Pathways and genes in common with other larval insect pest resistance studies
A similar study was done previously by this group on corn earworm (Helicoverpa zea (Boddie)) ear-damage levels in maize (Warburton et al., 2017), and five of the same or very closely related pathways were identified in both studies. These include wax esters biosynthesis II, simple coumarins biosynthesis, geranylgeranyl diphosphate (GGPP) biosynthesis, the chlorophyll degradation pathway, ent-kaurene biosynthesis I, and phospholipases biosynthesis. Wax esters are a component of epicuticular wax, which is a physical barrier to insect predation. Coumarins belong to the phenolics class of compounds, which repel feeding insects. The production of GGPP is the first step leading into the carotenoids and related pathways (Fig. 1). Phospholipases may be expressed when plants are wounded, as during insect feeding, and initiate production of important defense signaling molecules, such as oxylipins and jasmonates (De Vleesschauwer et al., 2014). All these mechanisms were important in FAW resistance as well and may form part of the common defense mechanisms of maize plants against many larval feeding insects.
Another recent study of the defense response of resistant maize lines to European corn borer (Ostrinia nubilalis ) and western corn rootworm (Diabrotica virgifera virgifera ), two insects whose larvae are economically damaging. These two studies used transcriptomics to identify changes in gene expression following feeding damage (Pingault et al., 2021). They found significant gene expression changes in a number of genes, some in common with the current study. These include genes encoding, regulating, or modifying carotenoids, coumarins, S-adenosyl-L-methionine, methionine, Acyl-CoA, glutathione, thioredoxin, histidine, myo-inositol, flavin, sterol, trehalose, chlorophyll, phospholipases, and phospholipids. While this list is too long and varied to point to a specific common mechanism of resistance, it does suggest that common mechanisms may exist, and may indicate where the search may begin.
Acknowledgments
The Authors would like to thank Susan Wolf, Gerald Matthews and Carol Carter-Wientjes for excellent technical and editorial help. Any mention of trade names or commercial products is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the USDA.
Conflict of Interest
The authors declare no conflict of interest.
ORCID
Marilyn L. Warburton: https://orcid.org/0000-0002-9542-9912
Lina Castano-Duque: https://orcid.org/0000-0001-9161-2907
W. Paul Williams: https://orcid.org/0000-0002-7827-3186
Matthew D. Lebar: https://orcid.org/0000-0003-4910-1438
Sandra W. Woolfolk: https://orcid.org/0000-0001-7025-9745
Supplemental Material
Supplemental Figure 1: QQ plot of association values calculated with the General Linear Model (GLM; 1a) and Mixed Linear Model (MLM; 1b).
Supplemental Figure 2: Box plots showing clusters and the distribution of the amounts of metabolites and Fall Armyworm ratings. Box-plot whiskers depict the maximum and minimum without outliers, and the box depicts median, first and third quantiles distribution. Data shown is transformed and scale to center around 0.
Supplemental Table 1: Fall Armyworm damage scores at 7 and 14 days after infestation for the panel of 289 diverse maize inbred lines used for this study, including averages and standard deviations over replications within years, and averaged over years.
Supplemental Table 2: Fall Armyworm damage score descriptions, from the original rating scale of Davis et al., 1991, for 7-day and 14-day time points following infestation with Fall Armyworm (FAW) neonates.
Supplemental Table 3: The MLM association scores for p < 0.05 associated with Fall Armyworm (FAW) damage levels.
Supplemental Table 4 : The pathways associated (p<0.05) with Fall Armyworm (FAW) damage levels.
Supplemental Table 5: Averaged data for the metabolites analyzed, clusters summary statistics and PCA variance contribution information.
References
Bradbury, P.J., Zhang, Z., Kroon, D.E., Casstevens, T.M., Ramdoss, Y., & Buckler, E.S. (2007). TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics , 23 (19), 2633-2635. https://doi.org/10.1093/bioinformatics/btm308
Benjamini Y. & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing.Journal of the Royal Statistical Society: Series B (Methodological) , 57 (1), 289-300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Brooks, T.D., Bushman, B.S., Williams, W.P., McMullen, M.D., & Buckley, P.M. (2007). Genetic basis of resistance to and southwestern corn borer (Lepidoptera: Crambidae) leaf-feeding damage in maize. Journal of Economic Entomology , 100 (4), 1470-1475. https://doi.org/10.1093/jee/100.4.1470
Davis, F.M. (1989). Rearing the southwestern corn borer and fall armyworm at Mississippi State. In, Toward insect resistance maize for the third world: Proceedings of the International Symposium on Methodologies for Developing Host Plant Resistance to Maize Insects .CIMMYT, Mexico, March 9-14, 1987 . (pp. 27-36). CIMMYT.
Davis, F.M., Ng, S.S., & Williams, W.P. (1992). Visual rating scales for screening whorl-stage corn for resistance to fall armyworm(Technical Bulletin 186). Mississippi Agricultural and Forestry Experiment Station.
Davis, F.M., Williams, W.P., & Buckley, P.M. (1998). Growth responses of southwestern corn borer (Lepidoptera: Crambidae) and fall armyworm (Lepidoptera: Noctuidae) larvae fed combinations of whorl leaf tissue from a resistant and a susceptible maize hybrid. Journal of Economic Entomology , 91 (5), 1213-1218. https://doi.org/10.1093/jee/91.5.1213
Davis, F. M., Williams, W. P., Chang, Y. M., Baker, G. T., & Hedin, P. A. (1999). Differential growth of fall armyworm larvae (Lepidoptera: Noctuidae) reared on three phenotypic regions of whorl leaves from a resistant and a susceptible maize hybrid. Florida Entomologist ,82 (2), 248-254.
De Vleesschauwer, D., Xu, J. & Höfte, M. (2014). Making sense of hormone-mediated defense networking: from rice to Arabidopsis.Frontiers in Plant Science , 5 , 611. https://doi.org/10.3389/fpls.2014.00611
Flint-Garcia, S.A., Thuillet, A.C., Yu, J.M., 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 (6), 1054-1064. https://doi.org/10.1111/j.1365-313X.2005.02591.x
Glaubitz, J.C., Casstevens, T.M., Lu, F., Harriman, J., Elshire, R.J., Sun, Q. & Buckler, E.S. (2014). TASSEL-GBS: a high capacity genotyping by sequencing analysis pipeline. PloS One9 (2), e90346. https://doi.org/10.1371/journal.pone.0090346
Goergen, G., Kumar, P.L., Sankung, S.B., Togola, A., & Tamò, M.. (2016). First report of outbreaks of the fall armyworm Spodoptera frugiperda (JE Smith) (Lepidoptera, Noctuidae), A new alien invasive pest in West and Central Africa. PLoS One , 11 (10), e0165632. https://doi.org/10.1371/journal.pone.0165632
Hoopes, G.M., Hamilton, J.P., Wood, J.C., Esteban, E., Pasha, A., Vaillancourt, B., Provart, N.J., & Buell, C.R. (2019). An updated gene atlas for maize reveals organ-specific and stress-induced genes.The Plant Journal , 97 (6), 1154-1167. https://doi.org/10.1111/tpj.14184
Li, H., Thrash, A., Tang, J.D., He, L., Yan, J., & Warburton, M.L. (2019). Leveraging GWAS data to identify metabolic pathways and networks involved in maize lipid biosynthesis. The Plant Journal ,98 (5), 853-863. https://doi.org/10.1111/tpj.14282
McMullen, M.D., Frey, M., & Degenhardt, J. (2009). Genetics and biochemistry of insect resistance in maize. In J.L. Bennetzen & S.C. Hake (Eds.), Handbook of maize: Its biology (pp. 271-289). Springer.
Mihm, J. A., Smith, M.E., and Deutsch, J.A. (1988). Development of open-pollinated varieties, non-conventional hybrids and inbred lines of tropical maize with resistance to fall armyworm, Spodoptera frugiperda ( Lepidoptera: Noctuidae), at CIMMYT. Florida Entomologist , 71 (3), 262-268.
Monaco, M.K., Sen, T.Z., Dharmawardhana, P.D., Ren, L., Schaeffer, M., Naithani, S., Amarasinghe, V., Thomason, J., Harper, L., Gardiner, J., Cannon, E.K.S., Lawrence, C.J., Ware, D., & Jaiswal, P. (2013). Maize metabolic network construction and transcriptome analysis. The Plant Genome , 6 (1), plantgenome2012.09.0025. https://doi.org/10.3835/plantgenome2012.09.0025
Overton, K., Maino, J.L., Day, R., Umina, P.A., Bett, B., Carnovale, D., Ekesi, S., Meagher, R., & Reynolds, O.L. (2021). Global crop impacts, yield losses and action thresholds for fall armyworm. (Spodoptera frugiperda): A review. Crop Protection , 145 , 105641 https://doi.org/10.1016/j.cropro.2021.105641
Pingault, L., Basu, S., Zogli, P., Williams, W.P., Palmer, N., Sarath, G., & Louis, J. (2021). Aboveground Herbivory Influences Belowground Defense Responses in Maize. Frontiers in Ecology and Evolution ,9 , 765940. https://doi.org/10.3389/fevo.2021.765940.
Scott, G.E., & Davis, F.M. (1981). Registration of Mp496 inbred of maize. Crop Science , 21 (2), 353. https://doi.org/10.2135/cropsci1981.0011183X002100020049x
Scott, G. E., Davis, F.M., and Williams, W.P. (1982). Registration of Mp701 and Mp702 germplasm lines of maize. Crop Science ,22 (6), 1270. https://doi.org/10.2135/cropsci1982.0011183X002200060070x
Swart, V., Crampton, B.G., Ridenour, J.B., Bluhm, B.H., Olivier, N.A., Meyer, J.J.M., & Berger, D.K. (2017). Complementation of CTB7 in the maize pathogen Cercospora zeina overcomes the lack of in vitro cercosporin production. Molecular Plant Microbe Interactions ,30 (9), 710-724. https://doi.org/10.1094/MPMI-03-17-0054-R
Tang, J.D., Perkins, A., Williams, W.P., and Warburton, M.L. (2015). Using genome-wide associations to identify metabolic pathways involved in maize aflatoxin accumulation resistance. BMC Genomics ,16 , 673. https://doi.org/10.1186/s12864-015-1874-9
Team, R.C. (2015). R: a language and environment for statistical computing [Online]. Vienna, Austria: R Foundation for Statistical Computing. Available: https://www.R-project.org.
Thrash, A., Tang, J.D., DeOrnellis, M., Peterson, D.G., & Warburton, M.L. (2020a). PAST: The Pathway Association Studies Tool to infer biological meaning from GWAS datasets. Plants 9 (1), 58. https://doi.org/10.3390/plants9010058
Thrash, A. & Warburton, M.L. (2020b). A Pathway Association Study Tool for GWAS analyses of metabolic pathway information . Journal of Visualized Experiments , 161 , e61268. https://doi.org/10.3791/61268-v
Turnbull, C., Lillemo, M., & Hvoslef-Eide, T.A. (2021). Global regulation of genetically modified crops amid the gene edited crop boom - A review. Frontiers in Plant Science12 , 630396. https://doi.org/10.3389/fpls.2021.630396
Warburton, M.L., Williams, W.P., Windham, G., Murray, S., Xu, W., Hawkins, L., & Franco, J. (2013). Phenotypic and genetic characterization of a maize association mapping panel developed for the identification of new sources of resistance to Aspergillus flavusand aflatoxin accumulation. Crop Science , 53 (6), 2374-2383. https://doi.org/10.2135/cropsci2012.10.0616
Warburton, M.L, Womack, E., Tang, J.D., Thrash, A., Smith, J.S., Xu, W., Murray, S.C., & Williams, W.P. (2017). Genome-wide association and metabolic pathway analysis of corn earworm resistance in maize.The Plant Genome , 11 (1), 170069. https://doi.org/10.3835/plantgenome2017.08.0069
Williams, W. P., & Davis, F.M. (1980). Registration of Mp703 germplasm line of maize. Crop Science, 20 (3), 418. https://doi.org/10.2135/cropsci1980.0011183X002000030052x
Williams, W.P., & Davis, F.M. (1982). Registration of Mp704 germplasm line of maize. Crop Science , 22 (6), 1269-1270. https://doi.org/10.2135/cropsci1982.0011183X002200060068x
Williams, W.P., & Davis, F.M. (1984). Registration of Mp705, Mp706, and Mp707 germplasm lines of maize. Crop Science , 24 (6), 1217. https://doi.org/10.2135/cropsci1984.0011183X002400060062x
Williams, W.P., Davis, F.M., & Windham, G.L. (1990). Registration of Mp708 germplasm line of maize. Crop Science , 30 (3), 757. https://doi.org/10.2135/cropsci1990.0011183X003000030082x
Williams, W.P., Sagers, J.B., Hanten, J.A., Davis, F.M., & Buckley, P.M. (1997). Transgenic corn evaluated for resistance to fall armyworm and southwestern corn borer. Crop Science , 37 (3), 957-962. https://doi.org/10.2135/cropsci1997.0011183X003700030042x
Williams, W.P., Davis, F.M., Buckley, P.M., Hedin, P.A., Baker, G.T., & Luthe, D.S. (1998). Factors associated with resistance to fall armyworm (Lepidoptera: Noctuidae) and southwestern corn borer (Lepidoptera: Crambidae) in corn at different vegetative stages. Journal of Economic Entomology , 91 (6): 1471-1480. https://doi.org/10.1093/jee/91.6.1471
Williams, W.P., & Davis, F.M. (2000). Registration of maize germplasms Mp713 and Mp714. Crop Science , 40 (2), 584. https://doi.org/10.2135/cropsci2000.0015rgp
Williams, W.P., & Davis, F.M. (2002). Registration of maize germplasm line Mp716. Crop Science , 42 (2), 671-672. https://doi.org/10.2135/cropsci2002.671a
Wiseman, B.R., Davis, F.M., & Campbell, J.E. 1980. Mechanical infestation device used in fall armyworm plant resistance program.Florida Entomologist , 63 (4), 425-432.
Wojdyło, A., Nowicka, P., Tkacz, K., & Turkiewicz, I.P. Fruit tree leaves as unconventional and valuable source of chlorophyll and carotenoid compounds determined by liquid chromatography-photodiode-quadrupole/time of flight-electrospray ionization-mass spectrometry (LC-PDA-qTof-ESI-MS), 2021, Food Chemistry, 349, 129156. https://doi.org/10.1016/j.foodchem.2021.129156
Womack, E.D., Williams, W.P., Smith, J.S., Warburton, M.L. & Bhattramakki, D. (2020). Mapping quantitative trait loci for resistance to fall armyworm (Lepidoptera: Noctuidae) leaf damage in maize inbred Mp705. Journal of Economic Entomology , 113 (2), 956-63. https://doi.org/10.1093/jee/toz357
Womack, E.D., Warburton, M.L., & Williams, W.P. (2018). Mapping of quantitative trait loci for resistance to fall armyworm and southwestern corn borer leaf-feeding damage in maize. Crop Science ,58 (2), 529-539. https://doi.org/10.2135/cropsci2017.03.0155
Yu, J., Pressoir, G., Briggs, W.H., Bi, I.V., Yamasaki, M., Doebley, J.F., McMullen, M.D., Gaut, B.S., Nielsen, D.M., Holland, J.B., Kresovich, S., & Buckler, E.S. (2006). A unified mixed-model method for association mapping that accounts for multiple levels of relatedness.Nature Genetics , 38 (2), 203-208. https://doi.org/10.1038/ng1702