Complex interactions between day length and diurnal patterns of gene expression drive photoperiodic responses in a perennial C₄ grass

Abstract

Photoperiod is a key environmental cue affecting flowering and biomass traits in plants. Key components of the photoperiodic flowering pathway have been identified in many species, but surprisingly few studies have globally examined the diurnal rhythm of gene expression with changes in day length. Using a cost‐effective 3′‐Tag RNA sequencing strategy, we characterize 9,010 photoperiod responsive genes with strict statistical testing across a diurnal time series in the C4 perennial grass, Panicum hallii. We show that the vast majority of photoperiod responses are driven by complex interactions between day length and sampling periods. A fine‐scale contrast analysis at each sampling time revealed a detailed picture of the temporal reprogramming of cis‐regulatory elements and biological processes under short‐ and long‐day conditions. Phase shift analysis reveals quantitative variation among genes with photoperiod‐dependent diurnal patterns. In addition, we identify three photoperiod enriched transcription factor families with key genes involved in photoperiod flowering regulatory networks. Finally, coexpression networks analysis of GIGANTEA homolog predicted 1,668 potential coincidence partners, including five well‐known GI‐interacting proteins. Our results not only provide a resource for understanding the mechanisms of photoperiod regulation in perennial grasses but also lay a foundation to increase biomass yield in biofuel crops.

Interaction between photoperiod and variation in circadian rhythms in tomato

“…Expression differences between samples in long days and samples in short days were consistent with the results observed before, with long days inducing on average higher expression in dusk genes and lower expression in dawn genes. These results indicate an advanced phase of the circadian clock of tomato under short days compared to long days, as reported for other species before (Dalchau et al, 2010; Michael et al, 2008; Weng et al, 2019). In summary, photoperiod shifts the timing of expression of cycling genes in tomato, thus causing substantial environment specific transcriptional differences.…”

“…Previous studies have determined that changes in photoperiod can impact the expression pattern of transcripts whose expression cycles throughout the day (Dalchau et al, 2010; Michael et al, 2008; Weng et al, 2019). We obtained a list of such transcripts in tomato together with their phase (the time of the day when they show their maximum expression) using previously published RNA-seq data from seedlings from cultivated tomato and its wild relative S. pennellii sampled every 4 hours for one day in 12 hours light / 12 hours dark photoperiods (Müller et al, 2016) (Table S2).…”

“…For example, these proteins reset the circadian clock each day by reading light and temperature signals at dawn or dusk (Jones, 2009). Moreover, they can change the time of the day when some transcripts are expressed depending on the duration of the light period (photoperiod), allowing plants to time biological processes differently depending on the season (Dalchau et al, 2010; Michael et al, 2008; Miwa et al, 2006; Roden et al, 2002; Webb et al, 2019; Weng et al, 2019).…”

TagSeq for gene expression in non-model plants: a pilot study at the Santa Rita Experimental Range NEON core site

“…Kenkel and Matz, 2016;Dixon et al, 2018;Kriefall et al, 2018;Rocker et al, 2019) . In plants, however, TagSeq studies to date appear to have been confined to model species for which a high quality reference genome is available (Meyer et al, 2014;Des Marais et al, 2015;Lovell et al, 2016;Kremling et al, 2018;Chu et al, 2019;Razzaque et al, 2019;Weng et al, 2019) . How TagSeq will perform using a reference transcriptome in plants is not clear given the lack of such studies and a paucity of relevant performance information for TagSeq.…”

TagSeq for gene expression in non‐model plants: A pilot study at the Santa Rita Experimental Range NEON core site

“…Many subsequent studies have successfully used a similar approach in other non-model animals (e.g., Kenkel and Matz, 2016;Dixon et al, 2018;Kriefall et al, 2018;Rocker et al, 2019). In plants, however, TagSeq studies to date appear to have been confined to model species for which a high-quality reference genome is available (Meyer et al, 2014;Des Marais et al, 2015;Lovell et al, 2016;Kremling et al, 2018;Chu et al, 2019;Razzaque et al, 2019;Weng et al, 2019). How TagSeq will perform using a reference transcriptome in plants is not clear given the lack of such studies and a paucity of relevant performance information for TagSeq.…”