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      New skulls and skeletons of the Cretaceous legged snake Najash, and the evolution of the modern snake body plan

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          Abstract

          New fossils from the legged snake Najash reveal the evolutionary origins of key features of the modern snake skull and body.

          Abstract

          Snakes represent one of the most dramatic examples of the evolutionary versatility of the vertebrate body plan, including body elongation, limb loss, and skull kinesis. However, understanding the earliest steps toward the acquisition of these remarkable adaptations is hampered by the very limited fossil record of early snakes. Here, we shed light on the acquisition of the snake body plan using micro–computed tomography scans of the first three-dimensionally preserved skulls of the legged snake Najash and a new phylogenetic hypothesis. These findings elucidate the initial sequence of bone loss that gave origin to the modern snake skull. Morphological and molecular analyses including the new cranial data provide robust support for an extensive basal radiation of early snakes with hindlimbs and pelves, demonstrating that this intermediate morphology was not merely a transient phase between limbed and limbless body plans.

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          A general comparison of relaxed molecular clock models.

          Several models have been proposed to relax the molecular clock in order to estimate divergence times. However, it is unclear which model has the best fit to real data and should therefore be used to perform molecular dating. In particular, we do not know whether rate autocorrelation should be considered or which prior on divergence times should be used. In this work, we propose a general bench mark of alternative relaxed clock models. We have reimplemented most of the already existing models, including the popular lognormal model, as well as various prior choices for divergence times (birth-death, Dirichlet, uniform), in a common Bayesian statistical framework. We also propose a new autocorrelated model, called the "CIR" process, with well-defined stationary properties. We assess the relative fitness of these models and priors, when applied to 3 different protein data sets from eukaryotes, vertebrates, and mammals, by computing Bayes factors using a numerical method called thermodynamic integration. We find that the 2 autocorrelated models, CIR and lognormal, have a similar fit and clearly outperform uncorrelated models on all 3 data sets. In contrast, the optimal choice for the divergence time prior is more dependent on the data investigated. Altogether, our results provide useful guidelines for model choice in the field of molecular dating while opening the way to more extensive model comparisons.
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            Total-Evidence Dating under the Fossilized Birth–Death Process

            Bayesian total-evidence dating involves the simultaneous analysis of morphological data from the fossil record and morphological and sequence data from recent organisms, and it accommodates the uncertainty in the placement of fossils while dating the phylogenetic tree. Due to the flexibility of the Bayesian approach, total-evidence dating can also incorporate additional sources of information. Here, we take advantage of this and expand the analysis to include information about fossilization and sampling processes. Our work is based on the recently described fossilized birth–death (FBD) process, which has been used to model speciation, extinction, and fossilization rates that can vary over time in a piecewise manner. So far, sampling of extant and fossil taxa has been assumed to be either complete or uniformly at random, an assumption which is only valid for a minority of data sets. We therefore extend the FBD process to accommodate diversified sampling of extant taxa, which is standard practice in studies of higher-level taxa. We verify the implementation using simulations and apply it to the early radiation of Hymenoptera (wasps, ants, and bees). Previous total-evidence dating analyses of this data set were based on a simple uniform tree prior and dated the initial radiation of extant Hymenoptera to the late Carboniferous (309 Ma). The analyses using the FBD prior under diversified sampling, however, date the radiation to the Triassic and Permian (252 Ma), slightly older than the age of the oldest hymenopteran fossils. By exploring a variety of FBD model assumptions, we show that it is mainly the accommodation of diversified sampling that causes the push toward more recent divergence times. Accounting for diversified sampling thus has the potential to close the long-discussed gap between rocks and clocks. We conclude that the explicit modeling of fossilization and sampling processes can improve divergence time estimates, but only if all important model aspects, including sampling biases, are adequately addressed.
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              Integrated Analyses Resolve Conflicts over Squamate Reptile Phylogeny and Reveal Unexpected Placements for Fossil Taxa

              Squamate reptiles (lizards and snakes) are a pivotal group whose relationships have become increasingly controversial. Squamates include >9000 species, making them the second largest group of terrestrial vertebrates. They are important medicinally and as model systems for ecological and evolutionary research. However, studies of squamate biology are hindered by uncertainty over their relationships, and some consider squamate phylogeny unresolved, given recent conflicts between molecular and morphological results. To resolve these conflicts, we expand existing morphological and molecular datasets for squamates (691 morphological characters and 46 genes, for 161 living and 49 fossil taxa, including a new set of 81 morphological characters and adding two genes from published studies) and perform integrated analyses. Our results resolve higher-level relationships as indicated by molecular analyses, and reveal hidden morphological support for the molecular hypothesis (but not vice-versa). Furthermore, we find that integrating molecular, morphological, and paleontological data leads to surprising placements for two major fossil clades (Mosasauria and Polyglyphanodontia). These results further demonstrate the importance of combining fossil and molecular information, and the potential problems of estimating the placement of fossil taxa from morphological data alone. Thus, our results caution against estimating fossil relationships without considering relevant molecular data, and against placing fossils into molecular trees (e.g. for dating analyses) without considering the possible impact of molecular data on their placement.
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                Author and article information

                Journal
                Sci Adv
                Sci Adv
                SciAdv
                advances
                Science Advances
                American Association for the Advancement of Science
                2375-2548
                November 2019
                20 November 2019
                : 5
                : 11
                : eaax5833
                Affiliations
                [1 ]CONICET, Área de Paleontología, Fundación de Historia Natural Félix de Azara, CEBBAD, Universidad Maimónides, Hidalgo 775, 1405 Buenos Aires, Argentina.
                [2 ]Department of Biological Sciences, University of Alberta, Edmonton, Alberta T6G 2E9, Canada.
                [3 ]College of Science and Engineering, Flinders University, Adelaide, SA 5042, Australia.
                [4 ]Earth Sciences Section, South Australian Museum, North Terrace, Adelaide, SA 5000, Australia.
                [5 ]CONICET, Departamento de Biodiversidad y Biología Experimental/Departamento de Ciencias Geológicas, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, 1428 Buenos Aires, Argentina.
                [6 ]Arizona College of Osteopathic Medicine, Midwestern University, 19555 N. 59th Ave., Glendale, AZ 85383, USA.
                [7 ]Redpath Museum, McGill University, 859 Sherbrooke Street W., Montreal, Quebec H3A 0C4, Canada.
                [8 ]Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, Alberta T6G 2E9, Canada.
                Author notes
                [* ]Corresponding author. Email: fernando.garberoglio@ 123456fundacionazara.org.ar
                [†]

                Present address: Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA.

                Author information
                http://orcid.org/0000-0003-1896-1830
                http://orcid.org/0000-0002-0414-0524
                http://orcid.org/0000-0003-4716-649X
                http://orcid.org/0000-0002-9312-0559
                http://orcid.org/0000-0002-6600-3787
                http://orcid.org/0000-0002-2186-0216
                http://orcid.org/0000-0002-3905-0887
                Article
                aax5833
                10.1126/sciadv.aax5833
                6867888
                31799393
                c0efc292-3472-49c6-afde-30424f69aed7
                Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

                History
                : 04 April 2019
                : 25 September 2019
                Funding
                Funded by: doi http://dx.doi.org/10.13039/100006363, National Geographic Society;
                Award ID: #8826-10
                Funded by: doi http://dx.doi.org/10.13039/100006363, National Geographic Society;
                Award ID: #9300-13
                Funded by: doi http://dx.doi.org/10.13039/501100000923, Australian Research Council;
                Award ID: DP160103005
                Funded by: NSERC Discovery Grant;
                Award ID: #234538
                Funded by: FONCYT;
                Award ID: PICT N°2010-0564
                Funded by: Canadian Foundation of Innovation;
                Award ID: 33122
                Categories
                Research Article
                Research Articles
                SciAdv r-articles
                Evolutionary Biology
                Evolutionary Biology
                Custom metadata
                Anne Suarez

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