100 million years of multigene family evolution: origin and evolution of the avian MHC class IIB
- Julien Goebel1,
- Marta Promerová2, 3,
- Francesco Bonadonna4,
- Karen D. McCoy5,
- Céline Serbielle5,
- Maria Strandh4, 6,
- Glenn Yannic7,
- Reto Burri†8Email author and
- Luca Fumagalli†1Email author
© The Author(s). 2017
Received: 26 August 2016
Accepted: 1 June 2017
Published: 13 June 2017
Gene duplication has led to a most remarkable adaptation involved in vertebrates’ host-pathogen arms-race, the major histocompatibility complex (MHC). However, MHC duplication history is as yet poorly understood in non-mammalian vertebrates, including birds.
Here, we provide evidence for the evolution of two ancient avian MHC class IIB (MHCIIB) lineages by a duplication event prior to the radiation of all extant birds >100 million years ago, and document the role of concerted evolution in eroding the footprints of the avian MHCIIB duplication history.
Our results suggest that eroded footprints of gene duplication histories may mimic birth-death evolution and that in the avian MHC the presence of the two lineages may have been masked by elevated rates of concerted evolution in several taxa. Through the presence of a range of intermediate evolutionary stages along the homogenizing process of concerted evolution, the avian MHCIIB provides a remarkable illustration of the erosion of multigene family duplication history.
Gene duplication represents an important source of evolutionary novelties and has led to outstanding adaptations, such as the vertebrates’ adaptive immune system (e.g. [1–3]). Genes of the major histocompatibility complex (MHC) take a prominent role in the latter, as they are strongly associated with individual fitness, and have been instrumental for understanding the evolution of multigene families. The duplication history and mode of evolution of the MHC have been debated over decades [2, 4–8], and remain obscure for major vertebrate classes, such as birds. To clarify the phylogenetic origins and evolutionary history of this important component of the avian immune system, analyses of MHC diversity across the entire avian tree of life have been called for .
The MHC multigene family was originally thought to evolve under concerted evolution , whereby gene conversion exchanges sequence information among paralogs (i.e. duplicate genes) and thereby homogenizes the sequence content across the multigene family. However, phylogenetic reconstructions showed that mammalian MHC sequences cluster by locus (i.e. according to duplication history) rather than by species (e.g. ). Together with the phylogenetically scattered loss of MHC lineages (e.g. [11, 12]) this observation suggested that the mammalian MHC rather follows a birth-death process, in which the dynamics of gene duplication (birth) and gene loss (death) are important determinants of the multigene family’s long-term evolution .
In contrast, phylogenetic evidence for birth-death evolution has emerged only recently from the avian MHC class IIB (MHCIIB) [9, 13]. Initial phylogenetic reconstructions of MHC diversity in fowl (Galliformes) and songbirds (Passeriformes) found mostly species-specific sequence clusters, leading to the conclusion that the avian MHC evolves under concerted evolution [14–18]. Later studies in these orders (e.g. [19, 20]) and in birds of prey (Accipitriformes) [13, 21] confirmed these patterns; though predominantly for exon 2 (see Additional file 1 for gene structure), which is involved in the binding of pathogen-derived peptides and evolves under strong balancing selection . However, the finding of two orthologous sequence clusters (DAB1 and DAB2) in owls (Strigiformes) started casting a different light. Based on a sequence signature comprised of 16 divergent sites scattered across the 5′-end of exon 3, duplication history was traced beyond the owl order to charadriiform birds , and subsequently to the root of the Neoaves radiation , confirming the persistence of two avian MHCIIB lineages over at least 70 million years (my) . Also in other bird orders, including tubenoses (Procellariiformes) and even passerines (Passeriformes), indications for divergently evolving MHC paralogs are accumulating [24–27]. Together with the supposed repeated loss of MHC lineages  and mammal-like MHC organizations in some bird species [24, 25], these results suggest that birth-death processes may constitute an important component of not only mammalian but also avian MHC evolution.
Still, the time of origin of the two avian MHCIIB lineages and the potential role of concerted evolution in concealing it remains unknown. To perform a systematic survey of MHCIIB lineages across the avian tree of life, we isolated avian MHCIIB sequences spanning from exon 1 to exon 4 with an unprecedented phylogenetic coverage . Based on phylogenetic analyses of these data along with sequences available from DNA sequence databases, we (i) determined the phylogenetic origin of the two avian MHCIIB lineages, and (ii) studied their evolution across the avian tree of life.
Results and discussion
The origin of avian MHCIIB lineages predates the radiation of extant birds
We next investigated whether sites other than the 16 originally described ones may reflect avian MHCIIB duplication history, and found that this is not the case. To identify sets of sites with a common phylogenetic history, we implemented a hypothesis-free algorithm that reconstructs site-wise phylogenetic relationships (Saguaro; ). Saguaro recovered two major types of topologies when run along an alignment including exon 2 and exon 3. The first split sequences from a given species up into two separate clusters (Additional file 6A) with a high distance between the most distant sequences of this species (Additional file 7), as expected for sites that recover duplication history. The second rather grouped sequences by species/order (Additional file 6B), with short distances between the most distant sequences of a given species (Additional file 7), as expected under concerted evolution. This approach identified ten sites that discriminate between the two sequence clusters and thus reflect duplication history (Fig. 1b, Additional files 8 and 9). These sites are a subset of the original 16 sites and recovered the duplication history reflected by entire exon 3 (Additional files 8 and 9). Variants at the six sites not recovered by Saguaro are present also in several orders across the phylogeny (Fig. 1b). Likely, the footprints of duplication at these sites were overwhelmed by the reticulate phylogenetic signals generated by concerted evolution (see below).
Concerted evolution erodes the footprints of avian MHCIIB duplication history and may mimic birth-death evolution
The phylogenetic distribution of the MHCIIB lineages may hint towards multiple independent losses of both MHCIIB lineages during the radiation of extant birds. According to phylogenetic reconstructions, a significant proportion of orders exhibit only one of the MHCIIB lineages (nine when only orders with significant sequencing efforts are included; 21 when including all orders). This scattered pattern of presence and absence of lineages is a hallmark of birth-death evolution  also observed in mammals [7, 30]. Assuming that the isolation of MHCIIB sequences did not miss lineages in many orders (an invalid assumption e.g. for orders with only a single MHCIIB exon 3 sequence available from genome assemblies; Fig. 1), this result might suggest that each lineage was lost multiple times independently.
Finally, our results suggest that, in many orders for which phylogenetic relationships would postulate the presence of only a single MHCIIB lineage, the two lineages might indeed be present despite the presence of only one lineage-specific signature. Careful inspection of the composition of avian MHCIIB lineages’ signatures reveals many sequences with signatures composed of variants from both lineages (Fig. 1b). Even orders such as passerines and galliforms, in which phylogenetic analyses identified only a single lineage despite a well-characterized MHCIIB (e.g. [32, 33]), exhibit single sites within the 16-bp signature with variants characteristic of the alternative lineage (Fig. 1b). Consequently, instead of multiple independent losses of avian MHCIIB lineages, in many avian orders the presence of the two MHCIIB lineages may have been masked by concerted evolution.
The retention time of signatures of each MHCIIB lineage across bird species is thus likely at least in part explained by variable rates of concerted evolution among avian taxa. Whether supposedly genomic properties (such as interspecific recombination rate variation) or differing genomic structures of the MHC region among orders are involved in determining the rates of concerted evolution remains to be investigated. Gene conversion, the form of recombination driving concerted evolution, occurs predominantly between repeated sequences (including duplicate genes) situated in physically close genomic locations . Variation in the proximity of MHCIIB paralogs could, therefore, cause rates of concerted evolution to vary among taxa. However, as in most vertebrates , avian MHCIIB genes are typically strongly linked (e.g. ). Apart from passerines , in the bird species for which the genomic structure of the MHC region is known, MHCIIB paralogs are typically situated at about the same distance of approximately five kilobases [24, 25, 36–38]. Other structural genomic features with possible effects on the rates of gene conversion could include the presence of MHC class IIA (MHCIIA) genes in- between MHCIIB paralogs. In crested ibis – the only bird species with both MHCIIB lineages for which the genomic structure of the MHC is known – MHCIIB and MHCIIA are tightly linked and duplicated as a unit in tandem [24, 25] such as in mammals, whereas in galliforms MHCIIA genes are situated outside the MHC region . In conclusion, determining the extent to which avian MHCIIB lineages were masked by concerted evolution or lost by birth-death evolution, and the role of genomic MHC structure in determining rates of concerted evolution will require comparative MHC genomic studies that examine the physical position of MHCIIB genes within the MHC region in a range of species.
We found that two ancient MHCIIB lineages evolved prior to the radiation of all extant birds >100 mya and that concerted evolution has contributed to the erosion of the phylogenetic signal of the duplication history to a varying degree in different bird orders.
The old age of the avian MHCIIB lineages may suggest that they have orthologs in as far relatives as mammals. Although the high evolutionary rates of MHCIIB genes hinder the identification of orthology across such vast timescales, MHCIIA genes may provide some insight on this question. In mammals, MHCIIA genes usually duplicated in tandem with MHCIIB genes  and their lower rates of evolution have previously enabled the establishment of orthology between chicken MHCII genes (DAB2 lineage) and the mammalian DR lineage . The isolation of avian MHCIIA sequences in species exhibiting both MHCIIB lineages might, therefore, provide an avenue to identify mammalian orthologs of the avian DAB1 region. Together with the study of the genomic architecture of the MHC region in such species, this approach may provide insights into the evolution of vertebrate adaptive immunity over unprecedented timescales.
Our results provide a striking example of how concerted evolution may mask the evolutionary origins of gene lineages, and lead to patterns that potentially mimic gene loss and birth-death evolution. This raises questions regarding the extent to which similar processes may have masked the evolutionary history of multigene families in other taxonomic groups. Future analyses of the genomic structure of the MHC in bird species at different evolutionary stages along this process will provide deeper insights into the relative contributions of birth-death processes and concerted evolution in the long-term evolution of the avian MHCIIB.
Identification of avian MHCIIB lineages
To screen for the sequence signatures specific to the avian DAB1 and DAB2 MHCIIB lineages situated in MHCIIB exon 3 we first compiled an alignment of this region from as many avian species and orders as possible. To this end, we performed blast searches of an owl exon 3 sequence (GenBank accession no. EF641251) against all bird sequences in the GenBank DNA sequence database using the blastn algorithm. Sequence hits from other genes than MHCIIB and with a sequence identity inferior of 80% were removed. We also removed poorly/erroneously aligning sequences retrieved from genome assemblies that are based on short-read sequencing, as multigene families are prone to be collapsed during the assembly. GenBank accession numbers of the used sequences are provided in Additional file 10. The remaining sequences were aligned separately for each intron and exon using MAFFT 7  with default settings on the MAFFT alignment server (http://mafft.cbrc.jp/alignment/server). Alignments are provided in Additional file 11.
Within this alignment, we then manually screened for the presence of the sequence signatures characteristic of the alternative MHCIIB lineages [9, 13] to determine the most recent common ancestor in birds that carried copies of both lineages. In addition, we performed phylogenetic reconstructions based on the first 220 bp of exon 3 (which were available for a large proportion of the species). The GTR + G nucleotide substitution model was evaluated as the best by jModeltest 2.1.7  according to the Akaike information criterion [43, 44]. Bayesian phylogenetic reconstructions were then performed using MrBayes 3.2 . Bayesian analyses were run with four chains for 5 × 106 generations with sequences from tuatara (Sphenodon punctatus, accession number DQ124232) and Chinese alligator (Alligator sinensis, XM_006036594) as outgroups. Trees were sampled every 1000 generations. Posterior distributions were examined in Tracer 1.4 . The first 25% of the topologies were discarded as burnin. Phylogenetic networks were computed in SplitsTree 4.13.1  based on uncorrected p-distances. Moreover, we performed Bayesian phylogenetic reconstructions and estimated phylogenetic networks based on the 16 sites previously recovered to reflect MHCIIB duplication history [9, 14] using the same settings as outlined for exon 3.
Screening for additional sites reflecting duplication history
To evaluate whether sites other than the 16 scattered across the 5′-end of MHCIIB exon 3 reflect duplication history of avian MHCIIB genes, we compiled a data set comprising MHCIIB sequences spanning MHCIIB exon 2 to exon 3 from 192 bird species from the GenBank database. These data included sequences that we previously isolated from 37 species from 13 orders with special attention to isolate sequences of both MHCIIB lineages where possible . Sequences from tuatara were added as outgroups (see above). Sequences were aligned using MAFFT 7  with E-INS-i settings recommended for sequences with long unalignable regions, such as expected for MHCIIB introns. To avoid difficulties with alignment due to repeat regions or transposable elements (TE), we ran CENSOR  to mask repeats and TEs in introns prior to alignment. The detected repeats and TEs were only found in single species and thus harboured no phylogenetic signal.
To identify sites that trace the duplication history of avian MHCIIB genes, we applied the hypothesis-free approach implemented in Saguaro , which applies a combination of a hidden Markov model (HMM) and a self-organising map (SOM) to characterize local phylogenetic relationships (‘cacti’) among aligned sequences. To determine the number of cacti that captures the phylogenetic histories contained in the alignment, we ran Saguaro with its default parameters for 2, 5, 10, and 15 iterations (each iteration a new cactus is proposed). The maximum number of sites reflecting duplication history was reached with five iterations. Results obtained with ≥5 iterations were all congruent and are not reported here.
We then determined which cacti might reflect duplication history. Within such cacti, sequences from the same species but from alternative lineages are expected to cluster separately and distant from each other, in each of the respective lineages. In contrast, for cacti that represent concerted evolution, a species’ sequences are expected to cluster close to each other. Therefore, the cross-species average of within-species’ pairwise distance among sequences should be higher for cacti reflecting duplication history than for cacti reflecting concerted evolution. Because the average pairwise distance among sequences for a given species would be biased by the number of sequences available for this species, and the number of sequences stemming from alternative paralogs, we retrieved the two most distant sequences of each species within a given cactus, and for each cactus estimated the mean of these across all species. Mean values were then normalized across cacti to compare values among runs with different numbers of iterations. For this, pairwise distances were extracted from cacti using the APE package  in R.
Finally, we concatenated the sites for which cacti reflecting duplication history were identified (Additional files 6A and 7) and performed phylogenetic reconstructions using MrBayes 3.2.0  with a GTR + G nucleotide substitution model that was found to best fit the data using jModelTest2  based on the Akaike information criterion , and estimated a phylogenetic network using SplitsTree 4.13.1 . Running parameters were the same as for the phylogenetic analyses presented above.
The authors thank Nagarjun Vijay for assistance with Saguaro and two anonymous reviewers for their helpful comments.
This work was supported by the Swiss National Science Foundation (grant numbers 31003A_138371 to L.F.; PBLAP3–134299, PBLAP3_140171 to R.B.), the Czech Science Foundation (grant number P505/10/1871 to M.P.), the ANR VECTADAPT (grant number ANR-06-JCJC-0095-01 to K.D.M.), the Institut Polaire-Paul Emile Victor (grant number 333 to K.D.M.), the Ellis Elliot and Nos Oiseaux Foundations and the Société Vaudoise des Sciences Naturelles (all to G.Y.).
Availability of data and materials
The data analyzed during this study were all available from the GenBank DNA sequence data base.
RB and LF conceived the study. MP, RB, and JG performed molecular lab work. JG analysed the data under the guidance of RB. RB wrote the manuscript with input from JG, LF and the other authors. FB, KDM, CS, MS, and GY provided materials and data. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
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- Ota T, Nei M. Divergent evolution and evolution by the birth-and-death process in the immunoglobulin VH gene family. Mol Biol Evol. 1994;11(3):469–82.PubMedGoogle Scholar
- Nei M, Gu X, Sitnikova T. Evolution by the birth-and-death process in multigene families of the vertebrate immune system. Proc Natl Acad Sci U S A. 1997;94(15):7799–806.View ArticlePubMedPubMed CentralGoogle Scholar
- Su C, Nei M. Evolutionary dynamics of the T-cell receptor VB gene family as inferred from the human and mouse genomic sequences. Mol Biol Evol. 2001;18(4):503–13.View ArticlePubMedGoogle Scholar
- Ohta T. Allelic and nonallelic homology of a supergene family. Proc Natl Acad Sci U S A. 1982;79(10):3251–4.View ArticlePubMedPubMed CentralGoogle Scholar
- Ohta T. On the evolution of multigene families. Theor Popul Biol. 1983;23(2):216–40.View ArticlePubMedGoogle Scholar
- Hughes AL, Nei M. Evolutionary relationships of class II major-histocompatibility-complex genes in mammals. Mol Biol Evol. 1990;7(6):491–514.PubMedGoogle Scholar
- Takahashi K, Rooney AP, Nei M. Origins and divergence times of mammalian class II MHC gene clusters. J Hered. 2000;91(3):198–204.View ArticlePubMedGoogle Scholar
- Kriener K, CO O’hU, Tichy H, Klein J. Convergent evolution of major histocompatibility complex molecules in humans and new world monkeys. Immunogenetics. 2000;51(3):169–78.View ArticlePubMedGoogle Scholar
- Burri R, Salamin N, Studer RA, Roulin A, Fumagalli L. Adaptive divergence of ancient gene duplicates in the avian MHC Class II B. Mol Biol Evol. 2010;27(10):2360–74.View ArticlePubMedGoogle Scholar
- Nei M, Rooney AP. Concerted and birth-and-death evolution of multigene families. Annu Rev Genet. 2005;39(1):121–52.View ArticlePubMedPubMed CentralGoogle Scholar
- Yuhki N, Beck T, Stephens RM, Nishigaki Y, Newmann K, O'Brien SJ. Comparative genome organization of human, murine, and feline MHC Class II region. Genome Res. 2003;13(6a):1169–79.View ArticlePubMedPubMed CentralGoogle Scholar
- Andersson L, Rask L. Characterization of the MHC class II region in cattle. The number of DQ genes varies between haplotypes. Immunogenetics. 1988;27(2):110–20.View ArticlePubMedGoogle Scholar
- Burri R, Niculita-Hirzel H, Salamin N, Roulin A, Fumagalli L. Evolutionary patterns of MHC class II B in owls and their implications for the understanding of avian MHC evolution. Mol Biol Evol. 2008;25(6):1180–91.View ArticlePubMedGoogle Scholar
- Wittzell H, Bernot A, Auffray C, Zoorob R. Concerted evolution of two Mhc class II B loci in pheasants and domestic chickens. Mol Biol Evol. 1999;16(4):479–90.View ArticlePubMedGoogle Scholar
- Hess CM, Gasper J, Hoekstra HE, Hill CE, Edwards SV. MHC class II pseudogene and genomic signature of a 32-kb cosmid in the house finch (Carpodacus mexicanus). Genome Res. 2000;10:613–23.View ArticlePubMedPubMed CentralGoogle Scholar
- Edwards SV, Gasper J, March M. Genomics and polymorphism of Agph-DAB1, an Mhc class II B gene in red-winged blackbirds (Agelaius phoeniceus). Mol Biol Evol. 1998;15:236–50.View ArticlePubMedGoogle Scholar
- Edwards SV, Hess CM, Gasper J, Garrigan D. Toward an evolutionary genomics of the avian Mhc. Immunol Rev. 1999;167:119–32.View ArticlePubMedGoogle Scholar
- Gasper JS, Shiina T, Inoko H, Edwards SV. Songbird genomics: analysis of 45 kb upstream of a polymorphic Mhc class II gene in red-winged blackbirds (Agelaius phoeniceus). Genomics. 2001;75:26–34.View ArticlePubMedGoogle Scholar
- Eimes JA, Bollmer JL, Whittingham LA, Johnson JA, Van Oosterhout C, Dunn PO. Rapid loss of MHC class II variation in a bottlenecked population is explained by drift and loss of copy number variation. J Evol Biol. 2011;24:1847–56.View ArticlePubMedGoogle Scholar
- Bollmer JL, Dunn PO, Whittingham LA, Wimpee C. Extensive MHC Class II B gene duplication in a passerine, the common yellowthroat (Geothlypis trichas). J Hered. 2010;101(4):448–60.View ArticlePubMedGoogle Scholar
- Alcaide M, Edwards SV, Negro JJ. Characterization, polymorphism, and evolution of MHC class IIB genes in birds of prey. J Mol Evol. 2007;65:541–54.View ArticlePubMedGoogle Scholar
- Klein J. Natural history of the major histocompatibility complex. New York: Wiley; 1986.Google Scholar
- Jarvis ED, Mirarab S, Aberer AJ, Li B, Houde P, Li C, et al. Whole-genome analyses resolve early branches in the tree of life of modern birds. Science. 2014;346(6215):1320–31.View ArticlePubMedPubMed CentralGoogle Scholar
- Taniguchi Y, Matsumoto K, Matsuda H, Yamada T, Sugiyama T, Homma K, et al. Structure and polymorphism of the major histocompatibility complex class II region in the Japanese Crested Ibis, Nipponia nippon. PLoS One. 2014;9(9):e108506.View ArticlePubMedPubMed CentralGoogle Scholar
- Chen L-C, Lan H, Sun L, Deng Y-L, Tang K-Y, Wan Q-H. Genomic organization of the crested ibis MHC provides new insight into ancestral avian MHC structure. Sci Rep. 2015;5:7963.View ArticlePubMedPubMed CentralGoogle Scholar
- Dearborn DC, Gager AB, Gilmour ME, McArthur AG, Hinerfeld DA, Mauck RA. Non-neutral evolution and reciprocal monophyly of two expressed Mhc class II B genes in Leach’s storm-petrel. Immunogenetics. 2015;67(2):111–23.View ArticlePubMedGoogle Scholar
- Eimes JA, Lee S-i, Townsend AK, Jablonski P, Nishiumi I, Satta Y. Early duplication of a single MHC IIB locus prior to the passerine radiations. PLoS One. 2016;11(9):e0163456.View ArticlePubMedPubMed CentralGoogle Scholar
- Burri R, Promerová M, Goebel J, Fumagalli L. PCR-based isolation of multigene families: lessons from the avian MHC class IIB. Mol Ecol Resour. 2014;14(4):778–88.View ArticlePubMedGoogle Scholar
- Zamani N, Russell P, Lantz H, Hoeppner M, Meadows J, Vijay N, et al. Unsupervised genome-wide recognition of local relationship patterns. BMC Genomics. 2013;14(1):347.View ArticlePubMedPubMed CentralGoogle Scholar
- Ohno S. Evolution by gene duplication. New York: Springer; 1970.View ArticleGoogle Scholar
- Chen J-M, Cooper DN, Chuzhanova N, Ferec C, Patrinos GP. Gene conversion: mechanisms, evolution and human disease. Nat Rev Genet. 2007;8(10):762–75.View ArticlePubMedGoogle Scholar
- Kaufman J, Jansen J, Shaw I, Walker B, Milne S, Beck S, et al. Gene organisation determines evolution of function in the chicken MHC. Immunol Rev. 1999;167:101–17.View ArticlePubMedGoogle Scholar
- Balakrishnan C, Ekblom R, Volker M, Westerdahl H, Godinez R, Kotkiewicz H, et al. Gene duplication and fragmentation in the zebra finch major histocompatibility complex. BMC Biol. 2010;8(1):29.View ArticlePubMedPubMed CentralGoogle Scholar
- Kelley J, Walter L, Trowsdale J. Comparative genomics of major histocompatibility complexes. Immunogenetics. 2005;56(10):683–95.View ArticlePubMedGoogle Scholar
- Gaigher A, Burri R, Gharib W, Taberlet P, Roulin A, Fumagalli L. Family-assisted inference of the genetic architecture of MHC variation. Mol Ecol Resour. 2016;Google Scholar
- Shiina T, Hosomichi K, Hanzawa K. Comparative genomics of the poultry major histocompatibility complex. Anim Sci J. 2006;77(2):151–62.View ArticleGoogle Scholar
- Chaves LD, Krueth SB, Reed KM. Defining the Turkey MHC: sequence and genes of the B locus. J Immunol. 2009;183:6530–7.View ArticlePubMedGoogle Scholar
- Ye Q, He K, Wu S-Y, Wan Q-H. Isolation of a 97-kb minimal essential MHC B locus from a new reverse-4D BAC Library of the Golden Pheasant. PLoS One. 2012;7(3):e32154.View ArticlePubMedPubMed CentralGoogle Scholar
- Salomonsen J, Marston D, Avila D, Bumstead N, Johansson B, Juul-Madsen H, et al. The properties of the single chicken MHC classical class II a chain (B-LA) gene indicate an ancient origin for the DR/E-like isotype of class II molecules. Immunogenetics. 2003;55(9):605–14.View ArticlePubMedGoogle Scholar
- Bontrop RE. Comparative genetics of MHC polymorphisms in different primate species: duplications and deletions. Hum Immunol. 2006;67(6):388–97.View ArticlePubMedGoogle Scholar
- Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30(4):772–80.View ArticlePubMedPubMed CentralGoogle Scholar
- Darriba D, Taboada GL, Doallo R, Posada D. jModelTest 2: more models, new heuristics and parallel computing. Nat Methods. 2012;9(8):772.View ArticlePubMedPubMed CentralGoogle Scholar
- Akaike H. A new look at the statistical model identification. IEEE Trans Autom Control. 1974;19(6):716–23.View ArticleGoogle Scholar
- Posada D, Buckley T. Model selection and model averaging in phylogenetics: advantages of akaike information criterion and Bayesian approaches over likelihood ratio tests. Syst Biol. 2004;53(5):793–808.View ArticlePubMedGoogle Scholar
- Ronquist F, Teslenko M, van der Mark P, Ayres DL, Darling A, Höhna S, et al. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol. 2012;61(3):539–42.View ArticlePubMedPubMed CentralGoogle Scholar
- Rambaut A, Drummond AJ. Tracer v1.4, Available from http://beast.bio.ed.ac.uk/Tracer. 2007.
- Huson DH, Bryant D. Application of phylogenetic networks in evolutionary studies. Mol Biol Evol. 2006;23(2):254–67.View ArticlePubMedGoogle Scholar
- Kohany O, Gentles AJ, Hankus L, Jurka J. Annotation, submission and screening of repetitive elements in Repbase: RepbaseSubmitter and Censor. BMC Bioinformatics. 2006;7:474.View ArticlePubMedPubMed CentralGoogle Scholar
- Paradis E, Claude J, Strimmer K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics. 2004;20:289–90.View ArticlePubMedGoogle Scholar