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      Renewal of planktonic foraminifera diversity after the Cretaceous Paleogene mass extinction by benthic colonizers

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          Abstract

          The biotic crisis following the end-Cretaceous asteroid impact resulted in a dramatic renewal of pelagic biodiversity. Considering the severe and immediate effect of the asteroid impact on the pelagic environment, it is remarkable that some of the most affected pelagic groups, like the planktonic foraminifera, survived at all. Here we queried a surface ocean metabarcoding dataset to show that calcareous benthic foraminifera of the clade Globothalamea are able to disperse actively in the plankton, and we show using molecular clock phylogeny that the modern planktonic clades originated from different benthic ancestors that colonized the plankton after the end-Cretaceous crisis. We conclude that the diversity of planktonic foraminifera has been the result of a constant leakage of benthic foraminifera diversity into the plankton, continuously refueling the planktonic niche, and challenge the classical interpretation of the fossil record that suggests that Mesozoic planktonic foraminifera gave rise to the modern communities.

          Abstract

          Planktonic foraminifera are key to understanding paleoclimate and plankton evolution, but their origins are unclear. Here, the authors use a molecular clock to suggest that benthic foraminifera dispersed in plankton and renew planktonic foraminifera diversity after the Cretaceous Paleogene mass extinction.

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          Most cited references48

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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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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              BLAST+: architecture and applications

              Background Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. Results We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. Conclusion The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
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                Author and article information

                Contributors
                rmorard@marum.de
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                21 November 2022
                21 November 2022
                2022
                : 13
                : 7135
                Affiliations
                [1 ]GRID grid.7704.4, ISNI 0000 0001 2297 4381, MARUM Center for Marine Environmental Sciences, , University of Bremen, ; Leobener Strasse, 28359 Bremen, Germany
                [2 ]GRID grid.423940.8, ISNI 0000 0001 2188 0463, Leibniz Institute for Baltic Sea Research Warnemünde (IOW), ; Seestrasse 15, 18119 Rostock-Warnemünde, Germany
                [3 ]GRID grid.413454.3, ISNI 0000 0001 1958 0162, Institute of Oceanology, , Polish Academy of Sciences, ; Sopot, Poland
                [4 ]GRID grid.5254.6, ISNI 0000 0001 0674 042X, Centre for GeoGenetics, Natural History Museum of Denmark, , University of Copenhagen, ; Øster Voldgade 5-7, Copenhagen, 1350K Denmark
                [5 ]52 chemin de Claret, F-05700 Serres, France
                [6 ]GRID grid.7849.2, ISNI 0000 0001 2150 7757, Université Lyon, Université Claude Bernard Lyon 1, CNRS, UMR 5023, ENTPE, , Laboratoire d’Ecologie des Hydrosystèmes Naturels et Anthropisés, ; Villeurbanne, France
                [7 ]GRID grid.440891.0, ISNI 0000 0001 1931 4817, Institut Universitaire de France, ; 103 Boulevard Saint-Michel, 75005 Paris, France
                Author information
                http://orcid.org/0000-0002-1181-5358
                http://orcid.org/0000-0003-1909-1726
                http://orcid.org/0000-0003-2416-6235
                http://orcid.org/0000-0002-8679-490X
                http://orcid.org/0000-0002-7817-9018
                Article
                34794
                10.1038/s41467-022-34794-5
                9681854
                36414628
                ad0103d2-ef0d-4af9-8e43-c5847c71f37c
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 9 February 2022
                : 8 November 2022
                Categories
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                © The Author(s) 2022

                Uncategorized
                palaeontology,palaeoecology,molecular ecology,microbial biooceanography
                Uncategorized
                palaeontology, palaeoecology, molecular ecology, microbial biooceanography

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