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Accurately reconstructing the reticulate histories of polyploids remains a central challenge for understanding plant evolution. Although phylogenetic networks can provide insights into relationships among polyploid lineages, inferring networks may be hindered by the complexities of homology determination in polyploid taxa. We use simulations to show that phasing alleles from allopolyploid individuals can improve phylogenetic network inference under the multispecies coalescent by obtaining the true network with fewer loci compared with haplotype consensus sequences or sequences with heterozygous bases represented as ambiguity codes. Phased allelic data can also improve divergence time estimates for networks, which is helpful for evaluating allopolyploid speciation hypotheses and proposing mechanisms of speciation. To achieve these outcomes in empirical data, we present a novel pipeline that leverages a recently developed phasing algorithm to reliably phase alleles from polyploids. This pipeline is especially appropriate for target enrichment data, where the depth of coverage is typically high enough to phase entire loci. We provide an empirical example in the North American Dryopteris fern complex that demonstrates insights from phased data as well as the challenges of network inference. We establish that our pipeline (PATÉ: Phased Alleles from Target Enrichment data) is capable of recovering a high proportion of phased loci from both diploids and polyploids. These data may improve network estimates compared with using haplotype consensus assemblies by accurately inferring the direction of gene flow, but statistical nonidentifiability of phylogenetic networks poses a barrier to inferring the evolutionary history of reticulate complexes., (© The Author(s) 2024. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Premise: Reticulate evolution, often accompanied by polyploidy, is prevalent in plants, and particularly in the ferns. Resolving the resulting non-bifurcating histories remains a major challenge for plant phylogenetics. Here, we present a phylogenomic investigation into the complex evolutionary history of the vining ferns, Lygodium (Lygodiaceae, Schizaeales)., Methods: Using a targeted enrichment approach with the GoFlag 408 flagellate land plant probe set, we generated large nuclear and plastid sequence datasets for nearly all taxa in the genus and constructed the most comprehensive phylogeny of the family to date using concatenated maximum likelihood and coalescence approaches. We integrated this phylogeny with cytological and spore data to explore karyotype evolution and generate hypotheses about the origins of putative polyploids and hybrids., Results: Our data and analyses support the origins of several putative allopolyploids (e.g., L. cubense, L. heterodoxum) and hybrids (e.g., L. ×fayae) and also highlight the potential prevalence of autopolyploidy in this clade (e.g., L. articulatum, L. flexuosum, and L. longifolium)., Conclusions: Our robust phylogenetic framework provides valuable insights into dynamic reticulate evolution in this clade and demonstrates the utility of target-capture data for resolving these complex relationships., (© 2024 The Author(s). American Journal of Botany published by Wiley Periodicals LLC on behalf of Botanical Society of America.)

Genomic data have provided evidence of previously unknown ancient whole genome duplications (WGDs) and highlighted the role of WGDs in the evolution of many eukaryotic lineages. Ancient WGDs often are detected by examining distributions of synonymous substitutions per site (Ks) within a genome, or "Ks plots." For example, WGDs can be detected from Ks plots by using univariate mixture models to identify peaks in Ks distributions. We performed gene family simulation experiments to evaluate the effects of different Ks estimation methods and mixture models on our ability to detect ancient WGDs from Ks plots. The simulation experiments, which accounted for variation in substitution rates and gene duplication and loss rates across gene families, tested the effects of WGD age and gene retention rates following WGD on inferring WGDs from Ks plots. Our simulations reveal limitations of Ks plot analyses. Strict interpretations of mixture model analyses often overestimate the number of WGD events, and Ks plot analyses typically fail to detect WGDs when ≤10% of the duplicated genes are retained following the WGD. However, WGDs can accurately be characterized over an intermediate range of Ks. The simulation results are supported by empirical analyses of transcriptomic data, which also suggest that biases in gene retention likely affect our ability to detect ancient WGDs. Although our results indicate mixture model results should be interpreted with great caution, using node-averaged Ks estimates and applying more appropriate mixture models can improve the accuracy of detecting WGDs.

Although numerous studies have surveyed the frequency with which different plant characters are associated with polyploidy, few statistical tools are available to identify the factors that potentially facilitate polyploidy. We describe a new probabilistic model, BiChroM, designed to associate the frequency of polyploidy and chromosomal change with a binary phenotypic character in a phylogeny. BiChroM provides a robust statistical framework for testing differences in rates of polyploidy associated with phenotypic characters along a phylogeny while simultaneously allowing for evolutionary transitions between character states. We used BiChroM to test whether polyploidy is more frequent in woody or herbaceous plants, based on tree with 4711 eudicot species. Although polyploidy occurs in woody species, rates of chromosome doubling were over six times higher in herbaceous species. Rates of single chromosome increases or decreases were also far higher in herbaceous than woody species. Simulation experiments indicate that BiChroM performs well with little to no bias and relatively little variance at a wide range of tree depths when trees have at least 500 taxa. Thus, BiChroM provides a first step toward a rigorous statistical framework for assessing the traits that facilitate polyploidy., (© 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.)

Like many fern lineages comprising reticulate species complexes, Polypodium s.s. (Polypodiacaeae) has a history shaped by rapid diversification, hybridization, and polyploidy that poses substantial challenges for phylogenetic inference with plastid and single-locus nuclear markers. Using target capture probes for 408 nuclear loci developed by the GoFlag project and a custom bioinformatic pipeline, SORTER, we constructed multi-locus nuclear datasets for diploid temperate and Mesoamerican species of Polypodium and five allotetraploid species belonging to the well-studied Polypodium vulgare complex. SORTER employs a clustering approach to separate putatively paralogous copies of targeted loci into orthologous matrices and haplotype phasing to infer allopolyploid haplotypes across loci, resulting in datasets amenable to both concatenated maximum likelihood and multi-species coalescent phylogenetic analyses. By comparing phylogenies derived from maximum likelihood and multi-species coalescent analyses of unphased and phased datasets, as well as evaluating discordance among gene trees and species trees, we recover support for incomplete lineage sorting within Polypodium s.s., novel relationships among diploid taxa of the Polypodium vulgare complex and its Mesoamerican sister clade, and the placement of several Polypodium species within other genera. Additionally, we were able to infer well-supported phylogenies that identified the hypothesized progenitors of the allotetraploid species, indicating that SORTER is an effective and accurate tool for reconstructing homeolog haplotypes of allopolyploids in fern taxa and other non-model organisms from target capture data. [ABSTRACT FROM AUTHOR]

Summary: If particular traits consistently affect rates of speciation and extinction, broad macroevolutionary patterns can be interpreted as consequences of selection at high levels of the biological hierarchy. Identifying traits associated with diversification rates is difficult because of the wide variety of characters under consideration and the statistical challenges of testing for associations from comparative phylogenetic data. Ploidy (diploid vs polyploid states) and breeding system (self‐incompatible vs self‐compatible states) are both thought to be drivers of differential diversification in angiosperms.We fit 29 diversification models to extensive trait and phylogenetic data in Solanaceae and investigate how speciation and extinction rate differences are associated with ploidy, breeding system, and the interaction between these traits.We show that diversification patterns in Solanaceae are better explained by breeding system and an additional unobserved factor, rather than by ploidy. We also find that the most common evolutionary pathway to polyploidy in Solanaceae occurs via direct breakdown of self‐incompatibility by whole genome duplication, rather than indirectly via breakdown followed by polyploidization.Comparing multiple stochastic diversification models that include complex trait interactions alongside hidden states enhances our understanding of the macroevolutionary patterns in plant phylogenies. [ABSTRACT FROM AUTHOR]

Premise of the Study: Polyploidy has profound evolutionary consequences for land plants. Despite the availability of large phylogenetic and chromosomal data sets, estimating the rates of polyploidy and chromosomal evolution across the tree of life remains a challenging, computationally complex problem. We introduce the R package chromploid, which allows scientists to perform inference of chromosomal evolution rates across large phylogenetic trees. Methods and Results: chromploid is an open‐source package in the R environment that calculates the likelihood function of models of chromosome evolution. Models of discrete character evolution can be customized using chromploid. We demonstrate the performance of the BiChroM model, testing for associations between rates of chromosome doubling (as a proxy for polyploidy) and a binary phenotypic character, within chromploid using simulations and empirical data from Solanum. In simulations, estimated chromosome‐doubling rates were unbiased and the variance decreased with larger trees, but distinguishing small differences in rates of chromosome doubling, even from large data sets, remains challenging. In the Solanum data set, a custom model of chromosome number evolution demonstrated higher rates of chromosome doubling in herbaceous species compared to woody. Conclusions: chromploid enables researchers to perform robust likelihood‐based inferences using complex models of chromosome number evolution across large phylogenies. [ABSTRACT FROM AUTHOR]

PREMISE OF THE STUDY: Whole-genome duplications (WGDs) can rapidly increase genome size in angiosperms. Yet their mean genome size is not correlated with ploidy. We compared three hypotheses to explain the constancy of genome size means across ploidies. The genome downsizing hypothesis suggests that genome size will decrease by a given percentage after a WGD. The genome size threshold hypothesis assumes that taxa with large genomes or large monoploid numbers will fail to undergo or survive WGDs. Finally, the genome downsizing and threshold hypothesis suggests that both genome downsizing and thresholds affect the relationship between genome size means and ploidy. METHODS: We performed nonparametric bootstrap simulations to compare observed angiosperm genome size means among species or genera against simulated genome sizes under the three different hypotheses. We evaluated the hypotheses using a decision theory approach and estimated the expected percentage of genome downsizing. KEY RESULTS:The threshold hypothesis improves the approximations between mean genome size and simulated genome size. At the species level, the genome downsizing with thresholds hypothesis best explains the genome size means with a 15% genome downsizing percentage. In the genus level simulations, the monoploid number threshold hypothesis best explains the data. CONCLUSIONS: Thresholds of genome size and monoploid number added to genome downsizing at species level simulations explain the observed means of angiosperm genome sizes, and monoploid number is important for determining the genome size mean at the genus level. [ABSTRACT FROM AUTHOR]