Maize is unique among cereal grasses because of its monoecious flowering habit. Male flowers are normally restricted to the tassel that terminates the primary shoot, whereas female flowers occur as ears at the terminal nodes of lateral branches. We observed Ki14, a tropical maize inbred that produces an ear tipped by a staminate (male) spike under certain environmental conditions, such as long daylengths. Recombinant inbred lines derived from the cross between temperate line B97, which was never observed to produce a staminate ear tip, and Ki14 segregated for the trait under long daylengths. Some progeny lines that had even longer staminate tips than Ki14 were male fertile. We mapped three QTL controlling staminate ear tip using a two-part (binomial plus normal) model. A major QTL on chromosome 3 had a large effect on penetrance of the trait (whether a line would produce staminate ear tips or not) as well as its severity (the length of the staminate tip). This QTL seems to be linked to, but at a distinct position from, a previously mapped QTL controlling the proportion of staminate florets in ears in progeny from crosses between maize and teosinte. Two additional QTL affecting staminate ear tip severity overlapped with QTL controlling photoperiod response previously mapped in this population. Alleles conferring photoperiod sensitivity for delayed flowering at these QTL seem to enhance the production of staminate ear tips under long daylengths.
Variation in maize for response to photoperiod is related to geographical adaptation in the species. Maize possesses homologs of many genes identified as regulators of flowering time in other species, but their relation to the natural variation for photoperiod response in maize is unknown. Candidate gene sequences were mapped in four populations created by crossing two temperate inbred lines to two photoperiod-sensitive tropical inbreds. Whole-genome scans were conducted by high-density genotyping of the populations, which were phenotyped over 3 years in both short- and long-day environments. Joint multiple population analysis identified genomic regions controlling photoperiod responses in flowering time, plant height, and total leaf number. Four key genome regions controlling photoperiod response across populations were identified, referred to as ZmPR1-4. Functional allelic differences within these regions among phenotypically similar founders suggest distinct evolutionary trajectories for photoperiod adaptation in maize. These regions encompass candidate genes CCA/LHY, CONZ1, CRY2, ELF4, GHD7, VGT1, HY1/SE5, TOC1/PRR7/PPD-1, PIF3, ZCN8, and ZCN19.
The transition from the vegetative to reproductive development is a critical event in the plant life cycle. The accurate prediction of flowering time in elite germplasm is important for decisions in maize breeding programs and best agronomic practices. The understanding of the genetic control of flowering time in maize has significantly advanced in the past decade. Through comparative genomics, mutant analysis, genetic analysis and QTL cloning, and transgenic approaches, more than 30 flowering time candidate genes in maize have been revealed and the relationships among these genes have been partially uncovered. Based on the knowledge of the flowering time candidate genes, a conceptual gene regulatory network model for the genetic control of flowering time in maize is proposed. To demonstrate the potential of the proposed gene regulatory network model, a first attempt was made to develop a dynamic gene network model to predict flowering time of maize genotypes varying for specific genes. The dynamic gene network model is composed of four genes and was built on the basis of gene expression dynamics of the two late flowering id1 and dlf1 mutants, the early flowering landrace Gaspe Flint and the temperate inbred B73. The model was evaluated against the phenotypic data of the id1 dlf1 double mutant and the ZMM4 overexpressed transgenic lines. The model provides a working example that leverages knowledge from model organisms for the utilization of maize genomic information to predict a whole plant trait phenotype, flowering time, of maize genotypes.
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