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Changes in chromosome numbers, including polyploidy and dysploidy events, play a key role in eukaryote evolution as they could expediate reproductive isolation and have the potential to foster phenotypic diversification. Deciphering the pattern of chromosome-number change within a phylogeny currently relies on probabilistic evolutionary models. All currently available models assume time homogeneity, such that the transition rates are identical throughout the phylogeny. Here, we develop heterogeneous models of chromosome-number evolution that allow multiple transition regimes to operate in distinct parts of the phylogeny. The partition of the phylogeny to distinct transition regimes may be specified by the researcher or, alternatively, identified using a sequential testing approach. Once the number and locations of shifts in the transition pattern are determined, a second search phase identifies regimes with similar transition dynamics, which could indicate on convergent evolution. Using simulations, we study the performance of the developed model to detect shifts in patterns of chromosome-number evolution and demonstrate its applicability by analyzing the evolution of chromosome numbers within the Cyperaceae plant family. The developed model extends the capabilities of probabilistic models of chromosome-number evolution and should be particularly helpful for the analyses of large phylogenies that include multiple distinct subclades., (© 2023 The Authors. New Phytologist © 2023 New Phytologist Foundation.)

The ChromEvol software was the first to implement a likelihood-based approach, using probabilistic models that depict the pattern of chromosome number change along a specified phylogeny. The initial models have been completed and expanded during the last years. New parameters that model polyploid chromosome evolution have been implemented in ChromEvol v.2. In recent years, new and more complex models have been developed. The BiChrom model is able to implement two distinct chromosome models for the two possible trait states of a binary character of interest. ChromoSSE jointly implements chromosome evolution, speciation, and extinction. In the near future, we will be able to study chromosome evolution with increasingly complex models., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Polyploidy, the genome wide duplication of chromosome number, is a key feature in eukaryote evolution. Polyploidy exists in diverse groups including animals, fungi, and invertebrates but is especially prevalent in plants with most, if not all, plant species having descended from a polyploidization event. Polyploids often differ markedly from their diploid progenitors in morphological, physiological, and life history characteristics as well as rates of adaptation. The altered characteristics displayed by polyploids may contribute to their success in novel ecological habitats. Clearly, a better understanding of the processes underlying changes in the number of chromosomes within genomes is a key goal in our understanding of speciation and adaptation for a wide range of families and genera. Despite the fundamental role of chromosome number change in eukaryotic evolution, probabilistic models describing the evolution of chromosome number along a phylogeny have not yet been formulated. We present a series of likelihood models, each representing a different hypothesis regarding the evolution of chromosome number along a given phylogeny. These models allow us to reconstruct ancestral chromosome numbers and to estimate the expected number of polyploidization events and single chromosome changes (dysploidy) that occurred along a phylogeny. We test, using simulations, the accuracy of this approach and its dependence on the number of taxa and tree length. We then demonstrate the application of the method for the study of chromosome number evolution in 4 plant genera: Aristolochia, Carex, Passiflora, and Helianthus. Considering the depth of the available cytological and phylogenetic data, formal models of chromosome number evolution are expected to advance significantly our understanding of the importance of polyploidy and dysploidy across different taxonomic groups.

See also the Commentary on this article by Spoelhof et al., 240: 909–911. [ABSTRACT FROM AUTHOR]

Summary: Chromosome number is a central feature of eukaryote genomes. Deciphering patterns of chromosome‐number change along a phylogeny is central to the inference of whole genome duplications and ancestral chromosome numbers. ChromEvol is a probabilistic inference tool that allows the evaluation of several models of chromosome‐number evolution and their fit to the data. However, fitting a model does not necessarily mean that the model describes the empirical data adequately. This vulnerability may lead to incorrect conclusions when model assumptions are not met by real data.Here, we present a model adequacy test for likelihood models of chromosome‐number evolution. The procedure allows us to determine whether the model can generate data with similar characteristics as those found in the observed ones.We demonstrate that using inadequate models can lead to inflated errors in several inference tasks. Applying the developed method to 200 angiosperm genera, we find that in many of these, the best‐fitting model provides poor fit to the data. The inadequacy rate increases in large clades or in those in which hybridizations are present.The developed model adequacy test can help researchers to identify phylogenies whose underlying evolutionary patterns deviate substantially from current modelling assumptions and should guide future methods development. [ABSTRACT FROM AUTHOR]

Chromosome numbers have been widely used to describe the most fundamental genomic attribute of an organism or a lineage. Although providing strong phylogenetic signal, chromosome numbers vary remarkably among eukaryotes at all levels of taxonomic resolution. Changes in chromosome numbers regularly serve as indication of major genomic events, most notably polyploidy and dysploidy. Here, we review recent advancements in our ability to make inferences regarding historical events that led to alterations in the number of chromosomes of a lineage. We first describe the mechanistic processes underlying changes in chromosome numbers, focusing on structural chromosomal rearrangements. Then, we focus on experimental procedures, encompassing comparative cytogenomics and genomics approaches, and on computational methodologies that are based on explicit models of chromosome-number evolution. Together, these tools offer valuable predictions regarding historical events that have changed chromosome numbers and genome structures, as well as their phylogenetic and temporal placements. [ABSTRACT FROM AUTHOR]

Summary Changes in chromosome numbers are a prominent driver of plant evolution, impacting ecological diversification, stress tolerance, and phenotypes. ChromEvol is a widely used software tool for deciphering patterns of chromosome‐number change along a phylogeny of interest. It evaluates the fit of alternative models to the data, estimates transition rates of different types of events, and infers the expected number of events along each branch of the phylogeny. We introduce ChromEvol v.3, featuring multiple novel methodological advancements that capture variation in the transition rates along a phylogeny. This version better allows researchers to identify how dysploidy and polyploidy rates change based on the number of chromosomes in the genome, with respect to a discrete trait, or at certain subclades of the phylogeny. We demonstrate the applicability of the new models on the Solanaceae phylogeny. Our analyses identify four chromosome‐number transition regimes that characterize distinct Solanaceae clades and demonstrate an association between self‐compatibility and altered dynamics of chromosome‐number evolution. ChromEvol v.3, available at https://github.com/anatshafir1/chromevol, offers researchers a more flexible, comprehensive, and accurate tool to investigate the evolution of chromosome numbers and the various processes affecting it. [ABSTRACT FROM AUTHOR]