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Genetic Relationship between Cultivated and Feral Creeping Bentgrass (Agrostis stolonifera) in a Cultural Landscape

Published online by Cambridge University Press:  20 January 2017

Collin W. Ahrens  and
Carol A. Auer
Collin W. Ahrens*
Affiliation:
Department of Plant Science, University of Connecticut, Agricultural Biotechnology Lab, 1390 Storrs Road, Unit 4163, Storrs, CT 06269
Carol A. Auer
Affiliation:
Department of Plant Science, University of Connecticut, Agricultural Biotechnology Lab, 1390 Storrs Road, Unit 4163, Storrs, CT 06269
*
Corresponding author's E-mail: collinwahrens@gmail.com
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Abstract

Gene flow is an important consideration in the adoption of crops with novel traits or transgenes when sexually compatible relatives occur in the landscape. Unfortunately, gene flow and its long-term environmental impacts are very difficult to predict without releasing and studying the novel genotype. This project uses a retrospective population genetics approach to characterize the relationship between cultivated creeping bentgrass (CB) on a golf course and the same species in five feral populations nearby. CB plants were collected from an 8-yr-old golf course, five weedy populations up to 1,020 m from the golf course, and four modern CB cultivars. Using microsatellite markers and Bayesian inference, two major genetic clusters were distinguished: (1) CB cultivars and individuals from the golf course (cultivar genotype), and (2) the majority of individuals (62%) from the five feral populations (feral genotype). Two feral CB individuals (3.3% of all feral plants) were partially assigned to the cultivar genotype. Principal coordinates analysis agreed with this assignment, suggesting that an intraspecific hybridization event may have occurred. Plants in four feral populations showed a high degree of genetic similarity, but one feral population (Reservoir) was heterogeneous indicating that genetically complex CB populations can develop in cultural landscapes. While recognizing the limitations inherent in a single study of CB population genetics, these results add to the relevant knowledge for predictive ecological risk assessment.

Keywords

Creeping bentgrass, Agrostis stolonifera LMicrosatellite markerspopulation geneticsgene flowecological risk assessment
Type
Weed Biology and Ecology
Information
Weed Science , Volume 60 , Issue 4 , December 2012 , pp. 583 - 588
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Ahrens, C., Chung, J., Meyer, T., and Auer, C. 2011a. Bentgrass distribution surveys and habitat suitability maps support ecological risk assessment in cultural landscapes. Weed Sci. 59:145–154.Google Scholar
Ahrens, C., Ecker, G., and Auer, C. 2011b. The intersection of ecological risk assessment and plant communities: an analysis of Agrostis and Panicum species in the northeastern U.S. Plant Ecol. 212:1629–1642.Google Scholar
[APHIS] Animal and Plant Health Inspection Service. 2012. Biotechnology. http://www.aphis.usda.gov/biotechnology/status.shtml. Accessed: February 7, 2012.Google Scholar
Arnaud, J.-F., Viard, F., Delescluse, M., and Cuguen, J. 2003. Evidence for gene flow via seed dispersal from crop to wild relatives in Beta vulgaris (Chenopodiaceae): consequences for the release of genetically modified crop species with weedy lineages. Proc. R. Soc. Lond. B. 270:1565–1571.Google Scholar
Barkworth, M., Anderton, L., Capels, K., and Long, S. 2007. Manual of grasses for North America. Logan, UT Utah State University Press, 627 p.Google Scholar
Behrendt, S. and Hanf, M. 1979. Grass weeds in world agriculture. BASF Aktiengesellschaft, Ludwigshafen am Rhein, Germany, 159 p.Google Scholar
Belanger, F., Meagher, T. R., Day, P. R., Plumley, K., and Meyer, W. A. 2003. Interspecific hybridization between Agrostis stolonifera and related Agrostis species under field conditions. Crop Sci. 43:240–246.Google Scholar
Bollman, M. A., Storm, M. J., King, G. A., and Watrud, L. S. 2012. Wetland and riparian plant communities at risk of invasion by transgenic herbicide-resistant Agrostis spp. in central Oregon. Plant Ecol. DOI:10.1007/s11258-011-0015-z.Google Scholar
Botstein, D., White, R. L., Skolnick, M., and Davis, R. W. 1980. Construction of a genetic linkage map in man using restriction fragment length polymporphisms. Am. J. Hum. Genet. 32:314–331.Google Scholar
Chandler, S. and Dunwell, J. M. 2009. Gene flow, risk assessment and the environmental release of transgenic plants. Crit. Rev. Plant. Sci. 27:25–49.Google Scholar
Charles, D. 2011. Scientist in the middle of the GM-organic wars. Science. 332:168–168.Google Scholar
Culley, T. M. and Hardiman, N. A. 2009. The role of intraspecific hybridization in the evolution of invasiveness: a case study of the ornamental pear tree Pyrus calleryana . Biol. Invasions. 11:1107–1119.Google Scholar
Earl, D. A. and von Holdt, B. M. 2011. STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conservation Genetics Resources. DOI:10.1007/s12686-011-9548-7 Version: v0.6.8 Oct 2011.Google Scholar
Ellstrand, N. 1992. Gene flow by pollen—implications for plant conservation genetics. Oikos. 63:77–86.Google Scholar
Ellstrand, N. 2003. Current knowledge of gene flow in plants: implications for transgene flow. Philos. Trans. R. Soc. Lond. B. 358:1163–1170.Google Scholar
Evanno, G., Regnaut, S., and Goudet, J. 2005. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol. 14:2611–2620.Google Scholar
Fei, S. and Nelson, E. 2003. Estimation of pollen viability, shedding pattern, and longevity of creeping bentgrass on artificial media. Crop Sci. 43:2177–2181.Google Scholar
Fei, S. and Nelson, E. 2004. Greenhouse evaluation of fitness-related reproductive traits in Roundup®-tolerant transgenic creeping bentgrass (Agrostis stolonifera L.). In Vitro Cell. Dev. Pl. 40:266–273.Google Scholar
Gardner, D. S., Danneberger, T. K., and Nelson, E. K. 2004. Lateral spread of glyphosate-resistant transgenic creeping bentgrass (Agrostis stolonifera) lines in established turfgrass swards. Weed Technol. 18:773–778.Google Scholar
Gardner, D. S., Nelson, E. K., Waldecker, M. A., and Tarter, W. R. 2006. Establishment and lateral growth of glyphosate-resistant creeping bentgrass in bare soil. HortTechnol. 16:590–594.Google Scholar
Golembiewski, R. C., Danneberger, T. K., and Sweeney, P. M. 1997. Potential of RAPD markers for use in the identification of creeping bentgrass cultivars. Crop Sci. 37:212–214.Google Scholar
Guadagnuolo, R., Savova-Bianchi, D., and Felber, F. 2001. Gene flow from wheat (Triticum aestivum L.) to jointed goatgrass (Aegilops cylindrica Host.), as revealed by RAPD and microsatellite markers. Theor. Appl. Genet. 103:1–8.Google Scholar
Hart, S. E., Belanger, F. C., McCullough, P. E., and Rotter, D. 2009. Competitiveness of interspecific hybrids in turfgrass swards. Crop Sci. 49:2275–2284.Google Scholar
Haygood, R., Ives, A. R., and Andow, D. A. 2003. Consequences of recurrent gene flow from crops to wild relatives. Proc. R. Soc. Lond. B. 270:1879–1886.Google Scholar
Hubbard, C. E. 1984. Grasses: A Guide to Their Structure, Identification, Uses and Distribution in the British Isles. New York Penguin Group. 476 p.Google Scholar
IPA. 2011. Invasive Plant Atlas. http://www.invasiveplantatlas.org/. Accessed: December 2011.Google Scholar
Jakobsson, M. and Rosenberg, N. A. 2007. CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics. 23:1801–1806.Google Scholar
Jenczewski, E., Prosperi, J.-M., and Ronfort, J. 1999. Evidence for gene flow between wild and cultivated Medicago sativa (Leguminosae) based on allozyme markers and quantitative traits. Am. J. Bot. 86:677–687.Google Scholar
Kik, C., Linders, T., and Bijlsma, R. 1993. Ploidy level and somatic chromosome number variation in Agrostis stolonifera . Acta Bot. Neerl. 42:73–80.Google Scholar
Kubik, C., Honig, J., Meyer, W. A., and Bonos, S. A. 2009. Genetic diversity of creeping bentgrass cultivars using SSR markers. Int. Turfgrass Soc. 11:533–547.Google Scholar
Leak-Garcia, J. A. 2009. Genetic origins and the evolution of invasiveness of Cynara cardunculus in California. Ph.D. dissertation. Riverside, CA University of California Riverside. 154 p.Google Scholar
MacBryde, B. 2006. White paper: perspective on creeping bentgrass, Agrostis stolonifera L. Riverdale, MD United States Department of Agriculture. 80 p.Google Scholar
McCarty, L. B. 2005. Best golf course management practices. 2nd Edition. Upper Saddle River, NJ Pearson Eduction Inc. 896 p.Google Scholar
Pritchard, J., Stephens, M., and Donnelly, P. 2000. Inference of population structure using multilocus genotype data. Genetics. 155:945–959.Google Scholar
Reichman, J. R., Smith, B. M., Londo, J. P., Bollman, M. A., Auer, C. A., and Watrud, L. S. 2011. Diallelic nuclear microsatellites for diversity and population analyses of the allotetraploid creeping bentgrass (Agrostis stolonifera). Crop Sci. 51:747–758.Google Scholar
Reichman, J. R., Watrud, L. S., Lee, E. H., Burdick, C. A., Bollman, M. A., Storm, M. J., King, G. A., and Mallory-Smith, C. 2006. Establishment of transgenic herbicide-resistant creeping bentgrass (Agrostis stolonifera L.) in nonagronomic habitats. Mol. Ecol. 15:4243–4255.Google Scholar
Rohlf, J. F. 2005. NTSYS-pc numerical taxonomy and multivariate analysis system version 2.1 Manual. Port Jefferson, NY Applied Biostatistics. 37 p.Google Scholar
Rosenberg, N. A. 2004. DISTRUCT: a program for the graphical display of population structure. Mol. Ecol. 4:137–138.Google Scholar
Rotter, D., Ambrose, K. V., and Belanger, F. C. 2010. Velvet bentgrass (Agrostis canina L.) is the likely ancestral diploid maternal parent of allotetraploid creeping bentgrass (Agrostis stolonifera L.). Genet. Resour. Crop Evol. 57:1065–1077.Google Scholar
Sahoo, L., Schmidt, J. J., Pedersen, J. F., Lee, D. J., and Lindquist, J. L. 2010. Growth and fitness components of wild × cultivated Sorghum bicolor (Poaceae) hybrids in Nebraska. Am. J. Bot. 97:1610–1617.Google Scholar
Scheef, E. A., Casler, M., and Jung, G. 2003. Development of species specific SCAR markers in bentgrass. Crop Sci. 43:345–349.Google Scholar
Schmidt, J. J. 2011. The rate of shattercane × sorghum hybridization in situ . . Lincoln, NE University of Nebraska. 32 p.Google Scholar
Snow, A. A., Andow, D. A., Gepts, P., Hallerman, E. M., Power, A., Tiedje, J. M., and Wolfenbarger, L. L. 2005. Genetically engineered organisms and the environment: Current status and recommendations. Ecol. Appl. 15:377–404.Google Scholar
[UNESCO] United Nations Educational, Scientific, and Cultural Organization. 2010. United Nations Educational, Scientific, and Cultural Organization. http://www.unesco.org/new/en/unesco/. Accessed: August 3, 2010.Google Scholar
Vergara, G. and Bughrara, S. 2003. AFLP analyses of genetic diversity in bentgrass. Crop Sci. 43:2162–2171.Google Scholar
Waltz, E. 2011. GM grass eludes outmoded USDA oversight. Nature. 29:772–773.Google Scholar
Wang, Z.-Y. and Brummer, E. C. 2012. Is genetic engineering ever going to take off in forage, turf and bioenergy crop breeding? Ann. Bot. DOI:10.1093/aob/mcs027Google Scholar
Warnke, S. E., Douches, D. S., and Branham, B. E. 1997. Relationships among creeping bentgrass cultivars based on isozyme polymorphisms. Crop Sci. 37:203–207.Google Scholar
Warwick, S. I., Legere, A., Simard, M.-J., and James, T. 2008. Do escaped transgenes persist in nature? The case of an herbicide resistance transgene in a weedy Brassica rapa population. Mol. Ecol. 17:1387–1395.Google Scholar
Waser, N., Price, M., and Shaw, R. 2000. Outbreeding depression varies among cohorts of Ipomopsis aggregata planted in nature. Evolution. 54:485–491.Google Scholar
Watrud, L. S., Lee, E. H., Fairbrother, A., Burdick, C., Reichman, J. R., Bollman, M., Storm, M., King, G., and Van de Water, P. K. 2004. Evidence for landscape-level, pollen-mediated gene flow from genetically modified creeping bentgrass with CP4 EPSPS as a marker. Proc. Natl. Acad. Sci. U.S.A. 101:14533–14538.Google Scholar
Wegier, A., Piñeyro-Nelson, A., Alarcón, J., Gálvez-Mariscal, A., Álvarez-Buylla, E. R., and Piñero, D. 2011. Recent long-distance transgene flow into wild populations conforms to historical patterns of gene flow in cotton (Gossypium hirsutum) at its centre of origin. Mol. Ecol. 20:4182–4194.Google Scholar
Wipff, J. K. and Fricker, C. R. 2000. Determining gene flow of transgenic creeping bentgrass and gene transfer to other bentgrass species. Diversity. 16:36–39.Google Scholar
Wright, S. 1978. Evolution and the Genetics of Populations. Volume 4: Variability within and among Natural Populations. Chicago University of Chicago Press. 590 p.Google Scholar
Yamamato, I. and Duich, J. M. 1994. Electrophoretic identification of cross-pollinated bentgrass species and cultivars. Crop Sci. 34:792–798.Google Scholar
Zapiola, M. L., Campbell, C. K., Butler, M. D., and Mallory-Smith, C. A. 2008. Escape and establishment of transgenic glyphosate-resistant creeping bentgrass (Agrostis stolonifera) in Oregon, USA: a 4-year study. J. Appl. Ecol. 45:486–494.Google Scholar
Zapiola, M. 2009. Escapes of glyphosate resistant creeping bentgrass in Oregon: a case study. Ph.D. dissertation. Corvallis, OR Oregon State University. 125 p.Google Scholar
Zhao, H., Bughrara, S., and Oliveira, J. 2006. Genetic diversity in colonial bentgrass (Agrostis capillaris L.) revealed by EcoRI-MseI and Pst-MseI AFLP markers. Genome. 49:328–335.Google Scholar