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Research Article | Open Access

Systematic dissection of disease resistance to southern corn rust by bulked-segregant and transcriptome analysis

Xiaohuan Mu1Zhuangzhuang Dai1Zhanyong GuoHui ZhangJianping YangXinke GanJiankun LiZonghua LiuJihua Tang( )Mingyue Gou( )
State Key Laboratory of Wheat and Maize Crop Science, Collaborative Innovation Center of Henan Grain Crops, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, Henan, China

1 These authors contributed equally to this work.

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Abstract

Southern corn rust (SCR) is a destructive maize disease caused by Puccinia polysora Underw. To investigate the mechanism of SCR resistance in maize, a highly resistant inbred line, L119A, and a highly susceptible line, Lx9801, were subjected to gene mapping and transcriptome analysis. Bulked-segregant analysis coupled with whole-genome sequencing revealed several quantitative trait loci (QTL) on chromosomes 1, 6, 8, and 10. A set of 25 genes, including two coiled-coil nucleotide-binding site leucine-rich repeat (CC-NBS-LRR) genes, were identified as candidate genes for a major-effect QTL on chromosome 10. To investigate the mechanism of SCR resistance in L119A, RNA-seq of P. polysora-inoculated and non-inoculated plants of L119A and Lx9801 was performed. Unexpectedly, the number of differentially expressed genes in inoculated versus non-inoculated L119A plants was about 10 times that of Lx9801, with only 29 common genes identified in both lines, suggesting extensive gene expression changes in the highly resistant but not in the susceptible line. Based on the transcriptome analysis, one of the CC-NBS-LRR candidate genes was confirmed to be upregulated in L119A relative to Lx9801 independently of P. polysora inoculation. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses indicated that transcription factors, as well as genes involved in defense responses and metabolic processes, were dominantly enriched, with the phenylpropanoid biosynthesis pathway most specifically activated. Consistently, accumulation of phenylpropanoid-derived lignin, especially S lignin, was drastically increased in L119A after P. polysora inoculation, but remained unchanged in Lx9801, suggesting a critical role of lignin in SCR resistance. A regulatory network of defense activation and metabolic change in SCR-resistant maize upon P. polysora infection is described.

References

[1]

T.J. Klopfenstein, G.E. Erickson, L.L. Berger, Maize is a critically important source of food, feed, energy and forage in the USA, Field Crops Res. 153 (2013) 5–11.

[2]

J.B. Holland, D.V. Uhr, D. Jeffers, M.M. Goodman, Inheritance of resistance to southern corn rust in tropical by corn-belt maize populations, Theor. Appl. Genet. 96 (1998) 232–241.

[3]

S. Wang, Z. Chen, L. Tian, Y. Ding, J. Zhang, J. Zhou, P. Liu, Y. Chen, L. Wu, Comparative proteomics combined with analyses of transgenic plants reveal ZmREM1.3 mediates maize resistance to southern corn rust, Plant Biotechnol. J. 17 (2019) 2153–2168.

[4]

R. Rodriguezardon, G.E. Scott, S.B. King, maize yield losses caused by southern corn rust, Crop Sci. 20 (1980) 812–814.

[5]

R.N. Raid, Characterization of Puccinia-Polysora epidemics in Pennsylvania and Maryland, Phytopathology 78 (5) (1988) 579.

[6]

P. Zhao, G. Zhang, X. Wu, N. Li, D. Shi, D. Zhang, C. Ji, M. Xu, S. Wang, Fine mapping of RppP25, a southern rust resistance gene in maize, J. Integr. Plant Biol. 55 (2013) 462–472.

[7]

L.u. Lu, Z. Xu, S. Sun, Q. Du, Z. Zhu, J. Weng, C. Duan, Discovery and fine mapping of qSCR6.01, a novel major QTL conferring southern rust resistance in maize, Plant Dis. 104 (2020) 1918–1924.

[8]

K. Wanlayaporn, J. Authrapun, A. Vanavichit, S. Tragoonrung, QTL mapping for partial resistance to southern corn rust using RILs of tropical sweet corn, Am. J. Plant Sci. 04 (2013) 878–889.

[9]

S. Wang, R. Zhang, Z. Shi, Y. Zhao, A. Su, Y. Wang, J. Xing, J. Ge, C. Li, X. Wang, J. Wang, X. Sun, Q. Liu, Y. Chen, Y. Zhang, S. Wang, W. Song, J. Zhao, Identification and fine mapping of RppM, a southern corn rust resistance gene in maize, Front. Plant Sci. 11 (2020) 1057.

[10]

Y.A. Zhang, L.I. Xu, D.F. Zhang, J.R. Dai, S.C. Wang, Mapping of southern corn rust-resistant genes in the W2D inbred line of maize (Zea mays L.), Mol. Breed. 25 (2010) 433–439.

[11]

C. Zhou, C. Chen, P. Cao, S. Wu, J. Sun, D. Jin, B. Wang, Characterization and fine mapping of RppQ, a resistance gene to southern corn rust in maize, Mol. Genet. Genomics 278 (2007) 723–728.

[12]

M.P. Jines, P. Balint-Kurti, L.A. Robertson-Hoyt, T. Molnar, J.B. Holland, M.M. Goodman, Mapping resistance to Southern rust in a tropical by temperate maize recombinant inbred topcross population, Theor. Appl. Genet. 114 (2007) 659–667.

[13]

M. Lv, C. Deng, X.Y. Li, X.D. Zhao, H.M. Li, Z.M. Li, Z.Q. Tian, A. Leonard, J. Jaqueth, B.L. Li, J.J. Hao, Y.X. Chang, J.Q. Ding, Identification and fine-mapping of RppCML496, a major QTL for resistance to Puccinia polysora in maize, Plant Genome 14 (2021) 7.

[14]

C. Deng, M. Lv, X. Li, X. Zhao, H. Li, Z. Li, Z. Tian, A. Lenoard, J. Jaqueth, B. Li, J. Hao, J. Ding, Identification and fine-mapping of qSCR4.01, a novel major QTL for resistance to Puccinia polysora Underw in Maize, Plant Dis. 104 (2020) 1944–1948.

[15]

K. Schneeberger, S. Ossowski, C. Lanz, T. Juul, A.H. Petersen, K.L. Nielsen, J.E. Jorgensen, D. Weigel, S.U. Andersen, SHOREmap: simultaneous mapping and mutation identification by deep sequencing, Nat. Methods 6 (2009) 550–551.

[16]

H. Klein, Y. Xiao, P.A. Conklin, R. Govindarajulu, J.A. Kelly, M.J. Scanlon, C.J. Whipple, M. Bartlett, Bulked-segregant analysis coupled to whole genome sequencing (BSA-Seq) for rapid gene cloning in maize, G3-Genes Genomes Genet. 8 (2018) 3583–3592.

[17]

V.K. Singh, A.W. Khan, R.K. Saxena, V. Kumar, S.M. Kale, P. Sinha, A. Chitikineni, L.T. Pazhamala, V. Garg, M. Sharma, C.V. Sameer Kumar, S. Parupalli, S. Vechalapu, S. Patil, S. Muniswamy, A. Ghanta, K.N. Yamini, P.S. Dharmaraj, R.K. Varshney, Next-generation sequencing for identification of candidate genes for Fusarium wilt and sterility mosaic disease in pigeonpea (Cajanus cajan), Plant Biotechnol. J. 14 (2016) 1183–1194.

[18]

A. Lanubile, A. Ferrarini, V. Maschietto, M. Delledonne, A. Marocco, D. Bellin, Functional genomic analysis of constitutive and inducible defense responses to Fusarium verticillioides infection in maize genotypes with contrasting ear rot resistance, BMC Genomics 15 (2014) 16.

[19]

I. Schliebner, R. Becher, M. Hempel, H.B. Deising, R. Horbach, New gene models and alternative splicing in the maize pathogen Colletotrichum graminicola revealed by RNA-Seq analysis, BMC Genomics 15 (2014) 842.

[20]

Y. Wang, Z. Zhou, J. Gao, Y. Wu, Z. Xia, H. Zhang, J. Wu, The mechanisms of maize resistance to Fusarium verticillioides by comprehensive analysis of RNA-seq Data, Front. Plant Sci. 7 (2016) 1654.

[21]

J. Meyer, D.K. Berger, S.A. Christensen, S.L. Murray, RNA-Seq analysis of resistant and susceptible sub-tropical maize lines reveals a role for kauralexins in resistance to grey leaf spot disease, caused by Cercospora zeina, BMC Plant Biol. 17 (2017) 197.

[22]

A.Z. Kebede, A. Johnston, D. Schneiderman, W. Bosnich, L.J. Harris, Transcriptome profiling of two maize inbreds with distinct responses to Gibberella ear rot disease to identify candidate resistance genes, BMC Genomics 19 (2018) 131.

[23]

F. Shi, Y. Zhang, K. Wang, Q. Meng, X. Liu, L. Ma, Y. Li, J. Liu, L. Ma, Expression profile analysis of maize in response to Setosphaeria turcica, Gene 659 (2018) 100–108.

[24]

M.G. Murray, W.F. Thompson, Rapid isolation of high molecular-weight plant DNA, Nucleic Acids Res. 8 (1980) 4321–4326.

[25]

H. Li, R. Durbin, Fast and accurate short read alignment with Burrows-Wheeler transform, Bioinformatics 25 (2009) 1754–1760.

[26]

A. McKenna, M. Hanna, E. Banks, A. Sivachenko, K. Cibulskis, A. Kernytsky, K. Garimella, D. Altshuler, S. Gabriel, M. Daly, M.A. DePristo, The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data, Genome Res. 20 (2010) 1297–1303.

[27]

B.N. Mansfeld, R. Grumet, QTLseqr: an R package for bulk segregant analysis with next-generation sequencing, Plant Genome 11 (2018) 5.

[28]

P. Cingolani, A. Platts, L. Wang le, M. Coon, T. Nguyen, L. Wang, S.J. Land, X. Lu, D.M. Ruden, A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3, Fly 6 (2012) 80–92.

[29]

P.M. Magwene, J.H. Willis, J.K. Kelly, The statistics of bulk segregant analysis using next generation sequencing, PLoS Comput. Biol. 7 (2011) e1002255.

[30]

H. Takagi, A. Abe, K. Yoshida, S. Kosugi, S. Natsume, C. Mitsuoka, A. Uemura, H. Utsushi, M. Tamiru, S. Takuno, H. Innan, L.M. Cano, S. Kamoun, R. Terauchi, QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations, Plant J. 74 (2013) 174–183.

[31]

D. Kim, B. Langmead, S.L. Salzberg, HISAT: a fast spliced aligner with low memory requirements, Nat. Methods 12 (2015) 357–360.

[32]

M. Pertea, G.M. Pertea, C.M. Antonescu, T.C. Chang, J.T. Mendell, S.L. Salzberg, StringTie enables improved reconstruction of a transcriptome from RNA-seq reads, Nat. Biotechnol. 33 (2015) 290–295.

[33]

M.I. Love, W. Huber, S. Anders, Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2, Genome Biol. 15 (2014) 550.

[34]

T. Tian, Y. Liu, H. Yan, Q. You, X. Yi, Z. Du, W. Xu, Z. Su, agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update, Nucleic Acids Res. 45 (2017) W122–W129.

[35]

G. Yu, L. Wang, Y. Han, Q. He, clusterProfiler: an R package for comparing biological themes among gene clusters, Omics 16 (2012) 284–287.

[36]

C.M. Hooper, I.R. Castleden, S.K. Tanz, N. Aryamanesh, A.H. Millar, SUBA4: the interactive data analysis centre for Arabidopsis subcellular protein locations, Nucleic Acids Res. 45 (2017) D1064–D1074.

[37]

J. Jin, F. Tian, D. Yang, Y. Meng, L. Kong, J. Luo, G. Gao, PlantTFDB 4.0: toward a central hub for transcription factors and regulatory interactions in plants, Nucleic Acids Res. 45 (2017) D1040–D1045.

[38]

C. Ginestet, ggplot2: elegant graphics for data analysis, J. Royal Stat. Soc. Ser. A-Stat. Soc. 174 (2011) 245–245.

[39]

M. Gou, X. Yang, Y. Zhao, X. Ran, Y. Song, C.J. Liu, Cytochrome is an obligate electron shuttle protein for syringyl lignin biosynthesis in Arabidopsis, Plant Cell 31 (2019) 1344–1366.

[40]

X. Ran, F. Zhao, Y. Wang, J. Liu, Y. Zhuang, L. Ye, M. Qi, J. Cheng, Y. Zhang, Plant Regulomics: a data-driven interface for retrieving upstream regulators from plant multi-omics data, Plant J. 101 (2020) 237–248.

[41]

C.M.J. Pieterse, D. Van der Does, C. Zamioudis, A. Leon-Reyes, S.C.M. van Wees, Wees, Hormonal modulation of plant immunity, Annu. Rev. Cell Dev. Biol. 28 (2012) 489–521.

[42]

C. Scheler, J. Durner, J. Astier, Nitric oxide and reactive oxygen species in plant biotic interactions, Curr. Opin. Plant Biol. 16 (2013) 534–539.

[43]

P. Buscaill, S. Rivas, Transcriptional control of plant defence responses, Curr. Opin. Plant Biol. 20 (2014) 35–46.

[44]

A. Piasecka, N. Jedrzejczak‐Rey, P. Bednarek, Secondary metabolites in plant innate immunity: conserved function of divergent chemicals, New Phytol. 206 (2015) 948–964.

[45]

S.P. Pandey, M. Roccaro, M. Schoen, E. Logemann, I.E. Somssich, Transcriptional reprogramming regulated by WRKY18 and WRKY40 facilitates powdery mildew infection of Arabidopsis, Plant J. 64 (2010) 912–923.

[46]

J. Li, G. Brader, T. Kariola, E. Tapio Palva, WRKY70 modulates the selection of signaling pathways in plant defense, Plant J. 46 (2006) 477–491.

[47]

F. Vailleau, X. Daniel, M. Tronchet, J.L. Montillet, C. Triantaphylides, D. Roby, A R2R3-MYB gene, AtMYB30, acts as a positive regulator of the hypersensitive cell death program in plants in response to pathogen attack, Proc. Natl. Acad. Sci. U. S. A. 99 (2002) 10179–10184.

[48]

W.R. Chezem, A. Memon, F.S. Li, J.K. Weng, N.K. Clay, SG2-Type R2R3-MYB transcription factor MYB15 controls defense-induced lignification and basal immunity in Arabidopsis, Plant Physiol. 29 (2017) 1907–1926.

[49]

P.J. Seo, C. Park, MYB96-mediated abscisic acid signals induce pathogen resistance response by promoting salicylic acid biosynthesis in Arabidopsis, New Phytol. 186 (2010) 471–483.

[50]

P. Geng, S. Zhang, J. Liu, C. Zhao, J. Wu, Y. Cao, C. Fu, X. Han, H. He, Q. Zhao, MYB20, MYB42, MYB43, and MYB85 regulate phenylalanine and lignin biosynthesis during secondary cell wall formation, Plant Physiol. 182 (2020) 1272–1283.

[51]

Q. Zhao, R.A. Dixon, Transcriptional networks for lignin biosynthesis: more complex than we thought?, Trends Plant Sci. 16 (2011) 227–233.

[52]

X.C. Wang, J. Wu, M.L. Guan, C.H. Zhao, P. Geng, Q. Zhao, Arabidopsis MYB4 plays dual roles in flavonoid biosynthesis, Plant J. 101 (2020) 637–652.

[53]

M. Gou, X. Ran, D.W. Martin, C.J. Liu, The scaffold proteins of lignin biosynthetic cytochrome P450 enzymes, Nat. Plants 4 (2018) 299–310.

[54]

Q. Yang, Y. He, M. Kabahuma, T. Chaya, A. Kelly, E. Borrego, Y. Bian, F. El Kasmi, L. Yang, P. Teixeira, J. Kolkman, R. Nelson, M. Kolomiets, J. L Dangl, R. Wisser, J. Caplan, X. Li, N. Lauter, P. Balint-Kurti, A gene encoding maize caffeoyl-CoA O-methyltransferase confers quantitative resistance to multiple pathogens, Nat. Genet. 49 (2017) 1364–1372.

[55]

N. Li, B. Lin, H. Wang, X. Li, F. Yang, X. Ding, J. Yan, Z. Chu, Natural variation in ZmFBL41 confers banded leaf and sheath blight resistance in maize, Nat. Genet. 51 (2019) 1540–1548.

[56]

L. Gallego‐Giraldo, S. Posé, S. Pattathil, A.G. Peralta, M.G. Hahn, B.G. Ayre, J. Sunuwar, J. Hernandez, M. Patel, J. Shah, X. Rao, J.P. Knox, R.A. Dixon, Elicitors and defense gene induction in plants with altered lignin compositions, New Phytol. 219 (2018) 1235–1251.

The Crop Journal
Pages 426-435
Cite this article:
Mu X, Dai Z, Guo Z, et al. Systematic dissection of disease resistance to southern corn rust by bulked-segregant and transcriptome analysis. The Crop Journal, 2022, 10(2): 426-435. https://doi.org/10.1016/j.cj.2021.07.001

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Received: 17 January 2021
Revised: 13 June 2021
Accepted: 26 July 2021
Published: 11 August 2021
© 2021 Crop Science Society of China and Institute of Crop Science, CAAS.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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