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Genome-wide association study for resistance to cassava root rot

Published online by Cambridge University Press:  26 October 2017

A. C. BRITO ,
S. A. S. OLIVEIRA  and
E. J. OLIVEIRA
A. C. BRITO
Affiliation:
Embrapa Mandioca e Fruticultura, Rua da Embrapa, Caixa Postal 007, Zip Code 44380-000 Cruz das Almas, BA, Brazil
S. A. S. OLIVEIRA
Affiliation:
Embrapa Mandioca e Fruticultura, Rua da Embrapa, Caixa Postal 007, Zip Code 44380-000 Cruz das Almas, BA, Brazil Universidade Federal do Recôncavo da Bahia, Campus Cruz das Almas, Zip Code 44380-000 Cruz das Almas, BA, Brazil
E. J. OLIVEIRA*
Affiliation:
Embrapa Mandioca e Fruticultura, Rua da Embrapa, Caixa Postal 007, Zip Code 44380-000 Cruz das Almas, BA, Brazil Universidade Federal do Recôncavo da Bahia, Campus Cruz das Almas, Zip Code 44380-000 Cruz das Almas, BA, Brazil
*
*To whom all correspondence should be addressed. Email: [email protected]
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Summary

Cassava root rot (CRR) disease associated with a complex of soil pathogens has caused great yield losses in the crop. The objective of the current work was to obtain insights about the genetic architecture of CRR resistance caused by Fusarium (dry root rot – DRR), Phytophthora (soft root rot – SRR) and Botryosphaeriaceae (black root rot – BRR) species, using genome-wide association studies (GWAS). Phenotyping data of 263 accessions (artificial inoculation) and 14 094 single-nucleotide polymorphisms (SNP) (missing data <0·10 and minor allele frequency >0·05) were used. The severity of CRR in peel and pulp was variable among accessions, but the pathogens that caused DRR were more aggressive. Broad-sense heritability ($h_g^2 $) was of medium magnitude for all groups of resistances for pathogens, with variation from 0·16 ± 0·019 (Fspp Pulp) to 0·31 ± 0·028 (Fspp Peel). The kinship matrix was used to correct for stratification as well as for clustering the accessions. Overall, this analysis showed that there was no relationship between agronomic traits and resistance to CRR and the four clusters obtained from kinship matrix. The GWAS identified 38 significant SNPs, of which eight and 22 are related to the severity of DRR in the pulp and peel, respectively. The other eight SNPs were associated with SRR-peel (1), SRR-pulp (1), BRR-peel (3) and BRR-pulp (3). Half of the SNPs associated with CRR resistance have functional annotations related to defence and response to pathogen attack as well as general cellular processes. The current study revealed that resistance to CRR is controlled by multiple loci with small effects, and significant SNPs can be used to identify putative genes that control these traits.

Type
Crops and Soils Research Papers
Information
The Journal of Agricultural Science , Volume 155 , Issue 9 , November 2017 , pp. 1424 - 1441
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Copyright © Cambridge University Press 2017 

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References

REFERENCES

Alleyne, A. T., Gilkes, J. M. & Briggs, G. (2015). Early detection of super-elongation disease in Manihot esculenta Crantz (cassava) using molecular markers for gibberellic acid biosynthesis. European Journal of Plant Pathology 141, 27–34.Google Scholar
Andolfo, G., Sanseverino, W., Aversano, R., Frusciante, L. & Ercolano, M. R. (2014). Genome-wide identification and analysis of candidate genes for disease resistance in tomato. Molecular Breeding 33, 227–233.Google Scholar
Arruda, M. P., Brown, P., Brown-Guedira, G., Krill, A. M., Thurber, C., Merrill, K. R., Foresman, B. J. & Kolb, F. L. (2016). Genome-wide association mapping of Fusarium head blight resistance in wheat (Triticum aestivum L.) using genotyping-by-sequencing. The Plant Genome 9, 1–14.Google Scholar
Bandyopadhyay, R., Mwangi, M., Aigbe, S. O. & Leslie, J. F. (2006). Fusarium species from the cassava root rot complex in West Africa. Phytopathology 96, 673–676.CrossRefGoogle ScholarPubMed
Banito, A., Kpémoua, K. E., Bissang, B. & Wydra, K. (2010). Assessment of cassava root and stem rots in ecozones of Togo and evaluation of the pathogen virulence. Pakistan Journal of Botany 42, 2059–2068.Google Scholar
Barros, J. A., Medeiros, E. V., Notaro, K. A., Moraes, W. S., Silva, J. M., Nascimento, T. C. E. S. & Moreira, K. A. (2014). Different cover promote sandy soil suppressiveness to root rot disease of cassava caused by Fusarium solani . African Journal of Microbiology Research 8, 967–973.Google Scholar
Begum, H., Spindel, J. E., Lalusin, A., Borromeo, T., Gregorio, G., Hernandez, J., Virk, P., Collard, B. & McCouch, S. R. (2015). Genome-wide association mapping for yield and other agronomic traits in an elite breeding population of tropical rice (Oryza sativa). PLoS ONE 10, e0119873. doi: 10.1371/journal.pone.0119873.Google Scholar
Bi, H., Aileni, M. & Zhang, P. (2010). Evaluation of cassava varieties for cassava mosaic disease resistance jointly by agro-inoculation screening and molecular markers. African Journal of Plant Science 4, 330–338.Google Scholar
Bonhomme, M., André, O., Badis, Y., Ronfort, J., Burgarella, C., Chantret, N., Prosperi, J. M., Briskine, R., Mudge, J., Debelle, F., Navier, H., Miteul, H., Hajri, A., Baranger, A., Tiffin, P., Dumas, B., Pilet-Nayel, M. L., Young, N. D. & Jacquet, C. (2014). High-density genome-wide association mapping implicates an F-box encoding gene in Medicago truncatula resistance to Aphanomyces euteiches . New Phytologist 201, 1328–1342.CrossRefGoogle ScholarPubMed
Carmo, C. D., da Silva, M. S., Oliveira, G. A. F. & de Oliveira, E. J. (2015). Molecular-assisted selection for resistance to cassava mosaic disease in Manihot esculenta Crantz. Scientia Agricola 72, 520–527.Google Scholar
Ceballos, H., Okogbenin, E., Pérez, J. C., López-Lavalle, L.A.B. & Debouck, D. (2010). Cassava. In Root and Tuber Crops (Ed. Bradshaw, J. E.), pp. 53-96. New York: Springer.Google Scholar
Ceballos, H., Kulakow, P. & Hershey, C. (2012). Cassava breeding: current status, bottlenecks and the potential of biotechnology tools. Tropical Plant Biology 5, 73–87.CrossRefGoogle Scholar
Ceballos, H., Kawuki, R. S., Gracen, V. E., Yencho, G. C. & Hershey, C. H. (2015). Conventional breeding, marker-assisted selection, genomic selection and inbreeding in clonally propagated crops: a case study for cassava. Theoretical and Applied Genetics 128, 1647–1667.Google Scholar
Covarrubias-Pazaran, G., Diaz-Garcia, L., Schlautman, B., Deutsch, J., Salazar, W., Hernandez-Ochoa, M., Grygleski, E., Steffan, S., Iorizzo, M., Polashock, J., Vorsa, N. & Zalapa, J. (2016). Exploiting genotyping by sequencing to characterize the genomic structure of the American cranberry through high-density linkage mapping. BMC Genomics 17, 451. doi: 10.1186/s12864-016-2802-3.Google Scholar
Dell'Acqua, M., Zuccolo, A., Tuna, M., Gianfranceschi, L. & Pè, M. E. (2014). Targeting environmental adaptation in the monocot model Brachypodium distachyon: a multi-faceted approach. BMC Genomics 15, 801. doi: 10.1186/1471-2164-15-801.Google Scholar
Doyle, J. J. & Doyle, J. L. (1990). Isolation of plant DNA from fresh tissue. Focus 12, 13–15.Google Scholar
Elshire, R. J., Glaubitz, J. C., Sun, Q., Poland, J. A., Kawamoto, K., Buckler, E. S. & Mitchell, S. E. (2011). A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS ONE 6, e19379. doi: 10.1371/journal.pone.0019379.Google Scholar
Ferguson, M., Koga, T. M., Johnson, D. A., Koga, K. A., Hirsch, G. N., Becerra López-Lavalle, L. A. & Messier, W. (2015). Identification of genes that have undergone adaptive evolution in cassava (Manihot esculenta) and that may confer resistance to cassava brown streak disease. African Journal of Biotechnology 14, 96–107.Google Scholar
Flint-Garcia, S. A., Thuillet, A. C., Yu, J., Pressoir, G., Romero, S. M., Mitchell, S. E., Doebley, J., Kresovich, S., Goodman, M. M. & Buckler, E. S. (2005). Maize association population: a high-resolution platform for quantitative trait locus dissection. The Plant Journal 44, 1054–1064.Google Scholar
Food and Agriculture Organization (FAO) (2013). Save and Grow: Cassava. A Guide to Sustainable Production Intensification. Rome, Italy: FAO. Available from: http://www.fao.org/docrep/018/i3278e/i3278e.pdf (accessed 9 February 2017).Google Scholar
Freitas, J. P. X., Santos, V. S. & Oliveira, E. J. (2016). Inbreeding depression in cassava for productive traits. Euphytica 209, 137–145.Google Scholar
Gupta, P. K., Rustgi, S. & Kulwal, P. L. (2005). Linkage disequilibrium and association studies in higher plants: present status and future prospects. Plant Molecular Biology 57, 461–485.Google Scholar
Hazzouri, K. M., Flowers, J. M., Visser, H. J., Khierallah, H. S. M., Rosas, U., Pham, G. M., Meyer, R. S., Johansen, C. K., Fresquez, Z. A., Masmoudi, K., Haider, N., El Kadri, N., Idaghdour, Y., Malek, J. A., Thirkhill, D., Markhand, G. S., Krueger, R. R., Zaid, A. & Purugganan, M. D. (2015). Whole genome re-sequencing of date palms yields insights into diversification of a fruit tree crop. Nature Communications 6, 8824. doi: 10.1038/ncomms9824.Google Scholar
Hokanson, K. E., Ellstrand, N. C., Dixon, A. G., Kulembeka, H. P., Olsen, K. M. & Raybould, A. (2016). Risk assessment of gene flow from genetically engineered virus resistant cassava to wild relatives in Africa: an expert panel report. Transgenic Research 25, 71–81.Google Scholar
Iquira, E., Humira, S. & François, B. (2015). Association mapping of QTLs for sclerotinia stem rot resistance in a collection of soybean plant introductions using a genotyping by sequencing (GBS) approach. BMC Plant Biology 15, 5. doi: 10.1186/s12870-014-0408-y.Google Scholar
Jansson, C., Westerbergh, A., Zhang, J., Hu, X. & Sun, C. (2009). Cassava, a potential biofuel crop in (the) People's Republic of China. Applied Energy 86 (Suppl. 1), S95–S99.Google Scholar
Kang, H. M., Zaitlen, N. A., Wade, C. M., Kirby, A., Heckerman, D., Daly, M. J. & Eskin, E. (2008). Efficient control of population structure in model organism association mapping. Genetics 178, 1709–1723.Google Scholar
Kaweesi, T., Kawuki, R., Kyaligonza, V., Baguma, Y., Tusiime, G. & Ferguson, M. E. (2014). Field evaluation of selected cassava genotypes for cassava brown streak disease based on symptom expression and virus load. Virology Journal 11, 216. doi: 10.1186/s12985-014-0216-x.Google Scholar
Kawuki, R. S., Ferguson, M., Labuschagne, M., Herselman, L. & Kim, D. J. (2009). Identification, characterisation and application of single nucleotide polymorphisms for diversity assessment in cassava (Manihot esculenta Crantz). Molecular Breeding 23, 669–684.Google Scholar
Kertho, A., Mamidi, S., Bonman, J. M., McClean, P. E. & Acevedo, M. (2015). Genome-wide association mapping for resistance to leaf and stripe rust in winter-habit hexaploid wheat landraces. PLoS ONE 10, e0129580. doi: 10.1371/journal.pone.0129580.Google Scholar
Khumaida, N., Ardie, S. W., Dianasari, M. & Syukur, M. (2015). Cassava (Manihot esculenta Crantz.) improvement through gamma irradiation. Procedia Food Science 3, 27–34.CrossRefGoogle Scholar
Li, L., Guo, N., Niu, J., Wang, Z., Cui, X., Sun, J., Zhao, T. & Xing, H. (2016). Loci and candidate gene identification for resistance to Phytophthora sojae via association analysis in soybean [Glycine max (L.) Merr.]. Molecular Genetics and Genomics 291, 1095–1103.Google Scholar
Lipka, A. E., Tian, F., Wang, Q., Peiffer, J., Li, M., Bradbury, P. J., Gore, M. A., Buckler, E. S. & Zhang, Z. (2012). GAPIT: genome association and prediction integrated tool. Bioinformatics 28, 2397–2399.Google Scholar
Louis, B. & Rey, C. (2015). Resistance gene analogs involved in tolerant cassava–geminivirus interaction that shows a recovery phenotype. Virus Genes 51, 393–407.Google Scholar
Lozano, R., Hamblin, M. T., Prochnik, S. & Jannink, J. C. (2015). Identification and distribution of the NBS-LRR gene family in the cassava genome. BMC Genomics 16, 360. doi: 10.1186/s12864-015-1554-9.CrossRefGoogle ScholarPubMed
Mammadov, J., Aggarwal, R., Buyyarapu, R. & Kumpatla, S. (2012). SNP markers and their impact on plant breeding. International Journal of Plant Genomics 2012, 1–11 Article ID 728398. doi: 10.1155/2012/728398.Google Scholar
Manu-Aduening, J. A., Peprah, B. B. & Agyeman, A. (2013). Genetic variability of cassava progenies developed through introgression of cassava mosaic disease resistance into Ghanaian landraces. Journal of Crop Science and Biotechnology 16, 23–28.Google Scholar
Marone, D., Panio, G., Ficco, D. B. M., Russo, M. A., De Vita, P., Papa, R., Rubiales, D., Cattivelli, L. & Mastrangelo, A. M. (2012). Characterization of wheat DArT markers: genetic and functional features. Molecular Genetics and Genomics 287, 741–753.Google Scholar
Mazzola, M. & Gu, Y. H. (2002). Wheat genotype-specific induction of soil microbial communities suppressive to disease incited by Rhizoctonia solani anastomosis group (AG)-5 and AG-8. Phytopathology 92, 1300–1307.Google Scholar
Mengistu, D. K., Kidane, Y. G., Catellani, M., Frascaroli, E., Fadda, C., Pè, M. E. & Dell'Acqua, M. (2016). High-density molecular characterization and association mapping in Ethiopian durum wheat landraces reveals high diversity and potential for wheat breeding. Plant Biotechnology Journal 14, 1800–1812.Google Scholar
Meuwissen, T. H. E., Hayes, B. J. & Goddard, M. E. (2001). Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 1819–1829.Google Scholar
Nwokoro, S. O., Orheruata, A. M. & Ordiah, P. I. (2002). Replacement of maize with cassava sievates in cockerel starter diets: effect on performance and carcass characteristics. Tropical Animal Health and Production 34, 163–167.Google Scholar
Nyaka, N. G. A. I. C., Kammegne, D. P., Ntsomboh, N. G., Mbenoun, M., Zok, S. & Fontem, D. (2015). Isolation and identification of some pathogenic fungi associated with cassava (Manihot esculenta Crantz) root rot disease in Cameroon. African Journal of Agricultural Research 10, 4538–4542.Google Scholar
Oliveira, E. J., Resende, M. D. V., Santos, V. S., Ferreira, C. S., Oliveira, G. A. F., Silva, M. S. & Aguilar-Vildoso, C. I. (2012). Genome-wide selection in cassava. Euphytica 187, 263–276.Google Scholar
Oliveira, E. J., Ferreira, C. F., Santos, V. S. & Oliveira, G. A. (2014). Development of a cassava core collection based on single nucleotide polymorphism markers. Genetics and Molecular Research 13, 6472–6485.Google Scholar
Oliveira, S. A. S., Hohenfeld, C. S., Santos, V. S., Haddad, F. & de Oliveira, E. J. (2013). Resistance to Fusarium dry root rot disease in cassava accessions. Pesquisa Agropecuária Brasileira 48, 1414–1417.Google Scholar
Onyeka, T. J., Dixon, A. G. O. & Ekpo, E. J. A. (2005). Identification of levels of resistance to cassava root rot disease (Botryodiplodia theobromae) in African landraces and improved germplasm using in vitro inoculation method. Euphytica 145, 281–288.Google Scholar
Pariaud, B., Ravigné, V., Halkett, F., Goyeau, H., Carlier, J. & Lannou, C. (2009). Aggressiveness and its role in the adaptation of plant pathogens. Plant Pathology 58, 409–424.Google Scholar
Parkes, E. Y., Fregene, M., Dixon, A., Boakye-Peprah, B. & Labuschagne, M. T. (2013). Combining ability of cassava genotypes for cassava mosaic disease and cassava bacterial blight, yield and its related components in two ecological zones in Ghana. Euphytica 194, 13–24.Google Scholar
Poland, J. A. & Rife, T. W. (2012). Genotyping-by-sequencing for plant breeding and genetics. The Plant Genome 5, 92–102.Google Scholar
Rabbi, I., Hamblin, M., Gedil, M., Kulakow, P., Ferguson, M., Ikpan, A. S., Ly, D. & Jannink, J. L. (2015). Genetic mapping using genotyping-by-sequencing in the clonally propagated cassava. Crop Science 54, 1384–1396.Google Scholar
Rabbi, I. Y., Hamblin, M. T., Kumar, P. L., Gedil, M. A., Ikpan, A. S., Jannink, J. L. & Kulakow, P. A. (2014). High-resolution mapping of resistance to cassava mosaic geminiviruses in cassava using genotyping-by-sequencing and its implications for breeding. Virus Research 186, 87–96.Google Scholar
Radhika, N. K., Sheela, M. N., Devi, A. A., Sreekumar, J., Kumar, T. M. & Chakrabarti, S. K. (2014). Genetic modification for designer starch from cassava. Journal of Tropical Agriculture 52, 1–6.Google Scholar
R Core Team (2015). R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing.Google Scholar
Resende, M. D. V. (2002). Genética Biométrica e Estatística no Melhoramento de Plantas Perenes. Colombo: Embrapa Florestas: Embrapa Informação Tecnológica, Brasília: Embrapa Informação Tecnológica.Google Scholar
Riedelsheimer, C., Czedik-Eysenberg, A., Grieder, C., Lisec, J., Technow, F., Sulpice, R., Altmann, T., Stitt, M., Willmitzer, L. & Melchinger, A. E. (2012). Genomic and metabolic prediction of complex heterotic traits in hybrid maize. Nature Genetics 44, 217–220.Google Scholar
Rutkoski, J. E., Poland, J., Jannink, J.-L. & Sorrells, M. E. (2013). Imputation of unordered markers and the impact on genomic selection accuracy. G3: Genes, Genomes, Genetics 3, 427–439.Google Scholar
Silva, C. A. D., Medeiros, E. V., Bezerra, C. B., Silva, W. M., Barros, J. A. & Santos, U. J. (2013). Interferência da incorporação de matéria orgânica no solo no controle da podridão negra da mandioca, causada por Scytalidium lignicola . Bioscience Journal 29, 1823–1831.Google Scholar
Singh, R. K., Banerjee, N., Khan, M. S., Yadav, S., Kumar, S., Duttamajumder, S. K., Lal, R. J., Patel, J. D., Guo, H., Zhang, D. & Paterson, A. H. (2016). Identification of putative candidate genes for red rot resistance in sugarcane (Saccharum species hybrid) using LD-based association mapping. Molecular Genetics and Genomics 291, 1363–1377.CrossRefGoogle ScholarPubMed
Soto, J. C., Ortiz, J. F., Perlaza-Jiménez, L., Vásquez, A. X., Lopez-Lavalle, L. A. B., Mathew, B., Léon, J., Bernal, A. J., Ballvora, A. & López, C. E. (2015). A genetic map of cassava (Manihot esculenta Crantz) with integrated physical mapping of immunity-related genes. BMC Genomics 16, 190. doi: 10.1186/s12864-015-1397-4.Google Scholar
Souza, L. S., Farias, A. R. N., Mattos, P. L. P. & Fukuda, W. M. G. (2006). Aspectos Socioeconômicos e Agronômicos da Mandioca. Cruz das Almas-Bahia, Brazil: Embrapa Mandioca e Fruticultura.Google Scholar
Tonukari, N. J. (2004). Cassava and the future of starch. Electronic Journal of Biotechnology 7, 5–8.Google Scholar
VanRaden, P. M. (2008). Efficient methods to compute genomic predictions. Journal of Dairy Science 91, 4414–4423.Google Scholar
Vilas Boas, S. A., Hohenfeld, C. S., Oliveira, S. A., Santos, V. S. & de Oliveira, E. J. (2016). Sources of resistance to cassava root rot caused by Fusarium spp.: a genotypic approach. Euphytica 209, 237–251.Google Scholar
Wang, Q., Tian, F., Pan, Y., Buckler, E. S. & Zhang, Z. (2014). A super powerful method for genome wide association study. PLoS ONE 9, e107684. doi: 10.1371/journal.pone.0107684.Google Scholar
Weisberg, S. (2005). Applied Linear Regression, 3rd edn. Hoboken, NJ: John Wiley & Sons.Google Scholar
Wolfe, M. D., Rabbi, I. Y., Egesi, C., Hamblin, M., Kawuki, R., Kulakow, P., Lozano, R., Carpio, D. P., Ramu, P. & Jannink, J. L. (2016). Genome-wide association and prediction reveals genetic architecture of cassava mosaic disease resistance and prospects for rapid genetic improvement. The Plant Genome 9, 1–13. doi: 10.3835/plantgenome2015.11.0118.Google Scholar
Wu, X., Wu, X., Xu, P., Wang, B., Lu, Z. & Li, G. (2015). Association mapping for Fusarium wilt resistance in Chinese asparagus bean germplasm. The Plant Genome 8, 1–6. doi: 10.3835/plantgenome2014.11.008.Google Scholar
Yan, J., Shah, T., Warburton, M. L., Buckler, E. S., McMullen, M. D. & Crouch, J. (2009). Genetic characterization and linkage disequilibrium estimation of a global maize collection using SNP markers. PLoS ONE 4, e8451. doi: 10.1371/journal.pone.0008451.Google Scholar
Zaitsev, V. S., Naroditsky, B. S. & Khavkin, E. E. (2002). Homologs of the genes for receptor-like kinase proteins conferring plant resistance to pathogens: resistance gene homologs in Solanum species. Russian Journal of Plant Physiology 49, 810–816.Google Scholar
Zanke, C. D., Ling, J., Plieske, J., Kollers, S., Ebmeyer, E., Korzun, V., Argillier, O., Stiewe, G., Hinze, M., Neumann, F., Eichhorn, A., Polley, A., Jaenecke, C., Ganal, M. W. & Röder, M. S. (2015). Analysis of main effect QTL for thousand grain weight in European winter wheat (Triticum aestivum L.) by genome-wide association mapping. Frontiers in Plant Science 6, 644. doi: 10.3389/fpls.2015.00644.Google Scholar
Zegeye, H., Rasheed, A., Makdis, F., Badebo, A. & Ogbonnaya, F. C. (2014). Genome-wide association mapping for seedling and adult plant resistance to stripe rust in synthetic hexaploid wheat. PLoS ONE 9, e105593. doi: 10.1371/journal.pone.0105593.Google Scholar
Zhang, J., Song, Q., Cregan, P. B. & Jiang, G. L. (2016). Genome-wide association study, genomic prediction and marker-assisted selection for seed weight in soybean (Glycine max). Theoretical and Applied Genetics 129, 117–130.Google Scholar
Zhang, Z., Ersoz, E., Lai, C. Q., Todhunter, R. J., Tiwari, H. K., Gore, M. A., Bradbury, P. J., Yu, J., Arnett, D. K., Ordovas, J. M. & Buckler, E. S. (2010). Mixed linear model approach adapted for genome-wide association studies. Nature Genetics 42, 355–360.Google Scholar
Zila, C. T., Ogut, F., Romay, M. C., Gardner, C. A., Buckler, E. S. & Holland, J. B. (2014). Genome-wide association study of Fusarium ear rot disease in the USA maize inbred line collection. BMC Plant Biology 14, 372. doi: 10.1186/s12870-014-0372-6.Google Scholar
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