Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-28T15:16:13.308Z Has data issue: false hasContentIssue false
  • English
  • Français

Genetic Diversity and Spread of Thiobencarb Resistant Early Watergrass (Echinochloa oryzoides) in California

Published online by Cambridge University Press:  20 January 2017

Maria D. Osuna ,
Miki Okada ,
Riaz Ahmad ,
Albert J. Fischer  and
Marie Jasieniuk
Maria D. Osuna
Affiliation:
Department of Plant Sciences, Mail Stop 4, University of California, Davis, CA 95616-8780
Miki Okada
Affiliation:
Department of Plant Sciences, Mail Stop 4, University of California, Davis, CA 95616-8780
Riaz Ahmad
Affiliation:
Department of Plant Sciences, Mail Stop 4, University of California, Davis, CA 95616-8780
Albert J. Fischer
Affiliation:
Department of Plant Sciences, Mail Stop 4, University of California, Davis, CA 95616-8780
Marie Jasieniuk*
Affiliation:
Department of Plant Sciences, Mail Stop 4, University of California, Davis, CA 95616-8780
*
Corresponding author's E-mail: mjasien@ucdavis.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Resistance to the thiocarbamates has been selected in early watergrass populations within the rice-growing region of California. To elucidate the processes contributing to the spread of resistance among rice fields, we characterized the genetic diversity and differentiation of thiobencarb-resistant (R) and thiobencarb-susceptible (S) populations across the Central Valley using microsatellite markers. A total of 406 individuals from 22 populations were genotyped using seven nuclear microsatellite primer pairs. Three analytical approaches (unshared allele, Shannon–Weaver, and allelic-phenotype statistics) were used to assess genetic diversity and differentiation in the allohexaploid species. Low levels of genetic variation were detected within populations, consistent with other highly selfing species, with S populations tending to be more diverse than R populations. FST values indicated that populations were genetically differentiated and that genetic differentiation was greater among S populations than R populations. Principal coordinate analysis generated two orthogonal axes that explained 88% of the genetic variance among early watergrass populations and differentiated populations by geographical region, which was associated with resistance phenotype. A Mantel test revealed that genetic distances between R populations were positively correlated with the geographical distances separating populations. Taken together, our results suggest that both short- and long-distance seed dispersal, and multiple local and independent evolutionary events, are involved in the spread of thiobencarb-resistant early watergrass across rice fields in the Sacramento Valley. In contrast, resistance was not detected in early watergrass populations in the San Joaquin Valley.

Keywords

Early watergrassEchinochloa oryzoides (Ard.) Fritsch ECHORGenetic diversitygenetic differentiationmicrosatellite markersherbicide resistance
Type
Weed Biology and Ecology
Information
Weed Science , Volume 59 , Issue 2 , June 2011 , pp. 195 - 201
Copyright
Copyright © Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

Andrews, T. S., Morrison, I. N., and Penner, G. A. 1998. Monitoring the spread of ACCase inhibitor resistance among wild oat (Avena fatua) patches using AFLP analysis. Weed Sci. 46:196–199.CrossRefGoogle Scholar
Bakkali, Y., Ruiz-Santaella, J. P., Osuna, M. D., Wagner, J., Fischer, A. J., and De Prado, R. 2007. Late watergrass (Echinochloa phyllopogon): mechanisms involved in the resistance to fenoxaprop-p-ethyl. J. Agric. Food Chem. 55:4052–4058.Google Scholar
Barrett, S. C. H. and Seaman, D. E. 1980. The weed flora of Californian rice fields. Aquat. Bot. 9:351–376.CrossRefGoogle Scholar
Calha, I. M., Osuna, M. D., Serra, C., Moreira, I., De Prado, R., and Rocha, F. 2007. Mechanism of resistance to bensulfuron-methyl in Alisma plantago-aquatica biotypes from Portuguese rice paddy fields. Weed Res. 47:231–240.CrossRefGoogle Scholar
Cavan, G., Bliss, P., and Moss, S. R. 1998a. Localized origins of herbicide resistance in Alopecurus myosuroides . Weed Res. 38:239–245.Google Scholar
Cavan, G., Bliss, P., and Moss, S. R. 1998b. Herbicide resistance and gene flow in wild-oats (Avena fatua and Avena sterilis ssp. ludoviciana). Ann. Appl. Biol. 133:207–217.Google Scholar
Danquah, E. Y., Hanley, S. J., Brookes, R. C., Aldam, C., and Karp, A. 2002a. Isolation and characterization of microsatellites in Echinochloa (L.). Beauv. spp. Mol. Ecol. Notes. 2:54–56.CrossRefGoogle Scholar
Danquah, E. Y., Johnson, D. E., Riches, C., Arnold, G. M., and Karp, A. 2002b. Genetic diversity in Echinochloa spp. collected from different geographic origins and within rice fields in Cote d'Ivoire. Weed Res. 42:394–405.Google Scholar
Délye, C., Michel, S., Bérard, A., Chauvel, B., Brunel, D., Guillemin, J. P., Dessaint, F., and Le Corre, V. 2010. Geographical variation in resistance to acetyl-coenzyme A carboxylase-inhibiting herbicides across the range of the arable weed Alopecurus myosuroides Huds. (black-grass). New Phytologist. 186:1005–1017.Google Scholar
Délye, C., Straub, C., Michel, S., and Le Corre, V. 2004. Nucleotide variability at the acetyl coenzyme A carboxylase gene and the signature of herbicide selection in the grass weed Alopecurus myosuroides (Huds.). Mol. Biol. Evol. 21:884–892.CrossRefGoogle ScholarPubMed
DiTomaso, J. M. and Healy, E. A. 2006. Weeds of California and Other Western States. Oakland, CA University of California. DANR. Publ. no. 3488.1808 p.Google Scholar
Doyle, J. J. and Doyle, J. L. 1987. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem. Bull. 19:11–15.Google Scholar
Fischer, A. J., Ateh, C. M., Bayer, D. E., and Hill, J. E. 2000. Herbicide-resistant Echinochloa oryzoides and E. phyllopogon in California Oryza sativa fields. Weed Sci. 48:225–230.Google Scholar
Fischer, A. J. and Hill, J. E. 1998. Weed control in rice. Pages 54–84 in Annual Report Comprehensive Rice Research. Davis, CA University of California-Davis and USDA.Google Scholar
Gressel, J. 2002. Evolution of resistance to herbicides. Pages 78–121 in Gressel, J., ed. Molecular Biology of Weed Control. London Taylor and Francis.Google Scholar
Gressel, J. and Segel, L. A. 1982. Interrelating factors controlling the rate of appearance of resistance: the outlook for the future. Pages 325–348 in LeBaron, H. M., and Gressel, J., eds. Herbicide Resistance in Plants. New York J. Wiley.Google Scholar
Heap, I. 2010. The International Survey of Herbicide Resistant Weeds. www.weedscience.com. Accessed: July 30, 2010.Google Scholar
Hill, J. E., Le Strange, M. L., Bayer, D. E., and Williams, J. F. 1985. Integrated weed management in California. Pages 100–104 in Proceedings of the Western Society of Weed Science. Volume 38. Reno, NV WSWS.Google Scholar
Holm, L. G., Pucknett, D., Pancho, J. V., and Heberger, J. P. 1977. The World's Worst Weeds. Honolulu, HI University Press of Hawaii.Google Scholar
Imaizumi, T., Wang, G. X., Ohsako, T., and Tominaga, T. 2008. Genetic diversity of sulfonylurea-resistant and –susceptible Monochoria vaginalis populations in Japan. Weed Res. 48:187–196.CrossRefGoogle Scholar
Jasieniuk, M., Brûlé-Babel, A. L., and Morrison, I. M. 1996. The evolution and genetics of herbicide resistance in weeds. Weed Sci. 44:176–193.Google Scholar
Jasieniuk, M. and Maxwell, B. D. 1994. Population genetics and the evolution of herbicide resistance in weeds. Phytoprotection. 75(Suppl.):25–35.Google Scholar
Linquist, B., Fischer, A., Godfrey, L., Greer, C., Hill, J., Koffler, K., Moeching, M., Mutters, R., and van Kessel, C. 2008. Minimum tillage could benefit California rice farmers. California Agriculture. 62:24–29.Google Scholar
Lowe, A., Harris, S., and Ashton, P. 2004. Ecological Genetics: Design, Analysis, and Application. Malden, MA Blackwell Science Ltd. 214 p.Google Scholar
Lu, Y-Q., Baker, J., and Preston, C. 2007. The spread of resistance to acetolactate synthase inhibiting herbicides in a wind borne, self-pollinated weed species, Lactuca serriola L. Theor. Appl. Genet. 115:443–450.Google Scholar
Mantel, N. 1967. The detection of disease clustering and a generalized regression approach. Cancer Res. 27:209–220.Google Scholar
Marchesi, C. 2009. Regional Analyses of Constraints Affecting Rice Production Systems in California Grain Milling Quality at Harvest and Evolution of Herbicide Resistant Echinochloa spp. . Davis, CA University of California. 179.Google Scholar
Meikle, A., Finch, R. P., McRoberts, N., and Marshall, G. 1999. A molecular genetic assessment of herbicide resistant Sinapis arvensis . Weed Res. 39:149–158.Google Scholar
Menchari, Y., Delye, C., and Le Corre, V. 2007. Genetic variation and population structure in black-grass (Alopecurus myosuroides Huds.), a successful, herbicide-resistant, annual grass weed of winter cereal fields. Mol. Ecol. 16:3161–3172.Google Scholar
Mengistu, L. W., Mueller-Warrant, G. W., and Barker, R. E. 2000. Genetic diversity of Poa annua in western Oregon grass seed crops. Theor. Appl. Genet. 101:70–79.Google Scholar
Nakayama, Y., Umemoto, S., and Yamaguchi, H. 1999. Identification of polyploid groups in the genus Echinochloa by isoenzyme analysis. J. Weed Sci. Techn. 44:205–217.Google Scholar
Obbard, D. J., Harris, S. A., and Pannell, J. R. 2006. Simple allelic-phenotype diversity and differentiation statistics for allopolyploids. Heredity. 97:296–303.CrossRefGoogle ScholarPubMed
Osuna, M. D., Vidotto, F., Fischer, A. J., Bayer, D. E., De Prado, R., and Ferrero, A. 2002. Cross-resistance to bispyribac-sodium and bensulfuron-methyl in Echinochloa phyllopogon and Cyperus difformis . Pesticide Biochem. Physiol. 73:9–17.Google Scholar
Peakall, R. and Smouse, P. E. 2006. Genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes. 6(1):288–295.CrossRefGoogle Scholar
Raymond, M. and Rousset, F. 1995. GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. J. Heredity. 86:248–249.Google Scholar
Refoufi, A. and Esnault, M. A. 2006. Genetic diversity and population structure of Elytrigia pycnantha (Godr.) (Triticeae) in Mont Saint-Michel Bay using microsatellite markers. Plant Biol. 8:234–242.Google Scholar
Rousset, F. 1997. Genetic differentiation and estimation of gene flow from F-statistics under isolation by distance. Genetics. 145:1219–1228.Google Scholar
Rousset, F. 2008. Genepop'007: a complete reimplementation of the Genepop software for Windows and Linux. Mol. Ecol. Resources. 8:103–106.Google Scholar
Rutledge, J., Talbert, R. E., and Sneller, C. H. 2000. RAPD analysis of genetic variation among propanil-resistant and –susceptible Echinochloa crus-galli populations in Arkansas. Weed Sci. 48:669–674.Google Scholar
Sundaram, R. M., Naveenkumar, B., Biradar, S. K., Viraktamath, B. C., Mishra, M. S., IlyasAhmed, M., Viraktamath, B. C., Ramesha, M. S., and Sarma, N. P. 2008. Identification of informative SSR markers capable of distinguishing hybrid rice parental lines and their utilization in seed purity assessment. Euphytica. 163(2):1573–1590.Google Scholar
Tabacchi, M., Mantegazza, R., Spada, A., and Ferrero, A. 2006. Morphological traits and molecular markers for classification of Echinochloa species from Italian rice fields. Weed Sci. 54:1086–1093.Google Scholar
Tsuji, R., Fischer, A. J., Yoshino, M., Roel, A., Hill, J. E., and Yamasue, Y. 2003. Herbicide-resistant late watergrass (Echinochloa phyllopogon): similarity in morphological and amplified fragment length polymorphism traits. Weed Sci. 51:740–747.Google Scholar
Vidotto, F., Tesio, F., Tabacchi, M., and Ferrero, A. 2007. Herbicide sensitivity of Echinochloa spp. accessions in Italian rice fields. Crop Prot. 26:285–293.Google Scholar
Ward, S. M. and Jasieniuk, M. 2009. Sampling weedy plant populations for genetic diversity analyses. Weed Sci. 57:593–602.Google Scholar
Warwick, S. and Black, L. D. 1993. Electrophoretic variation in triazine-resistant and susceptible populations of the allogamous weed Brassica napa . Weed Res. 35:105–114.Google Scholar
Yabuno, T. 1966. Biosystematic study of the genus Echinochloa . J. Bot. 19:277–323.Google Scholar
Yabuno, T. 1984. A biosystematic study on Echinochloa oryzoides (Ard.) Fritsch. Cytologia. 49:673–678.Google Scholar
Yamaguchi, H., Utano, A., Yasuda, K., Yano, A., and Soejima, A. 2005. A molecular phylogeny of wild and cultivated Echinochloa in East Asia inferred from non-coding region sequences of trnT-L-F. Weed Biol. Manag. 5:210–218.Google Scholar
Yasuor, H., Osuna, M. D., Ortiz, A., Saldain, N. E., Eckert, J. W., and Fischer, A. J. 2009. Mechanism of resistance to penoxsulam in late watergrass [Echinochloa phyllopogon (Stapf) Koss.]. J. Agric. Food Chem. 57(9):3653–3660.Google Scholar
Yasuor, H., Tenbrook, P. L., Tjeerdema, R. S., and Fischer, A. J. 2008. Responses to clomazone and 5-ketoclomazone by Echinochloa phyllopogon resistant to multiple herbicides in Californian rice fields. Pest Manag Sci. 64:1031–1039.Google Scholar