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      Gene Loss may have Shaped the Cnidarian and Bilaterian Hox and ParaHox Complement

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          Abstract

          Hox and ParaHox transcription factors are important for specifying cell fates along the primary body axes during the development of most animals. Within Cnidaria, much of the research on Hox/ParaHox genes has focused on Anthozoa (anemones and corals) and Hydrozoa (hydroids) and has concentrated on the evolution and function of cnidarian Hox genes in relation to their bilaterian counterparts. Here we analyze together the full complement of Hox and ParaHox genes from species representing all four medusozoan classes (Staurozoa, Cubozoa, Hydrozoa, and Scyphozoa) and both anthozoan classes (Octocorallia and Hexacorallia). Our results show that Hox genes involved in patterning the directive axes of anthozoan polyps are absent in the stem leading to Medusozoa. For the first time, we show spatial and temporal expression patterns of Hox and ParaHox genes in the upside-down jellyfish Cassiopea xamachana (Scyphozoa), which are consistent with diversification of medusozoan Hox genes both from anthozoans and within medusozoa. Despite unprecedented taxon sampling, our phylogenetic analyses, like previous studies, are characterized by a lack of clear homology between most cnidarian and bilaterian Hox and Hox-related genes. Unlike previous studies, we propose the hypothesis that the cnidarian–bilaterian ancestor possessed a remarkably large Hox complement and that extensive loss of Hox genes was experienced by both cnidarian and bilaterian lineages.

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          RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

          Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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            IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

            Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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              MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

              Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                Genome Biol Evol
                Genome Biol Evol
                gbe
                Genome Biology and Evolution
                Oxford University Press (US )
                1759-6653
                January 2023
                12 December 2022
                12 December 2022
                : 15
                : 1
                : evac172
                Affiliations
                Whitney Laboratory for Marine Bioscience, University of Florida , St Augustine, Florida 32080
                Department of Biology, University of Florida , Gainesville, Florida 32611
                Whitney Laboratory for Marine Bioscience, University of Florida , St Augustine, Florida 32080
                Department of Biology, University of Florida , Gainesville, Florida 32611
                Whitney Laboratory for Marine Bioscience, University of Florida , St Augustine, Florida 32080
                Department of Biology, University of Florida , Gainesville, Florida 32611
                Author notes
                Corresponding author: E-mail: joseph.ryan@ 123456whitney.ufl.edu .
                Author information
                https://orcid.org/0000-0001-7487-7225
                https://orcid.org/0000-0001-5478-0522
                Article
                evac172
                10.1093/gbe/evac172
                9825252
                36508343
                f1222f2a-ee24-4b4e-995c-d9ebd4b8a110
                © The Author(s) 2022. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 25 November 2022
                : 04 January 2023
                Page count
                Pages: 16
                Categories
                Research Article
                AcademicSubjects/SCI01130
                AcademicSubjects/SCI01140

                Genetics
                hox,homeobox,cnidarian–bilaterian ancestor,medusozoa,cassiopea xamachana
                Genetics
                hox, homeobox, cnidarian–bilaterian ancestor, medusozoa, cassiopea xamachana

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