Experimenters who seek to apply the many and diverse studies on quantitative trait loci (QTL) face complex problems in Summarizing, interrelating, and integrating them. We report a strategy for consensus QTL maps that leverages the highly curated data in MaizeGDB, in particular, the numerous QTL studies and maps that are integrated with other genome data on a common coordinate system. In addition, we exploit a systematic QTL nomenclature and a hierarchical categorization of over 400 maize traits developed in the mid 90's; the main nodes of the hierarchy are aligned with the trait ontology at Gramene, a comparative mapping database for cereals. Consensus maps are presented for one trait category, insect response (80 QTL); and two traits, grain yield (71 QTL) and kernel weight (113 QTL), representing over 20 separate QTL map sets of 10 chromosomes each. The strategy is germplasm-independent and reflects any trait relationships that may be chosen. Whether the goal of the experimenter is to understand processes of growth, development, or stress response; to define and isolate genes specific to traits; or to mark QTL segments for selection in maize improvement, the elements of the strategy can be applied equally well.
分享
引用
