Temporal analysis of physiological and transcriptome responses during high light exposure that lead to dynamic acclimation in Arabidopsis

The photosynthetic capacity of mature leaves increases upon exposing plants to continuous or intermittent high light (HL). This is termed dynamic acclimation, which is an important determinant of plant productivity. We hypothesized that genes coding for transcription regulators (TRs), which respond rapidly (≤1h) and transiently to HL, initiate dynamic acclimation. To find such genes, a highly replicated time series transcriptomic dataset was generated from leaf 7 of low light (LL)-grown Arabidopsis thaliana plants subjected to HL for up to 6h. This revealed 3844 HL-responsive differentially expressed genes (DEGs). 49 transiently HL-induced TR DEGs were selected for Bayesian modeling, which revealed that B-BOX TRANSCRIPTION (CO) FACTOR32 (BBX32) was the most connected gene in an inferred network. Dynamic acclimation was elicited in Arabidopsis Col-0 by exposure to daily 4h HL over 5 days. Using this procedure on over-expressing (OE) and null mutant plants, it was shown that BBX32 is a negative regulator of dynamic acclimation. The same modeling connected BBX32 to the TR gene LONG HYPOCOTYL5 (HY5), but unlike BBX32, HY5 was shown to positively regulate dynamic acclimation. The severely diminished response to daily HL of BBX32–OE/hy5 plants suggest that in wild type plants, BBX32 and HY5 exert a balanced, flexible and complete regulation of dynamic acclimation. A novel experimental design strategy (A Mead et al, in preparation), based on the principle of the loop design, was developed to enable efficient extraction of information about key sample comparisons using a two-color hybridization experimental system. With 100 distinct samples (four biological replicates, at each of 12 time points in control low light (LL) conditions and high light (HL) conditions plus 4 biological replicate time zero samples) to be compared, the experimental design included 200 two-color microarray slides, allowing four technical replicates of each sample to be observed. One third of the slides were devoted to assessment of changes in gene expression between time points, using a simple loop design to link samples from time points across the sampled times, directly comparing samples collected on adjacent sampling times (i.e. Time zero with 0.5h HL, 0.5h HL with 1h HL, etc.). With the remaining slides, four separate loops were constructed comparing treatments, biological replicates and sampling times.