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Genetic Analysis of Corn Kernel Chemical Composition in the Random Mated 7 Generation of the Cross of Generations 70 of IHP × ILP
Author(s) -
Dudley J. W.,
Clark Darryl,
Rocheford Torbert R.,
LeDeaux John R.
Publication year - 2007
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.2135/cropsci2006.03.0207
Subject(s) - biology , quantitative trait locus , kernel (algebra) , starch , zea mays , genetics , agronomy , food science , mathematics , gene , combinatorics
To identify and characterize quantitative trait loci (QTL) affecting kernel weight and concentrations of protein, oil, and starch in the corn ( Zea mays L.) kernel, plants from generations 70 of the Illinois High Protein (IHP) and Illinois Low Protein (ILP) strains, previously developed by divergent selection for kernel protein concentration, were crossed. The cross was random mated (RM) seven generations and selfed twice to develop 500 F 1 RM 7 S 2 lines. The lines per se were evaluated at three locations with two replications for 2 yr and testcrosses were evaluated at three locations in 1 yr. Genotypes were evaluated using 499 SNP markers on DNA from a bulk of leaf tissue from each line. As the parent plants used to make the original cross were not available for genotyping, previously reported multivariable and modified simple interval mapping (SIM) procedures were used. SIM identified more significant regions for all traits than did single marker analysis. Correlations and signs of QTL effects suggest development of high protein–high starch lines would be difficult but that it should be possible to develop high protein–high oil lines with minimal effects on kernel weight. The identification of a large number of QTL (at least 40 each for oil, protein, starch, and kernel weight) with small effects agrees in general with earlier estimates based on quantitative genetic theory and has implications for breeding strategies for improved corn kernel quality traits.