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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Mitochondrial DNA and trade data support multiple origins of <italic>Helicoverpa armigera</italic> (Lepidoptera, Noctuidae) in Brazil</title><author><name sortKey="Tay, Wee Tek" sort="Tay, Wee Tek" uniqKey="Tay W" first="Wee Tek" last="Tay">Wee Tek Tay</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation></author><author><name sortKey="Walsh, Thomas K" sort="Walsh, Thomas K" uniqKey="Walsh T" first="Thomas K." last="Walsh">Thomas K. Walsh</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation></author><author><name sortKey="Downes, Sharon" sort="Downes, Sharon" uniqKey="Downes S" first="Sharon" last="Downes">Sharon Downes</name><affiliation><nlm:aff id="a2"><institution>CSIRO, Myall Vale Laboratories, Kamilaroi Highway</institution>, Narrabri, NSW 2390,<country>Australia</country></nlm:aff></affiliation></author><author><name sortKey="Anderson, Craig" sort="Anderson, Craig" uniqKey="Anderson C" first="Craig" last="Anderson">Craig Anderson</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation><affiliation><nlm:aff id="a3"><institution>Biological and Environmental Sciences, University of Stirling</institution>, Stirling, FK9 4LA,<country>UK</country></nlm:aff></affiliation></author><author><name sortKey="Jermiin, Lars S" sort="Jermiin, Lars S" uniqKey="Jermiin L" first="Lars S." last="Jermiin">Lars S. Jermiin</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation><affiliation><nlm:aff id="a4"><institution>Research School of Biology, Australian National University</institution>, Acton, ACT 2601,<country>Australia</country></nlm:aff></affiliation></author><author><name sortKey="Wong, Thomas K F" sort="Wong, Thomas K F" uniqKey="Wong T" first="Thomas K. F." last="Wong">Thomas K. F. Wong</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation><affiliation><nlm:aff id="a4"><institution>Research School of Biology, Australian National University</institution>, Acton, ACT 2601,<country>Australia</country></nlm:aff></affiliation></author><author><name sortKey="Piper, Melissa C" sort="Piper, Melissa C" uniqKey="Piper M" first="Melissa C." last="Piper">Melissa C. Piper</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation></author><author><name sortKey="Chang, Ester Silva" sort="Chang, Ester Silva" uniqKey="Chang E" first="Ester Silva" last="Chang">Ester Silva Chang</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation><affiliation><nlm:aff id="a5"><institution>Universidade de São Paulo, Instituto de Biociências</institution>, São Paulo, SP, 05508-090,<country>Brazil</country></nlm:aff></affiliation></author><author><name sortKey="Macedo, Isabella Barony" sort="Macedo, Isabella Barony" uniqKey="Macedo I" first="Isabella Barony" last="Macedo">Isabella Barony Macedo</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation><affiliation><nlm:aff id="a6"><institution>Universidade Federal de Minas Gerais, Faculdade de Farmácia</institution>, Belo Horizonte, MG, 31270-901,<country>Brazil</country></nlm:aff></affiliation></author><author><name sortKey="Czepak, Cecilia" sort="Czepak, Cecilia" uniqKey="Czepak C" first="Cecilia" last="Czepak">Cecilia Czepak</name><affiliation><nlm:aff id="a7"><institution>Universidade Federal de Goiás, Escola de Agronomia</institution>, Goiânia, GO, 75804-020,<country>Brazil</country></nlm:aff></affiliation></author><author><name sortKey="Behere, Gajanan T" sort="Behere, Gajanan T" uniqKey="Behere G" first="Gajanan T." last="Behere">Gajanan T. Behere</name><affiliation><nlm:aff id="a8"><institution>Division of Crop Protection, ICAR Research Complex for North East Hill Region</institution>, Umroi Road, Umiam, Meghalaya, 793103,<country>India</country></nlm:aff></affiliation></author><author><name sortKey="Silvie, Pierre" sort="Silvie, Pierre" uniqKey="Silvie P" first="Pierre" last="Silvie">Pierre Silvie</name><affiliation><nlm:aff id="a9"><institution>IRD, UMR EGCE</institution>, FR-91198 Gif-sur-Yvette Cedex,<country>France</country></nlm:aff></affiliation><affiliation><nlm:aff id="a10"><institution>CIRAD, UPR AÏDA</institution>, F-34398 Montpellier Cedex 05,<country>France</country></nlm:aff></affiliation></author><author><name sortKey="Soria, Miguel F" sort="Soria, Miguel F" uniqKey="Soria M" first="Miguel F." last="Soria">Miguel F. Soria</name><affiliation><nlm:aff id="a11"><institution>Bayer S.A., Crop Science Division</institution>, São Paulo, SP, 04779-900,<country>Brazil</country></nlm:aff></affiliation></author><author><name sortKey="Frayssinet, Marie" sort="Frayssinet, Marie" uniqKey="Frayssinet M" first="Marie" last="Frayssinet">Marie Frayssinet</name><affiliation><nlm:aff id="a12"><institution>DGIMI, INRA, Université Montpellier</institution>, Montpellier, 34095,<country>France</country></nlm:aff></affiliation></author><author><name sortKey="Gordon, Karl H J" sort="Gordon, Karl H J" uniqKey="Gordon K" first="Karl H. J." last="Gordon">Karl H. J. Gordon</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">28350004</idno><idno type="pmc">5368605</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5368605</idno><idno type="RBID">PMC:5368605</idno><idno type="doi">10.1038/srep45302</idno><date when="2017">2017</date><idno type="wicri:Area/Pmc/Corpus">000875</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000875</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Mitochondrial DNA and trade data support multiple origins of <italic>Helicoverpa armigera</italic> (Lepidoptera, Noctuidae) in Brazil</title><author><name sortKey="Tay, Wee Tek" sort="Tay, Wee Tek" uniqKey="Tay W" first="Wee Tek" last="Tay">Wee Tek Tay</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation></author><author><name sortKey="Walsh, Thomas K" sort="Walsh, Thomas K" uniqKey="Walsh T" first="Thomas K." last="Walsh">Thomas K. Walsh</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation></author><author><name sortKey="Downes, Sharon" sort="Downes, Sharon" uniqKey="Downes S" first="Sharon" last="Downes">Sharon Downes</name><affiliation><nlm:aff id="a2"><institution>CSIRO, Myall Vale Laboratories, Kamilaroi Highway</institution>, Narrabri, NSW 2390,<country>Australia</country></nlm:aff></affiliation></author><author><name sortKey="Anderson, Craig" sort="Anderson, Craig" uniqKey="Anderson C" first="Craig" last="Anderson">Craig Anderson</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation><affiliation><nlm:aff id="a3"><institution>Biological and Environmental Sciences, University of Stirling</institution>, Stirling, FK9 4LA,<country>UK</country></nlm:aff></affiliation></author><author><name sortKey="Jermiin, Lars S" sort="Jermiin, Lars S" uniqKey="Jermiin L" first="Lars S." last="Jermiin">Lars S. Jermiin</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation><affiliation><nlm:aff id="a4"><institution>Research School of Biology, Australian National University</institution>, Acton, ACT 2601,<country>Australia</country></nlm:aff></affiliation></author><author><name sortKey="Wong, Thomas K F" sort="Wong, Thomas K F" uniqKey="Wong T" first="Thomas K. F." last="Wong">Thomas K. F. Wong</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation><affiliation><nlm:aff id="a4"><institution>Research School of Biology, Australian National University</institution>, Acton, ACT 2601,<country>Australia</country></nlm:aff></affiliation></author><author><name sortKey="Piper, Melissa C" sort="Piper, Melissa C" uniqKey="Piper M" first="Melissa C." last="Piper">Melissa C. Piper</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation></author><author><name sortKey="Chang, Ester Silva" sort="Chang, Ester Silva" uniqKey="Chang E" first="Ester Silva" last="Chang">Ester Silva Chang</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation><affiliation><nlm:aff id="a5"><institution>Universidade de São Paulo, Instituto de Biociências</institution>, São Paulo, SP, 05508-090,<country>Brazil</country></nlm:aff></affiliation></author><author><name sortKey="Macedo, Isabella Barony" sort="Macedo, Isabella Barony" uniqKey="Macedo I" first="Isabella Barony" last="Macedo">Isabella Barony Macedo</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation><affiliation><nlm:aff id="a6"><institution>Universidade Federal de Minas Gerais, Faculdade de Farmácia</institution>, Belo Horizonte, MG, 31270-901,<country>Brazil</country></nlm:aff></affiliation></author><author><name sortKey="Czepak, Cecilia" sort="Czepak, Cecilia" uniqKey="Czepak C" first="Cecilia" last="Czepak">Cecilia Czepak</name><affiliation><nlm:aff id="a7"><institution>Universidade Federal de Goiás, Escola de Agronomia</institution>, Goiânia, GO, 75804-020,<country>Brazil</country></nlm:aff></affiliation></author><author><name sortKey="Behere, Gajanan T" sort="Behere, Gajanan T" uniqKey="Behere G" first="Gajanan T." last="Behere">Gajanan T. Behere</name><affiliation><nlm:aff id="a8"><institution>Division of Crop Protection, ICAR Research Complex for North East Hill Region</institution>, Umroi Road, Umiam, Meghalaya, 793103,<country>India</country></nlm:aff></affiliation></author><author><name sortKey="Silvie, Pierre" sort="Silvie, Pierre" uniqKey="Silvie P" first="Pierre" last="Silvie">Pierre Silvie</name><affiliation><nlm:aff id="a9"><institution>IRD, UMR EGCE</institution>, FR-91198 Gif-sur-Yvette Cedex,<country>France</country></nlm:aff></affiliation><affiliation><nlm:aff id="a10"><institution>CIRAD, UPR AÏDA</institution>, F-34398 Montpellier Cedex 05,<country>France</country></nlm:aff></affiliation></author><author><name sortKey="Soria, Miguel F" sort="Soria, Miguel F" uniqKey="Soria M" first="Miguel F." last="Soria">Miguel F. Soria</name><affiliation><nlm:aff id="a11"><institution>Bayer S.A., Crop Science Division</institution>, São Paulo, SP, 04779-900,<country>Brazil</country></nlm:aff></affiliation></author><author><name sortKey="Frayssinet, Marie" sort="Frayssinet, Marie" uniqKey="Frayssinet M" first="Marie" last="Frayssinet">Marie Frayssinet</name><affiliation><nlm:aff id="a12"><institution>DGIMI, INRA, Université Montpellier</institution>, Montpellier, 34095,<country>France</country></nlm:aff></affiliation></author><author><name sortKey="Gordon, Karl H J" sort="Gordon, Karl H J" uniqKey="Gordon K" first="Karl H. J." last="Gordon">Karl H. J. Gordon</name><affiliation><nlm:aff id="a1"><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></nlm:aff></affiliation></author></analytic><series><title level="j">Scientific Reports</title><idno type="eISSN">2045-2322</idno><imprint><date when="2017">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>The Old World bollworm <italic>Helicoverpa armigera</italic> is now established in Brazil but efforts to identify incursion origin(s) and pathway(s) have met with limited success due to the patchiness of available data. Using international agricultural/horticultural commodity trade data and mitochondrial DNA (mtDNA) cytochrome oxidase I (COI) and cytochrome <italic>b</italic> (Cyt <italic>b</italic>) gene markers, we inferred the origins and incursion pathways into Brazil. We detected 20 mtDNA haplotypes from six Brazilian states, eight of which were new to our 97 global COI-Cyt <italic>b</italic> haplotype database. Direct sequence matches indicated five Brazilian haplotypes had Asian, African, and European origins. We identified 45 parsimoniously informative sites and multiple substitutions per site within the concatenated (945 bp) nucleotide dataset, implying that probabilistic phylogenetic analysis methods are needed. High diversity and signatures of uniquely shared haplotypes with diverse localities combined with the trade data suggested multiple incursions and introduction origins in Brazil. Increasing agricultural/horticultural trade activities between the Old and New Worlds represents a significant biosecurity risk factor. Identifying pest origins will enable resistance profiling that reflects countries of origin to be included when developing a resistance management strategy, while identifying incursion pathways will improve biosecurity protocols and risk analysis at biosecurity hotspots including national ports.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Hulme, P E" uniqKey="Hulme P">P. E. Hulme</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Monke, J" uniqKey="Monke J">J. Monke</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Monthei, D" uniqKey="Monthei D">D. Monthei</name></author><author><name sortKey="Mueller, S" uniqKey="Mueller S">S. Mueller</name></author><author><name sortKey="Lockwood, J" uniqKey="Lockwood J">J. Lockwood</name></author><author><name sortKey="Debboun, M" uniqKey="Debboun M">M. 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Sci Rep</journal-id><journal-id journal-id-type="iso-abbrev">Sci Rep</journal-id><journal-title-group><journal-title>Scientific Reports</journal-title></journal-title-group><issn pub-type="epub">2045-2322</issn><publisher><publisher-name>Nature Publishing Group</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">28350004</article-id><article-id pub-id-type="pmc">5368605</article-id><article-id pub-id-type="pii">srep45302</article-id><article-id pub-id-type="doi">10.1038/srep45302</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Mitochondrial DNA and trade data support multiple origins of <italic>Helicoverpa armigera</italic> (Lepidoptera, Noctuidae) in Brazil</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Tay</surname><given-names>Wee Tek</given-names></name><xref ref-type="corresp" rid="c1">a</xref><xref ref-type="aff" rid="a1">1</xref></contrib><contrib contrib-type="author"><name><surname>Walsh</surname><given-names>Thomas K.</given-names></name><xref ref-type="aff" rid="a1">1</xref></contrib><contrib contrib-type="author"><name><surname>Downes</surname><given-names>Sharon</given-names></name><xref ref-type="aff" rid="a2">2</xref></contrib><contrib contrib-type="author"><name><surname>Anderson</surname><given-names>Craig</given-names></name><xref ref-type="aff" rid="a1">1</xref><xref ref-type="aff" rid="a3">3</xref></contrib><contrib contrib-type="author"><name><surname>Jermiin</surname><given-names>Lars S.</given-names></name><xref ref-type="aff" rid="a1">1</xref><xref ref-type="aff" rid="a4">4</xref></contrib><contrib contrib-type="author"><name><surname>Wong</surname><given-names>Thomas K. F.</given-names></name><xref ref-type="aff" rid="a1">1</xref><xref ref-type="aff" rid="a4">4</xref></contrib><contrib contrib-type="author"><name><surname>Piper</surname><given-names>Melissa C.</given-names></name><xref ref-type="aff" rid="a1">1</xref></contrib><contrib contrib-type="author"><name><surname>Chang</surname><given-names>Ester Silva</given-names></name><xref ref-type="aff" rid="a1">1</xref><xref ref-type="aff" rid="a5">5</xref></contrib><contrib contrib-type="author"><name><surname>Macedo</surname><given-names>Isabella Barony</given-names></name><xref ref-type="aff" rid="a1">1</xref><xref ref-type="aff" rid="a6">6</xref></contrib><contrib contrib-type="author"><name><surname>Czepak</surname><given-names>Cecilia</given-names></name><xref ref-type="aff" rid="a7">7</xref></contrib><contrib contrib-type="author"><name><surname>Behere</surname><given-names>Gajanan T.</given-names></name><xref ref-type="aff" rid="a8">8</xref></contrib><contrib contrib-type="author"><name><surname>Silvie</surname><given-names>Pierre</given-names></name><xref ref-type="aff" rid="a9">9</xref><xref ref-type="aff" rid="a10">10</xref></contrib><contrib contrib-type="author"><name><surname>Soria</surname><given-names>Miguel F.</given-names></name><xref ref-type="aff" rid="a11">11</xref></contrib><contrib contrib-type="author"><name><surname>Frayssinet</surname><given-names>Marie</given-names></name><xref ref-type="aff" rid="a12">12</xref></contrib><contrib contrib-type="author"><name><surname>Gordon</surname><given-names>Karl H. J.</given-names></name><xref ref-type="aff" rid="a1">1</xref></contrib><aff id="a1"><label>1</label><institution>CSIRO, Black Mountain Laboratories</institution>, Clunies Ross Street, ACT 2601,<country>Australia</country></aff><aff id="a2"><label>2</label><institution>CSIRO, Myall Vale Laboratories, Kamilaroi Highway</institution>, Narrabri, NSW 2390,<country>Australia</country></aff><aff id="a3"><label>3</label><institution>Biological and Environmental Sciences, University of Stirling</institution>, Stirling, FK9 4LA,<country>UK</country></aff><aff id="a4"><label>4</label><institution>Research School of Biology, Australian National University</institution>, Acton, ACT 2601,<country>Australia</country></aff><aff id="a5"><label>5</label><institution>Universidade de São Paulo, Instituto de Biociências</institution>, São Paulo, SP, 05508-090,<country>Brazil</country></aff><aff id="a6"><label>6</label><institution>Universidade Federal de Minas Gerais, Faculdade de Farmácia</institution>, Belo Horizonte, MG, 31270-901,<country>Brazil</country></aff><aff id="a7"><label>7</label><institution>Universidade Federal de Goiás, Escola de Agronomia</institution>, Goiânia, GO, 75804-020,<country>Brazil</country></aff><aff id="a8"><label>8</label><institution>Division of Crop Protection, ICAR Research Complex for North East Hill Region</institution>, Umroi Road, Umiam, Meghalaya, 793103,<country>India</country></aff><aff id="a9"><label>9</label><institution>IRD, UMR EGCE</institution>, FR-91198 Gif-sur-Yvette Cedex,<country>France</country></aff><aff id="a10"><label>10</label><institution>CIRAD, UPR AÏDA</institution>, F-34398 Montpellier Cedex 05,<country>France</country></aff><aff id="a11"><label>11</label><institution>Bayer S.A., Crop Science Division</institution>, São Paulo, SP, 04779-900,<country>Brazil</country></aff><aff id="a12"><label>12</label><institution>DGIMI, INRA, Université Montpellier</institution>, Montpellier, 34095,<country>France</country></aff></contrib-group><author-notes><corresp id="c1"><label>a</label><email>weetek.tay@csiro.au</email></corresp></author-notes><pub-date pub-type="epub"><day>28</day><month>03</month><year>2017</year></pub-date><pub-date pub-type="collection"><year>2017</year></pub-date><volume>7</volume><elocation-id>45302</elocation-id><history><date date-type="received"><day>20</day><month>10</month><year>2016</year></date><date date-type="accepted"><day>23</day><month>02</month><year>2017</year></date></history><permissions><copyright-statement>Copyright © 2017, The Author(s)</copyright-statement><copyright-year>2017</copyright-year><copyright-holder>The Author(s)</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0/"><pmc-comment>author-paid</pmc-comment>
<license-p>This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><abstract><p>The Old World bollworm <italic>Helicoverpa armigera</italic> is now established in Brazil but efforts to identify incursion origin(s) and pathway(s) have met with limited success due to the patchiness of available data. Using international agricultural/horticultural commodity trade data and mitochondrial DNA (mtDNA) cytochrome oxidase I (COI) and cytochrome <italic>b</italic> (Cyt <italic>b</italic>) gene markers, we inferred the origins and incursion pathways into Brazil. We detected 20 mtDNA haplotypes from six Brazilian states, eight of which were new to our 97 global COI-Cyt <italic>b</italic> haplotype database. Direct sequence matches indicated five Brazilian haplotypes had Asian, African, and European origins. We identified 45 parsimoniously informative sites and multiple substitutions per site within the concatenated (945 bp) nucleotide dataset, implying that probabilistic phylogenetic analysis methods are needed. High diversity and signatures of uniquely shared haplotypes with diverse localities combined with the trade data suggested multiple incursions and introduction origins in Brazil. Increasing agricultural/horticultural trade activities between the Old and New Worlds represents a significant biosecurity risk factor. Identifying pest origins will enable resistance profiling that reflects countries of origin to be included when developing a resistance management strategy, while identifying incursion pathways will improve biosecurity protocols and risk analysis at biosecurity hotspots including national ports.</p></abstract></article-meta></front><body><p>Global growth, food security and prosperity of agricultural communities are closely connected to international trade in agricultural and horticultural commodities. The volume and value of this trade is influenced by both climatic and pest/pathogen factors and there is interest in increasing the diversity and volume of trade whilst minimizing the impact of pests and pathogens. This conflict of interests poses a number of challenges, both before and after the incursion of a pest or pathogen into a new location.</p><p>When ascertaining the order of events that led to the incursion of a pest or pathogen, understanding the roles of propagule pressure and geographical origins is very important, especially in revealing likely incursion pathways. This, in turn, enables a more detailed assessment of factors that might have contributed to breaches in biosecurity protocols, and may assist the development of appropriate strategies for managing and reducing future incursions. Incursions of insect pests associated with international trade in agricultural and horticultural commodities are likely to increase in frequency due to globalisation and increased transport networks<xref ref-type="bibr" rid="b1">1</xref>. This highlights the importance of differentiating trade-related ‘unintended’ incursions from malicious introductions of pest species (sometimes described as agricultural bioterrorism).</p><p>Agricultural bioterrorism is defined as deliberate damage to plant crops and livestock or intentional introduction of pests or pathogens, with an aim to cause fear and negatively impact food security, human, animal and plant health, and the economy of the targeted country<xref ref-type="bibr" rid="b2">2</xref><xref ref-type="bibr" rid="b3">3</xref>. Agricultural bioterrorism could also involve the introduction of organisms with genes of biosecurity importance (i.e., those associated with insecticide/herbicide resistance). Developing guidelines and policies on agricultural bioterrorism is an area rapidly gaining attention due to its potential impact to global food security and socio-economic stability<xref ref-type="bibr" rid="b4">4</xref>. Accurate assessments that differentiate between natural and/or accidental introduction of pests and pathogens from that of malicious introductions will require analyses of international trade routes and activities, and a sound scientific knowledge of pests, including their invasive biology and evolutionary genetics.</p><p>The genetic diversity of a recently invaded pest species offers clues to the number of founder lineages (e.g.<xref ref-type="bibr" rid="b5">5</xref><xref ref-type="bibr" rid="b6">6</xref><xref ref-type="bibr" rid="b7">7</xref>), and incorporating information from other parts of its geographical range will allow more accurate inference of origins and incursion pathways (e.g.<xref ref-type="bibr" rid="b6">6</xref><xref ref-type="bibr" rid="b8">8</xref><xref ref-type="bibr" rid="b9">9</xref><xref ref-type="bibr" rid="b10">10</xref>). When a high number of individuals are introduced into a region (consecutively or concurrently; and/or over multiple occasions), the species is more likely to establish (i.e., high propagule pressure) and become invasive, for both demographic and genetic reasons<xref ref-type="bibr" rid="b11">11</xref><xref ref-type="bibr" rid="b12">12</xref><xref ref-type="bibr" rid="b13">13</xref><xref ref-type="bibr" rid="b14">14</xref>. The number of incursions preceding an invasion can be inferred using mitochondrial DNA (mtDNA), which allows us to estimate the number of genetically unique female founders (e.g.<xref ref-type="bibr" rid="b5">5</xref><xref ref-type="bibr" rid="b6">6</xref><xref ref-type="bibr" rid="b8">8</xref><xref ref-type="bibr" rid="b15">15</xref>). Usually, it is assumed that each unique mtDNA haplotype at an affected location represents a separate and independent incursion event (e.g.<xref ref-type="bibr" rid="b16">16</xref><xref ref-type="bibr" rid="b17">17</xref>); and assumption that seems sensible especially when the introduced populations are found in distant locations and each population has a unique mtDNA haplotype signature (e.g.<xref ref-type="bibr" rid="b17">17</xref><xref ref-type="bibr" rid="b18">18</xref>).</p><p><italic>Helicoverpa armigera</italic> is a major polyphagous agricultural pest, with a propensity to develop insecticide resistance (e.g.<xref ref-type="bibr" rid="b19">19</xref><xref ref-type="bibr" rid="b20">20</xref>; see also<xref ref-type="bibr" rid="b21">21</xref><xref ref-type="bibr" rid="b22">22</xref>), and the ability to disperse over great distances under favourable conditions (e.g.<xref ref-type="bibr" rid="b23">23</xref>). Previously endemic to the Old World (Asia, Africa, Europe) and Australasia, it has now been reported in Argentina<xref ref-type="bibr" rid="b24">24</xref> and Paraguay and Uruguay<xref ref-type="bibr" rid="b25">25</xref>, since its initial detection in Brazil<xref ref-type="bibr" rid="b26">26</xref> with a likely arrival date of between 2006<xref ref-type="bibr" rid="b27">27</xref> and 2008<xref ref-type="bibr" rid="b28">28</xref>. Long-distance dispersal may explain how ancestors of <italic>H. zea</italic> arrived in the New World<xref ref-type="bibr" rid="b29">29</xref>, and gene flow analyses of <italic>H. armigera</italic> (e.g., Israel and Turkey<xref ref-type="bibr" rid="b30">30</xref>; Europe (e.g., France, Portugal) and Africa (e.g., Tunisia, Morocco, Burkina Faso, Ivory Coast)<xref ref-type="bibr" rid="b31">31</xref> suggest occurrence of long-distance migration between Africa, Europe and western Asia. Movements from Africa to Ascension Island (~1,600 km), and between Australia and New Zealand (∼2,200 km) are also known<xref ref-type="bibr" rid="b32">32</xref><xref ref-type="bibr" rid="b33">33</xref>. Genetic analysis of Brazilian <italic>H. armigera</italic><xref ref-type="bibr" rid="b27">27</xref> identified multiple female founders and indicated higher than expected genetic diversity among introduced populations, subsequently confirmed by other studies<xref ref-type="bibr" rid="b34">34</xref><xref ref-type="bibr" rid="b35">35</xref>. Economic losses in Brazil from this pest incursion have been estimated at US dollars (USD$) 2 billion for 2012 to 2014<xref ref-type="bibr" rid="b36">36</xref>.</p><p>Pathways of incursion by <italic>H. armigera</italic> into the New World are hypothesised to be associated with international agricultural trade routes<xref ref-type="bibr" rid="b27">27</xref>, however this hypothesis remained untested. In this paper, we provide a detailed analysis of mtDNA gene diversity in Brazilian <italic>H. armigera</italic> populations sampled during the 2012/13 early incursion period. We examined the concatenated partial mtDNA COI-Cyt <italic>b</italic> genes in previously studied samples from Australia, China, India, Pakistan, Uganda, Burkina Faso<xref ref-type="bibr" rid="b29">29</xref><xref ref-type="bibr" rid="b37">37</xref>, and include also new material from New Zealand, France, Spain, Madagascar, Ghana, Cameroon and Senegal, with the aim of consolidating relevant mtDNA data at the individual and population levels, for the purpose of identifying potential geographical origin(s) of the Brazilian incursion(s). We then consider international agricultural and horticultural trade data into Brazil to identify patterns that might enable testing of the ‘incursion pathways via international trade routes hypothesis’ and to corroborate inferred incursion pathways. These data are discussed in terms of the biological invasion processes and the potential of elucidating appropriate insecticide and Bt resistance management practices for <italic>H. armigera</italic> in Brazil.</p><sec disp-level="1"><title>Material and Methods</title><sec disp-level="2"><title>Sample collection and DNA extraction</title><p><italic>Helicoverpa armigera</italic> samples were collected either as larvae (from host plants) or adults (by light/pheromone traps) from Asia, Australasia, Africa, and Europe (n = 329; collected between 2001–2014), and from Brazil (n = 114; collected between March and August, 2013). Samples were preserved in ethanol (>95%) prior to DNA extraction using the Qiagen Blood and Tissue Kit. Taxonomic identity of each specimen was confirmed using molecular DNA markers i.e., using the mtDNA COI and Cyt b genes, as per<xref ref-type="bibr" rid="b37">37</xref> (<xref ref-type="fig" rid="f1">Fig. 1</xref>; <xref ref-type="supplementary-material" rid="S1">Suppl. Table 1</xref>).</p></sec><sec disp-level="2"><title>Molecular characterisation of the samples</title><p>PCR amplification of partial mtDNA COI and Cyt <italic>b</italic> genes was done as reported<xref ref-type="bibr" rid="b27">27</xref><xref ref-type="bibr" rid="b37">37</xref>. Amplicons were confirmed in 1.5% agarose gels containing 1% w/v GelRed prior to Sanger sequencing (Macrogen Inc., Seoul, Rep. of Korea; Biological Resources Facility, Australian National University, Canberra, Australia). DNA trace sequences were assembled using Staden Pregap 4 and Gap 4<xref ref-type="bibr" rid="b38">38</xref>. Species identity was confirmed through BLASTN searches against the non-redundant DNA database in GenBank<xref ref-type="bibr" rid="b39">39</xref>. Estimates of haplotype (<italic>h</italic>) and nucleotide (<italic>π</italic>) diversity for Brazil, Old World, and at the global level were inferred using DnaSP<xref ref-type="bibr" rid="b40">40</xref>. A haplotype network for the 97 unique mtDNA haplotypes identified from this study was inferred using TCS<xref ref-type="bibr" rid="b41">41</xref> within PopART<xref ref-type="bibr" rid="b42">42</xref>.</p></sec><sec disp-level="2"><title>Molecular data survey and phylogenetic analysis</title><p>Partial COI and Cyt <italic>b</italic> gene sequences were aligned prior to concatenation to form a master alignment (443 sequences; 945 base pairs (bp)), and surveyed for evidence of multiple substitutions at the same sites to minimise biases to phylogenetic estimates. Evidence of multiple substitutions was analysed using Reticulate<xref ref-type="bibr" rid="b43">43</xref> to yield a compatibility plot (<xref ref-type="supplementary-material" rid="S1">Suppl. Fig. 3</xref>), and the program dnapars<xref ref-type="bibr" rid="b44">44</xref> was used to infer the most parsimonious number of substitutions that might have occurred at the parsimony-informative sites (<xref ref-type="supplementary-material" rid="S1">Suppl. Fig. 4</xref>). Analysis was repeated 10,000 times to increase the chance of finding the most parsimonious estimate.</p><p>Phylogenetic analysis based on 134 aligned sequences (after removal of surplus identical sequences from the master alignment) involved a probabilistic maximum-likelihood approach to enable handling of detected multiple substitutions. ModelFinder<xref ref-type="bibr" rid="b45">45</xref> and the AICc optimality criterion were used to find the optimal sequence evolution model. IQ-TREE<xref ref-type="bibr" rid="b46">46</xref> was used to infer the most likely phylogeny with 10,000 replications, and the consistency of the phylogeny estimated using ultrafast bootstrap<xref ref-type="bibr" rid="b47">47</xref> with default settings. This enabled assessment of whether different sets of sites, drawn at random with replacement from the sub-alignment, generated a consistent phylogenetic result.</p><p>As geographical locations were unevenly sampled (i.e., ranging from 3 to 58 sequences/location), the potential impact of this uneven sampling effort on the phylogeny was evaluated using jackknifing. First, 200,000 sub-alignments that consisted of three sequences from each location were generated randomly from the master alignment using AliJack <ext-link ext-link-type="uri" xlink:href="http://github.com/thomaskf/AliJack">http://github.com/thomaskf/AliJack</ext-link> to produce sub-alignments with 104 sequences. Next, the most likely trees from these sub-alignments were inferred using IQ-TREE and the HKY + R2 model. Finally, from the inferred trees we computed the ratio, <italic>J</italic>, between (i) the number of trees with selected sequences forming a clade, and (ii) the number of trees with the selected sequences included. The jackknife score (i.e., product 100 × <italic>J</italic>) was obtained using CheckJack <ext-link ext-link-type="uri" xlink:href="http://github.com/thomaskf/CheckJack">http://github.com/thomaskf/CheckJack</ext-link>.</p></sec><sec disp-level="2"><title>Trade data</title><p>Trade data (value in USD$), were obtained from the Observatory of Economic Complexity (OEC) website<xref ref-type="bibr" rid="b48">48</xref>. The OEC compiled its source data from the United Nations Statistical Division (COMTRADE) for the period 2001–2013 using repository of official trade statistics, and as compiled by the International Merchandise Trade Statistics Section of COMTRADE. 2002–2013 trade data were extracted for live horticultural and agricultural commodities imported from the Old World to Brazil, to quantify the movement of potentially contaminated plant material and agricultural products. Trade data classified as ‘Live Trees and Other Plants’ (Harmonized System [HS] code 06; <xref ref-type="supplementary-material" rid="S1">Suppl. Table 3</xref>), ‘Edible Vegetables and certain roots and tubers’ (HS code 07; <xref ref-type="supplementary-material" rid="S1">Suppl. Table 4</xref>), and ‘Edible Fruits and Nuts, Peel of Citrus/Melons’ (HS code 08; <xref ref-type="supplementary-material" rid="S1">Suppl. Table 5</xref>) were used. Countries were grouped into respective continents (Africa, Asia, Australasia, Europe, North America, South America) as per the OEC website (see <xref ref-type="supplementary-material" rid="S1">Suppl. Tables 3, 4 and 5</xref>). Data excluded import activities from North and South American countries into Brazil (see <xref ref-type="supplementary-material" rid="S1">Suppl. Tables 3, 4 and 5</xref>) due to the presumed pre-2006 absence of <italic>H. armigera</italic> in these regions.</p></sec><sec disp-level="2"><title>Import risk factor analysis</title><p>We assessed the biosecurity import risks of <italic>H. armigera</italic> with respect to trade data, the import risk/likelihood of entry, population establishment and its subsequent spread against suitable commodities (i.e., HS codes 06, 07, 08) using Biosecurity Australia’s import risk analyses method<xref ref-type="bibr" rid="b49">49</xref>. This method considered trade volume (as measured by value) in a year to estimate pest entry likelihood<xref ref-type="bibr" rid="b49">49</xref>. Based on eight specific criteria (i.e., (<italic>i</italic>) ecological specificity, (<italic>ii</italic>) plant host availability and suitability, (<italic>iii</italic>) survey methodology, (<italic>iv</italic>) taxonomic recognition, (<italic>v</italic>) entry potential, (<italic>vi</italic>) destination of infested material, (<italic>vii</italic>) potential economic impact, and (<italic>viii</italic>) establishment potential), <italic>H. armigera</italic> has been rated as a ‘High’ risk pest to the New World<xref ref-type="bibr" rid="b50">50</xref>. We assessed <italic>H. armigera</italic>’s import risk on a per-year basis for the period 2002–2013. As the overall trade volumes are expected to grow over time, this in turn would lead to the increase in the likelihood for both pest entry and population establishment<xref ref-type="bibr" rid="b49">49</xref>. <xref ref-type="disp-formula" rid="eq1">Equation (1)</xref> (see from<xref ref-type="bibr" rid="b49">49</xref>) was applied with time (<italic>t</italic>) replaced by volume (<italic>ϑ</italic>), to estimate the likelihood of incursion (‘incursion’ as per ‘incursion’ as per<xref ref-type="bibr" rid="b49">49</xref>) and establishment by <italic>H. armigera</italic>:</p><p><disp-formula id="eq1"><inline-graphic id="d32e650" xlink:href="srep45302-m1.jpg"></inline-graphic></disp-formula></p><p>where <italic>L</italic> is the likelihood of incursion, <italic>p</italic> is the probability of incursion when importing one unit of volume of the product<xref ref-type="bibr" rid="b51">51</xref>, and <italic>ϑ</italic> is product units (note that 1−<italic>p</italic> represents the probability that <italic>H. armigera</italic> will not invade a location in a particular year of trade).</p><p>We inferred the volume units by calculating the ratio per commodity (i.e., HS codes 06, 07, 08) and for overall trade volume (HS codes 06 + 07 + 08), by dividing individual trade volumes per region (i.e., Asia, Africa, Europe, Australasia) per year by the highest trade volume for the HS code commodity in question (i.e., such that the highest volume for the particular HS code is equal to 1). This assessment of likelihood based on a semi-quantitative method relies on language-based likelihoods by intervals of probability (i.e., ‘high’ = 0.7–1.0; ‘Moderate’ = 0.3–0.7; ‘Low’ = 0.05–0.3)<xref ref-type="bibr" rid="b49">49</xref><xref ref-type="bibr" rid="b51">51</xref>. For <italic>H. armigera</italic>, we used the probability threshold of 0.7 to conservative represent the ‘lower end’ of high-risk likelihood of an incursion.</p></sec></sec><sec disp-level="1"><title>Results</title><sec disp-level="2"><title>MtDNA diversity</title><p>We analysed 945 bp (i.e., 511 bp COI; 434 bp Cyt <italic>b</italic>) from 443<italic>H. armigera</italic> individuals (Brazil: <italic>N</italic> = 114; Old world/Australasia: <italic>N</italic> = 329) and identified 97 haplotypes, including 20 from Brazil (<xref ref-type="supplementary-material" rid="S1">Suppl. Table 1</xref>). These samples were compared to those reported previously<xref ref-type="bibr" rid="b27">27</xref><xref ref-type="bibr" rid="b29">29</xref>, with additional samples from Chad (<italic>N</italic> = 6), Cameroon (<italic>N</italic> = 13), Senegal (<italic>N</italic> = 11), Ghana (<italic>N</italic> = 4), Madagascar (<italic>N</italic> = 14), Spain (<italic>N</italic> = 6), France/French Corsica (<italic>N</italic> = 17), and New Zealand (<italic>N</italic> = 9) (<xref ref-type="supplementary-material" rid="S1">Suppl. Table 1</xref>) also included in our analyses. 21 new mtDNA COI (GenBank: KX494879-KX494899) and 10 new Cyt <italic>b</italic> haplotypes (GenBank: KX494900-KX494909) were identified in Senegal, Madagascar, Chad, Cameroon, Spain, French Corsica, New Zealand, and Brazil (<xref ref-type="supplementary-material" rid="S1">Suppl. Table 2</xref>). Concatenating the partial gene haplotypes generated the 97<italic>H. armigera</italic> haplotypes mentioned above, and eight of the 20 Brazilian haplotypes have never been reported (<xref ref-type="supplementary-material" rid="S1">Suppl. Table 2</xref>).</p></sec><sec disp-level="2"><title>Mitochondrial DNA haplotype diversity of <italic>H. armigera</italic></title><p>Estimates of haplotype and nucleotide diversity among samples of <italic>H. armigera</italic> from Brazil, the Old World, and the globe are provided in <xref ref-type="table" rid="t1">Table 1</xref>. The haplotype diversity estimate for Brazil was 0.753, while that for the Old World was 0.820. However, these values overlap when their standard deviations are taken into account. The haplotype network showed a high level of complexity, but lacked obvious population/haplotype cluster patterns (<xref ref-type="supplementary-material" rid="S1">Suppl. Fig. 1</xref>). Five haplotypes were found in Brazil and one other country (i.e., Madagascar, Chad, India, China, France), implying five possible sources for incursions into Brazil. The lack of distinct clusters within Brazil is consistent with earlier studies (e.g.<xref ref-type="bibr" rid="b27">27</xref><xref ref-type="bibr" rid="b29">29</xref><xref ref-type="bibr" rid="b35">35</xref><xref ref-type="bibr" rid="b36">36</xref>) involving the new Brazilian populations and indicating high mobility in this species.</p><p>Trade data on horticultural and agricultural commodities into Brazil showed that we lacked samples from countries with significant export or re-export activities to Brazil (e.g., Israel, Tunisia, Turkey, Thailand, Egypt, South Africa, Nigeria, Italy, The Netherlands, Greece), with these countries being possible origins of novel and unique Brazilian haplotypes. Our mtDNA analysis also identified globally distributed haplotypes (e.g., Hap0101, Hap0108, Hap0111, Hap0201; <xref ref-type="supplementary-material" rid="S1">Suppl. Tables 1 and 2</xref>; <xref ref-type="supplementary-material" rid="S1">Suppl. Figs 1 and 2</xref>), suggesting that while some haplotypes might allow us to identify origins of introduction, others are too widespread to offer an insight into incursion sources.</p></sec><sec disp-level="2"><title>Phylogenetic analysis of the molecular data</title><p>The inferred phylogeny (<xref ref-type="fig" rid="f2">Fig. 2</xref>; HKY + R2 optimal sequence evolution model) is characterized by an abundance of polytomies, likely due to the low number of parsimony-informative sites. In some cases, the bootstrap scores (indicated for selected edges) are high (e.g., 321_Hap5131; 314_Hap5131), implying that the data are phylogenetically consistent for these sequences, but in the majority of cases are far below 100% due to phylogenetically inconsistent sequence data. The jackknife scores (i.e., for assessing the impact of incomplete taxon sampling) were generally high (<xref ref-type="fig" rid="f2">Fig. 2</xref>), suggesting that our taxon sampling for this study is unlikely to be an issue.</p><p>The phylogeny reveals that the eight unique Brazilian haplotypes are often not as closely related to one another as they are to a haplotype found in Australia (Hap1001, Hap3001, Hap0404 or Hap0105), New Zealand (Hap4701), China (Hap1001), India (Hap1001 or Hap1009), Burkina Faso (Hap1001), Uganda (Hap0404) or Senegal (Hap3401). Of these seven non-Brazilian haplotypes (i.e., Hap1001, Hap3001, Hap0404, Hap0105, Hap4701, Hap1009, Hap3401) found in distant locations, five are reported from only one country (i.e., Australia, New Zealand, India, Senegal). Therefore, it is possible that these eight uniquely Brazilian haplotypes could have originated from these populations, and perhaps also populations in Uganda, Burkina Faso, and China (<xref ref-type="supplementary-material" rid="S1">Suppl. Table 1</xref>), as supported also by genome-wide SNP data and pyrethroid resistance gene analysis<xref ref-type="bibr" rid="b52">52</xref>.</p><p>The phylogeny also reveals five haplotypes found in Brazil and one other country (i.e., France, Senegal, Ghana, India, and China). This result again suggests separate incursion events in addition to those mentioned above. Similarly, seven haplotypes were found in Brazil and in more than one other country (<xref ref-type="supplementary-material" rid="S1">Suppl. Table 2</xref>). The geographical distributions of these seven haplotypes also hint of multiple incursions (i.e., ≥three countries), however, the evolutionary relationship among these seven haplotypes is unclear (<xref ref-type="fig" rid="f2">Fig. 2</xref>). Taken as a whole, mtDNA haplotype analyses support multiple and perhaps continuous incursions of <italic>H. armigera</italic> into Brazil. At this early incursion stage, there exist at least 20<italic>H. armigera</italic> maternal lineages in Brazil. Of these, eight are unique to Brazil and their close evolutionary relationship with haplotypes found in other countries suggests that they are unlikely to be the result of recent divergence (<italic>c.f</italic>.<xref ref-type="bibr" rid="b35">35</xref>).</p></sec><sec disp-level="2"><title>Trade data</title><p>Trade data from 2002–2013 indicate an approximately fourfold increase in activity from Asia into Brazil with limited imports originating from Australasia (Australia, New Zealand). Within Asia; India, Thailand, Israel, Turkey and China were the main trading partners although others (e.g., Japan, Malaysia, South Korea, Sri Lanka, Lebanon, Saudi Arabia, United Arab Emirates, Syria) also had significant trade activity with Brazil over the surveyed period.</p><p>Significant exports to Brazil of HS code 06 commodities (Living Trees and Other Plants; <xref ref-type="supplementary-material" rid="S1">Suppl. Table 3</xref>) were identified from European countries (<xref ref-type="supplementary-material" rid="S1">Suppl. Fig. 5</xref>), including The Netherlands, France, Italy, Spain, Germany, Belgium, Luxemburg, Denmark, Greece, Portugal, Great Britain, and Ireland. During the 12-year period surveyed, the African continent exported high volume of HS code 07 commodities (Edible Vegetables, including Certain Roots and Tubers; <xref ref-type="supplementary-material" rid="S1">Suppl. Table 4</xref>). Over the period 2007–2012, there were significant imports of fresh or chilled vegetables from Egypt (<xref ref-type="supplementary-material" rid="S1">Suppl. Fig. 6</xref>), with a drop in (or absence of) this trade from Europe and Asia. European countries exported high volumes of HS code 08 commodities (Edible Fruits and Nuts, Peel of Citrus/Melons; <xref ref-type="supplementary-material" rid="S1">Suppl. Table 5</xref>) to Brazil, with a fourfold increase in trade since 2002 from Asia and a sevenfold increase in trade volume from New Zealand (<xref ref-type="supplementary-material" rid="S1">Suppl. Fig. 7</xref>).</p></sec><sec disp-level="2"><title>Trade volume and associated biosecurity import risk analysis</title><p>The biosecurity import risks of <italic>H. armigera</italic> increased expectedly with increasing trade volume (<xref ref-type="fig" rid="f3">Fig. 3</xref>; <xref ref-type="supplementary-material" rid="S1">Suppl. Figs 5, 6 and 7</xref>). For HS code 6 commodities, there was a moderate-to-high import risk (i.e., likelihood from 0.42 to 0.70) between 2008 and 2012 for products from Europe, followed by products from Asia with a likelihood of import risk that rapidly increased from ‘low’ (i.e., 0.07) in 2008 to moderate (i.e., 0.37) in 2012. For HS code 07 commodities, the likelihood of the <italic>H. armigera</italic> import risk from African products spiked at 0.7 (i.e., high) in 2010, and at ‘moderate risk levels’ (i.e., 0.3, 0.4 and 0.5) in 2002, 2007, and 2012, respectively, from Asian products. Import risks from <italic>H. armigera</italic> for HS code 08 commodities was the greatest from Europe, rapidly increasing from 0.15 (i.e., ‘low’) to 0.7 (i.e., ‘high’) over the 12 years surveyed, while those for the other three continents also grew from ≤0.01 (i.e., negligible/very low) to approximately 0.16 (i.e., low). When combining all three HS codes of commodities (<xref ref-type="fig" rid="f3">Fig. 3</xref>), the biosecurity import risk likelihood was similar to that for HS code 08, although the likelihood was slightly higher (but still ‘low’) for Asia (0.03 in 2002, to 0.23 in 2012), Australasia (0.0003 in 2002, to 0.09 in 2012) and Africa (0.008 in 2002, to 0.05 in 2012).</p></sec></sec><sec disp-level="1"><title>Discussion</title><p>By combining multiple mtDNA markers and increasing global sampling sites, we identified Asia (i.e., China, India), Africa (i.e., Madagascar, Senegal) and Europe (i.e., France) as potential origins of Brazilian <italic>H. armigera</italic>, and inferred incursion pathways by combining genetic and trade data. This approach may be relevant to other invasive organisms with high effective population sizes, such as the soybean stem fly (SSF) <italic>Melanagromyza sojae</italic><xref ref-type="bibr" rid="b53">53</xref>, the whitefly <italic>Bemisia tabaci</italic> cryptic species complex (e.g.<xref ref-type="bibr" rid="b54">54</xref>), the spotted-wing vinegar fruit fly <italic>Drosophila suzukii</italic><xref ref-type="bibr" rid="b55">55</xref>, the European Grapevine moth <italic>Lobesia botrana</italic><xref ref-type="bibr" rid="b56">56</xref><xref ref-type="bibr" rid="b57">57</xref>, and the Russian Wheat Aphid <italic>Diuraphis noxia</italic> and incorporating genetic signatures of endosymbiont bacteria (e.g.<xref ref-type="bibr" rid="b58">58</xref>), amongst other.</p><p>Leite <italic>et al</italic>.<xref ref-type="bibr" rid="b35">35</xref> compared the standard barcode mtDNA COI region of Brazilian <italic>H. armigera</italic> to publicly available mtDNA COI haplotypes from the Old World, and identified Asian (i.e., China) and European maternal lineages in Brazil, based on shared haplotypes. Africa, Australia and Pakistan were not identified as potential origins due to poor availability of sequence data from these countries. Furthermore, common global haplotypes shared widely between Brazil and Old World locations also reduced the power of detecting potential origins. We showed that these regions, especially China, India, and France, were significant export countries of live host material capable of supporting <italic>H. armigera</italic> into Brazil, thereby supporting the notion of increased international trade activities as risks factors<xref ref-type="bibr" rid="b1">1</xref><xref ref-type="bibr" rid="b59">59</xref>.</p><p>Rumours of ‘agricultural bioterrorism’ have surfaced periodically in Brazil (e.g., <underline>Jornal diz que ocorrência de lagarta pode ser bioterrorismo</underline>; <underline>New threat to Brazil’s breadbasket: a pesky caterpillar</underline>; <underline>The Helicoverpa armigera</underline>). The diverse origins of <italic>H. armigera</italic> detected in Brazil would mean it is highly unlikely there can have been a deliberate release of this pest. Previously, Spanish plant products were identified as the commodity category where most <italic>H. armigera</italic> interceptions occurred in the EU<xref ref-type="bibr" rid="b60">60</xref>. This is in general agreement with our trade data patterns, although we also identified France, Italy and The Netherlands as countries with significant export activities to Brazil. Since 2008<italic>H. armigera</italic> has been ‘deregulated’ in Europe for trade involving cut flowers from Africa<xref ref-type="bibr" rid="b61">61</xref>. Much of these horticultural/agricultural goods are exported to third countries including Brazil. This suggests that Europe might also be the route of introduction, and highlights the potential global impact of regional phytosanitary policies. The general lack of agricultural trade with Australia could explain the absence of unique Australian haplotypes in our Brazilian data. Interestingly, <italic>H. armigera</italic> was detected in 2014 in <italic>Capsicum</italic> sp. from the Dominican Republic into the EU<xref ref-type="bibr" rid="b62">62</xref>, a first reported incidence of a New World to Old World reintroduction.</p><p>A common finding between previous (e.g.<xref ref-type="bibr" rid="b27">27</xref><xref ref-type="bibr" rid="b34">34</xref><xref ref-type="bibr" rid="b35">35</xref>) and this study is the high genetic mtDNA haplotype diversity in the Brazilian populations, which is unusual for a recently introduced pest. Eight haplotypes (<xref ref-type="supplementary-material" rid="S1">Suppl. Tables 1 and 2</xref>) represented unique maternal lineages not currently known from Old World populations. Matching of these to better identify additional potential origins of <italic>H. armigera</italic> in Brazil will require sampling countries with substantial agricultural commodity exports to Brazil. Despite the lack of substantial trade in agricultural and horticultural commodities with Brazil, a Malagasy haplotype (Hap0208) was identified. Population movement of <italic>H. armigera</italic> between Madagascar and neighbouring African nations is currently unknown but significant trade does occur between South Africa and Brazil. It may be that this haplotype represents a general ‘southern African’ haplotype and is present in both South Africa and Madagascar.</p><p>The discovery of Asian and African/European haplotypes offers unique insights into two potential introduction pathways in Brazil: natural (chance) dispersals, and human-mediated dispersal. Our finding that Senegal, Madagascar, French Corsica and Brazilian populations share the same unique haplotypes could indicate chance dispersal from the African continent, as well as human mediated introductions from Asia and Europe. Insect dispersals from Africa to the New World are hypothesised to associate with easterly winds (e.g.<xref ref-type="bibr" rid="b63">63</xref>). Knowing the potential origins of <italic>H. armigera</italic> in Brazil will provide valuable insights for its managing in the New World. In Cameroon, China and India, <italic>H. armigera</italic> carries resistance to synthetic pyrethroids<xref ref-type="bibr" rid="b64">64</xref><xref ref-type="bibr" rid="b65">65</xref><xref ref-type="bibr" rid="b66">66</xref>, organophosphates<xref ref-type="bibr" rid="b67">67</xref><xref ref-type="bibr" rid="b68">68</xref> and carbamates<xref ref-type="bibr" rid="b69">69</xref><xref ref-type="bibr" rid="b70">70</xref>. Resistance to diverse classes of pyrethroids has also been reported in populations from Benin (west Africa)<xref ref-type="bibr" rid="b71">71</xref>. In southern France, pyrethroid-resistance <italic>H. armigera</italic> was also reported<xref ref-type="bibr" rid="b72">72</xref><xref ref-type="bibr" rid="b73">73</xref>, while populations resistant to pyrethroids, organophosphates and carbamates were identified in Spain<xref ref-type="bibr" rid="b74">74</xref><xref ref-type="bibr" rid="b75">75</xref>. Significant reduced susceptibility to Cry1Ac has also been detected in some Chinese <italic>H. armigera</italic> populations<xref ref-type="bibr" rid="b76">76</xref>, and <italic>H. armigera</italic> larvae on Bt cotton (BG-II) which has <italic>cry1Ac</italic>+ <italic>cry2Ab</italic> genes exists in India<xref ref-type="bibr" rid="b77">77</xref>.</p><p>In Brazil, farmers reported difficulties managing <italic>H. armigera</italic> and overused insecticides to restrict its outbreak<xref ref-type="bibr" rid="b78">78</xref>, potentially reflecting insecticide resistances in the introduced populations. This is supported by Anderson <italic>et al</italic>.<xref ref-type="bibr" rid="b52">52</xref> where Brazilian <italic>H. armigera</italic> grouped with Asian individuals for an allele for pyrethroid resistance in <italic>H. armigera</italic> sampled during this early stage of incursion. Population-wide studies (e.g.<xref ref-type="bibr" rid="b52">52</xref>) will therefore provide a starting point for prioritising screens for resistance in chemistries (organophosphates, carbamates, Cry1Ac, Cry2Ab) that are likely to be present in source populations and which have high use in the New World. This information will be critical for developing strategies to manage the further evolution of insecticide resistance and for the management of <italic>H. armigera</italic> elsewhere, including the re-introduction of <italic>H. armigera</italic> back into the Old World with heightened resistance acquired in the New World, and the potential spread into the North American final frontier.</p><p>While it may have been possible to eliminate the initial <italic>H. armigera</italic> population(s) in Brazil (assuming single incursion event), this is now unlikely given shared geographical boundaries and similar economic activities. <italic>H. armigera</italic>’s presence in the New World may also have been as early as the mid-2000’s, with individuals intercepted in 2006 in a Peruvian “mange-tout” bean consignment found to possess COI haplotypes (630 bp) that matched those from China, Spain, Uganda and Egypt<xref ref-type="bibr" rid="b79">79</xref>. This suggests that incursions into Brazil may well have involved neighbouring countries, and reinforcing the need to coordinate and co-operate in the area of biosecurity. Indeed, the study of Lopes-da-Silva <italic>et al</italic>.<xref ref-type="bibr" rid="b36">36</xref> has shown that at least in Brazil, there has been an increase in frequencies of incursions by exotic agricultural insect pests since the early 1900’s, with at least two more exotic insect pest incursions being reported in recent times (e.g.<xref ref-type="bibr" rid="b80">80</xref><xref ref-type="bibr" rid="b81">81</xref>). On-going monitoring of New World <italic>H. armigera</italic> populations though genetic analysis of quarantine-intercepted material will contribute to mapping its New World spread, thereby enabling early intervention via regional-specific pest management strategies to achieve their intended efficacies.</p></sec><sec disp-level="1"><title>Additional Information</title><p><bold>How to cite this article:</bold> Tay, W. T. <italic>et al</italic>. Mitochondrial DNA and trade data support multiple origins of <italic>Helicoverpa armigera</italic> (Lepidoptera, Noctuidae) in Brazil. <italic>Sci. Rep.</italic><bold>7</bold>, 45302; doi: 10.1038/srep45302 (2017).</p><p><bold>Publisher's note:</bold> Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></sec><sec sec-type="supplementary-material" id="S1"><title>Supplementary Material</title><supplementary-material id="d32e23" content-type="local-data"><caption><title>Supplementary Figures and Tables</title></caption><media xlink:href="srep45302-s1.pdf"></media></supplementary-material></sec></body><back><ack><p>ESC and IBM were supported by CSIRO Health and Biosecurity, the Brazilian Government’s, Science without Boarders (Ciência sem Fronteiras) summer internship program (242166/2012–1 (ESC); 209297/2013-1 (IBM)), and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) scholarships. CA was supported by a CSIRO OCE Post Doctoral Fellowship (R-03255-01). WTT and TKW acknowledged funing support from CSIRO Health & Biosecurity ‘Genes of Biosecurity Significance’ (R-8681-1). CC acknowledges funding support from FAPEG (Fundação de amparo a pesquisa do estado de Goiás) (Grant number: Helicoverpa/2013102670001419). Ghana samples were provided by Ibrahim Atokple. William James (CSIRO) assisted in the laboratory. Dean Paini, John Oakeshott (CSIRO) and Jonas Arnemann (UFSM, Brazil) provided helpful discussion.</p></ack><ref-list><ref id="b1"><mixed-citation publication-type="journal"><name><surname>Hulme</surname><given-names>P. 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L.</given-names></name> & <name><surname>Specht</surname><given-names>A.</given-names></name><article-title><italic>Lasiothyris luminosa</italic> (Razowski & Becker) (Lepidoptera: Tortricidae): a New Grapevine Pest in Northeastern Brazil</article-title>. <source>Neotrop Entomol</source><volume>45</volume>, <fpage>336</fpage>–<lpage>339</lpage>, doi: <pub-id pub-id-type="doi">10.1007/s13744-016-0379-9</pub-id> (<year>2016</year>).<pub-id pub-id-type="pmid">26957083</pub-id></mixed-citation></ref></ref-list><fn-group><fn fn-type="COI-statement"><p>The authors declare no competing financial interests.</p></fn><fn><p><bold>Author Contributions</bold> Project design: W.T.T., T.K.W., S.D., C.C., K.H.J.G. Laboratory work: W.T.T., T.K.W., E.S.C., I.B.M., C.A., M.C.P., G.T.B. Field data collection: M.F.S., M.F., C.C. Genetic data analysis: W.T.T., T.W., E.S.C., I.B.M., L.S.J., G.T.B., T.K.F.W., C.A., M.C.P. Project data coordination: P.S., C.C., S.D. Manuscript preparation: W.T.T., T.K.W., S.D., L.S.J., G.T.B., P.S., M.F., K.H.J.G., C.C. All authors gave final approval for publication.</p></fn></fn-group></back><floats-group><fig id="f1"><label>Figure 1</label><caption><title><italic>Helicoverpa armigera</italic> sampling sites from Brazil (BRA) (States of Goiás, Minas Gerais, Paraná, Bahia, Maranhão, Mato Grosso), Europe (France (FRA) (Montpellier, French Corsica), Spain (ESP) (Seville)), Africa (Ghana (GHA), Uganda (UGA), Burkina Faso (BFA), Chad TCD), Madagascar (MDG), Cameroon (CMR), Senegal (SEN)), Australasia (Australia (AUS) (State of Victoria), New Zealand (NZL) (Auckland)), Asia (China (CHN) (Shandong Province), India (IND) (States of Punjab, Maharashtra, Andhra Pradesh, Tamil Nadu, Telangana), and Pakistan (PAK) (Multan).</title><p>Map created using Mapchart <ext-link ext-link-type="uri" xlink:href="https://mapchart.net">https://mapchart.net</ext-link>. See <xref ref-type="supplementary-material" rid="S1">Supplementary Table 1</xref> for sampling details].</p></caption><graphic xlink:href="srep45302-f1"></graphic></fig><fig id="f2"><label>Figure 2</label><caption><title>Phylogenetic relationships among the 97 <italic>Helicoverpa armigera</italic> mtDNA haplotypes (some haplotypes are in duplicate to ensure that parsimony-informative splits in the data are represented in the tree).</title><p>Names of sequences are represented by individual ID (see <xref ref-type="supplementary-material" rid="S1">Suppl. Table 1</xref>) followed by haplotype ID (see <xref ref-type="supplementary-material" rid="S1">Suppl. Table 2</xref>). Sequence discussed in the main text are in bold. Blue edges indicate Brazilian unique haplotypes; red edges indicate haplotypes found in Brazil and one other country; grey edges indicate haplotypes found in Brazil and more than one other country. Bootstrap scores (from 10,000 replicates) for selected edges are shown in a light font; jackknife scores (from 200,000 replicates) for selected edges are shown in a bold font.</p></caption><graphic xlink:href="srep45302-f2"></graphic></fig><fig id="f3"><label>Figure 3</label><caption><title>Combined export trade volume from Asia, Africa, Europe and Australasia continents to Brazil.</title><p>Data are for 12-years period (2002–2013; X-axis) for Harmonized commodity description and coding system (HS) codes 06, 07 and 08 (<xref ref-type="supplementary-material" rid="S1">Suppl. Tables 3, 4 and 5</xref>) in USD$ (left Y-axis). Biosecurity entry risk factor (orange doted lines, right Y-axis) for <italic>H. armigera</italic> that considered introduction, establishment and population spread as calculated for trade volume per year by continental regions are also shown.</p></caption><graphic xlink:href="srep45302-f3"></graphic></fig><table-wrap position="float" id="t1"><label>Table 1</label><caption><title>Haplotype (<italic>h</italic>) and nucleotide (<italic>π</italic>) diversity estimates among mtDNA samples of <italic>Helicoverpa armigera</italic> from Brazil, the Old World, and the globe (the global data combined all populations from the Old World and Brazil), SD = standard deviation.</title></caption><table frame="hsides" rules="groups" border="1"><colgroup><col align="left"></col><col align="center"></col><col align="center"></col><col align="center"></col></colgroup><thead valign="bottom"><tr><th align="left" valign="top" charoff="50"> </th><th align="center" valign="top" charoff="50">No. haplotypes</th><th align="center" valign="top" charoff="50"><italic>h</italic> (±SD)</th><th align="center" valign="top" charoff="50">π (±SD)</th></tr></thead><tbody valign="top"><tr><td align="left" valign="top" charoff="50">Old World</td><td align="center" valign="top" charoff="50">75</td><td align="center" valign="top" charoff="50">0.820 (±0.0005)</td><td align="center" valign="top" charoff="50">0.0029 (±0.0003)</td></tr><tr><td align="left" valign="top" charoff="50">Brazil</td><td align="center" valign="top" charoff="50">20</td><td align="center" valign="top" charoff="50">0.753 (±0.0360)</td><td align="center" valign="top" charoff="50">0.0028 (±0.0005)</td></tr><tr><td align="left" valign="top" charoff="50">Global</td><td align="center" valign="top" charoff="50">97</td><td align="center" valign="top" charoff="50">0.806 (±0.0190)</td><td align="center" valign="top" charoff="50">0.0029 (±0.0002)</td></tr></tbody></table></table-wrap></floats-group></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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