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      Genome‐wide SNPs of vegetable leafminer, Liriomyza sativae: Insights into the recent Australian invasion

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          Abstract

          Liriomyza sativae, the vegetable leafminer, is an important agricultural pest originally from the Americas, which has now colonized all continents except Antarctica. In 2015, L. sativae arrived on the Australian mainland and established on the Cape York Peninsula in the northeast of the country near the Torres Strait, which provides a possible pathway for pests to enter Australia and evade biosecurity efforts. Here, we assessed genetic variation in L. sativae based on genome‐wide single nucleotide polymorphisms (SNPs) generated by double digest restriction‐site‐associated DNA sequencing (ddRAD‐seq), aiming to uncover the potential origin(s) of this pest in Australia and contribute to reconstructing its global invasion history. Our fineRADstructure results and principal component analysis suggest Australian mainland populations were genetically close to populations from the Torres Strait, whereas populations from Asia, Africa, and Papua New Guinea (PNG) were more distantly related. Hawaiian populations were genetically distinct from all other populations of L. sativae included in our study. Admixture analyses further revealed that L. sativae from the Torres Strait may have genetic variation originating from multiple sources including Indonesia and PNG, and which has now spread to the Australian mainland. The L. sativae lineages from Asia and Africa appear closely related. Isolation‐by‐distance (IBD) was found at a broad global scale, but not within small regions, suggesting that human‐mediated factors likely contribute to the local spread of this pest. Overall, our findings suggest that an exotic Liriomyza pest invaded Australia through the Indo‐Papuan conduit, highlighting the importance of biosecurity programs aimed at restricting the movement of pests and diseases through this corridor.

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          Fast model-based estimation of ancestry in unrelated individuals.

          Population stratification has long been recognized as a confounding factor in genetic association studies. Estimated ancestries, derived from multi-locus genotype data, can be used to perform a statistical correction for population stratification. One popular technique for estimation of ancestry is the model-based approach embodied by the widely applied program structure. Another approach, implemented in the program EIGENSTRAT, relies on Principal Component Analysis rather than model-based estimation and does not directly deliver admixture fractions. EIGENSTRAT has gained in popularity in part owing to its remarkable speed in comparison to structure. We present a new algorithm and a program, ADMIXTURE, for model-based estimation of ancestry in unrelated individuals. ADMIXTURE adopts the likelihood model embedded in structure. However, ADMIXTURE runs considerably faster, solving problems in minutes that take structure hours. In many of our experiments, we have found that ADMIXTURE is almost as fast as EIGENSTRAT. The runtime improvements of ADMIXTURE rely on a fast block relaxation scheme using sequential quadratic programming for block updates, coupled with a novel quasi-Newton acceleration of convergence. Our algorithm also runs faster and with greater accuracy than the implementation of an Expectation-Maximization (EM) algorithm incorporated in the program FRAPPE. Our simulations show that ADMIXTURE's maximum likelihood estimates of the underlying admixture coefficients and ancestral allele frequencies are as accurate as structure's Bayesian estimates. On real-world data sets, ADMIXTURE's estimates are directly comparable to those from structure and EIGENSTRAT. Taken together, our results show that ADMIXTURE's computational speed opens up the possibility of using a much larger set of markers in model-based ancestry estimation and that its estimates are suitable for use in correcting for population stratification in association studies.
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            adegenet: a R package for the multivariate analysis of genetic markers.

            The package adegenet for the R software is dedicated to the multivariate analysis of genetic markers. It extends the ade4 package of multivariate methods by implementing formal classes and functions to manipulate and analyse genetic markers. Data can be imported from common population genetics software and exported to other software and R packages. adegenet also implements standard population genetics tools along with more original approaches for spatial genetics and hybridization. Stable version is available from CRAN: http://cran.r-project.org/mirrors.html. Development version is available from adegenet website: http://adegenet.r-forge.r-project.org/. Both versions can be installed directly from R. adegenet is distributed under the GNU General Public Licence (v.2).
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              NCBI BLAST: a better web interface

              Basic Local Alignment Search Tool (BLAST) is a sequence similarity search program. The public interface of BLAST, http://www.ncbi.nlm.nih.gov/blast, at the NCBI website has recently been reengineered to improve usability and performance. Key new features include simplified search forms, improved navigation, a list of recent BLAST results, saved search strategies and a documentation directory. Here, we describe the BLAST web application's new features, explain design decisions and outline plans for future improvement.
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                Author and article information

                Contributors
                xuefenx@student.unimelb.edu.au
                ary@unimelb.edu.au
                Journal
                Evol Appl
                Evol Appl
                10.1111/(ISSN)1752-4571
                EVA
                Evolutionary Applications
                John Wiley and Sons Inc. (Hoboken )
                1752-4571
                28 June 2022
                July 2022
                : 15
                : 7 ( doiID: 10.1111/eva.v15.7 )
                : 1129-1140
                Affiliations
                [ 1 ] Bio21 Institute, School of BioSciences The University of Melbourne Parkville Victoria Australia
                [ 2 ] Cesar Australia Brunswick Victoria Australia
                [ 3 ] Chinese Academy of Agricultural Sciences Beijing China
                Author notes
                [*] [* ] Correspondence

                Xuefen Xu and Ary A. Hoffmann, Bio21 Institute, School of BioSciences, The University of Melbourne, 30 Flemington Road, Parkville, Vic. 3052, Australia.

                Email: xuefenx@ 123456student.unimelb.edu.au (X.X.) and ary@ 123456unimelb.edu.au (A.A.H.)

                Author information
                https://orcid.org/0000-0002-2839-6428
                https://orcid.org/0000-0003-4695-075X
                https://orcid.org/0000-0002-5760-7255
                https://orcid.org/0000-0001-6304-9387
                https://orcid.org/0000-0002-0627-0955
                https://orcid.org/0000-0003-3336-5703
                https://orcid.org/0000-0003-4541-3223
                https://orcid.org/0000-0002-1835-3571
                https://orcid.org/0000-0001-9497-7645
                Article
                EVA13430 EVA-2022-001-OA.R2
                10.1111/eva.13430
                9309458
                35899255
                a8ef4abd-614f-4893-95f9-d40cd200848d
                © 2022 The Authors. Evolutionary Applications 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
                : 26 May 2022
                : 02 January 2022
                : 29 May 2022
                Page count
                Figures: 5, Tables: 1, Pages: 12, Words: 8199
                Funding
                Funded by: Hort Innovation , doi 10.13039/501100000981;
                Award ID: MT16004
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                July 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.7 mode:remove_FC converted:25.07.2022

                Evolutionary Biology
                biological invasions,ddrad,gene flow,genome‐wide snps,leafminers,population genetics

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