Theoretical and Applied Genetics

, Volume 122, Issue 4, pp 771–782 | Cite as

QTL consistency and meta-analysis for grain yield components in three generations in maize

  • J. Z. Li
  • Z. W. Zhang
  • Y. L. Li
  • Q. L. Wang
  • Y. G. Zhou
Original Paper


Grain yield is the most important and complex trait in maize. In this study, a total of 258 F9 recombinant inbred lines (RIL), derived from a cross between dent corn inbred Dan232 and popcorn inbred N04, were evaluated for eight grain yield components under four environments. Quantitative trait loci (QTL) and their epistatic interactions were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL across three generations (RIL, F2:3 and BC2F2) derived from the same cross. In total, 103 QTL, 42 pairs of epistatic interactions and 16 meta-QTL (mQTL) were detected. Twelve out of 13 QTL with contributions (R 2) over 15% were consistently detected in 3–4 environments (or in combined analysis) and integrated in mQTL. Only q100GW-7-1 was detected in all four environments and in combined analysis. 100qGW-1-1 had the largest R 2 (19.3–24.6%) in three environments and in combined analysis. In contrast, 35 QTL for 6 grain yield components were detected in the BC2F2 and F2:3 generations, no common QTL across three generations were located in the same marker intervals. Only 100 grain weight (100GW) QTL on chromosome 5 were located in adjacent marker intervals. Four common QTL were detected across the RIL and F2:3 generations, and two between the RIL and BC2F2 generations. Each of five important mQTL (mQTL7-1, mQTL10-2, mQTL4-1, mQTL5-1 and mQTL1-3) included 7–12 QTL associated with 2–6 traits. In conclusion, we found evidence of strong influence of genetic structure and environment on QTL detection, high consistency of major QTL across environments and generations, and remarkable QTL co-location for grain yield components. Fine mapping for five major QTL (q100GW-1-1, q100GW-7-1, qGWP-4-1, qERN-4-1 and qKR-4-1) and construction of single chromosome segment lines for genetic regions of five mQTL merit further studies and could be put into use in marker-assisted breeding.


Quantitative Trait Locus Recombinant Inbred Line Yield Component Recombinant Inbred Line Population Major Quantitative Trait Locus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was funded by the Henan Industrial Development Project in High Technology, the Henan Science and Technology Research Program (92102110062).


  1. Arcade A, Labourdette A, Falque M, Mangin B, Chardon F, Charcosset A, Joets J (2004) BioMercator: integrating genetic maps and QTL towards discovery of candidate genes. Bioinformatics 20:2324–2326CrossRefPubMedGoogle Scholar
  2. Austin DF, Lee M (1996) Comparative mapping in F2:3 and F6:7 generations of quantitative trait loci for grain yield and yield components in maize. Theor Appl Genet 92:817–826CrossRefGoogle Scholar
  3. Austin DF, Lee M (1998) Detection of quantitative trait for grain yield and yield components in maize across generations in stress and nonstress environments. Crop Sci 38:1296–1308CrossRefGoogle Scholar
  4. Austin DF, Lee M, Veldboom LR, Hallauer AR (2000) Genetic mapping in maize with hybrid progeny across testers and generations: grain yield and grain moisture. Crop Sci 40:30–39CrossRefGoogle Scholar
  5. Blanc G, Charcosset A, Mangin B, Gallais A, Moreau L (2006) Connected populations for detecting quantitative trait loci and testing for epistasis: an application in maize. Theor Appl Genet 113:206–224CrossRefPubMedGoogle Scholar
  6. Chardon F, Virlon B, Moreau L, Falque M, Joets J, Decousset L, Murigneux A, Charcosset A (2004) Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome. Genetics 168:2169–2185CrossRefPubMedGoogle Scholar
  7. Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963–971PubMedGoogle Scholar
  8. Fan C, Xing Y, Mao H, Lu T, Han B, Xu C, Li X, Zhang Q (2006) GS3, a major QTL for grain length and weight and minor QTL for grain width and thickness in rice, encodes a putative transmembrane protein. Theor Appl Genet 112:1164–1171CrossRefPubMedGoogle Scholar
  9. Goffinet B, Gerber S (2000) Quantitative trait loci: a meta-analysis. Genetics 155:463–473PubMedGoogle Scholar
  10. Ho JC, McCouch SR, Smith ME (2002) Improvement of hybrid yield by advanced backcross yield analysis in elite maize. Theor Appl Genet 105:440–448CrossRefPubMedGoogle Scholar
  11. Kao CH, Zeng ZB, Robert DT (1999) Multiple interval mapping for quantitative trait loci. Genetics 521:203–1216Google Scholar
  12. Khowaja FS, Norton GJ, Courtois B, Price AH (2009) Improved resolution in the position of drought-related QTLs in a single mapping population of rice by meta-analysis. BMC Genomics 10:276CrossRefPubMedGoogle Scholar
  13. Knapp SJ, Stroup WW, Ross WM (1985) Exact confidence intervals for heritability on a progeny mean basis. Crop Sci 25:192–194CrossRefGoogle Scholar
  14. Lan JH, Li XH, Gao SR, Zhang BS, Zhang SH (2005) QTL analysis of yield components in maize under different environments. Acta Agro Sin 31(10):1253–1259Google Scholar
  15. Li ZK, Yu SB, Lafitte HR, Huang N, Courtois B, Hittalmani S, Vijayakumar CHM, Liu GF, Wang GC, Shashidhar HE, Zhuang JY, Zheng KL, Singh VP, Sidhu JS, Srivantaneeyakul S, Khush GS (2003) QTL × environment interactions in rice. I. Heading date and plant height. Theor Appl Genet 108:141–153CrossRefPubMedGoogle Scholar
  16. Li YL, Niu SZ, Dong YB, Cui DQ, Wang YZ, Liu YY, Wei MM (2007) Identification of trait-improving quantitative trait loci for grain yield components from a dent corn inbred line in an advanced backcross BC2F2 population and comparison with its F2:3 population in popcorn. Theor Appl Genet 115:129–140CrossRefPubMedGoogle Scholar
  17. Li YL, Dong YB, Niu SZ, Cui DQ, Wang YZ, Liu YY, Wei MG, Li XH (2008) Identification of agronomically favorable quantitative trait loci alleles from a dent corn inbred Dan232 using advanced backcross QTL analysis and comparison with the F2:3 population in popcorn. Mol Breed 21:1–14CrossRefGoogle Scholar
  18. Li YL, Li XH, Li JZ, Fu JF, Wang YZ, Wei MG (2009) Dent corn genetic background influences QTL detection for grain yield and yield components in high-oil maize. Euphytica 169:273–284CrossRefGoogle Scholar
  19. Liu YY, Dong YB, Niu SZ, Cui DQ, Wang YZ, Wei MG, Li XH, Fu JF, Zhang ZW, Chen HQ, Li YL (2008) QTL identification of kernel composition traits with popcorn using both F2:3 and BC2F2 populations developed from the same cross. J Cereal Sci 48:625–631CrossRefGoogle Scholar
  20. Ma XQ, 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
  21. Mihaljevic R, Utz HF, Melchinger AE (2004) Congruency of quantitative trait loci detected for agronomic traits in testcrosses of five populations of European maize. Crop Sci 44:114–124CrossRefGoogle Scholar
  22. Moreno-Gonzalez J (1993) Efficiency on generations for estimating marker-associated QTL effects by multiple regression. Genetics 135:223–231PubMedGoogle Scholar
  23. Shi JQ, Li RY, Qiu D, Jiang CC, Long Y, Morgan C, Bancroft I, Zhao JY, Meng JL (2009) Unraveling the complex trait of crop yield with quantitative trait loci mapping in Brassica napus. Genetics 182:851–861CrossRefPubMedGoogle Scholar
  24. Song XJ, Huang W, Shi M, Zhu MZ, Lin HX (2007) A QTL for rice grain width and weight encodes a previously unknown RING-type E3 ubiquitin ligase. Nat Genet 39:623–630CrossRefPubMedGoogle Scholar
  25. Stuber CW, Edwards MD, Wendel JF (1987) Molecular marker-facilitated investigations of in maize. II. Factors influencing yield and its component traits. Crop Sci 27:639–648CrossRefGoogle Scholar
  26. Stuber CW, Lincoln SE, Wolff DW, Helentjaris T, Lander ES (1992) Identification of genetic factors contributing to heterosis in a hybrid from two elite maize inbred lines using molecular markers. Genetics 132:823–839PubMedGoogle Scholar
  27. Tanksley SD, Nelson JC (1996) Advanced backcross QTL analysis: a method for the simultaneous discovery and transfer of valuable QTLs from unadapted germplasm into elite breeding lines. Theor Appl Genet 92:191–203CrossRefGoogle Scholar
  28. Veldboom L, Lee M (1994) Molecular-marker-facilitated studies of morphological traits in maize. II: Determination of QTLs for grain yield and yield components. Theor Appl Genet 89:451–458CrossRefGoogle Scholar
  29. Wang S, Basten CJ, Zeng ZB (2006) Windows QTL cartographer 2.5. Department of statistics, North Carolina State University, Ra-leigh, NC.
  30. Wang BT, Wu JY, Ding JQ, Xi ZY (2009) Map integration of QTLs for grain yield and its related traits in maize. Acta Agro Sin 35:1836–1843CrossRefGoogle Scholar
  31. Xie X, Jin F, Song MH, Suh JP, Hwang HG, Kim YG, McCouch SR, Ahn SN (2008) Fine mapping of a yield-enhancing QTL cluster associated with transgressive variation in an Oryza sativa × O. rufipogon cross. Theor Appl Genet 116:613–622CrossRefPubMedGoogle Scholar
  32. Xue W, Xing Y, Weng X, Zhao Y, Tang W, Wang L, Zhou H, Yu S, Xu C, Li X, Zhang Q (2008) Natural variation in Ghd7 is an important regulator of heading date and yield potential in rice. Nat Genet 40:761–767CrossRefPubMedGoogle Scholar
  33. Yan JB, Tang H, Huang YQ, Zheng YL, Li JS (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
  34. Zeng ZB (1993) Theoretical basis of separation of multiple linked gene effects on mapping quantitative trait loci. Proc Nat Acad Sci 90:10972–10976CrossRefPubMedGoogle Scholar
  35. Zeng ZB (1994) Precision mapping of quantitative trait loci. Genetics 136:1457–1468PubMedGoogle Scholar
  36. Zhang ZW (2009) Construction of normal corn × popcorn RIL population and analysis of QTL for main traits. MS D Thesis. Henan Agricultural University, Zhengzhou, Henan, ChinaGoogle Scholar
  37. Ziegler KE, Ashman B (1994) Popcorn. In: Hallauer AR (ed) Specialty corns. CRC Press, New York, pp 189–223Google Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • J. Z. Li
    • 1
  • Z. W. Zhang
    • 1
  • Y. L. Li
    • 1
  • Q. L. Wang
    • 1
  • Y. G. Zhou
    • 1
  1. 1.College of Agriculture, Henan Agricultural UniversityZhengzhouChina

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