A Practical Guide to Design and Assess a Phylogenomic Study

Sea anemone (Anthozoa, Actiniaria) diversity in Mo'orea (French Polynesia)

Sea anemones (Order Actiniaria) are a diverse group of marine invertebrates ubiquitous across marine ecosystems. Despite their wide distribution and success, a knowledge gap persists in our understanding of their diversity within tropical systems, owed to sampling bias of larger and more charismatic species overshadowing cryptic lineages. This study aims to delineate the sea anemone diversity in Mo'orea (French Polynesia) with the use of a dataset from the Mo'orea Biocode's "BioBlitz" initiative, which prioritized the sampling of more cryptic and understudied taxa. Implementing a target enrichment approach, we integrate 71 newly sequenced samples into an expansive phylogenetic framework and contextualize Mo'orea's diversity within global distribution patterns of sea anemones. Our analysis corroborates the presence of several previously documented sea anemones in French Polynesia and identifies for the first time the occurrence of members of genera Andvakia and Aiptasiomorpha. This research unveils the diverse sea anemone ecosystem in Mo'orea, spotlighting the area's ecological significance and emphasizing the need for continued exploration. Our methodology, encompassing a broad BLAST search coupled with phylogenetic analysis, proved to be a practical and effective approach for overcoming the limitations posed by the lack of comprehensive sequence data for sea anemones. We discuss the merits and limitations of current molecular methodologies and stress the importance of further research into lesser-studied marine organisms like sea anemones. Our work sets a precedent for future phylogenetic studies stemming from BioBlitz endeavors.

OrthoPhyl-streamlining large-scale, orthology-based phylogenomic studies of bacteria at broad evolutionary scales

There are a staggering number of publicly available bacterial genome sequences (at writing, 2.0 million assemblies in NCBI's GenBank alone), and the deposition rate continues to increase. This wealth of data begs for phylogenetic analyses to place these sequences within an evolutionary context. A phylogenetic placement not only aids in taxonomic classification but informs the evolution of novel phenotypes, targets of selection, and horizontal gene transfer. Building trees from multi-gene codon alignments is a laborious task that requires bioinformatic expertise, rigorous curation of orthologs, and heavy computation. Compounding the problem is the lack of tools that can streamline these processes for building trees from large-scale genomic data. Here we present OrthoPhyl, which takes bacterial genome assemblies and reconstructs trees from whole genome codon alignments. The analysis pipeline can analyze an arbitrarily large number of input genomes (>1200 tested here) by identifying a diversity-spanning subset of assemblies and using these genomes to build gene models to infer orthologs in the full dataset. To illustrate the versatility of OrthoPhyl, we show three use cases: E. coli/Shigella, Brucella/Ochrobactrum and the order Rickettsiales. We compare trees generated with OrthoPhyl to trees generated with kSNP3 and GToTree along with published trees using alternative methods. We show that OrthoPhyl trees are consistent with other methods while incorporating more data, allowing for greater numbers of input genomes, and more flexibility of analysis.

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.

Complexity of avian evolution revealed by family-level genomes

Despite tremendous efforts in the past decades, relationships among main avian lineages remain heavily debated without a clear resolution. Discrepancies have been attributed to diversity of species sampled, phylogenetic method and the choice of genomic regions1-3. Here we address these issues by analysing the genomes of 363 bird species4 (218 taxonomic families, 92% of total). Using intergenic regions and coalescent methods, we present a well-supported tree but also a marked degree of discordance. The tree confirms that Neoaves experienced rapid radiation at or near the Cretaceous-Palaeogene boundary. Sufficient loci rather than extensive taxon sampling were more effective in resolving difficult nodes. Remaining recalcitrant nodes involve species that are a challenge to model due to either extreme DNA composition, variable substitution rates, incomplete lineage sorting or complex evolutionary events such as ancient hybridization. Assessment of the effects of different genomic partitions showed high heterogeneity across the genome. We discovered sharp increases in effective population size, substitution rates and relative brain size following the Cretaceous-Palaeogene extinction event, supporting the hypothesis that emerging ecological opportunities catalysed the diversification of modern birds. The resulting phylogenetic estimate offers fresh insights into the rapid radiation of modern birds and provides a taxon-rich backbone tree for future comparative studies.

Asymmetric Cluster-Based Measures for Comparative Phylogenetics

Phylogenetic inference and reconstruction methods generate hypotheses on evolutionary history. Competing inference methods are frequently used, and the evaluation of the generated hypotheses is achieved using tree comparison costs. The Robinson-Foulds (RF) distance is a widely used cost to compare the topology of two trees, but this cost is sensitive to tree error and can overestimate tree differences. To overcome this limitation, a refined version of the RF distance called the Cluster Affinity (CA) distance was introduced. However, CA distances are symmetric and cannot compare different types of trees. These asymmetric comparisons occur when gene trees are compared with species trees, when disparate datasets are integrated into a supertree, or when tree comparison measures are used to infer a phylogenetic network. In this study, we introduce a relaxation of the original Affinity distance to compare heterogeneous trees called the asymmetric CA cost. We also develop a biologically interpretable cost, the Cluster Support cost that normalizes by cluster size across gene trees. The characteristics of these costs are similar to the symmetric CA cost. We describe efficient algorithms, derive the exact diameters, and use these to standardize the cost to be applicable in practice. These costs provide objective, fine-scale, and biologically interpretable values that can assess differences and similarities between phylogenetic trees.

Patchwork: Alignment-Based Retrieval and Concatenation of Phylogenetic Markers from Genomic Data

Low-coverage whole-genome sequencing (also known as "genome skimming") is becoming an increasingly affordable approach to large-scale phylogenetic analyses. While already routinely used to recover organellar genomes, genome skimming is rather rarely utilized for recovering single-copy nuclear markers. One reason might be that only few tools exist to work with this data type within a phylogenomic context, especially to deal with fragmented genome assemblies. We here present a new software tool called Patchwork for mining phylogenetic markers from highly fragmented short-read assemblies as well as directly from sequence reads. Patchwork is an alignment-based tool that utilizes the sequence aligner DIAMOND and is written in the programming language Julia. Homologous regions are obtained via a sequence similarity search, followed by a "hit stitching" phase, in which adjacent or overlapping regions are merged into a single unit. The novel sliding window algorithm trims away any noncoding regions from the resulting sequence. We demonstrate the utility of Patchwork by recovering near-universal single-copy orthologs within a benchmarking study, and we additionally assess the performance of Patchwork in comparison with other programs. We find that Patchwork allows for accurate retrieval of (putatively) single-copy genes from genome skimming data sets at different sequencing depths with high computational speed, outperforming existing software targeting similar tasks. Patchwork is released under the GNU General Public License version 3. Installation instructions, additional documentation, and the source code itself are all available via GitHub at https://github.com/fethalen/Patchwork.

kakapo: easy extraction and annotation of genes from raw RNA-seq reads

kakapo (kākāpō) is a Python-based pipeline that allows users to extract and assemble one or more specified genes or gene families. It flexibly uses original RNA-seq read or GenBank SRA accession inputs without performing global assembly of entire transcriptomes or metatranscriptomes. The pipeline identifies open reading frames in the assembled gene transcripts and annotates them. It optionally filters raw reads for ribosomal, plastid, and mitochondrial reads, or reads belonging to non-target organisms (e.g., viral, bacterial, human). kakapo can be employed for targeted assembly, to extract arbitrary loci, such as those commonly used for phylogenetic inference in systematics or candidate genes and gene families in phylogenomic and metagenomic studies. We provide example applications and discuss how its use can offset the declining value of GenBank's single-gene databases and help assemble datasets for a variety of phylogenetic analyses.

Confusion will be my epitaph: genome-scale discordance stifles phylogenetic resolution of Holothuroidea

Sea cucumbers (Holothuroidea) are a diverse clade of echinoderms found from intertidal waters to the bottom of the deepest oceanic trenches. Their reduced skeletons and limited number of phylogenetically informative traits have long obfuscated morphological classifications. Sanger-sequenced molecular datasets have also failed to constrain the position of major lineages. Noteworthy, topological uncertainty has hindered a resolution for Neoholothuriida, a highly diverse clade of Permo-Triassic age. We perform the first phylogenomic analysis of Holothuroidea, combining existing datasets with 13 novel transcriptomes. Using a highly curated dataset of 1100 orthologues, our efforts recapitulate previous results, struggling to resolve interrelationships among neoholothuriid clades. Three approaches to phylogenetic reconstruction (concatenation under both site-homogeneous and site-heterogeneous models, and coalescent-aware inference) result in alternative resolutions, all of which are recovered with strong support and across a range of datasets filtered for phylogenetic usefulness. We explore this intriguing result using gene-wise log-likelihood scores and attempt to correlate these with a large set of gene properties. While presenting novel ways of exploring and visualizing support for alternative trees, we are unable to discover significant predictors of topological preference, and our efforts fail to favour one topology. Neoholothuriid genomes seem to retain an amalgam of signals derived from multiple phylogenetic histories.

Phylogenomic analyses using a new 1013-gene Vitaceae bait-set support major groups of North American Vitis

A set of newly designed Vitaceae baits targeting 1013 genes was employed to explore phylogenetic relationships among North American Vitis. Eurasian Vitis taxa including Vitis vinifera were found to be nested within North American Vitis subgenus Vitis. North American Vitis subgenus Vitis can be placed into nine main groups: the Monticola group, the Occidentales group, the Californica group, the Vinifera group (introduced from Eurasia), the Mustangensis group, the Palmata group, the Aestivalis group, the Labrusca group, and the Cinerea group. Strong cytonuclear discordances were detected in North American Vitis, with many species non-monophyletic in the plastid phylogeny, while monophyletic in the nuclear phylogeny. The phylogenomic analyses support recognizing four distinct species in the Vitis cinerea complex in North America: V. cinerea, V. baileyana, V. berlandieri, and V. simpsonii. Such treatment will better serve the conservation of wild Vitis diversity in North America. Yet the evolutionary history of Vitis is highly complex, with the concordance analyses indicating conflicting signals across the phylogeny. Cytonuclear discordances and Analyses using the Species Networks applying Quartets (SNaQ) method support extensive hybridizations in North American Vitis. The results further indicate that plastid genomes alone are insufficient for resolving the evolutionary history of plant groups that have undergone rampant hybridization, like the case in North American Vitis. Nuclear gene data are essential for species delimitation, identification and reconstructing evolutionary relationships; therefore, they are imperative for plant phylogenomic studies.

Repeatedly Northwards and Upwards: Southern African Grasslands Fuel the Colonization of the African Sky Islands in Helichrysum (Compositae)

The Afromontane and Afroalpine areas constitute some of the main biodiversity hotspots of Africa. They are particularly rich in plant endemics, but the biogeographic origins and evolutionary processes leading to this outstanding diversity are poorly understood. We performed phylogenomic and biogeographic analyses of one of the most species-rich plant genera in these mountains, Helichrysum (Compositae-Gnaphalieae). Most previous studies have focused on Afroalpine elements of Eurasian origin, and the southern African origin of Helichrysum provides an interesting counterexample. We obtained a comprehensive nuclear dataset from 304 species (≈50% of the genus) using target-enrichment with the Compositae1061 probe set. Summary-coalescent and concatenation approaches combined with paralog recovery yielded congruent, well-resolved phylogenies. Ancestral range estimations revealed that Helichrysum originated in arid southern Africa, whereas the southern African grasslands were the source of most lineages that dispersed within and outside Africa. Colonization of the tropical Afromontane and Afroalpine areas occurred repeatedly throughout the Miocene-Pliocene. This timing coincides with mountain uplift and the onset of glacial cycles, which together may have facilitated both speciation and intermountain gene flow, contributing to the evolution of the Afroalpine flora.

Identifying and addressing methodological incongruence in phylogenomics: A review

The availability of phylogenetic data has greatly expanded in recent years. As a result, a new era in phylogenetic analysis is dawning-one in which the methods we use to analyse and assess our data are the bottleneck to producing valuable phylogenetic hypotheses, rather than the need to acquire more data. This makes the ability to accurately appraise and evaluate new methods of phylogenetic analysis and phylogenetic artefact identification more important than ever. Incongruence in phylogenetic reconstructions based on different datasets may be due to two major sources: biological and methodological. Biological sources comprise processes like horizontal gene transfer, hybridization and incomplete lineage sorting, while methodological ones contain falsely assigned data or violations of the assumptions of the underlying model. While the former provides interesting insights into the evolutionary history of the investigated groups, the latter should be avoided or minimized as best as possible. However, errors introduced by methodology must first be excluded or minimized to be able to conclude that biological sources are the cause. Fortunately, a variety of useful tools exist to help detect such misassignments and model violations and to apply ameliorating measurements. Still, the number of methods and their theoretical underpinning can be overwhelming and opaque. Here, we present a practical and comprehensive review of recent developments in techniques to detect artefacts arising from model violations and poorly assigned data. The advantages and disadvantages of the different methods to detect such misleading signals in phylogenetic reconstructions are also discussed. As there is no one-size-fits-all solution, this review can serve as a guide in choosing the most appropriate detection methods depending on both the actual dataset and the computational power available to the researcher. Ultimately, this informed selection will have a positive impact on the broader field, allowing us to better understand the evolutionary history of the group of interest.

nRCFV: a new, dataset-size-independent metric to quantify compositional heterogeneity in nucleotide and amino acid datasets

MOTIVATION

Compositional heterogeneity-when the proportions of nucleotides and amino acids are not broadly similar across the dataset-is a cause of a great number of phylogenetic artefacts. Whilst a variety of methods can identify it post-hoc, few metrics exist to quantify compositional heterogeneity prior to the computationally intensive task of phylogenetic tree reconstruction. Here we assess the efficacy of one such existing, widely used, metric: Relative Composition Frequency Variability (RCFV), using both real and simulated data.

RESULTS

Our results show that RCFV can be biased by sequence length, the number of taxa, and the number of possible character states within the dataset. However, we also find that missing data does not appear to have an appreciable effect on RCFV. We discuss the theory behind this, the consequences of this for the future of the usage of the RCFV value and propose a new metric, nRCFV, which accounts for these biases. Alongside this, we present a new software that calculates both RCFV and nRCFV, called nRCFV_Reader.

AVAILABILITY AND IMPLEMENTATION

nRCFV has been implemented in RCFV_Reader, available at: https://github.com/JFFleming/RCFV_Reader . Both our simulation and real data are available at Datadryad: https://doi.org/10.5061/dryad.wpzgmsbpn .