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      Spider phylogenomics: untangling the Spider Tree of Life

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          Abstract

          Spiders (Order Araneae) are massively abundant generalist arthropod predators that are found in nearly every ecosystem on the planet and have persisted for over 380 million years. Spiders have long served as evolutionary models for studying complex mating and web spinning behaviors, key innovation and adaptive radiation hypotheses, and have been inspiration for important theories like sexual selection by female choice. Unfortunately, past major attempts to reconstruct spider phylogeny typically employing the “usual suspect” genes have been unable to produce a well-supported phylogenetic framework for the entire order. To further resolve spider evolutionary relationships we have assembled a transcriptome-based data set comprising 70 ingroup spider taxa. Using maximum likelihood and shortcut coalescence-based approaches, we analyze eight data sets, the largest of which contains 3,398 gene regions and 696,652 amino acid sites forming the largest phylogenomic analysis of spider relationships produced to date. Contrary to long held beliefs that the orb web is the crowning achievement of spider evolution, ancestral state reconstructions of web type support a phylogenetically ancient origin of the orb web, and diversification analyses show that the mostly ground-dwelling, web-less RTA clade diversified faster than orb weavers. Consistent with molecular dating estimates we report herein, this may reflect a major increase in biomass of non-flying insects during the Cretaceous Terrestrial Revolution 125–90 million years ago favoring diversification of spiders that feed on cursorial rather than flying prey. Our results also have major implications for our understanding of spider systematics. Phylogenomic analyses corroborate several well-accepted high level groupings: Opisthothele, Mygalomorphae, Atypoidina, Avicularoidea, Theraphosoidina, Araneomorphae, Entelegynae, Araneoidea, the RTA clade, Dionycha and the Lycosoidea. Alternatively, our results challenge the monophyly of Eresoidea, Orbiculariae, and Deinopoidea. The composition of the major paleocribellate and neocribellate clades, the basal divisions of Araneomorphae, appear to be falsified. Traditional Haplogynae is in need of revision, as our findings appear to support the newly conceived concept of Synspermiata. The sister pairing of filistatids with hypochilids implies that some peculiar features of each family may in fact be synapomorphic for the pair. Leptonetids now are seen as a possible sister group to the Entelegynae, illustrating possible intermediates in the evolution of the more complex entelegyne genitalic condition, spinning organs and respiratory organs.

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          Most cited references 84

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          Estimating Absolute Rates of Molecular Evolution and Divergence Times: A Penalized Likelihood Approach

           M. Sanderson (2002)
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            ASTRAL: genome-scale coalescent-based species tree estimation

            Motivation: Species trees provide insight into basic biology, including the mechanisms of evolution and how it modifies biomolecular function and structure, biodiversity and co-evolution between genes and species. Yet, gene trees often differ from species trees, creating challenges to species tree estimation. One of the most frequent causes for conflicting topologies between gene trees and species trees is incomplete lineage sorting (ILS), which is modelled by the multi-species coalescent. While many methods have been developed to estimate species trees from multiple genes, some which have statistical guarantees under the multi-species coalescent model, existing methods are too computationally intensive for use with genome-scale analyses or have been shown to have poor accuracy under some realistic conditions. Results: We present ASTRAL, a fast method for estimating species trees from multiple genes. ASTRAL is statistically consistent, can run on datasets with thousands of genes and has outstanding accuracy—improving on MP-EST and the population tree from BUCKy, two statistically consistent leading coalescent-based methods. ASTRAL is often more accurate than concatenation using maximum likelihood, except when ILS levels are low or there are too few gene trees. Availability and implementation: ASTRAL is available in open source form at https://github.com/smirarab/ASTRAL/. Datasets studied in this article are available at http://www.cs.utexas.edu/users/phylo/datasets/astral. Contact: warnow@illinois.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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              Estimating absolute rates of molecular evolution and divergence times: a penalized likelihood approach.

               J. Sanderson (2001)
              Rates of molecular evolution vary widely between lineages, but quantification of how rates change has proven difficult. Recently proposed estimation procedures have mainly adopted highly parametric approaches that model rate evolution explicitly. In this study, a semiparametric smoothing method is developed using penalized likelihood. A saturated model in which every lineage has a separate rate is combined with a roughness penalty that discourages rates from varying too much across a phylogeny. A data-driven cross-validation criterion is then used to determine an optimal level of smoothing. This criterion is based on an estimate of the average prediction error associated with pruning lineages from the tree. The methods are applied to three data sets of six genes across a sample of land plants. Optimally smoothed estimates of absolute rates entailed 2- to 10-fold variation across lineages.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                23 February 2016
                2016
                : 4
                Affiliations
                [1 ]Department of Biological Sciences and Auburn University Museum of Natural History, Auburn University , Auburn, AL, United States
                [2 ]Department of Biology, University of Vermont , Burlington, VT, United States
                [3 ]Department of Entomology, National Museum of Natural History, Smithsonian Institution , Washingtion, DC, United States
                [4 ]Arachnology, California Academy of Sciences , San Francisco, CA, United States
                [5 ]Department of Biology, San Diego State University , San Diego, CA, United States
                [6 ]Department of Biological Sciences and Alabama Museum of Natural History, University of Alabama—Tuscaloosa , Tuscaloosa, AL, United States
                [7 ]Department of Plant Biology, University of California, Davis , Davis, CA, United States
                Article
                1719
                10.7717/peerj.1719
                4768681
                26925338
                ©2016 Garrison et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                Funding
                Funded by: Auburn University and National Science Foundation grant
                Award ID: DEB 1256139
                This work was partially funded by Auburn University and National Science Foundation grant DEB 1256139. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Evolutionary Studies
                Taxonomy
                Zoology

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