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QTL analysis of resistance to Mal de Río Cuarto disease in maize using recombinant inbred lines

Published online by Cambridge University Press:  11 January 2012

N. C. BONAMICO ,
M. A. DI RENZO ,
M. A. IBAÑEZ ,
M. L. BORGHI ,
D. G. DÍAZ ,
J. C. SALERNO  and
M. G. BALZARINI
N. C. BONAMICO*
Affiliation:
Facultad de Agronomía y Veterinaria, Universidad Nacional de Río Cuarto, Agencia No 3, 5800 Río Cuarto, Argentina
M. A. DI RENZO
Affiliation:
Facultad de Agronomía y Veterinaria, Universidad Nacional de Río Cuarto, Agencia No 3, 5800 Río Cuarto, Argentina
M. A. IBAÑEZ
Affiliation:
Facultad de Agronomía y Veterinaria, Universidad Nacional de Río Cuarto, Agencia No 3, 5800 Río Cuarto, Argentina
M. L. BORGHI
Affiliation:
Facultad de Agronomía y Veterinaria, Universidad Nacional de Río Cuarto, Agencia No 3, 5800 Río Cuarto, Argentina
D. G. DÍAZ
Affiliation:
Instituto de Genética ‘Ewald A. Favret’, Instituto Nacional de Tecnología Agropecuaria, cc 25, 1712 Castelar, Argentina
J. C. SALERNO
Affiliation:
Instituto de Genética ‘Ewald A. Favret’, Instituto Nacional de Tecnología Agropecuaria, cc 25, 1712 Castelar, Argentina
M. G. BALZARINI
Affiliation:
Facultad de Ciencias Agrarias, Universidad Nacional de Córdoba and CONICET (National Council of Scientific and Technological Research), cc 509, 5000 Córdoba, Argentina
*
*To whom all correspondence should be addressed. Email: [email protected]
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Summary

Mal de Río Cuarto (MRC) is a devastating disease that reduces yield, quality and economic value of maize in Argentina. The objective of the present study was to map quantitative trait loci (QTL) for reactions to MRC from recombinant inbred lines (RILs). Reactions to the endemic MRC disease were evaluated in 145 advanced F2:6 lines, derived from a cross between a resistant (BLS14) and a susceptible (Mo17) line, at four environments in the temperate semi-arid crop region of Argentina. The evaluations of disease score (SCO), disease incidence (INC) and disease severity (SEV) were carried out on each individual RIL. Low heritability estimates were found across environments for SCO (0·23), INC (0·27) and SEV (0·22). A genetic map of simple sequence repeat (SSR) markers covering a total genetic distance of 1019 cM was built. QTL for resistance to MRC disease were found on different maize chromosomes. Four significant QTL, each explaining between 0·08 and 0·14 of the total phenotypic variation, were located on chromosomes 1, 4 and 10. Two QTL specific to the INC, and one specific to SEV, may be involved in different mechanisms of resistance to MRC. Although MRC reaction is highly affected by environmental effects, the QTL×environment interaction for INC and SEV was low. Most of the QTL for reaction to MRC detected in the present study were mapped to regions of the maize genome containing genes conferring resistance to various pathogens. The significant QTL across environments are good candidates to select for MRC resistance.

Type
Crops and Soils Research Papers
Information
The Journal of Agricultural Science , Volume 150 , Issue 5 , October 2012 , pp. 619 - 629
Copyright
Copyright © Cambridge University Press 2012

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References

REFERENCES

Arneodo, J. D., Lorenzo, E., Laguna, I. G., Abdala, G. & Truol, G. A. (2002). Cytopathological characterization of Mal de Río Cuarto virus in corn, wheat and barley. Fitopatologia Brasileira 27, 298–302.CrossRefGoogle Scholar
Berke, T. G. & Rocheford, T. R. (1999). Quantitative trait loci for tassel traits in maize. Crop Science 39, 1439–1443.CrossRefGoogle Scholar
Bonamico, N. C., Balzarini, M. G., Arroyo, A. T., Ibañez, M. A., Díaz, D. G., Salerno, J. C. & Di Renzo, M. A. (2010). Association between microsatellites and resistance to Mal de Río Cuarto in maize by discriminant analysis. Phyton 79, 31–38.Google Scholar
Bubeck, D. M., Goodman, M. M., Beavis, W. D. & Grant, D. (1993). Quantitative trait loci controlling resistance to gray leaf spot in maize. Crop Science 33, 838–847.CrossRefGoogle Scholar
Cardinal, A. J., Lee, M., Sharopova, N., Woodman-Clikeman, W. L. & Long, M. J. (2001). Genetic mapping and analysis of quantitative trait loci for resistance to stalk tunneling by the European corn borer in maize. Crop Science 41, 835–845.CrossRefGoogle Scholar
Chen, C. X., Wang, Z. L., Yang, D. E., Ye, C. J., Zhao, Y. B., Jin, D. M., Weng, M. L. & Wang, B. (2004). Molecular tagging and genetic mapping of the disease resistance gene RppQ to southern corn rust. Theoretical and Applied Genetics 108, 945–950.CrossRefGoogle ScholarPubMed
Dintinger, J., Verger, D., Caiveau, S., Risterucci, A. M., Gilles, J., Chiroleu, F., Courtois, B., Reynaud, B. & Hamon, P. (2005). Genetic mapping of maize stripe disease resistance from the Mascarene source. Theoretical and Applied Genetics 111, 347–359.CrossRefGoogle ScholarPubMed
Di Renzo, M. A., Bonamico, N. C., Diaz, D. D., Salerno, J. C., Ibañez, M. M. & Gesumaria, J. J. (2002). Inheritance of resistance to Mal de Río Cuarto (MRC) disease in Zea mays (L.). Journal of Agricultural Science, Cambridge 139, 47–53.CrossRefGoogle Scholar
Di Renzo, M. A., Bonamico, N. C., Diaz, D. G., Ibanez, M. A., Faricelli, M. E., Balzarini, M. G. & Salerno, J. C. (2004). Microsatellite markers linked to QTL for resistance to Mal de Río Cuarto disease in Zea mays L. Journal of Agricultural Science, Cambridge 142, 289–295.CrossRefGoogle Scholar
Garat, O., Trumper, E. V., Gorla, D. E. & Perez-Harguindeguy, N. (1999). Spatial pattern of the Río Cuarto corn disease vector, Delphacodes kuscheli Fennah (Hom., Delphacidae), in oat fields in Argentina and design of sampling plans. Journal of Applied Entomology 123, 121–126.CrossRefGoogle Scholar
Hallauer, A. R. & Miranda, J. B. (1981). Quantitative Genetics in Maize Breeding. Ames, IA: Iowa State University Press.Google Scholar
Hogenhout, S. A., El-Desouky, A., Whitfield, A. E. & Redinbaugh, M. G. (2008). Insect vector interactions with persistently transmitted viruses. Annual Review of Phytopathology 46, 327–359.CrossRefGoogle ScholarPubMed
Hoisington, D. (1989). Working linkage maps. Maize Genetics Cooperation Newsletter 63, 141–151.Google Scholar
Jansen, R. C. & Stam, P. (1994). High resolution of quantitative traits into multiple loci via interval mapping. Genetics 136, 1447–1455.CrossRefGoogle ScholarPubMed
Knapp, S. J., Stroup, W. W. & Ross, W. M. (1985). Exact confidence intervals for heritability on a progeny mean basis. Crop Science 25, 192–194.CrossRefGoogle Scholar
Kreff, E. D., Pacheco, M. G., Díaz, D. G., Robredo, C. G., Puécher, D., Céliz, A. E. & Salerno, J. C. (2006). Resistance to Mal de Río Cuarto virus in maize: A QTL mapping analysis. Journal of Basic and Applied Genetics 17, 41–50.Google Scholar
Lander, E. S., Green, P., Abrahamson, J., Barlow, A., Daly, M. J., Lincoln, S. E. & Newburg, L. (1987). Mapmaker: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics 1, 174–181.CrossRefGoogle ScholarPubMed
Lenardón, S. L., March, G. J., Nome, S. F. & Ornaghi, J. A. (1998). Recent outbreak of ‘Mal de Río Cuarto’ virus on corn in Argentina. Plant Disease 82, 448 (Abstract).CrossRefGoogle ScholarPubMed
Lucas, J. A. (2010). Advances in plant disease and pest management. Journal of Agricultural Science, Cambridge 149 (Supp. 1), 91–114.CrossRefGoogle Scholar
McMullen, M. D. & Simcox, K. D. (1995). Genomic organization of disease and insect resistance genes in maize. Molecular Plant–Microbe Interactions 8, 811–815.CrossRefGoogle Scholar
Nome, S. F., Lenardón, S. L., Raju, B. C., Laguna, I. G., Lowe, S. K. & Docampo, D. (1981). Association of reovirus-like particles with Enfermedad de Río IV of maize in Argentina. Phytopathologische Zeitschrift 101, 7–15.CrossRefGoogle Scholar
Ornaghi, J. A., Boito, G., Sanchez, G., March, G. & Beviacqua, J. E. (1993). Studies on the populations of Delphacodes kuscheli Fennah in different years and agricultural areas. Journal of Genetics and Breeding 47, 277–282.Google Scholar
Ornaghi, J. A., March, G. J., Boito, G. T., Marinelli, A., Beviacqua, J. E., Giuggia, J. & Lenardón, S. L. (1999). Infectivity in natural populations of Delphacodes kuscheli vector of “Mal de Río Cuarto” virus. Maydica 44, 219–223.Google Scholar
Pernet, A., Hoisington, D., Dintinger, J., Jewell, D., Jiang, C., Khairallah, M., Letourmy, P., Marchand, J. L., Glaszmann, J. C. & González de León, D. (1999 b). Genetic mapping of maize streak virus resistance from the Mascarene source. II. Resistance in line CIRAD390 and stability across germplasm. Theoretical and Applied Genetics 99, 540–553.CrossRefGoogle ScholarPubMed
Pernet, A., Hoisington, D., Franco, J., Isnard, M., Jewell, D., Jiang, C., Marchand, J. L., Reynaud, B., Glaszmann, J. C. & González de León, D. (1999 a). Genetic mapping of maize streak virus resistance from the Mascarene source. I. Resistance in line D211 and stability against different virus clones. Theoretical and Applied Genetics 99, 524–540.CrossRefGoogle ScholarPubMed
Presello, D., Céliz, A. & Frutos, E. (1995). Efectos genéticos asociados con la resistencia a la enfermedad Mal de Río Cuarto en líneas endocriadas de maíz. In Proceedings of III Latin American and XVI Andean Zone of Maize Researchers Meeting, Tomo I, (Eds Avila, L. G. & Céspedes-P, L. M..), pp. 407–413. Bolivia: Fundación S. I. Patiño.Google Scholar
Redinbaugh, M. G., Jones, M. W. & Gingery, R. E. (2004). The genetics of virus resistance in maize (Zea mays L.). Maydica 49, 183–190.Google Scholar
Redinbaugh, M. G. & Pratt, R. C. (2009). Virus resistance. In Handbook of Maize: Its Biology (Eds Bennetzen, J. L. & Hake, S. C.), pp. 251–270. New York: Springer Verlag.CrossRefGoogle Scholar
Saghai-Maroof, M. A., Soliman, K. M., Jorgensen, R. A. & Allard, R. W. (1984). Ribosomal DNA spacer-length polymorphisms in barley: mendelian inheritance, chromosomal location, and population dynamics. Proceeding of National Academy of Sciences of the United States of America 81, 8014–8018.CrossRefGoogle ScholarPubMed
Sambrook, J., Fritsch, E. F. & Maniatis, T. (1989). Molecular Cloning: a Laboratory Manual, 2nd edn. New York: Cold Spring Harbor Laboratory Press.Google Scholar
Shapiro, S. S. & Francia, R. S. (1972). An approximate analysis of variance test for normality. Journal of the American Statistical Association 67, 215–216.CrossRefGoogle Scholar
SAS Institute (2002). SAS/STAT release 9.1. Cary, NC: SAS Institute.Google Scholar
Utz, H. F. & Melchinger, A. E. (1996). PLABQTL. A program for composite interval mapping of QTL. Journal of Agricultural Genomics. Available online at: https://www.uni-hohenheim.de/plantbreeding/software/ (verified 9 November 2011).Google Scholar
Wang, G. X., Chen, Y., Zhao, J. R., Li, L., Korban, S. S., Wang, F. G., Li, J. S., Dai, J. R. & Xu, M. L. (2007). Mapping of defense response gene homologs and their association with resistance loci in maize. Journal of Integrative Plant Biology 49, 1580–1598.CrossRefGoogle Scholar
Welz, H. G., Schechert, A., Pernet, A., Pixley, K. V. & Geiger, H. H. (1998). A gene for resistance to the maize streak virus in the African CIMMYT maize inbred line CML202. Molecular Breeding 4, 147–154.CrossRefGoogle Scholar
Wisser, R. J., Balint-Kurti, P. J. & Nelson, R. J. (2006). The genetic architecture of disease resistance in maize: A synthesis of published studies. Phytopathology 96, 120–129.CrossRefGoogle Scholar
Yan, W. & Rajcan, I. (2003). Prediction of cultivar performance based on single-versus multiple-year tests in soybean. Crop Science 43, 549–555.Google Scholar
Zeng, Z. B. (1994). Precision mapping of quantitative trait loci. Genetics 136, 1457–1468.CrossRefGoogle ScholarPubMed