Abstract  We propose a simple statistical approach for using Dispersal–Vicariance Analysis (DIVA) software to infer biogeographic histories without fully bifurcating trees. In this approach, ancestral ranges are first optimized for a sample of Bayesian trees. The probability P of an ancestral range r at a node is then calculated as where Y is a node, and F(r_Y) is the frequency of range r among all the optimal solutions resulting from DIVA optimization at node Y, t is one of n topologies optimized, and Pt is the probability of topology t. Node Y is a hypothesized ancestor shared by a specific crown lineage and the sister of that lineage “x”, where x may vary due to phylogenetic uncertainty (polytomies and nodes with posterior probability <100%). Using this method, the ancestral distribution at Y can be estimated to provide inference of the geographic origins of the specific crown group of interest. This approach takes into account phylogenetic uncertainty as well as uncertainty from DIVA optimization. It is an extension of the previously described method called Bayes‐DIVA, which pairs Bayesian phylogenetic analysis with biogeographic analysis using DIVA. Further, we show that the probability P of an ancestral range at Y calculated using this method does not equate to pp*F(r_Y) on the Bayesian consensus tree when both variables are <100%, where pp is the posterior probability and F(r_Y) is the frequency of range r for the node containing the specific crown group. We tested our DIVA‐Bayes approach using Aesculus L., which has major lineages unresolved as a polytomy. We inferred the most probable geographic origins of the five traditional sections of Aesculus and of Aesculus californica Nutt. and examined range subdivisions at parental nodes of these lineages. Additionally, we used the DIVA‐Bayes data from Aesculus to quantify the effects on biogeographic inference of including two wildcard fossil taxa in phylogenetic analysis. Our analysis resolved the geographic ranges of the parental nodes of the lineages of Aesculus with moderate to high probabilities. The probabilities were greater than those estimated using the simple calculation of pp*F(r_y) at a statistically significant level for two of the six lineages. We also found that adding fossil wildcard taxa in phylogenetic analysis generally increased P for ancestral ranges including the fossil's distribution area. The ΔP was more dramatic for ranges that include the area of a wildcard fossil with a distribution area underrepresented among extant taxa. This indicates the importance of including fossils in biogeographic analysis. Exmination of range subdivision at the parental nodes revealed potential range evolution (extinction and dispersal events) along the stems of A. californica and sect. Parryana.

The availability of genomic and proteomic data from across the tree of life has made it possible to infer features of the genome and proteome of the last universal common ancestor (LUCA). A number of studies have done so, all using a unique set of methods and bioinformatics databases. Here, we compare predictions across eight such studies and measure both their agreement with one another and with the consensus predictions among them. We find that some LUCA genome studies show a strong agreement with the consensus predictions of the others, but that no individual study shares a high or even moderate degree of similarity with any other individual study. From these observations, we conclude that the consensus among studies provides a more accurate depiction of the core proteome of the LUCA and its functional repertoire. The set of consensus LUCA protein family predictions between all of these studies portrays a LUCA genome that, at minimum, encoded functions related to protein synthesis, amino acid metabolism, nucleotide metabolism, and the use of common, nucleotide‐derived organic cofactors.

In this study, we used a computational approach to investigate the early evolutionary history of a system of proteins that, together, embed and translocate other proteins across cell membranes. Cell membranes comprise the basis for cellularity, which is an ancient, fundamental organizing principle shared by all organisms and a key innovation in the evolution of life on Earth. Two related requirements for cellularity are that organisms are able to both embed proteins into membranes and translocate proteins across membranes. One system that accomplishes these tasks is the signal recognition particle (SRP) system, in which the core protein components are the paralogs, FtsY and Ffh. Complementary to the SRP system is the Sec translocation channel, in which the primary channel-forming protein is SecY. We performed phylogenetic analyses that strongly supported prior inferences that FtsY, Ffh, and SecY were all present by the time of the last universal common ancestor of life, the LUCA, and that the ancestor of FtsY and Ffh existed before the LUCA. Further, we combined ancestral sequence reconstruction and protein structure and function prediction to show that the LUCA had an SRP system and Sec translocation channel that were similar to those of extant organisms. We also show that the ancestor of Ffh and FtsY that predated the LUCA was more similar to FtsY than Ffh but could still have comprised a rudimentary protein translocation system on its own. Duplication of the ancestor of FtsY and Ffh facilitated the specialization of FtsY as a membrane bound receptor and Ffh as a cytoplasmic protein that could bind nascent proteins with specific membrane-targeting signal sequences. Finally, we analyzed amino acid frequencies in our ancestral sequence reconstructions to infer that the ancestral Ffh/FtsY protein likely arose prior to or just after the completion of the canonical genetic code. Taken together, our results offer a window into the very early evolutionary history of cellularity.

Ferns and lycophytes have remarkably large genomes. However, little is known about how their genome size evolved in fern lineages. To explore the origins and evolution of chromosome numbers and genome size in ferns, we used flow cytometry to measure the genomes of 240 species (255 samples) of extant ferns and lycophytes comprising 27 families and 72 genera, of which 228 species (242 samples) represent new reports. We analyzed correlations among genome size, spore size, chromosomal features, phylogeny, and habitat type preference within a phylogenetic framework. We also applied ANOVA and multinomial logistic regression analysis to preference of habitat type and genome size. Using the phylogeny, we conducted ancestral character reconstruction for habitat types and tested whether genome size changes simultaneously with shifts in habitat preference. We found that 2C values had weak phylogenetic signal, whereas the base number of chromosomes (x) had a strong phylogenetic signal. Furthermore, our analyses revealed a positive correlation between genome size and chromosome traits, indicating that the base number of chromosomes (x), chromosome size, and polyploidization may be primary contributors to genome expansion in ferns and lycophytes. Genome sizes in different habitat types varied significantly and were significantly correlated with habitat types; specifically, multinomial logistic regression indicated that species with larger 2C values were more likely to be epiphytes. Terrestrial habitat is inferred to be ancestral for both extant ferns and lycophytes, whereas transitions to other habitat types occurred as the major clades emerged. Shifts in habitat types appear be followed by periods of genomic stability. Based on these results, we inferred that habitat type changes and multiple whole-genome duplications have contributed to the formation of large genomes of ferns and their allies during their evolutionary history.