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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, foll...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9291757/ https://www.ncbi.nlm.nih.gov/pubmed/34302709 http://dx.doi.org/10.1002/ps.6577 |
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author | Gonçalves Netto, Acácio Cordeiro, Erick MG Nicolai, Marcelo de Carvalho, Saul JP Ovejero, Ramiro Fernando Lopez Brunharo, Caio ACG Zucchi, Maria I Christoffoleti, Pedro J |
author_facet | Gonçalves Netto, Acácio Cordeiro, Erick MG Nicolai, Marcelo de Carvalho, Saul JP Ovejero, Ramiro Fernando Lopez Brunharo, Caio ACG Zucchi, Maria I Christoffoleti, Pedro J |
author_sort | Gonçalves Netto, Acácio |
collection | PubMed |
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 (F (ST) = [0; 0.16]), moderate expected heterozygosity (H (E) = 0.15; 0.44) and low inbreeding (F (IS) = [−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. |
format | Online Article Text |
id | pubmed-9291757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley & Sons, Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92917572022-07-20 Population genomics of Digitaria insularis from soybean areas in Brazil Gonçalves Netto, Acácio Cordeiro, Erick MG Nicolai, Marcelo de Carvalho, Saul JP Ovejero, Ramiro Fernando Lopez Brunharo, Caio ACG Zucchi, Maria I Christoffoleti, Pedro J Pest Manag Sci Research Articles 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 (F (ST) = [0; 0.16]), moderate expected heterozygosity (H (E) = 0.15; 0.44) and low inbreeding (F (IS) = [−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. John Wiley & Sons, Ltd. 2021-08-17 2021-12 /pmc/articles/PMC9291757/ /pubmed/34302709 http://dx.doi.org/10.1002/ps.6577 Text en © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Gonçalves Netto, Acácio Cordeiro, Erick MG Nicolai, Marcelo de Carvalho, Saul JP Ovejero, Ramiro Fernando Lopez Brunharo, Caio ACG Zucchi, Maria I Christoffoleti, Pedro J Population genomics of Digitaria insularis from soybean areas in Brazil |
title | Population genomics of
Digitaria insularis
from soybean areas in Brazil
|
title_full | Population genomics of
Digitaria insularis
from soybean areas in Brazil
|
title_fullStr | Population genomics of
Digitaria insularis
from soybean areas in Brazil
|
title_full_unstemmed | Population genomics of
Digitaria insularis
from soybean areas in Brazil
|
title_short | Population genomics of
Digitaria insularis
from soybean areas in Brazil
|
title_sort | population genomics of
digitaria insularis
from soybean areas in brazil |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9291757/ https://www.ncbi.nlm.nih.gov/pubmed/34302709 http://dx.doi.org/10.1002/ps.6577 |
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