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      Population genetic structure of the maize weevil, Sitophilus zeamais, in southern Mexico

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          Abstract

          The maize weevil, Sitophilus zeamais, is a ubiquitous pest of maize and other cereal crops worldwide and remains a threat to food security in subsistence communities. Few population genetic studies have been conducted on the maize weevil, but those that exist have shown that there is very little genetic differentiation between geographically dispersed populations and that it is likely the species has experienced a recent range expansion within the last few hundred years. While the previous studies found little genetic structure, they relied primarily on mitochondrial and nuclear microsatellite markers for their analyses. It is possible that more fine-scaled population genetic structure exists due to local adaptation, the biological limits of natural species dispersal, and the isolated nature of subsistence farming communities. In contrast to previous studies, here, we utilized genome-wide single nucleotide polymorphism data to evaluate the genetic population structure of the maize weevil from the southern and coastal Mexican states of Oaxaca and Chiapas. We employed strict SNP filtering to manage large next generation sequencing lane effects and this study is the first to find fine-scale genetic population structure in the maize weevil. Here, we show that although there continues to be gene flow between populations of maize weevil, that fine-scale genetic structure exists. It is possible that this structure is shaped by local adaptation of the insects, the movement and trade of maize by humans in the region, geographic barriers to gene flow, or a combination of these factors.

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          Most cited references34

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            MultiQC: summarize analysis results for multiple tools and samples in a single report

            Motivation: Fast and accurate quality control is essential for studies involving next-generation sequencing data. Whilst numerous tools exist to quantify QC metrics, there is no common approach to flexibly integrate these across tools and large sample sets. Assessing analysis results across an entire project can be time consuming and error prone; batch effects and outlier samples can easily be missed in the early stages of analysis. Results: We present MultiQC, a tool to create a single report visualising output from multiple tools across many samples, enabling global trends and biases to be quickly identified. MultiQC can plot data from many common bioinformatics tools and is built to allow easy extension and customization. Availability and implementation: MultiQC is available with an GNU GPLv3 license on GitHub, the Python Package Index and Bioconda. Documentation and example reports are available at http://multiqc.info Contact: phil.ewels@scilifelab.se
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              adegenet: a R package for the multivariate analysis of genetic markers.

              The package adegenet for the R software is dedicated to the multivariate analysis of genetic markers. It extends the ade4 package of multivariate methods by implementing formal classes and functions to manipulate and analyse genetic markers. Data can be imported from common population genetics software and exported to other software and R packages. adegenet also implements standard population genetics tools along with more original approaches for spatial genetics and hybridization. Stable version is available from CRAN: http://cran.r-project.org/mirrors.html. Development version is available from adegenet website: http://adegenet.r-forge.r-project.org/. Both versions can be installed directly from R. adegenet is distributed under the GNU General Public Licence (v.2).
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: VisualizationRole: Writing – original draft
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: Writing – review & editing
                Role: InvestigationRole: ResourcesRole: Writing – review & editing
                Role: InvestigationRole: ResourcesRole: Writing – review & editing
                Role: Funding acquisitionRole: Project administrationRole: ResourcesRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                12 April 2023
                2023
                : 18
                : 4
                : e0264469
                Affiliations
                [1 ] Genetic Engineering and Society Center, North Carolina State University, Raleigh, NC, United States of America
                [2 ] Graduate Program in Genetics, North Carolina State University, Raleigh, NC, United States of America
                [3 ] International Maize and Wheat Improvement Center (CIMMYT), Texcoco, México
                [4 ] Department of Agronomy, University of Wisconsin-Madison, Madison, WI, United States of America
                [5 ] Instituto Nacional de Salud Pública/CRISP, Tapachula, Chiapas, México
                [6 ] Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, United States of America
                ICAR-Indian Institute of Pulses Research, INDIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                [¤]

                Current address: College of Business and Public Policy, University of Alaska Anchorage, Anchorage, AK, United States of America

                Author information
                https://orcid.org/0000-0002-7315-8680
                https://orcid.org/0000-0002-5950-0830
                Article
                PONE-D-22-04080
                10.1371/journal.pone.0264469
                10096444
                37043502
                e650e7ff-63bd-48ca-8aeb-763d54135e37
                © 2023 Baltzegar 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
                : 9 February 2022
                : 22 February 2023
                Page count
                Figures: 4, Tables: 2, Pages: 12
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100008982, National Science Foundation;
                Award ID: 1068676
                Award Recipient :
                Funded by: Genetic Engineering and Society Center
                Award Recipient :
                This work was supported by the National Science Foundation – IGERT 1068676 ( https://www.nsf.gov/)(FG) and the Genetic Engineering and Society Center, North Carolina State University, Raleigh, NC. ( https://research.ncsu.edu/ges) (JB & MJ) There was no additional external funding received for this study.
                Categories
                Research Article
                Biology and Life Sciences
                Agriculture
                Pests
                Insect Pests
                Weevils
                Research and Analysis Methods
                Animal Studies
                Experimental Organism Systems
                Model Organisms
                Maize
                Research and Analysis Methods
                Model Organisms
                Maize
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Grasses
                Maize
                Research and Analysis Methods
                Animal Studies
                Experimental Organism Systems
                Plant and Algal Models
                Maize
                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
                Agriculture
                Crop Science
                Crops
                Cereal Crops
                Biology and Life Sciences
                Genetics
                Single Nucleotide Polymorphisms
                People and places
                Geographical locations
                North America
                Mexico
                Biology and Life Sciences
                Genetics
                Biology and Life Sciences
                Genetics
                Heredity
                Gene Flow
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Gene Flow
                Biology and Life Sciences
                Genetics
                Population Genetics
                Gene Flow
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Gene Flow
                Custom metadata
                The data that support the findings of this study are openly available in Dryad (doi: 10.5061/dryad.zpc866tcr).

                Uncategorized
                Uncategorized

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