We introduce Operational Genomic Unit (OGU), a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent from taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldomly applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in one synthetic and two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome datasets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project dataset, and more accurate prediction of human age by the gut microbiomes in the Finnish population. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate OGU adoption in future metagenomics studies.
Importance Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. However, current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution compared to 16S rRNA amplicon sequence variant analysis. To solve these challenges, we introduce Operational Genomic Units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition while (ii) permitting use of phylogeny-aware tools. Our analysis of real-world datasets shows several advantages over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGU as standard practice in metagenomic studies.
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A simple hierarchical model for heterogeneity in the evolutionary correlation on a phylogenetic tree
Numerous questions in phylogenetic comparative biology revolve around the correlated evolution of two or more phenotypic traits on a phylogeny. In many cases, it may be sufficient to assume a constant value for the evolutionary correlation between characters across all the clades and branches of the tree. Under other circumstances, however, it is desirable or necessary to account for the possibility that the evolutionary correlation differs through time or in different sections of the phylogeny. Here, we present a method designed to fit a hierarchical series of models for heterogeneity in the evolutionary rates and correlation of two quantitative traits on a phylogenetic tree. We apply the method to two datasets: one for different attributes of the buccal morphology in sunfishes (Centrarchidae); and a second for overall body length and relative body depth in rock- and non-rock-dwelling South American iguanian lizards. We also examine the performance of the method for parameter estimation and model selection using a small set of numerical simulations.
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- Award ID(s):
- 1759940
- NSF-PAR ID:
- 10391207
- Date Published:
- Journal Name:
- PeerJ
- Volume:
- 10
- ISSN:
- 2167-8359
- Page Range / eLocation ID:
- e13910
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract In the last decade and a half, advances in genetic sequencing technologies have revolutionized systematics, transforming the field from studying morphological characters or a few genetic markers, to genomic datasets in the phylogenomic era. A plethora of molecular phylogenetic studies on many taxonomic groups have come about, converging on, or refuting prevailing morphology or legacy‐marker‐based hypotheses about evolutionary affinities. Spider systematics has been no exception to this transformation and the inter‐relationships of several groups have now been studied using genomic data. About 51 500 extant spider species have been described, all with a conservative body plan, but innumerable morphological and behavioural peculiarities. Inferring the spider tree of life using morphological data has been a challenging task. Molecular data have corroborated many hypotheses of higher‐level relationships, but also resulted in new groups that refute previous hypotheses. In this review, we discuss recent advances in the reconstruction of the spider tree of life and highlight areas where additional effort is needed with potential solutions. We base this review on the most comprehensive spider phylogeny to date, representing 131 of the 132 spider families. To achieve this sampling, we combined six Sanger‐based markers with newly generated and publicly available genome‐scale datasets. We find that some inferred relationships between major lineages of spiders (such as Austrochiloidea, Palpimanoidea and Synspermiata) are robust across different classes of data. However, several new hypotheses have emerged with different classes of molecular data. We identify and discuss the robust and controversial hypotheses and compile this blueprint to design future studies targeting systematic revisions of these problematic groups. We offer an evolutionary framework to explore comparative questions such as evolution of venoms, silk, webs, morphological traits and reproductive strategies.
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Abstract Aim Closely related species tend to resemble each other in their morphology and ecology because of shared ancestry. When exploring correlations between species traits, therefore, species cannot be treated as statistically independent. Phylogenetic comparative methods (PCMs) attempt to correct statistically for this shared evolutionary history. Almost all such approaches, however, assume that correlations between traits are constant across the tips of the tree, which we refer to as phylogenetic stationarity. We suggest that this assumption of phylogenetic stationarity might be often violated and that relationships between species traits might evolve alongside clades, for example, owing to the effects of unmeasured traits or other latent variables. Specific examples range from shifts in allometric scaling relationships between clades (e.g., basal metabolic rate and body mass in endotherms, and tree diameter and biomass in trees) to the differing relationship between leaf mass per area and shade tolerance in deciduous versus evergreen trees and shrubs.
Innovation Here, we introduce an exploratory modelling framework, phylogenetically weighted regression, which represents an extension of geographically weighted regression (GWR) used in spatial studies, to allow non‐stationarity in model parameters across a phylogenetic tree. We demonstrate our approach using empirical data on flowering time and seed mass from a well‐studied plant community in southeastern Sweden. Our model reveals strong, diverging trends across the phylogeny, including changes in the sign of the relationship between clades.
Main conclusions By allowing for phylogenetic non‐stationarity, we are able to detect shifting relationships among species traits that would be obscured in traditional PCMs; thus, we suggest that PWR might be an important exploratory tool in the search for key missing variables in comparative analyses.
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Abstract The evolutionary history of archosaurs and their closest relatives is characterized by a wide diversity of locomotor modes, which has even been suggested as a pivotal aspect underlying the evolutionary success of dinosaurs vs. pseudosuchians across the Triassic–Jurassic transition. This locomotor diversity (e.g., more sprawling/erect; crouched/upright; quadrupedal/bipedal) led to several morphofunctional specializations of archosauriform limb bones that have been studied qualitatively as well as quantitatively through various linear morphometric studies. However, differences in locomotor habits have never been studied across the Triassic–Jurassic transition using 3D geometric morphometrics, which can relate how morphological features vary according to biological factors such as locomotor habit and body mass. Herein, we investigate morphological variation across a dataset of 72 femora from 36 different species of archosauriforms. First, we identify femoral head rotation, distal slope of the fourth trochanter, femoral curvature, and the angle between the lateral condyle and crista tibiofibularis as the main features varying between bipedal and quadrupedal taxa, all of these traits having a stronger locomotor signal than the lesser trochanter's proximal extent. We show a significant association between locomotor mode and phylogeny, but with the locomotor signal being stronger than the phylogenetic signal. This enables us to predict locomotor modes of some of the more ambiguous early archosauriforms without relying on the relationships between hindlimb and forelimb linear bone dimensions as in prior studies. Second, we highlight that the most important morphological variation is linked to the increase of body size, which impacts the width of the epiphyses and the roundness and proximodistal position of the fourth trochanter. Furthermore, we show that bipedal and quadrupedal archosauriforms have different allometric trajectories along the morphological variation in relation to body size. Finally, we demonstrate a covariation between locomotor mode and body size, with variations in femoral bowing (anteroposterior curvature) being more distinct among robust femora than gracile ones. We also identify a decoupling in fourth trochanter variation between locomotor mode (symmetrical to semi‐pendant) and body size (sharp to rounded). Our results indicate a similar level of morphological disparity linked to a clear convergence in femoral robusticity between the two clades of archosauriforms (Pseudosuchia and Avemetatarsalia), emphasizing the importance of accounting for body size when studying their evolutionary history, as well as when studying the functional morphology of appendicular features. Determining how early archosauriform skeletal features were impacted by locomotor habits and body size also enables us to discuss the potential homoplasy of some phylogenetic characters used previously in cladistic analyses as well as when bipedalism evolved in the avemetatarsalian lineage. This study illuminates how the evolution of femoral morphology in early archosauriforms was functionally constrained by locomotor habit and body size, which should aid ongoing discussions about the early evolution of dinosaurs and the nature of their evolutionary “success” over pseudosuchians.
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null (Ed.)Abstract Stochastic models of character trait evolution have become a cornerstone of evolutionary biology in an array of contexts. While probabilistic models have been used extensively for statistical inference, they have largely been ignored for the purpose of measuring distances between phylogeny-aware models. Recent contributions to the problem of phylogenetic distance computation have highlighted the importance of explicitly considering evolutionary model parameters and their impacts on molecular sequence data when quantifying dissimilarity between trees. By comparing two phylogenies in terms of their induced probability distributions that are functions of many model parameters, these distances can be more informative than traditional approaches that rely strictly on differences in topology or branch lengths alone. Currently, however, these approaches are designed for comparing models of nucleotide substitution and gene tree distributions, and thus, are unable to address other classes of traits and associated models that may be of interest to evolutionary biologists. Here we expand the principles of probabilistic phylogenetic distances to compute tree distances under models of continuous trait evolution along a phylogeny. By explicitly considering both the degree of relatedness among species and the evolutionary processes that collectively give rise to character traits, these distances provide a foundation for comparing models and their predictions, and for quantifying the impacts of assuming one phylogenetic background over another while studying the evolution of a particular trait. We demonstrate the properties of these approaches using theory, simulations, and several empirical datasets that highlight potential uses of probabilistic distances in many scenarios. We also introduce an open-source R package named PRDATR for easy application by the scientific community for computing phylogenetic distances under models of character trait evolution.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.7717/peerj.13910
