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R E S E A R C H A R T I C L E Open Access
Genome sequence, population history, and
pelage genetics of the endangered African
wild dog (Lycaon pictus)
Michael G. Campana
1,2*
, Lillian D. Parker
1,2,3
, Melissa T. R. Hawkins
1,2,3
, Hillary S. Young
4
, Kristofer M. Helgen
2,3
,
Micaela Szykman Gunther
5
, Rosie Woodroffe
6
, Jesús E. Maldonado
1,2
and Robert C. Fleischer
1
Abstract
Background: The African wild dog (Lycaon pictus) is an endangered African canid threatened by severe habitat
fragmentation, human-wildlife conflict, and infectious disease. A highly specialized carnivore, it is distinguished by
its social structure, dental morphology, absence of dewclaws, and colorful pelage.
Results: We sequenced the genomes of two individuals from populations representing two distinct ecological histories
(Laikipia County, Kenya and KwaZulu-Natal Province, South Africa). We reconstructed population demographic histories
for the two individuals and scanned the genomes for evidence of selection.
Conclusions: We show that the African wild dog has undergone at least two effective population size reductions in
the last 1,000,000 years. We found evidence of Lycaon individual-specific regions of low diversity, suggestive of
inbreeding or population-specific selection. Further research is needed to clarify whether these population reductions
and low diversity regions are characteristic of the species as a whole. We documented positive selection on the Lycaon
mitochondrial genome. Finally, we identified several candidate genes (ASIP,MITF,MLPH,PMEL) that may play a role in
the characteristic Lycaon pelage.
Keywords: Lycaon pictus, Genome, Population history, Selection, Pelage
Background
The African wild dog (Lycaon pictus) is an endangered
canid species (International Union for Conservation of
Nature Red List Classification: C2a (i)) [1]. While the
species formerly ranged over most of sub-Saharan
Africa, wild dogs suffer from a suite of threats including
severe habitat fragmentation, human persecution, and
disease epidemics. They are now restricted to less than
seven percent of their former range [2], with only small,
and frequently declining, remnant populations in frag-
mented pockets of eastern and southern Africa (Fig. 1).
They maintain enormous home ranges (varying between
200 and 2000 km
2
) and naturally live at very low
densities, even compared to other carnivores [3].
Primarily a hunter of antelopes, the African wild dog is a
highly distinct canine. Wild dogs are differentiated from
other canine species by their anatomical adaptations re-
lated to hypercarnivory and cursorial hunting, including
high-crowned, sectorial teeth and the lack of dewclaws
[4]. They have a highly specialized social structure in
which both males and females disperse to form new
packs and only a single dominant pair in each pack re-
produces [5]. Wild dogs are also noted for their colorful
pelage, from which they derive their species name pictus
(‘painted’), and the absence of an undercoat.
Eastern and southern populations of wild dogs are
genetically and morphologically distinct [6], although
there is a large admixture zone covering Botswana,
south-eastern Tanzania, and Zimbabwe [7]. Gene flow
occurs across the species’entire range [8], which is
unsurprising given the excellent dispersal capabilities
documented in Lycaon pictus [1]. Nevertheless, Marsden
et al. [2] documented both genetic structuring between
extant Lycaon populations (likely the result of habitat
* Correspondence: CampanaM@si.edu
1
Center for Conservation Genomics, Smithsonian Conservation Biology
Institute, 3001 Connecticut Avenue NW, Washington, DC 20008, USA
2
Department of Environmental Science and Policy, George Mason University,
4400 University Drive, Fairfax, VA 22030, USA
Full list of author information is available at the end of the article
© The Author(s). 2016 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.
Campana et al. BMC Genomics (2016) 17:1013
DOI 10.1186/s12864-016-3368-9
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
fragmentation) and a recent reduction in effective
population size (N
e
) since the 1980s. Furthermore,
African wild dogs exhibit very little major histocom-
patibility complex variation, which may reflect popu-
lation decline [8].
To better understand African wild dog genomic evolu-
tion, genetic variation and population history, we
shotgun sequenced whole genomes from two individuals
from widely separated populations with very different
modern ecological histories: Laikipia County, Kenya and
Hluhluwe-Imfolozi Park, KwaZulu-Natal Province,
South Africa. Wild dogs disappeared from Laikipia,
Kenya in the 1980s and reappeared in 2000 –likely
recolonizing from a small population in neighboring
Samburu district (~50 km distant). The population in
Laikipia alone now numbers more than 150 dogs and 15
packs [9]. We sequenced a female (sampled July 2003)
from this recolonized population. In contrast, wild dogs
were reintroduced to Hluhluwe-Imfolozi Park,
KwaZulu-Natal Province in 1980 and remained as a
single pack for many years [10]. Eventually, Lycaon
breeding effectively ceased until new animals were intro-
duced in 1997 and afterwards (2001, 2003, etc.) [11].
The KwaZulu-Natal wild dogs are now managed as part
of the South African Lycaon “metapopulation”[12, 13].
We sequenced a male (sampled October 2007), born in
KwaZulu-Natal to parents that were translocated from
Limpopo province in 2003. Therefore, the South African
individual’s ancestry represents genes from the northeastern
part of the country.
The genomes from these two populations represent
some of the first published wild canid genomes and are
particularly valuable given the susceptibility of wild dogs
to diseases and habitat fragmentation [9, 14]. We used
our novel genome sequences to reconstruct the last
1,000,000 years of Lycaon genome demography and
population history. We identified over a million poly-
morphic sequence variants for further population-level
study. These variants produced ~35 million predicted
genic effects. We identified over 15,000 candidate genes
that may have undergone adaptation since the Lycaon/
Canis divergence. We found evidence of positive selec-
tion on the Lycaon mitochondrial genome. Finally, we
examined genes involved in canid coat phenotype to
identify candidate genes underlying the characteristic
Lycaon pelage.
Results and discussion
Genome sequencing of the African wild dog
Based on alignment with the domestic dog genome, we
have sequenced ~90% (5.8× mean read depth) of the
Kenyan individual’s genome and ~93% (5.7×) of the
South African Lycaon individual’s genome. We identified
16,967,383 autosomal sequence variants (including
14,360,480 single nucleotide polymorphisms [SNPs] and
2,606,903 indels) separating our Lycaon genomes from
the domestic dog (Canis familiaris) genome [GenBank:
CanFam3.1] (Additional files 1 and 2) [15]. Of these,
1,092,450 (781,329 SNPs and 311,121 indels) were
polymorphic in the African wild dog. The remaining
15,874,933 autosomal sequence variants (13,579,151
SNPs and 2,295,782 indels) were monomorphic in the
two Lycaon individuals. We identified 717,870 X-
chromosomal variants (619,606 SNPs and 98,264 indels),
of which 32,801 (23,001 SNPs and 9,800 indels) were
polymorphic and 685,069 (596,605 SNPs and 88,464
indels) were monomorphic in the African wild dog.
Additionally, we sequenced the Kenyan and South
African wild dog mitochondrial genomes to depths of
943× and 1021×, respectively. We annotated the Lycaon
Fig. 1 South African wild dog pack (top)andmapofextantandformer
wild dog range (bottom). The sampling locations of the two individuals
are noted on the map. Ranges are modified from Woodroffe
and Sillero-Zubiri [1] and Marsden et al. [2]. Extant range data
used with permission from the International Union for the Conservation
of Nature [Woodroffe R, Sillero-Zubiri C 2012. Lycaon pictus.In:IUCN
2016. IUCN Red List of Threatened Species. Version 2016–2. http://
www.iucnredlist.org. Downloaded 12 July 2016]. Photograph by
Micaela Szykman Gunther
Campana et al. BMC Genomics (2016) 17:1013 Page 2 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
autosomal and X-chromosomal sequences using the do-
mestic dog genome annotations [GenBank:CanFam3.1.81]
and the mitochondrial genome [GenBank:NC_002008.4]
and MSY sequences [GenBank:KP081776.1] using their
reference sequence annotations [15–17].
Lycaon demographic history
We analyzed the two wild dogs’autosomal population
histories using PSMC (Fig. 2) [18]. Both genomes exhib-
ited a strong reduction in N
e
starting 700,000 years ago
from maximum N
e
s of ~28,000 (Kenyan) and ~35,000
(South African) individuals and leveling off 200,000 years
ago at N
e
s of ~7,000 individuals each. Analysis of the
Kenyan individual’s X - chromosomal history using
PSMC showed a similar pattern (Fig. 2). N
e
fell from a
maximum of ~40,000 individuals 600,000 years ago to
~7000 individuals 200,000 years ago. This N
e
reduction
may represent a past population bottleneck e.g. [19] or
lineage splitting e.g. [20]. Further genomic analysis of in-
dividuals from across the Lycaon range, especially those
from larger founder populations, would help clarify the
cause of this pattern.
PSMC analysis of the Kenyan X chromosome revealed
a secondary reduction in N
e
started 70,000 years ago to
a final N
e
of ~2000 individuals 10,000 years ago. We are
unable to infer more recent population history accur-
ately using this method due to the limited numbers of
available mutations in the short time frame [18]. Further
research using historical museum Lycaon specimens
would fill in this temporal gap e.g. [21]. While our
reconstructions were robust to coverage variation (see
‘Demographic history reconstruction’below), higher
coverage genomes would also increase the resolution of
population history reconstructions [20].
Candidate selected processes and genomic regions
Based on the domestic dog genome annotations, SnpEff
4.1 L predicted that the identified Lycaon autosomal and
X-chromosomal sequence variants would cause 34,001,288
and 36,362,161 genic effects in the Kenyan and South
African individuals, respectively (Additional files 1 and 2)
[22]. The majority of sequence variant effects fell within
introns (Kenyan: 62.604%, South African: 63.383%) and
intergenic regions (Kenyan: 23.081%, South African:
23.162%). To discover candidate genes that have diverged
since Lycaon ’s divergence with Canis, we identified Lycao n
genes that contained missensemutationsandstopcodon
gains using SnpSift 4.1 L [23]. We identified 15,611 (15,565
genes with missense mutations and 799 with stop codon
gains) Kenyan and 9793 (9440 genes containing missense
mutations and 741 with stop codon gains) South African
wild dog candidate divergent genes. 9506 divergent genes
(9159 with missense mutations and 653 with stop codon
gains) were found in both wild dogs. These divergent genes
were determined by 47,059 Kenyan sequence variants
(sequenced at 8.6× mean coverage) of and 27,893 South
African variants (6.0× mean coverage). 25,149 variants were
shared between the two Lycao n individuals. These variants
were very homozygous (Kenyan: 95%, South African: 95%),
whichsuggeststhattheyaretheresultofdivergence
between the Lycao n and Canis clades, rather than more
recent variants arising within Lycaon.
We annotated the candidate divergent genes’functions
using DAVID 6.7 with domestic dog (option “Canis
lupus”) as the genomic background [24]. We found 76
and 29 enriched processes in the Kenyan and South
African individuals, respectively (Additional files 3 and
4). We filtered these terms with a Benjamini-Hochberg
false discovery rate of 0.05 [25]. After filtration, seven
terms (‘Complement and coagulation cascades’,‘ECM-
0
1
2
3
4
5
6
104105106
Effective population size (x104)
Years before present
South Africa (Autosomes)
Kenya (Autosomes)
Kenya (X Chromosome)
Fig. 2 Reconstruction of the Lycaon individuals’autosomal and X-chromosomal demographic history using the pairwise sequentially Markovian
coalescent. Initial results are plotted using dark-colored curves, with the bootstrap replicates plotted in lighter hues of the corresponding colors
Campana et al. BMC Genomics (2016) 17:1013 Page 3 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
receptor interaction’,‘Neuroactive ligand-receptor inter-
action’,‘Hematopoietic cell lineage’,‘Lysosome’,‘ABC
transporters’,‘Aminoacyl-tRNA biosynthesis’) were sig-
nificantly enriched in the Kenyan individual. ‘Olfactory
transduction’was significant in the South African indi-
vidual. The differences in significant terms may reflect
population-specific selection pressures on wild dogs.
Further population-level investigation is needed to deter-
mine the roles these pathways play in Lycaon evolution.
In order to identify regions of low and high diversity, we
calculated the numbers of segregating SNP sites across the
Lycaon autosomes in 100,000 bp non-overlapping windows
using VCFtools 0.1.15 (Fig. 3) [26, 27]. By averaging over
large genomic windows, we limited the effects of sequen-
cing errors and allelic drop-out due to low sequencing
coverage. We identified 768,416 segregating Lycaon SNPs
(Kenyan: 398,891 SNPs, South African: 434,911 SNPs). We
observed individual-specific regions of low diversity (<10
segregating SNPs/100,000 bp). The Kenyan individual had
runs of low diversity (contiguous regions of low diversity at
least 5 million bp long) on chromosomes 4, 6, 7, 12, 15, 21,
27, and 30, while the South African individual had runs of
low diversity on chromosomes 1, 5, 8, 12, 14, 19, 27, 29, 30,
34, 36 and 38. These low-diversity regions may be the result
of inbreeding and/or population-specific natural selection.
Due to the long lengths of these low-diversity runs, encom-
passing numerous genes, we are not currently able to link
low diversity levels to selection on individual genes. These
results are not surprising since both populations are
recently re-established, either by natural recolonization
(Laikipia, Kenya) or deliberate reintroduction (KwaZulu-
Natal, South Africa). Previous genetic investigations using
microsatellites and mitochondrial DNA found some
evidence of rare inbreeding in wild dogs from the Greater
Limpopo Transfrontier Conservation Area and KwaZulu-
Natal [10, 28]. However, free-ranging wild dogs strongly
avoid incestuous matings [10]. For instance, at KwaZulu-
Natal, Becker et al. [10] observed only one of six breeding
pairs being more closely related than third-order kin. While
our chromosomal diversity data do not permit us to discern
Fig. 3 Segregating autosomal SNP sites across the Lycaon genomes. Chromosomes are distinguished by color and separated by black lines.Thenumber
of segregating SNPs per 100,000 bp window is plotted on the y-axis in logarithmic scale. We identified population-specific regions of low diversity inboth
the Kenyan (chromosomes 4, 6, 7, 12, 15, 21, 27, and 30) and South African (chromosomes 1, 5, 8, 12, 14, 19, 27, 29, 30, 34, 36 and 38) individuals. There are
also highly variable regions on chromosomes 3 and 16 in both individuals, chromosome 26 in the Kenyan individual, and chromosome 19 in the South
African individual
Campana et al. BMC Genomics (2016) 17:1013 Page 4 of 10
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between inbreeding and/or population-specific natural
selection, the possibility of inbreeding is, therefore, con-
cerning from a conservation standpoint. Additional
population-level data are required to determine the causes
and effects of these low-diversity regions.
We also identified regions of high diversity (>200
segregating SNPs per 100,000 bp) on chromosomes 3
and 16 in both individuals and chromosome 19 in the
South African individual (Fig. 3). The high-diversity re-
gions comprised 0.44% of the total segregating SNPs in
both individuals and included 1138 Kenyan and 970
South African segregating SNPs on chromosome 3,646
Kenyan and 704 South African segregating SNPs on
chromosome 16, and 249 South African segregating
SNPs on chromosome 19. Using the UCSC Genome
Browser [29], we scanned the genome within 100,000 bp
upstream and downstream of these high-diversity
regions for known genes mapped to CanFam3.1. These
included FER,FKBP3,SNRPF,andPJA2 on chromosome
3, HUS1 and PKDIL1 on chromosome 16, and RNF150
and TBC1D9 on chromosome 19. These genic regions
may have undergone positive or relaxed selection
since the Lyc aon/Canis divergence or may represent
chromosomal duplications. Future functional analyses
will determine which roles (if any) these genes play in
Lycaon evolution.
Positive selection on the mitochondrial genome
Each of the 13 protein-encoding mitochondrial genes
from the two novel Lycaon mitochondrial genomes were
aligned against the corresponding genic sequences from
the domestic dog mitochondrial reference sequence and
the one publically available near-complete Lycaon pictus
mitochondrial genome sequence [GenBank:KT448283.1]
[16, 30]. We calculated ratios of non-synonymous substi-
tutions per non-synonymous site to synonymous substi-
tutions per synonymous site (dN/dS) and tested for
positive selection using the codon-based Z-test in
MEGA6 [31]. We found evidence for positive selection
on 12 of 13 genes (COX1,COX2,COX3,ATP6,ATP8,
ND1,ND2,ND3,ND4,ND4L,ND5,CYTB; Additional
file 5). To determine whether selection occurred primar-
ily on the Lycaon or Canis branches, we reran these
analyses excluding the domestic dog sequence. We
found evidence for positive selection on all 13 Lycaon
mitochondrial genes (Additional file 5).
To confirm branch specific signatures of selection, we
aligned the Lycaon CYTB sequences against published
canid taxa [GenBank: AY656746, EU442884, GU063864,
JF342908, KF646248, KT448273–4, KU696390,
KU696404, KU696408, NC_008093, NC_013445] using
MAFFT 7.222 [32] as implemented in Geneious 10.0.2
(Biomatters, Ltd., Auckland, New Zealand). We then
generated a phylogenetic tree with FastTree 1.0 [33].
Using the ‘codonml’algorithm in PAML 4.8 [34], we per-
formed pairwise comparisons on CYTB codon data and
compared the likelihood of the alternate (non-fixed
omega values) or null hypotheses (fixed omega values).
A likelihood ratio test was calculated from ln values
obtained from these comparisons to determine where
evidence of selection was occurring in canids. We found
significant evidence (p≤0.001) of positive selection
between African wild dogs and coyotes (Canis latrans)
(statistic: 128.88) and between Lycaon and Cuon (statis-
tic: 81.48). We also found branch-specific selection be-
tween the Kenyan and South African Lycaon individuals
(statistic: 92.54).
The 13 candidate selected Lycaon mitochondrial
genes are involved in the electron transport chain and
adenosine triphosphate synthesis. This suggests
natural selection on Lyc aon metabolic processes e.g.
[35, 36], which is likely given their unique antelope
hunting strategies and diet. Moreover, these results
are consistent with African wild dogs’very high meta-
bolic rate and hunting energy expenditure in com-
parison to domestic dogs [37].
Pelage genes
We extracted CDS corresponding to 11 genes involved
in canid coat color (agouti signaling peptide [ASIP],
β-defensin 103 [DEFB103A], melanocortin 1 receptor
[MC1R], melanophilin [MLPH], microphthalmia-associated
transcription factor [MITF], premelanosome protein
[PMEL], tyrosinase-related protein 1 [TYRP1]) and type
(fibroblast growth factor 5 [FGF5], keratin 71 [KRT71],
R-spondin 2 [RSPO2]) [38–46] using Geneious 9.0.4. In
cases where there were multiple isoforms or CDS annota-
tions (DEFB103A,FGF5,MITF,PMEL), we chose the
longest variant alignable to the domestic dog CDS reference
sequence to maximize detection power. To detect positively
selected genes, we identified non-synonymous and syn-
onymous SNPs compared to the domestic dog sequence
and calculated the non-synonymous/synonymous (N/S)
ratio (Additional file 6).
ASIP and PMEL had elevated N/Sratios suggestive of
positive selection (5.00 and 9.00 respectively). Lycaon
PMEL also had a stop codon gain at amino acid 341,
suggesting selection at this locus. Additionally, we found
a threonine insertion at amino acid 371 in the Lycaon
MLPH gene and a six amino acid deletion corresponding
to domestic dog amino acids 186–191 in the Lycaon
MITF gene. To further characterize these four candidate
genes, we compared the Lycaon coding sequences
against all publically available canid sequences using
BLAST+ 2.5.0 [47]. None of the Lycaon ASIP,PMEL,
MITF, and MLPH CDS haplotypes have been identified
in other canids previously. Lycaon ASIP shares 99%
nucleotide identity, but only 96% amino acid identity,
Campana et al. BMC Genomics (2016) 17:1013 Page 5 of 10
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with domestic dogs. Wild dog PMEL shares both 99%
nucleotide identity and amino acid identity with do-
mestic dogs. Excluding the six amino acid deletion,
Lycaon MITF haplotypes had >99% nucleotide and
amino acid identity with domestic dogs. Lycaon
MLPH haplotypes had 98% nucleotide identity and
97–98% amino acid identity (excluding the amino
acid insertion) to domestic dogs.
These four genes are strong candidates to explain the
characteristic Lycaon pelage. Mutations in ASIP alter
relative production of eumelanin and pheomelanin,
resulting in lighter and darker hair colors, in numerous
species including domestic dogs [41]. Variants in PMEL
cause merle patterning in domestic dogs [40]. MITF is
associated with white-spotting phenotypes in domestic
dogs and causes coat color variants in laboratory mice
(Mus musculus). MITF variants are also associated with
deafness, small eye size, and poor bone resorption in
mice [46]. Nevertheless, further laboratory assays (such
as transgenic experiments) are needed to confirm that
these identified variants are functional and to determine
their phenotypic effects. Furthermore, our data do not
permit us to distinguish between positive selection on
the Lycaon and Canis branches (e.g. coat variation
associated with dog domestication and breed development).
Conclusions
We provide two genome sequences of Lycaon pictus,
representing two individuals from highly divergent
ecological regions (Laikipia County, Kenya and
KwaZulu-Natal Province, South Africa). We identified
over a million polymorphic Lycaon SNPs, useful for fur-
ther population-level analyses. Analyses of these ge-
nomes showed that extant Lycaon populations have
endured at least two population contractions within the
last 1,000,000 years. We identified chromosomal regions
of high and low diversity and over 15,000 candidate
divergent genes. Furthermore, Lycaon mitochondrial
genomes have undergone positive selection, suggestive
of selection for metabolic processes. Finally, we identi-
fied four candidate genes (ASIP,MITF,MLPH,PMEL)
that may be involved in Lycaon pelage patterns.
Methods
Samples
We sequenced two Lycaon pictus individuals sampled
during previous studies: a female from Laikipia County,
Kenya [2, 9] and a male from Hluhluwe-Imfolozi Park,
KwaZulu-Natal Province, South Africa [10, 48, 49]. The
Kenyan individual was sampled under an Institutional
Animal Care and Use Committee (IACUC) protocol ap-
proved by the University of California, Davis (10813) [9],
while the South African individual was sampled under
IACUC protocols approved by the Smithsonian National
Zoological Park (08-21) and Humboldt State University
(06/07.W.209.A) [10].
Laboratory methods
DNA was extracted from blood samples using Qiagen
blood and tissue kits (Qiagen, Valencia, CA, USA) and
sheared to ~350 bp using a Q800R sonicator (Qsonica,
LLC, Newtown, CT, USA). Double-indexed Illumina
libraries were built from the sheared DNA using the
KAPA Library Preparation Kit –Illumina (Kapa Biosystems,
Wilmington, MA, USA) with purification steps per-
formed using carboxyl paramagnetic beads [50].
Library quality was ensured via fluorometric analysis
using Qubit® dsDNA HS assays (Life Technologies,
Carlsbad, CA, USA), quantitative PCR using the
KAPA Library Quantification Kit –Illumina/Universal
(Kapa Biosystems, Wilmington, MA, USA), and ana-
lysis on a 2100 Bioanalyzer (Agilent Technologies,
Santa Clara, CA, USA) high-sensitivity DNA chip.
Libraries were pooled equimolarly and 2 × 250 bp
paired-end sequenced on a HiSeq 2500 lane (Illumina,
Inc., San Diego, CA, USA).
Sequence quality control
Read pairs were demultiplexed using the BaseSpace® pipe-
line (Illumina, Inc., San Diego, CA, USA). 75,651,396 and
63,766,266 read pairs were generated for the Kenyan and
South African Lycaon samples respectively. Raw reads
were trimmed and adapter artifacts were removed using
Trimmomatic 0.33 (options ILLUMINACLIP: NexteraPE-
PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWIN-
DOW:4:20 MINLEN:36) [51]. Library sequence quality
was confirmed using FastQC 0.11.2 [52].
Mitochondrial genome assembly
The quality-controlled reads were aligned against the
circularized domestic dog reference mitochondrial
genome [GenBank:NC_002008.4] [16] using Geneious
8.1.6 (medium-low sensitivity, 5 alignment iterations,
minimum mapping quality 30). The aligned reads were
merged using FLASH 1.2.11 (option –M 250) [53]. PCR
duplicates were removed from the merged reads using
CD-HIT-DUP 0.5 [54]. The deduplicated reads were
then realigned against the dog reference mitochondrial
genome in Geneious 8.1.6 (medium sensitivity align-
ment, 10 alignment iterations, minimum mapping
quality 30) to generate the final sequences.
Autosomal assembly
The non-mitochondrial reads were merged using
FLASH 1.2.11 (option –M 250) [51]. The merged,
unmerged, and unpaired reads were then concatenated
and treated as single-end sequences for downstream
processing. The concatenated reads were aligned against
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Content courtesy of Springer Nature, terms of use apply. Rights reserved.
the autosomes of the domestic dog genome build
CanFam3.1 [15] using the ‘mem’algorithm in BWA
0.7.12 [55, 56]. Aligned reads below mapping quality 30
and PCR duplicates were removed using the ‘view’
(option –q 30) and ‘rmdup’(option –s) commands in
SAMtools 1.3 [57]. Sequence variants (minimum quality
20) were identified using the SAMtools 1.3 ‘mpileup’
command (option –C50) and BCFtools 1.3 ‘call’
command (option –m) pipeline [57, 58]. Genome com-
pleteness was evaluated using BUSCO 1.1b1 and the
‘Vertebrates’gene set (Additional files 7, 8 and 9) [59].
Genome assemblies were very complete: compared to
the 1663 ‘complete’BUSCO autosomal orthologs found
in the domestic dog, 1614 (97%) of the Kenyan and 1665
(100.1%) of the South African individual’s orthologs were
complete. Similarly, 747 ‘fragmented’BUSCO autosomal
orthologs were found in the domestic dog, compared to
688 (92.1%) for the Kenyan individual and 707 (94.6%)
for the South African individual.
Allosomal assembly
The Kenyan Lycaon individual was a female, while the
South African individual was a male. To reconstruct the
allosomal sequences, we aligned the unmapped,
concatenated nuclear reads against either the CanFam3.1
X chromosome assembly (Kenyan individual) [15] or
both the CanFam3.1 X chromosome and domestic dog
MSY chromosome assemblies (South African individual)
[17] using the ‘mem’algorithm in BWA 0.7.12 [55, 56].
Aligned reads below mapping quality 30 and PCR dupli-
cates were removed using the ‘view’(option –q 30) and
‘rmdup’(option –s) commands in SAMtools 1.3 [57].
Sequence variants (minimum quality 20) were identified
using the SAMtools 1.3 ‘mpileup’command (option –
C50) and BCFtools 1.3 ‘call’command (option –m)
pipeline [57, 58]. The mapped MSY reads were then
realigned against the reference sequence [Gen-
Bank:KP081776.1] using Geneious 8.1.7 (medium sensi-
tivity alignment, five alignment iterations). Y coding
region sequences were extracted based on the domestic
dog MSY annotations, and consensus sequences were
generated using Geneious 8.1.7 (options Highest Quality
and Total). We excluded non-coding regions from
analysis due to the Y chromosome’s large number of re-
petitive elements, which complicates accurate alignment
[17]. We identified 87 Y SNPs between the African wild
dog and the domestic dog, of which 32 were silent muta-
tions, 53 produced amino acid substitutions, and two
caused gene truncations (Additional file 10).
Demographic history reconstruction
Autosomal population history parameters were recon-
structed using PSMC r62 (options –N25 –t15–r5 –p
“64*1”, minimum quality 20) and tested with 100
bootstrap replicates [18]. We calculated the autosomal
mutation rate for each Lycaon individual using the total
number of identified autosomal sequence variants
(13,985,381 and 15,132,667 for the Kenyan and South
African individuals respectively), an estimated autosomal
genome size of 2.3 Gbp, an estimated generation time of
5 years/generation [7] and an estimated divergence time
from the Canis/Cuon clade of 2.74 million years ago
(95% highest posterior density: 2.15–3.38 million years
ago) [30]. We estimated the Kenyan and South African
Lycaon mutation rates as 5.5 × 10
−9
mutations/site/gen-
eration (range: 5.0–7.1 × 10
−9
mutations/site/generation)
and 6.0 × 10
−9
mutations/site/generation (range: 4.9–
7.7 × 10
−9
mutations/site/generation) respectively. Final
PSMC demographic reconstructions were scaled based
on an estimated generation time of 5 years/generation
[7] and a mutation rate of 5.8 × 10
−9
mutations/site/gen-
eration. While variation of the reconstruction scaling
within the extremes of the estimated mutation rates
(4.9–7.7 × 10
−9
mutations/site/generation) varied
estimates of N
e
and timing of population history events,
overall demographic history patterns remained similar.
The Kenyan X-chromosomal history was recon-
structed separately from the autosomal history. We cal-
culated the X-chromosomal mutation rate for the
Kenyan individual using the total number of observed
Kenyan X-chromosomal variants (634,216), the same di-
vergence and generation times as for the autosomal ana-
lyses and a chromosome size of 124 Mbp. We estimated
the Kenyan X-chromosomal mutation rate as 4.7 × 10
−9
mutations/site/generation (range: 3.8–5.9 × 10
−9
muta-
tions/site/generation). We did not estimate the
X-chromosomal mutation rate for the South African
male due to his hemizygosity. X-chromosomal PSMC
demographic reconstruction and scaling parameters
were the same as for the autosomal analyses except
that the results were scaled with a mutation rate of
4.7 × 10
−9
mutations/site/generation. Variation of the
mutation rate scaling again did not affect inference of
demographic history.
To test the effects of coverage on our demographic re-
constructions, we repeated the PSMC analyses under
medium depth stringency settings (minimum sequencing
depth 2, maximum sequencing depth 12) recommended
by PSMC’s authors and high depth stringency settings
(minimum sequencing depth 10) recommended in [20].
We recovered nearly identical demographic reconstruc-
tions under the medium depth stringency settings
(Additional file 11). Under the high depth stringency
settings, we were unable to resolve the Kenyan
X-chromosomal reconstruction due to missing data.
Nevertheless, our autosomal reconstructions under the
high depth stringency recovered very similar demo-
graphic histories for the last 1,000,000 years, except that
Campana et al. BMC Genomics (2016) 17:1013 Page 7 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
N
e
estimates were larger (particularly in the South
African individual) (Additional file 12). Increased N
e
estimates are expected since heterozygotes are more
likely to be observed in the higher coverage regions [20].
Therefore, we conclude that our reconstructed demo-
graphic patterns were robust to coverage variation.
Interestingly, under the high depth stringency
settings, we also reconstructed two additional contrac-
tion and expansion cycles between 10,000,000 and
600,000 years ago in the South African individual’s
population history (Additional file 12). These results
require further verification with additional genome
sequences.
Additional files
Additional file 1: Genic effects of SnpEff-annotated autosomal and
X-chromosomal variants for the Kenyan Lycaon individual. (HTML 1596 kb)
Additional file 2: Genic effects of SnpEff-annotated autosomal and
X-chromosomal variants for the South African Lycaon individual.
(HTML 1535 kb)
Additional file 3: DAVID-annotated enriched functional processes for
the Kenyan Lycaon individual. For each functional term, the total gene
count, the associated genes, and the Benjamini-Hochberg false discovery
rate value are given. (XLSX 23 kb)
Additional file 4: DAVID-annotated enriched functional processes for
the South African Lycaon individual. For each functional term, the total
gene count, the associated genes, and the Benjamini-Hochberg false
discovery rate value are given. (XLSX 16 kb)
Additional file 5: Positive selection test results on the Lycaon
mitochondrial genome. Zstatistics are included in parentheses after the
probability for each of the three competing models (Neutrality, Positive
Selection, Purifying Selection). Results for the tests excluding the domestic
dog sequence are denoted by ‘Lycaon’in the column heading. (XLSX 48 kb)
Additional file 6: Positive selection scan results on candidate Lycaon
pelage genes. Genes were aligned to the reference CDS provided in the
table. Gene coordinates are given with reference to the domestic dog
genome [GenBank:CanFam3.1]. The total numbers of fixed and polymorphic
synonymous and non-synonymous SNPs and the N/Sratios are provided.
Also listed are non-SNP variants identified during the scan. (XLSX 41 kb)
Additional file 7: Autosomal BUSCO orthologs identified in the
CanFam3.1 assembly. Scaffolds are identified by GenBank accession.
(XLSX 182 kb)
Additional file 8: Autosomal BUSCO orthologs identified in the Kenyan
Lycaon pictus genome. Scaffolds are identified by GenBank accession.
(XLSX 166 kb)
Additional file 9: Autosomal BUSCO orthologs identified in the South
African Lycaon pictus genome. Scaffolds are identified by GenBank
accession. (XLSX 170 kb)
Additional file 10: Genic effects of Lycaon MSY coding sequence
variants. (XLSX 55 kb)
Additional file 11: Reconstruction of the Lycaon individuals’
autosomal and X-chromosomal demographic history using the
pairwise sequentially Markovian coalescent with medium coverage
stringency. Initial results are plotted using dark-colored curves, with
the bootstrap replicates plotted in lighter hues of the corresponding
colors. (EPS 252 kb)
Additional file 12: Reconstruction of the Lycaon individuals’autosomal
and X-chromosomal demographic history using the pairwise sequentially
Markovian coalescent with high coverage stringency. Initial results are
plotted using dark-colored curves, with the bootstrap replicates plotted
in lighter hues of the corresponding colors. (EPS 189 kb)
Abbreviations
bp: Base pairs; CDS: Coding sequence; dN/dS: Non-synonymous substitutions
per non-synonymous site to synonymous substitutions per synonymous site;
IACUC: Institutional Animal Care and Use Committee; MSY: Male-specific Y
chromosome; N/S: Non-synonymous substitutions to synonymous substitutions;
N
e
: Effective population size; SNP: Single nucleotide polymorphism
Acknowledgements
We thank Penny Becker (United States Fish and Wildlife Service), Michael
Somers (University of Pretoria) and David Wildt (Smithsonian Conservation
Biology Institute) for facilitating collection of the South African sample. We
are grateful for the assistance of Adam Ferguson (Mpala Research Centre) in
the production of the Lycaon range map. We thank the members of the
Center for Conservation Genomics, Smithsonian Conservation Biology
Institute for helpful advice on this manuscript.
Funding
The Morris Animal Foundation (D14ZO-308) and the National Geographic
Society (8846–10) supported this research.
Availability of data and materials
The data sets supporting the results of this article are available in the
Sequence Read Archive and GenBank repositories, (BioProject PRJNA304992;
http://www.ncbi.nlm.nih.gov/bioproject/PRJNA304992; GenBank
LPRA00000000 and LPRB00000000; http://www.ncbi.nlm.nih.gov/nuccore/
LPRA00000000 and http://www.ncbi.nlm.nih.gov/nuccore/LPRB00000000).
Authors’contributions
MGC performed the molecular genetic assays, carried out bioinformatics
analyses, and wrote the manuscript. KHM and RFC conceived the study.
MTRH and LDP performed bioinformatics analyses and contributed to the
manuscript. RW, MSG, and JEM provided the Lycaon samples. KHM, RFC, HSY,
RW and JEM participated in the design of the study. All authors reviewed
and approved the manuscript.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
Not applicable.
Ethics approval and consent to participate
The Lycaon pictus individuals were sampled under IACUC protocols approved
by the University of California, Davis (10813), the Smithsonian National
Zoological Park (08–21), and Humboldt State University (06/07.W.209.A).
Ezemvelo KZN Wildlife, the Kenya Wildlife Service, the National Museums of
Kenya, the Kenya National Council for Science and Technology, and Mpala
Research Centre gave permission and relevant permits to conduct this research
and provided logistical support. All experiments were conducted in compliance
with the Convention on the Trade in Endangered Species of Wild Fauna and
Flora and the International Union for the Conservation of Nature Policy
Statement on Research Involving Species at Risk of Extinction.
Author details
1
Center for Conservation Genomics, Smithsonian Conservation Biology
Institute, 3001 Connecticut Avenue NW, Washington, DC 20008, USA.
2
Department of Environmental Science and Policy, George Mason University,
4400 University Drive, Fairfax, VA 22030, USA.
3
Division of Mammals, National
Museum of Natural History, MRC 108, Smithsonian Institution, Washington,
DC 20013, USA.
4
Department of Ecology, Evolution and Marine Biology,
University of California Santa Barbara, Santa Barbara, CA 93106, USA.
5
Department of Wildlife, Humboldt State University, 1 Harpst St, Arcata, CA
95521, USA.
6
Institute of Zoology, Zoological Society of London, Regent’s
Park, London NW1 4RY, UK.
Received: 22 July 2016 Accepted: 2 December 2016
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