Identifying and addressing methodological incongruence in phylogenomics: A review

Scoutknife: A naïve, whole genome informed phylogenetic robusticity metric

Background: The phylogenetic bootstrap, first proposed by Felsenstein in 1985, is a critically important statistical method in assessing the robusticity of phylogenetic datasets. Core to its concept was the use of pseudo sampling - assessing the data by generating new replicates derived from the initial dataset that was used to generate the phylogeny. In this way, phylogenetic support metrics could overcome the lack of perfect, infinite data. With infinite data, however, it is possible to sample smaller replicates directly from the data to obtain both the phylogeny and its statistical robusticity in the same analysis. Due to the growth of whole genome sequencing, the depth and breadth of our datasets have greatly expanded and are set to only expand further. With genome-scale datasets comprising thousands of genes, we can now obtain a proxy for infinite data. Accordingly, we can potentially abandon the notion of pseudo sampling and instead randomly sample small subsets of genes from the thousands of genes in our analyses. Methods: We introduce Scoutknife, a jackknife-style subsampling implementation that generates 100 datasets by randomly sampling a small number of genes from an initial large-gene dataset to jointly establish both a phylogenetic hypothesis and assess its robusticity. We assess its effectiveness by using 18 previously published datasets and 100 simulation studies. Results: We show that Scoutknife is conservative and informative as to conflicts and incongruence across the whole genome, without the need for subsampling based on traditional model selection criteria. Conclusions: Scoutknife reliably achieves comparable results to selecting the best genes on both real and simulation datasets, while being resistant to the potential biases caused by selecting for model fit. As the amount of genome data grows, it becomes an even more exciting option to assess the robusticity of phylogenetic hypotheses.

A comprehensive phylogenomic study unveils evolutionary patterns and challenges in the mitochondrial genomes of Carcharhiniformes: A focus on Triakidae

The complex evolutionary patterns in the mitochondrial genome (mitogenome) of the most species-rich shark order, the Carcharhiniformes (ground sharks) has led to challenges in the phylogenomic reconstruction of the families and genera belonging to the order, particularly the family Triakidae (houndsharks). The current state of Triakidae phylogeny remains controversial, with arguments for both monophyly and paraphyly within the family. We hypothesize that this variability is triggered by the selection of different a priori partitioning schemes to account for site and gene heterogeneity within the mitogenome. Here we used an extensive statistical framework to select the a priori partitioning scheme for inference of the mitochondrial phylogenomic relationships within Carcharhiniformes, tested site heterogeneous CAT + GTR + G4 models and incorporated the multi-species coalescent model (MSCM) into our analyses to account for the influence of gene tree discordance on species tree inference. We included five newly assembled houndshark mitogenomes to increase resolution of Triakidae. During the assembly procedure, we uncovered a 714 bp-duplication in the mitogenome of Galeorhinus galeus. Phylogenetic reconstruction confirmed monophyly within Triakidae and the existence of two distinct clades of the expanded Mustelus genus. The latter alludes to potential evolutionary reversal of reproductive mode from placental to aplacental, suggesting that reproductive mode has played a role in the trajectory of adaptive divergence. These new sequences have the potential to contribute to population genomic investigations, species phylogeography delineation, environmental DNA metabarcoding databases and, ultimately, improved conservation strategies for these ecologically and economically important species.

New algorithm for the analysis of nucleotide and amino acid evolutionary relationships based on Klein four-group

Phylogenetics is the study of ancestral relationships among biological species. Such sequence analyses are often represented as phylogenetic trees. The branching pattern of each tree and its topology reflect the evolutionary relatedness between analyzed sequences. We present a Klein four-group algorithm (K4A) for the evolutionary analysis of nucleotide and amino acid sequences. Klein four-group set of operators consists of: identity e (U), and three elements-a = transition (C), b = transversion (G) and c = transition-transversion or complementarity (A). We generated Klein four-group based distance matrices of: 1. Cayley table (CK4), 2. Table rows (K4R), 3. Table columns (K4C), and 4. Euclidean 2D distance (K4E). The performance of the matrices was tested on a dataset of RecA proteins in bacteria, eukaryotes (Rad51 homolog) and archaea (RadA homolog). RecA and its functional homologs are found in all species, and are essential for the repair and maintenance of DNA. Consequently, they represent a good model for the study of evolutionary relationship of protein and nucleotide sequences. The ancestral relationship between the sequences was correctly classified by all K4A matrices concerning general topology. All distance matrices exhibited small variations among species, and overall results of tree classification were in agreement with the general patterns obtained by standard BLOSUM and PAM substitution matrices. During the evolution of a code there is a phase of optimization of system rules, the ambiguity of a code is eliminated, and the system starts producing specific components. Klein four-group algorithm is consistent with the concept of ambiguity reduction. It also enables the use of different genetic code table variants optimized for particular transitions in evolution based on biological specificity.