Population genomics of Digitaria insularis from soybean areas in Brazil
BACKGROUND Digitaria insularis is a weed species that has gained considerable importance in Brazil's soybean production areas that rely on glyphosate‐resistant cultivars. Herbicide‐resistant weed populations of this species have been reported in many regions in Brazil, first in the south, follo...
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creator | Gonçalves Netto, Acácio Cordeiro, Erick MG Nicolai, Marcelo Carvalho, Saul JP Ovejero, Ramiro Fernando Lopez Brunharo, Caio ACG Zucchi, Maria I Christoffoleti, Pedro J |
description | BACKGROUND
Digitaria insularis is a weed species that has gained considerable importance in Brazil's soybean production areas that rely on glyphosate‐resistant cultivars. Herbicide‐resistant weed populations of this species have been reported in many regions in Brazil, first in the south, followed by later reports in the north. We hypothesized that the spread of herbicide‐resistant D. insularis is facilitated by movement of agricultural machinery from the southern regions of Brazil.
RESULTS
Population genomics revealed a weak or no genetic structure (FST = [0; 0.16]), moderate expected heterozygosity (HE = 0.15; 0.44) and low inbreeding (FIS = [−0.1; 0.1]) in D. insularis populations. Our data supported the hypothesis that herbicide resistance gene flow predominantly occurred in a south‐to‐north direction based on a migration analysis. We also found evidence of local adaptation of resistant populations in the northern soybean‐growing regions of Brazil.
CONCLUSION
Evidence in our work suggests that gene flow of glyphosate‐resistant D. insularis is associated with movement of agricultural machinery, although local selection pressure seems to play an important role in the evolution of herbicide resistance throughout the country. Our results suggest preventive practices such as equipment sanitation should be implemented to limit the spread of herbicide resistant D. insularis. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
An agricultural machine transporting Digitaria insularisacross the country. This represents our results that glyphosate‐resistant D. insularis was likely dispersed via movement of agricultural machinery from the south to the north. |
doi_str_mv | 10.1002/ps.6577 |
format | Article |
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Digitaria insularis is a weed species that has gained considerable importance in Brazil's soybean production areas that rely on glyphosate‐resistant cultivars. Herbicide‐resistant weed populations of this species have been reported in many regions in Brazil, first in the south, followed by later reports in the north. We hypothesized that the spread of herbicide‐resistant D. insularis is facilitated by movement of agricultural machinery from the southern regions of Brazil.
RESULTS
Population genomics revealed a weak or no genetic structure (FST = [0; 0.16]), moderate expected heterozygosity (HE = 0.15; 0.44) and low inbreeding (FIS = [−0.1; 0.1]) in D. insularis populations. Our data supported the hypothesis that herbicide resistance gene flow predominantly occurred in a south‐to‐north direction based on a migration analysis. We also found evidence of local adaptation of resistant populations in the northern soybean‐growing regions of Brazil.
CONCLUSION
Evidence in our work suggests that gene flow of glyphosate‐resistant D. insularis is associated with movement of agricultural machinery, although local selection pressure seems to play an important role in the evolution of herbicide resistance throughout the country. Our results suggest preventive practices such as equipment sanitation should be implemented to limit the spread of herbicide resistant D. insularis. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
An agricultural machine transporting Digitaria insularisacross the country. This represents our results that glyphosate‐resistant D. insularis was likely dispersed via movement of agricultural machinery from the south to the north.</description><identifier>ISSN: 1526-498X</identifier><identifier>EISSN: 1526-4998</identifier><identifier>DOI: 10.1002/ps.6577</identifier><identifier>PMID: 34302709</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>adaptation ; admixture ; Agricultural equipment ; Brazil ; Chemical pest control ; Crop production ; Cultivars ; Digitaria ; Digitaria insularis ; Farm machinery ; Flow resistance ; Gene flow ; Genetic structure ; Genomics ; Glycine max - genetics ; Glyphosate ; glyphosate resistance ; Herbicide resistance ; Herbicide Resistance - genetics ; Herbicides ; Herbicides - pharmacology ; Heterozygosity ; Inbreeding ; Metagenomics ; Pest control ; Plant Weeds ; Populations ; Sanitation ; sourgrass ; Soybeans ; weed genomics ; Weeds</subject><ispartof>Pest management science, 2021-12, Vol.77 (12), p.5375-5381</ispartof><rights>2021 The Authors. published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.</rights><rights>2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.</rights><rights>2021. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4337-4b02a5a4e1935e8d3c56598e35384377e9b8d1105c386ab5785e91664ade8e323</citedby><cites>FETCH-LOGICAL-c4337-4b02a5a4e1935e8d3c56598e35384377e9b8d1105c386ab5785e91664ade8e323</cites><orcidid>0000-0003-4500-6302 ; 0000-0001-9735-1648 ; 0000-0002-4863-1843 ; 0000-0003-2926-968X ; 0000-0003-4031-7179 ; 0000-0002-8558-6922 ; 0000-0001-9741-3992 ; 0000-0002-2741-5615</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fps.6577$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fps.6577$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,1411,27903,27904,45553,45554</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34302709$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gonçalves Netto, Acácio</creatorcontrib><creatorcontrib>Cordeiro, Erick MG</creatorcontrib><creatorcontrib>Nicolai, Marcelo</creatorcontrib><creatorcontrib>Carvalho, Saul JP</creatorcontrib><creatorcontrib>Ovejero, Ramiro Fernando Lopez</creatorcontrib><creatorcontrib>Brunharo, Caio ACG</creatorcontrib><creatorcontrib>Zucchi, Maria I</creatorcontrib><creatorcontrib>Christoffoleti, Pedro J</creatorcontrib><title>Population genomics of Digitaria insularis from soybean areas in Brazil</title><title>Pest management science</title><addtitle>Pest Manag Sci</addtitle><description>BACKGROUND
Digitaria insularis is a weed species that has gained considerable importance in Brazil's soybean production areas that rely on glyphosate‐resistant cultivars. Herbicide‐resistant weed populations of this species have been reported in many regions in Brazil, first in the south, followed by later reports in the north. We hypothesized that the spread of herbicide‐resistant D. insularis is facilitated by movement of agricultural machinery from the southern regions of Brazil.
RESULTS
Population genomics revealed a weak or no genetic structure (FST = [0; 0.16]), moderate expected heterozygosity (HE = 0.15; 0.44) and low inbreeding (FIS = [−0.1; 0.1]) in D. insularis populations. Our data supported the hypothesis that herbicide resistance gene flow predominantly occurred in a south‐to‐north direction based on a migration analysis. We also found evidence of local adaptation of resistant populations in the northern soybean‐growing regions of Brazil.
CONCLUSION
Evidence in our work suggests that gene flow of glyphosate‐resistant D. insularis is associated with movement of agricultural machinery, although local selection pressure seems to play an important role in the evolution of herbicide resistance throughout the country. Our results suggest preventive practices such as equipment sanitation should be implemented to limit the spread of herbicide resistant D. insularis. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
An agricultural machine transporting Digitaria insularisacross the country. This represents our results that glyphosate‐resistant D. insularis was likely dispersed via movement of agricultural machinery from the south to the north.</description><subject>adaptation</subject><subject>admixture</subject><subject>Agricultural equipment</subject><subject>Brazil</subject><subject>Chemical pest control</subject><subject>Crop production</subject><subject>Cultivars</subject><subject>Digitaria</subject><subject>Digitaria insularis</subject><subject>Farm machinery</subject><subject>Flow resistance</subject><subject>Gene flow</subject><subject>Genetic structure</subject><subject>Genomics</subject><subject>Glycine max - genetics</subject><subject>Glyphosate</subject><subject>glyphosate resistance</subject><subject>Herbicide resistance</subject><subject>Herbicide Resistance - genetics</subject><subject>Herbicides</subject><subject>Herbicides - pharmacology</subject><subject>Heterozygosity</subject><subject>Inbreeding</subject><subject>Metagenomics</subject><subject>Pest control</subject><subject>Plant Weeds</subject><subject>Populations</subject><subject>Sanitation</subject><subject>sourgrass</subject><subject>Soybeans</subject><subject>weed genomics</subject><subject>Weeds</subject><issn>1526-498X</issn><issn>1526-4998</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>EIF</sourceid><recordid>eNp1kF1LwzAUhoMoTqf4DyTghRfSmY-mSW4EnTqFgQMVvAtpm86MrqlJq8xfb-fm0AuvzoH34TmHF4AjjAYYIXJeh0HCON8Ce5iRJIqlFNubXbz0wH4IM4SQlJLsgh6NKSIcyT0wmri6LXVjXQWnpnJzmwXoCnhtp7bR3mpoq9AB3gZYeDeHwS1SoyuovdGhC-GV15-2PAA7hS6DOVzPPni-vXka3kXjh9H98HIcZTGlPIpTRDTTscGSMiNymrGESWEooyKmnBuZihxjxDIqEp0yLpiROElinZuOIrQPLlbeuk3nJs9M1XhdqtrbufYL5bRVf5PKvqqpe1eSSMwZ7wQna4F3b60JjZq51lfdz4owyShFKFlSpysq8y4Eb4rNBYzUsnFVB7VsvCOPfz-04X4q7oCzFfBhS7P4z6Mmj9-6LzOAiUw</recordid><startdate>202112</startdate><enddate>202112</enddate><creator>Gonçalves Netto, Acácio</creator><creator>Cordeiro, Erick MG</creator><creator>Nicolai, Marcelo</creator><creator>Carvalho, Saul JP</creator><creator>Ovejero, Ramiro Fernando Lopez</creator><creator>Brunharo, Caio ACG</creator><creator>Zucchi, Maria I</creator><creator>Christoffoleti, Pedro J</creator><general>John Wiley & Sons, Ltd</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QR</scope><scope>7SS</scope><scope>7ST</scope><scope>7T7</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>SOI</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-4500-6302</orcidid><orcidid>https://orcid.org/0000-0001-9735-1648</orcidid><orcidid>https://orcid.org/0000-0002-4863-1843</orcidid><orcidid>https://orcid.org/0000-0003-2926-968X</orcidid><orcidid>https://orcid.org/0000-0003-4031-7179</orcidid><orcidid>https://orcid.org/0000-0002-8558-6922</orcidid><orcidid>https://orcid.org/0000-0001-9741-3992</orcidid><orcidid>https://orcid.org/0000-0002-2741-5615</orcidid></search><sort><creationdate>202112</creationdate><title>Population genomics of Digitaria insularis from soybean areas in Brazil</title><author>Gonçalves Netto, Acácio ; Cordeiro, Erick MG ; Nicolai, Marcelo ; Carvalho, Saul JP ; Ovejero, Ramiro Fernando Lopez ; Brunharo, Caio ACG ; Zucchi, Maria I ; Christoffoleti, Pedro J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4337-4b02a5a4e1935e8d3c56598e35384377e9b8d1105c386ab5785e91664ade8e323</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>adaptation</topic><topic>admixture</topic><topic>Agricultural equipment</topic><topic>Brazil</topic><topic>Chemical pest control</topic><topic>Crop production</topic><topic>Cultivars</topic><topic>Digitaria</topic><topic>Digitaria insularis</topic><topic>Farm machinery</topic><topic>Flow resistance</topic><topic>Gene flow</topic><topic>Genetic structure</topic><topic>Genomics</topic><topic>Glycine max - genetics</topic><topic>Glyphosate</topic><topic>glyphosate resistance</topic><topic>Herbicide resistance</topic><topic>Herbicide Resistance - genetics</topic><topic>Herbicides</topic><topic>Herbicides - pharmacology</topic><topic>Heterozygosity</topic><topic>Inbreeding</topic><topic>Metagenomics</topic><topic>Pest control</topic><topic>Plant Weeds</topic><topic>Populations</topic><topic>Sanitation</topic><topic>sourgrass</topic><topic>Soybeans</topic><topic>weed genomics</topic><topic>Weeds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gonçalves Netto, Acácio</creatorcontrib><creatorcontrib>Cordeiro, Erick MG</creatorcontrib><creatorcontrib>Nicolai, Marcelo</creatorcontrib><creatorcontrib>Carvalho, Saul JP</creatorcontrib><creatorcontrib>Ovejero, Ramiro Fernando Lopez</creatorcontrib><creatorcontrib>Brunharo, Caio ACG</creatorcontrib><creatorcontrib>Zucchi, Maria I</creatorcontrib><creatorcontrib>Christoffoleti, Pedro J</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Free Content</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Chemoreception Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environment Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Pest management science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gonçalves Netto, Acácio</au><au>Cordeiro, Erick MG</au><au>Nicolai, Marcelo</au><au>Carvalho, Saul JP</au><au>Ovejero, Ramiro Fernando Lopez</au><au>Brunharo, Caio ACG</au><au>Zucchi, Maria I</au><au>Christoffoleti, Pedro J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Population genomics of Digitaria insularis from soybean areas in Brazil</atitle><jtitle>Pest management science</jtitle><addtitle>Pest Manag Sci</addtitle><date>2021-12</date><risdate>2021</risdate><volume>77</volume><issue>12</issue><spage>5375</spage><epage>5381</epage><pages>5375-5381</pages><issn>1526-498X</issn><eissn>1526-4998</eissn><abstract>BACKGROUND
Digitaria insularis is a weed species that has gained considerable importance in Brazil's soybean production areas that rely on glyphosate‐resistant cultivars. Herbicide‐resistant weed populations of this species have been reported in many regions in Brazil, first in the south, followed by later reports in the north. We hypothesized that the spread of herbicide‐resistant D. insularis is facilitated by movement of agricultural machinery from the southern regions of Brazil.
RESULTS
Population genomics revealed a weak or no genetic structure (FST = [0; 0.16]), moderate expected heterozygosity (HE = 0.15; 0.44) and low inbreeding (FIS = [−0.1; 0.1]) in D. insularis populations. Our data supported the hypothesis that herbicide resistance gene flow predominantly occurred in a south‐to‐north direction based on a migration analysis. We also found evidence of local adaptation of resistant populations in the northern soybean‐growing regions of Brazil.
CONCLUSION
Evidence in our work suggests that gene flow of glyphosate‐resistant D. insularis is associated with movement of agricultural machinery, although local selection pressure seems to play an important role in the evolution of herbicide resistance throughout the country. Our results suggest preventive practices such as equipment sanitation should be implemented to limit the spread of herbicide resistant D. insularis. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
An agricultural machine transporting Digitaria insularisacross the country. This represents our results that glyphosate‐resistant D. insularis was likely dispersed via movement of agricultural machinery from the south to the north.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><pmid>34302709</pmid><doi>10.1002/ps.6577</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0003-4500-6302</orcidid><orcidid>https://orcid.org/0000-0001-9735-1648</orcidid><orcidid>https://orcid.org/0000-0002-4863-1843</orcidid><orcidid>https://orcid.org/0000-0003-2926-968X</orcidid><orcidid>https://orcid.org/0000-0003-4031-7179</orcidid><orcidid>https://orcid.org/0000-0002-8558-6922</orcidid><orcidid>https://orcid.org/0000-0001-9741-3992</orcidid><orcidid>https://orcid.org/0000-0002-2741-5615</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | adaptation admixture Agricultural equipment Brazil Chemical pest control Crop production Cultivars Digitaria Digitaria insularis Farm machinery Flow resistance Gene flow Genetic structure Genomics Glycine max - genetics Glyphosate glyphosate resistance Herbicide resistance Herbicide Resistance - genetics Herbicides Herbicides - pharmacology Heterozygosity Inbreeding Metagenomics Pest control Plant Weeds Populations Sanitation sourgrass Soybeans weed genomics Weeds |
title | Population genomics of Digitaria insularis from soybean areas in Brazil |
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