Correlations and comparisons of quantitative trait loci with family per se and testcross performance for grain yield and related traits in maize
- PMID: 23183923
- DOI: 10.1007/s00122-012-2017-1
Correlations and comparisons of quantitative trait loci with family per se and testcross performance for grain yield and related traits in maize
Abstract
Simultaneous improvement in grain yield and related traits in maize hybrids and their parents (inbred lines) requires a better knowledge of genotypic correlations between family per se performance (FP) and testcross performance (TP). Thus, to understand the genetic basis of yield-related traits in both inbred lines and their testcrosses, two F (2:3) populations (including 230 and 235 families, respectively) were evaluated for both FP and TP of eight yield-related traits in three diverse environments. Genotypic correlations between FP and TP, [Formula: see text] (FP, TP), were low (0-0.16) for grain yield per plant (GYPP) and kernel number per plant (KNPP) in the two populations, but relatively higher (0.32-0.69) for the other six traits with additive effects as the primary gene action. Similar results were demonstrated by the genotypic correlations between observed and predicted TP values based on quantitative trait loci positions and effects for FP, [Formula: see text] (M (FP), Y (TP)). A total of 88 and 35 QTL were detected with FP and TP, respectively, across all eight traits in the two populations. However, the genotypic variances explained by the QTL detected in the cross-validation analysis were much lower than those in the whole data set for all traits. Several common QTL between FP and TP that accounted for large phenotypic variances were clustered in four genomic regions (bin 1.10, 4.05-4.06, 9.02, and 10.04), which are promising candidate loci for further map-based cloning and improvement in grain yield in maize. Compared with publicly available QTL data, these QTL were also detected in a wide range of genetic backgrounds and environments in maize. These results imply that effective selection based on FP to improve TP could be achieved for traits with prevailing additive effects.
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