Time‐series transcriptomics reveals a drought‐responsive temporal network and crosstalk between drought stress and the circadian clock in foxtail millet

Abstract

SUMMARY Drought stress is a serious factor affecting crop growth and production worldwide. The circadian clock has been identified as key to improving regional adaptability of plants. However, our understanding of the contribution of the circadian clock to drought response and the impacts of drought stress on the circadian clock in plants is still limited. To explore the interactions between the circadian clock and drought stress, foxtail millet seedlings were treated with simulated drought (20% polyethylene glycol‐6000) treatment starting at the day (DD) onset zeitgeber time 0 (ZT0, lights on) and at the night (DN) onset zeitgeber time 16 (ZT16, lights off). A high temporal‐resolution transcriptomic investigation was performed using DD and DN samples collected at intervals of 2 or 4 h within a 24‐h drought‐treatment period. Overall, we identified 13 294 drought‐responsive genes (DRGs). Among these DRGs, 7931 were common between DD and DN samples, 2638 were specific to DD, and 2725 were specific to DN. Additionally, we identified 1257 circadian genes, of which 67% were DRGs. Interestingly, with drought treatment starting at the day for 8, 12 or 16 h, the circadian phase shifted to 12 h. We also found that the circadian clock led to different day and night drought‐responsive pathways. The identification of DRG_Clock (DRG and circadian clock) and DRG_NonClock (DRG and not circadian clock) genes provides a reference for selecting candidate drought resistance genes. Our work reveals the temporal drought‐response process and crosstalk between drought stress and the circadian clock in foxtail millet.

Genome-Wide Identification and Characterization of the CCT Gene Family in Foxtail Millet (Setaria italica) Response to Diurnal Rhythm and Abiotic Stress

“…To further explore the CCT genes response to diurnal rhythm, an expression analysis of CCT genes under diurnal rhythm was performed. The transcriptome data (PRJNA684771) used for diurnal rhythm analysis were downloaded from NCBI database according to the research of Yi et al [ 42 ]. The expression pattern of 16/37 CCT genes shoedn diurnal rhythm oscillations, which includes all PRR members, 6 COL members, and 5 CMF members ( Figure 7 and Table S5 ).…”

“…Actin gene ( SETIT_010361mg ) was used as internal control for this experiment. Transcriptome data used in this study were downloaded from the NCBI SRA database under accession number PRJNA684771 [ 42 ]. We processed per kilobase per million (FPKM) data for diurnal rhythm analysis.…”

“…We processed per kilobase per million (FPKM) data for diurnal rhythm analysis. Yi et al [ 42 ] sampled the two groups of samples at the beginning of light and the beginning of darkness, respectively, and there were two groups of data at 16 h, 20 h, and 24 h. Therefore, we draw the line graph using the average of the FPKM values of these two sets of data.…”

Transcriptome profiling, physiological, and biochemical analyses provide new insights towards drought stress response in sugar maple (Acer saccharum Marshall) saplings

“…Time-series gene expression analysis revealed different functional groups of genes regulated at 7, 14, and 21 days of drought ( Table S11 ). Time series analysis was used in previous studies to understand the gene regulation patterns in response to drought stress in plants ( He et al., 2020 ; Yi et al., 2022 ). Some plant physiological functions were suppressed, and a series of responses were activated to overcome the drought stress effects by complex gene regulatory and networks, as evidenced by global transcriptomic changes in eight clusters of regulation patterns we found in sugar maple ( Table S11 ).…”

Diurnal transcriptome dynamics reveal the photoperiod response of Pyrus

“…With the research on circadian clock genes and output pathways, it is critical to decode the function and regulation of genes from the diurnal dynamics throughout the day. The combination of transcriptome sequencing technology and time‐series experimental design makes it possible to examine global transcriptional changes in response to the circadian clock and environmental cues (Desai et al, 2021; Kiseleva et al, 2022; Wang et al, 2021; Weng et al, 2019; Yi et al, 2022). Previous analyses have established comprehensive molecular mechanisms under a certain day length (e.g., 12/12 h day/night) (Filichkin et al, 2011; Hotta et al, 2013; Xu et al, 2011) or under constant light conditions (Hudson, 2010; Muller et al, 2020).…”