Literature DB >> 33155426

Population genomics of selectively neutral genetic structure and herbicide resistance in UK populations of Alopecurus myosuroides.

Andrea Dixon1,2, David Comont1, Gancho T Slavov1,3, Paul Neve1,4.   

Abstract

BACKGROUND: Alopecurus myosuroides (blackgrass) is a major weed in Europe with known resistance to multiple herbicide modes of action. In the UK, there is evidence that blackgrass has undergone a range expansion. In this paper, genotyping-by-sequencing and population-level herbicide resistance phenotypes are used to explore spatial patterns of selectively neutral genetic variation and resistance. We also perform a preliminary genome-wide association study (GWAS) and genomic prediction analysis to evaluate the potential of these approaches for investigating nontarget site herbicide resistance.
RESULTS: Blackgrass was collected from 47 fields across the British Isles and up to eight plants per field population (n = 369) were genotyped by Restriction site-associated DNA (RAD)-sequencing. A total of 20 426 polymorphic loci were identified and used for population genetic analyses. Phenotypic assays revealed significant variation in herbicide resistance between populations. Population structure was weak (FST = 0.024-0.048), but spatial patterns were consistent with an ongoing westward and northward range expansion. We detected strong and consistent Wahlund effects (FIS = 0.30). There were no spatial patterns of herbicide resistance or evidence for confounding with population structure. Using a combination of population-level GWAS and genomic prediction we found that the top 20, 200, and 2000 GWAS loci had higher predictive abilities for fenoxaprop resistance compared to all markers.
CONCLUSION: There is likely extensive human-mediated gene flow between field populations of the weed blackgrass at a national scale. The lack of confounding of adaptive and neutral genetic variation can enable future, more extensive GWAS analyses to identify the genetic architecture of evolved herbicide resistance.
© 2020 Society of Chemical Industry. © 2020 Society of Chemical Industry.

Entities:  

Keywords:  GWAS; RAD-sequencing; blackgrass; metabolic resistance; population genetics; population structure

Year:  2020        PMID: 33155426     DOI: 10.1002/ps.6174

Source DB:  PubMed          Journal:  Pest Manag Sci        ISSN: 1526-498X            Impact factor:   4.845


  5 in total

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Authors:  J Antonio Tafoya-Razo; Saul Alonso Mora-Munguía; Jesús R Torres-García
Journal:  Plants (Basel)       Date:  2022-06-22

2.  Intra- and interspecies competition of blackgrass and wheat in the context of herbicidal resistance and environmental conditions in Poland.

Authors:  Anna Wenda-Piesik; Agnieszka Synowiec; Katarzyna Marcinkowska; Barbara Wrzesińska; Cezary Podsiadło; Krzysztof Domaradzki; Piotr Kuc; Ewa Kwiecińska-Poppe
Journal:  Sci Rep       Date:  2022-05-24       Impact factor: 4.996

3.  Genomic-based epidemiology reveals independent origins and gene flow of glyphosate resistance in Bassia scoparia populations across North America.

Authors:  Karl Ravet; Crystal D Sparks; Andrea L Dixon; Anita Küpper; Eric P Westra; Dean J Pettinga; Patrick J Tranel; Joel Felix; Don W Morishita; Prashant Jha; Andrew Kniss; Phillip W Stahlman; Paul Neve; Eric L Patterson; Philip Westra; Todd A Gaines
Journal:  Mol Ecol       Date:  2021-10-21       Impact factor: 6.622

4.  Dissecting weed adaptation: Fitness and trait correlations in herbicide-resistant Alopecurus myosuroides.

Authors:  David Comont; Dana R MacGregor; Laura Crook; Richard Hull; Lieselot Nguyen; Robert P Freckleton; Dylan Z Childs; Paul Neve
Journal:  Pest Manag Sci       Date:  2022-05-09       Impact factor: 4.462

5.  Population genomics of Digitaria insularis from soybean areas in Brazil.

Authors:  Acácio Gonçalves Netto; Erick Mg Cordeiro; Marcelo Nicolai; Saul Jp de Carvalho; Ramiro Fernando Lopez Ovejero; Caio Acg Brunharo; Maria I Zucchi; Pedro J Christoffoleti
Journal:  Pest Manag Sci       Date:  2021-08-17       Impact factor: 4.462

  5 in total

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