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Theoretical and Applied Genetics

, Volume 115, Issue 1, pp 129–140 | Cite as

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

  • Y. L. Li
  • S. Z. Niu
  • Y. B. Dong
  • D. Q. Cui
  • Y. Z. Wang
  • Y. Y. Liu
  • M. G. Wei
Original Paper

Abstract

Normal maize germplasm could be used to improve the grain yield of popcorn inbreds. Our first objective was to locate genetic factors associated with trait variation and make first assessment on the efficiency of advanced backcross quantitative trait locus (AB-QTL) analysis for the identification and transfer of favorable QTL alleles for grain yield components from the dent corn inbred. A second objective was to compare the detection of QTL in the BC2F2 population with results using F2:3 lines of the same parents. Two hundred and twenty selected BC2F2 families developed from a cross between Dan232 and an elite popcorn inbred N04 were evaluated for six grain yield components under two environments, and genotyped by means of 170 SSR markers. Using composite interval mapping (CIM), a total of 19 significant QTL were detected. Eighteen QTL had favorable alleles contributed by the dent corn parent Dan232. Sixteen of these favorable QTL alleles were not in the same or near marker intervals with QTL for popping characteristics. Six QTL were also detected in the F2:3 population. Improved N04 could be developed from 210 and 208 families with higher grain weight per plant and/or 100-grain weight, respectively, and 35 families with the same or higher popping expansion volume than N04. In addition, near isogenic lines containing detected QTL (QTL-NILs) for grain weight per plant and/or 100-grain weight could be obtained from 12 families. Our study demonstrated that the AB-QTL method can be applied to identify and manipulate favorable QTL alleles from normal corn inbreds and combine QTL detection and popcorn breeding efficiently.

Keywords

Yield Component BC2F2 Population Genotypic Correlation Positive Allele Normal Maize 
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.

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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Y. L. Li
    • 1
  • S. Z. Niu
    • 1
  • Y. B. Dong
    • 1
  • D. Q. Cui
    • 1
  • Y. Z. Wang
    • 1
  • Y. Y. Liu
    • 1
  • M. G. Wei
    • 1
  1. 1.College of AgricultureHenan Agricultural UniversityZhengzhouChina

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