Meta-analysis combined with syntenic metaQTL mining dissects candidate loci for maize yield

Yield potential and stability improvement with the goal of ensuring global food security is an important priority. Yield has a quantitative nature and is controlled by quantitative trait loci (QTL) and environmental factors. An increasingly large number of maize yield QTL have been identified, and how to integrate and re-analyze them is challenging. To this end, we tried to combine QTL meta-analysis with homology-based cloning techniques to dissect candidate loci/genes for maize yield. We first collected maize yield-related QTL from public resources. Then, 351 collected QTL were iteratively projected and meta-analyzed to obtain metaQTL (MQTL). A total of 54 MQTL were identified and tended to cluster in the maize genome. Seven MQTL containing ten maize orthologs of rice yield genes were dissected and temporarily termed syntenic MQTL. Maize orthologs of three functionally-characterized rice yield genes, GIF1, WFP/IPA1, and DEP1, were specially selected to undergo phylogenetic, proliferation, and selective pattern analysis. The results showed that maize orthologs were closely related to rice yield genes and subjected to mixed selective pressures, including positive selection during selective sweeps. The power of the combined techniques reported here was primarily validated not only by the congruency of MQTL and recently reported maize yield QTL but also by mined syntenic MQTL containing the well-characterized Miniature1 (Mn1) gene for maize kernel size and weight determination. Maize MQTL, especially syntenic MQTL regions, could serve not only for QTL fine-mapping and cloning but also for the marker-assisted selection breeding program. The maize yield candidate loci/genes presented here also deserve further investigation and will provide clues to the molecular bases of grain yield. Additionally, the combined technique described here will find its way into further quantitative trait research.