, 215:148 | Cite as

QTL analysis for plant architecture-related traits in maize under two different plant density conditions

  • Qiang Yi
  • Xianbin Hou
  • Yinghong Liu
  • Xiangge Zhang
  • Junjie Zhang
  • Hanmei Liu
  • Yufeng Hu
  • Guowu Yu
  • Yangping Li
  • Yubi HuangEmail author


The erectophile plant architecture in maize is responsible for high plant density tolerance, yet the genetic basis for this relationship remains elusive, especially for how canopy architecture and plant height related traits at different positions respond to plant density. In this study, nine canopy traits and six plant height (PH) traits were evaluated across four environments under low plant density (57,000 plants/ha, LD) and high plant density (114,000 plants/ha, HD), using a set of 301 recombinant inbred lines originating from two foundation parents in China, the inbred lines YE478 and 08-641. In total, 176 quantitative trait loci (QTLs) for plant architecture related traits (94 only in LD, 44 only in HD and 38 under both densities) and 36 QTL clusters were detected via combined analysis. We identified 21 sharing QTL regions associated with plant height, leaf width and leaf angle at different positions. These results suggest that plant architecture-related traits were greatly influenced by density-specific and environment-specific alleles, and epistasis, QTL × environment interaction and QTL pleiotropy also play essential roles for plant architecture via complex interactions. Though PH-related traits, leaf widths and leaf angles at different positions could be partially affected by several common QTLs, there are still different genetic mechanisms of plant architecture response to plant density. Furthermore, elite line YE478 provided most of the favorable plant architecture alleles for high-density tolerance. Five QTL clusters containing six major QTLs, were useful for further studies of plant architecture and will provide helpful information for ideal plant type, high-density tolerance and marker-assisted selection.


Maize Plant architecture RIL QTL mapping Density 



Research supported by the Project of National Major Basic Dairy Research “973” Plan (#2014CB138202 and #2011CB100106) and Science and Technology Plan Projects in Sichuan Province (#2016JY0065). We thank Dr. Pedro Revilla for valuable suggestions and careful corrections, and also thank the help of Dr. Zhengqiao Liao and Dr. Yulin Jiang in the data analysis.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Supplementary material

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Supplementary material 1 (DOCX 1227 kb)
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Supplementary material 2 (DOCX 50 kb)


  1. Becraft P, Freeling M (1994) Genetic analysis of Rough sheath-1 developmental mutants of maize. Genetics 136:295–311PubMedPubMedCentralGoogle Scholar
  2. Bensen RJ, Johal GS, Crane VC, Tossberg JT, Schnable PS, Meeley RB, Briggs RB (1995) Cloning and characterization of the maize An1 gene. Plant Cell 7:75–84PubMedPubMedCentralGoogle Scholar
  3. Bomblies K, Wang R, Ambrose BA, Schmidt RJ, Meeley RB, Doebley JM (2003) Duplicate FLORICAULA/LEAFY homologs zfl1 and zfl2 control inflorescence architecture and flower patterning in maize. Development 130:2385–2395CrossRefGoogle Scholar
  4. Candela H, Johnston R, Gerhold A, Foster T, Hake S (2008) The milkweed pod1 gene encodes a KANADI protein that is required for abaxial-adaxial patterning in maize. Plant Cell 20(8):2073–2087CrossRefGoogle Scholar
  5. Chen DH, Ronald PC (1999) A rapid DNA minipreparation method suitable for AFLP and other PCR applications. Plant Mol Biol Rep 17:53–57CrossRefGoogle Scholar
  6. Chuck G, Muszynski M, Kellogg E, Hake S, Schmidt RJ (2002) The control of spikelet meristem identity by the branched silkless1 gene in maize. Science 298(5596):1238–1241CrossRefGoogle Scholar
  7. Ci X, Li M, Liang X, Xie Z, Zhang D, Li X, Lu Z, Ru G, Bai L, Xie C, Hao Z, Zhang S (2011) Genetic contribution to advanced yield for maize hybrids released from 1970 to 2000 in China. Crop Sci 51:13–20CrossRefGoogle Scholar
  8. Ci X, Li M, Xu J, Lu Z, Bai P, Ru G, Liang X, Zhang D, Li X, Bai L, Xie C, Hao Z, Zhang S, Dong S (2012) Trends of grain yield and plant traits in Chinese maize cultivars from the 1950s to the 2000s. Euphytica 185:395CrossRefGoogle Scholar
  9. Doerge RW, Churchill GA (1996) Permutation tests for multiple loci affecting a quantitative character. Genetics 142:285–294PubMedPubMedCentralGoogle Scholar
  10. Duvick DN (2004) Long-term selection in a commercial hybrid maize breeding program. In: Janick J (ed) Plant breeding reviews 24, part 2. Wiley, Hoboken, pp 109–151Google Scholar
  11. Duvick DN (2005) The contribution of breeding to yield advances in maize. Adv Agron 86:83–145CrossRefGoogle Scholar
  12. Eastin JA (1969) Leaf position and leaf function in corn. Carbon-14 1abeled photosynthate distribution in corn in relation to leaf position and leaf function. In: Paper presented at: proceedings of the 24th annual corn and sorghum research conference (ASTA). Washington, TX, pp 81–89Google Scholar
  13. Edmeades G, Banziger M, Campos H, Schussler J (2006) Improved tolerance to abiotic stresses in staple crops: arandom or planned process? In: Lamkey KR, Lee M (eds) Plant breeding: the Arnel R. Hallauer international symposium. Wiley, Ames, pp 293–309Google Scholar
  14. Fan JB, Gunderson KL, Bibikova M, Yeakley JM, Chen J, Wickham Garcia E, Lebruska LL, Laurent M, Shen R, Barker D (2006) Illumina universal bead arrays. Methods Enzymol 410:57–73CrossRefGoogle Scholar
  15. Foster TM, Timmermans MCP (2009) Axial patterning of the maize leaf. In: Bennetzen JL, Hake SC (eds) Handbook of maize: its biology. Springer, New York, pp 161–178CrossRefGoogle Scholar
  16. Gao YM, Zhu J (2007) Mapping QTLs with digenic epistasis under multiple environments and predicting heterosis based on QTL effects. Theor Appl Genet 115:325–333CrossRefGoogle Scholar
  17. Gardiner J, Coe EH, Melia-Hancock S, Hoisington DA, Chao S (1993) Development of a core RFLP map in maize using an imortalized-F2 population. Genetics 134:917–930PubMedPubMedCentralGoogle Scholar
  18. Gong F, Wu X, Zhang H, Chen Y, Wang W (2015) Making better maize plants for sustainable grain production in a changing climate. Front Plant Sci 6:835PubMedPubMedCentralGoogle Scholar
  19. Gonzalo M, Vyn TJ, Holland JB, McIntyre LM (2006) Mapping density response in maize: a direct approach for testing genotype and treatment interactions. Genetics 173:331–348CrossRefGoogle Scholar
  20. Gonzalo M, Holland JB, Vyn TJ, McIntyre LM (2010) Direct mapping of density response in a population of B73 × Mo17 recombinant inbred lines of maize (Zea Mays L.). Heredity 104:583–599CrossRefGoogle Scholar
  21. Guo JJ, Chen ZL, Liu ZP, Wang BB, Song WB, Li W, Chen J, Dai JR, Lai JS (2011) Identification of genetic factors affecting plant density response through QTL mapping of yield component traits in maize (Zea mays L.). Euphytica 182:409CrossRefGoogle Scholar
  22. Hallauer AR, Mirando FJB (1988) Quantitative genetics in maize breeding, 2nd edn. Iowa State University Press, Iowa State University, AmesGoogle Scholar
  23. Hartwig T, Chuck GS, Fujioka S, Klempien A, Weizbauer R, Potluri DP, Choe S, Johal GS, Schulz B (2011) Brassinosteroid control of sex determination in maize. Proc Natl Acad Sci 108(49):19814–19819CrossRefGoogle Scholar
  24. Hou X, Liu Y, Xiao Q, Wei B, Zhang X, Gu Y, Wang Y, Chen J, Hu Y, Liu H, Zhang J, Huang Y (2015) Genetic analysis for canopy architecture in an F2:3 population derived from two-type foundation parents across multi-environments. Euphytica 205:421–440CrossRefGoogle Scholar
  25. Jackson D, Veit B, Hake S (1994) Expression of maize KNOTTED1 related homeobox genes in the shoot apical meristem predicts patterns of morphogenesis in the vegetative shoot. Development 120:405–413Google Scholar
  26. Jannink JL (2007) Identifying quantitative trait locus by genetic background interactions in association studies. Genetics 176:553–561CrossRefGoogle Scholar
  27. Jiao Y, Zhao H, Ren L, Song W, Zeng B, Guo J, Wang B, Liu Z, Chen J, Li W, Zhang M, Xie S, Lai J (2012) Genome-wide genetic changes during modern breeding of maize. Nat Genet 44:812–815CrossRefGoogle Scholar
  28. Knapp SJ, Stroup WW, Ross WM (1985) Exact confidence intervals for heritability on a progeny mean basis. Crop Sci 25:192–194CrossRefGoogle Scholar
  29. Kosambi DD (1943) The estimation of map distances from recombination values. Ann Eugen 12:172–175CrossRefGoogle Scholar
  30. Ku L, Wei X, Zhang S, Zhang J, Guo S, Chen Y (2011) Cloning and characterization of a putative TAC1 ortholog associated with leaf angle in maize (Zea mays L.). PLoS ONE 6(6):e20621CrossRefGoogle Scholar
  31. Ku L, Cao L, Wei X, Su H, Tian Z, Guo S, Zhang L, Ren Z, Wang X, Zhu Y, Li G, Wang Z, Chen Y (2015a) Genetic dissection of internode length above the uppermost ear in four RIL populations of maize (Zea mays L.). G3-Genes Genom Genet 5(2):281–289Google Scholar
  32. Ku L, Zhang L, Tian Z, Guo S, Su H, Ren Z, Wang Z, Li G, Wang X, Zhu Y, Zhou J, Chen Y (2015b) Dissection of the genetic architecture underlying the plant density response by mapping plant height-related traits in maize (Zea mays L.). Mol Genet Genom 290:1223–1233CrossRefGoogle Scholar
  33. Ku L, Ren Z, Chen X, Shi Y, Qi J, Su H, Wang Z, Li G, Wang X, Zhu Y, Zhou J, Zhang X, Chen Y (2016) Genetic analysis of leaf morphology underlying the plant density response by QTL mapping in maize (Zea mays L.). Mol Breed 36:63CrossRefGoogle Scholar
  34. Lai J, Li R, Xu X, Jin W, Xu M, Zhao H, Xiang Z, Song W, Ying K, Zhang M, Jiao Y, Ni P, Zhang J, Li D, Guo X, Ye K, Jian M, Wang B, Zheng H, Liang H, Zhang X, Wang S, Chen S, Li J, Fu Y, Springer NM, Yang H, Wang J, Dai J, Schnable PS, Wang J (2010) Genome-wide patterns of genetic variation among elite maize inbred lines. Nat Genet 42:1027–1030CrossRefGoogle Scholar
  35. Li Y, Wang TY (2010) Germplasm base of maize breeding in China and formation of foundation parents. J Maize Sci 18:1–8Google Scholar
  36. Li Z, Pinson SRM, Park WD, Paterson AH, Stansel JW (1997) Epistasis for three grain yield components in rice (Oryza sativa L.). Genetics 145:453–465PubMedPubMedCentralGoogle Scholar
  37. Liu W, Tollenaar M (2009) Response of yield heterosis to increasing plant density in maize. Crop Sci 49:1807–1816CrossRefGoogle Scholar
  38. Liu Y, Hou X, Xiao Q, Yi Q, Bian S, Hu Y, Liu H, Zhang J, Hao X, Cheng W, Li Y, Huang Y (2016) Genetic analysis in maize foundation parents with mapping population and testcross population: Ye478 carried more favorable alleles and using QTL information could improve foundation parents. Front Plant Sci 7:1417PubMedPubMedCentralGoogle Scholar
  39. Liu R, Meng Q, Zheng F, Kong L, Yuan J, Lu¨bberstedt T (2017) Genetic mapping of QTL for maize leaf width combining RIL and IF2 populations. PLoS ONE 12(12):e0189441CrossRefGoogle Scholar
  40. Ma X, Tang JH, Teng WT, Yan JB, Meng YJ, Li JS (2007) Epistatic interaction is an important genetic basis of grain yield and its components in maize. Mol Breed 20:41–51CrossRefGoogle Scholar
  41. Martre P, Quilot-Turion B, Luquet D, Memmah MMOS, Chenu K, Debaeke P (2015) Model-assisted phenotyping and ideotype design. In: Sadras V, Calderini D (eds) Crop physiology. Academic Press, London, pp 349–373CrossRefGoogle Scholar
  42. Mathias L (2012) MapDisto: fast and efficient computation of genetic linkage maps. Mol Breed 30:1231–1235CrossRefGoogle Scholar
  43. Mihaljevic R, Utz HF, Melchinger AE (2005) No evidence for epistasis in hybrid and per se performance of elite European flint maize inbreds from generation means and QTL analyses. Crop Sci 45:2605–2613CrossRefGoogle Scholar
  44. Mock JJ, Pearce RB (1975) An ideotype of maize. Euphytica 24(3):613–623CrossRefGoogle Scholar
  45. Moreno MA, Harper LC, Krueger RW, Dellaporta SL, Freeling M (1997) Liguleless1 encodes a nuclear-localized protein required for induction of ligules and auricles during maize leaf organogenesis. Gene Dev 11:616–628CrossRefGoogle Scholar
  46. Multani DS, Briggs SP, Chamberlin MA, Blakeslee JJ, Murphy AS, Johal GS (2003) Loss of an MDR transporter in compact stalks of maize br2 and sorghum dw3 mutants. Science 302:81–84CrossRefGoogle Scholar
  47. Nardmann J, Ji J, Werr W, Scanlon MJ (2004) The maize duplicate genes narrow sheath1 and narrow sheath2 encode a conserved homeobox gene function in a lateral domain of shoot apical meristems. Development 131:2827–2839CrossRefGoogle Scholar
  48. Pan Q, Xu Y, Li K, Peng Y, Zhan W, Li W, Li L, Yan J (2017) The genetic basis of plant architecture in 10 maize recombinant inbred line populations. Plant Physiol 175(2):858–873CrossRefGoogle Scholar
  49. Peng J, Richards DE, Hartley NM, Murphy GP, Devos KM, Flintham JE, Beales J, Fish LJ, Worland AJ, Pelica F, Sudhakar D, Christou P, Snape JW, Gale MD, Harberd NP (1999) Green revolution genes encode mutant gibberellin response modulators. Nature 400:256–261CrossRefGoogle Scholar
  50. Peng B, Li YX, Wang Y, Liu C, Liu ZZ, Tan WW, Zhang Y, Wang D, Shi YS, Sun BC, Song YC, Wang TY, Li Y (2011) QTL analysis for yield components and kernel-related traits in maize across multi-environments. Theor Appl Genet 122:1305–1320CrossRefGoogle Scholar
  51. Pepper GE, Pearce RB, Mock JJ (1977) Leaf orientation and yield of maize. Crop Sci 17:883–886CrossRefGoogle Scholar
  52. Qin X, Feng F, Li Y, Xu S, Siddique KHM, Liao Y (2016) Maize yield improvements in China: past trends and future directions. Plant Breed 135(2):166–176CrossRefGoogle Scholar
  53. Rice WR (1989) Analyzing tables of statistical tests. Evolution 43:223–225CrossRefGoogle Scholar
  54. Shi Y, Wang X, Guo S, Ren Z, Ku L, Zhu Y, Li G, Qi J, Zhang X, Ren Z, Chen Y (2017) Detection of epistatic and environmental interaction QTLs for leaf orientation-related traits in maize. Plant Breed 136:33–40CrossRefGoogle Scholar
  55. Sinclair T, Sheehy J (1999) Erect leaves and photosynthesis in rice. Science 283:2CrossRefGoogle Scholar
  56. Stewart DW, Costa C, Dwyer LM, Smith DL, Hamilton RI, Ma BL (2003) Canopy sructure, light interception, and photosynthesis in maize. Agron J 95(6):1465–1474CrossRefGoogle Scholar
  57. Tang J, Teng W, Yan Y, Ma X, Meng Y, Dai J, Lai J (2007) Genetic dissection of plant height by molecular markers using a population of recombinant inbred lines in maize. Euphytica 155:117–124CrossRefGoogle Scholar
  58. Teng F, Zhai L, Liu R, Bai W, Wang L, Huo D, Tao Y, Zheng Y, Zhang Z (2013) ZmGA3ox2, a candidate gene for a major QTL, qPH3.1, for plant height in maize. Plant J 73:405–416CrossRefGoogle Scholar
  59. Tian F, Bradbury PJ, Brown PJ, Hung H, Sun Q, Flint-Garcia S, Rocheford TR, McMullen MD, Holland JB, Buckler ES (2011) Genome-wide association study of leaf architecture in the maize nested association mapping population. Nat Genet 43:159–162CrossRefGoogle Scholar
  60. Troyer A (1996) Breeding widely adapted, popular maize hybrids. Euphytica 92:163–174CrossRefGoogle Scholar
  61. Tuberosa R, Salvi S (2009) QTL for agronomic traits in maize production. In: Bennetzen JL, Hake SC (eds) Handbook of maize: its biology. Springer, New York, pp 501–542CrossRefGoogle Scholar
  62. Van Roekel RJ, Coulter JA (2011) Agronomic responses of corn hybrids to row width and plant density. Agron J 104(3):612–620CrossRefGoogle Scholar
  63. Vargas M, Eeuwijk FA, Crossa J, Ribaut JM (2006) Mapping QTLs and QTL × environment interaction for CIMMYT maize drought stress program using factorial regression and partial least squares methods. Theor Appl Genet 112:1009–1023CrossRefGoogle Scholar
  64. Vollbrecht E, Veit B, Sinha N, Hake S (1991) The developmental gene Knotted-1 is a member of a maize homeobox gene family. Nature 350:241–243CrossRefGoogle Scholar
  65. Vollbrecht E, Springer PS, Goh L, Buckler ES, Martienssen R (2005) Architecture of floral branch systems in maize and related grasses. Nature 436:1119–1126CrossRefGoogle Scholar
  66. Voorrips RE (2002) MapChart: software for the graphical presentation of linkage maps and QTLs. J Hered 93:77–78CrossRefGoogle Scholar
  67. Walsh J, Waters CA, Freeling M (1998) The maize gene liguleless2 encodes a basic-leucine zipper protein involved in the establishment of the blade-sheath boundary. Genes Dev 12:208–218CrossRefGoogle Scholar
  68. Wang D, Zhu J, Li Z, Paterson A (1999) Mapping QTLs with epistatic effects and QTL × environment interactions by mixed linear model approaches. Theor Appl Genet 99:1255–1264CrossRefGoogle Scholar
  69. Wang H, Liang Q, Li K, Hu X, Wu Y, Wang H, Liu Z, Huang C (2017) QTL analysis of ear leaf traits in maize (Zea mays L.) under different planting densities. Crop J 5(5):387–395CrossRefGoogle Scholar
  70. Weng J, Xie C, Hao Z, Wang J, Liu C, Li M, Zhang D, Bai L, Zhang S, Li X (2011) Genome-wide association study identifies candidate genes that affect plant height in Chinese elite maize (Zea mays L.) inbred lines. PLoS ONE 6:e29229CrossRefGoogle Scholar
  71. Winkler RG, Helentjaris T (1995) The maize Dwarf3 encodes a cytochrome P450-mediated step in gibberellin biosynthesis. Plant Cell 7:1307–1317PubMedPubMedCentralGoogle Scholar
  72. Wu X, Li Y, Shi Y, Song Y, Wang T, Huang Y, Li Y (2014) Fine genetic characterization of elite maize germplasm using high-throughput SNP genotyping. Theor Appl Genet 127:621–631CrossRefGoogle Scholar
  73. Wu X, Li Y, Fu J, Li X, Li C, Zhang D, Shi Y, Song Y, Li Y, Wang T (2016) Exploring identity-by-descent segments and putative functions using different foundation parents in maize. PLoS ONE 11(12):e0168374CrossRefGoogle Scholar
  74. Xing A, Gao Y, Ye L, Zhang W, Cai L, Ching A, Llaca V, Johnson B, Liu L, Yang X, Kang D, Yan J, Li J (2015) A rare SNP mutation in Brachytic2 moderately reduces plant height and increases yield potential in maize. J Exp Bot 66(13):3791–3802CrossRefGoogle Scholar
  75. Yan J, Tang H, Huang Y, Zheng Y, Li J (2006) Quantitative trait loci mapping and epistatic analysis for grain yield and yield components using molecular markers with an elite maize hybrid. Euphytica 149:121–131CrossRefGoogle Scholar
  76. Yang J, Zhu J, Williams RW (2007) Mapping the genetic architecture of complex traits in experimental populations. Bioinformatics 23:1527–1536CrossRefGoogle Scholar
  77. Yang J, Hu C, Hu H, Yu R, Xia Z, Ye X, Zhu J (2008) QTLNetwork: mapping and visualizing genetic architecture of complex traits in experimental populations. Bioinformatics 24:721–723CrossRefGoogle Scholar
  78. Yang C, Tang D, Qu J, Zhang L, Zhang L, Chen Z, Liu J (2016) Genetic mapping of QTL for the sizes of eight consecutive leaves below the tassel in maize (Zea mays L.). Theor Appl Genet 129(11):2191–2209CrossRefGoogle Scholar
  79. Yi Q, Liu YH, Zhang XG, Hou XB, Zhang JJ, Liu HM, Hu YF, Yu GW, Huang YB (2018) Comparative mapping of quantitative trait loci for tassel-related traits of maize in F2:3 and RIL populations. J Genet 97:253CrossRefGoogle Scholar
  80. Yu S, Li J, Xu C, Tan Y, Gao Y, Li X, Zhang Q, Maroof MAS (1997) Importance of epistasis as the genetic basis of heterosis in an elite rice hybrid. Proc Natl Acad Sci 94:9226–9231CrossRefGoogle Scholar
  81. Zhang J, Ku L, Han Z, Guo S, Liu H, Zhang Z, Cao L, Cui X, Chen Y (2014) The ZmCLA4 gene in the qLA4-1 QTL controls leaf angle in maize (Zea mays L.). J Exp Bot 65(17):5063–5076CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Qiang Yi
    • 1
  • Xianbin Hou
    • 2
  • Yinghong Liu
    • 3
  • Xiangge Zhang
    • 1
  • Junjie Zhang
    • 4
  • Hanmei Liu
    • 4
  • Yufeng Hu
    • 1
  • Guowu Yu
    • 1
  • Yangping Li
    • 1
  • Yubi Huang
    • 1
    Email author
  1. 1.State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China and Agronomy CollegeSichuan Agricultural UniversityChengduChina
  2. 2.College of Agriculture and Food EngineeringBaise UniversityBaiseChina
  3. 3.Maize Research InstituteSichuan Agricultural UniversityChengduChina
  4. 4.Life Science CollegeSichuan Agricultural UniversityYa’anChina

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