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      Species complex diversification by host plant use in an herbivorous insect: The source of Puerto Rican cactus mealybug pest and implications for biological control

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          Abstract

          Cryptic taxa have often been observed in the form of host‐associated species that diverged as the result of adaptation to alternate host plants. Untangling cryptic diversity in species complexes that encompass invasive species is a mandatory task for pest management. Moreover, investigating the evolutionary history of a species complex may help to understand the drivers of their diversification. The mealybug Hypogeococcus pungens was believed to be a polyphagous species from South America and has been reported as a pest devastating native cacti in Puerto Rico, also threatening cactus diversity in the Caribbean and North America. There is neither certainty about the identity of the pest nor the source population from South America. Recent studies pointed to substantial genetic differentiation among local populations, suggesting that H. pungens is a species complex. In this study, we used a combination of genome‐wide SNPs and mtDNA variation to investigate species diversity within H. pungens sensu lato to establish host plant ranges of each one of the putative members of the complex, to evaluate whether the pattern of host plant association drove diversification in the species complex, and to determine the source population of the Puerto Rican cactus pest. Our results suggested that H. pungens comprises at least five different species, each one strongly associated with specific host plants. We also established that the Puerto Rican cactus pest derives from southeastern Brazilian mealybugs. This is an important achievement because it will help to design reliable strategies for biological control using natural enemies of the pest from its native range.

          Abstract

          Hypogeococcus pungens is a species complex native to South America. Some of its members are cactophilic, and one of them has been reported as a pest threatening cactus diversity in the Caribbean and North America. Using a combination of genome‐wide SNPs and mtDNA, we found that the complex comprises at least five different species, each strongly associated with specific host plants. Our study also shows that the Puerto Rican cactus pest derives from southeastern Brazilian mealybugs. These results will help to design reliable strategies for biological control using natural enemies of the pest from its native range.

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          DnaSP 6: DNA Sequence Polymorphism Analysis of Large Data Sets.

          We present version 6 of the DNA Sequence Polymorphism (DnaSP) software, a new version of the popular tool for performing exhaustive population genetic analyses on multiple sequence alignments. This major upgrade incorporates novel functionalities to analyze large data sets, such as those generated by high-throughput sequencing technologies. Among other features, DnaSP 6 implements: 1) modules for reading and analyzing data from genomic partitioning methods, such as RADseq or hybrid enrichment approaches, 2) faster methods scalable for high-throughput sequencing data, and 3) summary statistics for the analysis of multi-locus population genetics data. Furthermore, DnaSP 6 includes novel modules to perform single- and multi-locus coalescent simulations under a wide range of demographic scenarios. The DnaSP 6 program, with extensive documentation, is freely available at http://www.ub.edu/dnasp.
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            A general species delimitation method with applications to phylogenetic placements

            Motivation: Sequence-based methods to delimit species are central to DNA taxonomy, microbial community surveys and DNA metabarcoding studies. Current approaches either rely on simple sequence similarity thresholds (OTU-picking) or on complex and compute-intensive evolutionary models. The OTU-picking methods scale well on large datasets, but the results are highly sensitive to the similarity threshold. Coalescent-based species delimitation approaches often rely on Bayesian statistics and Markov Chain Monte Carlo sampling, and can therefore only be applied to small datasets. Results: We introduce the Poisson tree processes (PTP) model to infer putative species boundaries on a given phylogenetic input tree. We also integrate PTP with our evolutionary placement algorithm (EPA-PTP) to count the number of species in phylogenetic placements. We compare our approaches with popular OTU-picking methods and the General Mixed Yule Coalescent (GMYC) model. For de novo species delimitation, the stand-alone PTP model generally outperforms GYMC as well as OTU-picking methods when evolutionary distances between species are small. PTP neither requires an ultrametric input tree nor a sequence similarity threshold as input. In the open reference species delimitation approach, EPA-PTP yields more accurate results than de novo species delimitation methods. Finally, EPA-PTP scales on large datasets because it relies on the parallel implementations of the EPA and RAxML, thereby allowing to delimit species in high-throughput sequencing data. Availability and implementation: The code is freely available at www.exelixis-lab.org/software.html. Contact: Alexandros.Stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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              hierfstat, a package for r to compute and test hierarchical F-statistics

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                Author and article information

                Contributors
                danielpovedam@gmail.com
                mbaguirre@conicet.gov.ar
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                20 August 2020
                October 2020
                : 10
                : 19 ( doiID: 10.1002/ece3.v10.19 )
                : 10463-10480
                Affiliations
                [ 1 ] Fundación para el Estudio de Especies Invasivas (FuEDEI) Hurlingham Argentina
                [ 2 ] Instituto de Ecología Genética y Evolución de Buenos Aires (IEGEBA) Departamento de Ecología Genética y Evolución Universidad de Buenos Aires Buenos Aires Argentina
                [ 3 ] Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Ciudad Autónoma de Buenos Aires Argentina
                [ 4 ] Grupo de investigación en Evolución, Ecología y Conservación (EECO) Universidad del Quindío Armenia Colombia
                [ 5 ] U.S. Department of Agriculture‐ARS Tallahassee FL USA
                [ 6 ] Department of Entomology University of California Riverside CA USA
                [ 7 ] Caribbean Advisor to the APHIS Administrator USDA San Juan Puerto Rico
                [ 8 ] Departamento de Engenharia Florestal Programa de Pós‐graduação em Engenharia Florestal ‐ PPGEF Lab. de Monitoramento e Proteção Florestal ‐ LAMPF Universidade Regional de Blumenau – FURB Blumenau Brazil
                Author notes
                [*] [* ] Correspondence

                Daniel Poveda‐Martínez and María Belén Aguirre, Fundación para el Estudio de Especies Invasivas (FuEDEI), Hurlingham, Buenos Aires, Argentina.

                Emails: danielpovedam@ 123456gmail.com (D. P. M.), mbaguirre@ 123456conicet.gov.ar (M. B. A.)

                Author information
                https://orcid.org/0000-0003-3657-8421
                https://orcid.org/0000-0002-3773-8805
                https://orcid.org/0000-0003-3326-9877
                Article
                ECE36702
                10.1002/ece3.6702
                7548167
                33072273
                f20f6391-a29b-443d-870c-4d7d477e0ba0
                © 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd

                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
                : 23 July 2020
                : 28 July 2020
                : 29 July 2020
                Page count
                Figures: 3, Tables: 4, Pages: 18, Words: 30988
                Funding
                Funded by: USDA‐APHIS Farm Bill
                Award ID: 17‐8130‐0757‐IA
                Award ID: 19‐8130‐0852‐IA
                Funded by: USDA‐APHIS Biological Control Program
                Award ID: 18‐8130‐0757‐IA
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                October 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.2 mode:remove_FC converted:11.10.2020

                Evolutionary Biology
                cryptic species,host plants,hypogeococcus pungens,insect pests,invasion,snps
                Evolutionary Biology
                cryptic species, host plants, hypogeococcus pungens, insect pests, invasion, snps

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