Biases of tree-independent-character-subsampling methods

A Guide to Phylogenomic Inference

Phylogenomics aims at reconstructing the evolutionary histories of organisms taking into account whole genomes or large fractions of genomes. Phylogenomics has significant applications in fields such as evolutionary biology, systematics, comparative genomics, and conservation genetics, providing valuable insights into the origins and relationships of species and contributing to our understanding of biological diversity and evolution. This chapter surveys phylogenetic concepts and methods aimed at both gene tree and species tree reconstruction while also addressing common pitfalls, providing references to relevant computer programs. A practical phylogenomic analysis example including bacterial genomes is presented at the end of the chapter.

A phylogenomic backbone for gastropod molluscs

Gastropods have survived several mass extinctions during their evolutionary history resulting in extraordinary diversity in morphology, ecology, and developmental modes, which complicate the reconstruction of a robust phylogeny. Currently, gastropods are divided into six subclasses: Caenogastropoda, Heterobranchia, Neomphaliones, Neritimorpha, Patellogastropoda, and Vetigastropoda. Phylogenetic relationships among these taxa historically lack consensus, despite numerous efforts using morphological and molecular information. We generated sequence data for transcriptomes derived from twelve taxa belonging to clades with little or no prior representation in previous studies in order to infer the deeper cladogenetic events within Gastropoda and, for the first time, infer the position of the deep-sea Neomphaliones using a phylogenomic approach. We explored the impact of missing data, homoplasy, and compositional heterogeneity on the inferred phylogenetic hypotheses. We recovered a highly supported backbone for gastropod relationships that is congruent with morphological and mitogenomic evidence, in which Patellogastropoda, true limpets, are the sister lineage to all other gastropods (Orthogastropoda) which are divided into two main clades (i) Vetigastropoda s.l. (including Pleurotomariida + Neomphaliones) and (ii) Neritimorpha + (Caenogastropoda + Heterobranchia). As such, our results support the recognition of five subclasses (or infraclasses) in Gastropoda: Patellogastropoda, Vetigastropoda, Neritimorpha, Caenogastropoda and Heterobranchia.

Phylogenetic Signal, Congruence, and Uncertainty across Bacteria and Archaea

Reconstruction of the Tree of Life is a central goal in biology. Although numerous novel phyla of bacteria and archaea have recently been discovered, inconsistent phylogenetic relationships are routinely reported, and many inter-phylum and inter-domain evolutionary relationships remain unclear. Here, we benchmark different marker genes often used in constructing multidomain phylogenetic trees of bacteria and archaea and present a set of marker genes that perform best for multidomain trees constructed from concatenated alignments. We use recently-developed Tree Certainty metrics to assess the confidence of our results and to obviate the complications of traditional bootstrap-based metrics. Given the vastly disparate number of genomes available for different phyla of bacteria and archaea, we also assessed the impact of taxon sampling on multidomain tree construction. Our results demonstrate that biases between the representation of different taxonomic groups can dramatically impact the topology of resulting trees. Inspection of our highest-quality tree supports the division of most bacteria into Terrabacteria and Gracilicutes, with Thermatogota and Synergistota branching earlier from these superphyla. This tree also supports the inclusion of the Patescibacteria within the Terrabacteria as a sister group to the Chloroflexota instead of as a basal-branching lineage. For the Archaea, our tree supports three monophyletic lineages (DPANN, Euryarchaeota, and TACK/Asgard), although we note the basal placement of the DPANN may still represent an artifact caused by biased sequence composition. Our findings provide a robust and standardized framework for multidomain phylogenetic reconstruction that can be used to evaluate inter-phylum relationships and assess uncertainty in conflicting topologies of the Tree of Life.

A Total-Evidence Dated Phylogeny of Echinoidea Combining Phylogenomic and Paleontological Data

Phylogenomic and paleontological data constitute complementary resources for unraveling the phylogenetic relationships and divergence times of lineages, yet few studies have attempted to fully integrate them. Several unique properties of echinoids (sea urchins) make them especially useful for such synthesizing approaches, including a remarkable fossil record that can be incorporated into explicit phylogenetic hypotheses. We revisit the phylogeny of crown group Echinoidea using a total-evidence dating approach that combines the largest phylogenomic data set for the clade, a large-scale morphological matrix with a dense fossil sampling, and a novel compendium of tip and node age constraints. To this end, we develop a novel method for subsampling phylogenomic data sets that selects loci with high phylogenetic signal, low systematic biases, and enhanced clock-like behavior. Our results demonstrate that combining different data sources increases topological accuracy and helps resolve conflicts between molecular and morphological data. Notably, we present a new hypothesis for the origin of sand dollars, and restructure the relationships between stem and crown echinoids in a way that implies a long stretch of undiscovered evolutionary history of the crown group in the late Paleozoic. Our efforts help bridge the gap between phylogenomics and phylogenetic paleontology, providing a model example of the benefits of combining the two. [Echinoidea; fossils; paleontology; phylogenomics; time calibration; total evidence.].

A simple method for data partitioning based on relative evolutionary rates

BACKGROUND

Multiple studies have demonstrated that partitioning of molecular datasets is important in model-based phylogenetic analyses. Commonly, partitioning is done a priori based on some known properties of sequence evolution, e.g. differences in rate of evolution among codon positions of a protein-coding gene. Here we propose a new method for data partitioning based on relative evolutionary rates of the sites in the alignment of the dataset being analysed. The rates are inferred using the previously published Tree Independent Generation of Evolutionary Rates (TIGER), and the partitioning is conducted using our novel python script RatePartitions. We conducted simulations to assess the performance of our new method, and we applied it to eight published multi-locus phylogenetic datasets, representing different taxonomic ranks within the insect order Lepidoptera (butterflies and moths) and one phylogenomic dataset, which included ultra-conserved elements as well as introns.

METHODS

We used TIGER-rates to generate relative evolutionary rates for all sites in the alignments. Then, using RatePartitions, we partitioned the data into partitions based on their relative evolutionary rate. RatePartitions applies a simple formula that ensures a distribution of sites into partitions following the distribution of rates of the characters from the full dataset. This ensures that the invariable sites are placed in a partition with slowly evolving sites, avoiding the pitfalls of previously used methods, such as k-means. Different partitioning strategies were evaluated using BIC scores as calculated by PartitionFinder.

RESULTS

Simulations did not highlight any misbehaviour of our partitioning approach, even under difficult parameter conditions or missing data. In all eight phylogenetic datasets, partitioning using TIGER-rates and RatePartitions was significantly better as measured by the BIC scores than other partitioning strategies, such as the commonly used partitioning by gene and codon position. We compared the resulting topologies and node support for these eight datasets as well as for the phylogenomic dataset.

DISCUSSION

We developed a new method of partitioning phylogenetic datasets without using any prior knowledge (e.g. DNA sequence evolution). This method is entirely based on the properties of the data being analysed and can be applied to DNA sequences (protein-coding, introns, ultra-conserved elements), protein sequences, as well as morphological characters. A likely explanation for why our method performs better than other tested partitioning strategies is that it accounts for the heterogeneity in the data to a much greater extent than when data are simply subdivided based on prior knowledge.

Noise and biases in genomic data may underlie radically different hypotheses for the position of Iguania within Squamata

Squamate reptiles are a major component of vertebrate biodiversity whose crown-clade traces its origin to a narrow window of time in the Mesozoic during which the main subclades diverged in rapid succession. Deciphering phylogenetic relationships among these lineages has proven challenging given the conflicting signals provided by genomic and phenomic data. Most notably, the placement of Iguania has routinely differed between data sources, with morphological evidence supporting a sister relationship to the remaining squamates (Scleroglossa hypothesis) and molecular data favoring a highly nested position alongside snakes and anguimorphs (Toxicofera hypothesis). We provide novel insights by generating an expanded morphological dataset and exploring the presence of phylogenetic signal, noise, and biases in molecular data. Our analyses confirm the presence of strong conflicting signals for the position of Iguania between morphological and molecular datasets. However, we also find that molecular data behave highly erratically when inferring the deepest branches of the squamate tree, a consequence of limited phylogenetic signal to resolve this ancient radiation with confidence. This, in turn, seems to result from a rate of evolution that is too high for historical signals to survive to the present. Finally, we detect significant systematic biases, with iguanians and snakes sharing faster rates of molecular evolution and a similarly biased nucleotide composition. A combination of scant phylogenetic signal, high levels of noise, and the presence of systematic biases could result in the misplacement of Iguania. We regard this explanation to be at least as plausible as the complex scenario of convergence and reversals required for morphological data to be misleading. We further evaluate and discuss the utility of morphological data to resolve ancient radiations, as well as its impact in combined-evidence phylogenomic analyses, with results relevant for the assessment of evidence and conflict across the Tree of Life.

Phylogenomics

Phylogenomics aims at reconstructing the evolutionary histories of organisms taking into account whole genomes or large fractions of genomes. The abundance of genomic data for an enormous variety of organisms has enabled phylogenomic inference of many groups, and this has motivated the development of many computer programs implementing the associated methods. This chapter surveys phylogenetic concepts and methods aimed at both gene tree and species tree reconstruction while also addressing common pitfalls, providing references to relevant computer programs. A practical phylogenomic analysis example including bacterial genomes is presented at the end of the chapter.