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. 2022 Oct 17;109(10):1596–1606. doi: 10.1002/ajb2.16065

A first complete phylogenomic hypothesis for diploid blueberries (Vaccinium section Cyanococcus)

Andrew A Crowl 1,2,✉, Peter W Fritsch 3, George P Tiley 2,4, Nathan P Lynch 1,5, Thomas G Ranney 1,5, Hamid Ashrafi 1, Paul S Manos 2
PMCID: PMC10286767  PMID: 36109839

Abstract

Premise

The true blueberries (Vaccinium sect. Cyanococcus; Ericaceae), endemic to North America, have been intensively studied for over a century. However, with species estimates ranging from nine to 24 and much confusion regarding species boundaries, this ecologically and economically valuable group remains inadequately understood at a basic evolutionary and taxonomic level. As a first step toward understanding the evolutionary history and taxonomy of this species complex, we present the first phylogenomic hypothesis of the known diploid blueberries.

Methods

We used flow cytometry to verify the ploidy of putative diploid taxa and a target‐enrichment approach to obtain a genomic data set for phylogenetic analyses.

Results

Despite evidence of gene flow, we found that a primary phylogenetic signal is present. Monophyly for all morphospecies was recovered, with two notable exceptions: one sample of V. boreale was consistently nested in the V. myrtilloides clade and V. caesariense was nested in the V. fuscatum clade. One diploid taxon, Vaccinium pallidum, is implicated as having a homoploid hybrid origin.

Conclusions

This foundational study represents the first attempt to elucidate evolutionary relationships of the true blueberries of North America with a phylogenomic approach and sets the stage for multiple avenues of future study such as a taxonomic revision of the group, the verification of a homoploid hybrid taxon, and the study of polyploid lineages within the context of a diploid phylogeny.

Keywords: alleles, Ericaceae, homoploid hybridization, HybSeq, phasing, phylogenetics, target enrichment, Vaccinium

A ubiquitous component of heathlands and other acidophilic plant communities, as well as a food source for wildlife and humans, the true blueberries (Vaccinium section Cyanococcus A. Gray; henceforth “Cyanococcus”) are of immense ecological and economic value. Commercially cultivated blueberries originate from this group—representing one of only a handful of widely cultivated plants originating in North America. Despite its economic importance, Cyanococcus has suffered from conflicting taxonomies with poorly defined species boundaries and little investigation into the evolutionary history of wild populations.

Cyanococcus is a reticulate species complex of ca. 9–24 species comprising diploids (2n = 2x = 24), tetraploids, and hexaploids distributed across much of temperate North America (Figure 1). The section is easily distinguished from other sections of Vaccinium L. by several unique or otherwise diagnostic characters (e.g., verrucose branchlets, articulated pedicels, awnless anthers, and pseudo‐10‐locular berries; Camp, 1945; Vander Kloet, 1983). In addition to morphological characters, the available molecular data suggest that the group forms a clade (Kron et al., 2002; A. Crowl et al., unpublished data), although sufficient sampling has yet to be undertaken to satisfactorily test monophyly.

Figure 1.

Figure 1

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Geographic distribution maps for diploid Cyanococcus morphospecies. Black symbols indicate populations included in our broad survey of ploidy and morphology. Yellow symbols indicate a subset of those samples sequenced and included in phylogenomic analyses.

Cyanococcus served as a model system during the Modern Synthesis (Huxley, 1942), playing a pivotal role in furthering our understanding of polyploidy and expanding the scope of the movement to include plants. Toward the goal of crop improvement, W. H. Camp and colleagues (Camp, 1942, 1945; Camp and Gilly, 1943; Darrow and Camp, 1945) used data from morphology, crossing studies, genetics, and cytology to propose a complex series of ancestor‐descendant polyploid species relationships in Cyanococcus, some through autopolyploidy, others through allopolyploidy. In some cases, Camp (1945) documented size differences correlated with ploidy, such as larger stature and flowers, which has recently been confirmed in one mixed diploid and tetraploid population (Poster et al., 2017). Finally, by equating artificially produced hybrid progeny with morphologically similar plants in the wild, Camp concluded that natural hybrids are rampant among blueberry species, although a strong triploid block, now well known among plant breeders (e.g., Lyrene et al., 2003), was seen to inhibit the viability of progeny with odd‐numbered sets of chromosomes.

Subsequently, S. P. Vander Kloet revised Camp's taxonomy in the context of morphological phenetics. The most consequential of Vander Kloet's conclusions from this work was the supposition that all Cyanococcus species >1 m tall (“highbush”) have been derived from a genetic amalgamation of mostly diploid species <1 m tall (“lowbush”), thus forming a “compilospecies” (Harlan and de Wet, 1963) of multiple origins and of variable ploidy (Vander Kloet, 1980, 1983, 1988). In this context, Vander Kloet aggregated 12 of Camp's species into a single highly variable highbush blueberry, V. corymbosum L. Although many authors have questioned this extremely broad concept—on the basis of habit; leaf, flower, and stem morphology; phenology; and ecology (e.g., Uttal, 1987; Weakley, 2020; Fritsch et al., in press)—this taxonomic view of Cyanococcus is currently considered the standard, having been adopted by the USDA, plant breeders, and many local and regional floras, including the Flora of North America (Vander Kloet, 2009).

Much prior research on Cyanococcus has highlighted the challenges involved in disentangling this group, but more recent research suggests that the prospects are hopeful for resolving long‐standing questions regarding its species composition, patterns of speciation, and evolutionary history (Fritsch et al., in press). In this respect, the rapid maturation of genomic approaches to the study of complex groups of organisms affords a timely opportunity to revisit the evolution of the true blueberries. The multiple ploidy levels inherent in Cyanococcus, the group's ecological and economic importance, and the genomic resources now available make Cyanococcus an ideal system for understanding polyploidy and cryptic speciation in flowering plants. Surprisingly, however, the evolution of the group as a whole has yet to be studied with such approaches. This has left Cyanococcus in an unsatisfactory state, for both evolutionary biologists and plant breeders alike.

Here, we provide a first glimpse into the evolutionary history of Cyanococcus with genomic data by reconstructing a diploid phylogeny with genomic data from hundreds of nuclear loci, with flow cytometry analyses conducted to verify ploidy of all currently recognized putative diploid taxa. Our results will be useful for future study of polyploid Cyanococcus lineages and updating the taxonomy of this important group of plants.

MATERIALS AND METHODS

Flow cytometry

Ploidy was estimated with flow cytometry at the Mountain Horticultural Crops Research and Extension Center (North Carolina, USA). Leaf samples were quickly dried in the field with silica gel. This dried tissue (~1.5 cm2) was finely chopped with a razor blade in a Petri dish with 400 mL of nuclei extraction buffer (CyStain UV Precise P Nuclei Extraction Buffer, Sysmex Partec, Görlitz, Germany). The solution was incubated for 1–2 min at ~24°C and then filtered through Partec CellTrics disposable filters with a pore size of 50 µm to remove tissue debris. Nuclei were stained with 1.6 mL of 4′,6‐Diamidino‐2‐phenylindole (DAPI) staining buffer (CyStain UV Precise P Staining Buffer, Sysmex Partec). Stained nuclei were analyzed with a flow cytometer (Partec PA‐II, Partec) to determine relative genome size. Counts exceeded a minimum of 3000 cells per sample, and two subsamples were run for each sample. Genome sizes were determined by comparing mean relative fluorescence of each sample with an internal standard, Pisum sativum L. ‘Ctirad,’ with a known genome size of 8.76 pg (Doležel et al., 2007) and calculated as follows: 2 C genome size of sample = 8.76 pg × (mean fluorescence value of sample/mean fluorescence value of standard). The validity of this method for estimating ploidy levels in Vaccinium has been previously demonstrated (with fresh leaf material) by Hummer et al. (2015) and Costich et al. (1993), the latter showing that an observed increase in nuclear DNA content is concurrent with an equivalent increase in ploidy.

Sampling and sequencing

We sampled 36 Cyanococcus individuals, each from different natural populations, representing eight putative diploid species (Appendix S1). Species determination followed the morphospecies concepts summarized in Weakley (2020), in addition to the V. boreale I.V. Hall & Aalders concept of Vander Kloet (1988). Three additional taxa—V. arboreum Marshall (Vaccinium sect. Batodendron), V. macrocarpon Aiton (Vaccinium sect. Oxycoccus), and V. stamineum L. (Vaccinium sect. Polycodium)—comprised the outgroup.

DNA extractions were carried out with a modified CTAB approach for all samples (Doyle and Doyle, 1987). The concentration of DNA from extractions was quantified with a Qubit 2.0 (Invitrogen, Carlsbad, California, USA) and the Qubit dsDNA Broad Range Assay Kit following the manufacturer's recommendations. Samples ranging from 115 to 3000 ng of DNA were sent to Arbor Biosciences (Ann Arbor, Michigan, USA) for library preparation and DNA sequencing on a NovaSeq S4 sequencer (Illumina, San Diego, California, USA) with 2 × 150 bp chemistry. The Angiosperms353 v1 target capture kit (Johnson et al., 2019) was used for targeted enrichment of each sample.

Sequence data processing

Raw sequences were filtered and processed with the Trim Galore wrapper script (version 0.6.5), which uses Cutadapt (version 2.6; Martin, 2011) and FastQC (version 0.11.9; Andrews, 2010) to trim adapters and low‐quality reads based on a given Phred quality score cutoff (‐q 20). Consensus read assembly for target loci was performed with the default settings in HybPiper (version 1.3.1; Johnson et al., 2016). Following the recommendations of McLay et al. (2021), we included available Ericales sequences in the target reference file in addition to the standard Angiosperms353 targets to improve the recovery of targeted loci. Supercontig sequences were then assembled with the intronerate.py script available as a part of HybPiper. To screen for potential paralogs, we identified loci/samples in which multiple contigs were generated during the assembly step with the paralog_investigator.py script. All loci in which a paralog was suspected were removed from the data set. The remaining consensus reads were used as the reference to generate both IUPAC and allele data sets (see below).

Allele phasing

HybSeq data are typically processed in a way that results in single consensus sequences for loci, thus ignoring allelic variation (Andermann et al., 2018; Tiley et al., 2021 [preprint]). However, allelic data may be important in the estimation of species networks when gene flow among taxa is present (Tiley et al., 2021 [preprint]). To include this variation, we employed the recently developed bioinformatics pipeline PATÉ (Tiley et al., 2021 [preprint]) to phase alleles. The pipeline uses consensus loci (in this case, supercontig sequences) created with HybPiper as reference sequences, and Illumina reads are mapped back to these loci using the BWA‐MEM algorithm from BWA (Li and Durbin, 2009). Variant calling is carried out at the ploidy level determined by flow cytometry for each individual using the HaplotypeCaller program from GATK (McKenna et al., 2010). Potentially erroneous variant calls are filtered out, based on the following parameters outlined in DePristo et al. (2011), with the VariantFiltration program in GATK: (1) QD < 2.0, (2) FS > 60.0, (3) MQ < 40.0, (4) ReadPosRankSum < 8.0. We also remove variants present on <5% or >95% of reads (AF < 0.05 || AF > 0.95) and variants with a depth of <10 reads (DP < 10). The resulting vcf file for each individual is passed to H‐PoPG (Xie et al., 2016) for allele phasing, which solves for the specified number of haplotypes that minimizes the number of switch errors among the reads present in the BAM file using a dynamic programming solution. PATÉ then takes variants from the largest phase block, combines them with sequences from regions of the locus that could not be phased because of insufficient read overlap, and replaces them with ambiguity codes so that the resulting alleles are the same length as the original consensus loci, similar to previous phasing strategies exclusive to diploids (Kates et al., 2018). PATÉ additionally provides full IUPAC sequences in which all heterozygous sites are replaced by ambiguity codes, which were analyzed alongside individual allele sequences.

Maximum likelihood analyses

Alignments were carried out with FSA (Bradley et al., 2009). To reduce potential issues with missing data and poorly aligned ends, we removed alignment columns containing >50% missing data. Individual IUPAC gene trees and allele trees were constructed with IQ‐TREE (version 1.6.9; Nguyen et al., 2015). ModelFinder Plus was used to first select the best model for each locus. To assess topological support, we implemented the ultrafast bootstrap approximation UFBoot2 (Hoang et al., 2018) with 1000 replicates in which sites within partitions (loci) were resampled, an approach that is similar to the standard nonparametric bootstrap.

A concatenated alignment was produced for the IUPAC data set with the pxcat command in Phyx (Brown et al., 2017). A partitioned phylogenetic analysis, where partitions were individual loci, was performed with IQ‐TREE. The best‐fit partitioning scheme was chosen with the PartitionFinder algorithm (‐m TESTMERGE; Lanfear et al., 2012) implemented in IQ‐TREE. A relaxed clustering algorithm (‐rcluster 10; Lanfear et al., 2014) was implemented to consider only the top 10% of partitioning schemes. As above, 1000 ultrafast bootstrap replicates were performed to assess support.

Species‐tree analyses

Multiple species‐tree methods were used to estimate a diploid species tree for Cyanococcus. Singular value decomposition quartet species‐tree estimation (SVDquartets; Chifman and Kubatko, 2014), implemented in Paup* (version 4a142; Swofford, 2002), was run on the concatenated IUPAC data matrix, all possible quartets were evaluated, and support was assessed with 100 bootstrap replicates. We also used ASTRAL‐III (version 5.5.6; Zhang et al., 2018) on the individual IUPAC gene trees and allele trees. Alleles were assigned to individuals or species with the allele mapping (‐a) option. We additionally used STACEY (Jones, 2017), available as part of the BEAST2 package (Bouckaert et al., 2014), to estimate a species tree from the IUPAC and allele data sets in a Bayesian framework. Substitution models, clock models, and gene trees were unlinked for all loci. The birth‐death‐collapse model was used as a species‐tree prior. To enable ambiguous site processing of the IUPAC data set, we manually added useAmbiguities = “true” to the gene‐tree likelihood priors in the XML file. All analyses were run for 10 million generations, retaining one sample every 10,000 generations, or until convergence of all parameters (ESS values > 200), as assessed with Tracer (version 1.7.2; Rambaut et al., 2018).

Network analyses

Hybridization is thought to be common in Cyanococcus (Camp, 1945; Vander Kloet, 1988). To investigate potential reticulation between diploid taxa, we used a pseudolikelihood approach as implemented in SNaQ (Solís‐Lemus and Ané, 2016). For each data set (IUPAC and alleles), we tested models in which we allowed a maximum of zero to three hybridization events (hmax = 0–3) and used the log pseudolikelihood profile of these runs to estimate the best‐fitting model. Gene trees inferred from IQ‐TREE were used as input. Twenty independent runs were used for each hmax value. The computational constraints of this method precluded the estimation of a network with every sample represented as a tip in the tree. Instead, alleles from individual allele trees were assigned to species, resulting in a network in which tips represented species. The IUPAC data set was subsampled such that each species was represented by one to three samples. To more precisely estimate the placement of the hybrid event suggested by these analyses (i.e., was a single V. pallidum population involved or did the hybrid event predate all sampled V. pallidum populations?), we constructed an additional IUPAC data set including all eight sampled individuals of V. pallidum.

Concordance‐discordance analyses

Because high bootstrap support can be recovered from phylogenetic analyses despite a low number of genes supporting the topology (e.g., Minh et al., 2020), we additionally assessed conflict within our data set using gene concordance factors (gCF; percentage of genes supporting a given clade) and site concordance factors (sCF; percentage of informative sites) as implemented in IQ‐TREE. Individual IUPAC gene trees were used to calculate both gCF and sCF with 1000 random quartets in the sCF analysis (–scf 1000) for each of the topologies inferred from concatenated and species‐tree analyses (see above).

Discordance was additionally assessed with PhyParts (version 0.0.1; Smith et al., 2015). The best individual IUPAC gene trees inferred from IQ‐TREE were rooted and outgroup taxa were removed with Phyx. Results from these analyses were visualized with the PhyPartsPieCharts script. As in the gCF/sCF analyses, we tested each of the topologies inferred from concatenated and species‐tree analyses.

RESULTS

Flow cytometry

Flow cytometry analysis of silica‐dried leaf material provided clear genome‐size estimation for 33 of 36 Cyanococcus samples (Appendix S1). Average 2 C values ranged from 1.08 to 1.65 pg, within the range for diploid Vaccinium individuals previously determined by Hummer et al. (2015) and Redpath et al. (2022). Although we are in the process of reassessing the morphological characters traditionally used to define species in Cyanococcus, ploidy estimates mostly conformed to expectations based on morphological identification and observations of the size and density of stomata on second‐year branchlets (Fritsch et al., in press). The one conspicuous exception is V. boreale, which was nearly indistinguishable on the basis of morphology from its tetraploid counterpart, V. angustifolium, although more detailed analysis of stomatal size and density may facilitate identification (Aalders and Hall, 1962).

Sequence data

Of the 353 loci targeted with the Angiosperms353 probe set, we successfully captured and sequenced 348. Of these, 25 were flagged as potentially containing paralogs. After removing these loci and all columns containing >50% missing data, the final concatenated IUPAC alignment consisted of 323 loci of alignment length 672,737 bp (= characters); 22,421 of the characters were parsimony informative. Individual supercontig gene (and allele) alignments ranged in length from 272 to 7064 bp.

Maximum likelihood analyses

Concatenated maximum likelihood (ML) analyses of the IUPAC data set with IQ‐TREE resulted in an overall well‐supported topology and maximally supported Cyanococcus clade (Figure 2A). A northern lineage of V. boreale and V. myrtilloides was placed as sister to a large clade composed of the remaining taxa with distributions extending into the southeastern United States. Within this clade, we found three sister‐species relationships: V. elliottii–V. pallidum, V. darrowii–V. tenellum, and V. fuscatum–V. caesariense. This diploid analysis distinguished six maximally supported terminal groups. One sample of V. boreale was found to be nested within V. myrtilloides, and our only sample of V. caesariense nested within V. fuscatum.

Figure 2.

Figure 2

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Comparison of topologies recovered from concatenated and species‐tree analyses for the diploid Cyanococcus clade (highlighted in blue). Note the inconsistent placement of V. pallidum and V. elliottii populations between analyses and data sets. Sample numbers refer to the voucher table in Appendix S1. Values above branches indicate support (bootstrap or posterior probability). Values below branches indicate gene concordance factors (gCF) and site concordance factors (sCF). These are reported as gCF/sCF. Intraspecific (population‐level) support values are not shown. (A) Phylogenetic estimate from IQ‐TREE analysis of the concatenated IUPAC data set. (B) Species tree inferred from SVDquartets analysis of the concatenated IUPAC data set. (C) Species tree inferred from ASTRAL‐III analysis of the IUPAC data set. (D) Species tree inferred from ASTRAL‐III analysis of the allele data set.

Species‐tree analyses

The SVDquartets analysis (IUPAC data set) recovered V. elliottii as non‐monophyletic, with one sample sister to the V. fuscatum–V. caesariense clade and the other two in a much deeper position in the tree, albeit with low support (Figure 2B). The remaining relationships were consistent with the results from IQ‐TREE and ASTRAL‐III, including the non‐monophyly of V. boreale and the nested position of V. caesariense within the V. fuscatum clade (Figure 2). ASTRAL‐III analyses recovered a topology (Figure 2C, D) largely consistent with the concatenated ML results. However, the placement of V. elliottii differed between IUPAC (Figure 2C) and allele analyses (Figure 2D). This taxon was recovered as sister to V. pallidum with the IUPAC data set, whereas it was recovered as sister to other diploid highbush taxa, V. fuscatum and V. caesariense, with the allele data set, again with low support. This conflicting placement was observed regardless of whether alleles were assigned to individuals (Figure 2) or species (Figure 3). Species‐tree analyses with STACEY placed V. elliottii sister to the V. fuscatum–V. caesariense clade and V. pallidum as a stand‐alone lineage. This topology was recovered with both the IUPAC and allele data sets and is consistent with the topology inferred in our ASTRAL analysis of allele data. A unique topology in which V. pallidum is sister to the V. boreale–V. myrtilloides clade was observed when scrutinizing the posterior distribution of trees (Figure 4). This signal, however, is only present in the lowest 5% of the posterior distribution from the IUPAC analysis.

Figure 3.

Figure 3

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Comparison of species trees inferred from IUPAC and allele data. In both instances, alleles and IUPAC sequences were assigned to species. Note the inconsistent placement of V. pallidum and V. elliottii between data sets. (A) Species tree inferred from ASTRAL‐III analysis of the IUPAC data set. (B) Species tree inferred from ASTRAL‐III analysis of the allele data set. Values on branches indicate local posterior probability support.

Figure 4.

Figure 4

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Evidence for the homoploid hybrid origin of Vaccinium pallidum. (A) Network inferred from the allele data set in which alleles were assigned to species. Values on hybrid edges are the estimated genomic contributions from each parent (gamma). (B) Posterior distribution of Bayesian species‐tree analysis. The lowest 5% of trees from the posterior distribution are depicted in yellow, showing alternative placement of V. pallidum sister to V. myrtilloides and V. boreale. (C) Network inferred from IUPAC data set with increased population sampling. Note that the hybrid event predates divergence of all sampled V. pallidum populations.

Network analyses

Network analyses of both the IUPAC and allele data with SNaQ suggested a single hybridization event in our sampling of diploid taxa (Figure 4; Appendix S2). Analysis of the allele data in which alleles were assigned to species recover V. pallidum as a hybrid taxon with parental lineages identified as V. elliottii and the clade comprising V. boreale and V. myrtilloides (Figure 4A). Our estimates suggest a nearly equal parental contribution from these two lineages (gamma = 0.57 from V. elliottii, and gamma = 0.43 from V. boreale–V. myrtilloides). Subsequent analysis of the IUPAC data (in which sequences were assigned to samples rather than species) including eight V. pallidum individuals confirmed that the hybrid event predates the divergence of all sampled V. pallidum populations and that there was a nearly equal genomic contribution from V. elliottii (gamma = 0.56) and an ancestor of V. boreale–V. myrtilloides (gamma = 0.44; Figure 4C).

Concordance‐discordance analyses

High levels of discordance were found within the IUPAC data set. Despite high bootstrap and posterior probability values, we found relatively low gene (gCF) and site (sCF) concordance factors for the major clades recovered in concatenated and species‐tree analyses (Figure 2). Regarding the inconsistent placement of V. elliottii, 1.9% of genes (41% of sites) place it sister to V. pallidum whereas 0.6% of loci (36% of sites) support V. elliottii as sister to V. fuscatum. These results are consistent with those obtained with PhyParts (Appendix S3).

DISCUSSION

Despite the reputation of Cyanococcus as taxonomically intractable, the results of this study, in addition to recent field experience, have led us to agree with Ward (1974) that Cyanococcus “is difficult but not in any way an irresolvable tangle of intergrading populations” (p. 192). Although high levels of gene‐tree discordance and topological differences between concatenated ML and species tree methods were observed, the overall topology, monophyly of major clades corresponding to various morphospecies concepts, and placement of these clades were consistent across analyses and data sets. All analyses resolve a northern lineage of V. boreale and V. myrtilloides sister to the remaining primarily southeastern taxa. Moreover, the analyses consistently recover a close association between V. darrowii and V. tenellum and between V. fuscatum and V. caesariense. These results are consistent with an early allozyme study of diploid Cyanococcus populations based on phenetic analysis (Bruederle and Vorsa, 1994).

Observed areas of discordance are primarily from inconsistencies in the placement of V. pallidum and V. elliottii, suggesting hybridization involving these taxa. Network estimation specifically implicated V. pallidum as a hybrid taxon. Further analyses including numerous V. pallidum individuals sampled across a wide geographic range yielded results showing that the hybrid event predates the divergence of all sampled populations, suggesting that V. pallidum is a species of homoploid‐hybrid origin. Parental taxa are suggested to be V. elliottii and the lineage giving rise to V. boreale and V. myrtilloides. A recent study of expressed sequence tag‐polymerase chain reaction markers (Rowland et al., 2021) inferred V. pallidum as a close relative of V. boreale and V. myrtilloides, consistent with this supposition. Although several of our analyses inferred a sister relationship of V. pallidum with V. elliottii, none found V. pallidum to be sister to the V. boreale‐myrtilloides clade. This signal does, however, appear to be present in our data set when examining the posterior distribution of trees from a Bayesian analysis in STACEY. Vaccinium pallidum occupies a geographic range largely overlapping those of its two putative parents (which do not overlap in range), extending farther north than V. elliottii and farther south than either V. boreale or V. myrtilloides (Figure 1). Morphologically, there are not immediately clear characters consistent with the hybrid origin of V. pallidum, though this would be expected if the hybrid event was ancient and V. pallidum has had sufficient evolutionary time to accumulate morphological attributes distinct from either parent. Moreover, the lack of intermediate morphological characters does not preclude V. pallidum as a potential hybrid taxon, because hybridization is not necessarily expected to leave a consistent or predictable phenotypic signature (Anderson, 1948; Rieseberg et al., 1993).

Monophyly for all morphospecies was recovered, with two notable exceptions: V. boreale and V. fuscatum. One sample of V. boreale consistently nested within V. myrtilloides, and our V. caseariense sample nested within V. fuscatum (see also Bruederle and Vorsa, 1994). In the case of V. boreale, no evidence of gene flow was detected in our data set, although hybrids of V. boreale and V. myrtilloides have been reported (Aalders and Hall, 1962). Gene flow was detected between V. caesariense and V. fuscatum in a suboptimal SNaQ network (not shown), potentially explaining the non‐monophyly of V. fuscatum. Alternatively, the long‐standing decision to recognize V. caesariense (essentially a glabrous version of V. fuscatum occurring on the coastal plain) as an independent entity may be erroneous, and the morphological attributes (i.e., the lack of pubescence on stems and/or leaves) used to distinguish it from V. fuscatum may merely be variation within a species. Regarding the V. corymbosum “highbush” concept, this result and the apparent sister relationship of V. elliottii would appear to at least partially corroborate Vander Kloet's decision to combine these taxa into a single species. The morphologically distinct and phylogenetically cohesive V. elliottii, however, challenges this broad concept. Unfortunately, without the inclusion of polyploid taxa we cannot yet satisfactorily address this issue. Furthermore, we have sampled only two populations of V. boreale and one population of V. caesariense in this study; meaningful conclusions regarding these taxa must await further sampling and more in‐depth analyses.

Although our study of the morphological characters defining species in Cyanococcus is ongoing, our working morphospecies concepts for diploid Cyanococcus taxa appear to be largely verified with molecular data, as is our hypothesis that the true species composition of this clade likely falls somewhere between the highly divided concept of Camp (1945) and the highly combined concept of Vander Kloet (1988).

Alleles vs. IUPAC data

Recent studies have attempted to address questions as to the necessity of phasing alleles in phylogenetic reconstruction (e.g., Kamneva et al., 2017; Andermann et al., 2018; Kates et al., 2018; Tiley et al., 2021 [preprint]). We found that in the presence of hybridization, IUPAC and allele data resulted in different topologies. Analyses of IUPAC data consistently inferred a close phylogenetic association between V. pallidum and V. elliottii, often as sister lineages. Conversely, allele data inferred V. pallidum as a lone lineage, phylogenetically intermediate between its two putative parental lineages. This pattern of phylogenetic intermediacy of hybrids in relation to their parents has been previously observed across a wide range of time scales and data types, including morphological data from F1 individuals produced through controlled crosses (McDade, 1990), RADseq data from putative naturally formed F1 hybrids (Hauser et al., 2017), and target‐enrichment data from taxa involved in ancient introgression events (Crowl et al., 2020). Allele data resolved V. elliottii as sister to other “highbush” taxa (i.e., V. fuscatum and V. caesariense), consistent with our network analyses. This pattern is recovered regardless of whether alleles were assigned to individuals or species. These results suggest that phasing alleles is useful in data sets containing hybrid taxa.

On homoploid hybrids

Homoploid hybrid speciation is the process by which a new species is formed through hybridization of divergent parent lineages, but without an increase in ploidy (Grant, 1981; Rieseberg, 1997). Although several potential homoploid hybrid species are known in various plant groups—for example, Carex (Hodel et al., 2022), Senecio (James and Abbott, 2005; Brennan et al., 2012), Iris (Arnold, 1993; Taylor et al., 2013; Zalmat et al., 2021), Pinus (Wang and Szmidt, 1994), Penstemon (Wolfe et al., 1998), and Paeonia (Pan et al., 2007)—they appear to be somewhat rare in nature (but see Nieto Feliner et al., 2017). Results of the present study suggest that V. pallidum is an additional example. While hybridization is well known in Vaccinium, to our knowledge this is the first report of a naturally formed homoploid hybrid species in the group.

To further test this supposition, we additionally considered an F1 homoploid (diploid) hybrid resulting from a controlled cross between V. myrtilloides and elliottii. When included in our data set, network analyses correctly inferred the parents of this hybrid plant and an equal genomic contribution from each parent (Appendix S2). Although far from conclusive, this test case serves as a positive control of sorts and provides increased confidence that our genomic data set and analytical approach can accurately identify a homoploid hybrid taxon. We caution, however, that much work is needed to verify these findings, including further sampling of putative parental taxa, tests of reproductive isolation, investigation of niche divergence, and a detailed morphological study.

What about polyploids?

While our efforts have been focused on the diploid species of Cyanococcus, the group contains numerous polyploid lineages. Polyploids, with more than two copies of each chromosome, remain difficult to analyze in a phylogenetic context. The central challenge of analyzing sequence data from polyploids, and especially allopolyploids, lies in identifying divergent homeolog copies from parental taxa. The majority of bioinformatic tools available for processing next‐generation sequence data were developed for diploid organisms and therefore collapse variable homeolog sequences into a single consensus sequence for downstream analysis. For polyploids, this creates chimeric sequences that obscure signals of polyploidy and a polyploid mode of origin. Conversely, allelic data more accurately capture the complex genomic histories of polyploids and allow for the incorporation of divergent signals from polyploid loci into phylogenomic inference, thus distinguishing allopolyploidy from autopolyploidy and identifying parental taxa.

The diploid phylogenetic estimate presented here, in combination with recent advances in phylogenetic network analysis and a recently developed bioinformatics approach to phasing alleles for arbitrary ploidy from target enrichment data (Tiley et al., 2021 [preprint]), provides an exciting opportunity to investigate polyploid Cyanococcus taxa and infer parentage and mode of polyploidization in this challenging group.

AUTHOR CONTRIBUTIONS

A.A.C., P.W.F., H.A., and P.S.M. designed the study. A.A.C., P.W.F., and P.S.M. carried out fieldwork. N.P.L. conducted flow cytometry analyses. A.A.C. ran phylogenomic analyses. All authors contributed to the intellectual content and writing of the manuscript.

Supporting information

Appendix S1. Voucher table.

Click here for additional data file. (53.5KB, xlsx)

Appendix S2. Comparison of network analyses with different data sets.

Click here for additional data file. (637.2KB, pdf)

Appendix S3. Results from concordance/discordance analyses.

Click here for additional data file. (279.6KB, pdf)

 

Click here for additional data file. (12.7KB, docx)

ACKNOWLEDGMENTS

The authors thank A. Liston for many helpful comments that improved the manuscript. Funding for this research was provided by the Trinity College of Arts and Sciences at Duke University and the National Science Foundation (DEB‐2038213 to Duke and North Carolina State University; DEB‐2038217 to the Botanical Research Institute of Texas).

Crowl, A. A. , Fritsch P. W., Tiley G. P., Lynch N. P., Ranney T. G., Ashrafi H., and Manos P. S.. 2022. A first complete phylogenomic hypothesis for diploid blueberries (Vaccinium section Cyanococcus). American Journal of Botany 109(10): 1596–1606. 10.1002/ajb2.16065

DATA AVAILABILITY STATEMENT

Raw reads are deposited in the NCBI Sequence Reads Archive (BioProject: PRJNA854616). Final DNA alignment and gene‐tree files are available from the Dryad Digital Repository: doi:10.5061/dryad.cc2fqz68x (Consuegra et al., 2020).

REFERENCES

  1. Aalders, L. E. , and Hall I. V.. 1962. New evidence on the cytotaxonomy of Vaccinium species as revealed by stomatal measurements from herbarium specimens. Nature 196: 694.13972774 [Google Scholar]
  2. Andermann, T. , Fernandes A. M., Olsson U., Töpel M., Pfeil B., Oxelman B., Aleixo A., et al. 2018. Allele phasing greatly improves the phylogenetic utility of ultraconserved elements. Systematic Biology 68: 32–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Anderson, E. 1948. Hybridization of the habitat. Evolution 2: 1–9. [Google Scholar]
  4. Andrews, S. 2010. FastQC ‐ A quality control tool for high throughput sequence data. Website: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/
  5. Arnold, M. L. 1993. Iris nelsonii (Iridaceae): Origin and genetic composition of a homoploid hybrid species. American Journal of Botany 80: 577–583. [DOI] [PubMed] [Google Scholar]
  6. Bouckaert, R. , Heled J., Kühnert D., Vaughan T., Wu C.‐H., Xie D., Suchard M. A., et al. 2014. BEAST 2: a software platform for Bayesian evolutionary analysis. PLoS Computational Biology 10: e1003537. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Bradley, R. K. , Roberts A., Smoot M., Juvekar S., Do J., Dewey C., Holmes I., and Pachter L.. 2009. Fast Statistical Alignment. PLoS Computational Biology 5: e1000392. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Brennan, A. C. , Barker D., Hiscock S. J., and Abbott R. J.. 2012. Molecular genetic and quantitative trait divergence associated with recent homoploid hybrid speciation: a study of Senecio squalidus (Asteraceae). Heredity 108: 87–95. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Brown, J. W. , Walker J. F., and Smith S. A.. 2017. Phyx: phylogenetic tools for unix. Bioinformatics 33: 1886–1888. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Bruederle, L. P. , and Vorsa N.. 1994. Genetic differentiation of diploid blueberry, Vaccinium sect. Cyanococcus (Ericaceae). Systematic Botany 19: 337–349. [Google Scholar]
  11. Camp, W. H. 1942. On the Structure of populations in the genus Vaccinium . Brittonia 4: 189. [Google Scholar]
  12. Camp, W. H. 1945. The North American blueberries with notes on other groups of Vacciniaceae. Brittonia 5: 203–275. [Google Scholar]
  13. Camp, W. H. , and Gilly C. L.. 1943. The structure and origin of species. Brittonia 4: 323–385. [Google Scholar]
  14. Chifman, J. , and Kubatko L.. 2014. Quartet inference from SNP data under the coalescent model. Bioinformatics 30: 3317–3324. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Consuegra, J. , Gaffé J., Lenski R. E., Hindre T., Barrick J. E. Tenaillon O., andSchneider D. 2020. IS‐mediated mutations both promote and constrain evolvability during a long‐term experiment with bacteria Dryad, Dataset. 10.5061/dryad.m3pvmd0v [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Costich, D. E. , Ortiz R., Meagher T. R., Bruederle L. P., and Vorsa N.. 1993. Determination of ploidy level and nuclear DNA content in blueberry by flow cytometry. Theoretical and Applied Genetics 86: 1001–1006. [DOI] [PubMed] [Google Scholar]
  17. Crowl, A. A. , Manos P. S., McVay J. D., Lemmon A. R., Lemmon E. M., and Hipp A. L.. 2020. Uncovering the genomic signature of ancient introgression between white oak lineages (Quercus). New Phytologist 226: 1158–1170. [DOI] [PubMed] [Google Scholar]
  18. Darrow, G. M. , and Camp W. H.. 1945. Vaccinium hybrids and the development of new horticultural material. Bulletin of the Torrey Botanical Club 72: 1. [Google Scholar]
  19. DePristo, M. A. , Banks E., Poplin R., Garimella K. V., Maguire J. R., Hartl C., Philippakis A. A., et al. 2011. A framework for variation discovery and genotyping using next‐generation DNA sequencing data. Nature Genetics 43: 491–498. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Doležel, J. , Greilhuber J., and Suda J.. 2007. Estimation of nuclear DNA content in plants using flow cytometry. Nature Protocols 2: 2233–2244. [DOI] [PubMed] [Google Scholar]
  21. Doyle, J. J. , and Doyle J. L.. 1987. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochemical Bulletin 19: 11–15. [Google Scholar]
  22. Fritsch, P. W. , Crowl A. A., Ashrafi H., and Manos P. S.. In press. Understanding the systematics and evolution of Vaccinium sect. Cyanococcus (Ericaceae): progress and prospects. Rhodora .
  23. Grant, V. 1981. Plant Speciation. Columbia University Press. [Google Scholar]
  24. Harlan, J. R. , and de Wet J. M. J.. 1963. The compilospecies concept. Evolution 17: 497. [Google Scholar]
  25. Hauser, D. A. , Keuter A., McVay J. D., Hipp A. L., and Manos P. S.. 2017. The evolution and diversification of the red oaks of the California Floristic Province (Quercus section Lobatae, series Agrifoliae). American Journal of Botany 104: 1581–1595. [DOI] [PubMed] [Google Scholar]
  26. Hoang, D. T. , Chernomor O., von Haeseler A., Minh B. Q., and Vinh L. S.. 2018. UFBoot2: Improving the ultrafast bootstrap approximation. Molecular Biology and Evolution 35: 518–522. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Hodel, R. G. J. , Massatti R., and Knowles L. L.. 2022. Hybrid enrichment of adaptive variation revealed by genotype–environment associations in montane sedges. Molecular Ecology 31: 3722–3737. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Hummer, K. E. , Bassil N. V., Rodríquez Armenta H. P., and Olmstead J. W.. 2015. Vaccinium species ploidy assessment. Acta Horticulturae 1101: 199–204. [Google Scholar]
  29. Huxley, J. 1942. Evolution. The Modern Synthesis. London: George Alien & Unwin Ltd. [Google Scholar]
  30. James, J. K. , and Abbott R. J.. 2005. Recent, allopatric, homoploid hybrid speciation: The origin of Senecio squalidus (Asteraceae) in the British Isles from a hybrid zone on Mount Etna, Sicily. Evolution 59: 2533–2547. [PubMed] [Google Scholar]
  31. Johnson, M. G. , Gardner E. M., Liu Y., Medina R., Goffinet B., Shaw A. J., Zerega N. J. C., and Wickett N. J.. 2016. HybPiper: Extracting coding sequence and introns for phylogenetics from high‐throughput sequencing reads using target enrichment. Applications in Plant Sciences 4: 1600016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Johnson, M. G. , Pokorny L., Dodsworth S., Botigué L. R., Cowan R. S., Devault A., Eiserhardt W. L., et al. 2019. A universal probe set for targeted sequencing of 353 nuclear genes from any flowering plant designed using k‐medoids clustering. Systematic Biology 68: 594–606. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Jones, G. 2017. Algorithmic improvements to species delimitation and phylogeny estimation under the multispecies coalescent. Journal of Mathematical Biology 74: 447–467. [DOI] [PubMed] [Google Scholar]
  34. Kamneva, O. K. , Syring J., Liston A., and Rosenberg N. A.. 2017. Evaluating allopolyploid origins in strawberries (Fragaria) using haplotypes generated from target capture sequencing. BMC Evolutionary Biology. 17: 180. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Kates, H. R. , Johnson M. G., Gardner E. M., Zerega N. J. C., and Wickett N. J.. 2018. Allele phasing has minimal impact on phylogenetic reconstruction from targeted nuclear gene sequences in a case study of Artocarpus . American Journal of Botany 105: 404–416. [DOI] [PubMed] [Google Scholar]
  36. Kron, K. A. , Powell E. A., and Luteyn J. L.. 2002. Phylogenetic relationships within the blueberry tribe (Vaccinieae, Ericaceae) based on sequence data from matK and nuclear ribosomal ITS regions, with comments on the placement of Satyria . American Journal of Botany 89: 327–336. [DOI] [PubMed] [Google Scholar]
  37. Lanfear, R. , Calcott B., Ho S. Y. W., and Guindon S.. 2012. PartitionFinder: Combined selection of partitioning schemes and substitution models for phylogenetic analyses. Molecular Biology and Evolution 29: 1695–1701. [DOI] [PubMed] [Google Scholar]
  38. Lanfear, R. , Calcott B., Kainer D., Mayer C., and Stamatakis A.. 2014. Selecting optimal partitioning schemes for phylogenomic datasets. BMC Evolutionary Biology 14: 82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Li, H. , and Durbin R.. 2009. Fast and accurate short read alignment with Burrows‐Wheeler transform. Bioinformatics 25: 1754–1760. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Lyrene, P. M. , Vorsa N., and Ballington J. R.. 2003. Polyploidy and sexual polyploidization in the genus Vaccinium . Euphytica 133: 27–36. [Google Scholar]
  41. Martin, M. 2011. Cutadapt removes adapter sequences from high‐throughput sequencing reads. EMBnet.journal 17: 10. [Google Scholar]
  42. McDade, L. 1990. Hybrids and phylogenetic systematics I. Patterns of character expression in hybrids and their implications for cladistic analysis. Evolution 44: 1685–1700. [DOI] [PubMed] [Google Scholar]
  43. McKenna, A. , Hanna M., Banks E., Sivachenko A., Cibulskis K., Kernytsky A., Garimella K., et al. 2010. The Genome Analysis Toolkit: A MapReduce framework for analyzing next‐generation DNA sequencing data. Genome Research 20: 1297–1303. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. McLay, T. G. B. , Birch J. L., Gunn B. F., Ning W., Tate J. A., Nauheimer L., Joyce E. M., et al. 2021. New targets acquired: Improving locus recovery from the Angiosperms353 probe set. Applications in Plant Sciences 9: aps3.11420. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Minh, B. Q. , Hahn M. W., and Lanfear R.. 2020. New methods to calculate concordance factors for phylogenomic datasets. Molecular Biology and Evolution 37: 2727–2733. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Nguyen, L.‐T. , Schmidt H. A., von Haeseler A., and Minh B. Q.. 2015. IQ‐TREE: A fast and effective stochastic algorithm for estimating maximum‐likelihood phylogenies. Molecular Biology and Evolution 32: 268–274. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Nieto Feliner, G. , Álvarez I., Fuertes‐Aguilar J., Heuertz M., Marques I., Moharrek F., Piñeiro R., et al. 2017. Is homoploid hybrid speciation that rare? An empiricist's view. Heredity 118: 513–516. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Pan, J. , Zhang D., and Sang T.. 2007. Molecular phylogenetic evidence for the origin of a diploid hybrid of Paeonia (Paeoniaceae). American Journal of Botany 94: 400–408. [DOI] [PubMed] [Google Scholar]
  49. Poster, L. S. , Handel S. N., and Smouse P. E.. 2017. Corolla size and temporal displacement of flowering times among sympatric diploid and tetraploid highbush blueberry (Vaccinium corymbosum). Botany 95: 395–404. [Google Scholar]
  50. Rambaut, A. , Drummond A. J., Xie D., Baele G., and Suchard M. A.. 2018. Posterior summarization in Bayesian phylogenetics using Tracer 1.7. Systematic Biology 67: 901–904. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Redpath, L. E. , Aryal R., Lynch N., Spencer J. A., Hulse‐Kemp A. M., Ballington J. R., Green J., et al. 2022. Nuclear DNA contents and ploidy levels of North American Vaccinium species and interspecific hybrids. Scientia Horticulturae 297: 110955. [Google Scholar]
  52. Rieseberg, L. H. , Ellstrand N. C., and Arnold M.. 1993. What can molecular and morphological markers tell us about plant hybridization? Critical Reviews in Plant Sciences 12: 213–241. [Google Scholar]
  53. Rieseberg, L. H. 1997. Hybrid origins of plant species. Annual Review of Ecology and Systematics 28: 359–389. [Google Scholar]
  54. Rowland, L. J. , Ogden E. L., and Ballington J. R. 2021. Relationships among blueberry species within the section Cyanococcus of the Vaccinium genus based on EST‐PCR markers. Canadian Journal of Plant Science 102: 744–748. [Google Scholar]
  55. Smith, S. A. , Moore M. J., Brown J. W., and Yang Y.. 2015. Analysis of phylogenomic datasets reveals conflict, concordance, and gene duplications with examples from animals and plants. BMC Evolutionary Biology 15: 150. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Solís‐Lemus, C. , and Ané C.. 2016. Inferring phylogenetic networks with maximum pseudolikelihood under incomplete lineage sorting. PLoS Genetics 12: e1005896. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Swofford, D. L. 2002. PAUP*. Phylogenetic analysis using parsimony (*and other methods). Version 4. Sinauer Associates, Sunderland, Massachusetts. [Google Scholar]
  58. Taylor, S. J. , Rojas L. D., Ho S. W., and Martin N. H.. 2013. Genomic collinearity and the genetic architecture of floral differences between the homoploid hybrid species Iris nelsonii and one of its progenitors, Iris hexagona . Heredity 110: 63–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Tiley, G. P. , Crowl A. A., Manos P. S., Sessa E. B., Solís‐Lemus C., Yoder A. D., and Burleigh J. G.. 2021. Phasing alleles improves network inference with allopolyploids. bioRxiv 10.1101/2021.05.04.442457 [preprint]. [DOI] [PubMed] [Google Scholar]
  60. Uttal, L. J. 1987. The Genus Vaccinium L. (Ericaceae) in Virginia.Castanea 52: 231–255.   [Google Scholar]
  61. Vander Kloet, S. P. 1980. The taxonomy of the highbush blueberry, Vaccinium corymbosum . Canadian Journal of Botany 58: 1187–1201. [Google Scholar]
  62. Vander Kloet, S. P. 1983. The taxonomy of Vaccinium § Cyanococcus: a summation. Canadian Journal of Botany 61: 256–266. [Google Scholar]
  63. Vander Kloet, S. P. 1988. The genus Vaccinium in North America. Research Branch, Agriculture Canada, Ottawa, Canada. [Google Scholar]
  64. Vander Kloet, S. P. 2009. Vaccinium. In Flora of North America Editorial Committee [ed.], Flora of North America North of Mexico, vol. 8. Magnoliophyta: Paeoniaceae to Ericaceae, 515–530. Oxford University Press, New York, NY. [Google Scholar]
  65. Wang, X.‐R. , and Szmidt A. E.. 1994. Hybridization and chloroplast DNA variation in a Pinus species complex from Asia. Evolution 48: 1020–1031. [DOI] [PubMed] [Google Scholar]
  66. Ward, D. B. 1974. Contributions to the Flora of Florida: 6, Vaccinium (Ericaceae). Castanea 39: 191–205. [Google Scholar]
  67. Weakley, A. 2020. Flora of the Southern and Mid–Atlantic States. University of North Carolina Herbarium, North Carolina Botanical Garden, Chapel Hill, NC. [Google Scholar]
  68. Wolfe, A. D. , Xiang Q.‐Y., and Kephart S. R.. 1998. Diploid hybrid speciation in Penstemon (Scrophulariaceae). Proceedings of the National Academy of Sciences 95: 5112–5115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Xie, M. , Wu Q., Wang J., and Jiang T.. 2016. H‐PoP and H‐PoPG: heuristic partitioning algorithms for single individual haplotyping of polyploids. Bioinformatics 32: 3735–3744. [DOI] [PubMed] [Google Scholar]
  70. Zalmat, A. S. , Sotola V. A., Nice C. C., and Martin N. H.. 2021. Genetic structure in Louisiana Iris species reveals patterns of recent and historical admixture. American Journal of Botany 108: 2257–2268. [DOI] [PubMed] [Google Scholar]
  71. Zhang, C. , Rabiee M., Sayyari E., and Mirarab S.. 2018. ASTRAL‐III: polynomial time species tree reconstruction from partially resolved gene trees. BMC Bioinformatics 19: 153. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

Appendix S1. Voucher table.

Click here for additional data file. (53.5KB, xlsx)

Appendix S2. Comparison of network analyses with different data sets.

Click here for additional data file. (637.2KB, pdf)

Appendix S3. Results from concordance/discordance analyses.

Click here for additional data file. (279.6KB, pdf)

 

Click here for additional data file. (12.7KB, docx)

Data Availability Statement

Raw reads are deposited in the NCBI Sequence Reads Archive (BioProject: PRJNA854616). Final DNA alignment and gene‐tree files are available from the Dryad Digital Repository: doi:10.5061/dryad.cc2fqz68x (Consuegra et al., 2020).

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