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Confronting sources of systematic error to resolve historically contentious relationships: a case study using gadiform fishes (Teleostei, Paracanthopterygii, Gadiformes)

Citation

Roa-Varon, Adela et al. (2021), Confronting sources of systematic error to resolve historically contentious relationships: a case study using gadiform fishes (Teleostei, Paracanthopterygii, Gadiformes), Dryad, Dataset, https://doi.org/10.5061/dryad.5qfttdz2w

Abstract

Reliable estimation of phylogeny is central to avoid inaccuracy in downstream macroevolutionary inferences. However, limitations exist in the implementation of concatenated and summary coalescent approaches, and Bayesian and full coalescent inference methods may not yet be feasible for computation of phylogeny using complicated models and large datasets. Here, we explored methodological (e.g., optimality criteria, character sampling, model selection) and biological (e.g., heterotachy, branch length heterogeneity) sources of systematic error that can result in biased or incorrect parameter estimates when reconstructing phylogeny by using the gadiform fishes as a model clade. Gadiformes include some of the most economically important fishes in the world (e.g., Cods, Hakes, and Rattails). Despite many attempts, a robust higher-level phylogenetic framework was lacking due to limited character and taxonomic sampling, particularly from several species-poor families that have been recalcitrant to phylogenetic placement. We compiled the first phylogenomic dataset, including 14,208 loci (>2.8 M bp) from 58 species representing all recognized gadiform families, to infer a time-calibrated phylogeny for the group. Data were generated with a gene-capture approach targeting coding DNA sequences from single-copy protein-coding genes. Species-tree and concatenated maximum-likelihood analyses resolved all family-level relationships within Gadiformes. While there were a few differences between topologies produced by the DNA and the amino acid datasets, most of the historically unresolved relationships among gadiform lineages were consistently well resolved with high support in our analyses regardless of the methodological and biological approaches used. However, at deeper levels, we observed inconsistency in branch support estimates between bootstrap and gene and site coefficient factors (gCF, sCF). Despite numerous short internodes, all relationships received unequivocal bootstrap support while gCF and sCF had very little support, reflecting hidden conflict across loci. Most of the gene-tree and species-tree discordance in our study is a result of short divergence times, and consequent lack of informative characters at deep levels, rather than incomplete lineage sorting (ILS). We use this phylogeny to establish a new higher-level classification of Gadiformes as a way of clarifying the evolutionary diversification of the order. We recognize 17 families in five suborders: Bregmacerotoidei, Gadoidei, Ranicipitoidei, Merluccioidei, and Macrouroidei (including two subclades). A time-calibrated analysis using 15 fossil taxa suggests that Gadiformes evolved ~79.5 million years ago (Ma) in the late Cretaceous, but that most extant lineages diverged after the Cretaceous-Paleogene (K-Pg) mass extinction (66 Ma). Our results reiterate the importance of examining phylogenomic analyses for evidence of systematic error that can emerge as a result of unsuitable modeling of biological factors and/or methodological issues, even when datasets are large and yield high support for phylogenetic relationships.

Methods

We compiled the first phylogenomic dataset, including 14,208 loci (>2.8 M bp) from 58 species representing all recognized gadiform families, to infer a time-calibrated phylogeny for the group. Data were generated with a gene-capture approach targeting coding DNA sequences from single-copy protein-coding genes. Species-tree and concatenated maximum-likelihood analyses resolved all family-level relationships within Gadiformes.

Funding

National Science Foundation, Award: NSF 1514994

National Science Foundation, Award: NSF DEB-1601433

Smithsonian Institution, Award: Predoctoral Smithsonian Fellowship