15 Oct 2015: Jiang L, Chen J, Wang P, Ren Q, Yuan J, et al. (2015) Correction: The Mitochondrial Genomes of Aquila fasciata and Buteo lagopus (Aves, Accipitriformes): Sequence, Structure and Phylogenetic Analyses. PLOS ONE 10(10): e0141037. https://doi.org/10.1371/journal.pone.0141037 View correction
The family Accipitridae is one of the largest groups of non-passerine birds, including 68 genera and 243 species globally distributed. In the present study, we determined the complete mitochondrial sequences of two species of accipitrid, namely Aquila fasciata and Buteo lagopus, and conducted a comparative mitogenome analysis across the family. The mitogenome length of A. fasciata and B. lagopus are 18,513 and 18,559 bp with an A + T content of 54.2% and 55.0%, respectively. For both the two accipitrid birds mtDNAs, obvious positive AT-skew and negative GC-skew biases were detected for all 12 PCGs encoded by the H strand, whereas the reverse was found in MT-ND6 encoded by the L strand. One extra nucleotide‘C’is present at the position 174 of MT-ND3 gene of A. fasciata, which is not observed at that of B. lagopus. Six conserved sequence boxes in the Domain II, named boxes F, E, D, C, CSBa, and CSBb, respectively, were recognized in the CRs of A. fasciata and B. lagopus. Rates and patterns of mitochondrial gene evolution within Accipitridae were also estimated. The highest dN/dS was detected for the MT-ATP8 gene (0.32493) among Accipitridae, while the lowest for the MT-CO1 gene (0.01415). Mitophylogenetic analysis supported the robust monophyly of Accipitriformes, and Cathartidae was basal to the balance of the order. Moreover, we performed phylogenetic analyses using two other data sets (two mitochondrial loci, and combined nuclear and mitochondrial loci). Our results indicate that the subfamily Aquilinae and all currently polytypic genera of this subfamily are monophyletic. These two novel mtDNA data will be useful in refining the phylogenetic relationships and evolutionary processes of Accipitriformes.
Citation: Jiang L, Chen J, Wang P, Ren Q, Yuan J, Qian C, et al. (2015) The Mitochondrial Genomes of Aquila fasciata and Buteo lagopus (Aves, Accipitriformes): Sequence, Structure and Phylogenetic Analyses. PLoS ONE 10(8): e0136297. https://doi.org/10.1371/journal.pone.0136297
Editor: Bi-Song Yue, Sichuan University, CHINA
Received: June 1, 2015; Accepted: August 2, 2015; Published: August 21, 2015
Copyright: © 2015 Jiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Data Availability: All mito-genome sequences files are available from the GenBank (accession numbers: KP329567, KP337337).
Funding: This work was funded by (1) the Key Programme of Natural Science Foundation of the Anhui Higher Education Institutions (no. KJ2013A127), Special to Prof. XK (website: http://220.127.116.11/Srmis/login.aspx), and (2) the Anhui Provincial Natural Science Foundation (no. 1308085MC38), Special to Prof. XK (website: http://www.ahinfo.gov.cn/zrkxjj/index.htm).
Competing interests: The authors have declared that no competing interests exist.
Bonelli’s eagle (Aquila fasciata) and Rough-legged buzzard (Buteo lagopus) are birds of prey of the hawk and eagle family (Accipitridae). A. fasciata, which previously was a member of the genus Hieraaetus, has a fragmented distribution from Mediterranean basin to India, south of China, and Indochina . B. lagopus, also called Rough-legged hawk, is a widespread bird of prey. In China, these two species are protected species, and listed in the first category of National Key Protected Wild Animals. The family Accipitridae (hawks, eagles, and kites), with other four families (Cathatidae, Pandionidae, Sagittariidae, and Falconidae), was traditionally classified within the order Falconiformes[2–4]. The monophyly of Falconiformes was supported by some morphological classifications[4–6]. However, recent comprehensive genetic analyses disprove any close phylogenetic relationship between the Falconidae and other families included in the order Falconiformes [7–10]. Based on the proposals of Hackett et al. and the South American Classification Committee(SACC), the Falconiformes is now restricted to include only the family Falconidae, and the remaining four families are put in the separate order Accipitriformes[1,11,12]. The family Accipitridae is one of the largest groups of non-passerine birds, including 68 genera and 243 species globally distributed . Within the 68 genera of Accipitridae, 36 are monotypic, and 32 are polytypic. This family has been variously divided into three to fourteen subfamilies[13–17]. Peters(1931) recognized eight subfamilies within Accipitridae. Lerner and Mindell (2005)  accepted that the Accipitridae consisted of fourteen subfamilies (Accipitrinae, Aegypiinae, Aquilinae, Buteoninae, Circaetinae, Circinae, Elaninae, Gypaetinae, Haliaeetinae, Harpiinae, Melieraxinae, Milvinae, Perninae, and Polyboroidinae). Griffiths et al. (2007)  found that the family included eight major lineages (Elanini, Gypaetina, Pernina, Circaetina, Gypina, Harpiita, Aquilita, and Accipitrita), which they named using tribe, subtribe, and infratribe ranks.
The aquiline eagles (Aquilinae), one of the largest accipitrid groups, traditionally include 35–36 species in six monotypic genera (Ictinaetus, Lophaetus, Oroaetus, Polemaetus, Spizastur, and Stephanoaetus) and three polytypic genera (Aquila, Hieraaetus, and Spizaetus) . There is no doubt about the monophyly of aquiline eagles [13,18]. However, all three polytypic genera (Aquila, Hieraaetus, and Spizaetus) turned out to be paraphyletic[14,17–21]. The three spotted eagles (A. clanga, A. hastata, and A. pomarina) were treated as a new genus Clanga [22,23], which formed a clade sister to Ictinaetus and to Lophaetus. Because Spizastur merged into Spizaetus [18,24], the former should be moved to the latter [1,12]. Based on the phylogenetic analysis of MT-CYB (mitochondrially encoded cytochrome b) and control region sequences, Haring et al.  proposed the following four suggestions: (1) the monotypic genus Oroaetus should be moved to Spizaetus, (2) the Old World species of Spizaetus were separated into Nisaetus, (3) Cassin’s hawk-eagle was moved from Spizaetus to Aquila, and (4) Rufous-bellied hawk-eagle was separated from Hieraaetus into the monotypic genus Lophotriorchis. So, in the present study, we recognize aquiline eagles as 39 species in five monotypic genera (Ictinaetus, Lophaetus, Lophotriorchis, Polemaetus, and Stephanoaetus) and five polytypic genera (Aquila, Clanga, Hieraaetus, Nisaetus, and Spizaetus), respectively. The extensive molecular data, with full complete taxonomic representation, are urgently needed to reassess the monophyly of currently polytypic genera of Aquiline eagles. Typical metazoan mitochondrial genomes are double-stranded, circular molecules, 16–20 kb in length, and typically include 13 protein-coding genes, 22 tRNA genes, two rRNA genes, as well as one control region (CR). Compared with the nuclear genome, the mitochondrial genome has several intrinsic characteristics, such as small genome, maternal inheritance mode and fast substitution rate. Mitochondrial genomes have been proposed to show potential in resolving ancient patterns of evolutionary history . Recently, a number of studies performed using mitochondrial genome sequences to elucidate avian phylogeny[25–35]. For example, Here, we present the complete mitochondrial genomes of Bonelli’s eagle and Rough-legged hawk. Based on new data generated from A. fasciata, B. lagopus and existing sequence data from GenBank, we tried to address: (1) features of the mitogenomes of A. fasciata and B. lagopus, (2) rates and patterns of mitochondrial gene evolution within Accipitridae, and (3) the monophyletic status of currently recognized polytypic genera of Aquilinae.
Materials and Methods
Sample collection and DNA extraction
The frozen muscle tissue samples of A. fasciata (code Kan-K0318) and B. lagopus (code Kan-K0381) were provided by the Ningguo Museum of Natural History (NMNH), Anhui Province, China. NMNH is authorized to collect specimens. Tissues were stored at -20°C at the College of Life Sciences, Anhui Normal University, China. Total genomic DNA of these specimens were extracted from the muscle tissue following the method of Sambrook and Russell (2001) .
PCR amplification and sequencing
The PCR primers and several internal primers (S1 Table) used in PCR amplification or sequencing were designed based on available mitochondrial sequences of Accipitriformes. Each primer set amplified a mtDNA fragment, including an overlap region of at least 100 bp with its adjacent amplified fragments at both the terminals. Long PCR and nested-PCR were performed as described by Kan et al. . The amplified fragments were purified using TIANgel Midi Purification Kit (Tiangen Biotech Co., Ltd, Beijing, China). The purified PCR products were sequenced directly on ABI-PRISM 3730 sequencer using BigDye Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems) with their corresponding primers.
Genome assembly and annotation
DNA sequences were analyzed using software BioEdit  and Ugene . Contig assembly was performed with the program Sequencher 4.14 (Gene Codes Corporation, Ann Harbor, USA). The boundaries of protein-coding genes and rRNA genes were initially identified via the MITOS  and DOGMA  webservers, and refined by alignment with mitochondrial genomes of other species of Accipitriformes. Transfer RNA genes were identified using tRNAscan-SE v.1.21  and ARWEN v.1.2 . The whole-mtgenome comparison maps were visualized using the software CGView Comparison Tool (CCT) . All gene names included mitochondrial and nuclear gene are in accordance with the HUGO Gene Nomenclature Committee’s database (HGNC) .
Sequence alignment and Rate heterogeneity
Sequence alignment was carried out using MAFFT 7.2  with the default settings. The nucleotide bias, skew can be calculated as (G − C) / (G + C) or (A − T) / (A + T). The rates (number of variable sites, ratio of nonsynonymous-to-synonymous substitutions rates (dN/dS)) and patterns (Transition-to-transversion (ts/tv) ratio) of evolution for each gene were calculated in the present study. Number of variable sites was conducted using DnaSP ver. 5.10 . dN/dS was performed with Datamonkey. ts/tv was estimated by MEGA ver. 6.06 .
To investigate the evolutionary relationships among A. fasciata, B. lagopus and their related species, three data sets were performed with the maximum likelihood (ML) and the Bayesian inference (BI) methods: (1) for mitogenomic phylogeny of Accipitriformes data set, 13 PCGs of 16 Accipitriformes species were used (Table 1), with two species from Strigiformes (Phodilus badius, NC_023787; Strix leptogrammica, NC_021970) as the outgroups,(2) for phylogeny of Accipitridae data set, two mitochondrial genes (MT-CYB and MT-ND2 (mitochondrially encoded NADH dehydrogenase 2)) of 148 species from Accipitridae were used (S2 Table), and (3) for phylogeny of Aquilinae data set, available multiple sequences of four mtDNA loci (MT-CYB, MT-ND2, MT-CO1 (mitochondrially encoded cytochrome c oxidase I) and CR) and five nuclear loci (RAG1 (recombination activating gene 1) coding region, LDH (lactate dehydrogenase) intron 3, MYC (v-myc avian myelocytomatosis viral oncogene homolog), AK1 (adenylate kinase 1) exon 6, FIB7 (beta-fibrinogen gene, intron 7)) of all 39 species in this subfamily from GenBank were used (S3 Table), with Morphnus guianensis and Harpia harpyja as the outgroups. Codon positions included in the analysis were the 1st, 2nd and 3rd. Sequence alignment was carried out using MAFFT 7.2  with the default settings. Sequence format convertion was performed with DAMBE 5.5 . To check for saturation in nucleotide codons, substitution saturation analysis  was performed for subsets with the first, second and third codon positions using DAMBE 5.5. According to the results, none of the substitutions from three codon positions of all protein-coding genes in our two data sets were saturated. The best-fit models were selected using Bayesian Information Criterion (BIC) as implemented in ModelGenerator version 0.85. For 13 PCGs mitogenome nucleotides data set, we defined the independent mitochondrial partitions as each of the 13 loci. For combined mitochondrial and nuclear data set, we defined independent partitions as each of the 9 loci.
The ML analyses were conducted in RAxML v.8.0.26 , as implemented in the graphical user interface RaxML GUI v.1.3.1 . We performed analyses with ML + slow bootstrap for ten runs and 1000 replicates under GTR + CAT  model. Due to lower computational and memory costs, CAT, which is a rate heterogeneity and fast approximation of the gamma model, appears to yield better log likelihood scores even when calculated under a real gamma model [54,55]. Under the GTR + CAT model, the default number of categories (c = 25) and random starting trees were employed.
The BI analyses were performed with MrBayes 3.2.2 , applying independent models of evolution for each partition. For 13 PCGs nucleotides data set, GTR + G was chosen for MT-ND4 (mitochondrially encoded NADH dehydrogenase 4), HKY+I+G was chosen for MT-ND1 (mitochondrially encoded NADH dehydrogenase 1), HKY+G was chosen for MT-ATP8 (mitochondrially encoded ATP synthase 8), MT-ND3 (mitochondrially encoded NADH dehydrogenase 3) and MT-ND4L (mitochondrially encoded NADH dehydrogenase 4L), while GTR + I + G for the remaining 10 loci. For combined mitochondrial and nuclear data set, GTR + I + G was chosen for MT-CYB, MT-ND2, and MT-CO1, while GTR + G for the remaining six loci were selected as the best substitution model for the 1st, 2nd, and 3rd codon positions, respectively. Four Markov chains were run for ten million generations (sampling every 100 generations) allowing adequate time for convergence. After discarding 25% of the initial trees as burn-in, the remaining trees were used to estimate 50% majority rule consensus tree and Bayesian posterior probabilities (BPP). All MCMC runs were repeated twice to confirm consistent approximation of the posterior parameter distributions. PSRF (potential scale reduction factor) is close to 1 as runs converge, and the ESS (effective sample sizes) for all parameters are above 200.
Results and Discussion
Features of the mitogenomes of A. fasciata and B. lagopus
The complete mitochondrial genomes (mt-genomes) of A. fasciata and B. lagopus were determined to be 18,513 and 18,559 bp in length, respectively. These are close to the other Accipitriformes mt-genomes sizes reported (S4 Table). The two sequences were deposited in GenBank (A. fasciata: KP329567 and B. lagopus: KP337337). The number and order of 37 mitochondrial genes and two control regions (CR and ΨCR (pseuo control region)) of both A. fasciata and B. lagopus are identical (Fig 1A, and S5 Table). The nucleotide compositions of the complete mtDNA sequences (Heavy-strand) of A. fasciata and B. lagopus are slightly biased toward A and T (S4 Table), which is similar to that from other avian species[28,29,35]. Comparative analyses of the nucleotide sequences of each mt gene (excluded tRNA genes) and non-coding regions, together with the amino acid sequences, are given in Table 2. The sequence lengths of 13 PCGs were the same for A. fasciata and B. lagopus, except for MT-ND3 gene (Table 2). One extra nucleotide ‘C’ is present at the position 174 of MT-ND3 gene of A. fasciata, which is not observed at that of B. lagopus. In mitochondrial MT-ND3 for 16 species of Accipitriformes (Fig 2), 6 have the extra base, whereas 10 lack it. Additional putative frameshift sites have been proposed in the mitochondrial of many birds, turtles and ants[28,29,35,57–59]. Mindell el al.  suggested that the site was subject to a +1 programmed frameshit during translation, allowing correct translational of functional protein. We also found that the extra base insertion appear to be dynamically gained and lost from the MT-ND3 of closely related taxa, such as the MT-ND3 of A. fasciata and A. chrysaetos. So, we infered that there was no evolutionary significance for the extra insertion site.
(A) Graphical map of the BLAST results showing nucleotide identity between A. fasciata mitogenome and 15 related species listed in Table 1, as generated by the CGView comparison tool (CCT). CCT arranges BLAST result in an order where sequence that is most similar to the reference (A. fasciata) is placed closer to the outer edge of the map. The rings labelled 1 to17 indicate BLAST results of A. fasciata mitogenome against A. chrysaetos, N. nipalensis, N. alboniger, S. cheela, A. monachus, B. lagopus, B. buteo, B. buteo burmanicus, A. soloensis, A. virgatus, A. gentilis, A. nisus, P. haliaetus, S. serpentarius, C. aura, P. badius, and S. leptogrammica, respectively. (B) Nucleotide-based phylogenetic tree of 16 Accipitriformes species, with two Strigiformes birds as outgroups. This analysis is based on 13PCGs. Both ML and Bayesian analyses produced identical tree topologies. The ML bootstrap and Bayesian posterior probability values for each node are indicated.
MT-ND3 for A. nisus, A. monachus, A. fasciata, C. aura, P. haliaetus, S. serpentarius with and for the other 10 species without the extra base.
In addition, for both A. fasciata and B. lagopus mtDNAs, obvious positive AT-skew and negative GC-skew biases were detected for all 12 PCGs encoded by the H strand, whereas the reverses were found in MT-ND6 (mitochondrially encoded NADH dehydrogenase 6) encoded by the L strand (Fig 3). The nucleotide variation across the entire genome sequence between the two accipitrid species was 19.07%. The values of nucleotide sequence difference in 13 PCGs and two RNA genes between A. fasciata and B. lagopus ranged from 9.54% (MT-CO3 (mitochondrially encoded cytochrome c oxidase III)) to 22.02% (MT-ATP8) (Table 2). The amino acid sequence differences ranged from 3.45 to 34.55%, with MT-ND3 being the most conserved PCG and MT-ATP8 the least conserved. Like other Accipitriformes species (expect for Cathartes aura and Sagittarius serpentarius) [34,60,61] (S4 Table), two putative control regions (CR and ΨCR) of A. fasciata and B. lagopus mitogenomes were found between MT-TT (mitochondrially encoded tRNA threonine) and MT-TF (mitochondrially encoded tRNA phenylalanine), and were separated by MT-TP (mitochondrially encoded tRNA proline), MT-ND6 and MT-TE (mitochondrially encoded tRNA glutamic acid) (Fig 1A). The length of CR of Accipitriformes species varies between 1,117 bp (S. serpentarius) and 2,329 bp (Accipiter nisus), with AT content ranging from 55.9% (A. monachus and Spilornis cheela) to 65.0% (A. nisus) (S4 Table).
AT skew and GC skew are calculated for each protein-coding gene and other gene regions.
Based on the distribution of the conserved motifs in other avian CRs [29,35,62,63], the CRs of the two accipitrid species could be divided into three domains: ETAS (extended termination-associated sequence) Domain I, Central Conserved Domain II and CSB (conserved sequence block) Domain III. Six conserved sequence boxes in the Domain II , named boxes F, E, D, C, CSBa, and CSBb, respectively, were recognized in the CRs of A. fasciata and B. lagopus. Nevertheless, conserved sequence box B was only found in the CR of A. fasciata (Fig 4). In the CR of B. lagopus, we observed three minisatellites, one was 23 nucleotides (5′-TTTATCATCATATTTTATTATTA) with six tandem repeats, and two were 11 nucleotides (5′-AAATTTTTACA, and 5′- AATTTATCATG) with 3 and 17 tandem repeats, correspondingly. Moreover, we only found one minisatellite, which was 22 nucleotides (5′-TTTTTTCACAATTTTTTCACAT) with two tandem repeats, in the CR of A. fasciata. The size, repeats, and sequence composition of minisatellite in Accipitriformes CRs might be served as useful genus- and species-specific molecular markers.
Positions of the conserved boxes and the division into the three domains Domain I (ETAS), Domain II (Central), Domain III (CSB) are shown. ETAS = extended termination-associated sequences; F through B boxes = conserved sequence boxes in the central domain, CSBa is highly conserved stretches that vary in length, while CSBb is more variable; CSB = conserved sequence block; CSB-like = a sequence similar to the CSB; LSP = light-strand transcription promoter; HSP = heavy-strand transcription promoter; twill box means the comparison of two CRs, the lack of base number.
Rates and patterns of mitochondrial gene evolution within Accipitridae
As can be seen in the CCT BLAST map, CR and ΨCR of these accipitrids are highly divergent (Fig 1A). Comparison of the evolutionary rate of different genes provides a better understanding of the patterns of molecular evolution of the mtDNA. Due to the length and sequence heterogeneity, CR and ΨCR sequences were not included in these analyses. Among the eleven mtDNA sequences (excluding CR and ΨCR), 5213 nucleotides sites (33.28%) are variable (Table 3). In the protein coding region, the most variable region of the genomes by percent variable sites is MT-ND3, followed by, MT-ATP8, MT-ND4 and MT-ND6. In contrast, the lowest one is tRNA genes (20.19%), followed by MT-RNR1 (mitochondrially encoded 12S RNA) and MT-RNR2 (mitochondrially encoded 16S RNA).
The ts/tv in the concatenated nucleotide data varies from MT-CYB (2.242) to tRNAs (6.640) (Table 3). As we know, transversions are typically rare in the slow-evolving regions, such as tRNA genes. However, the patterns (ts/tv) among protein-coding genes are variable and do not reflect differences in either synonymous or nonsynonymous rates among the genes [31,64]. For example, high ts/tv ratios were found for MT-CO1, MT-CO2 (mitochondrially encoded cytochrome c oxidase II), and MT-ND4L genes, which have intermediate rates in both these substitution categories. Furthermore, the highest dN/dS was detected for the MT-ATP8 gene (0.29896) among Accipitridae, while the lowest for the MT-CO1 gene (0.01546).
To infer mitophylogenetic relationships among accipitrids, evolutionary analysis was carried out using 13PCGs of 16 species, with two species of Strigiformes as outgroups. The ML and BI trees showed identical topologies (Fig 1B) [65–68]. The monophyly of Accipitridae was strongly supported (Fig 1B). New World vultures (Cathartidae) have some characters in common with storks, and a close phylogenetic relationship with storks was suggested [69–72]. However, recent molecular studies demonstrated that the New World vultures clearly have their affinity with other raptors and not with storks[7,8,21]. Our phylogeny indicated that C. aura (Cathartidae) was basal to the remaining of Accipitriformes. Based on relatively short sequences, Wink and Sauer-Gurth  placed Secretarybird (S. serpentarius) with storks. In our analysis, the Secretarybird is deepest on the branch with Osprey (Pandion haliaetus) and Accipitridae(Fig 1B). This result is in congruence with more and more recent studies, such as Lerner and Mindell, Mahmood et al. and Hackett et al.. Furthermore, P. haliaetus (Pandionidae) is the sister one to Accipitridae. The relationships among the four families of Accipitriformes is consistent with Burleigh et al.’ s results . There were three clades in Accipitridae. One was (Aegypius + Spilornis), one was (Aquila + Nisaetus), and the other was (Accipiter + Buteo). Aegypius is a member of Aegypiinae, while Spilornis is that of Circaetinae.
To test monophyly of Aquilinae, phylogenetic analysis was performed using MT-ND2 and MT-CYB genes for 60 genera and 148 species of Accipitridae, plus two species (S. serpentarius and P. haliaetus) as outgroups. There were a number of well-resolved basal clades within the family (Fig 5); the four most basal of these included: (1) a clade composed of monotypic genus Elanus (Elaninae), (2) a clade composed of Polyboroidinae, Perninae and Gypaetinae, (3) a clade that contained Circaetinae and Aegypiinae, and (4) a very large clade consisting of all remaining taxa. Within the last large clade, all species from aquiline eagles formed a robust monophyletic clade (Fig 5). Our results strongly support previous research on monophyly of Aquilinae[13,18]. Beyond recognizing the monophyly of Aquilinae, we also analysed phyloegentic relationships among and within subfamilies of Accipitridae. Our results were largely consistent with Jetz et al.’s phylogenetic trees (the trees for this are available online at http://birdtree.org/), but differed in the positions of Polyboroides typus, Accipiter striatus, Buteo nitidus, and Buteogallus lacernulatus (Fig 5).
ML bootstrap and Bayesian posterior probability values are presented above branches. Branch length and topology are taken from the ML analyses.
To reassess monophyly of polytypic genera from Aquilinae, a phylogenetic analysis was carried out by combining mitochondrial and nuclear loci for 39 birds, representing all species and all genera from this subfamily. Some taxa are sampled for many loci, while other taxa are only represented by two loci (S3 Table). To a large-scale, sparse supermatrix of sequence data currently available, Burleigh et al. demonstrated that it be sufficient to produce a robust estimate of the avian tree of life . So, in this analysis, we used the heterogeneous concatenated matrix data to infer phylogeny of Aquilinae. The ML and the BI methods generated identical topological trees (Fig 6). The monophyly of Clanga, Hieraaetus, Nisaetus and Spizaetus were strongly supported (>99% in ML, 1.00 in BI). The genus Nisaetus, previously the Old World birds of Spizaetus, was composed of two sister clades. Clade I included five species (N. alboniger, N. bartelsi, N. kelaarti, N. nanus and N. nipalensis), while Clade II harbored the remaining species of Nisaetus. The genus Aquila also consisted of two sister clades. Clade I was composed of four species (A. adalberti, A. heliaca, A. rapax, and A. nipalensis) (100% in ML, 1.00 in BI), while Clade II included the remaining birds of Aquila (97% in ML, 1.00 in BI). Notably, the monophyly of Aquila was weakly supported (63% in ML, 0.89 in BI). Based on above analyses, we recognize all currently polytypic genera of Aquilinae as monophyly.
Phylogenetic tree of the relationships based on the nucleotide sequences of the 4 mitochondrial protein-coding genes(MT-CYB, MT-ND2, MT-CO1, CR) and 5 nuclear genes (RAG1, LDH, MYC, AK1, FIB7). Branch length and topology are taken from the Bayesian inference analyses.
The complete mitochondrial sequences of A. fasciata and B. lagopus were found to be 18,513 and 18,559 bp with an A + T content of 54.2% and 55.0%, respectively. The genomes consist of 37 typical genes (13 energy pathway protein-coding genes, two ribosomal RNA genes and 22 transfer RNA genes)and two putative control regions (CR and ΨCR). The nucleotide variation across the entire genome sequence between the two accipitrid species was 19.07%. Obvious positive AT-skew and negative GC-skew biases were detected for all 12 PCGs encoded by the H strand, whereas the reverses were found in MT-ND6 encoded by the L strand. Six conserved sequence boxes in the Domain II, named boxes F, E, D, C, CSBa, and CSBb, respectively, were recognized in the CRs of A. fasciata and B. lagopus. The highest dN/dS was detected for the MT-ATP8 gene (0.29896) among Accipitridae, while the lowest for the MT-CO1 gene (0.01546). Mitophylogenetic analysis supported the robust monophyly of Accipitriformes, and Cathartidae was basal to the balance of the order. Moreover, our results indicate that the subfamily Aquilinae and all currently polytypic genera of this subfamily are monophyletic. These two novel mtDNA data will be useful in refining the phylogenetic relationships and evolutionary processes of Accipitriformes.
S1 Table. Primers used in amplifying the mitogenomes of Aquila fasciata and Buteo lagopus.
S2 Table. GenBank accession numbers (MT-CYB, MT-ND2) for the 148 Accipitriformes species in this study.
S3 Table. GenBank accession numbers (MT-CYB, MT-ND2, MT-CO1, CR, RAG1, LDH, MYC, AK1 and FIB7) for 39 Aquilinae species in this study.
S4 Table. Genomic characteristics of Accipitriformes mtDNAs.
The authors would like to thank Binghua Li, Xifeng Li and Lei Chen for assistance, suggestions and comments. We particularly thank T. Vines, J. Weir and three anonymous reviewers from AXIOS Review for comments on an earlier version of this manuscript.
Conceived and designed the experiments: LJ XK. Performed the experiments: LJ JC DB ZZ QW. Analyzed the data: LJ XK PW QR ZG LZ J. Yang YW QZ HD. Contributed reagents/materials/analysis tools: CQ XH J. Yuan DC. Wrote the paper: LJ XK.
- 1. Clements J, Schulenberg T, Iliff M, Roberson D, Fredericks TA, Sullivan BL, et al. (2014) The eBird/Clements checklist of birds of the world: Version 6.9. Avaliable: http://www.birds.cornell.edu/clementschecklist/download.
- 2. Cracraft J (1981) Toward a phylogenetic classification of the recent birds of the world (class Aves). The Auk 98: 681–714.
- 3. del Hoyo J, Elliot A, Sargatal J, editors (1994) Handbook of the birds of the world, vol. 2. Lynx Editions, Barcelona, pp. 434–557.
- 4. Livezey BC, Zusi RL (2007) Higher-order phylogeny of modern birds (Theropoda, Aves: Neornithes) based on comparative anatomy. II. Analysis and discussion. Zool J Linn Soc 149: 1–95. pmid:18784798
- 5. Livezey BC, Zusi RL (2001) Higher-Order Phylogenetics of Modern Aves Based On Comparative Anatomy. Neth J Zool 51: 179–205.
- 6. Mayr G, Clarke J (2003) The deep divergences of neornithine birds: a phylogenetic analysis of morphological characters. Cladistics 19: 527–553.
- 7. Burleigh JG, Kimball RT, Braun EL (2015) Building the avian tree of life using a large-scale, sparse supermatrix. Mol Phylogenet Evol 84: 53–63. pmid:25550149
- 8. Hackett SJ, Kimball RT, Reddy S, Bowie RC, Braun EL, Braun MJ, et al. (2008) A phylogenomic study of birds reveals their evolutionary history. Science 320: 1763–1768. pmid:18583609
- 9. Jarvis ED, Mirarab S, Aberer AJ, Li B, Houde P, Li C, et al. (2014) Whole-genome analyses resolve early branches in the tree of life of modern birds. Science 346: 1320–1331. pmid:25504713
- 10. Mahmood MT, McLenachan PA, Gibb GC, Penny D (2014) Phylogenetic position of avian nocturnal and diurnal raptors. Genome Biol Evol 6: 326–332. pmid:24448983
- 11. Chesser RT, Banks RC, Barker FK, Cicero C, Dunn JL, Kratter AW, et al. (2010) Fifty-first supplement to the American Ornithologists’ Union check-list of north American birds. The Auk 127: 726–744.
- 12. Gill F, Donsker D (2015) IOC World Bird List (v 5.1). Avaliable: http://www.worldbirdnames.org.
- 13. Amadon D, Bull J. Hawks and owls of the world: an annotated list of species; 1988. pp. 295–357.
- 14. Griffiths CS, Barrowclough GF, Groth JG, Mertz LA (2007) Phylogeny, diversity, and classification of the Accipitridae based on DNA sequences of the RAG-1 exon. J Avian Biol 38: 587–602.
- 15. Jollie MT (1977) A contribution to the morphology and phylogeny of the Falconiformes, part 2–3.—Evol. Theory 2: 115–300.
- 16. Lepage D, Warnier J (2014) The Peters’ Check-list of the Birds of the World (1931–1987) Database. Accessed on 08/01/2015 from Avibase, the World Database. Avaliable: http://avibase.bsc-eoc.org/peterschecklist.jsp.
- 17. Lerner HR, Mindell DP (2005) Phylogeny of eagles, Old World vultures, and other Accipitridae based on nuclear and mitochondrial DNA. Mol Phylogenet Evol 37: 327–346. pmid:15925523
- 18. Helbig AJ, Kocum A, Seibold I, Braun MJ (2005) A multi-gene phylogeny of aquiline eagles (Aves: Accipitriformes) reveals extensive paraphyly at the genus level. Mol Phylogenet Evol 35: 147–164. pmid:15737588
- 19. Nagy J, Tökölyi J (2014) Phylogeny, historical biogeography and the evolution of migration in accipitrid birds of prey (Aves: Accipitriformes). Ornis Hungarica 22: 15–35.
- 20. Ong PS, Luczon AU, Quilang JP, Sumaya AMT, Ibanez JC, Salvador DJ, et al. (2011) DNA barcodes of Philippine accipitrids. Mol Ecol Resour 11: 245–254. pmid:21429130
- 21. Wink M, Sauer-Gürth H (2004) Phylogenetic relationships in diurnal raptors based on nucleotide sequences of mitochondrial and nuclear marker genes. Raptors worldwide WWGBP, Berlin 483–498.
- 22. Gregory S, Dickinson E (2012) Clanga has priority over Aquiloides (or how to drop a clanger). Bulletin of the British Ornithologists’ Club 132: 135.
- 23. Wells DR, Inskipp T (2012) A proposed new genus of booted eagles (tribe Aquilini). Bulletin of the British Ornithologists’ Club 132: 70–72.
- 24. Haring E, Kvaløy K, Gjershaug JO, Røv N, Gamauf A (2007) Convergent evolution and paraphyly of the hawk‐eagles of the genus Spizaetus (Aves, Accipitridae)-phylogenetic analyses based on mitochondrial markers. J Zool Syst Evol Res 45: 353–365.
- 25. Kan XZ, Yang JK, Li XF, Chen L, Lei ZP, Wang M, et al. (2010) Phylogeny of major lineages of galliform birds (Aves: Galliformes) based on complete mitochondrial genomes. Genet Mol Res 9: 1625–1633. pmid:20730714
- 26. Gibb GC, Kardailsky O, Kimball RT, Braun EL, Penny D (2007) Mitochondrial genomes and avian phylogeny: complex characters and resolvability without explosive radiations. Mol Biol Evol 24: 269–280. pmid:17062634
- 27. Haring E, Kruckenhauser L, Gamauf A, Riesing MJ, Pinsker W (2001) The complete sequence of the mitochondrial genome of Buteo buteo (Aves, Accipitridae) indicates an early split in the phylogeny of raptors. Mol Biol Evol 18: 1892–1904. pmid:11557795
- 28. Kan XZ, Li XF, Lei ZP, Wang M, Chen L, Gao H, et al. (2010) Complete mitochondrial genome of Cabot’s tragopan, Tragopan caboti (Galliformes: Phasianidae). Genet Mol Res 9: 1204–1216. pmid:20589618
- 29. Kan XZ, Li XF, Zhang LQ, Chen L, Qian CJ, Zhang XW, et al. (2010) Characterization of the complete mitochondrial genome of the Rock pigeon, Columba livia (Columbiformes: Columbidae). Genet Mol Res 9: 1234–1249. pmid:20603809
- 30. Li X, Huang Y, Lei F (2015) Comparative mitochondrial genomics and phylogenetic relationships of the Crossoptilon species (Phasianidae, Galliformes). BMC Genomics 16: 42. pmid:25652939
- 31. Ren Q, Yuan J, Ren L, Zhang L, Zhang L, Jiang L, et al. (2014) The complete mitochondrial genome of the yellow-browed bunting, Emberiza chrysophrys (Passeriformes: Emberizidae), and phylogenetic relationships within the genus Emberiza. J Genet 93: 699–707. pmid:25572228
- 32. Riesing MJ, Kruckenhauser L, Gamauf A, Haring E (2003) Molecular phylogeny of the genus Buteo (Aves: Accipitridae) based on mitochondrial marker sequences. Mol Phylogenet Evol 27: 328–342. pmid:12695095
- 33. Slack KE, Delsuc F, McLenachan PA, Arnason U, Penny D (2007) Resolving the root of the avian mitogenomic tree by breaking up long branches. Mol Phylogenet Evol 42: 1–13. pmid:16854605
- 34. Song X, Huang J, Yan C, Xu G, Zhang X, Yue BS (2015) The complete mitochondrial genome of Accipiter virgatus and evolutionary history of the pseudo-control regions in Falconiformes. Biochem Syst Ecol 58: 75–84.
- 35. Zhang L, Wang L, Gowda V, Wang M, Li X, Kan X (2012) The mitochondrial genome of the Cinnamon Bittern, Ixobrychus cinnamomeus (Pelecaniformes: Ardeidae): sequence, structure and phylogenetic analysis. Mol Biol Rep 39: 8315–8326. pmid:22699875
- 36. Sambrook J, Russell DW (2001) Molecular Cloning: A Laboratory Manual. 3rd ed. New York: Cold Spring Harbor Laboratory Press.
- 37. Hall TA (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis program for windows 95/98/NT. Nucl Acids Symp Ser 41: 95–98.
- 38. Okonechnikov K, Golosova O, Fursov M (2012) Unipro UGENE: a unified bioinformatics toolkit. Bioinformatics 28: 1166–1167. pmid:22368248
- 39. Bernt M, Donath A, Jühling F, Externbrink F, Florentz C, Fritzsch G, et al. (2013) MITOS: Improved de novo metazoan mitochondrial genome annotation. Mol Phylogenet Evol 69: 313–319. pmid:22982435
- 40. Wyman SK, Jansen RK, Boore JL (2004) Automatic annotation of organellar genomes with DOGMA. Bioinformatics 20: 3252–3255. pmid:15180927
- 41. Schattner P, Brooks AN, Lowe TM (2005) The tRNAscan-SE, snoscan and snoGPS web servers for the detection of tRNAs and snoRNAs. Nucleic Acids Res 33: W686–689. pmid:15980563
- 42. Laslett D, Canbäck B (2008) ARWEN: a program to detect tRNA genes in metazoan mitochondrial nucleotide sequences. Bioinformatics 24: 172–175. pmid:18033792
- 43. Grant JR, Arantes AS, Stothard P (2012) Comparing thousands of circular genomes using the CGView Comparison Tool. BMC genomics 13: 202. pmid:22621371
- 44. Gray KA, Yates B, Seal RL, Wright MW, Bruford EA (2015) Genenames. org: the HGNC resources in 2015. Nucleic Acids Res 43: D1079–D1085. pmid:25361968
- 45. Katoh K, Standley DM (2013) MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 30: 772–780. pmid:23329690
- 46. Librado P, Rozas J (2009) DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25: 1451–1452. pmid:19346325
- 47. Delport W, Poon AF, Frost SD, Pond SLK (2010) Datamonkey 2010: a suite of phylogenetic analysis tools for evolutionary biology. Bioinformatics 26: 2455–2457. pmid:20671151
- 48. Tamura K, Stecher G, Peterson D, Filipski A, Kumar S (2013) MEGA6: molecular evolutionary genetics analysis version 6.0. Mol Biol Evol 30: 2725–2729. pmid:24132122
- 49. Xia X (2013) DAMBE5: a comprehensive software package for data analysis in molecular biology and evolution. Mol Biol Evol 30: 1720–1728. pmid:23564938
- 50. Xia X, Xie Z, Salemi M, Chen L, Wang Y (2003) An index of substitution saturation and its application. Mol Phylogenet Evol 26: 1–7. pmid:12470932
- 51. Keane TM, Creevey CJ, Pentony MM, Naughton TJ, Mclnerney JO (2006) Assessment of methods for amino acid matrix selection and their use on empirical data shows that ad hoc assumptions for choice of matrix are not justified. BMC Evol Biol 6: 29. pmid:16563161
- 52. Stamatakis A (2014) RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30: 1312–1313. pmid:24451623
- 53. Silvestro D, Michalak I (2012) raxmlGUI: a graphical front-end for RAxML. Org Divers Evol 12: 335–337.
- 54. Stamatakis A. Phylogenetic models of rate heterogeneity: a high performance computing perspective; 2006. IEEE. pp. 8 pp.
- 55. Higdon JW, Bininda-Emonds OR, Beck RM, Ferguson SH (2007) Phylogeny and divergence of the pinnipeds (Carnivora: Mammalia) assessed using a multigene dataset. BMC Evol Biol 7: 216. pmid:17996107
- 56. Ronquist F, Teslenko M, van der Mark P, Ayres DL, Darling A, Höhna S, et al. (2012) MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol 61: 539–542. pmid:22357727
- 57. Beckenbach AT, Robson SK, Crozier RH (2005) Single nucleotide +1 frameshifts in an apparently functional mitochondrial cytochrome b gene in ants of the genus Polyrhachis. J Mol Evol 60: 141–152. pmid:15785844
- 58. Mindell DP, Sorenson MD, Dimcheff DE (1998) An extra nucleotide is not translated in mitochondrial ND3 of some birds and turtles. Mol Biol Evol 15: 1568–1571. pmid:12572620
- 59. Russell RD, Beckenbach AT (2008) Recoding of translation in turtle mitochondrial genomes: programmed frameshift mutations and evidence of a modified genetic code. J Mol Evol 67: 682–695. pmid:19030769
- 60. Cadahía L, Pinsker W, Negro JJ, Pavlicev M, Urios V, Haring E, et al. (2009) Repeated sequence homogenization between the control and pseudo-control regions in the mitochondrial genomes of the subfamily Aquilinae. J Expe Zool Part B 312: 171–185.
- 61. Väli Ü (2002) Mitochondrial pseudo-control region in old world eagles (genus Aquila). Mol Ecol 11: 2189–2194. pmid:12296960
- 62. Kan X, Yuan J, Zhang L, Li X, Yu L, Chen L, et al. (2013) Complete mitochondrial genome of the Tristram’s Bunting, Emberiza tristrami (Aves: Passeriformes): The first representative of the family Emberizidae with six boxes in the central conserved domain II of control region. Mitochondrial DNA 24: 648–650. pmid:23521209
- 63. Ren Q, Yuan J, Zhu X, Wang P, Zhang L, Jiang L, et al. (2014) Complete mitochondrial genome of a Light-vented Bulbul subspecies, Pycnonotus sinensis hainanus (Passeriformes: Pycnonotidae). Mitochondrial DNA.
- 64. Marshall HD, Baker AJ, Grant AR (2013) Complete mitochondrial genomes from four subspecies of common chaffinch (Fringilla coelebs): New inferences about mitochondrial rate heterogeneity, neutral theory, and phylogenetic relationships within the order Passeriformes. Gene 517: 37–45. pmid:23313296
- 65. Zhang H, Dou H, Yang X, Zhao C, Liu G, Zhang J (2014) The complete mitochondrial genome sequence of the Sparrowhawk (Accipiter nisus). Mitochondrial DNA.
- 66. Doyle JM, Katzner TE, Bloom PH, Ji Y, Wijayawardena BK, DeWoody JA (2014) The Genome Sequence of a Widespread Apex Predator, the Golden Eagle (Aquila chrysaetos). PloS one 9(4): e95599. pmid:24759626
- 67. Peng QK, Zhang K, Wu YX, Tan S, Zou FD (2014) Complete mitochondrial genome of Himalayan buzzard (Buteo buteo burmanicus). Mitochondrial DNA.
- 68. Asai S, Yamamoto Y, Yamagishi S (2006) Genetic diversity and extent of gene flow in the endangered Japanese population of Hodgson’s hawk-eagle, Spizaetus nipalensis. Bird Conserv Int 16: 113–129.
- 69. König C (1982) Zur systematischen stellung der Neuweltgeier (Cathartidae). Journal für Ornithologie 123: 259–267.
- 70. Seibold I, Helbig AJ (1995) Evolutionary history of New and Old World vultures inferred from nucleotide sequences of the mitochondrial cytochrome b gene. Philos T R Soc B 350: 163–178.
- 71. Sibley CG, Monroe BL (1990) The Distribution and Taxonomy of the Birds of the Word. New Haven: Yale University Press.
- 72. Wink M (1995) Phylogeny of Old and New World vultures (Aves: Accipitridae and Cathartidae) inferred from nucleotide sequences of the mitochondrial cytochrome b gene. Zeitschrift fur Naturforschung C-Journal of Biosciences 50: 868–882.
- 73. Asai S, Akoshima D, Yamamoto Y, Shigeta Y, Matsue M, Momose H (2008) Current status of the Northern Goshawk Accipiter gentilis in Japan based on mitochondrial DNA. Ornithol Sci 7: 143–156.