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      Nuclear Orthologs Derived from Whole Genome Sequencing Indicate Cryptic Diversity in the Bemisia tabaci (Insecta: Aleyrodidae) Complex of Whiteflies

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          Abstract

          The Bemisia tabaci complex of whiteflies contains globally important pests thought to contain cryptic species corresponding to geographically structured phylogenetic clades. Although mostly morphologically indistinguishable, differences have been shown to exist among populations in behavior, plant virus vector capacity, ability to hybridize, and DNA sequence divergence. These differences allow for certain populations to become invasive and cause great economic damage in a monoculture setting. Although high mitochondrial DNA divergences have been reported between putative conspecifics of the B. tabaci species complex, there is limited data that exists across the whole genome for this group. Using data from 2184 orthologs obtained from whole genome sequencing (Illumina), a phylogenetic analysis using maximum likelihood and coalescent methodologies was completed on ten individuals of the B. tabaci complex. In addition, automatic barcode gap discovery methods were employed, and results suggest the existence of five species. Although the divergences of the mitochondrial cytochrome oxidase I gene are high among members of this complex, nuclear divergences are much lower in comparison. Single-copy orthologs from whole genome sequencing demonstrate divergent population structures among members of the B. tabaci complex and the sequences provide an important resource to aid in future genomic studies of the group.

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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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              The Sweetpotato or Silverleaf Whiteflies: Biotypes of Bemisia tabaci or a Species Complex?

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                Author and article information

                Journal
                DIVEC6
                Diversity
                Diversity
                MDPI AG
                1424-2818
                September 2019
                August 29 2019
                : 11
                : 9
                : 151
                Article
                10.3390/d11090151
                a192c44b-7a89-445b-95ed-e08806e118f9
                © 2019

                https://creativecommons.org/licenses/by/4.0/

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