Abstract:

Maize (Zea mays L.) is one of the crops studied widely by QTL mapping. There are a lot of reports about QTL for important traits, including yield components, plant height, grain moisture and growth data and so on. Thereinto, grain yield is a very complicated quantitative trait, existing interactions not only with gene by gene, but also gene by environment. Studying the relationship of the interaction between genes and environments and finding the yield QTL expressed in given environment are of importance in practice for cultivating new varieties adapting to some area. If consensus QTL of yield and its adjacent marker can be found, it will provide possibility for molecular breeding by marker assisted selection (MAS). The objective of this experiment was to analysis the expression character of QTL controlling yield, and to detect common genetic loci of yield, as well as adjacent marker, in different environment, which could provide technical basis for fine mapping of yield QTL and MAS. One hundred and ninety-one F₂ individuals derived from the cross, Mo17×Huangzao4, were genotyped by SSR and AFLP markers to construct the genetic linkage map, and 184 corresponding F_2∶3 families were phenotyped for maize yield components in Beijing and Xinjiang. The performance and correlations among 5 yield components including ears per plant (EPP), row number per ear (RN), kernel number per row (KR), 100-kernel weight (KW) and grain yield per plant (GY) were evaluated, and the quantitative trait loci (QTL) were characterized. Totally, 47 QTLs were identified for 5 traits, locating on 9 chromosomes with exception of the chromosome 10. 10, 13, 9, 10 and 5 QTLs were detected for EPP, RN, KR, KW and GY, respectively. Each of these QTLs could explain 5.3% to 25.6% phenotypic variation of EPP, 4.5% to 23.2% of RN, 5.4% to 13.7% of KR, 4.9% to 13.3% of KW and 6.1% to 35.8% of GY. Most of the QTLs are detected in single environment, indicating the significant interactions between QTL and environments. Different QTLs relevant to the yield components which are correlated each other can be identified easily in the same or adjacent chromosome regions. Several regions with clustered QTLs relevant to multiple yield components identified in the study may provide the genetic loci of the universal yield QTLs.

Key words: Zea mays L., Yield components, Environment, Quantitative trait loci