Abstract
Maize grain yield and related traits are complex and are controlled by a large number of genes of small effect or quantitative trait loci (QTL). Over the years, a large number of yield-related QTLs have been identified in maize and deposited in public databases. However, integrating and re-analyzing these data and mining candidate loci for yield-related traits has become a major issue in maize. In this study, we collected information on QTLs conferring maize yield-related traits from 33 published studies. Then, 999 of these QTLs were iteratively projected and subjected to meta-analysis to obtain metaQTLs (MQTLs). A total of 76 MQTLs were found across the maize genome. Based on a comparative genomics strategy, several maize orthologs of rice yield-related genes were identified in these MQTL regions. Furthermore, three potential candidate genes (Gene ID: GRMZM2G359974, GRMZM2G301884, and GRMZM2G083894) associated with kernel size and weight within three MQTL regions were identified using regional association mapping, based on the results of the meta-analysis. This strategy, combining MQTL analysis and regional association mapping, is helpful for functional marker development and rapid identification of candidate genes or loci.
Highlights
Maize is one of the most important cereal crops in the world and plays an important role in maintaining food security, promoting the development of animal husbandry, and satisfying the demand for industrial raw materials
These results suggest that grain yield and related traits in maize are mainly controlled by numerous loci of minor effect and display a complex genetic architecture
Grain yield and related traits are complex quantitative traits controlled by numerous quantitative trait loci (QTL) of small effect in maize
Summary
Maize is one of the most important cereal crops in the world and plays an important role in maintaining food security, promoting the development of animal husbandry, and satisfying the demand for industrial raw materials. Improvement of grain yield is consistently one of the most important goals for maize breeders. Grain yield is a complex quantitative trait controlled by many quantitative trait loci (QTL) with a small effect (Wu and Lin, 2006). A better understanding of the genetic architecture and molecular mechanisms of yield-related traits could help improve grain yield in maize. Linkage mapping is an efficient way to identify genetic loci for complex quantitative traits in maize (Wallace et al, 2014). In the past two decades, many QTLs have been identified for yield and related traits far, such as ear-related traits (ERT) and kernel-related traits Marker-assisted selection (MAS) is a more efficient selection method for yield and its related traits improvement in the process of crop breeding.
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