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JOURNAL ARTICLE

Genetic analysis and major QTL detection for maize kernel size and weight in multi-environments

Ying Liu, Liwei Wang, Chuanlong Sun, Zuxin Zhang, Yonglian Zheng, Fazhan Qiu
TAG. Theoretical and Applied Genetics. Theoretische und Angewandte Genetik 2014, 127 (5): 1019-37
24553962
Twelve major QTL in five optimal clusters and several epistatic QTL are identified for maize kernel size and weight, some with pleiotropic will be promising for fine-mapping and yield improvement. Kernel size and weight are important target traits in maize (Zea mays L.) breeding programs. Here, we report a set of quantitative trait loci (QTL) scattered through the genome and significantly controlled the performance of four kernel traits including length, width, thickness and weight. From the cross V671 (large kernel) × Mc (small kernel), 270 derived F2:3 families were used to identify QTL of maize kernel-size traits and kernel weight in five environments, using composite interval mapping (CIM) for single-environment analysis along with mixed linear model-based CIM for joint analysis. These two mapping strategies identified 55 and 28 QTL, respectively. Among them, 6 of 23 coincident were detected as interacting with environment. Single-environment analysis showed that 8 genetic regions on chromosomes 1, 2, 4, 5 and 9 clustered more than 60 % of the identified QTL. Twelve stable major QTLs accounting for over 10 % of phenotypic variation were included in five optimal clusters on the genetic region of bins 1.02-1.03, 1.04-1.06, 2.05-2.07, 4.07-4.08 and 9.03-9.04; the addition and partial dominance effects of significant QTL play an important role in controlling the development of maize kernel. These putative QTL may have great promising for further fine-mapping with more markers, and genetic improvement of maize kernel size and weight through marker-assisted breeding.

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