The extant seed plants include more than 260,000 species that belong to five main lineages: angiosperms, conifers, cycads, Ginkgo, and gnetophytes. Despite tremendous effort using molecular data, phylogenetic relationships among these five lineages remain uncertain. Here, we provide the first broad coalescent-based species tree estimation of seed plants using genome-scale nuclear and plastid data By incorporating 305 nuclear genes and 47 plastid genes from 14 species, we identify that i) extant gymnosperms (i.e., conifers, cycads, Ginkgo, and gnetophytes) are monophyletic, ii) gnetophytes exhibit discordant placements within conifers between their nuclear and plastid genomes, and iii) cycads plus Ginkgo form a clade that is sister to all remaining extant gymnosperms. We additionally observe that the placement of Ginkgo inferred from coalescent analyses is congruent across different nucleotide rate partitions. In contrast, the standard concatenation method produces strongly supported, but incongruent placements of Ginkgo between slow- and fast-evolving sites. Specifically, fast-evolving sites yield relationships in conflict with coalescent analyses. We hypothesize that this incongruence may be related to the way in which concatenation methods treat sites with elevated nucleotide substitution rates. More empirical and simulation investigations are needed to understand this potential weakness of concatenation methods.
Citation: Xi Z, Rest JS, Davis CC (2013) Phylogenomics and Coalescent Analyses Resolve Extant Seed Plant Relationships. PLoS ONE 8(11): e80870. https://doi.org/10.1371/journal.pone.0080870
Editor: Paul V. A. Fine, University of California, Berkeley, United States of America
Received: September 4, 2013; Accepted: October 15, 2013; Published: November 21, 2013
Copyright: © 2013 Xi 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.
Funding: This study was funded by a grant from the United States National Science Foundation DEB-1120243 to C.C.D. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Seed plants originated at least 370 million years ago  and include more than 260,000 extant species , making them the most species rich land plant clade. These species are placed in five main lineages: angiosperms, conifers, cycads, Ginkgo, and gnetophytes . By far the greatest species diversity is found in the angiosperms; the remaining four lineages constitute the extant gymnosperms (Figure 1A), meaning “naked seeds”. Today’s gymnosperms are a shadow of their former glory–only ~1,000 species currently exist . Nevertheless, they are of huge ecological and economic importance, especially for their timber and horticultural value.
(A) The four main lineages of extant gymnosperms: (1) conifers (Pinus resinosa), (2) cycads (Cycas sp.), (3) Ginkgo biloba, and (4) gnetophytes (Ephedra chilensis). (B) Two main hypotheses for phylogenetic relationships of gymnosperms. (C) Three main hypotheses for the phylogenetic placement of gnetophytes. (D) Two main hypotheses for the phylogenetic placement of Ginkgo.
Despite tremendous efforts to resolve phylogenetic relationships among the five extant seed plant lineages using molecular data, these relationships remain uncertain. For example, early studies identified the monophyly of extant gymnosperms [4-11], but more recent studies using duplicate gene rooting have suggested that cycads are instead more closely related to angiosperms than they are to other extant gymnosperms (Figure 1B) [3,12]. Similarly, the gnetophytes, which were previously thought to be sister to angiosperms based on morphological characters (i.e., the anthophyte hypothesis; [13,14]), are now grouped with other extant gymnosperms using molecular data. Establishing the phylogenetic placement of gnetophytes among extant gymnosperms, however, remains problematic. Recent molecular studies have suggested three conflicting hypotheses of gnetophyte relationships: the gnecup (i.e., gnetophytes sister to cupressophytes; [9,15]), gnepine (i.e., gnetophytes sister to Pinaceae; [7,8,10,16-24]), and gnetifer (i.e., gnetophytes sister to conifers; [5,25]) hypotheses (Figure 1C). In addition, early studies concatenating multiple genes placed Ginkgo alone as sister to conifers and gnetophytes within the extant gymnosperm clade [7-11,16-18,26-28]. However, more recent studies using additional genes have suggested that a clade containing cycads plus Ginkgo cannot be excluded as sister to all remaining extant gymnosperms (Figure 1D) [15,19,21-24,29,30]. In particular, attempts to include data that are less prone to saturation due to high rates of substitution (e.g., amino acid sequences and slow-evolving nucleotide sequences) have lead to increasing support for the placement of cycads plus Ginkgo as sister to all remaining extant gymnosperms [15,21,23,24]. For all of these reasons, a broader comparative phylogenomic assessment of these questions is warranted to better understand the evolution of extant seed plants.
Advances in next-generation sequencing and computational phylogenomics represent tremendous opportunities for inferring species relationships using hundreds, or even thousands, of genes. Until now the reconstruction of broad seed plant phylogenies from multiple genes has relied almost entirely on concatenation methods [7-11,15-19,21,23,24,29,31-37], in which phylogenies are inferred from a single combined gene matrix . These analyses assume that all genes have the same, or very similar, evolutionary histories. Theoretical and simulation studies, however, have shown that concatenation methods can yield misleading results, especially if gene trees are highly heterogeneous [39-43]. In contrast, recently developed coalescent-based methods estimate the species phylogeny from a collective set of gene trees, which permit different genes to have different evolutionary histories [44-46]. Both theoretical and empirical studies have shown that coalescent methods can better accommodate gene heterogeneity [44-48].
Here, our phylogenomic analyses of 14 species represent the first coalescent-based species tree estimation of seed plants. By incorporating hundreds of nuclear genes as well as a full complement of plastid genes, we also provide a direct comparison of phylogenetic relationships inferred from nuclear and plastid genomes.
Results and Discussion
Taxon and gene sampling of nuclear and plastid genes
Our nuclear gene taxon sampling included 12 species representing all major lineages of extant seed plants (i.e., angiosperms [Amborella trichopoda and Nuphar advena], conifers [Cryptomeria japonica, Picea glauca, Picea sitchensis, Pinus contorta, and Pinus taeda], cycads [Cycas rumphii and Zamia furfuracea], Ginkgo biloba, and gnetophytes [Gnetum gnemon and Welwitschia mirabilis]) . One fern (Adiantum capillus-veneris) and one lycophyte (Selaginella moellendorffii) were included as outgroups (Table 1). Of these 14 species, the coding sequences of Selaginella were obtained from a whole-genome sequencing project, and the rest were from deeply sequenced transcriptomes that each included at least 6,000 assembled unigenes. Using a Markov clustering algorithm , the 234,040 protein-coding sequences (sequences with in-frame stop codons or shifted reading frames were excluded prior to clustering) from these 14 species were grouped into 14,215 gene clusters, of which 496 passed our initial criteria for establishing low-copy nuclear genes as described in the Materials and Methods section. Following this initial filter, the average numbers of sequences and species for each gene cluster were ten and eight, respectively. Additionally, of these 496 gene clusters, 305 remained following our paralogue pruning filter (see Materials and Methods), and the average number of species and sites for each gene cluster were nine and 509, respectively (Table S1). The final concatenated nuclear gene matrix included 155,295 nucleotide sites and 37.1% missing data (including gaps and undetermined characters).
|Species||Sources||No. of coding sequences used in clustering||No. of sequences used in phylogenetic analyses||Average GC-content|
To compare the evolutionary history between nuclear and plastid genomes, we obtained the annotated plastid genomes from 12 seed plants (i.e., angiosperms [Amborella trichopoda and Nuphar advena], conifers [Cryptomeria japonica, Picea abies, Picea morrisonicola, Pinus koraiensis, and Pinus taeda], cycads [Cycas revoluta and Zamia furfuracea], Ginkgo biloba, and gnetophytes [Gnetum parvifolium and Welwitschia mirabilis]), plus one fern (Adiantum capillus-veneris) and one lycophyte (Selaginella moellendorffii) as outgroups (Table 2). These 14 species represent the same taxonomic placeholders as those in our nuclear gene analyses. The 685 protein-coding sequences from the 14 plastid genomes were grouped into 59 gene clusters, of which 47 remained following the filtering criteria described above. The average number of species and sites for these 47 gene clusters were 12 and 1,063, respectively (Table S2). The final concatenated plastid gene matrix included 49,968 nucleotide sites and 14.1% missing data.
|Species||GenBank accession number||No. of sequences used in phylogenetic analyses||Average GC-content|
Inferring Species Relationships Using Coalescent and Concatenation Methods
Species relationships were first estimated from nucleotide sequences using the recently developed coalescent method: Species Tree Estimation using Average Ranks of Coalescence (STAR) . Since this method is based on summary statistics calculated across all gene trees, a small number of outlier genes that significantly deviate from the coalescent model have relatively little effect on the accurate inference of the species tree . We note that while all plastid genes are generally expected to share the same history, evidence of recombination, heteroplasmy, and incomplete lineage sorting in plastid genomes suggests that this may not always apply (e.g., 53-57). Thus, we additionally analyzed plastid genes using the coalescent method. We compared the results from coalescent analyses of both nuclear and plastid genes with those from concatenation analyses using maximum likelihood (ML) as implemented in RAxML . Statistical confidence was established for both methods using a multilocus bootstrapping approach , in which genes were resampled with replacement followed by resampling sites with replacement within each gene.
Our species trees inferred from coalescent and concatenation methods largely agree with each other (Figure 2). Similarly, analyses of nuclear and plastid genes are largely in agreement. All analyses strongly support (≥87 bootstrap percentage [BP]) the monophyly of extant gymnosperms. The lone placement that shows conflict between the nuclear and plastid gene trees is for the gnetophytes (i.e., Gnetum and Welwitschia). Our coalescent and concatenation analyses of nuclear genes support the gnepine hypothesis (i.e., gnetophytes sister to Pinaceae [Picea and Pinus]) with 64 BP and 85 BP, respectively (Figure 2A). In contrast, our coalescent and concatenation analyses of plastid genes support the gnecup hypothesis (i.e., gnetophytes sister to cupressophytes [Cryptomeria]) with 60 BP and 94 BP, respectively (Figure 2B). Moreover, in each of these cases the rival topology is rejected using the approximately unbiased (AU) test : the gnecup placement is rejected for concatenated nuclear gene matrix (p-value = 0.001) and the gnepine placement is rejected for concatenated plastid gene matrix (p-value = 0.001). This conflicting placement between the nuclear and plastid genomes is consistent with previous studies (e.g., 15,19,22), although our study is a direct comparison using a similar set of species for both genomes. These results suggest that the nuclear and plastid genomes of gnetophytes may have distinctly different evolutionary histories.
Bootstrap percentages (BPs) from STAR/RAxML are indicated above each branch; an asterisk indicates that the clade is supported by 100 BPs from both STAR and RAxML. Branch lengths were estimated by fitting the concatenated matrices to the inferred topology from STAR.
An additional well-supported placement we uncovered here relates to cycads and Ginkgo. Our coalescent and concatenation analyses of nuclear genes strongly support (100 BP and 93 BP, respectively) cycads (i.e., Cycas and Zamia) plus Ginkgo as sister to all remaining extant gymnosperms (Figure 2A and see red dots in Figure 1D for clades under consideration). The rival placement of Ginkgo alone as sister to conifers and gnetophytes (i.e., the “Gingko alone” hypothesis) is rejected for the concatenated nuclear gene matrix (p-value = 0.004, AU test). In addition, our coalescent analyses of plastid genes similarly support (71 BP) the monophyly of cycads plus Ginkgo (Figure 2B). The concatenation analyses of plastid genes, in contrast, weakly support (56 BP) the “Gingko alone” hypothesis.
Because sequences from both cycads and Ginkgo were not present in all 305 nuclear genes, we conducted an additional analysis using only those genes that included both cycads and Ginkgo (sequences from both cycads and Ginkgo were present in all 47 plastid genes; see Table 2). This allows us to test if the phylogenetic placement of Ginkgo inferred from nuclear genes is sensitive to missing data. Although the number of nuclear gene clusters declines to 69 when applying this taxon filter, the results are identical to those above: the coalescent and concatenation analyses strongly support (95 BP and 97 BP, respectively) cycads plus Ginkgo as sister to all remaining extant gymnosperms.
To further investigate if the placement of Ginkgo is sensitive to the number of sampled genes, we randomly subsampled the 305 nuclear genes in four different gene size categories (i.e., 25, 47, 100, or 200 genes; 10 replicates each). We similarly subsampled the 47 plastid genes (i.e., 25 genes with 10 replicates). Even as the sample size declines, the coalescent and concatenation analyses of nuclear genes strongly support (≥80 BP) cycads plus Ginkgo as sister to all remaining extant gymnosperms. Support for this relationship only dropped below 80 BP when the number of subsampled nuclear genes was 25 for the coalescent analyses (Figure 3A). For the 25 subsampled plastid genes, the coalescent analyses also support cycads plus Ginkgo with ≥80 BP. In contrast, concatenation analyses of 25 subsampled plastid genes support the “Gingko alone” hypothesis with ≥80 BP (Figure 3A). Thus, our results are robust to the number of genes sampled, including the discordant placements of Ginkgo between coalescent and concatenation analyses of plastid genes.
(A) BPs from coalescent and concatenation analyses using different gene subsampling. The 305 nuclear genes were subsampled for four different gene size categories (i.e., 25, 47, 100, or 200 genes; 10 replicates each), and the 47 plastid genes were subsampled for 25 genes (10 replicates). Cells with hatching indicate that support for the placement of Ginkgo biloba from all replicates is below 80 BP; colored cells indicate relationships that received bootstrap support ≥80 BP from at least one replicate (pink = cycads plus Ginkgo as sister to all remaining extant gymnosperms, yellow = Ginkgo alone as sister to conifers and gnetophytes within extant gymnosperms; see also Figure 1D). (B) BPs from coalescent and concatenation analyses across different nucleotide rate partitions. Parsimony informative sites in concatenated matrices were sorted based on estimated evolutionary rates, and subsequently divided into two equal partitions. The index of substitution saturation (ISS) was used to measure nucleotide substitution saturation for sites within each rate partition. The two critical ISS values, i.e., ISS.C1 and ISS.C2, were estimated using an asymmetrical and symmetrical topology, respectively (for data including more than 32 species, only values estimated from 32 terminals are shown here).
Accommodating rate heterogeneity in coalescent and concatenation analyses
Despite the fact that our coalescent and concatenation analyses largely agree with each other, we are interested in exploring the influence of nucleotide substitution rates on phylogenetic inference of seed plant relationships. It has long been appreciated that elevated rates of molecular evolution can lead to multiple substitutions at the same site [61,62], which can be especially misleading for resolving deeper relationships if the substitution model fails to correct for high levels of saturation in fast-evolving sites [24,62-68]. This is especially relevant for inferring the phylogeny of early diverging gymnosperms given their ancient origin [69-72]. Here, to assess the effect of rate heterogeneity, we partitioned nucleotide sites in our concatenated matrices according to estimated evolutionary rates.
The relative evolutionary rate of each site in our concatenated matrices was estimated using the Observed Variability (OV) method , which compares all sequences at a given site in a pair-wise manner, and uses the total number of mismatches between species as the measure of site variability. Importantly, since the OV is a tree-independent approach, it is free from systematic bias of estimating evolutionary rates using an inaccurate phylogeny . We sorted all parsimony informative sites in our concatenated nucleotide matrices based on their relative evolutionary rates and then divided them into two equal partitions (Figures S1A and S1B). For nuclear genes each rate partition contains 25,647 sites, and for plastid genes each partition contains 8,369 sites.
When analyzing data from each rate partition separately, the coalescent method supports (≥76 BP) cycads plus Ginkgo as sister to all remaining extant gymnosperms across all rate partitions for both nuclear and plastid genes (Figure 3B). In contrast, the concatenation method produces well supported, but incongruent results, across different rate partitions (Figure 3B). Here, the slow-evolving sites corroborate results from our coalescent analyses and place cycads sister to Ginkgo with 100 BP for both nuclear and plastid genes. However, fast-evolving sites support the “Gingko alone” hypothesis with 82 BP and 99 BP for nuclear and plastid genes, respectively. Additionally, when the placement of cycads plus Ginkgo is inferred using the concatenation method, the rival placement of “Ginkgo alone” is rejected (p-value < 0.001, AU test). Similarly, in all cases when “Ginkgo alone” is supported, the rival placement of cycads plus Ginkgo is rejected (p-value < 0.001, AU test).
To determine if nucleotide substitution saturation might influence the incongruent placements of Ginkgo in our concatenation analyses, we characterized sites within each of our rate partitions using an entropy-based index of substitution saturation (ISS) . As ISS approaches 1, or if ISS is not smaller than the critical ISS value (ISS.C), then sequences are determined to exhibit substantial saturation . Our analyses demonstrate that for plastid genes (Figure 3B), the slow-evolving sites exhibit no evidence of saturation (i.e., ISS is significantly smaller than ISS.C; p-value < 0.001, two-tailed t-test), while the fast-evolving sites show evidence of substantial saturation (i.e., ISS is greater than ISS.C when the true topology is asymmetrical). In contrast, our analyses indicate that all rate partitions for nuclear genes show evidence of substantial saturation, but the slow-evolving sites exhibit lower overall levels of saturation (Figure 3B). Thus, the nuclear and plastid genes together suggest that the incongruence we observe in the placement of Ginkgo across rate partitions using the concatenation method may be related to higher overall levels of substitution saturation in fast-evolving nucleotide sites. Further exploration of this question is warranted.
Finally, since previous studies have established the importance of taxon sampling in determining the placement of Ginkgo , we re-analyzed three concatenated nucleotide matrices from previous studies to confirm that our results are not biased by insufficient taxon sampling. These three matrices include a wide breadth of taxon and gene sampling: i) 16 seed plants using 52 plastid genes from Zhong et al. , ii) 64 vascular plants using 53 plastid genes from Wu et al. , and iii) 193 green plants using six genes representing all three plant genomic compartments (i.e., nucleus, plastid, and mitochondrion) from Qiu et al. . Our phylogenetic analyses of these three matrices mirror the results using the concatenation method summarized above. When including only those slow-evolving sites identified by the OV method (Figures S1C–S1E), the clade containing cycads plus Ginkgo is well supported (≥82 BP; Figure 3B). In contrast, analyzing only the fast-evolving sites supports (≥78 BP) the “Gingko alone” hypothesis (Figure 3B). Importantly, the slow-evolving sites in all three matrices exhibit no evidence of saturation (p-value < 0.001, two-tailed t-test); while the fast-evolving sites in two of three matrices show evidence of substantial saturation (Figure 3B).
Our phylogenomic analyses of seed plants identify three main results: i) extant gymnosperms are monophyletic, ii) gnetophytes exhibit discordant placements within conifers between their nuclear and plastid genomes, and iii) cycads plus Ginkgo form a clade that is sister to all remaining extant gymnosperms. Our results also show that standard concatenation analyses of both nuclear and plastid genes produce well supported, but conflicting placements of key taxa across sites with different substitution rates. Determining the causes of this incongruence, however, requires more empirical and simulation studies. Here, we hypothesize that this incongruence may be related to the way in which concatenation methods treat sites with elevated nucleotide substitution rates. Although our concatenation analyses of fast-evolving nucleotide sites produced the “Ginkgo alone” topology, the signal from slow-evolving sites appears to have prevailed. Thus, we did not observe strongly conflicting placements of Ginkgo between coalescent and concatenation methods when analyzing all sites together. One interpretation of these results is that concatenation analyses of full data sets may not be heavily misled by a subset of sites with elevated substitution rates. However, an extrapolation of our specific results suggests that as saturated sites increase in phylogenomic data sets, standard concatenation methods may produce strongly supported but incorrect results. In contrast, coalescent analyses of the same data sets demonstrated consistent placement of cycads plus Ginkgo, suggesting that coalescent-based methods better deal with rate heterogeneity [44-48].
How does this increased phylogenetic resolution enhance our understanding of seed plant evolution? Cycads and Ginkgo share a number of morphological characters, such as their unusual pattern of pollen tube development , flagellated male gametes [75,76], simple female strobili , and embryo development . In light of the increasing support of cycads plus Ginkgo we identify here, some of these traits, which have been commonly thought to be symplesiomorphies of gymnosperms [13,78], may actually represent synapomorphies of the cycads plus Ginkgo clade . Assessing these questions going forward will be challenging, however, given the phenomenally high rate of extinction suffered by gymnosperms . A thoughtful assessment of this question is only likely to be answered with more exhaustive sampling of fossil lineages.
Materials and Methods
Data acquisition and sequence translation
Gene sequences from both nuclear and plastid genomes were gathered for this study. For nuclear genes, assembled unique transcripts were obtained (Table 1) and then translated to amino acid sequences using prot4EST v2.2 . For plastid genes, the fully annotated plastid genomes were obtained from NCBI GenBank (Table 2).
Homology Assignment and Sequence Alignment
The establishment of sequence homology for phylogenetic analyses followed Dunn et al.  and Hejnol et al. . Briefly, sequence similarity was first assessed for all amino acid sequences using BLASTP v2.2.25  with 10-20 e-value threshold, and then grouped using a Markov cluster algorithm as implemented in MCL v09-308  with the inflation value equals 5.0. Clusters were required to i) include at least one sequence from Selaginella (for outgroup rooting), ii) include sequences from at least four species, iii) include at least 100 amino acids for each sequence , iv) have a mean of less than five sequences per species, and v) have a median of less than two sequences per species. Amino acid sequences from each cluster were aligned using MUSCLE v3.8.31 , and ambiguous sites were trimmed using trimAl v1.2rev59  with the heuristic automated method. Sequences were removed from the alignment if they contained less than 70% of the total alignment length . Nucleotide sequences were then aligned according to the corresponding amino acid alignments using PAL2NAL v14 . For each cluster, the gene tree was inferred from nucleotide alignments using RAxML v7.2.8 with the GTRGAMMA substitution model. All but one sequence were deleted in clades of sequences derived from the same species, i.e., monophyly masking, using Phyutility v2.2.6 .
Paralogue pruning and species tree assessment
Paralogue pruning of each gene tree used for species tree assessment followed Hejnol et al. . Briefly, we first identified the maximally inclusive subtree that contains no more than one sequence per species. This subtree is then pruned away and the remaining tree is used as a substrate for another round of pruning. The process is repeated until the remaining tree has no more than one sequence per species. Subtrees produced by paralogue pruning were then filtered to include only those with i) seven or more species and ii) 60% of the species present in the original cluster from which they were derived.
For the coalescent approach, individual gene trees were first inferred using RAxML with the GTRGAMMA substitution model from nucleotide sequences, species relationships were then estimated from gene trees using STAR as implemented in Phybase v1.3 . For concatenation analyses, the concatenated nucleotide matrix was generated from individual genes using Phyutility, and the best-scoring ML tree was obtained using RAxML with the GTRGAMMA substitution model. Bootstrap support was estimated for both coalescent and concatenation methods using a multilocus bootstrap approach as described in the Results and Discussion section with 200 replicates.
Alternative topology tests were performed in the ML framework using the AU test as implemented in scaleboot v0.3-3 . All constrained searches were conducted in RAxML using the GTRGAMMA substitution model.
To subsample gene clusters, the 305 nuclear gene clusters were randomly selected for the sizes of 25, 47, 100, and 200 genes, and the 47 plastid gene clusters were randomly selected for the size of 25 genes. Ten sets of gene clusters were selected as replicates for each size. Species trees and bootstrap support were estimated using STAR and RAxML for each replicate as described above.
Estimation of evolutionary rate and substitution saturation assessment
The OV method was used to measure the relative evolutionary rate of each site in all five concatenated matrices (Figure 3B) as described in the Results and Discussion section. Species trees and bootstrap supports were estimated using STAR and RAxML for each rate partition as described above.
Nucleotide substitution saturation was measured using ISS as implemented in DAMBE . ISS was estimated for each rate partition from 200 replicates with gaps treated as unknown states.
The estimated evolutionary rates for nucleotide sites in all five concatenated matrices analyzed in this study. Parsimony informative sites in each concatenated matrix were sorted based on the Observed Variability (OV) method, and subsequently divided into two equal partitions.
Data characteristics for all 305 nuclear genes, including the locus ID of sequence from Selaginella moellendorffii in each gene, number of species per gene, number of nucleotide sites per gene, and percentage of gaps per gene.
We thank Dannie Durand, Andrew Knoll, and members of the Davis, Durand, and Rest laboratories for advice and discussion. We also thank Casey Dunn, Mike Ethier, and Alexandros Stamatakis for technical support.
Conceived and designed the experiments: ZX JSR CCD. Performed the experiments: ZX. Analyzed the data: ZX JSR CCD. Wrote the manuscript: ZX JSR CCD.
- 1. Rothwell GW, Scheckler SE, Gillespie WH (1989) Elkinsia gen. nov., a late Devonian gymnosperm with cupulate ovules. Bot Gaz 150: 170-189. doi:https://doi.org/10.1086/337763.
- 2. Fiz-Palacios O, Schneider H, Heinrichs J, Savolainen V (2011) Diversification of land plants: insights from a family-level phylogenetic analysis. BMC Evol Biol 11: 341. doi:https://doi.org/10.1186/1471-2148-11-341. PubMed: 22103931.
- 3. Mathews S (2009) Phylogenetic relationships among seed plants: persistent questions and the limits of molecular data. Am J Bot 96: 228-236. doi:https://doi.org/10.3732/ajb.0800178. PubMed: 21628186.
- 4. Goremykin V, Bobrova V, Pahnke J, Troitsky A, Antonov A et al. (1996) Noncoding sequences from the slowly evolving chloroplast inverted repeat in addition to rbcL data do not support Gnetalean affinities of angiosperms. Mol Biol Evol 13: 383-396. doi:https://doi.org/10.1093/oxfordjournals.molbev.a025597. PubMed: 8587503.
- 5. Chaw SM, Zharkikh A, Sung HM, Lau TC, Li WH (1997) Molecular phylogeny of extant gymnosperms and seed plant evolution: analysis of nuclear 18S rRNA sequences. Mol Biol Evol 14: 56-68. doi:https://doi.org/10.1093/oxfordjournals.molbev.a025702. PubMed: 9000754.
- 6. Samigullin TK, Martin WF, Troitsky AV, Antonov AS (1999) Molecular data from the chloroplast rpoC1 gene suggest deep and distinct dichotomy of contemporary spermatophytes into two monophyla: gymnosperms (including Gnetales) and angiosperms. J Mol Evol 49: 310-315. doi:https://doi.org/10.1007/PL00006553. PubMed: 10473771.
- 7. Bowe LM, Coat G, dePamphilis CW (2000) Phylogeny of seed plants based on all three genomic compartments: extant gymnosperms are monophyletic and Gnetales' closest relatives are conifers. Proc Natl Acad Sci U S A 97: 4092-4097. doi:https://doi.org/10.1073/pnas.97.8.4092. PubMed: 10760278.
- 8. Chaw SM, Parkinson CL, Cheng YC, Vincent TM, Palmer JD (2000) Seed plant phylogeny inferred from all three plant genomes: monophyly of extant gymnosperms and origin of Gnetales from conifers. Proc Natl Acad Sci U S A 97: 4086-4091. doi:https://doi.org/10.1073/pnas.97.8.4086. PubMed: 10760277.
- 9. Nickrent DL, Parkinson CL, Palmer JD, Duff RJ (2000) Multigene phylogeny of land plants with special reference to bryophytes and the earliest land plants. Mol Biol Evol 17: 1885-1895. doi:https://doi.org/10.1093/oxfordjournals.molbev.a026290. PubMed: 11110905.
- 10. Gugerli F, Sperisen C, Büchler U, Brunner L, Brodbeck S et al. (2001) The evolutionary split of Pinaceae from other conifers: evidence from an intron loss and a multigene phylogeny. Mol Phylogenet Evol 21: 167-175. doi:https://doi.org/10.1006/mpev.2001.1004. PubMed: 11697913.
- 11. Soltis DE, Soltis PS, Zanis MJ (2002) Phylogeny of seed plants based on evidence from eight genes. Am J Bot 89: 1670-1681. doi:https://doi.org/10.3732/ajb.89.10.1670. PubMed: 21665594.
- 12. Mathews S, Clements MD, Beilstein MA (2010) A duplicate gene rooting of seed plants and the phylogenetic position of flowering plants. Philos Trans R Soc Lond B Biol Sci 365: 383-395. doi:https://doi.org/10.1098/rstb.2009.0233. PubMed: 20047866.
- 13. Crane PR (1985) Phylogenetic analysis of seed plants and the origin of angiosperms. Ann Missouri Bot Gard 72: 716-793. doi:https://doi.org/10.2307/2399221.
- 14. Doyle JA, Donoghue MJ (1986) Seed plant phylogeny and the origin of angiosperms: an experimental cladistic approach. Bot Rev 52: 321-431. doi:https://doi.org/10.1007/BF02861082.
- 15. Wu CS, Chaw SM, Huang YY (2013) Chloroplast phylogenomics indicates that Ginkgo biloba is sister to cycads. Genome Biol Evol 5: 243-254. doi:https://doi.org/10.1093/gbe/evt001. PubMed: 23315384.
- 16. Burleigh JG, Mathews S (2004) Phylogenetic signal in nucleotide data from seed plants: implications for resolving the seed plant tree of life. Am J Bot 91: 1599-1613. doi:https://doi.org/10.3732/ajb.91.10.1599. PubMed: 21652311.
- 17. Hajibabaei M, Xia JN, Drouin G (2006) Seed plant phylogeny: gnetophytes are derived conifers and a sister group to Pinaceae. Mol Phylogenet Evol 40: 208-217. doi:https://doi.org/10.1016/j.ympev.2006.03.006. PubMed: 16621615.
- 18. Qiu YL, Li LB, Wang B, Chen ZD, Dombrovska O et al. (2007) A nonflowering land plant phylogeny inferred from nucleotide sequences of seven chloroplast, mitochondrial, and nuclear genes. Int J Plant Sci 168: 691-708. doi:https://doi.org/10.1086/513474.
- 19. Finet C, Timme RE, Delwiche CF, Marlétaz F (2010) Multigene phylogeny of the green lineage reveals the origin and diversification of land plants. Curr Biol 20: 2217-2222. doi:https://doi.org/10.1016/j.cub.2010.11.035. PubMed: 21145743.
- 20. Regina TMR, Quagliariello C (2010) Lineage-specific group II intron gains and losses of the mitochondrial rps3 gene in gymnosperms. Plant Physiol Biochem 48: 646-654. doi:https://doi.org/10.1016/j.plaphy.2010.05.003. PubMed: 20605476.
- 21. Zhong B, Yonezawa T, Zhong Y, Hasegawa M (2010) The position of gnetales among seed plants: overcoming pitfalls of chloroplast phylogenomics. Mol Biol Evol 27: 2855-2863. doi:https://doi.org/10.1093/molbev/msq170. PubMed: 20601411.
- 22. Wodniok S, Brinkmann H, Glöckner G, Heidel AJ, Philippe H et al. (2011) Origin of land plants: do conjugating green algae hold the key? BMC Evol Biol 11: 104. doi:https://doi.org/10.1186/1471-2148-11-104. PubMed: 21501468.
- 23. Wu CS, Wang YN, Hsu CY, Lin CP, Chaw SM (2011) Loss of different inverted repeat copies from the chloroplast genomes of Pinaceae and cupressophytes and influence of heterotachy on the evaluation of gymnosperm phylogeny. Genome Biol Evol 3: 1284-1295. doi:https://doi.org/10.1093/gbe/evr095. PubMed: 21933779.
- 24. Zhong B, Deusch O, Goremykin VV, Penny D, Biggs PJ et al. (2011) Systematic error in seed plant phylogenomics. Genome Biol Evol 3: 1340-1348. doi:https://doi.org/10.1093/gbe/evr105. PubMed: 22016337.
- 25. Ran JH, Gao H, Wang XQ (2010) Fast evolution of the retroprocessed mitochondrial rps3 gene in Conifer II and further evidence for the phylogeny of gymnosperms. Mol Phylogenet Evol 54: 136-149. doi:https://doi.org/10.1016/j.ympev.2009.09.011. PubMed: 19761858.
- 26. Qiu YL, Lee JH, Bernasconi-Quadroni F, Soltis DE, Soltis PS et al. (1999) The earliest angiosperms: evidence from mitochondrial, plastid and nuclear genomes. Nature 402: 404-407. doi:https://doi.org/10.1038/46536. PubMed: 10586879.
- 27. Qiu YL, Lee J, Bernasconi-Quadroni F, Soltis DE, Soltis PS et al. (2000) Phylogeny of basal angiosperms: analyses of five genes from three genomes. Int J Plant Sci 161: S3-S27. doi:https://doi.org/10.1086/317584.
- 28. Qiu YL, Li LB, Hendry TA, Li RQ, Taylor DW et al. (2006) Reconstructing the basal angiosperm phylogeny: evaluating information content of mitochondrial genes. Taxon 55: 837-856. doi:https://doi.org/10.2307/25065680.
- 29. Qiu YL, Li LB, Wang B, Chen ZD, Knoop V et al. (2006) The deepest divergences in land plants inferred from phylogenomic evidence. Proc Natl Acad Sci U S A 103: 15511-15516. doi:https://doi.org/10.1073/pnas.0603335103. PubMed: 17030812.
- 30. Wu CS, Wang YN, Liu SM, Chaw SM (2007) Chloroplast genome (cpDNA) of Cycas taitungensis and 56 cp protein-coding genes of Gnetum parvifolium: Insights into cpDNA evolution and phylogeny of extant seed plants. Mol Biol Evol 24: 1366-1379. doi:https://doi.org/10.1093/molbev/msm059. PubMed: 17383970.
- 31. Rydin C, Kallersjo M, Friist EM (2002) Seed plant relationships and the systematic position of Gnetales based on nuclear and chloroplast DNA: conflicting data, rooting problems, and the monophyly of conifers. Int J Plant Sci 163: 197-214. doi:https://doi.org/10.1086/338321.
- 32. Burleigh JG, Mathews S (2007) Assessing among-locus variation in the inference of seed plant phylogeny. Int J Plant Sci 168: 111-124. doi:https://doi.org/10.1086/509586.
- 33. Rai HS, Reeves PA, Peakall R, Olmstead RG, Graham SW (2008) Inference of higher-order conifer relationships from a multi-locus plastid data set. Botany 86: 658-669. doi:https://doi.org/10.1139/B08-062.
- 34. de la Torre-Bárcena JE, Kolokotronis SO, Lee EK, Stevenson DW, Brenner ED et al. (2009) The impact of outgroup choice and missing data on major seed plant phylogenetics using genome-wide EST data. PLOS ONE 4: e5764. doi:https://doi.org/10.1371/journal.pone.0005764. PubMed: 19503618.
- 35. Graham SW, Iles WJD (2009) Different gymnosperm outgroups have (mostly) congruent signal regarding the root of flowering plant phylogeny. Am J Bot 96: 216-227. doi:https://doi.org/10.3732/ajb.0800320. PubMed: 21628185.
- 36. Cibrián-Jaramillo A, De la Torre-Bárcena JE, Lee EK, Katari MS, Little DP et al. (2010) Using phylogenomic patterns and gene ontology to identify proteins of importance in plant evolution. Genome Biol Evol 2: 225-239. doi:https://doi.org/10.1093/gbe/evq012. PubMed: 20624728.
- 37. Lee EK, Cibrian-Jaramillo A, Kolokotronis SO, Katari MS, Stamatakis A et al. (2011) A functional phylogenomic view of the seed plants. PLOS Genet 7: e1002411.
- 38. Huelsenbeck JP, Bull JJ, Cunningham CW (1996) Combining data in phylogenetic analysis. Trends Ecol Evol 11: 152-158. doi:https://doi.org/10.1016/0169-5347(96)10006-9. PubMed: 21237790.
- 39. Mossel E, Vigoda E (2005) Phylogenetic MCMC algorithms are misleading on mixtures of trees. Science 309: 2207-2209. doi:https://doi.org/10.1126/science.1115493. PubMed: 16195459.
- 40. Degnan JH, Rosenberg NA (2006) Discordance of species trees with their most likely gene trees. PLoS Genet 2: e68. doi:https://doi.org/10.1371/journal.pgen.0020068. PubMed: 16733550.
- 41. Kubatko LS, Degnan JH (2007) Inconsistency of phylogenetic estimates from concatenated data under coalescence. Syst Biol 56: 17-24. doi:https://doi.org/10.1080/10635150601146041. PubMed: 17366134.
- 42. Rosenberg NA, Tao R (2008) Discordance of species trees with their most likely gene trees: the case of five taxa. Syst Biol 57: 131-140. doi:https://doi.org/10.1080/10635150801905535. PubMed: 18300026.
- 43. Liu L, Edwards SV (2009) Phylogenetic analysis in the anomaly zone. Syst Biol 58: 452-460. doi:https://doi.org/10.1093/sysbio/syp034. PubMed: 20525599.
- 44. Liu L, Pearl DK, Brumfield RT, Edwards SV (2008) Estimating species trees using multiple-allele DNA sequence data. Evolution 62: 2080-2091. doi:https://doi.org/10.1111/j.1558-5646.2008.00414.x. PubMed: 18462214.
- 45. Degnan JH, Rosenberg NA (2009) Gene tree discordance, phylogenetic inference and the multispecies coalescent. Trends Ecol Evol 24: 332-340. doi:https://doi.org/10.1016/j.tree.2009.01.009. PubMed: 19307040.
- 46. Liu L, Yu L, Pearl DK, Edwards SV (2009) Estimating species phylogenies using coalescence times among sequences. Syst Biol 58: 468-477. doi:https://doi.org/10.1093/sysbio/syp031. PubMed: 20525601.
- 47. Liu L, Yu L, Edwards SV (2010) A maximum pseudo-likelihood approach for estimating species trees under the coalescent model. BMC Evol Biol 10: 302. doi:https://doi.org/10.1186/1471-2148-10-302. PubMed: 20937096.
- 48. Song S, Liu L, Edwards SV, Wu S (2012) Resolving conflict in eutherian mammal phylogeny using phylogenomics and the multispecies coalescent model. Proc Natl Acad Sci U S A 109: 14942-14947. doi:https://doi.org/10.1073/pnas.1211733109. PubMed: 22930817.
- 49. Enright AJ, van Dongen S, Ouzounis CA (2002) An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res 30: 1575-1584. doi:https://doi.org/10.1093/nar/30.7.1575. PubMed: 11917018.
- 50. Duvick J, Fu A, Muppirala U, Sabharwal M, Wilkerson MD et al. (2008) PlantGDB: a resource for comparative plant genomics. Nucleic Acids Res 36: D959-D965. PubMed: 18063570.
- 51. Jiao Y, Wickett NJ, Ayyampalayam S, Chanderbali AS, Landherr L et al. (2011) Ancestral polyploidy in seed plants and angiosperms. Nature 473: 97-100. doi:https://doi.org/10.1038/nature09916. PubMed: 21478875.
- 52. Banks JA, Nishiyama T, Hasebe M, Bowman JL, Gribskov M et al. (2011) The Selaginella genome identifies genetic changes associated with the evolution of vascular plants. Science 332: 960-963. doi:https://doi.org/10.1126/science.1203810. PubMed: 21551031.
- 53. Medgyesy P, Fejes E, Maliga P (1985) Interspecific chloroplast recombination in a Nicotiana somatic hybrid. Proc Natl Acad Sci U S A 82: 6960-6964. doi:https://doi.org/10.1073/pnas.82.20.6960. PubMed: 16593619.
- 54. Ogihara Y, Terachi T, Sasakuma T (1988) Intramolecular recombination of chloroplast genome mediated by short direct-repeat sequences in wheat species. Proc Natl Acad Sci U S A 85: 8573-8577. doi:https://doi.org/10.1073/pnas.85.22.8573. PubMed: 3186748.
- 55. Rajora OP, Dancik BP (1995) Chloroplast DNA variation in Populus. III. Novel chloroplast DNA variants in natural Populus × canadensis hybrids. Theor Appl Genet 90: 331-334. PubMed: 24173921.
- 56. Wolfe AD, Randle CP (2004) Recombination, heteroplasmy, haplotype polymorphism, and paralogy in plastid genes: Implications for plant molecular systematics. Syst Bot 29: 1011-1020. doi:https://doi.org/10.1600/0363644042451008.
- 57. Jakob SS, Blattner FR (2006) A chloroplast genealogy of Hordeum (Poaceae): long-term persisting haplotypes, incomplete lineage sorting, regional extinction, and the consequences for phylogenetic inference. Mol Biol Evol 23: 1602-1612. doi:https://doi.org/10.1093/molbev/msl018. PubMed: 16754643.
- 58. Stamatakis A (2006) RAxML-VI-HPC: Maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 22: 2688-2690. doi:https://doi.org/10.1093/bioinformatics/btl446. PubMed: 16928733.
- 59. Seo TK (2008) Calculating bootstrap probabilities of phylogeny using multilocus sequence data. Mol Biol Evol 25: 960-971. doi:https://doi.org/10.1093/molbev/msn043. PubMed: 18281270.
- 60. Shimodaira H (2002) An approximately unbiased test of phylogenetic tree selection. Syst Biol 51: 492-508. doi:https://doi.org/10.1080/10635150290069913. PubMed: 12079646.
- 61. Olsen GJ (1987) Earliest phylogenetic branchings: comparing rRNA-based evolutionary trees inferred with various techniques. Cold Spring Harb Symp Quant Biol 52: 825-837. doi:https://doi.org/10.1101/SQB.1987.052.01.090. PubMed: 3454291.
- 62. Goremykin VV, Nikiforova SV, Bininda-Emonds OR (2010) Automated removal of noisy data in phylogenomic analyses. J Mol Evol 71: 319-331. doi:https://doi.org/10.1007/s00239-010-9398-z. PubMed: 20976444.
- 63. Brinkmann H, Philippe H (1999) Archaea sister group of bacteria? Indications from tree reconstruction artifacts in ancient phylogenies. Mol Biol Evol 16: 817-825. doi:https://doi.org/10.1093/oxfordjournals.molbev.a026166. PubMed: 10368959.
- 64. Hirt RP, Logsdon JM, Healy B, Dorey MW, Doolittle WF et al. (1999) Microsporidia are related to Fungi: evidence from the largest subunit of RNA polymerase II and other proteins. Proc Natl Acad Sci U S A 96: 580-585. doi:https://doi.org/10.1073/pnas.96.2.580. PubMed: 9892676.
- 65. Philippe H, Lopez P, Brinkmann H, Budin K, Germot A et al. (2000) Early-branching or fast-evolving eukaryotes? An answer based on slowly evolving positions. Proc Biol Sci 267: 1213-1221. doi:https://doi.org/10.1098/rspb.2000.1130. PubMed: 10902687.
- 66. Gribaldo S, Philippe H (2002) Ancient phylogenetic relationships. Theor Popul Biol 61: 391-408. doi:https://doi.org/10.1006/tpbi.2002.1593. PubMed: 12167360.
- 67. Pisani D (2004) Identifying and removing fast-evolving sites using compatibility analysis: an example from the arthropoda. Syst Biol 53: 978-989. doi:https://doi.org/10.1080/10635150490888877. PubMed: 15764565.
- 68. Philippe H, Roure B (2011) Difficult phylogenetic questions: more data, maybe; better methods, certainly. BMC Biol 9: 91. doi:https://doi.org/10.1186/1741-7007-9-91. PubMed: 22206462.
- 69. Schneider H, Schuettpelz E, Pryer KM, Cranfill R, Magallón S et al. (2004) Ferns diversified in the shadow of angiosperms. Nature 428: 553-557. doi:https://doi.org/10.1038/nature02361. PubMed: 15058303.
- 70. Smith SA, Beaulieu JM, Donoghue MJ (2010) An uncorrelated relaxed-clock analysis suggests an earlier origin for flowering plants. Proc Natl Acad Sci U S A 107: 5897-5902. doi:https://doi.org/10.1073/pnas.1001225107. PubMed: 20304790.
- 71. Clarke JT, Warnock RCM, Donoghue PCJ (2011) Establishing a time-scale for plant evolution. New Phytol 192: 266-301. doi:https://doi.org/10.1111/j.1469-8137.2011.03794.x. PubMed: 21729086.
- 72. Magallón S, Hilu KW, Quandt D (2013) Land plant evolutionary timeline: gene effects are secondary to fossil constraints in relaxed clock estimation of age and substitution rates. Am J Bot 100: 556-573. doi:https://doi.org/10.3732/ajb.1200416. PubMed: 23445823.
- 73. 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. doi:https://doi.org/10.1016/S1055-7903(02)00326-3. PubMed: 12470932.
- 74. Friedman WE (1993) The evolutionary history of the seed plant male gametophyte. Trends Ecol Evol 8: 15-21. doi:https://doi.org/10.1016/0169-5347(93)90125-9. PubMed: 21236093.
- 75. Brenner ED, Stevenson DW, Twigg RW (2003) Cycads: evolutionary innovations and the role of plant-derived neurotoxins. Trends Plant Sci 8: 446-452. doi:https://doi.org/10.1016/S1360-1385(03)00190-0. PubMed: 13678912.
- 76. Norstog KJ, Gifford EM, Stevenson DW (2004) Comparative development of the spermatozoids of cycads and Ginkgo biloba. Bot Rev 70: 5-15. Available online at: 10.1663/0006-8101(2004)070[0005:CDOTSO]2.0.CO;2
- 77. Rudall PJ, Bateman RM (2010) Defining the limits of flowers: the challenge of distinguishing between the evolutionary products of simple versus compound strobili. Philos Trans R Soc Lond B Biol Sci 365: 397-409. doi:https://doi.org/10.1098/rstb.2009.0234. PubMed: 20047867.
- 78. Wang L, Wang D, Lin MM, Lu Y, Jiang XX et al. (2011) An embryological study and systematic significance of the primitive gymnosperm Ginkgo biloba. J Syst Evol 49: 353-361. doi:https://doi.org/10.1111/j.1759-6831.2011.00123.x.
- 79. Crisp MD, Cook LG (2011) Cenozoic extinctions account for the low diversity of extant gymnosperms compared with angiosperms. New Phytol 192: 997-1009. doi:https://doi.org/10.1111/j.1469-8137.2011.03862.x. PubMed: 21895664.
- 80. Wasmuth JD, Blaxter ML (2004) prot4EST: translating expressed sequence tags from neglected genomes. BMC Bioinformatics 5: 187. doi:https://doi.org/10.1186/1471-2105-5-187. PubMed: 15571632.
- 81. Dunn CW, Hejnol A, Matus DQ, Pang K, Browne WE et al. (2008) Broad phylogenomic sampling improves resolution of the animal tree of life. Nature 452: 745-749. doi:https://doi.org/10.1038/nature06614. PubMed: 18322464.
- 82. Hejnol A, Obst M, Stamatakis A, Ott M, Rouse GW et al. (2009) Assessing the root of bilaterian animals with scalable phylogenomic methods. Proc Biol Sci 276: 4261-4270. doi:https://doi.org/10.1098/rspb.2009.0896. PubMed: 19759036.
- 83. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215: 403-410. doi:https://doi.org/10.1016/S0022-2836(05)80360-2. PubMed: 2231712.
- 84. Liu QP, Xue QZ (2005) Comparative studies on codon usage pattern of chloroplasts and their host nuclear genes in four plant species. J Genet 84: 55-62. doi:https://doi.org/10.1007/BF02715890. PubMed: 15876584.
- 85. Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32: 1792-1797. doi:https://doi.org/10.1093/nar/gkh340. PubMed: 15034147.
- 86. Capella-Gutiérrez S, Silla-Martínez JM, Gabaldón T (2009) trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25: 1972-1973. doi:https://doi.org/10.1093/bioinformatics/btp348. PubMed: 19505945.
- 87. Jiao Y, Leebens-Mack J, Ayyampalayam S, Bowers JE, McKain MR et al. (2012) A genome triplication associated with early diversification of the core eudicots. Genome Biol 13: R3. doi:https://doi.org/10.1186/gb-2012-13-1-r3. PubMed: 22280555.
- 88. Suyama M, Torrents D, Bork P (2006) PAL2NAL: robust conversion of protein sequence alignments into the corresponding codon alignments. Nucleic Acids Res 34: W609-W612. doi:https://doi.org/10.1093/nar/gkl315. PubMed: 16845082.
- 89. Smith SA, Dunn CW (2008) Phyutility: a phyloinformatics tool for trees, alignments and molecular data. Bioinformatics 24: 715-716. doi:https://doi.org/10.1093/bioinformatics/btm619. PubMed: 18227120.
- 90. Liu L, Yu L (2010) Phybase: an R package for species tree analysis. Bioinformatics 26: 962-963. doi:https://doi.org/10.1093/bioinformatics/btq062. PubMed: 20156990.
- 91. Shimodaira H (2008) Testing regions with nonsmooth boundaries via multiscale bootstrap. J Stat Plan Infer 138: 1227-1241. doi:https://doi.org/10.1016/j.jspi.2007.04.001.
- 92. Xia X, Xie Z (2001) DAMBE: software package for data analysis in molecular biology and evolution. J Hered 92: 371-373. doi:https://doi.org/10.1093/jhered/92.4.371. PubMed: 11535656.