Impact of increasing morphological information by micro-CT scanning on the phylogenetic placement of Darwin wasps (Hymenoptera, Ichneumonidae) in amber

The correct interpretation of fossils and their reliable taxonomic placements are fundamental for understanding the evolutionary history of biodiversity. Amber inclusions often preserve more morphological information than compression fossils, but are often partially hidden or distorted, which can impede taxonomic identification. Here, we studied four new fossil species of Darwin wasps from Baltic and Dominican amber, using micro computed tomography (micro-CT) scans and 3D reconstructions to accurately interpret and increase the availability of morphological information. We then infer their taxonomic placement in a Bayesian phylogenetic analysis by combining morphological and molecular data of extant and fossil Darwin wasps and evaluate the impact and usefulness of the additional information from micro-CT scanning. The results show that although we gained significant morphological information from micro-CT scanning, especially concerning measurements and hidden dorsal and ventral structures, this did not impact subfamily-level placement for any of the four fossils. However, micro-CT scanning improved the precision of fossil placements at the genus level, which might be key in future dating and diversification analyses. Finally, we describe the four new fossil species as Rhyssa gulliveri sp. nov. in Rhyssinae, Triclistus levii sp. nov. in Metopiinae, Firkantus freddykruegeri gen. et. sp. nov. in Pimplinae and Magnocula sarcophaga gen. et sp. nov. in Phygadeuontinae. The first two species are the first known representatives of the subfamilies Rhyssinae and Metopiinae in amber.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13358-023-00294-2.

Bayesian phylogenetic inference of HIV latent lineage ages using serial sequences

HIV evolves rapidly within individuals, allowing phylogenetic studies to infer histories of viral lineages on short time scales. Latent HIV sequences are an exception to this rapid evolution, as their transcriptional inactivity leads to negligible mutation rates compared with non-latent HIV lineages. This difference in mutation rates generates potential information about the times at which sequences entered the latent reservoir, providing insight into the dynamics of the latent reservoir. A Bayesian phylogenetic method is developed to infer integration times of latent HIV sequences. The method uses informative priors to incorporate biologically sensible bounds on inferences (such as requiring sequences to become latent before being sampled) that many existing methods lack. A new simulation method is also developed, based on widely used epidemiological models of within-host viral dynamics, and applied to evaluate the new method-showing that point estimates and credible intervals are often more accurate than existing methods. Accurate estimates of latent integration dates are crucial in relating integration times to key events during HIV infection, such as treatment initiation. The method is applied to publicly available sequence data from four HIV patients, providing new insights regarding the temporal pattern of latent integration.

Adaptive Tree Proposals for Bayesian Phylogenetic Inference

Bayesian inference of phylogeny with MCMC plays a key role in the study of evolution. Yet, this method still suffers from a practical challenge identified more than two decades ago: designing tree topology proposals that efficiently sample tree spaces. In this article, I introduce the concept of adaptive tree proposals for unrooted topologies, that is tree proposals adapting to the posterior distribution as it is estimated. I use this concept to elaborate two adaptive variants of existing proposals and an adaptive proposal based on a novel design philosophy in which the structure of the proposal is informed by the posterior distribution of trees. I investigate the performance of these proposals by first presenting a metric that captures the performance of each proposal within a mixture of proposals. Using this metric, I compare the performance of the adaptive proposals to the performance of standard and parsimony-guided proposals on 11 empirical datasets. Using adaptive proposals led to consistent performance gains and resulted in up to 18-fold increases in mixing efficiency and 6-fold increases in convergence rate without increasing the computational cost of these analyses.

A Bayesian phylogenetic study of the Dravidian language family

The Dravidian language family consists of about 80 varieties (Hammarström H. 2016 Glottolog 2.7) spoken by 220 million people across southern and central India and surrounding countries (Steever SB. 1998 In The Dravidian languages (ed. SB Steever), pp. 1-39: 1). Neither the geographical origin of the Dravidian language homeland nor its exact dispersal through time are known. The history of these languages is crucial for understanding prehistory in Eurasia, because despite their current restricted range, these languages played a significant role in influencing other language groups including Indo-Aryan (Indo-European) and Munda (Austroasiatic) speakers. Here, we report the results of a Bayesian phylogenetic analysis of cognate-coded lexical data, elicited first hand from native speakers, to investigate the subgrouping of the Dravidian language family, and provide dates for the major points of diversification. Our results indicate that the Dravidian language family is approximately 4500 years old, a finding that corresponds well with earlier linguistic and archaeological studies. The main branches of the Dravidian language family (North, Central, South I, South II) are recovered, although the placement of languages within these main branches diverges from previous classifications. We find considerable uncertainty with regard to the relationships between the main branches.

Total-Evidence Dating under the Fossilized Birth-Death Process

Bayesian total-evidence dating involves the simultaneous analysis of morphological data from the fossil record and morphological and sequence data from recent organisms, and it accommodates the uncertainty in the placement of fossils while dating the phylogenetic tree. Due to the flexibility of the Bayesian approach, total-evidence dating can also incorporate additional sources of information. Here, we take advantage of this and expand the analysis to include information about fossilization and sampling processes. Our work is based on the recently described fossilized birth-death (FBD) process, which has been used to model speciation, extinction, and fossilization rates that can vary over time in a piecewise manner. So far, sampling of extant and fossil taxa has been assumed to be either complete or uniformly at random, an assumption which is only valid for a minority of data sets. We therefore extend the FBD process to accommodate diversified sampling of extant taxa, which is standard practice in studies of higher-level taxa. We verify the implementation using simulations and apply it to the early radiation of Hymenoptera (wasps, ants, and bees). Previous total-evidence dating analyses of this data set were based on a simple uniform tree prior and dated the initial radiation of extant Hymenoptera to the late Carboniferous (309 Ma). The analyses using the FBD prior under diversified sampling, however, date the radiation to the Triassic and Permian (252 Ma), slightly older than the age of the oldest hymenopteran fossils. By exploring a variety of FBD model assumptions, we show that it is mainly the accommodation of diversified sampling that causes the push toward more recent divergence times. Accounting for diversified sampling thus has the potential to close the long-discussed gap between rocks and clocks. We conclude that the explicit modeling of fossilization and sampling processes can improve divergence time estimates, but only if all important model aspects, including sampling biases, are adequately addressed.

Improved calibration of the human mitochondrial clock using ancient genomes

Reliable estimates of the rate at which DNA accumulates mutations (the substitution rate) are crucial for our understanding of the evolution and past demography of virtually any species. In humans, there are considerable uncertainties around these rates, with substantial variation among recent published estimates. Substitution rates have traditionally been estimated by associating dated events to the root (e.g., the divergence between humans and chimpanzees) or to internal nodes in a phylogenetic tree (e.g., first entry into the Americas). The recent availability of ancient mitochondrial DNA sequences allows for a more direct calibration by assigning the age of the sequenced samples to the tips within the human phylogenetic tree. But studies also vary greatly in the methodology employed and in the sequence panels analyzed, making it difficult to tease apart the causes for the differences between previous estimates. To clarify this issue, we compiled a comprehensive data set of 350 ancient and modern human complete mitochondrial DNA genomes, among which 146 were generated for the purpose of this study and estimated substitution rates using calibrations based both on dated nodes and tips. Our results demonstrate that, for the same data set, estimates based on individual dated tips are far more consistent with each other than those based on nodes and should thus be considered as more reliable.