Research Article
Abstract
The lion
Panthera leo
is one of the world's most charismatic carnivores and is one of
Africa's key predators. Here, we used a large dataset from 357 lions
comprehending 1.13 megabases of sequence data and genotypes from 22
microsatellite loci to characterize its recent evolutionary history.
Patterns of molecular genetic variation in multiple maternal (mtDNA),
paternal (Y-chromosome), and biparental nuclear (nDNA) genetic markers
were compared with patterns of sequence and subtype variation of the
lion feline immunodeficiency virus (FIV
Ple), a lentivirus
analogous to human immunodeficiency virus (HIV). In spite of the ability
of lions to disperse long distances, patterns of lion genetic diversity
suggest substantial population subdivision (mtDNA Φ
ST = 0.92; nDNA
FST = 0.18), and reduced gene flow, which, along with large differences in sero-prevalence of six distinct FIV
Ple
subtypes among lion populations, refute the hypothesis that African
lions consist of a single panmictic population. Our results suggest that
extant lion populations derive from several Pleistocene refugia in East
and Southern Africa (~324,000–169,000 years ago), which expanded during
the Late Pleistocene (~100,000 years ago) into Central and North Africa
and into Asia. During the Pleistocene/Holocene transition
(~14,000–7,000 years), another expansion occurred from southern refugia
northwards towards East Africa, causing population interbreeding. In
particular, lion and FIV
Ple variation affirms that the large,
well-studied lion population occupying the greater Serengeti Ecosystem
is derived from three distinct populations that admixed recently.
Author Summary
The lion
Panthera leo,
a formidable carnivore with a complex cooperative social system, has
fascinated humanity since pre-historical times, inspiring hundreds of
religious and cultural allusions. Here, we use a comprehensive sample of
357 individuals from most of the major lion populations in Africa and
Asia. We assayed appropriately informative autosomal, Y-chromosome, and
mitochondrial genetic markers, and assessed the prevalence and genetic
variation of the lion-specific feline immunodeficiency virus (FIV
Ple),
a lentivirus analogous to human immunodeficiency virus (HIV) that
causes AIDS-like immunodeficiency disease in domestic cats. We compare
the large multigenic dataset from lions with patterns of genetic
variation of the FIV
Ple to characterize the
population-genomic legacy of lions. We refute the hypothesis that
African lions consist of a single panmictic population, highlighting the
importance of preserving populations in decline rather than
prioritizing larger-scale conservation efforts. Interestingly, lion and
FIV
Ple variation revealed evidence of unsuspected genetic
diversity even in the well-studied lion population of the Serengeti
Ecosystem, which consists of recently admixed animals derived from three
distinct genetic groups.
Citation: Antunes A, Troyer JL, Roelke ME, Pecon-Slattery J, Packer C, et al. (2008) The Evolutionary Dynamics of the Lion Panthera leo Revealed by Host and Viral Population Genomics. PLoS Genet 4(11):
e1000251.
doi:10.1371/journal.pgen.1000251
Editor: Arnaud Estoup, INRA, France
Received: July 27, 2007; Accepted: October 2, 2008; Published: November 7, 2008
This
is an open-access article distributed under the terms of the Creative
Commons Public Domain declaration which stipulates that, once placed in
the public domain, this work may be freely reproduced, distributed,
transmitted, modified, built upon, or otherwise used by anyone for any
lawful purpose.
Funding: This research has been
funded in part by federal funds from the National Cancer Institute,
National Institutes of Health (N01-CO-12400), by the Intramural Research
Program of the NIH, National Cancer Institute, Center for Cancer
Research, by the National Science Foundation (No. 0343960) and by the
Portuguese Foundation for Science and Technology
(PTDC/BIA-BDE/69144/2006). AA received a grant from the Portuguese
Foundation for Science and Technology (SFRH/BPD/5700/2001).
Competing interests: The authors have declared that no competing interests exist.
Introduction
Lion
fossils trace to the Late Pliocene in Eastern Africa and the Early
Pleistocene in Eastern and Southern Africa coincident with the
flourishing of grasslands ~2–1.5 million years ago
[1],
[2].
By Mid Pleistocene (~500,000 years ago), lions occupied Europe and by
the Late Pleistocene (~130,000–10,000 years ago) lions had the greatest
intercontinental distribution for a large land mammal (excluding man),
ranging from Africa into Eurasia and the Americas
[3].
Lions were extirpated from Europe 2,000 years ago and within the last
150 years from the Middle East and North Africa. Today, there are less
than 50,000 free-ranging lions
[4] that occur only in sub-Saharan Africa and the Gir Forest, India (
Figure 1A).
Figure 1. Geographic location of the lion samples and the variability of host and viral genetic markers among lion populations.
(A) Historical and current geographic distribution of lion,
Panthera leo.
A three-letter code pointing to a white dotted circle represents the
geographic location of the 11 lion populations determined by Bayesian
analyses
[22] and factorial correspondence analyses
[23]
of the genetic distinctiveness of 357 lion samples (see text): GIR, Gir
Forest, India; UGA, Uganda (Queen Elizabeth National Park); KEN, Kenya
(Laikipia), SER, Serengeti National Park, Tanzania; NGC, Ngorongoro
Crater, Tanzania; KRU, Kruger National Park, South Africa; BOT-I,
southern Botswana and Kalahari, South Africa; BOT-II, northern Botswana;
and NAM, Namibia. Green squares represent captive individual samples to
explore the relationship of lions from more
isolated/endangered/depleted areas: ATL, Morocco Atlas lions (
n = 4); ANG, Angola (
n = 2); and ZBW, Zimbabwe (
n
= 1). Deduced historical expansions (M1 and M2) are represented by red
arrows (see text). (B) Haplotype frequencies observed in the 11 lion
populations for nDNA (
ADA and
TF), and mtDNA (
12S–
16S) genes, paralleled with the FIV
Ple
serum-prevalence frequencies (black – sero-positive; gray –
indeterminate; white – sero-negative). Population sample sizes are
indicated within parenthesis. (C) Statistical parsimony networks of lion
ADA,
TF, and
12S–
16S haplotypes.
Circle size is proportional to the haplotype frequency and crossbars
represent the number of step mutations connecting haplotypes. The mtDNA
haplotypes H5 and H6 are shaded gray as they were detected only in the
individual samples from ANG, ATL, and ZBW, which do not group in unique
population clusters (see text).
doi:10.1371/journal.pgen.1000251.g001
Understanding
the broader aspects of lion evolutionary history has been hindered by a
lack of comprehensive sampling and appropriately informative genetic
markers
[5]–
[9], which in species of modern felids requires large, multigenic data sets due to its generally rapid and very recent speciation
[10],
[11]. Nevertheless, the unique social ecology of lions
[12]–
[14]
and the fact that lions have experienced well-documented infectious
disease outbreaks, including canine distemper virus, feline parvovirus,
calicivirus, coronavirus, and lion feline immunodeficiency virus (FIV
Ple)
[15]–
[18]
provide a good opportunity to study lion evolutionary history using
both host and virus genetic information. Indeed, population genetics of
transmitted pathogens can accurately reflect the demographic history of
their hosts
[19],
[20].
Unlike other of the 36 cat species, lions have a cooperative social
system (prides of 2–18 adult females and 1–9 males) and their
populations can have high frequencies of FIV
Ple, a lentivirus
analogous to human immunodeficiency virus (HIV), which causes AIDS-like
immunodeficiency disease in domestic cats. FIV
Ple is a
retrovirus that integrates into the host genome and is transmitted by
cell-to-cell contact, which in felids occurs during mating, fighting and
mother-to-offspring interactions. Thus, viral dissemination is a
function in part of the frequency of contact between infected and naïve
lions within and among populations. The virus is quite genetically
diverse in lions
[15],
[18], offering a unique marker for assessing ongoing lion demographic processes.
To
unravel lion population demographic history we used a large multigenic
dataset. Distinct sets of markers may not necessarily yield similar
inferences of population history, as coalescent times vary as a function
of their pattern of inheritance
[21].
There is also a large variance in coalescent times across loci sharing a
common pattern of inheritance especially in complex demographical
histories (
Table 1).
However, the accurate interpretation of the differences among loci can
provide a more resolved and coherent population history, affording
more-nuanced insights on past demographic processes, levels of
admixture, taxonomic issues, and on the most appropriate steps for
effective conservation and management of remaining populations.
The
goal of this study was to assess the evolutionary history of lion by
(1) characterizing lion population structure relative to patterns of FIV
Ple
genetic variation, (2) detect signatures of migration using both host
and viral population genomics, and (3) reconstruct lion demographic
history and discuss its implication for lion conservation. We assess
genetic variation from 357 lions from most of its current distribution,
including mitochondrial (mtDNA;
12S–
16S, 1,882 bp), nuclear (nDNA) Y-chromosome (
SRY, 1,322 bp) and autosomal (
ADA, 427 bp;
TF, 169 bp) sequences, and 22 microsatellites markers. We further document patterns of FIV
Ple variation in lions (FIV
Ple pol-RT gene, up to 520 bp).
Results/Discussion
Population Structure of Lion
Genetic analyses of 357 lions from throughout the extant species range showed that paternally inherited nDNA (
SRY) and maternal inherited (mtDNA) sequence variation was generally low (only one paternal
SRY-haplotype and 12 mtDNA haplotypes; π = 0.0066) (
Figure 1;
Figure S1;
Tables S1 and
S2).
The most common mtDNA haplotype H11 was ubiquitous in Uganda/Tanzania
and parts of Botswana/South Africa, H1 was common in Southern Africa,
and H7 and H8 were unique to Asian lions. The autosomal nDNA sequences
showed fairly distinct patterns of variation (
Figure 1;
Figure S1). Of the five
ADA
haplotypes, A2 was the most common and most-widely distributed. The
other four haplotypes, which are derived and much less common, included
one (A5) that was fixed in Asian lions. The three
TF haplotypes were more widely and evenly distributed.
Levels
of population subdivision among lions were assessed using
microsatellite and sequencing data. Eleven groups were identified using
Bayesian analyses
[22] and three-dimensional factorial correspondence analyses
[23] (
Figure 2;
Table S3). Most clusters represented geographically circumscribed populations: Namibia (N
am), Kruger National Park (K
ru), Ngorongoro Crater (N
gc), Kenya (K
en), Uganda (U
ga), and Gir (G
ir). Two distinct clusters were found in Botswana, B
ot-I that included lions from southern Botswana and Kalahari (South Africa) (
Fk = 0.24) and B
ot-II found exclusively in northern Botswana (
Fk
= 0.18). Surprisingly, three distinct clusters were found in a single
geographical locale (approximately 60×40 km square) in the large
panmyctic population of the Serengeti National Park (S
er-I/S
er-II/S
er-III) (
Fk = 0.18, 0.21, and 0.15, respectively).
Two captive lions from Angola (A
ng), one from Zimbabwe (Z
bw) and four Morocco Zoo Atlas lions (A
tl; presently extinct from the wild) (
Figure 1A) were included in the analyses to explore the relationship of lions from more isolated, endangered, or depleted areas. A
ng and Z
bw lions were assigned to B
ot-II (
q = 0.90 and 0.87; 90%CI: 0.47–1.00) and K
ru (
q = 0.85; 90%CI: 0.52–1.00) (Bayesian analyses
[22]) populations, respectively, as expected based on their geographical proximity. However, these lions differed from B
ot-II and K
ru by up to 8 mtDNA mutations, sharing haplotypes with the A
tl lions (H5 in A
ng and H6 in Z
bw) (
Figure 1B and 1C). The A
tl lions did not group in a unique cluster.
Both
nDNA and mtDNA pairwise genetic distances among the 11 lion populations
showed a significant relationship with geographic distance (
R2 = 0.75; Mantel's test,
P = 0.0097; and
R2 = 0.15; Mantel's test,
P = 0.0369; respectively) (
Figure 3).
The significant positive and monotonic correlation across all the
scatterplot pairwise comparisons for the nDNA markers (bi-parental) was
consistent with isolation-by-distance across the sampled region.
However, the correlation between nDNA
FST and geographic distance considerably decreased when the Asian G
ir population was removed (
R2 = 0.19; Mantel's test,
P
= 0.0065) suggesting that caution should be taken in interpreting the
pattern of isolation-by-distance in lions. We further compared
linearized
FST estimates
[24]
plotted both against the geographic distance (model assuming habitat to
be arrayed in an infinite one-dimensional lattice) and the log
geographic distance (model assuming an infinite two-dimensional
lattice). The broad distribution of lions might suggest
a priori that a two-dimensional isolation-by-distance model would provide the best fit for the nDNA data (
R2 = 0.25; Mantel's test,
P = 0.0022), but instead the one-dimensional isolation-by-distance model performed better (
R2 = 0.71; Mantel's test,
P = 0.0476) (
Figure S2).
The pattern observed for the mtDNA (maternal) was more complex. While there was a significant relationship between mtDNA
FST and geographic distance, there was an inconsistent pattern across broader geographic distances (
Figure 3).
This is partly due to the fixation or near fixation of haplotype H11 in
six populations and the fixation of a very divergent haplotype H4 in K
en population (
Figure 1B and 1C). The removal of the K
en population considerably increased the correlation between mtDNA
FST and geographic distance (
R2 = 0.27; Mantel's test,
P
= 0.0035). Thus, the null hypothesis of regional equilibrium for mtDNA
across the entire sampled region is rejected despite the possibility
that isolation-by-distance may occur regionally.
These
contrasting nDNA and mtDNA results may be indicative of differences in
dispersal patterns between males and females, which would be consistent
with evidence that females are more phylopatric than males.
Alternatively, selection for matrilineally transmitted traits upon which
neutral mtDNA alleles hitchhike is possible, given the low values of
nucleotide diversity of the mtDNA (π = 0.0066). A similar process has
been suggested in whales (π = 0.0007)
[25] and African savannah elephants (π = 0.0200)
[26],
where both species have female phylopatry and like lions, a matriarchal
social structure. However, genetic drift tends to overwhelm selection
in small isolated populations, predominantly affecting haploid elements
due to its lower effective population size (
Table 1).
Therefore, we suggest that the contrasting results obtained for nDNA
and mtDNA are more likely further evidence that lion populations
underwent severe bottlenecks. The highly structured lion matrilines
comprise four monophyletic mtDNA haplo-groups (
Figure 4A;
Figure S3). Lineage I consisted of a divergent haplotype H4 from K
en,
lineage II was observed in most Southern Africa populations, lineage
III was widely distributed from Central and Northern Africa to Asia, and
lineage IV occurred in Southern and Eastern Africa.
Population Structure of FIVPle
Seroprevalence studies indicate that FIV
Ple is endemic in eight of the 11 populations but absent from the Asian G
ir lions in India and in Namibia and southern Botswana/Kalahari regions (N
am/B
ot-I) in Southwest Africa (
Figure 1B). Phylogenetic analysis of the conserved
pol-RT region in 117 FIV-infected lions depicted monophyletic lineages
[15],
[18] that affirm six distinct subtypes (A–F) that are distributed geographically in three distinct patterns (
Figure 4B;
Figure S4).
First, multiple subtypes may circulate within the same population as
exemplified by subtypes A, B and C all ubiquitous within the three
Serengeti lion populations (S
er-I, S
er-II and S
er-III) and subtypes A and E within lions of Botswana (B
ot-II) (
Figure 4B and 4C and
Figure S4). Second, unique FIV
Ple subtypes may be restricted to one location as subtype F in Kenya, subtype E in Botswana (B
ot-II), subtype C in Serengeti, and subtype D in Krugar Park (
Figure 4B and 4C and
Figure S4).
Third, intra-subtype strains cluster geographically, as shown by
distinct clades within subtype A that were restricted to lions within
Krugar Park, Botswana and Serengeti and within subtype B that
corresponded to Uganda, Serengeti and Ngorongoro Crater lions (
Figure 4B and 4C and
Figure S4).
Not unexpectedly, FIV
Ple pairwise genetic distances, represented as population
FST among the eight lion FIV-infected populations, were not significantly correlated with geographic distance (
R2 = 0.08; Mantel's test,
P = 0.165) (
Figure 3),
and affirms that patterns of viral dissemination do not conform to a
strict isolation-by-distance model. Rather, the two distinct clusters
observed (
Figure 3) reflect the complex distribution of FIV
Ple among African lions. Indeed, despite the low geographic distance within East-African lion populations, the FIV
Ple genetic divergence showed a broader range in
FST (0.03 to 0.79 for most of first cluster;
Figure 3). By contrast, approximately half of the range in
FST (0.26 to 0.69 for the second cluster;
Figure 3)
was observed among East and Southern Africa in spite of its large
geographic separation. In contrast with the patterns observed in lions,
linearized
FST estimates
[24] for FIV
Ple were better correlated with log geographic distance (two-dimensional lattice model) (
R2 = 0.15) than with geographic distance (one-dimensional model) (
R2 = 0.02), although in both cases the Mantel's test was not significant (
P>0.2474) (
Figure S2).
Natural History of Lions as Inferred from Lion and FIVPle Markers
The mtDNA coalescence dating suggested that the East African lineage I (K
en haplotype H4) had an old origin of ~324,000 years (95% CI: 145,000–502,000). Extant East African populations (K
en/N
gc/S
er-I/S
er-II/S
er-III) also showed a slightly significant higher nDNA allelic richness and genetic diversity (
Table S4) relative to populations to the south (K
ru/N
am/B
ot-I/B
ot-II) and north (U
ga/G
ir) (
A = 2.43, 2.39, and 1.62,
P = 0.021;
HO = 0.64, 0.62, and 0.34,
P = 0.019; respectively). Moreover, the FIV
Ple
subtype diversity was higher in East African clades (exhibiting four
out of the six known viral-strains), including the most divergent FIV
Ple subtype C (
Figure 4B and 4C). These genetic data from lions and FIV
Ple
is consistent with the older origin of extant East African lions, which
is further supported by the oldest lion fossils discovered in East
Africa
[1].
Relative to East Africa, Southern lions have a slightly more recent mtDNA coalescence. Lineage II, found in N
am, B
ot-II and K
ru
has an estimated coalescence of 169,000 years (95% CI: 34,000–304,000)
and the more widespread lineage IV found in the Southern populations of B
ot-I, B
ot-II and K
ru as well as the Eastern populations of S
er (I, II, and III), N
gc and U
ga,
coalesces ~101,000 years ago (95% CI: 11,000–191,000). However, the
similar levels of nDNA genetic diversity, the occurrence of an
exclusively Southern mtDNA lineage II and highly divergent FIV
Ple subtypes, FIV
Ple subtype D found only in K
ru and subtype E exclusive to B
ot-II,
suggests that both East and Southern Africa were important refugia for
lions during the Pleistocene. Therefore, the co-occurrence of divergent
mtDNA haplotypes (6 to 10 mutations;
Figure 1B and 1C)
in southern populations may be the consequence of further isolation
within refugia during colder climatic periods. Contemporary
fragmentation of lion populations could further explain the results of
nested-clade phylogeographical analysis (NCPA
[27]) (
Figure S5), which inferred restricted gene flow with isolation-by-distance between mtDNA haplotypes H9 (B
ot-II) and H10 (K
ru) (χ
2 = 10.00,
P = 0.0200), between haplotypes H1 (B
ot-II/N
am) and H2 (K
ru) (χ
2 = 71.00,
P≤0.0001), and between haplotypes H9–H10 (B
ot-II/K
ru) and haplotypes H11–H12 (B
ot-I/K
ru/S
er/N
gc/U
ga) (χ
2 = 187.83,
P≤0.0001).
Further
isolation within refugia (sub-refugia) may also have occurred in East
Africa. This is suggested by the distinctive mtDNA haplotype H4 and the
unique FIV
Ple subtype F found in the Kenya population, which
may have resulted from reduced gene flow across the Rift valley, a
scenario that has been suggested for several bovid and carnivore
populations (see
[28] and references therein).
The
best example of concordance between host genome markers and viral
transmission patterns is observed in the Serengeti National Park in
Tanzania. Our previous findings described markedly high levels of FIV
Ple
subtype A, B and C circulating within the Serengeti lion population to
such an extent that 43% of the lions sampled were multiply-infected with
two or three subtypes
[15],
[18]
and were hypothesized to represent recent admixture of three formerly
separated populations. Such result is confirmed here by lion genomic
markers (
Figure 2). Further, although lions within the Serengeti can be assigned to one of three populations (S
er-I, S
er-II or S
er-III) by host genomic markers, FIV
Ple
subtypes are distributed ubiquitously in all three, characteristic of
rapid horizontal retroviral transmission subsequent to host population
admixture. The possible isolating mechanism remains to be elucidated as
there is no apparent barrier to gene flow in this ecosystem.
Genomic Signatures Left by Migration
Based on patterns of genetic diversity and phylogenetic analysis of lion nDNA/mtDNA and FIV
Ple
markers, we propose a scenario of a period of refugia/isolation in the
Late Pleistocene followed by two major lion expansions across Africa and
Asia. The first expansion, supported by the mtDNA NCPA
[27] (χ
2 = 690.00,
P≤0.0001;
Figure S5), was a long-distance colonization of mtDNA lineage-III (G
ir/A
tl/A
ng/Z
bw)
around 118,000 years ago (95% CI: 28,000–208,000), with subsequent
fragmentation of haplotypes H5–H6 into Central and North Africa and
haplotypes H7–H8 into West Asia (M1-
Figure 1A). Support for this initial expansion is also found in nDNA. The
ADA haplotype A5 fixed in G
ir in also present in K
en, S
er-II, and S
er-III, suggesting that lions likely colonized West Asia from the East Africa refugia (
Figure 1B). Such an expansion may have been favored by the start of a warmer and less arid period in Africa 130,000–70,000 years ago
[29].
This “out-of-Africa event” would have occurred much later than the
initial lion expansion through Eurasia based on fossils (~500,000 years
ago)
[3]. It is likely that multiple lion expansions occurred in the Pleistocene, as occurred with humans
[21].
A
second, more recent lion expansion probably occurred at the
Pleistocene/Holocene transition, this one from Southern Africa toward
East Africa (M2-
Figure 1A,
Figure 3).
This is reflected in the mtDNA linage IV, where haplotypes present in
Southern lions are basal (older) to those found in the East. Overall,
mtDNA population nucleotide diversity decreases from Southern to East
Africa (
Figure 1B and 1C), a finding supported by pairwise mismatch analysis
[30] (raggedness,
r = 0.086;
P<0.001). The fixation of mtDNA haplotype H11 in B
ot-I
(otherwise fixed only in East Africa populations) suggests that the
colonizing lions expanded northwards from the Kalahari Desert, which
included bush, woodland and savannah habitats during the climatic
fluctuations of the Pleistocene
[31]. This expansion would have occurred relatively recently as the single rare tip mtDNA haplotype H12, found only in S
er-I, is derived from the interior widespread haplotype H11 (~14,000–7,000 years; given one mtDNA substitution every 7,000 years;
Table 1). This expansion is also supported by FIV
Ple subtype A where haplotypes present in Southern lions (K
ru and B
ot-I) are basal to those found in the East (S
er-I, S
er-II and S
er-III) and a decrease of nucleotide-diversity of this FIV
Ple subtype is observed from Southern (π = 0.15) to Eastern Africa (π = 0.03) (
Figure 3B).
Interestingly, a similar northward colonization process from Southern
Africa has been suggested for some of the lion preys, namely the impala,
greater kudu, and wildebeest
[32],
[33].
Utility of Population Genomic Datasets
If
we had restricted our inferences to mtDNA, we might have concluded that
East African lion populations, which are fixed or nearly fixed for
haplotype H11, went extinct during the Pleistocene/Holocene transition
(similar to the well known mega-fauna extinctions of the Late
Pleistocene
[34])
and were then colonized by Southern populations. However, our
population genomics data better fit a scenario of lion population
expansion and interbreeding rather than simple replacement. First,
genetic diversity and allelic richness at nDNA are slightly higher in
East Africa populations relatively to those in Southern Africa. This is
contrary to the expected pattern of population expansion in which there
is usually a progressive decline in genetic diversity and allelic
richness. Second, S
er lions carry two diverse FIV
Ple subtypes found only in East Africa (B–C), and not only FIV
Ple
subtype A, which was presumably introduced in East Africa coincidently
with the mtDNA expansion event northwards from South. Third, the East
African FIV
Ple subtype B found in U
ga/S
er-I/S
er-II/S
er-III/N
gc showed evidence of a population expansion (raggedness,
r = 0.004;
P<0.01;
Fs = −20.37;
P<0.00001) and the highest nucleotide diversity observed within FIV
Ple subtypes (π = 0.09). Four, the FIV
Ple subtype diversity is higher in East African clades (four out of the six viral strains).
The utility of FIV
Ple pol-RT
as a marker of lion population structure and natural history is that it
can be informative on a contemporaneous time scale, though it may be
less useful at capturing more ancient demographic events. The extreme
divergence among FIV
Ple subtypes, considered with high
sero-prevalence in eight of the 11 lion populations, and combined with
patterns of geographic concordance, support the hypothesis that FIV
Ple is not a recent emergence within modern lions
[35]. Populations that harbor one private FIV
Ple subtype such K
en (subtype F), B
ot-II (subtype E), and K
ru
(subtype D) must have been sufficiently isolated for enough time for
the virus to evolve into unique subtypes, a result corroborated by the
high nDNA and mtDNA genetic structure present in these lion populations (
Figure 4). Thus, it is possible that the initial emergence of FIV
Ple pre-dates the Late-Pleistocene expansions of contemporary lion populations
[36],
but present day distributions are more useful indicators of very recent
host population dynamics, a result also observed with FIV
Pco in a panmictic population of pumas in western North America
[19].
Conservation Implications
Accurate
interpretation of past and contemporary population demographic
scenarios is a primary goal for the effective conservation of endangered
species. In this study, we found substantial population subdivision,
reduced gene flow, and large differences in FIV
Ple sequence and sero-prevalence among lion populations, as well as evidence of historic secondary contact between populations (
Figure 3C;
Table S4 to
S9). The very low population level of mtDNA nucleotide diversity, the number of haplotypes private to a single population (
Figure 1), and probably also the lack of
SRY genetic variation across all male lions (haplotype S1,
n
= 183) suggests that lion numbers diminished considerably following the
Late Pleistocene. The last century reduction in lion distribution
further eroded its genomic diversity, and microsatellite variation
suggested recent population bottlenecks in seven out of the 11
populations (standardized differences test,
P<0.05;
Table S5)
[37].
Although
we did not explicitly try to address the adequacy of lion subspecies
designations (currently only one African subspecies is widely
recognized)
[38],
[39],
we provided strong evidence that there is no evidence of substantial
genetic exchange of matrilines among existing populations as the AMOVA
[40] within-population component was uniformly high in all distinct subdivision scenarios (Φ
ST≈0.920;
P<0.0001; three-six groups;
Table S6). Similarly, significant population structure was detected from nDNA (
FST = 0.18), with low levels of admixture evident from Bayesian analysis
[22]
(α = 0.033). Therefore, employing a bottom-up perspective that
prioritizes populations, rather than large-scale units (e.g. all African
lions), might preserve and maintain lion diversity and evolutionary
processes most efficiently
[41].
Material and Methods
Study Site, Sampling, and Molecular Genetic Analyses of Lions
A total of 357 individuals were obtained across most of the lion range in Africa and Asia (
Figure 1A;
Table S1). Genetic variation among lion specimens was assessed using maternal (
12S and
16S genes), paternal (
SRY gene) and bi-parental autosomal (22 microsatelite loci, and the
ADA and
TF genes) markers (GenBank accession numbers: FJ151632–FJ151652). Analyses of mtDNA in
Panthera species are complicated by the presence of a 12.5 kb mtDNA integration into chromosome F2
[42]. Accordingly, mtDNA specific primers were designed for the
12S and
16S genes (
Table S2) and we used long-range PCR amplification. We designed primers to amplify segments of the
ADA (exon 10 and intron 10) and the
TF (intron 3) genes (
Table S2), two of the most variable protein loci in lion populations
[5], localized on the domestic cat
Felis catus chromosome A3p and C2q, respectively. The Y-chromosome
SRY-3′UTR gene was also amplified
[43].
PCR products were amplified from 50 ng of genomic DNA in a 25 µL reaction system containing 1.5 mM MgCl
2,
1.0 mM dNTPs, 0.25 units of AmpliTaq Gold DNA polymerase (Applied
Biosystems), and 1× PCR buffer II; the amplification protocol was:
denaturation 10 min at 95°C, a touch-down cycle of 95°C for 30 s, 52°C
for 60 s decreased by 1°C in the next cycle for 10 cycles, 72°C for 120
s, then 35 amplification cycles of 95°C for 30 s, 52°C for 60 s, and
72°C for 120 s, followed by an extension of 10 min at 72°C. PCR products
were sequenced on an ABI 377. Sequences were aligned and cleaned using
SEQUENCHER (Gene Codes).
Twenty
two polymorphic microsatellite loci (20 dinucleotide repeats: FCA006,
FCA008, FCA014, FCA069, FCA077, FCA085, FCA091, FCA098, FCA105, FCA126,
FCA129, FCA139, FCA205, FCA208, FCA211, FCA224, FCA229, FCA230, FCA247,
and FCA281; and two tetranucleotide repeats: FCA391 and FCA441) were
amplified
[44]. Microsatellites were scored in an ABI 377 and analyzed using G
enescan 2.1 and G
enotyper 2.5. These loci are located on 11 of the 19
F. catus chromosomes, occurring in different linkage groups or at least 12 centimorgans apart
[44],
[45].
Sero-Prevalence and Molecular Genetics of FIVPle
Western blots using domestic cat and lion FIV as antigen were performed as previously described
[46],
[47].
The supernatant from virus-infected cells was centrifuged at 200 g for
10 min at 5°C. The resultant supernatant was centrifuged at 150,000 g at
4°C for 2 hours. Pelleted viral proteins were resuspended in 1/20
th
of the original volume and total protein content was assayed using the
Biorad Protein Assay. Twenty mg of viral protein were run on 4–20%
Tris-Glycine gels and transferred to PDVF membranes (BioRad). Membrane
strips were exposed 2–12 h to a 1:25 or 1:200 dilution of serum or
plasma. After washing, samples were labeled with goat anti-cat HRP or
phosphate conjugated antibody (KPL laboratories) at a 1:2000 dilution,
washed, and incubated in ECL Western Blotting detection reagents
(Amersham Biosciences) for 2 min, then exposed to Lumi-Film
Chemiluminescent Detection Film (Boehringer Mannheim) or incubated in
BCIP/NBP phosphatase substrate (KPL laboratories) for 15 min
[46]–
[48]. Results were visualized and scored manually based on the presence and intensity of antibody binding to the
p24 gag capsid protein.
Nested PCR amplification of partial FIV
Ple pol-RT was performed
[18],
[46]. Briefly, first round PCR reactions used 100 ng of genomic DNA, 2.5 mM MgCl
2
and an annealing temperature of 52°C. Second round PCR reactions used
identical conditions with 1–5 µl of first-round product as template. All
PCR products were sequenced as described above for lion genetic
analyses (GenBank accession numbers: AY549217–AY552683;
AY878208–AY878235; FJ225347–FJ225382).
Statistical Analyses
We used the G
enetix 4.02
[49], G
enepop 3.3
[50], M
icrosat [51], and D
naSP 4.10
[52] to calculate the following descriptive statistics: (i) percentage of polymorphic loci (
P95), number of alleles per locus (
A), observed and expected heterozygosity (
HE and
HO), and number of unique alleles (
AU); (ii) assess deviations from HWE; (iii) estimate the coefficient of differentiation (
FST), and (iv) nucleotide (π) and haplotype (
h) diversity.
We tested the hypothesis that all loci are evolving under neutrality for both the lion and the FIV
Ple data. For frequency data, we used the method described by Beaumont and Nichols
[53] and implemented in F
dist (
http://www.rubic.rdg.ac.uk/~mab/software.html). The
FST
values estimated from microsatellite loci plotted against
heterozygosity showed that all values fall within the expected 95%
confidence limit and consequently no outlier locus were identified. For
sequence data (lion nDNA/mtDNA and FIV
Ple pol-RT), we ruled out any significant evidence for genetic hitchhiking and background selection by assessing Fu and Li's
D* and
F* tests
[54] and Fu's
FS statistics
[55].
A Bayesian clustering method implemented in the program S
tructure [22]
was used to infer number of populations and assign individual lions to
populations based on multilocus genotype (microsatellites) and sequence
data (
ADA,
TF, and mtDNA genes) and without
incorporating sample origin. For haploid mtDNA data, each observed
haplotype was coded with a unique integer (e.g. 100, 110) for the first
allele and missing data for the second (S
tructure [22] analyses with or without the mtDNA data were essentially identical). For
K population clusters, the program estimates the probability of the data, Pr(
X|K),
and the probability of individual membership in each cluster using a
Markov chain Monte Carlo method under the assumption of Hardy-Weinberg
equilibrium (HWE) within each cluster. Initial testing of the HWE in
each of the populations defined by the geographic origin of sampling
revealed no significant deviation from HW expectations with the
exception of S
er and B
ot population (later subdivided by S
tructure [22]
in 3 and 2 clusters, respectively; such deviations from HW expectations
were interpreted as evidence of further population structuring). We
conducted six independent runs with
K = 1–20 to guide an
empirical estimate of the number of identifiable populations, assuming
an admixture model with correlated allele frequencies and with burn-in
and replication values set at 30,000 and 10
6, respectively. S
tructure
also estimates allele frequencies of a hypothetical ancestral
population and an alpha value that measures admixed individuals in the
data set. The assignment of admixed individuals to populations using S
tructure [22] has been considered in subsequent population analyses. For each population cluster
k, the program estimates
Fk, a quantity analogous to Wright's
FST, but describing the degree of genetic differentiation of population
k from the ancestral population.
Patterns
of gene flow and divergence among populations were described using a
variety of tests. First, to visualize subtle relationships among
individual autosomal genotypes, three-dimensional factorial
correspondence analyses
[23] (FCA) were performed in G
enetix [49],
which graphically projects the individuals on the factor space defined
by the similarity of their allelic states. Second, neighbor-joining (NJ)
analyses implementing the Cavalli-Sforza & Edwards' chord genetic
distance
[56] (
DCE) were estimated in P
hylip 3.6
[57], and the tree topology support was assessed by 100 bootstraps. Third, the difference in average
HO and
A was compared among population groups using a two-sided test in F
stat 2.9.3.2
[58], which allows to assess the significance of the statistic OS
x using 1,000 randomizations. Four, the equilibrium between drift and gene flow was tested using a regression of pairwise
FST on geographic distance matrix among all populations for host nDNA(microsatellites)/mtDNA and FIV
Ple data. A Mantel test
[59]
was used to estimate the 95% upper probability for each matrix
correlation. Assuming a stepping stone model of migration where gene
flow is more likely between adjacent populations, one can reject the
null hypothesis that populations in a region are at equilibrium if (1)
there is a non-significant association between genetic and geographic
distances, and/or (2) a scatterplot of the genetic and geographic
distances fails to reveal a positive and monotonic relationship over all
distance values of a region
[60]. We also evaluated linearized
FST [i.e.
FST/(1−
FST)]
[24]
among populations. We tested two competing models of
isolation-by-distance, one assuming the habitat to be arrayed in an
infinite one-dimensional lattice and another assuming an infinite
two-dimensional lattice. Both models showed that genetic differentiation
increased with raw and log-transformed Euclidean distances,
respectively
[24].
We determined the confidence interval value of the slope of the
regression for the nDNA data using a non parametric ABC bootstrap
[61] in G
enepop 4.0
[62].
The
demographic history of populations was compared using a variety of
estimators based on the coalescence theory. First, signatures of old
demographic population expansion were investigated for mtDNA and FIV
Ple pol-RT haplotypes using pairwise mismatch distributions
[63] in D
naSP
[52]. The goodness-of-fit of the observed data to a simulated model of expansion was tested with the raggedness (
r) index
[64].
Second, the occurrence of recent bottlenecks was evaluated for microsatellite data using the method of Cornuet & Luikart
[37] in B
ottleneck [65]
and using 10,000 iterations. This approach, which exploits the fact
that rare alleles are generally lost first through genetic drift after
reduction in population size, employs the standardize differences test,
which is the most appropriate and powerful when using 20 or more
polymorphic loci
[37].
Tests were carried out using the stepwise mutation model (SMM), which
is a conservative mutation model for the detection of bottleneck
signatures with microsatellites
[66].
Third, to discriminate between recurrent gene flow and historical events we used the nested-clade phylogeographical analysis
[27],
[67]
(NCPA) for the mtDNA data. When the null-hypothesis of no correlation
between genealogy and geography is rejected, biological inferences are
drawn using a priori criteria. The NCPA started with the estimation of a
95% statistical parsimony
[68] mtDNA network in T
cs 1.20
[69]. Tree ambiguities were further resolved using a coalescence criteria
[70]. The network was converted into a series of nested branches (clades)
[71],
[72], which were then tested against their geographical locations through a permutational contingency analysis in G
eoD
is 2.2
[73]. The inferences obtained were also corroborated with the automated implementation of the NCPA in AN
eCA
[74]. To address potential weaknesses in some aspects of the NCPA analysis
[75],
[76],
we further validated the NCPA inferences with independent methods for
detecting restricted gene-flow/isolation-by-distance (using matrix
correlation of pairwise
FST and geographic distance) and population expansion (using pairwise mismatch distributions).
Four, to test the significance of the total mtDNA genetic variance, we conducted hierarchical analyses of molecular variance
[40] (AMOVA) using A
rlequin 2.0
[77].
Total genetic variation was partitioned to compare the amount of
difference among population groups, among populations within each
groups, and within populations.
Phylogenetic relationships among mtDNA and FIV
Ple pol-RT
sequences were assessed using Minimum evolution (ME), Maximum parsimony
(MP), and Maximum likelihood (ML) approaches implemented in P
aup [78].
The ME analysis for mtDNA consisted of NJ trees constructed from Kimura
two-parameter distances followed by a branch-swapping procedure and for
FIV
Ple data employed the same parameter estimates as were
used in the ML analysis. The MP analysis was conducted using a heuristic
search, with random additions of taxa and tree-bisection-reconnection
branch swapping. The ML analysis was done after selecting the best
evolutionary model fitting the data using M
odeltest 3.7
[79]. Tree topologies reliability was assessed by 100 bootstraps. For the FIV
Ple data, the reliability of the tree topology was further assessed through additional analyses using 520 bp of FIV
Ple pol-RT sequences in a representative subset of individuals.
The time to the most recent common ancestor (TMRCA) for the
ADA and
TF haplotypes was estimated following Takahata et al.
[80],
where we calculate the ratio of the average nucleotide differences
within the lion sample to one-half the average nucleotide difference
between leopards (
P. pardus) and lions and multiplying the
ratio by an estimate of the divergence time between lions and leopards
(2 million years based on undisputed lion fossils in Africa)
[81],
[82]. The mtDNA TMRCA was estimated with a linearized tree method in L
intree [83]
and using the equation H = 2μT, where H was the branch height
(correlated to the average pairwise distance among haplotypes), μ the
substitution rate, and T the divergence time. Leopard and snow leopard (
P. uncia) sequences were used as outgroups. Inference of the TMRCA for microsatellite loci followed Driscoll et al.
[6]
where the estimate of microsatellite variance in average allele
repeat-size was used as a surrogate for evolutionary time based on the
rate of allele range reconstitution subsequent to a severe founder
effect. Microsatellite allele variance has been shown to be a reliable
estimator for microsatellite evolution and demographic inference in
felid species
[6].
Supporting Information
Figure_S1.pdf
Genetic variation of 12S–16S (mtDNA) and ADA and TF (nDNA) genes in lions. (A) Haplotypes and variable sites for the 12S–16S mtDNA region surveyed in lions (total length 1,882 bp). Position 1 corresponds to position 1441 of the domestic cat (Felis catus)
mtDNA genome (GenBank U20753). The “-” represents a gap and “.” matches
the nucleotide in the first sequence. Shading indicates a fixed
difference in the mtDNA lineage. (B) Haplotypes and variable sites for
the ADA gene segment surveyed in lions (total length 427 bp). (C) Haplotypes and variable sites for the TF gene segment surveyed in lions (total length 427 bp).
Genetic variation of 12S–16S (mtDNA) and ADA and TF (nDNA) genes in lions. (A) Haplotypes and variable sites for the 12S–16S mtDNA region surveyed in lions (total length 1,882 bp). Position 1 corresponds to position 1441 of the domestic cat (Felis catus)
mtDNA genome (GenBank U20753). The “-” represents a gap and “.” matches
the nucleotide in the first sequence. Shading indicates a fixed
difference in the mtDNA lineage. (B) Haplotypes and variable sites for
the ADA gene segment surveyed in lions (total length 427 bp). (C) Haplotypes and variable sites for the TF gene segment surveyed in lions (total length 427 bp).
doi:10.1371/journal.pgen.1000251.s001
(0.12 MB PDF)
Linearized genetic differentiation of host and viral genetic markers with geographic distance. Regression of linearized
FST estimates
[24] for lion (nDNA and mtDNA) and FIV
Ple (
pol-RT)
genetic data plotted both against the geographic distance (model
assuming habitat to be arrayed in an infinite one-dimensional lattice;
one-dimension isolation-by-distance [IBD]) and the log geographic
distance (model assuming an infinite two-dimensional lattice;
two-dimension isolation-by-distance) on geographic distance.
doi:10.1371/journal.pgen.1000251.s002
(0.13 MB PDF)
Phylogenetic relationships of the 12S–16S mtDNA lion haplotypes. Neighbour-joining tree of the 1,882 bp 12S–16S
mtDNA sequences. Bootstrap values are placed at each branchpoint for
the minimum evolution/maximum parsimony/maximum likelihood analyses,
respectively (ME/MP/ML). Outgroups: Ppa – leopard, Panthera pardus; Pun – snow-leopard, Panthera uncia.
The symbol (•) represents nodes with bootstrap support <50 or an
inferred polytomy in the bootstrap 50% majority-rule consensus tree.
doi:10.1371/journal.pgen.1000251.s003
(0.10 MB PDF)
Phylogenetic relationships of the FIVPle pol-RT sequences. Neighbour-joining tree of the 301 bp FIVPle pol-RT sequences. The distinct FIVPle
subtypes were labelled A to F. Bootstrap (BPS) values are placed at
each branchpoint (ME/MP/ML) and in parenthesis are the BPS values
obtained for a tree established with 520 bp of FIVPle pol-RT sequence for a representative subset of individuals.
doi:10.1371/journal.pgen.1000251.s004
(0.13 MB PDF)
Nested
design and summary results of the nested clade phylogeographic analysis
(NCPA) for lion mtDNA data. (A) Nested design of the mtDNA haplotype
network used for the NCPA. (B) Summary results of the NCPA. RGF/IBD -
Restricted gene flow/isolation by distance. LDC/FR – long distance
colonization/fragmentation.
doi:10.1371/journal.pgen.1000251.s005
(0.10 MB PDF)
List of the lion samples used in this study.
doi:10.1371/journal.pgen.1000251.s006
(0.11 MB PDF)
Primers used to amplify the mtDNA (12S–16S) and nDNA (ADA and TF) portions surveyed in this study.
doi:10.1371/journal.pgen.1000251.s007
(0.06 MB PDF)
Structure
cluster assignment results of 357 lions based on nDNA (ADA, TF, and 22
microsatellites) and mtDNA markers. Burn-in and replication values set
at 30,000 and 1,000,000, respectively.
doi:10.1371/journal.pgen.1000251.s008
(0.06 MB PDF)
Gene diversity and frequency values in lion populations.
doi:10.1371/journal.pgen.1000251.s009
(0.07 MB PDF)
Bottleneck analysis in lion populations using the standardized differences test and the stepwise mutation model (SMM).
doi:10.1371/journal.pgen.1000251.s010
(0.05 MB PDF)
Results of the hierarchical AMOVA in lions for four different geographical scenarios.
doi:10.1371/journal.pgen.1000251.s011
(0.06 MB PDF)
Lion population pairwise FST estimates. Below the diagonal mtDNA data (12S–16S) and above the diagonal microsatellite data (22 loci).
doi:10.1371/journal.pgen.1000251.s012
(0.06 MB PDF)
Taxon specific unique nDNA alleles in lion populations (FCA-microsatellites and ADA locus).
doi:10.1371/journal.pgen.1000251.s013
(0.06 MB PDF)
Summary statistics for FIVPle data.
doi:10.1371/journal.pgen.1000251.s014
(0.00 MB PDF)
Acknowledgments
Tissues
were obtained in full compliance with specific Federal Fish and
Wildlife Permits. The content of this publication does not necessarily
reflect the views or policies of the Department of Health and Human
Services, nor does mention of trade names, commercial products, or
organizations imply endorsement by the U.S. Government. We would like to
thank A. Beja-Pereira, M. Branco and J. Martenson for suggestions and
technical assistance. Comments made by the Associate Editor A. Estoup
and three anonymous referees improved a previous version of this
manuscript.
Author Contributions
Conceived
and designed the experiments: AA JLT SJO WEJ. Performed the
experiments: AA JLT MER WEJ. Analyzed the data: AA JLT MER SJO WEJ.
Contributed reagents/materials/analysis tools: AA JLT MER JPS CP CW HW
GH LF PS LS MD PJF KAA KCP GM DW MB SJO WEJ. Wrote the paper: AA JLT JPS
CP SJO WEJ.
References
- 1.
Werdelin
L, Lewis ME (2005) Plio-Pleistocene Carnivora of eastern Africa:
species richness and turnover patterns. Zool J Linn Soc 144: 121–144.
doi:
10.1038/sj.hdy.6800110.
Find this article online
- 2.
Petter
G (1973) Carnivores Pléistocènes du Ravin d'Olduvai (Tanzanie). In:
Leakey LSB, Savage RJG, Coryndon SC, , editors. Fossil vertebrates of
Africa. 3. London: Academic Press. pp. 43–100.
- 3.
Hemmer H (1974) Untersuchungen zur Stammesgeschichte der Pantherkatzen (Pantherinae) Teil 3. Zur Artgeschichte de Löwen Panthera (Panthera) leo (Linnaeus, 1758). Veröffentlichungen der Zoologischen Staatssammlung 17: 167–280.
Find this article online
- 4.
Bauer H, Nowell K (2006) Panthera leo. IUCN 2006. 2006 IUCN Red List of Threatened Species (http://www.iucnredlist.org/search/details.php/15951/all).
- 5.
O'Brien
SJ, Martenson JS, Packer C, Herbst L, De Vos V, Joslin P, Ott-Joslin J,
Wildt DE, Bush M (1987) Biochemical genetic variation in geographic
isolates of African and Asiatic lions. National Geographic Research 3:
114–124.
Find this article online
- 6.
Driscoll
CA, Menotti-Raymond M, Nelson G, Goldstein D, O'Brien SJ (2002) Genomic
microsatellites as evolutionary chronometers: a test in wild cats.
Genome Res 12: 414–423.
Find this article online
- 7.
Burger J, Rosendahl W, Loreille O, Hemmer H, Eriksson T, et al. (2004) Molecular phylogeny of the extinct cave lion Panthera leo spelaea. Mol Phylogenet Evol 30: 841–849.
doi:
10.1111/j.1365-294X.2006.03046.x.
Find this article online
- 8.
Dubach
J, Patterson B, Briggs M, Venzke K, Flamand J, et al. (2005) Molecular
genetic variation across the southern and eastern geographic ranges of
the African lion, Panthera leo. Cons Genet 6: 15–24.
doi:
10.1046/j.1365-294x.2001.01205.x.
Find this article online
- 9.
Barnett R, Yamaguchi N, Barnes I, Cooper A (2006) Lost populations and preserving genetic diversity in the lion Panthera leo: implications for its ex situ conservation. Cons Genet 7: 507–514.
doi:
10.1093/bioinformatics/14.9.817.
Find this article online
- 10.
Luo
SJ, Kim JH, Johnson WE, van der Walt J, Martenson J, et al. (2004)
Phylogeography and genetic ancestry of tigers (Panthera tigris). PLoS
Biol 2(12): e442.
doi:
10.1101/gr.185702.
Find this article online
- 11.
Johnson
WE, Eizirik E, Pecon-Slattery J, Murphy WJ, Antunes A, et al. (2006)
The late Miocene radiation of modern Felidae: a genetic assessment.
Science 311: 73–77.
Find this article online
- 12.
Packer
C, Gilbert DA, Pusey AE, O'Brien SJ (1991) A molecular genetic analysis
of kinship and cooperation in Africa lions. Nature 351: 562–565.
Find this article online
- 13.
Packer
C, Hilborn R, Mosser A, Kissui B, Borner M, et al. (2005) Ecological
change, group territoriality, and population dynamics in Serengeti
lions. Science 307: 390–393.
doi:
10.1007/s10592-004-7729-6.
Find this article online
- 14.
Spong G, Stone J, Creel S, Björklund M (2002) Genetic structure of lions (Panthera leo L.) in the Selous Game Reserve: implications for the evolution of sociality. J Evol Biol 15: 945–953.
doi:
10.1159/000115429.
Find this article online
- 15.
Brown
EW, Yuhki N, Packer C, O'Brien SJ (1994) A lion lentivirus related to
feline immunodeficiency virus: epidemiologic and phylogenetic aspects. J
Virol 68: 5953–5968.
Find this article online
- 16.
Roelke-Parker
ME, Munson L, Packer C, Kock R, Cleaveland S, et al. (1996) A canine
distemper virus epidemic in Serengeti lions (Panthera leo). Nature 379: 441–445.
Find this article online
- 17.
Packer
C, Altizer S, Appel M, Brown E, Martenson J, et al. (1999) Viruses of
the Serengeti: patterns of infection and mortality in African lions. J
Anim Ecol 68: 1161–1178.
Find this article online
- 18.
Troyer
JL, Pecon-Slattery J, Roelke ME, Black L, Packer C, et al. (2004)
Patterns of feline immunodeficiency virus multiple infection and genome
divergence in a free-ranging population of African lions. J Virol 78:
3777–3791.
doi:
10.1046/j.1365-294x.2000.00887.x.
Find this article online
- 19.
Biek
R, Drummond AJ, Poss M (2006) A virus reveals population structure and
recent demographic history of its carnivore host. Science 311: 538–541.
doi:
10.1006/geno.1999.5743.
Find this article online
- 20.
Falush D, Wirth T, Linz B, Pritchard JK, Stephens M, et al. (2003) Traces of human migrations in Helicobacter pylori populations. Science 299: 1582–1585.
Find this article online
- 21.
Templeton AR (2002) Out of Africa again and again. Nature 416: 45–51.
doi:
10.1128/JVI.79.13.8282-8294.2005.
Find this article online
- 22.
Pritchard
JK, Stephens M, Donnelly P (2000) Inference of population structure
using multilocus genotype data. Genetics 155: 945–959.
doi:
10.1126/science.1122277.
Find this article online
- 23.
Benzécri JP (1982) L'analyse des données, vol II. L' analyse des correspondances. Paris: Dunod.
- 24.
Rousset
F (1997) Genetic differentiation and estimation of gene flow from
F-statistics under isolation by distance. Genetics 145: 1219–1228.
doi:
10.1371/journal.pbio.0020442.
Find this article online
- 25.
Whitehead H (1998) Cultural selection and genetic diversity in matrilineal whales. Science 282: 1708–1711.
doi:
10.1016/0031-0182(93)90016-C.
Find this article online
- 26.
Nyakaana
S, Arctander P, Siegismund HR (2002) Population structure of the
African savannah elephant inferred from mitochondrial control region
sequences and nuclear microsatellite loci. Heredity 89: 90–98.
doi:
10.1093/oxfordjournals.molbev.a026085.
Find this article online
- 27.
Templeton
AR, Routman E, Phillips CA (1995) Separating population structure from
population history: a cladistic analysis of the geographical
distribution of mitochondrial DNA haplotypes in the tiger salamander, Ambystoma tigrinum. Genetics 140: 767–782.
Find this article online
- 28.
Pitra
C, Hansen AJ, Lieckfeldt D, Arctander P (2002) An exceptional case of
historical outbreeding in African sable antelope populations. Mol Ecol
11: 1197–208.
doi:
10.1093/jhered/esg008.
Find this article online
- 29.
van
Andel TH, Tzedakis PC (1996) Palaeolithic landscapes of Europe and
environs, 150,000–25,000 years ago: an overview. Quat Sci Rev 15:
481–500.
doi:
10.1006/viro.1997.8587.
Find this article online
- 30.
Rogers
AR, Harpending H (1992) Population growth makes waves in the
distribution of pairwise genetic differences. Mol Biol Evol 9: 552–569.
Find this article online
- 31.
Partridge
T (1993) Warming phases in Southern Africa during the last 150,000
years; an overview. Palaeogeography, Palaeoclimatology, Palaeoecology
101: 237–244.
doi:
10.1038/416045a.
Find this article online
- 32.
Arctander
P, Johansen C, Coutellec-Vreto MA (1999) Phylogeography of three
closely related African bovids (tribe Alcelaphini). Mol Biol Evol 16:
1724–39.
Find this article online
- 33.
Nersting LG, Arctander P (2001) Phylogeography and conservation of impala and greater kudu. Mol Ecol 10: 711–719.
Find this article online
- 34.
Barnosky
AD, Koch PL, Feranec RS, Wing SL, Shabel AB (2004) Assessing the causes
of late Pleistocene extinctions on the continents. Science 306: 70–75.
doi:
10.1093/jhered/90.4.502.
Find this article online
- 35.
Carpenter
MA, Brown EW, Culver M, Johnson WE, Pecon-Slattery J, et al. (1996)
Genetic and phylogenetic divergence of feline immunodeficiency virus in
the puma (Puma concolor). J Virol 70: 6682–6693.
doi:
10.1046/j.1365-294X.2002.01516.x.
Find this article online
- 36.
Pecon-Slattery
J, Troyer JL, Johnson WE, O'Brien SJ (2008) Evolution of Feline
Immunodeficiency Virus in Felidae: Implications For Human Health And
Wildlife Ecology. Vet Immunol Immunopathol 123: 32–44.
doi:
10.1093/molbev/msg034.
Find this article online
- 37.
Cornuet
JM, Luikart G (1996) Description and power analysis of two tests for
detecting recent population bottlenecks from allele frequency data.
Genetics 144: 2001–2014.
Find this article online
- 38.
Neff N (1983) The Big Cats: the Paintings of Guy Cheleach. New York: Abrams.
- 39.
Nowak RM, Paradiso JL (1983) Walker's Mammals of the World, 4th ed. Baltimore: Johns Hopkins University Press.
- 40.
Excoffier
L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred
from metric distances among DNA haplotypes: application to human
mitochondrial DNA restriction data. Genetics 131: 479–491.
doi:
10.1046/j.1365-294x.1998.00308.x.
Find this article online
- 41.
Antunes
A, Faria R, Weiss S, Alexandrino P (2001) Complex evolutionary history
in the brown trout: insights on the recognition of conservation units.
Cons Genet 2: 337–347.
Find this article online
- 42.
Kim JH, Antunes A, Luo SJ, Menninger J, Nash WG, et al. (2006) Evolutionary analysis of a large mtDNA translocation (numt) into the nuclear genome of the Panthera genus species. Gene 366: 292–302.
Find this article online
- 43.
King
V, Goodfellow PN, Pearks Wilkerson AJ, Johnson WE, O'Brien SJ, et al.
(2007) Evolution of the male determining gene SRY within the cat family
Felidae. Genetics 175: 1855–1867.
Find this article online
- 44.
Menotti-Raymond
M, David VA, Lyons LA, Schaffer AA, Tomlin JF, et al. (1999) A genetic
linkage map of microsatellites in the domestic cat (Felis catus). Genomics 57: 9–23.
Find this article online
- 45.
Menotti-Raymond
M, David VA, Roelke ME, Chen ZQ, Menotti KA, et al. (2003)
Second-generation integrated genetic linkage/radiation hybrid maps of
the domestic cat (Felis catus). J Hered 94: 95–106.
doi:
10.1046/j.1420-9101.2002.00473.x.
Find this article online
- 46.
Troyer
JL, Pecon-Slattery J, Roelke ME, Johnson W, VandeWoude S, et al.
(2005) Seroprevalence and genomic divergence of circulating strains of
feline immunodeficiency virus among Felidae and Hyaenidae species. J
Virol 79: 8282–8294.
doi:
10.1046/j.1365-294X.2002.01637.x.
Find this article online
- 47.
VandeWoude
S, O'Brien SJ, Langelier K, Hardy WD, Pecon-Slattery J, et al. (1997)
Growth of lion and puma lentiviruses in domestic cat cells and
comparisons with FIV. Virology 233: 185–192.
doi:
10.1111/j.1096-3642.2005.00165.x.
Find this article online
- 48.
Brown
EW, Miththapala S, O'Brien SJ (1993) Prevalence of exposure to feline
immunodeficiency virus is exotic felid species. J Zool Wildl Med 20:
265–272.
doi:
10.1007/s10592-005-9062-0.
Find this article online
- 49.
Belkir
K, Borsa P, Goudet J, Chikhi L, Bonhomme F (1999) Genetix, logiciel
sous Windows TM pour la génétique des populations. Montpellier (France):
Laboratoire Génome et Populations, CNRS UPR 9060, Université de
Montpellier II.
- 50.
Raymond M, Rousset F (1995) Population genetics software for exact tests and ecumenicism. J Hered 86: 248–249.
Find this article online
- 51.
Minch
E, Ruiz-Linares A, Goldstein D, Feldman M, Cavalli-Sforza LL (1995)
MICROSAT Version 1.4d: a computer program for calculating various
statistics on microsatellite allele data
Find this article online
- 52.
Rozas
J, Sanchez-DelBarrio JC, Messeguer X, Rozas R (2003) DnaSP, DNA
polymorphism analyses by the coalescent and other methods.
Bioinformatics 19: 2496–2497.
doi:
10.1126/science.1105122.
Find this article online
- 53.
Beaumont
MA, Nichols RA (1996) Evaluating loci for use in the genetic analysis
of population structure. Proc R Soc Lond B 263: 1619–1626.
doi:
10.1016/j.gene.2005.08.023.
Find this article online
- 54.
Fu Y-X, Li W-H (1993) Statistical tests of neutrality of mutations. Genetics 133: 693–709.
Find this article online
- 55.
Fu
Y-X (1997) Statistical tests of neutrality against population growth,
hitchhiking and background selection. Genetics 147: 915–925.
doi:
10.1111/j.1558-5646.2007.00124.x.
Find this article online
- 56.
Cavalli-Sforza LL, Edwards AWF (1967) Phylogenetic analysis: models and estimation procedures. Evolution 32: 550–570.
doi:
10.1126/science.282.5394.1708.
Find this article online
- 57.
Felsenstein
J (1993) PHYLIP (Phylogeny inference package). Version 3.5c. Seattle:
Distributed by the author, Department of Genetics, University of
Washington.
- 58.
Goudet J (1995) FSTAT. Vers. 1.2. A computer program to calculate F-statistics. J Hered 86: 485–486.
doi:
10.1093/bioinformatics/btl614.
Find this article online
- 59.
Mantel N (1967) The detection of disease clustering and a generalized regression approach. Cancer Res 27: 209–220.
Find this article online
- 60.
Hutchison
DW, Templeton AR (1999) Correlation of pairwise genetic and geographic
distance measures: inferring the relative influences of gene flow and
drift on the distribution of genetic variability. Evolution 53:
1898–1914.
doi:
10.1016/j.ympev.2003.07.020.
Find this article online
- 61.
Leblois
R, Estoup A, Rousset F (2003) Influence of mutational and sampling
factors on the estimation of demographic parameters in a “continuous”
population under isolation by distance. Mol Biol Evol 20: 491–502.
doi:
10.2307/2406616.
Find this article online
- 62.
Rousset
F (2008) Genepop'007: a complete re-implementation of the Genepop
software for Windows and Linux. Mol Ecol Res 8: 103–106.
Find this article online
- 63.
Rogers
AR, Harpending H (1992) Population growth makes waves in the
distribution of pairwise genetic differences. Mol Biol Evol 9: 552–569.
Find this article online
- 64.
Harpending
HC (1994) Signature of ancient population growth in a low-resolution
mitochondrial DNA mismatch distribution. Hum Biol 66: 591–600.
doi:
10.1534/genetics.106.066779.
Find this article online
- 65.
Piry
S, Luikart G, Cornuet JM (1999) BOTTLENECK: a computer program for
detecting recent effective population size reductions from allele
frequency data. J Hered 90: 502–503.
doi:
10.1126/science.1121360.
Find this article online
- 66.
Leblois
R, Estoup A, Streiff R (2006) Genetics of recent habitat contraction
and reduction in population size: does isolation by distance matter? Mol
Ecol 15: 3601–3615.
doi:
10.1111/j.1471-8286.2007.01931.x.
Find this article online
- 67.
Templeton
AR (1998) Nested clade analysis of phylogeographic data: Testing
hypotheses about gene flow and population history. Mol Ecol 7: 381–397.
Find this article online
- 68.
Templeton
AR, Crandall KA, Sing CF (1992) A cladistic analysis of phenotypic
associations with haplotypes inferred from restriction endonuclease
mapping and DNA sequence data. III. Cladogram estimation. Genetics 132:
619–633.
doi:
10.1038/351562a0.
Find this article online
- 69.
Clement M, Posada D, Crandall KA (2000) TCS: a computer program to estimate gene genealogies. Mol Ecol 9: 1657–1660.
doi:
10.1016/j.vetimm.2008.01.010.
Find this article online
- 70.
Crandall
KA, Templeton AR (1993) Empirical tests of some predictions from
coalescent theory with applications to intraspecific phylogeny
reconstruction. Genetics 134: 959–969.
Find this article online
- 71.
Templeton
AR, Boerwinkle E, Sing CF (1987) A cladistic analysis of phenotypic
associations with haplotypes inferred from restriction endonuclease
mapping. I. Basic theory and an analysis of alcohol dehydrogenase
activity in Drosophila. Genetics 117: 343–351.
doi:
10.1016/0277-3791(96)00028-5.
Find this article online
- 72.
Templeton
AR, Sing CF (1993) A cladistic analysis of phenotypic associations with
haplotypes inferred from restriction endonuclease mapping. IV. Nested
analyses with cladogram uncertainty and recombination. Genetics 134:
659–669.
doi:
10.1126/science.1080857.
Find this article online
- 73.
Posada
D, Crandall KA, Templeton AR (2000) GeoDis: a program for the cladistic
nested analysis of the geographical distribution of genetic haplotypes.
Mol Ecol 9: 487–488.
doi:
10.1038/381172a0.
Find this article online
- 74.
Panchal M (2007) The automation of Nested Clade Phylogeographic Analysis. Bioinformatics 23: 509–10.
Find this article online
- 75.
Knowles LL, Maddison WP (2002) Statistical phylogeography. Mol Ecol 11: 2623–2635.
Find this article online
- 76.
Panchal M, Beaumont MA (2007) The automation and evaluation of nested clade phylogeographic analysis. Evolution 61: 1466–1480.
doi:
10.2307/2640449.
Find this article online
- 77.
Schneider
S, Kueffer JM, Roesslie D, Excoffier L (1997) Arlequin Version 1.1.
Switzerland: Genetics and Biometry Laboratory, Dept. of Anthropology,
University of Geneva.
- 78.
Swofford
DL (2001) PAUP* Phylogenetic Analysis Using Parsimony and Other
Methods' Computer Program. Sunderland, , MA: Sinauer.
- 79.
Posada D, Crandall KA (1998) MODELTEST: Testing the model of DNA substitution. Bioinformatics 14: 817–818.
doi:
10.1046/j.1365-294x.2000.01020.x.
Find this article online
- 80.
Takahata N, Lee SH, Satta Y (2001) Testing multiregionality of modern human origins. Mol Biol Evol 18: 172–183.
Find this article online
- 81.
Petter
G (1973) Carnivores Pléistocènes du Ravin d'Olduvai (Tanzanie). In:
Leakey LSB, Savage RJG, Coryndon SC, , editors. Fossil vertebrates of
Africa. 3. London: Academic Press. pp. 43–100.
- 82.
Werdelin
L, Lewis ME (2005) Plio-Pleistocene Carnivora of eastern Africa:
species richness and turnover patterns. Zool J Linn Soc 144: 121–144.
Find this article online
- 83.
Takezaki
N, Rzhetsky A, Nei M (1995) Phylogenetic test of the molecular clock
and linearized trees. Mol Biol Evol 12: 823–833.
Find this article online
Source: http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1000251#s4
The apex court on Monday directed the Centre to shift the Asiatic lions from the Gir forest to Kuno sanctuary in Madhya Pradesh.
