Skip to main content
PMC home page
BMC Evolutionary Biology logoLink to BMC Evolutionary Biology
. 2011 Apr 10;11:92. doi: 10.1186/1471-2148-11-92

On the phylogeny of Mustelidae subfamilies: analysis of seventeen nuclear non-coding loci and mitochondrial complete genomes

Li Yu 1,✉,#, Dan Peng 1,#, Jiang Liu 1,#, Pengtao Luan 1, Lu Liang 2, Hang Lee 3, Muyeong Lee 3, Oliver A Ryder 4, Yaping Zhang 1,2,✉
PMCID: PMC3088541  PMID: 21477367

Abstract

Background

Mustelidae, as the largest and most-diverse family of order Carnivora, comprises eight subfamilies. Phylogenetic relationships among these Mustelidae subfamilies remain argumentative subjects in recent years. One of the main reasons is that the mustelids represent a typical example of rapid evolutionary radiation and recent speciation event. Prior investigation has been concentrated on the application of different mitochondrial (mt) sequence and nuclear protein-coding data, herein we employ 17 nuclear non-coding loci (>15 kb), in conjunction with mt complete genome data (>16 kb), to clarify these enigmatic problems.

Results

The combined nuclear intron and mt genome analyses both robustly support that Taxidiinae diverged first, followed by Melinae. Lutrinae and Mustelinae are grouped together in all analyses with strong supports. The position of Helictidinae, however, is enigmatic because the mt genome analysis places it to the clade uniting Lutrinae and Mustelinae, whereas the nuclear intron analysis favores a novel view supporting a closer relationship of Helictidinae to Martinae. This finding emphasizes a need to add more data and include more taxa to resolve this problem. In addition, the molecular dating provides insights into the time scale of the origin and diversification of the Mustelidae subfamilies. Finally, the phylogenetic performances and limits of nuclear introns and mt genes are discussed in the context of Mustelidae phylogeny.

Conclusion

Our study not only brings new perspectives on the previously obscured phylogenetic relationships among Mustelidae subfamilies, but also provides another example demonstrating the effectiveness of nuclear non-coding loci for reconstructing evolutionary histories in a group that has undergone rapid bursts of speciation.

Background

The Mustelidae is the largest and most-diverse family of Carnivora with a distribution throughout all continents except Australia and Antarctica [1,2]. Recent classifications of the Mustelidae recognize up to eight subfamilies: Mustelinae, Galictinae, Helictidinae, Martinae, Melinae, Lutrinae, Mellivorinae, and Taxidiinae [3-5]. Phylogenetic relationships among these subfamlies have been hotly disputed in pioneer studies [3-15] and are not well established yet. The main problem is that the family Mustelidae represents a typical example of rapid evolutionary radiation and recent speciation event [6,7], dating back to the Oligocene [16-18]. For this reason, attempts to clarify relationships among the eight Mustelidae subfamilies based on a variety of molecular studies have encountered challenges.

Previously, molecular studies of the phylogenetic reconstruction of subfamilies within the Mustelidae were based on short fragments of nuclear and mt DNA. Recently, some efforts have been made to obtain the phylogenetic tree based on large datasets, including those using 12 mt protein-coding genes [15], 5 nuclear genes [4,12], 4 nuclear genes and 1 mt gene [10,14], 21 nuclear genes and 1 mt gene [5] and 25 nuclear genes and mt genes [13]. Despite numerous efforts, however, evolutionary relationships among the Mustelidae subfamilies remain controversial (see Figure 1).

Figure 1.

Figure 1

Open in a new tab

Hypotheses of phylogenetic relationships among Mustelidae subfamilies. Trees were reconstructed based on (a) 46 morphological characters [8], (b) analyses of 21 nuclear genes and 1 mt gene [5], (c) analyses of 5 nuclear genes and 1 mt gene [10] (support values are indicated above the line) and 25 nuclear genes and mt genome [13] (support values are indicated below the line), (d) analyses of 5 nuclear genes [4] (support values are indicated above the line) [12] support values are indicated below the line), (e) supertree analyses of 5 nuclear genes [4].

Hence, it is necessary to exploit larger independent sources of phylogenetic characters to clarify these enigmatic problems. Several studies have shown that relative to the commonly used nuclear protein-coding and mt genes, the noncoding intron sequences can be an equally fruitful source of phylogenetic characters as they possess a number of traits that are desirable for molecular phylogenetics [19-24], for example, lack of functional constraints, a high substitution rate and less homoplasy [19,25,26]. In these studies, the nuclear introns have been shown to provide powerful complementary data to address the ambiguous relationships of different taxonomic levels, including the beaked whale species [23], the Asian pitvipers genus [19], the carnivoran families [24,27], and the eutherian orders [21].

In the present study, we aim to sequence 17 nuclear intron loci comprising a total of >15 kb from 17 mustelids. The mustelids examined here represent all subfamilies of Mustelidae, except for Mellivorinae and Galictinae. Of the 17 nuclear loci, 14 were first applied in the studies of Mustelidae phylogeny. In addition, we undertook the sequencing of the mt genome from these species and presented a phylogeny based on the mt genome data currently available for mustelids. Our objectives were to: (1) provide new insights into the relationships among the Mustelidae subfamilies, and (2) examine the utilities and evolutionary dynamics of the nuclear and mt genes in the context of Mustelidae phylogeny, with special attention to the previously unexplored nuclear intron genes.

Results

Characteristics of the Nuclear Intron Data and Mt Genomes

The general characteristics of the nuclear intron data and mt genomes are summarized in Table 1. The 17 nuclear introns of 21 species varied in length from 642 (Fgb-7) to 1685 (Plod2-14) aligned positions. The removal of ambiguous areas resulted in length variation of the aligned sequences from 523 (Fgb-4) to 1332 (Coro1c-4) positions. The numbers of parsimony-informative sites range from 71 (13.58%) (Fgb-4) to 343 (30.25%) (Cidea-1). According to different gap selection criteria in Gblocks, the alignment of the combined dataset comprised 15688 (allowed gap positions = all), 15038 (allowed gap positions = with half) and 12570 (allowed gap positions = none) positions. The parsimony-informative sites in these three datasets are 2170 (13.83%), 2137(14.21%) and 1735 (13.80%), respectively. An A-T bias (average = 58.64%) and low transition (Ti)/transversion (Tv) rate ratio (average = 1.93) were observed in most introns. In addition, most introns showed gamma shape parameters (α) close to or larger than 1.0. The nuclear sequence divergence among ingroup taxa ranged from 3% (Wasf1-7) to 8.2% (Tbc1d7-6), and averaged 4.7%.

Table 1.

Characterization of Nuclear introns and mt genes examined in the present study

Sequence type Fragments name TEs Aligneda Final datab Parsimony-informative sites Nucleotide Composition Ti/Tv Best fit model Among-site Rate Variation Pairwise Distance (%)
A T G C I α
Nucear introns Cidea-1 YES 1590 1134 343 0.308 0.240 0.230 0.222 1.5 TrN+G 0 0.9770 7.5
Coro1c-4 YES 1435 1332 339 0.242 0.280 0.234 0.243 2.4 K81uf+G 0 0.9379 6.3
Coro1c-5 YES 1380 1099 140 0.309 0.321 0.210 0.160 2.2 TVM+G 0 0.9084 4.7
Guca1b-3 YES 711 711 149 0.230 0.186 0.289 0.295 1.6 HKY+G 0 0.7174 6.1
Ociad1-4 YES 1576 1014 200 0.328 0.393 0.145 0.134 1.9 TVM+G 0 1.3754 4.1
Plod2-13 NO 1317 1230 236 0.293 0.325 0.229 0.153 2.0 GTR+G 0 1.555 3.3
Plod2-14 YES 1685 1068 263 0.342 0.327 0.180 0.151 1.4 TVM+G 0 1.4866 3.7
Ssr1-5 YES 1180 783 131 0.324 0.382 0.160 0.134 2.2 GTR+G 0 1.4043 3.6
Tbc1d7-6 YES 1153 1095 326 0.247 0.293 0.261 0.199 1.5 TIM+G 0 0.7365 8.2
Tinagl1-1 YES 1263 1260 250 0.208 0.208 0.295 0.290 2.4 HKY+G 0 0.7637 3.2
Tinagl1-3 YES 1115 1014 193 0.179 0.238 0.281 0.301 1.9 K81uf+G 0 0.7201 3.7
Wasf1-3 YES 1195 1021 161 0.314 0.345 0.170 0.171 1.8 GTR+G 0 1.6253 3.9
Wasf1-6 YES 1276 1077 207 0.308 0.354 0.191 0.147 2.2 TVM+G 0 1.7531 4.1
Wasf1-7 NO 1380 1147 223 0.314 0.355 0.165 0.166 2.0 GTR+G 0 0.6571 3
Ttr-1 YES 1130 895 159 0.263 0.279 0.227 0.231 2.4 TVM+G 0 1.3403 4.6
Fgb-4 YES 847 523 71 0.307 0.307 0.215 0.171 2.0 HKY 0 equal 4.5
Fgb-7 YES 642 611 102 0.292 0.327 0.186 0.195 1.4 GTR 0 equal 5.1
Com1c 15893 12570 1735 0.279 0.301 0.219 0.201 2.0 TVM+I+G 0.17 0.9090 4.4
Com2c 15893 15038 2137 0.279 0.302 0.218 0.201 1.9 GTR+I+G 0.18 0.9078 4.6
Com3c 15893 15688 2170 0.279 0.303 0.218 0.200 1.8 GTR+I+G 0.18 0.9052 4.6
Mt genes ND1 957 357 0.309 0.274 0.122 0.295 2.6 GTR+I+G 0.53 0.7988 17.3
ND2 1044 483 0.363 0.263 0.098 0.275 2.1 GTR+I+G 0.35 0.859 23
COX1 1545 556 0.282 0.302 0.175 0.241 3.1 GTR+I+G 0.58 1.1772 19.1
COX2 684 252 0.323 0.276 0.142 0.260 3.3 K81uf+I+G 0.56 1.0711 19.6
ATP8 204 92 0.388 0.291 0.077 0.243 2.2 GTR+I+G 0.42 1.3437 22.8
ATP6 681 290 0.306 0.291 0.116 0.287 3.3 GTR+I+G 0.46 0.7582 21.6
COX3 784 303 0.273 0.286 0.154 0.286 2.6 TrN+I+G 0.53 0.8079 20.2
ND3 348 160 0.320 0.279 0.130 0.272 2.5 TrN+I+G 0.38 0.956 22.3
ND4L 297 127 0.287 0.324 0.124 0.265 2.9 TVM+I+G 0.43 0.7530 22.5
ND4 1378 609 0.323 0.278 0.115 0.284 2.8 GTR+I+G 0.42 0.835 22.1
ND5 1830 739 0.331 0.274 0.115 0.280 2.6 TIM+I+G 0.42 0.8367 19.6
ND6 534 192 0.417 0.203 0.101 0.278 2.7 K81uf+I+G 0.46 0.656 16.3
CYTB 1140 446 0.295 0.278 0.134 0.293 2.8 TVM+I+G 0.5 1.1027 18.7
12SrRNA 988 236 0.371 0.229 0.178 0.223 2.8 GTR+I+G 0.37 0.3532 9.2
16SrRNA 1626 403 0.369 0.243 0.174 0.213 2.1 GTR+I+G 0.47 0.5765 10.5
tRNA 1558 301 0.353 0.281 0.157 0.209 4.0 GTR+I+G 0.48 0.4371 7.3
D-loop 941 315 0.308 0.277 0.166 0.249 1.9 HKY+I+G 0.3 0.4867 11.4
Combined 16537 5855 0.329 0.272 0.140 0.259 2.7 GTR+I+G 0.5 0.9372 16.9
Open in a new tab

Note: Ti = Transition; Tv = Transversion; I = Proportion of invariable sites; α = Gamma distribution shape parameter; TEs = Transposible Elements. If TEs were detected in introns, it indicated YES, otherwise it indicated NO.

a The length of sequences which were aligned using the CLUSTAL software with default settings.

b The length of analyzed data, after the ambiguous areas of the alignment were removed by Gblocks 0.91b.

c The length of all introns concatenated, after the ambiguous areas of the alignment were removed by Gblocks 0.91b with no gap (Com1), half gap (Com2), and all gap (Com3) parameters.

The complete mt genomes of 25 species ranged from 16388 to 16623 bp in size. Length differences are largely due to the variation in tandem repeats within the control region. All genomes shared the same 13 protein-coding genes, 22 tRNAs genes, 2 rRNAs, and a control region, and also the same gene order. These mt genomes are apparently AT-biased (average = 60.1%). The sequence divergence among ingroup taxa ranged from 16.3 (ND6) to 23% (ND2) for the protein-coding dataset (average 20.4%), from 9.2 (12S rRNA) to 10.5% (16S rRNA) for the rRNA dataset (average 9.85%), 7.3% for the tRNA dataset, 11.4% for the control region, and 16.6% for the complete dataset.

Occurrence of Transposable Elements (TEs)

In our intron datasets, pervasive transposable element (TE) insertions were discovered (Table 2), which are mainly non-long-terminal repeat retrotransposons (non-LTR), e.g., long interspersed elements (LINEs), short interspersed elements (SINEs), mammalian-wide interspersed repeats (MIRs), and DNA transposons. MIRs and DNA transposons integrated into the orthologous loci of all examined species, which suggested an ancient origin. The result was consistent with the earlier finding that these two classes of TEs represented remnants or "fossils" of TEs, predating the radiation of mammalian orders, and had long ago become inactive in mammalian lineages [28-30].

Table 2.

Transposable Elements (TEs) discovered in the present study

Intron Fragments Species Transposable Elements (TEs)
Species-specific Orthologous
TEs Class Length(bp) TEs Class Length(bp)
Cidea1 Martes penanti SINEC_b2 SINE/tRNA-Lys 192 L1_Canid_ LINE/L1 54-82
Mephitis mephitis SINEC_b1 SINE/tRNA-Lys 188
Meles meles SINEC_b1 SINE/tRNA-Lys 194
Arctonyx collaris SINEC_b2 SINE/tRNA-Lys 194
Coro1c-4 Tigger12c DNA/TcMar-Tigger 56-59
MIRb SINE/MIR 93-112
Coro1c-5 Lutra lutra SINEC_b1 SINE/tRNA-Lys 187 SINEC_old SINE/tRNA-Lys 104-107
L1ME4a LINE/L1 65-67
Guca1b-3 MIR SINE/MIR 58-63
Ociad1-4 Mephitis mephitis SINEC_b2 SINE/tRNA-Lys 268 MIRc SINE/MIR 92-122
Martes flavigula/Martes zibellina/Gulo gulo/Martes foina/Martes amaricana/Martes penanti SINEC_b1 SINE/tRNA-Lys 175-187
Plod2-14 Raccoon/Kinkajou SINEC_b1 SINE/tRNA-Lys 192-195 Kanga1a DNA/TcMar-Tc2 129-188
Kanga1c DNA/TcMar-Tc2 81-92
Ssr1-5 Ailurus fulgens SINEC_b1 SINE/tRNA-Lys 196
Tbc1d7-6 MIR SINE/MIR 134-195
Tinagl1-1 Mephitis mephitis/Ailurus fulgens MIR3 SINE/MIR 72-76 MIR SINE/MIR 49-64
Tinagl1-3 MIR SINE/MIR 85-87
Wasf1-3 L2c LINE/L2 85-90
Wasf1-6 MER58A DNA/hAT-Charlie 197
Fgb-4 Taxidea taxus SINEC_b1 SINE/tRNA-Lys 199
Lutra lutra SINEC_b2 SINE/tRNA-Lys 187
Fgb-7 Mephitis mephitis SINEC_b1 SINE/tRNA-Lys 193 MIRb SINE/MIR 196-198
Mephitis mephitis SINEC_b2 SINE/tRNA-Lys 193
Ttr-1 SINEC_b1 SINE/tRNA-Lys 166-193
Open in a new tab

The great majority of LINEs and SINEs identified here were members of the L1_Canid (Fc) and CAN SINE groups that have been exclusively found in Carnivora [31-38]. Most of SINEs showed restricted taxonomic distributions and were characterized by sporadic locations in the intronic regions. This suggests that those SINEs emerged after species diversification, likely retaining their ability to retrotranspose.

The insertions of TEs at genomic sites are often considered irreversible and random [39], which suggests that they may be excellent homoplasy-free markers in phylogenetic analyses [40-43]. Here, we identified one SINE insertion shared by Martes flavigula, Martes zibellina, Martes foina, Martes pennanti, Martes amaricana, and Gulo gulo, supporting their close relationship and the monophyly of Martinae subfamily.

Occurrence of Intra-individual Allele Heterozygotes (IIAHs)

The overall incidence of intra-individual allele heterozygotes (IIAHs) in our 14 new introns appears universal (Table 3). There were 106 cases of IIAHs in total. Of the 21 species examined, 3 to 11 cases of IIAHs were detected from each intron. IIAHs were observed to be either of equal or variable length. 11 of 14 introns had allele length variant heterozygotes due to a 1-bp indel, with the other nucleotide sites either the same or distinct at 1-11 bp. IIAHs of identical length were discovered in all introns with 1-10 substitutional differences.

Table 3.

Intra-individual Allele Heterozygotes (IIAHs) detected in the present study

Introns Species
Mephitis mephitis Ailurus fulgens Procyon lotor Potos flavus Martes flavigula Martes zibellina Martes foina Martes amaricana Martes penanti Gulo gulo Mustela kathiah Mustela nivalis Mustela sibirica Mustela frenata Mustela putorius Mustela vison Arctonyx collaris Meles meles Melogale moschata Taxidea taxus Lutra lutra
Cidea-1 0/1/0 0/0/0 0/1/0 0/1/0 0/0/0 0/3/0 0/0/0 0/0/0 0/0/0 -- 0/0/0 0/0/0 1/1/1 0/0/0 0/0/0 0/0/0 0/3/1 0/2/0 0/1/0 0/0/0 --
Coro1c-4 3/1/0 3/1/0 0/0/0 0/1/0 0/0/0 2/0/1 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 2/0/0 -- 0/0/0 -- 0/0/0 0/0/0 4/6/0 0/0/0 0/0/0 2/0/0
Coro1c-5 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/1/0 -- -- -- 0/0/0 0/5/0 0/0/0 -- 0/5/0 -- 0/0/0 0/0/0 -- 0/1/0 0/0/0
Guca1b-3 0/0/0 0/0/0 0/0/1 -- 5/0/0 0/0/0 0/0/0 0/0/0 4/0/0 0/0/0 0/0/0 3/0/1 0/2/0 0/0/0 2/0/0 0/0/0 4/6/0 0/1/0 0/0/0 1/0/0 0/1/0
Ociad1-4 0/0/0 0/0/0 0/3/0 0/1/1 1/0/1 0/1/0 1/1/0 0/0/0 0/0/0 0/0/0 1/4/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/1/0 0/0/0 0/0/0 1/1/0 0/0/0
Plod2-13 0/0/0 1/1/0 0/0/0 4/1/1 0/0/1 2/1/0 0/0/0 0/0/0 0/0/0 0/0/0 1/0/0 0/0/0 0/0/0 1/0/0 1/0/0 0/0/0 0/0/0 1/5/0 3/2/0 0/0/0 0/1/0
Plod2-14 0/1/1 0/0/0 0/0/0 1/6/1 0/3/0 0/1/0 0/1/0 0/0/0 0/0/0 0/0/0 0/0/0 1/1/0 1/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0
Ssr1-5 0/0/0 0/0/0 0/1/1 0/0/1 0/0/0 0/2/0 0/3/0 0/0/0 0/0/0 0/0/0 0/1/0 0/0/0 0/0/0 0/0/0 1/3/0 0/0/0 0/0/0 0/0/0 0/0/0 0/2/0 0/0/0
Tbc1d7-6 1/2/1 0/0/1 0/0/0 2/1/0 1/0/0 1/2/0 4/2/0 0/0/0 0/0/0 0/0/0 1/0/0 7/4/1 0/0/0 1/0/0 1/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/1/0 0/0/0
Tinag1-1 0/0/0 0/0/0 0/0/0 3/0/0 2/1/1 3/1/0 0/0/0 0/0/0 1/0/0 0/0/0 3/0/0 2/0/0 0/0/0 0/0/0 3/0/0 0/0/0 0/0/0 0/0/0 3/0/0 0/0/0 1/0/0
Tinagl1-3 0/0/0 0/1/0 0/0/0 1/6/0 1/0/0 0/1/0 0/0/0 0/0/0 0/0/0 0/0/0 0/5/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 1/1/0 1/0/0 1/0/0 0/0/0 --
Wasf1-3 0/0/0 0/0/0 0/0/0 2/0/1 0/0/0 0/2/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/3/0 2/0/0 1/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0
Wasf1-6 0/0/0 0/0/0 3/1/0 2/0/0 0/0/0 0/0/0 0/0/0 -- 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 1/0/0 0/0/0
Wasf1-7 0/0/1 1/0/1 2/0/0 1/1/0 1/0/0 0/0/0 1/0/0 0/0/0 0/0/0 0/0/0 0/0/0 7/1/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 0/0/0 3/0/0 1/0/0 0/0/0
Open in a new tab

Notes: The information of IIAHs were represented as transitions/transversions/indels. The numbers correspond to the number of transitions, the number of transversions and the length of indels, respectively. -- stands for unknown numbers due to the unavailiablity of sequences data

Generally, IIAHs formed monophyletic pairs on the phylogenetic trees as expected (see Additional file 1). Two cases of strongly-supported nonmonophyletic IIAHs were illustrated by the close relatedness of one allele of the least weasel Mustela nivalis to one allele of the European polecat Mustela putorius (Plod2-13 and Guca1b-3 genes; Figure 2), which are most likely to indicate the cases of incomplete lineage sorting.

Figure 2.

Figure 2

Open in a new tab

MP/Bayesian/ML phylogenetic tree of 21 mustelidae species for 17 combined nuclear intron loci. MP/ML bootstrap values (allowed gap positions = all in Gblocks) are shown above nodes. Posterior probabilities are shown below nodes. Node numbers that were used in the divergence time estimations and phylogenetic performance evaluation are indicated in the tree.

Phylogenetic Inference

Although individual nuclear gene analyses produced inconsistent topologies with low levels of support (Additional file 1), possibly due to limited phylogenetic information harbored in a single gene, the analyses of the combined nuclear data set using three gap selection criteria in Gblocks (allowed gap positions = none, with half, and all) and different tree-building methods (MP, ML and Bayesian methods) yielded nearly identical, well-resolved trees with strong support for all nodes, except for the relationships among Gulo gulo, Martes americana, and Martes pennanti (Figure 2). In the tree, Taxidiinae diverged first (MP BS = 100%, ML BS = 100%, PP = 1.00), followed by Melinae (MP BS = 85%, ML BS = 98%, PP = 1.00). The remaining mustelids were divided into two clades, one consisting of Martinae and Helictidinae (MP BS = 99%, ML BS = 99%, PP = 1.00), and the other one consisting of Lutrinae and Mustelinae (MP BS = 82%, ML BS = 99%, PP = 1.00). In addition, both the inclusion of IIAHs in the combined nuclear analysis using software POFAD [44] and the Bayesian concordance analysis (BCA) analysis (Additional file 2) using software BUCKy [45] produced the same tree topologies as that in Figure 2. At the subfamily level, all nodes in the BCA analysis received high concordance factors (CF) value (1.000).

For individual mt gene analyses, the rRNA and tRNA data sets demonstrated reduced resolving power for phylogenetic inference compared to protein-coding gene analysis (Additional file 3). The complete mtDNA genome-based analyses, irrespective of the used tree-building methods and parameter sets, produced a well-resolved and well-supported tree (Figure 3), with the tree topology and branch supports identical to that of the combined protein-coding gene analysis. At the subfamilial level, the single difference between mt genome tree (Figure 3) and combined nuclear gene tree (Figure 2) is the phylogenetic position of Helictidinae. In mt genome tree, Helictidinae is closer to the clade uniting Lutrinae and Mustelinae than to Martinae (MP = 60%; ML BS = 95%; PP = 1.00).

Figure 3.

Figure 3

Open in a new tab

MP/Bayesian/ML phylogenetic of 25 mustelidae species for the complete mt genomes. MP/ML bootstrap values/Posterior probabilities are shown below nodes. Node numbers that were used in the divergence time estimations and phylogenetic performance evaluation are indicated in the tree.

The phylogenetic tree reconstructed from the combined nuclear and mt genome data set by using the BCA analysis [45] produced a tree topology (Additional file 2) identical to that from the combined nuclear gene analysis (Figure 2). At the subfamily level, all nodes received high CFs (1.000), except for that of Helictidinae (CF = 0.502), whose position is the single discrepancy between the combined nuclear and mt gene trees.

Shimodaira-Hasegawa (SH) test and the approximately unbiased (AU) test were carried out to examine the degree of significant difference between the nuclear and mt trees produced in the present study. Both tests indicated significant topological incongruence concerning the phylogenetic position of Helictidinae between the nuclear and mt trees. When using nuclear data, the mt genome tree topology, in which Helictidinae is closer to the clade uniting Lutrinae and Mustelinae, was rejected by the AU and SH tests (P < 0.05). When using mt genome data, the nuclear tree topology, in which Helictidinae and Martinae are grouped together, was rejected by the AU and SH tests (P < 0.05).

Divergence Time Estimation

Divergence time estimates for the origin and diversification of Mustelidae subfamilies yielded broadly consistent results between combined nuclear and mt genome data set (Table 4). Combined nuclear gene analysis placed the earliest branching Taxidiinae around 23.73 Mya (95% confidence intervals = 22.80-24.70 Mya). After that, Melinae diverged from the other mustelids at 17.33 Mya (95% confidence intervals = 12.44-22.10 Mya). The split between Martinae/Helictidinae and Lutrinae/Mustelinae took place at 16.05 Mya (95% confidence intervals = 11.34-20.91 Mya). The divergence between Martinae and Helictidinae occurred at 10.21 Mya (95% confidence intervals = 5.66-15.04 Mya), and that between Lutrinae and Mustelinae at 11.43 Mya (95% confidence intervals = 7.02-16.00 Mya). The origins of Mustelinae and Martinae were estimated to be 5.89 Mya (95% confidence intervals = 4.99-6.83 Mya) and 5.97 Mya (95% confidence intervals = 3.39-8.90 Mya), respectively.

Table 4.

Divergence time estimations (in millions of years ago) for major diversification events of Mustelidae, including data from previous studies

Node Diversification event Nuclear dataa(95% CI)c Mt datab(95% CI) Fossil record Wayne (1989) Bininda-Emonds (1999) Hosoda (2000) Sato (2003) Yonezawa (2007) Koepli (2008) Eizirik et al (2010)
1 divergence of Taxidiinae to the other mustelids 23.73(22.80-24.70) 23.46(22.50-24.41) - - 20.8 - - 20.21(18.78-21.64) 24.2(22.3-26) 13.0 (9.6-17.1)
2 divergence of Melinae 17.33(12.44-22.10) 17.19(13.96-20.58) 18-20.5 - 13.7 - 14.5-18.1 16.98(15.52-18.44) 11(9.4-12.5) 11.7 (8.5-15.5)
3 origin of the other mustlids except for Taxidiinae and Melinae 16.05(11.34-20.91) 15.79(12.65-19.11) 21.5-22.5 - 11.4 - 14.7-14.8 14.83(13.39-16.27) 11.6(10.1-13) 10.8 (7.8-14.5)
4 divergence of Helictidinae 10.21(5.66-15.04) 13.86(10.45-17.02) - - 6.9 - - - 10.8(9.4-12.2) -
5 divergence between Lutrinae and Mustelinae 11.43(7.02-16.00) 12.54(9.24-15.87) 11.1-13.5 20-25 9.9-17.1 15-23 13.5-14.1 12.74(11.41-14.07) 8.7(7.3-10.0) 8.4(5.9-11.5)
7 origin of Mustelinae 5.89(4.99-6.83) 6.30(5.39-7.24) 3.4-4.2 12-20 10.4-11.4 10-23 8.5-9.9 - 6.1(4.9-7.2) -
6 origin of Martinae 5.97(3.39-8.90) 10.91(7.82-14.37) 3.3-4.0 - 8.2 10-14 - 11.48(10.15-12.81) 6.8(5.1-8.5) 7.7(5.3-10.8)
Open in a new tab

Node numbers correspond to those indicated in Figure 2 and 3

a the divergence times were estimated based on combined nuclear genes and tree topology in Figure 2

b the divergence times were estimated based on mt genomes and tree topology in Figure 3

c 95% confidence intervals

The analyses of the mt genome data set suggested the origin of Taxidiinae around 23.46 Mya (95% confidence intervals = 22.50-24.41 Mya). Other time estimates included the split of the Melinae clade from other mustelids at 17.19 Mya (95% confidence intervals = 13.96-20.58 Mya), the separation between Helictidinae/Lutrinae/Mustelinae and Martinae about 15.79 Mya (95% confidence intervals = 12.65-19.11 Mya), the divergence between Helictidinae and Lutrinae/Mustelinae at 13.86 Mya (95% confidence intervals = 10.45-17.02 Mya), and the divergence between Lutrinae and Mustelinae at 12.54 Mya (95% confidence intervals = 9.24-15.87 Mya). The origins of Mustelinae and Martinae were estimated to be 6.30 Mya (95% confidence intervals = 5.39-7.24 Mya) and 10.91 Mya (95% confidence intervals = 7.82-14.39 Mya), respectively.

Discussion

Phylogeny of Mustelidae Subfamilies

Among mammalian phylogenies, those characterized by rapid species radiations have long been one of the plaguing and challenging problems in species tree reconstruction [46]. This is the first study utilizing data from such large-scale nuclear non-coding loci from Mustelidae.

Both our combined nuclear intron and mt genome phylogenies not only strongly favor the prevailing view that Taxidiinae was the most basal member within family Mustelidae [4,5,10-14], but also provide strong evidence that Melinae diverged between Taxidiinae and all the other mustelids examined as well. The latter is in contradiction to morphological investigations [8], but supports the nuclear gene results from Sato et al. [11,12] and Wolsan and Sato [13], and disagree those from Koepfli et al. [5] and Yu et al. [15].

Notably, the sister relationship between Lutrinae and Mustelinae was reinforced by consistent recovery from both our mt genome and combined nuclear intron analyses with high confidence, upholding and strengthening the hypothesis drawn by almost all sequence-based analyses in previous studies [4,5,7,10-15]. In contrast, the position of Helictidinae varied between our nuclear and mt genome analyses. Nuclear data analysis placed it as sister to Martinae, whereas mt genome data indicated a sister-taxa association of it to the clade uniting Lutrinae and Mustelinae. Our mt genome result (Figure 3) is consistent with that inferred from most previous nuclear studies [3-5,10-13], but dissented from morphological view and karyological analyses [8,47-49]. Interestingly, our combined nuclear analysis (Figure 2) yields a result that is different from all previous hypotheses, suggesting for the first time Helictidinae and Martinae are more closely related to each other than any other taxa in Mustelidae.

Corresponding tests (AU and KH tests) have indicated significant topological incongruence between nuclear and mt trees. When using nuclear data, the mt genome tree topology was rejected by the AU and SH tests (P < 0.05), and vice versa. Phylogenetic incongruence between nuclear and mitochondrial genes has also been reported in Drosophila, Aves and bears [50-53]. Various elements may bear the responsibility for the presence of conflicting signal regarding the placement of Helictidinae, including different evolutionary histories and gene properties in gene regions from different genomes, sampling error and lineage sorting. The probability of their occurrence increased especially when separation time between different species is short [54-57], as in the present study. Although the BCA analysis of the combined nuclear intron and mt genome sequences, which is an approach that allows for gene tree discordance, retrieved an identical tree topology to that of the nuclear intron gene, the position of Helictidinae received week support. Therefore, the analyses involving more characters in the future may help to confirm the precise position of Helictidinae.

Implications for Mustelidae Radiation

Mustelidae has one of the most extensive fossil records of extant Carnivora families [8], and molecular dating of the Mustelidae radiation has also been attempted in several studies previously. Our results, from an independent character source, provide important insights into the time scale of the origin and diversification of extant subfamilies of Mustelidae. It is interesting to draw a comparison of the dating results estimated from prior and present studies (Table 4).

Among the subfamilies, Taxidiinae is the basal-most branching lineage in mustelid diversification dating to the late Oligocene, which is more concordant with the time estimate of Koepfli et al. [5], but earlier than those of Bininda-Emonds et al. [58], Yonezawa et al. [15] and Eizirik et al. [59]. The divergence time of the next branching lineage, i.e., Melinae clade, is dated to the early Miocene in our analysis, which is more broadly consistent with the paleontological data [60] and the sequence-based data from Yonezawa et al. [15] than those from Sato et al. [2], Bininda-Emonds et al. [54], Koepfli et al. [5], and Eizirik et al [59]. The estimates of the origin of the remaining mustelids are more recent than those fossil-based ages [61], and older than the other sequence-based dates [2,5,15,58,59].

Among the remaining mustelids, one important event of the mustelid diversification is the divergence between Lutrinae and Mustelinae. Our estimated dates are consistent with the corresponding fossil records [60,62] and that from Yonezawa et al. [15], but more recent than those from Hosoda et al. [63], Wayne [64], and Sato et al. [2], and older than those from Koepfli et al. [5] and Eizirik et al. [59]. Other important events are the origins of Mustelinae and Martinae. Our estimates for them are both much older than the existing fossil record [65,66]. The dates of Mustelinae origin are older than most of the other molecular estimates, but in good agreement with that of Koepfli et al. [5]. As regards the origin of Martinae, there is large difference between our nuclear and mt genome estimates. The nuclear estimate is more in agreement with those from Koepfli et al. [5] and Eizirik et al. [59], while the mt estimate is more concordant with those from Hosoda et al. [63] and Yonezawa et al. [15].

In addition, our analyses resulted in time estimates of divergence of Helictidinae that more agree with that from Koepfli et al. [5] than that from Bininda-Emonds et al. [58], which is younger than the present results. More intensive taxonomic sampling will improve accuracy on the time estimation of mustelid diversification.

Utilities of the nuclear introns in phylogenetic study of Mustelidae subfamilies

Several recent studies have indicated that nuclear introns hold considerable signals for resolution of difficult phylogenies at both shallow and deeper species level hierarchies [21-24,27,67,68]. We are among the first to use large-scale nuclear intron genes in inferring phylogenies of Mustelidae. Our analysis not only brings new perspectives on the phylogenetic relationship of Mustelidae subfamilies, but provides another example demonstrating that the nuclear non-coding genes can be an effective data source for reconstructing evolutionary histories in a group that has undergone rapid bursts of speciation as well.

We assessed the phylogenetic utilities of individual introns and mt genes in resolution of the inter-subfamilial relationships of Mustelidae by counting the number of congruent nodes between the individual phylogenies and the combined gene trees (Table 5). In the individual nuclear gene analyses, the Plod2-13 gene recovered all 8 nodes of the combined nuclear gene tree. Anyway, the Plod2-13 and Plod2-14 genes recovered the highest number of congruent nodes of the combined nuclear gene tree, whereas the Wasf1-7, Guca1b-3, Ssr1-5, and Tbc1d7-6 genes showed the lowest phylogenetic performance. As regards the mt gene analyses, we observed that the ND5 and CYTB genes recovered all 9 nodes of the mt genome tree. Ranking the single mt gene shows that the ND5, CYTB, 16SrRNA and ND2 genes are better indicators of Mustelidae phylogeny at subfamilial level than are other genes, such as Atp8, Atp6 and ND4L genes. This result agrees broadly with previous conclusions about the rough classification of mt genes into good, medium, and poor performance categories [69-74] (Additional file 4). In summary, the assessment of phylogenetic utility and limits of these individual nuclear and mt genes makes it possible to preselect subsets of genes for future molecular studies of vertebrate phylogeny.

Table 5.

Phylogenetic performance of nuclear and mt genes

Genea no. congruent branches (BP > 0.95) no. congruent branches (BP < 0.95) total no. congruent branches Nodeb
1 2 3 4 5 6 7 8 9
Mt gene nd5 8 1 9 * * * # * * * * *
cytb 8 1 9 * * * * # * * * *
16sRNA 8 0 8 * * * * * * * *
nd2 6 1 7 * # * * * * *
cox2 6 0 6 * * * * * *
nd4 6 0 6 * * * * * *
nd6 5 1 6 * * * * * #
12sRNA 5 1 6 * # * * * *
nd3 4 2 6 * # * # * *
cox1 5 0 5 * * * * *
cox3 5 0 5 * * # * * *
tRNAs 4 1 5 * # * * *
nd1 4 1 5 * # * * *
atp8 3 1 4 * # * *
atp6 4 0 4 * * * *
nd4l 2 0 2 * # *
Nuclear gene Plod2-13 6 2 8 * * # # * * * *
Plod2-14 6 1 7 * * * * # * *
Coro1c-5 5 1 6 * * * # * - *
Tinagl1-3 5 1 6 * * # * - * *
Coro1c-4 6 0 6 * * * * * *
Tinagl1-1 6 0 6 * * * * * *
Cidea-1 6 0 6 * * * * - * *
Ociad1-4 4 2 6 * # * * # *
Wasf1-3 5 1 6 * * * # * *
Fgb-7 5 1 6 # * * * * *
Ttr-1 6 0 6 * * * * * - *
Wasf1-6 5 0 5 * * * * *
Fgb-4 4 1 5 * * # * *
Wasf1-7 3 0 3 * * *
Guca1b-3 2 0 2 * *
Ssr1-5 2 0 2 * *
Tbc1d7-6 0 0 0
Open in a new tab

Node numbers correspond to those indicated in Figure 2 and 3

a genes are ranked by the total number of congruent branches in the combined topologies

b there are 9 nodes in total indicated in the mt genome tree (Figure 3) and 8 nodes in the combined nuclear gene tree (Figure 2)

* branches with PP > 0.95 congruent in the combined topology

# branches with PP < 0.95 congruent in the combined topology

Although the use of nuclear introns as genetic markers has now been implemented as a powerful approach in recent phylogenetic studies, there are, however, numerous potential problems associated with this approach. Chief among these is the difficulties in sequence data acquisition, alignment, and analysis of the nuclear introns compared to the traditional mt and nuclear protein-coding genes, as a result of the higher rates of variation and frequencies of indels. The common presence of indels (including TEs, small gaps and tandem repeats) and IIAHs, as reported in this study, makes experimental work labor-intensive by virtue of the additional time and money required to isolate alleles and optimize PCR amplification and sequencing. In addition, they can create positional homology problems associated with areas of ambiguous alignment [75]. Several studies have also shown that the phylogenetic inference is sensitive to the various treatments of indels. These issues are central to the appropriate application of intron data in phylogenetic reconstruction and they should be comprehensively and explicitly addressed in the future studies [19].

Conclusions

The phylogenetic relationships among Mustelidae subfamilies have posed one of the major problems concerning Carnivora systematics. In this study, phylogenetic relationships among Mustelidae subfamilies are presented based on 17 nuclear intron loci and mt whole genomes. Our results resolve some of the ambiguous issues in Mustelidae phylogeny, whereas some phylogenetic relationships require confirmation by analyzing additional samples and character information, such as the precise position of Helictidinae. Our study not only brings new perspectives on the previously obscured phylogenetic relationships among Mustelidae subfamilies, but also provides another example demonstrating the effectiveness of nuclear non-coding loci for reconstructing evolutionary histories in a group that has undergone rapid bursts of speciation.

Methods

Sequence Data

Detailed information of the 14 nuclear intron loci first used in the Mustelidae phylogeny is shown in Additional file 5. These loci were amplified with primers as described in Yu et al. [27] from 17 mustelids and 4 non-mustelid carnivoran species. Three other nuclear introns (Ttr-1, Fgb-4 and Fgb-7), which were available from our previous published studies [14,76,77], were also included in the present nuclear data set.

The species examined in this study and their Genbank accession numbers are listed in Additional file 6. A "touch-down" PCR amplification was carried out using the following parameters: 95°C hot start (5 min), 10 cycles of 94°C denaturation (1 min), 60-50°C annealing (1 min), 72°C extension (1 min), and finally 25 cycles of 94°C denaturation (1 min), 50°C annealing (1 min), 72°C extension (1 min). The amplified DNA fragments were purified and sequenced in both directions with an ABI PRISM(tm) 3730 DNA sequencer following the manufacturer's protocol. In the case of poor performance of direct sequencing resulting from complex DNA structures, tandem repeats or intron heterozygotes, the amplified PCR products were gel-purified and cloned into the pMD18-T vector (TaKaRa Biotechnology Co., Ltd. Dalian, China) and transformed into ultracompetent E. coli cells (TaKaRa Biotechnology Co., Ltd. Dalian, China). Thirty positive clones per ligation reaction were sequenced. All sequences obtained were checked carefully and queried in BLAST searches of GenBank to assess homology. In a few cases, PCR attempts using different primer pairs and cloning methods failed to produce sequence data (see Additional file 6). These sequences were excluded from the independent gene analyses and treated as missing data in the combined analyses. The newly determined nuclear sequences have been deposited in GenBank with accession numbers HM063147-HM063412.

The mt complete genome sequences were amplified using LA PCR™ Kit (Takara Biotechnology Co., Ltd) and 9 universal long PCR primers from 14 mustelids and 2 non-mustelid carnivoran species (Additional file 6). In addition, 23 species-specific primers were designed when the universal PCR primers failed to produce successful PCR amplification. A "touch-down" long PCR amplification was carried out using the following parameters: 95°C hot start (2 min), 10 cycles of 98°C denaturation (10 sec), 67-58°C annealing (1 min 30 sec; °C/cycle), 72°C extension (5 min), and finally 25 cycles of 98°C denaturation (10 sec), 58°C annealing (1 min 30 sec), 72°C extension (5 min). At the end, a final 10-min extension at 72°C was performed. Long PCR products were sequenced in both directions using a primer walking strategy with a total of 306 primers. Sequencing was performed in an ABI PRISM(tm) 3700 DNA sequencer following the manufacturer's protocol. Primer sequence information is available upon request. Where necessary, PCR products were cloned into the pMD18-T vector and transformed into ultracompetent E. coli cells (TaKaRa Biotechnology Co., Ltd. Dalian, China) in order to resolve the difficulty of direct sequencing of control regions arising from long tandem repeats. Five positive clones per ligation reaction were sequenced. Mt sequences obtained were checked to ensure that they did not include nuclear copies of mtDNA-like pseudogenes. In addition to these new 16 mt genomes, 6 other mustelid and 3 other non-mustelid mt genomes available in public database were included in the mt analyses (Additional file 6).

Alignments and sequence Characterizations

Sequences were aligned using CLUSTAL X under the default settings [78]. The nuclear alignment was divided into two data sets: (1) each of the 17 intron loci and (2) combined sequences of all introns. The mt alignment was divided into four data sets: (1) each of the 13 protein-coding genes, (2) 22 tRNAs, (3) two rRNAs, and (4) combined sequences of the tRNAs, rRNAs and protein-coding genes. Due to the presence of ambiguous areas in the nuclear alignments, we excluded the alignment ambiguities using Gblocks 0.91b [79] with default parameters (allowed gap positions = all).

Pairwise comparisons and sequence characterizations were estimated using MEGA 4.0 [80]. Given that nuclear introns tend to be favorable chromosomal regions for integration of transposable elements (TEs) [81], they were screened for interspersed repeats by using the program RepeatMasker (Smit, Hubley and Green, RepeatMasker Open-3.0. 1996-2004, http://www.repeatmasker.org).

Phylogenetic Analyses

Phylogenetic analyses of the individual introns and mt genes, i.e., nuclear data set (1) and mt data set (1), (2), and (3), were performed using PAUP* 4.0b10 [82] for maximum parsimony (MP) and maximum likelihood (ML) analyses, and using MrBayes 3.1.2 [83] for the Bayesian inference. In MP analyses, a heuristic search was performed with tree-bisection-reconnection (TBR) branch swapping, random addition of taxa, and 1000 replicates per search. Only one of the best trees found during branch swapping was saved. In ML analysis, the best-fit models of sequence evolution were selected using the Akaike Information Criterion (AIC) [84,85] with Modeltest version 3.7 [86]. The chosen models and their parameters were used to infer ML trees with the heuristic algorithm, 10 random-addition sequence replicates, and TBR branch swapping. The tree reliability under ML analysis was assessed using a bootstrap resampling of 100 replicates (BP) [87]. In Bayesian inference, each Metropolis-coupled Markov chain Monte Carlo (MCMC) run for all individual genes employed the model selected by ModelTest for that gene, or the nearest model to that model that could be implemented in MrBayes. Three heated chains and a single cold chain were used in all MCMC analyses and run for 2 × 106 generations, Trees were sampled every 100 generation. The average standard deviation of split frequencies was close to 0.001 when the run was end. The first 25% were discarded as the burn-in. A 50% majority-rule consensus of post burn-in trees was constructed to summarize posterior probabilities (PP) for each branch.

In addition to individual analyses, phylogenetic reconstruction were performed based on the combined data sets, i.e., nuclear data set (2) and mt data set (4), using PAUP* 4.0b10 [82] for MP analysis, RAxML online web server [88] for partitioned ML analysis and using MrBayes [83] for partitioned Bayesian analysis (pBI) [89]. For the combined data sets, we identified model partitions based on partitioning matrices by locus. That is, in the analysis of combined nuclear data set, each nuclear intron gene was considered as a different partition, whereas in that of combined mt data set, each of the 13 individual protein-coding genes, all tRNAs, and each of the two rRNA genes were considered as different partitions. Based on the selected models using the AIC [84] as mentioned above for individual analyses, we assigned a separate substitution model for each of the data partitions. Three heated chains and a single cold chain were used in all MCMC analyses and run for 5 × 106 generations, sampling trees every 100 generations. The average standard deviation of split frequencies was close to 0.001 when the run was end. The first 25% were discarded as the burn-in. A 50% majority-rule consensus of post burn-in trees was constructed to summarize posterior probabilities (PP) for each branch.

In addition, given the heterogeneous gene trees observed among 17 nuclear intron gene analyses and between the combined nuclear intron and mt genome analyses, Bayesian concordance analysis (BCA) [45] implemented in the program BUCKy [45], which uses individually calculated gene trees to infer the species tree that maximizes the bipartition concordance among each gene tree, was also performed for both the nuclear intron gene datasets and the nuclear plus the mt genome datasets. Tree reliability was evaluated by sample concordance factors (CFs). The MCMCMC sampled with 2 × 106 generations was employed (4 runs and 4 chains) and a priori level of discordance α = 2.5 was used in BCA.

In all analyses, trees were rooted with the red panda Ailurus fulgens and the skunk Mephitis mephitis, based on the general consensus that they branched off earlier than the mustelids [2,4,11,12,76,77].

Intra-individual allele heterozygotes

For individual intron analyses, both copies of alleles from a species were included. For combined nuclear data sets, we performed phylogenetic analyses by (1) choosing randomly an allele per species for portioned ML analysis and Bayesian analysis (without the inclusion of IIAHs), and (2) using POFAD v1.03 algorithm (Phylogeny Analysis From Allelic Data) [90] to incorporate IIAHs. POFAD is a recently developed method of constructing phylogeny from multiple datasets that contain allelic information. It converts a distance matrix of alleles into a distance matrix of organisms so that individuals become the terminals of the analyses. First, we calculated the average uncorrected pairwise distances in PAUP* [82]. These distances then served as the input for the calculation of standardized pairwise distances between species in POFAD [90]. The standardized distances were then used as input for the neighbor-joining analysis conducted using PAUP* [82] to produce a phylogenetic tree.

Divergence time estimation

Divergence times based on combined nuclear intron and combined mt data sets were estimated using the Bayesian relaxed phylogenetic approach implemented in BEAST v1.5.4 [91]. We assumed a GTR+I+G model of DNA substitution with four rate categories. Uniform priors were employed for GTR substitution parameters (0, 100), gamma shape parameter (0, 100) and proportion of invariant sites parameter (0, 1). The uncorrelated lognormal relaxed molecular clock model was used to estimate substitution rates for all nodes in the tree, with uniform priors on the mean (0, 100) and standard deviation (0, 10) of this clock model. We employed the Yule process of speciation as the tree prior and a UPGMA tree to construct a starting tree, with the ingroup assumed to be monophyletic with respect to the outgroup.

Three calibration points from the fossil records were applied in the dating analyses. These calibration points are all implemented as minimum age constraints, including 27.6 Mya for the split between Procyonidae and Mustelidae [12,15,92], 24 Mya for the crown Mustelidae [2,5,17], and 5.3 Mya for the origin of the genus Mustela in Mustelinae [5,93]. All fossil constraint priors were set as means of a normal distribution, with a standard deviation of 1.0 MYA. Two independent MCMC runs of 30,000,000 generations were performed for each data set with parameters logged every 1,000 generations. The Auto Optimize Operators function was enabled to maximize efficiency of MCMC runs. Two independent MCMC runs for each analysis were combined to estimate the posterior distribution of the substitution model and tree model parameters, as well as node ages. Analyses of these parameters in Tracer 1.5 [94] suggested that the number of MCMC steps was more than adequate, with effective sample sizes of all parameters often exceeding 1,000 and Tracer plots showing strong equilibrium after discarding burn-in.

Testing Tree Incongruence

The incongruence among different tree topologies was evaluated using the Shimodaira-Hasegawa (SH) test [95] and the approximately unbiased (AU) test [96], as implemented in the CONSELV0.1i program [97] with default scaling and replicate values. The site-wise log-likelihood values were estimated by PAUP* [82].

Authors' contributions

LY, YPZ and OAR designed the study and wrote the manuscript. DP and JL carried out the experiment work and performed the sequence analyses. PTL and LL contributed to the experiment work and sequence analyses. HL and ML helped collect samples. All authors read and approved the final manuscript.

Supplementary Material

Additional file 1

Phylogenetic relationships of Mustelidae based on the analyses of 17 single introns. The IIAHs within a species was shown as 1 and 2. All trees shown were reconstructed using Bayesian method. Posterior probabilities (PP) are shown above internal nodes.

Click here for file (353.5KB, DOC)
Additional file 2

Phylogenetic relationships of Mustelidae based on the Bayesian concordance analysis (BCA) of the nuclear intron gene datasets and the nuclear plus the mt genome datasets. The concordance factors (CFs) from the nuclear intron gene analysis and the nuclear plus the mt genome analysis are shown above internal nodes.

Click here for file (2.5MB, DOC)
Additional file 3

Phylogenetic relationships of Mustelidae based on the analyses of 13 individual protein-coding genes, 2 individual rRNA genes, 22 tRNAs, combined protein-coding genes, combined rRNA genes, and combined tRNA genes. All trees shown were reconstructed using Bayesian method. Posterior probabilities (PP) are shown above internal nodes.

Click here for file (448KB, DOC)
Additional file 4

Comparisons of phylogenetic performances of mt genes among studies.

Click here for file (24.5KB, XLS)
Additional file 5

Detailed information of 14 nuclear intron loci that were first used in the Mustelidae phylogeny.

Click here for file (25.5KB, XLS)
Additional file 6

The species examined in this study and their Genbank accession numbers.

Click here for file (30KB, XLS)

Contributor Information

Li Yu, Email: yuli1220@yahoo.com.cn.

Dan Peng, Email: danpeng08@gmail.com.

Jiang Liu, Email: urrican_2403024@sina.com.

Pengtao Luan, Email: pengtaoluan@gmail.com.

Lu Liang, Email: tudou_ll@163.com.

Hang Lee, Email: hanglee@snu.ac.kr.

Muyeong Lee, Email: muyeong@gmail.com.

Oliver A Ryder, Email: oryder@sandiegozoo.org.

Yaping Zhang, Email: zhangyp@mail.kiz.ac.cn.

Acknowledgements

We would like to give thanks to Mammalogy Collections of the Department of Natural History, Royal Ontario Museum, for providing some samples. This work was supported by grants from the State Key Basic Research and Development Plan (2007CB411600), and National Natural Science Foundation of China (30600067, U083660). We thank C. Steiner for helpful comments on the manuscript.

References

  1. Nowak RM. Walker's mammals of the world. 6. Baltimore, MaryLand: Johns Hopkins University Press; 1999. [Google Scholar]
  2. Sato JJ, Hosoda T, Wolsan M, Tsuchiya K, Yamamoto Y, Suzuki H. Phylogenetic relationships and divergence times among mustelids (Mammalia: Carnivora) based on nucleotide sequences of the nuclear interphotoreceptor retinoid binding protein and mitochondrial cytochrome b genes. Zool Sci. 2003;20:243–264. doi: 10.2108/zsj.20.243. [DOI] [PubMed] [Google Scholar]
  3. Sato JJ, Hosoda T, Wolsan M, Suzuki H. Molecular phylogeny of arctoids (Mammalia: Carnivora) with emphasis on phylogenetic and taxonomic positions of ferret-badgers and skunks. Zool Sci. 2004;21:111–118. doi: 10.2108/0289-0003(2004)21[111:MPOAMC]2.0.CO;2. [DOI] [PubMed] [Google Scholar]
  4. Fulton TL, Strobeck C. Molecular phylogeny of the Arctoidea (Carnivora): effect of missing data on supertree and supermatrix analyses of multiple gene data sets. Mol Phylogenet Evol. 2006;41:165–181. doi: 10.1016/j.ympev.2006.05.025. [DOI] [PubMed] [Google Scholar]
  5. Koepfli KP, Deere KA, Slater GJ, Begg C, Begg K, Grassman L, Lucherini M, Veron G, Wayne RK. Multigene phylogeny of the Mustelidae: Resolving relationships, tempo and biogeographic history of a mammalian adaptive radiation. BMC Biol. 2008;6:10. doi: 10.1186/1741-7007-6-10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Koepfli KP, Wayne RK. Phylogenetic relationships of otters (Carnivora; Mustelidae) based on mitochondrial cytochrome b sequences. J Zool. 1998;246:401–416. doi: 10.1111/j.1469-7998.1998.tb00172.x. [DOI] [Google Scholar]
  7. Marmi J, López-Giráldez J, Domingo-Roura X. Phylogeny, evolutionary history and taxonomy of the Mustelidae based on sequences of the cytochrome b gene and a complex repetitive flanking region. Zool Scri. 2004;33:481–499. doi: 10.1111/j.0300-3256.2004.00165.x. [DOI] [Google Scholar]
  8. Bryant HN, Russell AP, Fitch WB. Phylogenetic relationships within the extant Mustelidae (Carnivora): appraisal of the cladistic status of the Simpsonian subfamilies. Zool J Linn Soc. 1993;108:301–334. doi: 10.1111/j.1096-3642.1993.tb00301.x. [DOI] [Google Scholar]
  9. Dragoo JW, Honeycutt RL. Systematics of mustelid-like carnivores. J Mamm. 1997;78:426–443. doi: 10.2307/1382896. [DOI] [Google Scholar]
  10. Koepfli KP, Wayne RK. Type 1 STS markers are more informative than cytochrome b in phylogenetic reconstruction of the Mustelidae (Mammalia: Carnivora) Syst Biol. 2003;52:571–593. doi: 10.1080/10635150390235368. [DOI] [PubMed] [Google Scholar]
  11. Sato JJ, Wolsan M, Suzuki H, Hosoda T, Yamaguchi Y, Hiyama K, Kobayashi M, Minami S. Evidence from nuclear DNA sequences sheds light on the phylogenetic relationships of Pinnipedia: single origin with affinity to Musteloidea. Zool Sci. 2006;23:125–146. doi: 10.2108/zsj.23.125. [DOI] [PubMed] [Google Scholar]
  12. Sato JJ, Wolsan M, Minami S, Hosoda T, Sinaga MH, Hiyama K, Yamaguchi Y, Suzuki H. Deciphering and dating the red panda's ancestry and early adaptive radiation of Musteloidea. Mol Phylogenet Evol. 2009;53:907–922. doi: 10.1016/j.ympev.2009.08.019. [DOI] [PubMed] [Google Scholar]
  13. Wolsana M, Sato JJ. Effects of data incompleteness on the relative performance of parsimony and Bayesian approaches in a supermatrix phylogenetic reconstruction of Mustelidae and Procyonidae (Carnivora) Cladistics. 2010;26:168–194. doi: 10.1111/j.1096-0031.2009.00281.x. [DOI] [PubMed] [Google Scholar]
  14. Yu L, Liu J, Luan PT, Lee H, Lee M, Min MS, Ryder OA, Chemnick L, Davis H, Zhang YP. New insights into the evolution of intronic sequences of the beta-fibrinogen gene and their application in reconstructing mustelid phylogeny. Zool Sci. 2008;25:662–672. doi: 10.2108/zsj.25.662. [DOI] [PubMed] [Google Scholar]
  15. Yonezawa T, Nikaido M, Kohno N, Fukumoto Y, Okada N, Hasegawa M. Molecular phylogenetic study on the origin and evolution of Mustelidae. Gene. 2007;396:1–12. doi: 10.1016/j.gene.2006.12.040. [DOI] [PubMed] [Google Scholar]
  16. Wolsan M. Phylogeny and classification of early European Mustelida (Mammalia: Carnivora) Acta Theriol. 1993;38:345–384. [Google Scholar]
  17. Wolsan M. Oldest mephitine cranium and its implications for the origin of skunks. Acta Palaeontol Pol. 1999;44:223–230. [Google Scholar]
  18. Wolsan M. Fossil-based minimum divergence dates for the major clades of musteloid carnivorans. Abstracts of Plenary, Symposium, Poster and Oral Papers Presented at Ninth International Mammalogical Congress (IMC 9) 2005. pp. 372–373.
  19. Creer S, Pook CE, Malhotra A, Thorpe RS. Optimal intron analyses in the trimeresurus radiation of Asian pitvipers. Syst Biol. 2006;55:57–72. doi: 10.1080/10635150500431213. [DOI] [PubMed] [Google Scholar]
  20. Beltrán M, Jiggins CD, Bull V, Linares M, Mallet J, McMillan WO, Bermingham E. Phylogenetic discordance at the species boundary: comparative gene genealogies among rapidly radiating Heliconius butterflies. Mol Biol Evol. 2002;19:2176–2190. doi: 10.1093/oxfordjournals.molbev.a004042. [DOI] [PubMed] [Google Scholar]
  21. Matthee CA, Eick G, Willows-Munro S, Montgelard C, Pardini AT, Robinson TJ. Indel evolution of mammalian introns and the utility of non-coding nuclear markers in eutherian phylogenetics. Mol Phylogenet Evol. 2007;42:827–837. doi: 10.1016/j.ympev.2006.10.002. [DOI] [PubMed] [Google Scholar]
  22. Möller-Krull M, Delsuc F, Churakov G, Marker C, Superina M, Brosius J, Douzery EJ, Schmitz J. Retroposed elements and their flanking regions resolve the evolutionary history of xenarthran mammals (armadillos, anteaters, and sloths) Mol Biol Evol. 2007;24:2573–2582. doi: 10.1093/molbev/msm201. [DOI] [PubMed] [Google Scholar]
  23. Dalebout ML, Steel D, Baker CS. Phylogeny of the beaked whale genus Mesoplodon (Ziphiidae: Cetacea) revealed by nuclear introns: implications for the evolution of male tusks. Syst Biol. 2008;57:857–875. doi: 10.1080/10635150802559257. [DOI] [PubMed] [Google Scholar]
  24. Schröder C, Bleidorn C, Hartmann S, Tiedemann R. Occurrence of Can-SINEs and intron sequence evolution supports robust phylogeny of pinniped carnivores and their terrestrial relatives. Gene. 2009;448:221–226. doi: 10.1016/j.gene.2009.06.012. [DOI] [PubMed] [Google Scholar]
  25. Friesen V. In: Molecular Methods in Ecology. Baker AJ, editor. Oxford: Blackwell Science Ltd; 2000. Introns; pp. 274–294. [Google Scholar]
  26. Friesen VL, Congdon BC, Walsh HE, Birt TP. Intron variation in marbled murrelets detected using analyses of single-stranded conformational polymorphisms. Mol Ecol. 1997;6:1047–1058. doi: 10.1046/j.1365-294X.1997.00277.x. [DOI] [PubMed] [Google Scholar]
  27. Yu L, Luan PT, Jin W, Ryder OA, Chemnick LG, Davis HA, Zhang YP. Phylogenetic Utility of Nuclear Introns in Interfamilial Relationships of Caniformia (Order Carnivora) Syst Biol. 2011;60:175–187. doi: 10.1093/sysbio/syq090. [DOI] [PubMed] [Google Scholar]
  28. Jurka J, Zietkiewicz E, Labuda D. Ubiquitous mammalian-wide interspersed repeats (MIRs) are molecular fossils from the mesozoic era. Nucleic Acids Res. 1995;23:170–175. doi: 10.1093/nar/23.1.170. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Smit AF, Riggs AD. MIRs are classic, tRNA-derived SINEs that amplified before the mammalian radiation. Nucleic Acids Res. 1995;23:98–102. doi: 10.1093/nar/23.1.98. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Waterston RH, Lander ES, Sulston JE. On the sequencing of the human genome. Proc Natl Acad Sci USA. 2002;99:3712–3716. doi: 10.1073/pnas.042692499. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Minnick MF, Stillwell LC, Heineman JM, Stiegler GL. A highly repetitive DNA sequence possibly unique to canids. Gene. 1992;110:235–238. doi: 10.1016/0378-1119(92)90654-8. [DOI] [PubMed] [Google Scholar]
  32. Coltman DW, Wright JM. Can SINEs: a family of tRNA-derived retroposons specific to the superfamily Canoidea. Nucleic Acids Res. 1994;22:2726–2730. doi: 10.1093/nar/22.14.2726. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. van der Vlugt HH, Lenstra JA. SINE elements of carnivores. Mamm Genome. 1995;6:49–51. doi: 10.1007/BF00350894. [DOI] [PubMed] [Google Scholar]
  34. Das M, Chu LL, Ghahremani M, Abrams-Ogg T, Roy MS, Housman D, Pelletier J. Characterization of an abundant short interspersed nuclear element (SINE) present in Canis familiaris. Mamm Genome. 1998;9:64–69. doi: 10.1007/s003359900681. [DOI] [PubMed] [Google Scholar]
  35. Pecon-Slattery J, Pearks Wilkerson AJ, Murphy WJ, O'Brien SJ. Phylogenetic assessment of introns and SINEs within the Y chromosome using the cat family felidae as a species tree. Mol Biol Evol. 2004;21:2299–2309. doi: 10.1093/molbev/msh241. [DOI] [PubMed] [Google Scholar]
  36. Zehr SM, Nedbal MA, Flynn JJ. Tempo and mode of evolution in an orthologous Can SINE. Mamm Genome. 2001;12:38–44. doi: 10.1007/s003350010224. [DOI] [PubMed] [Google Scholar]
  37. Vassetzky NS, Kramerov DA. CAN--a pan-carnivore SINE family. Mamm Genome. 2002;13:50–57. doi: 10.1007/s00335-001-2111-1. [DOI] [PubMed] [Google Scholar]
  38. Yu L, Zhang YP. Evolutionary implications of multiple SINE insertions in an intronic region from diverse mammals. Mamm Genome. 2005;16:651–660. doi: 10.1007/s00335-004-2456-3. [DOI] [PubMed] [Google Scholar]
  39. Nikaido M, Matsuno F, Hamilton H, Brownell RL, Cao Y, Ding W, Zuoyan Z, Shedlock AM, Fordyce RE, Hasegawa M, Okada N. Retroposon analysis of major cetacean lineages: the monophyly of toothed whales and the paraphyly of river dolphins. Proc Natl Acad Sci USA. 2001;98:7384–7389. doi: 10.1073/pnas.121139198. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Kawai K, Nikaido M, Harada M, Matsumura S, Lin LK, Wu Y, Hasegawa M, Okada N. Intra- and interfamily relationships of Vespertilionidae inferred by various molecular markers including SINE insertion data. J Mol Evol. 2002;55:284–301. doi: 10.1007/s00239-002-2326-0. [DOI] [PubMed] [Google Scholar]
  41. Sasaki T, Takahashi K, Nikaido M, Miura S, Yasukawa Y, Okada N. First application of the SINE (short interspersed repetitive element) method to infer phylogenetic relationships in reptiles: an example from the turtle superfamily Testudinoidea. Mol Biol Evol. 2004;21:705–715. doi: 10.1093/molbev/msh069. [DOI] [PubMed] [Google Scholar]
  42. Nikaido M, Hamilton H, Makino H, Sasaki T, Takahashi K, Goto M, Kanda N, Pastene LA, Okada N. Baleen whale phylogeny and a past extensive radiation event revealed by SINE insertion analysis. Mol Biol Evol. 2006;23:866–873. doi: 10.1093/molbev/msj071. [DOI] [PubMed] [Google Scholar]
  43. Nishihara H, Smit AF, Okada N. Functional noncoding sequences derived from SINEs in the mammalian genome. Genome Res. 2006;16:864–874. doi: 10.1101/gr.5255506. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Joly S, Bruneau A. Incorporating allelic variation for reconstructing the evolutionary history of organisms from multiple genes: An example from Rosa in North America. Syst Biol. 2006;55:623–636. doi: 10.1080/10635150600863109. [DOI] [PubMed] [Google Scholar]
  45. Ané C, Larget B, Baum DA, Smith SD, Rokas A. Bayesian estimation of concordance among gene trees. Mol Phylogenet Evol. 2007;24:412–426. doi: 10.1093/molbev/msl170. [DOI] [PubMed] [Google Scholar]
  46. Rokas A, Carroll S. Bushes in the tree of life. Plos Biol. 2006;4:1899–1904. doi: 10.1371/journal.pbio.0040352. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Baryshnikov GF, Abramov AV. Structure of baculum (os penis) in Mustelidae (Mammalia, Carnivora). Communication 1. Zoo Zh. 1997;76:1399–1410. in Russian. [Google Scholar]
  48. Baryshnikov GF, Abramov AV. Structure of baculum (os penis) in Mustelidae (Mammalia, Carnivora). Communication 2. Zoo Zh. 1998;77:231–236. in Russian. [Google Scholar]
  49. Nie W, Wang J, O'Brien PCM, Fu B, Ying T, Ferguson-Smith MA, Yang F. The genome phylogeny of domestic cat, red panda and five mustelid species revealed by comparative chromosome painting and G-banding. Chromosome Res. 2002;10:209–222. doi: 10.1023/A:1015292005631. [DOI] [PubMed] [Google Scholar]
  50. Durando CM, Baker RH, Etges WJ, Heed EW, Wasserman M, Desalle R. Phylogenetic analysis of the repleta species group of the Genus Drosophila using multiple sources of characters. Mol Phylogenet Evol. 2000;16:296–307. doi: 10.1006/mpev.2000.0824. [DOI] [PubMed] [Google Scholar]
  51. Goto SG, Kimura MT. Phylogenetic utility of mitochondrial COI and nuclear Gpdh genes in Drosophila. Mol Phylogenet Evol. 2001;18:404–422. doi: 10.1006/mpev.2000.0893. [DOI] [PubMed] [Google Scholar]
  52. Giannasi N, Malhotra A, Thorpe RS. Nuclear and mtDNA phylogenies of the Trimeresurus complex: implications for the gene versus species tree debate. Mol Phylogenet Evol. 2001;19:57–66. doi: 10.1006/mpev.2001.0899. [DOI] [PubMed] [Google Scholar]
  53. Yu L, Li QW, Ryder OA, Zhang YP. Phylogeny of the bears (Ursidae) based on nuclear and mitochondrial genes. Mol Phylogenet Evol. 2004;32:480–494. doi: 10.1016/j.ympev.2004.02.015. [DOI] [PubMed] [Google Scholar]
  54. Nei M. Molecular evolutionary genetics. New York: Columbia University Press; 1987. [Google Scholar]
  55. Pamilo P, Nei M. Relationships between gene trees and species trees. Mol Biol Evol. 1988;4:526–543. doi: 10.1093/oxfordjournals.molbev.a040517. [DOI] [PubMed] [Google Scholar]
  56. Wu C-I. Inferences of species phylogeny in relation to segregation of ancient polymorphisms. Genetics. 1991;127:429–435. doi: 10.1093/genetics/127.2.429. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Moore WS. Inferring phylogenies from mtDNA variation: Mitochondrial gene trees versus nuclear gene trees. Evolution. 1995;49:718–726. doi: 10.2307/2410325. [DOI] [PubMed] [Google Scholar]
  58. Bininda-Emonds ORP, Gittleman JL, Purvis A. Building large trees by combining phylogenetic information: A complete phylogeny of the extant Carnivora (Mammalia) Biol Rev. 1999;74:143–175. doi: 10.1017/S0006323199005307. [DOI] [PubMed] [Google Scholar]
  59. Eizirik E, Murphy WJ, Koepfli KP, Johnson WE, Dragoo JW, Wayne RK, O'Brien SJ. Pattern and timing of diversification of the mammalian order Carnivora inferred from multiple nuclear gene sequences. Mol Phylogenet Evol. 2010;56:49–63. doi: 10.1016/j.ympev.2010.01.033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Steininger FF. In: The Miocene Land Mammals of Europe. Rossner GE, Heissig K, editor. Munich: Verlag Dr. Friedrich Pfeil; 1999. Chronostratigraphy, geochronology and biochronology of the Miocene "European Land Mammal Mega-Zones" (ELMMZ) and the Miocene "Mammal-Zones (MN-Zones)"; pp. 9–24. [Google Scholar]
  61. Schlunegger F, Burbank DW, Matter A, Engesser B, Modden C. Magnetostraitigraphic calibration of the Oligocene to Middle Miocene (30-15 Ma) mammal biozones and depositional sequences of the Swiss Molasse Basin. Eclogae Geol Helv. 1996;89:753–788. [Google Scholar]
  62. Morlo M Kundrát M The first carnivoran fauna from the Ruscinium (Early Pliocene, MN 15) of Germany Paléontol Z 200175163–187.21541755 [Google Scholar]
  63. Hosoda T, Suzuki H, Harada M, Tsuchiya K, Han S-H, Zhang Y-P, Kryukov AP, Lin L-K. Evolutionary trends of the mitochondrial lineage differentiation in species of genera Martes and Mustela. Genes Genet Syst. 2000;75:259–267. doi: 10.1266/ggs.75.259. [DOI] [PubMed] [Google Scholar]
  64. Wayne RK, Benveniste RE, Janczewski DN, O'Brien SJ. In: Carnivore Behavior, Ecology, and Evolution. Gittleman JL, editor. New York: Cornell University Press; 1989. Molecular and biochemical evolution of the Carnivora. [Google Scholar]
  65. Glazek J, Sulimski A, Wysoczanski-Minkowicz T. Proceedings of the 6th International Congress of Speleology, Olomouc-CSSR. Vol. 1. Prague; 1976. On the stratigraphic position of Weze 1 locality (Middle Poland) pp. 435–442. [Google Scholar]
  66. Glazek J, Szynkiewicz A. In: Przewodnik LII Zjazdu Polskiego Towarzystwa Geologicznego, Belchatow, 11-14 wrzesnia 1980. Barczyk WW, editor. Wydawnictwa Geologiczne; 1980. Kras; pp. 242–267. [Google Scholar]
  67. Möller-Krull M, Delsuc F, Churakov G, Marker C, Superina M, Brosius J, Douzery EJ, Schmitz J. Retroposed elements and their flanking regions resolve the evolutionary history of xenarthran mammals (armadillos, anteaters, and sloths) Mol Biol Evol. 2007;24:2573–2582. doi: 10.1093/molbev/msm201. [DOI] [PubMed] [Google Scholar]
  68. Benavides E, Baum R, McClellan D, Sites JW. Molecular phylogenetics of the lizard genus Microlophus (squamata:tropiduridae): aligning and retrieving indel signal from nuclear introns. Syst Biol. 2007;56:776–797. doi: 10.1080/10635150701618527. [DOI] [PubMed] [Google Scholar]
  69. Zardoya R, Meyer A. Phylogenetic performance of mitochondrial protein-coding genes in resolving relationships among vertebrates. Mol Biol Evol. 1996;13:933–942. doi: 10.1093/oxfordjournals.molbev.a025661. [DOI] [PubMed] [Google Scholar]
  70. Russo CAM, Takezaki N, Masatoshi N. Efficiencies of different genes and different tree-building methods in recovering a known vertebrate phylogeny. Mol Biol Evol. 1996;13:525–536. doi: 10.1093/oxfordjournals.molbev.a025613. [DOI] [PubMed] [Google Scholar]
  71. Miya M, Nishida M. Use of mitogenomic information in teleostean molecular phylogenetics: a tree-based exploration under the maximum parsimony optimality criterion. Mol Phylogenet Evol. 2000;17:437–455. doi: 10.1006/mpev.2000.0839. [DOI] [PubMed] [Google Scholar]
  72. Mueller RL. Evolutionary rates, divergence dates, and the performance of mitochondrial genes in Bayesian phylogenetic analysis. Syst Biol. 2006;55:289–300. doi: 10.1080/10635150500541672. [DOI] [PubMed] [Google Scholar]
  73. Yu L, Li YW, Ryder OA, Zhang YP. Analysis of complete mitochondrial genome sequences increases phylogenetic resolution of bears (Ursidae), a mammalian family that experienced rapid speciation. BMC Evol Biol. 2007;7:198. doi: 10.1186/1471-2148-7-198. [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Cunha RL, Grande C, Zardoya R. Neogastropod phylogenetic relationships based on entire mitochondrial genomes. BMC Evol Biol. 2009;9:210. doi: 10.1186/1471-2148-9-210. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Creer S. Choosing and using introns in molecular phylogenetics. Evol Bioinform. 2007;3:99–108. [PMC free article] [PubMed] [Google Scholar]
  76. Yu L, Li QW, Ryder OA, Zhang YP. Phylogenetic relationships within mammalian order Carnivora indicated by sequences of two nuclear DNA genes. Mol Phylogenet Evol. 2004;33:694–705. doi: 10.1016/j.ympev.2004.08.001. [DOI] [PubMed] [Google Scholar]
  77. Yu L, Zhang YP. Phylogeny of the caniform carnivora: evidence from multiple genes. Genetica. 2006;127:65–79. doi: 10.1007/s10709-005-2482-4. [DOI] [PubMed] [Google Scholar]
  78. Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG. The clustalx windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 1997;24:4876–4882. doi: 10.1093/nar/25.24.4876. [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol. 2000;17:540–552. doi: 10.1093/oxfordjournals.molbev.a026334. [DOI] [PubMed] [Google Scholar]
  80. Tamura K, Dudley J, Nei M, Kumar S. MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Mol Biol Evol. 2007;24:1596–1599. doi: 10.1093/molbev/msm092. [DOI] [PubMed] [Google Scholar]
  81. Yu L, Zhang YP. Evolutionary implications of multiple SINE insertions in an intronic region from diverse mammals. Mamm Genome. 2005;16:651–660. doi: 10.1007/s00335-004-2456-3. [DOI] [PubMed] [Google Scholar]
  82. Swofford DL. PAUP*: Phylogenetic analysis using parsimony (* and Other Methods), Version 4. Sinauer Associates, Sunderland, Massachusetts; 2002. [Google Scholar]
  83. Ronquist F, Huelsenbeck JP. MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics. 2003;19:1572–1574. doi: 10.1093/bioinformatics/btg180. [DOI] [PubMed] [Google Scholar]
  84. Akaike H. A new look at the statistical model identification. IEEE Trans Autom contr. 1974;19:716–723. doi: 10.1109/TAC.1974.1100705. [DOI] [Google Scholar]
  85. Posada D, Buckley TR. Model selection and model averaging in phylogenetics: advantages of akaike information criterion and bayesian approaches over likelihood ratio tests. Syst Biol. 2004;53:793–808. doi: 10.1080/10635150490522304. [DOI] [PubMed] [Google Scholar]
  86. Posada D, Crandall KA. MODELTEST: testing the model of DNA substitution. Bioinformatics. 1998;14:817–818. doi: 10.1093/bioinformatics/14.9.817. [DOI] [PubMed] [Google Scholar]
  87. Felsenstein J. Confidence limits on phylogenies: An approach using the bootstrap. Evolution. 1985;39:783–791. doi: 10.2307/2408678. [DOI] [PubMed] [Google Scholar]
  88. Stamatakis A, Hoover P, Rougemont J. A rapid bootstrap algorithm for the RAxML Web servers. Syst Biol. 2008;57:758–771. doi: 10.1080/10635150802429642. [DOI] [PubMed] [Google Scholar]
  89. Larget B, Simon DL. Markov chain Monte Carlo algorithms for the Bayesian analysis of phylogenetic trees. Mol Biol Evol. 1999;16:750–759. [Google Scholar]
  90. Joly S, Bruneau A. Incorporating allelic variation for reconstructing the evolutionary history of organisms from multiple genes: An example from Rosa in North America. Syst Biol. 2006;55:623–636. doi: 10.1080/10635150600863109. [DOI] [PubMed] [Google Scholar]
  91. Drummond AJ, Rambaut A. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol. 2007;7:214. doi: 10.1186/1471-2148-7-214. [DOI] [PMC free article] [PubMed] [Google Scholar]
  92. Luterbacher HP, Ali JR, Brinkhuis H, Gradstein FM, Hooker JJ, Monechi S, Ogg JG, Powell J, Röhl U, Sanfilippo A, Schmitz B. In: A Geologic Time Scale. Gradstein FM, Ogg JG, Smith AG, editor. Cambridge: Cambridge University Press; 2004. The Paleogene Period; pp. 384–408. [Google Scholar]
  93. Fortelius M, Werdelin L, Andrews P, Bernor RL, Gentry A, Humphrey L, Mittmann H-W, Viratana S. In: The evolution of western Eurasian Neogene mammal faunas. Bernor RL, Fahlbusch V, Mittmann H-V, editor. New York: Columbia University Press; 1996. Provinciality, diversity, turnover, and paleoecology on land mammal faunas of the later Miocene of Western Eurasia. [Google Scholar]
  94. Rambaut A, Drummond AJ. Tracer v1.5. 2007. http://beast.bio.ed.ac.uk/Tracer
  95. Shimodaira H, Hasegawa M. Multiple Comparisons of Log-Likelihoods with Applications to Phylogenetic Inference. Mol Biol Evol. 1999;6:1114–1116. [Google Scholar]
  96. Shimodaira H. An approximately unbiased test of phylogenetic tree selection. Syst Biol. 2002;51:492–508. doi: 10.1080/10635150290069913. [DOI] [PubMed] [Google Scholar]
  97. Shimodaira H, Hasegawa M. CONSEL: for assessing the confidence of phylogenetic tree selection. Bioinformatics. 2001;17:1246–1247. doi: 10.1093/bioinformatics/17.12.1246. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Additional file 1

Phylogenetic relationships of Mustelidae based on the analyses of 17 single introns. The IIAHs within a species was shown as 1 and 2. All trees shown were reconstructed using Bayesian method. Posterior probabilities (PP) are shown above internal nodes.

Click here for file (353.5KB, DOC)
Additional file 2

Phylogenetic relationships of Mustelidae based on the Bayesian concordance analysis (BCA) of the nuclear intron gene datasets and the nuclear plus the mt genome datasets. The concordance factors (CFs) from the nuclear intron gene analysis and the nuclear plus the mt genome analysis are shown above internal nodes.

Click here for file (2.5MB, DOC)
Additional file 3

Phylogenetic relationships of Mustelidae based on the analyses of 13 individual protein-coding genes, 2 individual rRNA genes, 22 tRNAs, combined protein-coding genes, combined rRNA genes, and combined tRNA genes. All trees shown were reconstructed using Bayesian method. Posterior probabilities (PP) are shown above internal nodes.

Click here for file (448KB, DOC)
Additional file 4

Comparisons of phylogenetic performances of mt genes among studies.

Click here for file (24.5KB, XLS)
Additional file 5

Detailed information of 14 nuclear intron loci that were first used in the Mustelidae phylogeny.

Click here for file (25.5KB, XLS)
Additional file 6

The species examined in this study and their Genbank accession numbers.

Click here for file (30KB, XLS)

Articles from BMC Evolutionary Biology are provided here courtesy of BMC

RESOURCES