Exploring contribution to early flowering in plants under daily variable temperature and its tissue-specific flowering gene network.

Molecular mechanisms of how constant temperatures affect flowering time have been largely characterized in the model plant ; however, the effect of natural daily variable temperature outside laboratories is only partly explored. Several flowering genes have been shown to play important roles in temperature responses, including () and (), the two genes encoding for the transcription factors (TFs) that act antagonistically to regulate flowering time by activating and repressing floral integrator (), respectively. In this study, we have taken a multidisciplinary approach to explore the contribution of to the early flowering observed in the daily variable temperature (VAR) and to broaden its transcriptional network using publicly available transcriptomic data. We observed early flowering in the natural accessions Col-0, C24 and their late flowering hybrid C24xCol grown under VAR, as compared with a constant temperature (CON). The loss-of-function mutation of exhibits later flowering in VAR in both the Col-0 parent and the C24xCol hybrid, suggesting that , at least in part, contributes to acceleration of flowering in the VAR condition. To investigate the interplay between and its flowering regulator counterparts, and , we performed transcriptional analyses and found that VAR increased transcription at the end of the day when temperature peaked at 32°C, when transcription was also elevated. On the other hand, we observed a decrease in transcription in the 4-week-old plants grown in VAR, as well as in the plants with overexpression grown in CON. These results raise a possibility that PIF4 might also regulate indirectly through the repression of , in addition to the well-characterized direct control of PIF4 over . To further expand our view on the PIF4-orientated flowering gene network in response to temperature changes, we have constructed a coexpression-transcriptional regulatory network by combining publicly available transcriptomic data and gene regulatory interactions of and its closely related flowering genes, , , and . The network model reveals conserved and tissue-specific regulatory functions, which are useful for confirming as well as predicting the functions and regulatory interactions between these key flowering genes.