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      Parallel and nonparallel genomic responses contribute to herbicide resistance in Ipomoea purpurea, a common agricultural weed

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          Abstract

          The repeated evolution of herbicide resistance has been cited as an example of genetic parallelism, wherein separate species or genetic lineages utilize the same genetic solution in response to selection. However, most studies that investigate the genetic basis of herbicide resistance examine the potential for changes in the protein targeted by the herbicide rather than considering genome-wide changes. We used a population genomics screen and targeted exome re-sequencing to uncover the potential genetic basis of glyphosate resistance in the common morning glory, Ipomoea purpurea, and to determine if genetic parallelism underlies the repeated evolution of resistance across replicate resistant populations. We found no evidence for changes in 5‐enolpyruvylshikimate‐3‐phosphate synthase ( EPSPS), glyphosate’s target protein, that were associated with resistance, and instead identified five genomic regions that showed evidence of selection. Within these regions, genes involved in herbicide detoxification—cytochrome P450s, ABC transporters, and glycosyltransferases—are enriched and exhibit signs of selective sweeps. One region under selection shows parallel changes across all assayed resistant populations whereas other regions exhibit signs of divergence. Thus, while it appears that the physiological mechanism of resistance in this species is likely the same among resistant populations, we find patterns of both similar and divergent selection across separate resistant populations at particular loci.

          Author summary

          Although there are many examples of herbicide resistance among natural populations of weeds, it is unknown if the same genetic mechanism underlies its repeated evolution across the landscape. Using a population genomics screen and exome re-sequencing, we examined the genetic basis of RoundUp resistance across populations of Ipomoea purpurea, a noxious agricultural weed. We identified multiple regions of the genome that exhibit signs of selection, and found genes involved in herbicide detoxification to be enriched within these regions. Interestingly, while one genomic region under selection exhibited a similar haplotype among resistant populations, other regions of the genome under selection exhibited signs of divergence. Overall, our results find evidence for both parallel and nonparallel genetic changes associated with resistance, suggesting there are more genetic avenues underlying the adaptation to herbicide than previously considered.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform

            Due to the increasing throughput of current DNA sequencing instruments, sample multiplexing is necessary for making economical use of available sequencing capacities. A widely used multiplexing strategy for the Illumina Genome Analyzer utilizes sample-specific indexes, which are embedded in one of the library adapters. However, this and similar multiplex approaches come with a risk of sample misidentification. By introducing indexes into both library adapters (double indexing), we have developed a method that reveals the rate of sample misidentification within current multiplex sequencing experiments. With ~0.3% these rates are orders of magnitude higher than expected and may severely confound applications in cancer genomics and other fields requiring accurate detection of rare variants. We identified the occurrence of mixed clusters on the flow as the predominant source of error. The accuracy of sample identification is further impaired if indexed oligonucleotides are cross-contaminated or if indexed libraries are amplified in bulk. Double-indexing eliminates these problems and increases both the scope and accuracy of multiplex sequencing on the Illumina platform.
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              Convergence, adaptation, and constraint.

              Convergent evolution of similar phenotypic features in similar environmental contexts has long been taken as evidence of adaptation. Nonetheless, recent conceptual and empirical developments in many fields have led to a proliferation of ideas about the relationship between convergence and adaptation. Despite criticism from some systematically minded biologists, I reaffirm that convergence in taxa occupying similar selective environments often is the result of natural selection. However, convergent evolution of a trait in a particular environment can occur for reasons other than selection on that trait in that environment, and species can respond to similar selective pressures by evolving nonconvergent adaptations. For these reasons, studies of convergence should be coupled with other methods-such as direct measurements of selection or investigations of the functional correlates of trait evolution-to test hypotheses of adaptation. The independent acquisition of similar phenotypes by the same genetic or developmental pathway has been suggested as evidence of constraints on adaptation, a view widely repeated as genomic studies have documented phenotypic convergence resulting from change in the same genes, sometimes even by the same mutation. Contrary to some claims, convergence by changes in the same genes is not necessarily evidence of constraint, but rather suggests hypotheses that can test the relative roles of constraint and selection in directing phenotypic evolution. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: Funding acquisitionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, CA USA )
                1553-7390
                1553-7404
                3 February 2020
                February 2020
                : 16
                : 2
                : e1008593
                Affiliations
                [1 ] Biology Department, Penn State-Scranton, Dunmore, Pennsylvania, United States of America
                [2 ] Department of Biological Sciences, Columbia University, New York, New York, United States of America
                [3 ] Plant Biology Department, University of Georgia, Athens, Georgia, United States of America
                [4 ] Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America
                University of Minnesota, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0001-7594-1380
                http://orcid.org/0000-0002-6005-2238
                http://orcid.org/0000-0001-7960-498X
                Article
                PGENETICS-D-19-01094
                10.1371/journal.pgen.1008593
                7018220
                32012153
                7cb135c2-971b-460c-a101-0807341acb6d
                © 2020 Van Etten et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 5 July 2019
                : 3 January 2020
                Page count
                Figures: 6, Tables: 1, Pages: 32
                Funding
                Funded by: USDA NIFA
                Award ID: 24892
                Award Recipient :
                Funded by: USDA NIFA
                Award ID: 28497
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000076, Directorate for Biological Sciences;
                Award ID: 1148897
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000076, Directorate for Biological Sciences;
                Award ID: 1353380
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: GM108779
                Award Recipient :
                MVE, S-MC and RSB were supported by USDA NIFA (United States Dept of Agriculture, NIFA: https://nifa.usda.gov/) (awards 24892 & 28497); KL was supported by NSF GRFP (National Science Foundation, NSF: https://www.nsf.gov/) (1148897), NSF (1353380); and an NIH NIGMS (National Institutes of Health, NIGMS: https://www.nigms.nih.gov/) (R01 GM108779) awarded to G. Coop. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Agriculture
                Agrochemicals
                Herbicides
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Biology and Life Sciences
                Genetics
                Population Genetics
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Biology and Life Sciences
                Genetics
                Heredity
                Genetic Mapping
                Haplotypes
                Biology and Life Sciences
                Toxicology
                Detoxification
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Toxicology
                Detoxification
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Sequence Assembly Tools
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Sequence Assembly Tools
                Biology and Life Sciences
                Genetics
                Molecular Genetics
                Biology and Life Sciences
                Molecular Biology
                Molecular Genetics
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Genetics
                Custom metadata
                vor-update-to-uncorrected-proof
                2020-02-13
                EPSPS sequencing data (MK421977-MK422097), NextRAD sequencing data Genbank: PRJNA515629) genome assembly (Genbank: VALG00000000) and Exome resequencing data (Genbank: PRJNA515629) are available in GenBank.

                Genetics
                Genetics

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