Abstract

A set of RIL population was used to detect QTL associated with the sizes of eight consecutive leaves, across different environments, and ten QTL clusters were identified as main QTLs. One of the important parameters of the maize leaf architecture that affects light penetration into the canopy, leaf size, has long attracted breeders' attention for optimizing the plant type of maize and for maximizing the grain yield (GY). In this study, we used 253 RIL lines derived from a cross between B73 and SICAU1212 to investigate the leaf widths (LWs), leaf lengths (LLs), and leaf areas (LAs) of eight consecutive leaves of maize below the tassel and GY across different environments and to identify quantitative traits loci (QTLs) controlling the above-mentioned traits, using inclusive interval mapping for single-environment analysis plus a mixed-model-based composite interval mapping for joint analysis. A total of 171 and 159 putative QTLs were detected through these two mapping methods, respectively. Single-environment mapping revealed that 39 stable QTLs explained more than 10% of the phenotypic variance, and 35 of the 39 QTLs were also detected by joint analysis. In addition, joint analysis showed that nine of the 159 QTLs exhibited significant QTL×environment interaction and 15 significant epistatic interactions were identified. Approximately 47.17% of the QTLs for leaf architectural traits in joint analysis were concentrated in ten main chromosomal regions, namely, bins 1.07, 2.02, 3.06, 4.09, 5.01, 5.02, 5.03-5.04, 5.07, 6.07, and 8.05. This study should provide a basis for further fine-mapping of these main genetic regions and improvement of maize leaf architecture.

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