The resurgence of influenza A/H3N2 virus in Australia after the relaxation of COVID-19 restrictions during the 2022 season.

This study retrospectively analyzed the genetic characteristics of influenza A H3N2 (A/H3N2) viruses circulating in New South Wales (NSW), the Australian state with the highest number of influenza cases in 2022, and explored the phylodynamics of A/H3N2 transmission within Australia during this period. Sequencing was performed on 217 archived specimens, and A/H3N2 evolution and spread within Australia were analyzed using phylogenetic and phylodynamic methods. Hemagglutinin genes of all analyzed NSW viruses belonged to subclade 3C.2a1b.2a.2 and clustered together with the 2022 vaccine strain. Complete genome analysis of NSW viruses revealed highly frequent interclade reassortments between subclades 3C.2a1b.2a.2 and 3C.2a1b.1a. The estimated earliest introduction time of the dominant subgroup 3C.2a1b.2a.2a.1 in Australia was February 22, 2022 (95% highest posterior density: December 19, 2021-March 13, 2022), following the easing of Australian travel restrictions, suggesting a possible international source. Phylogeographic analysis revealed that Victoria drove the transmission of A/H3N2 viruses across the country during this season, while NSW did not have a dominant role in viral dissemination to other regions. This study highlights the importance of continuous surveillance and genomic characterization of influenza viruses in the postpandemic era, which can inform public health decision-making and enable early detection of novel strains with pandemic potential.

The ClaDS rate-heterogeneous birth-death prior for full phylogenetic inference in BEAST2.

Bayesian phylogenetic inference requires a tree prior, which models the underlying diversification process that gives rise to the phylogeny. Existing birth-death diversification models include a wide range of features, for instance, lineage-specific variations in speciation and extinction (SSE) rates. While across-lineage variation in SSE rates is widespread in empirical datasets, few heterogeneous rate models have been implemented as tree priors for Bayesian phylogenetic inference. As a consequence, rate heterogeneity is typically ignored when reconstructing phylogenies, and rate heterogeneity is usually investigated on fixed trees. In this paper, we present a new BEAST2 package implementing the cladogenetic diversification rate shift (ClaDS) model as a tree prior. ClaDS is a birth-death diversification model designed to capture small progressive variations in birth and death rates along a phylogeny. Unlike previous implementations of ClaDS, which were designed to be used with fixed, user-chosen phylogenies, our package is implemented in the BEAST2 framework and thus allows full phylogenetic inference, where the phylogeny and model parameters are co-estimated from a molecular alignment. Our package provides all necessary components of the inference, including a new tree object and operators to propose moves to the Monte-Carlo Markov chain. It also includes a graphical interface through BEAUti. We validate our implementation of the package by comparing the produced distributions to simulated data and show an empirical example of the full inference, using a dataset of cetaceans.

Genomics evolution of Jingmen viruses associated with ticks and vertebrates.

Jingmen virus (JMV) associated with ticks and vertebrates have been found to be related to human disease. We obtained the genome of a Jingmen tick virus (JMTV) strain from Rhipicephalus microplus in Guizhou province and compared the genomes of seven JMV species associated with ticks and vertebrates to understand the evolutionary relationships. The topology of the phylogenetic tree of segment 1 and segment 3 is similar, and segment 2 and segment 4 formed two different topologies, with the main differences being between Alongshan virus (ALSV), Takachi virus, Yanggou tick virus and Pteropus lylei jingmen virus (PLJV), and the possibility of genetic reassortment among these viruses. Moreover, we detected recombination within JMTV and between PLJV and ALSV. The genetic reassortment and recombination that occurs during cross-species transmission of these JMV associated with ticks and vertebrates not only complicates their evolutionary relationships, but also raises the risk of these viruses to humans.

Structure, Evolution, and Mitochondrial Genome Analysis of Mussel Species (Bivalvia, Mytilidae).

Based on the nucleotide sequences of the mitochondrial genome (mitogenome) of specimens taken from two mussel species (Arcuatula senhousia and Mytilus coruscus), an investigation was performed by means of the complex approaches of the genomics, molecular phylogenetics, and evolutionary genetics. The mitogenome structure of studied mussels, like in many other invertebrates, appears to be much more variable than in vertebrates and includes changing gene order, duplications, and deletions, which were most frequent for tRNA genes; the mussel species' mitogenomes also have variable sizes. The results demonstrate some of the very important properties of protein polypeptides, such as hydrophobicity and its determination by the purine and pyrimidine nucleotide ratio. This fact might indirectly indicate the necessity of purifying natural selection for the support of polypeptide functionality. However, in accordance with the widely accepted and logical concept of natural cutoff selection for organisms living in nature, which explains its action against deleterious nucleotide substitutions in the nonsynonymous codons (mutations) and its holding of the active (effective) macromolecules of the polypeptides in a population, we were unable to get unambiguous evidence in favor of this concept in the current paper. Here, the phylogeny and systematics of mussel species from one of the largest taxons of bivalve mollusks are studied, the family known as Mytilidae. The phylogeny for Mytilidae (order Mytilida), which currently has no consensus in terms of systematics, is reconstructed using a data matrix of 26-27 mitogenomes. Initially, a set of 100 sequences from GenBank were downloaded and checked for their gender: whether they were female (F) or male (M) in origin. Our analysis of the new data confirms the known drastic differences between the F/M mitogenome lines in mussels. Phylogenetic reconstructions of the F-lines were performed using the combined set of genetic markers, reconstructing only protein-coding genes (PCGs), only rRNA + tRNA genes, and all genes. Additionally, the analysis includes the usage of nucleotide sequences composed of other data matrices, such as 20-68 mitogenome sequences. The time of divergence from MRCA, estimated via BEAST2, for Mytilidae is close to 293 Mya, suggesting that they originate in the Silurian Period. From all these data, a consensus for the phylogeny of the subfamily of Mytilinae and its systematics is suggested. In particular, the long-debated argument on mussel systematics was resolved as to whether Mytilidae, and the subfamily of Mytilinae, are monophyletic. The topology signal, which was strongly resolved in this paper and in the literature, has refuted the theory regarding the monophyly of Mytilinae.

Phylodynamic Inference of Bacterial Outbreak Parameters Using Nanopore Sequencing.

Nanopore sequencing and phylodynamic modeling have been used to reconstruct the transmission dynamics of viral epidemics, but their application to bacterial pathogens has remained challenging. Cost-effective bacterial genome sequencing and variant calling on nanopore platforms would greatly enhance surveillance and outbreak response in communities without access to sequencing infrastructure. Here, we adapt random forest models for single nucleotide polymorphism (SNP) polishing developed by Sanderson and colleagues (2020. High precision Neisseria gonorrhoeae variant and antimicrobial resistance calling from metagenomic nanopore sequencing. Genome Res. 30(9):1354-1363) to estimate divergence and effective reproduction numbers (Re) of two methicillin-resistant Staphylococcus aureus (MRSA) outbreaks from remote communities in Far North Queensland and Papua New Guinea (PNG; n = 159). Successive barcoded panels of S. aureus isolates (2 × 12 per MinION) sequenced at low coverage (>5× to 10×) provided sufficient data to accurately infer genotypes with high recall when compared with Illumina references. Random forest models achieved high resolution on ST93 outbreak sequence types (>90% accuracy and precision) and enabled phylodynamic inference of epidemiological parameters using birth-death skyline models. Our method reproduced phylogenetic topology, origin of the outbreaks, and indications of epidemic growth (Re > 1). Nextflow pipelines implement SNP polisher training, evaluation, and outbreak alignments, enabling reconstruction of within-lineage transmission dynamics for infection control of bacterial disease outbreaks on portable nanopore platforms. Our study shows that nanopore technology can be used for bacterial outbreak reconstruction at competitive costs, providing opportunities for infection control in hospitals and communities without access to sequencing infrastructure, such as in remote northern Australia and PNG.

Phylogeography Reveals Association between Swine Trade and the Spread of Porcine Epidemic Diarrhea Virus in China and across the World.

The ongoing SARS (severe acute respiratory syndrome)-CoV (coronavirus)-2 pandemic has exposed major gaps in our knowledge on the origin, ecology, evolution, and spread of animal coronaviruses. Porcine epidemic diarrhea virus (PEDV) is a member of the genus Alphacoronavirus in the family Coronaviridae that may have originated from bats and leads to significant hazards and widespread epidemics in the swine population. The role of local and global trade of live swine and swine-related products in disseminating PEDV remains unclear, especially in developing countries with complex swine production systems. Here, we undertake an in-depth phylogeographic analysis of PEDV sequence data (including 247 newly sequenced samples) and employ an extension of this inference framework that enables formally testing the contribution of a range of predictor variables to the geographic spread of PEDV. Within China, the provinces of Guangdong and Henan were identified as primary hubs for the spread of PEDV, for which we estimate live swine trade to play a very important role. On a global scale, the United States and China maintain the highest number of PEDV lineages. We estimate that, after an initial introduction out of China, the United States acted as an important source of PEDV introductions into Japan, Korea, China, and Mexico. Live swine trade also explains the dispersal of PEDV on a global scale. Given the increasingly global trade of live swine, our findings have important implications for designing prevention and containment measures to combat a wide range of livestock coronaviruses.

Bayesian inference of reassortment networks reveals fitness benefits of reassortment in human influenza viruses.

Reassortment is an important source of genetic diversity in segmented viruses and is the main source of novel pathogenic influenza viruses. Despite this, studying the reassortment process has been constrained by the lack of a coherent, model-based inference framework. Here, we introduce a coalescent-based model that allows us to explicitly model the joint coalescent and reassortment process. In order to perform inference under this model, we present an efficient Markov chain Monte Carlo algorithm to sample rooted networks and the embedding of phylogenetic trees within networks. This algorithm provides the means to jointly infer coalescent and reassortment rates with the reassortment network and the embedding of segments in that network from full-genome sequence data. Studying reassortment patterns of different human influenza datasets, we find large differences in reassortment rates across different human influenza viruses. Additionally, we find that reassortment events predominantly occur on selectively fitter parts of reassortment networks showing that on a population level, reassortment positively contributes to the fitness of human influenza viruses.

Assessing the relative performance of fast molecular dating methods for phylogenomic data.

Advances in genome sequencing techniques produced a significant growth of phylogenomic datasets. This massive amount of data represents a computational challenge for molecular dating with Bayesian approaches. Rapid molecular dating methods have been proposed over the last few decades to overcome these issues. However, a comparative evaluation of their relative performance on empirical data sets is lacking. We analyzed 23 empirical phylogenomic datasets to investigate the performance of two commonly employed fast dating methodologies: penalized likelihood (PL), implemented in treePL, and the relative rate framework (RRF), implemented in RelTime. They were compared to Bayesian analyses using the closest possible substitution models and calibration settings. We found that RRF was computationally faster and generally provided node age estimates statistically equivalent to Bayesian divergence times. PL time estimates consistently exhibited low levels of uncertainty. Overall, to approximate Bayesian approaches, RelTime is an efficient method with significantly lower computational demand, being more than 100 times faster than treePL. Thus, to alleviate the computational burden of Bayesian divergence time inference in the era of massive genomic data, molecular dating can be facilitated using the RRF, allowing evolutionary hypotheses to be tested more quickly and efficiently.

Relax, Keep Walking - A Practical Guide to Continuous Phylogeographic Inference with BEAST.

Spatially explicit phylogeographic analyses can be performed with an inference framework that employs relaxed random walks to reconstruct phylogenetic dispersal histories in continuous space. This core model was first implemented 10 years ago and has opened up new opportunities in the field of phylodynamics, allowing researchers to map and analyze the spatial dissemination of rapidly evolving pathogens. We here provide a detailed and step-by-step guide on how to set up, run, and interpret continuous phylogeographic analyses using the programs BEAUti, BEAST, Tracer, and TreeAnnotator.

Analysis of the genome of grapevine red blotch virus and related grabloviruses indicates diversification prior to the arrival of Vitis vinifera in North America.

In this study 163 complete whole-genome sequences of the emerging pathogen grapevine red blotch virus (GRBV; genus Grablovirus, family Geminiviridae) were used to reconstruct phylogenies using Bayesian analyses on time-tipped (heterochronous) data. Using different combinations of priors, Bayes factors identified heterochronous datasets (3×200 million chains) generated from strict clock and exponential tree priors as being the most robust. Substitution rates of 3.2×10-5 subsitutions per site per year (95% HPD 4.3-2.1×10-5) across the whole of the GRBV genome were estimated, suggesting ancestral GRBV diverged from ancestral wild Vitis latent virus 1 around 9 000 years ago, well before the first documented arrival of Vitis vinifera in North America. Whole-genome analysis of GRBV isolates in a single infected field-grown grapevine across 12 years identified 12 single nucleotide polymorphisms none of which were fixed substitutions: an observation not discordant with the in silico estimate. The substitution rate estimated here is lower than those estimated for other geminiviruses and is the first for a woody-host-infecting geminivirus.

SNP-based phylogenomic inference in Holarctic ground squirrels (Urocitellus).

Resolution of rapid evolutionary radiatons requires harvesting maximal signal from phylogenomic datasets. However, studies of non-model clades often target conserved loci that are characterized by reduced information content, which can negatively affect gene tree precision and species tree accuracy. Single nucleotide polymorphism (SNP)-based methods are an underutilized but potentially valuable tool for estimating phylogeny and divergence times because they do not rely on resolved gene trees, allowing information from many or all variant loci to be leveraged in species tree reconstruction. We evaluated the utility of SNP-based methods in resolving phylogeny of Holarctic ground squirrels (Urocitellus), a radiation that has been difficult to disentangle, even in prior phylogenomic studies. We inferred phylogeny from a dataset of >3,000 ultraconserved element loci (UCEs) using two methods (SNAPP, SVDquartets) and compared our results with a new mitogenome phylogeny. We also systematically evaluated how phasing of UCEs improves per-locus information content, inference of topology, and other parameters within each of these SNP-based methods. Phasing improved topological resolution and branch length estimation at shallow levels (within species complexes), but less so at deeper levels, likely reflecting true uncertainty due to ancestral polymorphisms segregating in rapidly diverging lineages. We resolved key clades in Urocitellus and present targeted opportunities for future phylogenomic inquiry. Our results also extend the roadmap for use of SNPs to address vertebrate radiations and inform comparative analyses at multiple temporal scales.

MEM-EX: An exemplar memory model of decisions from experience.

Many real-world decisions must be made on basis of experienced outcomes. However, there is little consensus about the mechanisms by which people make these decisions from experience (DfE). Across five experiments, we identified several factors influencing DfE. We also introduce a novel computational modeling framework, the memory for exemplars model (MEM-EX), which posits that decision makers rely on memory for previously experienced outcomes to make choices. Using MEM-EX, we demonstrate how cognitive mechanisms provide intuitive and parsimonious explanations for the effects of value-ignorance, salience, outcome order, and sample size. We also conduct a cross-validation analysis of several models within the MEM-EX framework. We compare these to three alternative models; two baseline models built on the principle of expected value maximization, and another employing a suite of choice methods previously shown to perform well in prediction tournaments. We find that MEM-EX consistently outperforms these competitors, demonstrating its value as a tool for making quantitative predictions without overfitting. We discuss the implications of these findings for our understanding of the interplay between attention, memory, and experience-based choice.

Development, validation, and implementation of a Short Breast Health Perception Questionnaire.

BACKGROUND: Health status and perception can be assessed by general or disease-specific questionnaires, and disease specific questionnaires are more specific than general questionnaires. Considering the importance of breast health perception (BHP) in women's lives and the lack of any pertinent questionnaires, we performed this study to develop a valid and reliable short BHP questionnaire (BHPQ); and then used it to assess the participants' BHP. METHODS: We first designed and developed the instrument and then measured its inter-rater agreement (IRA), content validity including content validity index (I-CVI) and scale content validity index (S-CVI), and reliability (through internal consistency and test-retest). We then evaluated the BHP of eligible women with normal breasts and benign breast disorders who attended our breast clinic. RESULTS: The IRA index (78.6%) showed the optimal relevance and clarity of the questionnaire. The content validity was acceptable; with S-CVIs of 87.35 and 84.42 for clarity and relevance, respectively. The internal reliability was high (Cronbach's alpha = 0.93). Three questions were eliminated for internal consistency (intraclass correlation coefficient < 0.7) but the rest of the questions showed good and excellent reliability. In the next step, BHP in the 350 eligible participants showed an overall score of 43.89 ± 9.09. CONCLUSION: This study introduces a valid and reliable 11-item BHPQ. We propose its use in various circumstances throughout breast cancer screening, diagnosis, and treatment; and in the assessment of BHP in various physiologic and reproductive situations.

Multidimensional Phylogenetic Metrics Identify Class I Aminoacyl-tRNA Synthetase Evolutionary Mosaicity and Inter-Modular Coupling.

The role of aminoacyl-tRNA synthetases (aaRS) in the emergence and evolution of genetic coding poses challenging questions concerning their provenance. We seek evidence about their ancestry from curated structure-based multiple sequence alignments of a structurally invariant "scaffold" shared by all 10 canonical Class I aaRS. Three uncorrelated phylogenetic metrics-mutation frequency, its uniformity, and row-by-row cladistic congruence-imply that the Class I scaffold is a mosaic assembled from successive genetic sources. Metrics for different modules vary in accordance with their presumed functionality. Sequences derived from the ATP- and amino acid- binding sites exhibit specific two-way coupling to those derived from Connecting Peptide 1, a third module whose metrics suggest later acquisition. The data help validate: (i) experimental fragmentations of the canonical Class I structure into three partitions that retain catalytic activities in proportion to their length; and (ii) evidence that the ancestral Class I aaRS gene also encoded a Class II ancestor in frame on the opposite strand. A 46-residue Class I "protozyme" roots the Class I tree prior to the adaptive radiation of the Rossmann dinucleotide binding fold that refined substrate discrimination. Such rooting implies near simultaneous emergence of genetic coding and the origin of the proteome, resolving a conundrum posed by previous inferences that Class I aaRS evolved after the genetic code had been implemented in an RNA world. Further, pinpointing discontinuous enhancements of aaRS fidelity establishes a timeline for the growth of coding from a binary amino acid alphabet.

Genomic Epidemiology, Evolution, and Transmission Dynamics of Porcine Deltacoronavirus.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown once again that coronavirus (CoV) in animals are potential sources for epidemics in humans. Porcine deltacoronavirus (PDCoV) is an emerging enteropathogen of swine with a worldwide distribution. Here, we implemented and described an approach to analyze the epidemiology of PDCoV following its emergence in the pig population. We performed an integrated analysis of full genome sequence data from 21 newly sequenced viruses, along with comprehensive epidemiological surveillance data collected globally over the last 15 years. We found four distinct phylogenetic lineages of PDCoV, which differ in their geographic circulation patterns. Interestingly, we identified more frequent intra- and interlineage recombination and higher virus genetic diversity in the Chinese lineages compared with the USA lineage where pigs are raised in different farming systems and ecological environments. Most recombination breakpoints are located in the ORF1ab gene rather than in genes encoding structural proteins. We also identified five amino acids under positive selection in the spike protein suggesting a role for adaptive evolution. According to structural mapping, three positively selected sites are located in the N-terminal domain of the S1 subunit, which is the most likely involved in binding to a carbohydrate receptor, whereas the other two are located in or near the fusion peptide of the S2 subunit and thus might affect membrane fusion. Finally, our phylogeographic investigations highlighted notable South-North transmission as well as frequent long-distance dispersal events in China that could implicate human-mediated transmission. Our findings provide new insights into the evolution and dispersal of PDCoV that contribute to our understanding of the critical factors involved in CoVs emergence.

PIQMEE: Bayesian Phylodynamic Method for Analysis of Large Data Sets with Duplicate Sequences.

Next-generation sequencing of pathogen quasispecies within a host yields data sets of tens to hundreds of unique sequences. However, the full data set often contains thousands of sequences, because many of those unique sequences have multiple identical copies. Data sets of this size represent a computational challenge for currently available Bayesian phylogenetic and phylodynamic methods. Through simulations, we explore how large data sets with duplicate sequences affect the speed and accuracy of phylogenetic and phylodynamic analysis within BEAST 2. We show that using unique sequences only leads to biases, and using a random subset of sequences yields imprecise parameter estimates. To overcome these shortcomings, we introduce PIQMEE, a BEAST 2 add-on that produces reliable parameter estimates from full data sets with increased computational efficiency as compared with the currently available methods within BEAST 2. The principle behind PIQMEE is to resolve the tree structure of the unique sequences only, while simultaneously estimating the branching times of the duplicate sequences. Distinguishing between unique and duplicate sequences allows our method to perform well even for very large data sets. Although the classic method converges poorly for data sets of 6,000 sequences when allowed to run for 7 days, our method converges in slightly more than 1 day. In fact, PIQMEE can handle data sets of around 21,000 sequences with 20 unique sequences in 14 days. Finally, we apply the method to a real, within-host HIV sequencing data set with several thousand sequences per patient.

Online Bayesian Phylodynamic Inference in BEAST with Application to Epidemic Reconstruction.

Reconstructing pathogen dynamics from genetic data as they become available during an outbreak or epidemic represents an important statistical scenario in which observations arrive sequentially in time and one is interested in performing inference in an "online" fashion. Widely used Bayesian phylogenetic inference packages are not set up for this purpose, generally requiring one to recompute trees and evolutionary model parameters de novo when new data arrive. To accommodate increasing data flow in a Bayesian phylogenetic framework, we introduce a methodology to efficiently update the posterior distribution with newly available genetic data. Our procedure is implemented in the BEAST 1.10 software package, and relies on a distance-based measure to insert new taxa into the current estimate of the phylogeny and imputes plausible values for new model parameters to accommodate growing dimensionality. This augmentation creates informed starting values and re-uses optimally tuned transition kernels for posterior exploration of growing data sets, reducing the time necessary to converge to target posterior distributions. We apply our framework to data from the recent West African Ebola virus epidemic and demonstrate a considerable reduction in time required to obtain posterior estimates at different time points of the outbreak. Beyond epidemic monitoring, this framework easily finds other applications within the phylogenetics community, where changes in the data-in terms of alignment changes, sequence addition or removal-present common scenarios that can benefit from online inference.

Biogeographic origins of southern African Silene (Caryophyllaceae).

Silene (Caryophyllaceae) is distributed predominantly in the northern Hemisphere, where it is most diverse around the Mediterranean Basin. The genus is also well represented in North Africa, extending into tropical, sub-Saharan and southern Africa. Eight native species are recognized in southern Africa, taxonomically placed in two sections: Elisanthe and Silene s.l. Although the taxonomy of the southern African taxa has recently been revised, their phylogenetic relationships and biogeographic history remain unclear. This study aims to infer the phylogenetic position and geographic origins of the southern African taxa. We generated DNA sequences of nuclear and plastid loci from several individuals belonging to all eight species of Silene recognized from southern Africa, and combined our DNA sequences with existing data representing species from major clades (i.e. sections) based on the recently revised Silene infrageneric taxonomy. We used a Bayesian coalescent species tree continuous diffusion approach to co-estimate the species tree and the ancestral areas of representative members of the genus. Our results show that the perennial southern African members of section Elisanthe form a strongly-supported clade with the Eurasian annual S. noctiflora and the Central Asian perennial S. turkestanica. The rest of the perennial species form a strongly-supported clade together with the annual S. aethiopica, which is nested in a larger Mediterranean clade comprising mostly annual species classified in section Silene s.l. Estimates of ancestral areas indicate a late Pleistocene dispersal to southern Africa from central and East Africa for the sub-Saharan members of section Silene s.l. The Elisanthe clade is inferred to have colonized southern Africa through long-distance dispersal from Eurasia during the late Pleistocene. Our findings support the hypothesis of a relatively recent colonization into southern Africa resulting from two independent dispersal events during the Pleistocene.

Bayesian Estimation of Past Population Dynamics in BEAST 1.10 Using the Skygrid Coalescent Model.

Inferring past population dynamics over time from heterochronous molecular sequence data is often achieved using the Bayesian Skygrid model, a nonparametric coalescent model that estimates the effective population size over time. Available in BEAST, a cross-platform program for Bayesian analysis of molecular sequences using Markov chain Monte Carlo, this coalescent model is often estimated in conjunction with a molecular clock model to produce time-stamped phylogenetic trees. We here provide a practical guide to using BEAST and its accompanying applications for the purpose of drawing inference under these models. We focus on best practices, potential pitfalls, and recommendations that can be generalized to other software packages for Bayesian inference. This protocol shows how to use TempEst, BEAUti, and BEAST 1.10 (http://beast.community/; last accessed July 29, 2019), LogCombiner as well as Tracer in a complete workflow.

Temporal patterns of diversification in Brassicaceae demonstrate decoupling of rate shifts and mesopolyploidization events.

BACKGROUND AND AIMS: Whole-genome duplication (WGD) events are considered important driving forces of diversification. At least 11 out of 52 Brassicaceae tribes had independent mesopolyploid WGDs followed by diploidization processes. However, the association between mesopolyploidy and subsequent diversification is equivocal. Herein we show the results from a family-wide diversification analysis on Brassicaceae, and elaborate on the hypothesis that polyploidization per se is a fundamental driver in Brassicaceae evolution. METHODS: We established a time-calibrated chronogram based on whole plastid genomes comprising representative Brassicaceae taxa and published data spanning the entire Rosidae clade. This allowed us to set multiple calibration points and anchored various Brassicaceae taxa for subsequent downstream analyses. All major splits among Brassicaceae lineages were used in BEAST analyses of 48 individually analysed tribes comprising 2101 taxa in total using the internal transcribed spacers of nuclear ribosomal DNA. Diversification patterns were investigated on these tribe-wide chronograms using BAMM and were compared with family-wide data on genome size variation and species richness. KEY RESULTS: Brassicaceae diverged 29.9 million years ago (Mya) during the Oligocene, and the majority of tribes started diversification in the Miocene with an average crown group age of about 12.5 Mya. This matches the cooling phase right after the Mid Miocene climatic optimum. Significant rate shifts were detected in 12 out of 52 tribes during the Mio- and Pliocene, decoupled from preceding mesopolyploid WGDs. Among the various factors analysed, the combined effect of tribal crown group age and net diversification rate (speciation minus extinction) is likely to explain sufficiently species richness across Brassicaceae tribes. CONCLUSIONS: The onset of the evolutionary splits among tribes took place under cooler and drier conditions. Pleistocene glacial cycles may have contributed to the maintenance of high diversification rates. Rate shifts are not consistently associated with mesopolyploid WGD. We propose, therefore, that WGDs in general serve as a constant 'pump' for continuous and high species diversification.