Association analysis of candidate genes for maysin and chlorogenic acid accumulation in maize silks
- First Online:
- 597 Downloads
Two compounds, the C-glycosyl flavone maysin and the phenylpropanoid product chlorogenic acid (CGA), have been implicated in corn earworm (Helicoverpa zea Boddie) resistance in maize (Zea mays L.). Previous quantitative trait locus (QTL) analyses identified the pericarp color (p) locus, which encodes a transcription factor, as the major QTL for maysin and CGA. QTL analysis has also implicated the dihydroflavanol reductase (DFR; E.C. no. 220.127.116.11) locus anthocyaninless1 (a1) and the duplicate chalcone synthase (CHS; E.C. no. 18.104.22.168) loci colorless2 (c2) and white pollen1 (whp1) as genes underlying QTL for maysin and/or CGA synthesis. Epistatic interactions between p and a1 and between p and c2 were also defined. CHS catalyzes the first step in the flavonoid pathway and represents one of the first enzyme steps following the branch off the general phenylpropanoid pathway towards CGA synthesis. In maize, the reduction of dihydroflavanol to leucoanthocyanin by DFR immediately follows the pathway branch leading to C-glycosyl flavone production. The detection of QTLs for maysin and CGA concentration at loci encoding enzyme steps following the pathway branch points implicates alterations in the flow of biochemical intermediates as the biological basis of the QTL effects. To examine if sequence variation among alleles of a1, c2, and whp1 affect maysin and CGA synthesis in maize silks, we performed an association analysis. Because the p locus has often been a major QTL for maysin and CGA and has exhibited epistatic interactions with a1, c2, and whp1, association analysis was conditioned on the p genotype. A highly significant association of two sequence polymorphisms in the promoter of a1 with maysin synthesis was demonstrated. Additional conditioning on the genotype of the significant a1 polymorphism allowed the detection of a significant polymorphism within the whp1 promoter. Our analyses demonstrate that conditioning for epistatic factors greatly increases the power of association testing.