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Data Curation and Modeling of Compositional Heterogeneity In Molecular Phylogenetics and Evolution 147 (2020) 106782 Contents lists available at ScienceDirect Molecular Phylogenetics and Evolution journal homepage: www.elsevier.com/locate/ympev Data curation and modeling of compositional heterogeneity in insect T phylogenomics: A case study of the phylogeny of Dytiscoidea (Coleoptera: Adephaga) ⁎ ⁎ Chenyang Caia,b, , Erik Tihelkac, Davide Pisanib,d, Philip C.J. Donoghueb, a State Key Laboratory of Palaeobiology and Stratigraphy, Nanjing Institute of Geology and Palaeontology, and Centre for Excellence in Life and Paleoenvironment, Chinese Academy of Sciences, Nanjing 210008, China b School of Earth Sciences, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol BS8 1TQ, UK c Department of Animal Science, Hartpury College, Hartpury GL19 3BE, UK d School of Biological Sciences, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol BS8 1TQ, UK ARTICLE INFO ABSTRACT Keywords: Diving beetles and their allies are an almost ubiquitous group of freshwater predators. Knowledge of the phy- Hydradephaga logeny of the adephagan superfamily Dytiscoidea has significantly improved since the advent of molecular Hygrobiidae phylogenetics. However, despite recent comprehensive phylogenomic studies, some phylogenetic relationships Transcriptomics among the constituent families remain elusive. In particular, the position of the family Hygrobiidae remains Compositional heterogeneity uncertain. We address these issues by re-analyzing recently published phylogenomic datasets for Dytiscoidea, Site-heterogeneous model using approaches to reduce compositional heterogeneity and adopting a site-heterogeneous mixture model. We obtained a consistent, well-resolved, and strongly supported tree. Consistent with previous studies, our analyses support Aspidytidae as the monophyletic sister group of Amphizoidae, and more importantly, Hygrobiidae as the sister of the diverse Dytiscidae, in agreement with morphology-based phylogenies. Our analyses provide a backbone phylogeny of Dytiscoidea, which lays the foundation for better understanding the evolution of mor- phological characters, life habits, and feeding behaviors of dytiscoid beetles. 1. Introduction questioned by recent phylogenomic studies (Pauli et al., 2018; Ding et al., 2019; Hamilton et al., 2019; McKenna et al., 2019; Tang et al., Just like many other fields of biology, entomology has experienced a 2019; Wang et al., 2019; Winterton et al., 2019). It is remains unclear to true genomic revolution in the past few decades (Cameron, 2014; what extent these inconsistencies between traditional and phylogen- Behura, 2015; Kjer et al., 2016a; Johnson, 2019). While the first omically-derived hypotheses represent progress in elucidating insect Sanger-era molecular phylogeny of insects only analyzed 18S sequences phylogeny and to what extent they are the result of factors confounding and restriction sites for 12 species (Wheeler, 1989), the most recent the reliable reconstruction of phylogenetic relationships (Borowiec insect super tree included 440 transcriptomes, 1,490 mitogenomes, and et al., 2019; Cai et al., 2019). DNA barcodes for some 69,000 species (Chesters, 2019). However, One of the key sources of uncertainty and error in inferring phylo- despite the almost exponential increase in sequence data, this growth genies is compositional and rate heterogeneity (Bleidorn, 2017). Some has not been matched by a growing consensus over insect phylogeny. of the most popular inference methods used in phylogenomics operate Many old controversies in insect evolution remain unresolved, such as under the assumption that the rate of evolutionary change is equal for the relationships among the earliest-branching endognathous orders, every position of a sequence alignment (Sheffield et al., 2009). How- early-branching winged insects (the ‘Palaeoptera problem’), and the ever, this assumption is unrealistic and does not reflect the high com- phylogenetic position of highly specialized parasites such as fleas (Kjer positional and rate heterogeneity observed in metazoan genomes et al., 2016b; Misof et al., 2014; Beutel et al., 2017; Johnson et al., (Lartillot and Philippe, 2008); not only does mutation rate vary among 2018; Simon et al., 2018; Wipfler et al., 2019). Likewise, the mono- bases (Hodgkinson and Eyre-Walker, 2011), but different parts of the phyly and position of numerous traditionally well-defined taxa has been genome are under selection pressures of different intensities (Xing and ⁎ Corresponding authors at: State Key Laboratory of Palaeobiology and Stratigraphy, Nanjing Institute of Geology and Palaeontology, and Centre for Excellence in Life and Paleoenvironment, Chinese Academy of Sciences, Nanjing 210008, China (C. Cai). E-mail addresses: [email protected] (C. Cai), [email protected] (P.C.J. Donoghue). https://doi.org/10.1016/j.ympev.2020.106782 Received 3 February 2020; Accepted 26 February 2020 Available online 05 March 2020 1055-7903/ © 2020 Elsevier Inc. All rights reserved. C. Cai, et al. Molecular Phylogenetics and Evolution 147 (2020) 106782 Lee, 2006), typically resulting in a highly unequal evolutionary rate prothoracic glands (Beutel, 1986, 1988). across any given sequence. Models which assume compositional and To understand the systematic position of Hygrobiidae and the rate homogeneity can consistently recover incorrect topologies, albeit backbone phylogeny of Dytiscoidea, we re-analyzed the recently pub- often with high statistical support (Ho and Jermiin, 2004; Jermiin et al., lished phylogenomic data for Dytiscoidea of Vasilikopoulos et al. 2004; Cox et al., 2008; Sheffield et al., 2009). To combat these pro- (2019) using a site-heterogeneous mixture model (CAT-GTR + G in blems, an arsenal of methods has been developed to reduce site com- PhyloBayes). We also investigated the effects of different approaches of positional heterogeneity in datasets, such as various data filtering and reducing compositional heterogeneity of the datasets by the data block data recoding approaches (Bleidorn, 2017). Moreover, some recent mapping and gathering using entropy (BMGE) method. complex site-heterogeneous models can account for both compositional and rate heterogeneity across sites. These models, such as CAT- 2. Materials and methods GTR + G, have been shown to fit real data better than conventional site-homogeneous models and suppress common sources of phyloge- 2.1. Dataset selection netic error such as long branch attraction (Lartillot et al., 2007; Blanquart and Lartillot, 2008; Wang et al., 2008; Foster et al., 2009). We used the amino acid transcriptome alignments from When reanalyzed using these approaches, some of the most con- Vasilikopoulos et al. (2019). The authors produced and analyzed dif- troversial debates in evolutionary biology today such as the origin of ferent variants of nucleotide and amino acid alignments of their data. eukaryotes and metazoans seem to boil down to problems caused by Among the eleven amino-acid supermatrices they generated, their focal compositional and/or rate heterogeneity (Cox et al., 2008; Feuda et al., analyses were principally based upon the full dataset (Supermatrix A: 2017; Pisani et al., 2015; Puttick et al., 2018; Tarver et al., 2016; 14 taxa, 1,661,023 amino-acid sites) and two datasets reduced to in- Williams et al., 2020). crease data coverage and phylogenetic information (Supermatrix E: 14 The adephagan superfamily Dytiscoidea (Amphizoidae, Aspidytidae, taxa, 948,772 amino-acid sites) and diminish the negative effects of Dytiscidae, Hygrobiidae, Meruidae, and Noteridae) is a well-established among-species compositional heterogeneity (Supermatrix H: 14 taxa, group of beetles (e.g. Baca et al., 2017; Beutel et al., 2013; Dressler et al., 211,275 amino-acid sites) (Vasilikopoulos et al., 2019). Here we fo- 2011; but see López-López and Vogler, 2017). Dytiscoid species occur in cused on the same three supermatrices download from MENDELEY diverse freshwater habitats, including springs, rivers, acidic swamps, DATA (https://doi.org/10.17632/j8xwxdtbyb.1) to test hypotheses lakes, and even in hypersaline and hygropetric habitats. Bell (1966) about the back bone phylogeny of Dytiscoidea. suggested a clade, Dytiscoidea, comprising aquatic (or semi-aquatic) fa- To reduce among-site compositional heterogeneity and ease the milies such as Noteridae, Amphizoidae, Hygrobiidae, and Dytiscidae. The convergence of runs, we used data block mapping and gathering using monophyly of Dytiscoidea has been confirmed in many phylogenetic entropy (BMGE). BMGE identifies phylogenetically informative sites by analyses of morphological characters (Beutel and Haas, 1996; Beutel, computing entropy-like scores weighted with BLOSUM similarity ma- 1998; Beutel and Haas, 2000) as well as analyses of molecular data trices in order to distinguish among biologically expected and un- (Ribera et al., 2002a,b; McKenna et al., 2015). expected variability for each aligned character (Criscuolo and Gribaldo, Although the phylogenetic relationships of dytiscoids have been 2010). BMGE can select characters associated with a score value below extensively investigated based on morphology, gland chemical com- a fixed threshold. We prepared four stringently filtered datasets (Su- pounds, fossils, and molecular data (e.g. Alarie et al., 2011; Alarie and permatrices A′, A″, E′ and H′) by trimming the previously published Bilton, 2005; Baca et al., 2017; Balke et al., 2008; Beutel et al., 2006, supermatrices A, E
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