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      Primate phylogenomics uncovers multiple rapid radiations and ancient interspecific introgression

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          Abstract

          Our understanding of the evolutionary history of primates is undergoing continual revision due to ongoing genome sequencing efforts. Bolstered by growing fossil evidence, these data have led to increased acceptance of once controversial hypotheses regarding phylogenetic relationships, hybridization and introgression, and the biogeographical history of primate groups. Among these findings is a pattern of recent introgression between species within all major primate groups examined to date, though little is known about introgression deeper in time. To address this and other phylogenetic questions, here, we present new reference genome assemblies for 3 Old World monkey (OWM) species: Colobus angolensis ssp. palliatus (the black and white colobus), Macaca nemestrina (southern pig-tailed macaque), and Mandrillus leucophaeus (the drill). We combine these data with 23 additional primate genomes to estimate both the species tree and individual gene trees using thousands of loci. While our species tree is largely consistent with previous phylogenetic hypotheses, the gene trees reveal high levels of genealogical discordance associated with multiple primate radiations. We use strongly asymmetric patterns of gene tree discordance around specific branches to identify multiple instances of introgression between ancestral primate lineages. In addition, we exploit recent fossil evidence to perform fossil-calibrated molecular dating analyses across the tree. Taken together, our genome-wide data help to resolve multiple contentious sets of relationships among primates, while also providing insight into the biological processes and technical artifacts that led to the disagreements in the first place.

          Abstract

          Combining three newly sequenced primate genomes with other published genomes, this study adapts a little-known method for detecting ancient introgression to genome-scale data, revealing multiple previously unknown examples of hybridization between primate species.

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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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            Basic local alignment search tool.

            A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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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
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: MethodologyRole: Software
                Role: Methodology
                Role: Data curationRole: Resources
                Role: Data curationRole: Resources
                Role: Data curationRole: Resources
                Role: Data curationRole: Resources
                Role: Data curationRole: Resources
                Role: Data curationRole: Resources
                Role: MethodologyRole: Software
                Role: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Biol
                PLoS Biol
                plos
                plosbiol
                PLoS Biology
                Public Library of Science (San Francisco, CA USA )
                1544-9173
                1545-7885
                3 December 2020
                December 2020
                3 December 2020
                : 18
                : 12
                : e3000954
                Affiliations
                [1 ] Department of Biology and Department of Computer Science, Indiana University, Bloomington, Indiana, United States of America
                [2 ] Research School of Computer Science, Australian National University, Canberra, Australian Capital Territory, Australia
                [3 ] Research School of Biology, Australian National University, Canberra, Australian Capital Territory, Australia
                [4 ] Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, United States of America
                [5 ] Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America
                [6 ] Department of Computer Science and Software Engineering and Department of Biology and Biomedical Engineering, Rose-Hulman Institute of Technology, Terre Haute, Indiana, United States of America
                University of Cambridge, UNITED KINGDOM
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-6856-5636
                https://orcid.org/0000-0002-1140-2596
                https://orcid.org/0000-0002-7333-4752
                https://orcid.org/0000-0001-6185-4059
                https://orcid.org/0000-0002-4651-3704
                https://orcid.org/0000-0001-9732-0964
                https://orcid.org/0000-0002-0282-1000
                https://orcid.org/0000-0002-7374-6490
                https://orcid.org/0000-0002-5731-8808
                Article
                PBIOLOGY-D-20-01019
                10.1371/journal.pbio.3000954
                7738166
                33270638
                b3e2a4b2-55fe-452b-9ccc-a25ce858759a
                © 2020 Vanderpool et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 April 2020
                : 2 November 2020
                Page count
                Figures: 4, Tables: 2, Pages: 27
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100008982, National Science Foundation;
                Award ID: DBI-1564611
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100008982, National Science Foundation;
                Award ID: DEB-1936187
                Award Recipient :
                Funded by: Chan-Zuckerberg Initiative grant for Essential Open Source Software for Science
                Award Recipient :
                Funded by: Chan-Zuckerberg Initiative grant for Essential Open Source Software for Science
                Award Recipient :
                Funded by: Australian Research Council
                Award ID: DP-200103151
                Award Recipient :
                Funded by: Australian Research Council
                Award ID: DP-200103151
                Award Recipient :
                Funded by: Australian Research Council
                Award ID: DP-200103151
                Award Recipient :
                Funded by: Australian National University Futures Grant
                Award Recipient :
                Funding for this study was provided by grants from the National Science Foundation, grant numbers: DBI-1564611 and DEB-1936187 awarded to M.W.H. Salary was provided to D.V. and M.W.H by grant number: DBI-1564611. Additional salary was provided to M.W.H by grant number: DEB-1936187. The authors received no specific funding for this work. Additional funding was provided by the Chan-Zuckerberg Initiative grant for Essential Open Source Software for Science ( https://chanzuckerberg.com/eoss/) awarded to B.Q.M. and R.L. The authors received no specific funding for this work. Additional funding was provided by the Australian Research Council under grant number: DP-200103151 awarded to R.L., B.Q.M., and M.W.H. The authors received no specific funding for this work. Additional funding was provided by a Australian National University ( https://www.anu.edu.au/) Futures grant awarded to R.L, which paid salary for B.Q.M. The sequencing and assembly of the colobus, pig-tailed macaque, and drill genomes was funded by National Institutes of Health grant number: U54-HG006484 awarded to R.G. Salaries from this award were received by R.G., J.R., K.W., S.M., D.H., and D.M. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Biology and Life Sciences
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Computer and Information Sciences
                Data Management
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Primates
                Biology and Life Sciences
                Zoology
                Animals
                Vertebrates
                Amniotes
                Mammals
                Primates
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Processes
                Introgression
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Sequence Alignment
                Biology and Life Sciences
                Genetics
                Genomics
                Animal Genomics
                Mammalian Genomics
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Systematics
                Phylogenetics
                Animal Phylogenetics
                Biology and Life Sciences
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Animal Phylogenetics
                Computer and Information Sciences
                Data Management
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Animal Phylogenetics
                Biology and Life Sciences
                Zoology
                Animal Phylogenetics
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Genome Annotation
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Genome Annotation
                Custom metadata
                vor-update-to-uncorrected-proof
                2020-12-15
                The relevant assembly accessions and associated references used in this study are provided in S1 Table. All raw data, assemblies, and annotation information used in theses analyses are available through each species’ NCBI BioProject link available in the relevant assembly accessions and associated references used in this study are provided in S1 Table. The Data Dryad repository associated with this study can be accessed through the following link: https://doi.org/10.5061/dryad.rfj6q577d [ 22]. The repository contains the following files and archives: • 1730_ALIGNMENT_CONCAT.paup.nex – Concatenated alignment with PAUP block of commands used to generate the parsimony concatenated tree. • 1730_Alignments_FINAL.tar.gz: 1,730 single-copy ortholog alignments. • 1730_ML_GENETREEs.treefile: Maximum likelihood gene trees estimated from from the 1,730 ortholog alignments. • ASTRAL_Tree_AVGdates.tre: The ASTRAL topology ( Fig 1) with average dates from 10 independent datasets. • All_Dating_Datasets_DRYAD.tar.gz: The concatenated alignments used for dating analyses. • PARSIMONY_1730_Gene_Trees.tre: All 1,730 parsimony gene trees fro MPBoot. • Supp_fig4A_F_s6_b1_v2_1.slim-SLiM3 recipe for S4A Fig simulation • Supp_fig4B_F_s6_b1_v2_highmut_1.slim- SLiM3 recipe for S4B Fig simulation • All_1735_UNALIGNED_Seqs.tar.gz: All unaligned single-copy gene sequences. • plot_DATING.R: R script used for plotting Fig 3.

                Life sciences
                Life sciences

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