Genetic variation of growth dynamics in maize (Zea mays L.) revealed through automated non‐invasive phenotyping. (7th January 2017) - Muraya, Moses M.; Chu, Jianting; Zhao, Yusheng; Junker, Astrid; Klukas, Christian; Reif, Jochen C.; Altmann, Thomas
Summary: Hitherto, most quantitative trait loci of maize growth and biomass yield have been identified for a single time point, usually the final harvest stage. Through this approach cumulative effects are detected, without considering genetic factors causing phase‐specific differences in growth rates. To assess the genetics of growth dynamics, we employed automated non‐invasive phenotyping to monitor the plant sizes of 252 diverse maize inbred lines at 11 different developmental time points; 50 k SNP array genotype data were used for genome‐wide association mapping and genomic selection. The heritability of biomass was estimated to be over 71%, and the average prediction accuracy amounted to 0.39. Using the individual time point data, 12 main effect marker‐trait associations (MTAs) and six pairs of epistatic interactions were detected that displayed different patterns of expression at various developmental time points. A subset of them also showed significant effects on relative growth rates in different intervals. The detected MTAs jointly explained up to 12% of the total phenotypic variation, decreasing with developmental progression. Using non‐parametric functional mapping and multivariate mapping approaches, four additional marker loci affecting growth dynamics were detected. Our results demonstrate that plant biomass accumulation is a complex trait governed by many small effect loci, most of which act at certain restricted developmental phases. This highlights the need for investigation of stage‐specific growth affecting genes to elucidate important processes operating at different developmental phases. Significance Statement: Most genetic studies of biomass accumulation or yield in crops have focused on a single growth stage, but agronomic traits are complex and controlled by many genes, each with small effect. Here we use high‐throughput non‐invasive phenotyping to show that genetic effects on maize biomass accumulation differ across developmental phases, that there are complex interactions of loci with developmental progression, that allele effects and epistatic interaction patterns change over time, and that functional mapping can uncover additional genetic factors. Our results indicate that continuous assessment of growth dynamics coupled with transcript profiling will aid in detecting superior stage‐specific genes/alleles and thus provide a powerful tool for crop improvement.