenated and run using a strict molecular clock
with BEAST. One replicate was not partitioned, and in-
cluded a substitution model of HKY. A second analysis
incorporated HKY +G for the single partition. The k-
means partitioning algorithm was used for the dataset
containing the 362 UCE loci [49] and implemented
through PartitionFinder [83]. This algorithm considers
nucleotides separately, and not from locus information.
Partitions as found from PartitionFinder were extracted
with RAxML (using the –f s and –q options) [90]. The
Yule process of speciation was used, and all operators
were left to default. The same fossil calibration prior was
used as described above. Four independent runs of
BEAST were performed for each partitioning scheme
and substitution model to assess for convergence be-
tween runs, which was done with Tracer v.1.5 [86]. Fi-
nally, an empty alignment was run to evaluate the effect
of the priors on the data, which was also evaluated with
Tracer v.1.5 [86].
Ethics
All research involving animals followed institutional
approval, and conformed to ethical guidelines (Smith-
sonian Institution, National Museum of Natural His-
tory, Proposal Number 2012–04, and Estación
Biológica de Doñana Proposal Number CGL2010-
21524). Research permits from Sabah Parks was ap-
proved under permit number TS/PTD/5/4 Jld. 47
(25), and exported with permissions from the Sabah
Biodiversity Council (Ref: TK/PP:8/8Jld.2).
Consent to publish
Not applicable.
Availability of supporting data
All complete mitogenome sequences have been submit-
ted to Genbank via the following accession numbers:
KR911784-KR911801, KT001463.
The raw reads used to assemble UCEs have been
uploaded to NCBI’s SRA under the Bioproject: PRJNA
284011 and Biosamples: SAMN03658740, SAMN036583
03, SAMN03658302, SAMN03658301, SAMN03658299,
SAMN03658298, SAMN03658472, SAMN03658475, SA
MN03658474, SAMN03658471, SAMN03658451. The raw
reads were subjected to the phyluce pipeline available at:
www.ultraconserved.org. All tree files have been placed on
Dryad at http://dx.doi.org/10.5061/dryad.7v5p3.
Additional files
Additional file 1: Table S1. Overall mean genetic distance across the
28 UCE loci in the complete dataset, as well as the 28 ‘most informative’
loci. The complete dataset is the first two columns, with the loci name,
and overall mean distance (OMD) in the second column. The third and
fourth columns are the ‘28 most informative’ loci. All calculations of
overall mean distance were performed in MEGA v6.0 under default
settings. (PDF 46 kb)
Additional file 2: Figure S1. A species tree generated from NJst, which
recovered the same topology as ASTRAL as well as the concatenated
phylogenetic trees. (PDF 605 kb)
Additional file 3: Figure S2. Graphs showing information from two
subsets of the incomplete matrix of UCE loci. The left column contains all
loci enriched (4046 total) and the right column shows all loci which
contain at least three informative sites (1137 loci). The top graph shows
the overall length distribution across all loci for both subsets, the middle
shows the number of informative sites, and the bottom shows the total
number of differences across the loci. Note the two show very similar
patterns, which was justification to use a smaller, yet equally informative
subset of all loci. (PDF 194 kb)
Additional file 4: Table S2. Number of reads for each individual enriched
for UCEs, and total number of recovered loci. (XLSX 48 kb)
Abbreviations
HTS: high throughput sequencing; Mitogenome: mitochondrial genome;
UCEs: ultraconserved elements; MYA: millions of years ago; ML: maximum
likelihood; BI: Bayesian inference.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
MTRH and MMM performed the experiments. MTRH analyzed the data, and
wrote the manuscript. JAL, JEM, KMH, and MTRH conceived of the
experimental design. MTRH, JAL, KMH, JEM, MMM, and LLR revised the
manuscript. All authors have read, and approved of the final version of the
manuscript.
Acknowledgements
This project would not have been possible without the support of many.
This includes Nancy Rotzel McInerney, Robert Fleischer and the Smithsonian
Conservation Biology Institute’s Center for Conservation and Evolutionary
Genetics. Travis Glenn and Brant Faircloth provided training and guidance for
the UCEs. Klaus-Peter Koepfli provided guidance in species tree and divergence
dating analyses. Paul Frandsen performed the partitioning analysis on the UCE
Hawkins et al. BMC Evolutionary Biology  (2016) 16:80 Page 14 of 16
dataset. Anna Cornellas assisted with various aspects of library preparation.
Anang Achmadi, Jake Esselstyn, and Kevin Rowe provided several critical samples
from Sulawesi. Lawrence Flynn provided expertise and guidance regarding fossil
calibrations. Funding for this project came from the Smithsonian Institution’s
Grand Challenges Award Program (JEM, KMH), the Smithsonian Institution’s Small
Grants Program (KMH, JEM and MTRH), the American Society of Mammalogists
Grants-in-Aid, and travel award (MTRH, JEM, KMH), the Spanish Research Council
(JAL, JEM) and the Department of Biology (George Mason University, to MTRH
and LLR). Museum specimens were sampled from a variety of collections,
including the National Museum of Natural History, Smithsonian Institution,
Washington, DC (R. Thorington, D. Lunde, E. Langan, N. Edmison, S. Peurach, and
L. Gordon), American Museum of Natural History, New York (R. Voss, and E.
Westwig), and Museum Zoologicum Bogoriense, Research Center for Biology,
Indonesia Institute of Sciences, Cibinong, Indonesia (A. Achmadi). Logistical
support was provided by the Laboratorio de Ecología Molecular, Estación Biológica
de Doñana, CSIC (LEM-EBD). Two anonymous reviewers and the associate editor
provided valuable feedback that improved the quality of this manuscript.
Author details
1Center for Conservation and Evolutionary Genetics, Smithsonian
Conservation Biology Institute, National Zoological Park, Washington, DC
20008, USA. 2Division of Mammals, National Museum of Natural History, MRC
108, Smithsonian Institution, P.O. Box 37012, Washington, DC 20013-7012,
USA. 3Department of Environmental Science and Policy, George Mason
University, Fairfax, VA 22030, USA. 4Conservation and Evolutionary Genetics
Group, Estación Biológica de Doñana(EBD-CSIC), 41092 Sevilla, Spain.
5Department of Biology, George Mason University, Fairfax, VA 22030, USA.
Received: 22 November 2015 Accepted: 3 April 2016
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