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Microarray and Growth Analyses Identify Differences and Similarities of Early Corn Response to Weeds, Shade, and Nitrogen Stress

Published online by Cambridge University Press:  20 January 2017

Janet Moriles ,
Stephanie Hansen ,
David P. Horvath ,
Graig Reicks ,
David E. Clay  and
Sharon A. Clay
Janet Moriles
Affiliation:
Department of Plant Science, South Dakota State University, 1110 Rotunda Lane, Brookings, SD 57007
Stephanie Hansen
Affiliation:
Department of Plant Science, South Dakota State University, 1110 Rotunda Lane, Brookings, SD 57007
David P. Horvath
Affiliation:
USDA-ARS, 1605 Albrecht Blvd. N, Fargo, ND, 58102-2765
Graig Reicks
Affiliation:
Department of Plant Science, South Dakota State University, 1110 Rotunda Lane, Brookings, SD 57007
David E. Clay
Affiliation:
Department of Plant Science, South Dakota State University, 1110 Rotunda Lane, Brookings, SD 57007
Sharon A. Clay*
Affiliation:
Department of Plant Science, South Dakota State University, 1110 Rotunda Lane, Brookings, SD 57007
*
Corresponding author's E-mail: sharon.clay@sdstate.edu
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Abstract

Weed interference with crop growth is often attributed to water, nutrient, or light competition; however, specific physiological responses to these stresses are not well described. This study's objective was to compare growth, yield, and gene expression responses of corn to nitrogen (N), low light (40% shade), and weed stresses. Corn vegetative parameters from V2 to V12 stages, yield parameters, and gene expression using transcriptome (2008) and quantitative polymerase chain reaction (qPCR) (2008/09) analyses at V8 were compared among the stresses and with nonstressed corn. N stress did not affect vegetative parameters, although grain yield was reduced by 40% compared with nonstressed plants. Shade, present until V2, reduced biomass and leaf area > 50% at V2, and recovering plants remained smaller than nonstressed plants at V12. However, grain yields of shade-stressed and nonstressed plants were similar, unless shade remained until V8. Weed stress reduced corn growth and yield in 2008 when weeds remained until V6. In 2009, weed stress until V2 reduced corn vegetative growth, but yield reductions occurred only if weed stress remained until V6 or later. Principle component analysis of differentially expressed genes indicated that shade and weed stress had more similar gene expression patterns to each other than they did to nonstressed or N-stressed tissues. However, corn grown in N-stressed conditions shared 252 differentially expressed genes with weed-stressed plants. Ontologies associated with light/photosynthesis, energy conversion, and signaling were down-regulated in response to all three stresses. Shade and weed stress clustered most tightly together, based on gene expression, but shared only three ontologies, O-METHYLTRANSFERASE activity (lignification processes), POLY(U)-BINDING activity (posttranscriptional gene regulation), and stomatal movement. Based on morphologic and genomic observations, weed stress to corn was not explained by individual effects of N or light stress. Therefore, we hypothesize that these stresses share limited signaling mechanisms.

Keywords

Corn, Zea mays LWeed competitiongenomicstranscriptome analysiscritical weed free period
Type
Physiology, Chemistry, and Biochemistry
Information
Weed Science , Volume 60 , Issue 2 , June 2012 , pp. 158 - 166
Copyright
Copyright © Weed Science Society of America 

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References

Literature Cited

Agronomy Extension. 2007. Corn Production. Iowa State University. http://www.agronext.iastate.edu/corn/ Accessed: April 15, 2011.Google Scholar
Ballaré, C. L., Sanchez, R. A., Scopel, A. L., Casal, J. J., and Ghersa, C. M. 1987. Early detection of neighbour plants by phytochrome perception of spectral changes in reflected sunlight. Plant Cell Environ. 10:551–557.Google Scholar
Ballaré, C. L., Scopel, A. L., and Sanchez, R. A. 1990. Far-red radiation reflected from adjacent leaves: an early signal of competition in plant canopies. Science. 247:329–332.Google Scholar
Boerjan, W., Ralph, J., and Baucher, M. 2003. Lignin biosynthesis. Ann. Rev. Plant Biol. 54:519–546.Google Scholar
Churchill, G. A. 2002. Fundamentals of experimental design for cDNA microarrays. Nat. Genet. 32(Suppl.):490–495.Google Scholar
Clay, S. A., Clay, D. E., Horvath, D. P., Pullis, J., Carlson, C. G., Hansen, S., and Reicks, G. 2009. Corn response to competition: growth alteration vs. yield limiting factors. Agron. J. 101:1522–1529.Google Scholar
Coruzzi, G. M. and Zhou, L. 2001. Carbon and nitrogen sensing and signaling in plants: emerging “matrix effects.”. Curr. Opin. Plant Biol. 4:247–253.Google Scholar
Deen, W., Cousens, R., Warringa, J., et al. 2003. An evaluation of four crop ∶ weed competition models using a common data set. Weed Res. 43:116–129.Google Scholar
De la Torre, W. R. and Burkey, K. O. 1990. Acclimation of barley to changes in light intensity: chlorophyll organization. Photosynth. Res. 24:117–125.Google Scholar
Donald, C. M. 1963. Competition among crop and pasture plants. Adv. Agron. 15:1–118.Google Scholar
Evans, S. P., Knezevic, S. Z., Lindquist, J. L., and Shapiro, C. A. 2003a. Influence of nitrogen and duration of weed interference on corn growth and development. Weed Sci. 51:546–556.Google Scholar
Evans, S. P., Knezevic, S. Z., Lindquist, J. L., Shapiro, C. A., and Blankenship, E. E. 2003b. Nitrogen application influences the critical period for weed control in corn. Weed Sci. 51:408–417.Google Scholar
Gardiner, J. M., Buell, C. R., Elumalai, R., et al. 2005. Design, production, and utilization of long oligonucleotide microarrays for expression analysis in maize. Maydica. 50:425–435.Google Scholar
Hall, M. R., Swanton, C. J., and Anderson, G. W. 1992. The critical period of weed control in grain corn (Zea mays). Weed Sci. 40:441–447.Google Scholar
Horvath, D. P., Gulden, R., and Clay, S. A. 2006. Microarray analysis of late season velvetleaf (Abutilon theophrasti) impact on corn. Weed Sci. 54:983–994.Google Scholar
Horvath, D. P., Llewellyn, D., and Clay, S. A. 2007. Heterologous hybridization of cotton microarrays with velvetleaf (Abutilon theophrasti) reveals physiological responses due to corn competition. Weed Sci. 55:546–557.Google Scholar
Kasperbauer, M. J. and Karlen, D. L. 1994. Plant spacing and reflected far-red light effects on phytochrome-regulated photosynthate allocation in corn seedlings. Crop Sci. 34:1564–1569.CrossRefGoogle Scholar
Knake, E. L. and Slife, F. W. 1969. Effect of time of giant foxtail removal from corn and soybeans. Weed Sci. 17:281–283.Google Scholar
Knezevic, S. Z., Evans, S. P., Blankenship, E. E., van Acker, R. C., and Lindquist, J. L. 2002. Critical period of weed control: the concept and data analysis. Weed Sci. 50:773–786.Google Scholar
Kropff, M. J. 1993. Mechanisms of competition for nitrogen. Pages 77–82 in Kropff, M. J. and van Laar, H. H., eds. Modelling Crop–Weed Interactions. Wallingford, UK CAB International.Google Scholar
Li, M-Y. 1960. An evaluation of the critical period and the effects of weed competition on oats and corn. . New Brunswick, NJ Rutgers University. 166 p.Google Scholar
Liu, J. G., Mahoney, K. J., Sikkema, P. H., and Swanton, C. J. 2009. The importance of light quality in crop–weed competition. Weed Res. 49:217–224.Google Scholar
Livak, K. J. and Schmittgen, T. D. 2001. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods. 25:402–408.Google Scholar
Maddonni, G. A. and Otegui, M. E. 2004. Intra-specific competition in maize: early establishment of hierarchies among plants affects final kernel set. Field Crops Res. 85:1–13.Google Scholar
Massinga, R. A., Currie, R. S., Horak, M. J., and Boyer, J. Jr. 2001. Interference of Palmer amaranth in corn. Weed Sci. 49:202–208.CrossRefGoogle Scholar
Merotto, A. Jr., Fischer, A. J., and Vidal, R. A. 2009. Perspectives for using light quality knowledge as an advanced ecophysiological weed management tool. Planta Daninha. 27:407–419.Google Scholar
Moriles, J. C. 2011. Early corn growth and development in response to weed competition, altered light quantity, and light quality. . Brookings, SD South Dakota State University. 147 p.Google Scholar
Mohler, C. L. 2001. Enhancing the competitive ability of crops. Pages 269–321 in Liebman, M., Mohler, C., and Staver, C., eds. Ecological Management of Agricultural Weeds. Cambridge, UK Cambridge University Press.Google Scholar
Mulvaney, R. L. 1996. Nitrogen – inorganic forms. Pages 1123–1184 in Sparks, D. L., ed. Methods of Soil Analysis: Part 3: Chemical Methods. Madison, WI Soil Sci. Soc. Amer. and Amer. Soc. Agronomy.Google Scholar
Nieto, H. J., Bondo, M. A., and Gonzalez, J. T. 1968. Critical periods of the crop growth cycle for competition from weeds. PANS Pest Articles News Summaries. 14:159–166.Google Scholar
Nitikin, A., Egorov, S., Daraselia, N., and Mazo, I. 2003. Pathway studio—the analysis and navigation of molecular networks. Bioinformatics. 19:2155–2157.CrossRefGoogle Scholar
Norsworthy, J. K. and Oliveira, M. J. 2004. Comparison of the critical period for weed control in wide- and narrow-row corn. Weed Sci. 52:802–807.Google Scholar
Patterson, D. T. 1995. Effects of environmental stress on weed/crop interactions. Weed Sci. 43:483–490.Google Scholar
Rajcan, I., Chandler, K. J., and Swanton, C. J. 2004. Red-far-red ratio of reflected light: a hypothesis of why early season weed control is important in corn. Weed Sci. 52:774–778.Google Scholar
Rajcan, I. and Swanton, C. J. 2001. Understanding maize-weed competition: resource competition, light quality and the whole plant. Field Crops Res. 71:139–150.CrossRefGoogle Scholar
Subramanian, A., Tamayo, P., Mootha, V. K., et al. 2005. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. U. S. A. 102:15545–15550.Google Scholar
[USDA-NRCS] U.S. Department of Agriculture–Natural Resources Conservation Service. 2004. Soil Survey of Brookings County, South Dakota. http://soildatamart.nrcs.usda.gov/Manuscripts/SD011/0/Brookings_SD.pdf Accessed: April 15, 2011.Google Scholar
Wasternack, C. 2007. Jasmonates: An update on biosynthesis, signal transduction and action in plant stress response, growth and development. Ann. Bot. (Lond.) 100:681–697.Google Scholar
Weaver, S. E. 2001. Impact of lambsquarters, common ragweed and green foxtail on yield of corn and soybean in Ontario. Can. J. Plant Sci. 81:821–828.Google Scholar
Weaver, S. E., Kropff, M. J., and Groenveld, R. M. W. 1992. Use of ecophysiological models for crop-weed interference: the critical period of weed interference. Weed Sci. 40:302–307.Google Scholar
Werner, H. 1993. Checkbook irrigation scheduling: irrigation management manual for South Dakota. Brookings, SD South Dakota Cooperative Extension Service, South Dakota State University Circular 897. Brookings, http://agbiopubs.sdstate.edu/articles/EC897.pdf Accessed: April 15, 2011.Google Scholar
Zimdahl, R. L. 2004. Weed–Crop Competition: A review. 2nd ed. Ames, IA Blackwell.Google Scholar