QTL Analysis of Husk Coverage on Maize (Zea mays) Ear
ZHU Qiu-Li2, ZHANG Shu-Yu1, ZHANG Hui-Min1, SONG Xu-Dong1, ZHANG Zhen-Liang1, LU Hu-Hua1, CHEN Guo-Qing1,3, HAO De-Rong1, MAO Yu-Xiang1, SHI Ming-Liang1, XUE Lin1,3, ZHOU Guang-Fei1,*
1 Jiangsu Yanjiang Institute of Agricultural Science, Nantong 226012, China; 2 Nantong Crop Cultivation Technique Direction Station, Nantong 226007, China; 3 Jiangsu Collaborative Innovation Centre for Modern Crop Production, Nanjing 210095, China
Abstract：Maize (Zea mays) husk coverage is associated with the resistance to Aspergillus and Gibberella ear rot, also affects the mechanical harvesting of maize grain. Thus, the identification of genetic loci for husk coverage will provide available targets for maize molecular breeding. In this study, a set of 204 recombinant inbred lines developed from the T877×DH4866, was phenotypically evaluated under 5 field environments, and was genotyped using Axiom® Maize56K SNP Array. A total of 9 QTL for husk coverage were detected by individual environmental QTL mapping, of which 8 QTLs were putatively novel loci, the phenotypic variance explained by single QTL ranged from 4.70% to 17.00%. In addition, 26 additive QTL-by-environment loci were detected by joint environmental QTL analysis. The phenotypic variance explained by single additive QTL ranged from 0.73% to 4.77%, and the contributions of interaction between each additive QTL and environment ranged from 0.10% to 4.55%. qHC4.09, a stable QTL for husk coverage, was colocalized with the genomic region for maize resistance to Aspergillus and Gibberella ear rot, suggesting that this locus might be a pleiotropic QTL for maize husk coverage and resistance to ear rot. These results could provide theoretical basis for elucidating the genetic basis of husk coverage and available marker for maize molecular breeding.
[1] 王克如, 李少昆. 2017. 玉米籽粒脱水速率影响因素分析[J]. 中国农业科学, 50(11): 2027-2035. (Wang K R, Li S K.2017. Analysis of influencing factors on kernel dehydration rate of maize hybrids[J]. Scienta Agricultura Sinica, 50(11): 2027-2035.) [2] Abadassi J.2015. Maize agronomic traits needed in tropical zone[J]. International Journal of Science, Environment and Technology, 4(2): 371-392. [3] Butrón A M, Li R, Guo B, et al.2001. Molecular markers to increase corn earworm resistance in a maize population[J]. Maydica, 46: 117-124. [4] Jansen R C, Van J W, Stam P, et al.1995. Genotype-by-environment interaction in genetic mapping of multiple quantitative trait loci[J]. Theoretical Applied Genetics, 91: 33-37. [5] Kebede A Z, Woldemariam T, Reid L M, et al.2016. Quantitative trait loci mapping for Gibberella ear rot resistance and associated agronomic traits using genotyping-by-sequencing in maize[J]. Theoretical and Applied Genetics, 129(1): 17-29. [6] Knapp S J, Stroup W W, Ross W M.1985. Exact confidence intervals for heritability on a progeny mean basis1[J]. Crop Science, 25: 192-194. [7] Li P, Zhang Y, Yin S, et al.2018. QTL-by-environment interaction in the response of maize root and shoot traits to different water regimes[J]. Frontiers in Plant Science, 9: 229. [8] Li S S, Wang J K, Zhang L Y.2015. Inclusive composite interval mapping of QTL by environment interactions in biparental populations[J]. PLOS ONE, 10(7): e0132414. [9] Li Z K, Yu S B, Lafitte H R.2003. QTL×environment interaction in rice. I. heading date and plant height[J]. Theoretical and Applied Genetics, 108(1): 141-153. [10] Meng L, Li H, Zhang L, et al.2015. QTL IciMapping: Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations[J]. The Crop Journal, 3(3): 269-283. [11] Mideros S X, Warburton M L, Jamann T M, et al.2014. Quantitative trait loci influencing mycotoxin contamination of maize: Analysis by linkage mapping, characterization of near-isogenic lines, and meta‐analysis[J]. Crop Science, 54(1): 127-142. [12] Sun H, Zhai L H, Teng F, et al.2021. qRgls1.06, a major QTL conferring resistance to gray leaf spot disease in maize[J]. The Crop Journal, 9: 342-350. [13] Wang P, Kelly S, Fouracre J P, et al.2013. Genome-wide transcript analysis of early maize leaf development reveals gene cohorts associated with the differentiation of C4 kranz anatomy[J]. Plant Journal, 75(4): 656-670. [14] Warfield C Y, Davis R M.1996. Importance of the husk covering on the susceptibility of corn hybrids to Fusarium ear rot[J]. Plant Disease, 80(2): 208-210. [15] Widstrom N, Butron A, Guo B, et al.2003. Control of preharvest aflatoxin contamination in maize by pyramiding QTL involved in resistance to ear-feeding insects and invasion by Aspergillus spp[J]. European Journal of Agronomy, 19(4): 563-572. [16] Xu Y, Crouch J H.2008. Marker‐assisted selection in plant breeding: From publications to practice[J]. Crop Science, 48(2): 391-407. [17] Zeng Z B.1994. Precision mapping of quantitative trait loci[J]. Genetics, 136(4): 1457-1468. [18] Zhang J, Zhang F, Tian L, et al.2022. Molecular mapping of quantitative trait loci for 3 husk traits using genotyping by sequencing in maize (Zea mays L.)[J]. G3 (Bethesda), 12(10): jkac198. [19] Zhou G, Mao Y, Xue L, et al.2020. Genetic dissection of husk number and length across multiple environments and fine-mapping of a major-effect QTL for husk number in maize (Zea mays L.)[J]. The Crop Journal, 8(6): 1071-1080. [20] Zhou G, Li S, Ma L, et al.2021. Mapping and validation of a stable quantitative trait locus conferring maize resistance to Gibberella ear rot[J]. Plant Disease, 105(7): 1984-1991.
