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      A customized nuclear target enrichment approach for developing a phylogenomic baseline for Dioscorea yams (Dioscoreaceae)

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          Abstract

          Premise

          We developed a target enrichment panel for phylogenomic studies of Dioscorea, an economically important genus with incompletely resolved relationships.

          Methods

          Our bait panel comprises 260 low‐ to single‐copy nuclear genes targeted to work in Dioscorea, assessed here using a preliminary taxon sampling that includes both distantly and closely related taxa, including several yam crops and potential crop wild relatives. We applied coalescent‐based and maximum likelihood phylogenomic inference approaches to the pilot taxon set, incorporating new and published transcriptome data from additional species.

          Results

          The custom panel retrieved ~94% of targets and >80% of full gene length from 88% and 68% of samples, respectively. It has minimal gene overlap with existing panels designed for angiosperm‐wide studies and generally recovers longer and more variable targets. Pilot phylogenomic analyses consistently resolve most deep and recent relationships with strong support across analyses and point to revised relationships between the crop species D. alata and candidate crop wild relatives.

          Discussion

          Our customized panel reliably retrieves targeted loci from Dioscorea, is informative for resolving relationships in denser samplings, and is suitable for refining our understanding of the independent origins of cultivated yam species; the panel likely has broader promise for phylogenomic studies across Dioscoreales.

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          Most cited references52

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          SequenceMatrix: concatenation software for the fast assembly of multi-gene datasets with character set and codon information

          We present SequenceMatrix, software that is designed to facilitate the assembly and analysis of multi-gene datasets. Genes are concatenated by dragging and dropping FASTA, NEXUS, or TNT files with aligned sequences into the program window. A multi-gene dataset is concatenated and displayed in a spreadsheet; each sequence is represented by a cell that provides information on sequence length, number of indels, the number of ambiguous bases ("Ns"), and the availability of codon information. Alternatively, GenBank numbers for the sequences can be displayed and exported. Matrices with hundreds of genes and taxa can be concatenated within minutes and exported in TNT, NEXUS, or PHYLIP formats, preserving both character set and codon information for TNT and NEXUS files. SequenceMatrix also creates taxon sets listing taxa with a minimum number of characters or gene fragments, which helps assess preliminary datasets. Entire taxa, whole gene fragments, or individual sequences for a particular gene and species can be excluded from export. Data matrices can be re-split into their component genes and the gene fragments can be exported as individual gene files. SequenceMatrix also includes two tools that help to identify sequences that may have been compromised through laboratory contamination or data management error. One tool lists identical or near-identical sequences within genes, while the other compares the pairwise distance pattern of one gene against the pattern for all remaining genes combined. SequenceMatrix is Java-based and compatible with the Microsoft Windows, Apple MacOS X and Linux operating systems. The software is freely available from http://code.google.com/p/sequencematrix/. © The Willi Hennig Society 2010.
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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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              Fast Coalescent-Based Computation of Local Branch Support from Quartet Frequencies

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                Author and article information

                Contributors
                marybel.soto@botany.ubc.ca
                Journal
                Appl Plant Sci
                Appl Plant Sci
                10.1002/(ISSN)2168-0450
                APS3
                Applications in Plant Sciences
                John Wiley and Sons Inc. (Hoboken )
                2168-0450
                13 June 2019
                June 2019
                : 7
                : 6 ( doiID: 10.1002/aps3.2019.7.issue-6 )
                : e11254
                Affiliations
                [ 1 ] Department of Botany University of British Columbia 6270 University Boulevard Vancouver British Columbia V6T 1Z4 Canada
                [ 2 ] UBC Botanical Garden and Centre for Plant Research University of British Columbia 6804 Marine Drive SW Vancouver British Columbia V6T 1Z4 Canada
                [ 3 ] Royal Botanic Gardens Kew, Richmond Surrey TW9 3DS United Kingdom
                [ 4 ] Department of Tropical Plant and Soil Sciences University of Hawai‘i at Manoa Honolulu Hawai‘i 96822 USA
                [ 5 ] Naturalis Biodiversity Center Endless Forms Sylviusweg 72 Leiden 2333 BE The Netherlands
                [ 6 ] Institute Biology Leiden Leiden University Sylviusweg 72 Leiden 2333 BE The Netherlands
                [ 7 ] Faculty of Science and Technology University of Applied Sciences Leiden Zernikedreef 11 Leiden 2333 CK The Netherlands
                Author notes
                [*] [* ]Author for correspondence: marybel.soto@ 123456botany.ubc.ca
                Author information
                https://orcid.org/0000-0003-1812-7416
                https://orcid.org/0000-0002-2478-8555
                https://orcid.org/0000-0001-5542-0975
                https://orcid.org/0000-0002-2004-433X
                https://orcid.org/0000-0002-3837-8186
                https://orcid.org/0000-0002-6508-0895
                https://orcid.org/0000-0003-4982-7175
                https://orcid.org/0000-0001-8209-5231
                https://orcid.org/0000-0001-5658-8411
                Article
                APS311254
                10.1002/aps3.11254
                6580989
                31236313
                3629c50c-490e-4a09-8eb7-f145a049beff
                © 2019 Soto Gomez et al. Applications in Plant Sciences is published by Wiley Periodicals, Inc. on behalf of the Botanical Society of America

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 13 November 2018
                : 01 April 2019
                Page count
                Figures: 2, Tables: 2, Pages: 13, Words: 13113
                Funding
                Funded by: NSERC
                Award ID: 704464
                Categories
                Application Article
                Application Article
                Custom metadata
                2.0
                aps311254
                June 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.4 mode:remove_FC converted:18.06.2019

                dioscorea target capture kit,herbarium,hyb‐seq,monocot phylogenomics,ortholog identification,tuber crop wild relatives

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