Temperature Sensing Is Distributed throughout the Regulatory Network that Controls FLC Epigenetic Silencing in Vernalization

Abstract

SummaryMany organisms need to respond to complex, noisy environmental signals for developmental decision making. Here, we dissect how Arabidopsis plants integrate widely fluctuating field temperatures over month-long timescales to progressively upregulate VERNALIZATION INSENSITIVE3 (VIN3) and silence FLOWERING LOCUS C (FLC), aligning flowering with spring. We develop a mathematical model for vernalization that operates on multiple timescales—long term (month), short term (day), and current (hour)—and is constrained by experimental data. Our analysis demonstrates that temperature sensing is not localized to specific nodes within the FLC network. Instead, temperature sensing is broadly distributed, with each thermosensory process responding to specific features of the plants’ history of exposure to warm and cold. The model accurately predicts FLC silencing in new field data, allowing us to forecast FLC expression in changing climates. We suggest that distributed thermosensing may be a general property of thermoresponsive regulatory networks in complex natural environments.

Noncoding SNPs influence a distinct phase of Polycomb silencing to destabilize long-term epigenetic memory at Arabidopsis FLC

“…S5), in an effort to reproduce the reactivation of Lov-1 FLC after 4 wk of vernalization. This model is an extension of the vernalization model presented in Antoniou-Kourounioti et al (2018), adapted to Lov-1 and fitted to H3K27me3 and H3K36me3 ChIP data, as well as FLC expression data. This model broadly reproduced all these data, except for the continued reduction of the FLC levels after the cold in Col FRI (Supplemental Fig.…”

“…Early transcriptional shutdown and VIN3-dependent silencing The "VIN3-independent pathway" ) and the "VIN3-dependent" nucleation switch (including the dynamics of VIN3) were modeled as described in Antoniou-Kourounioti et al (2018). The same temperature sensitivity was also used, though in this study only 5°C (cold) and 22°C (warm) were relevant.…”

“…where T is temperature, V is the VIN3 concentration, calculated according to the LSCD model of Antoniou-Kourounioti et al (2018), and T 1 , T 2 , and p s2 are parameters defined in Supplemental Table S6. The newly defined transitions N S, S P, and P I only occur in dividing cells and therefore have rates that depend on the temperature-dependent growth rate g(T) = p g1 , warm (22 • C) p g2 , cold (5 • C) , s 3 = p s3 g, and r 2 = p r2 g, where p g1 , p g2 , p s3 , and p r2 are parameters defined in Supplemental Table S6.…”

Fine tuning of hormonal signaling is linked to dormancy status in sweet cherry flower buds

“…The next steps, in addition to the integration of GA signaling and its crosstalk with ABA, will be to provide information on temperaturemediated control of the regulatory cascades. Recent research led on Arabidopsis, allowed by highthroughput sequencing techniques, has hastened the pace for the incorporation of molecular data into phenology models (Satake et al 2013, Kudoh 2016, Antoniou-Kourounioti et al 2018, Nishio et al 2020), thus opening new roads for perennial studies.…”

Duration of cold exposure defines the rate of reactivation of a perennial FLC orthologue via H3K27me3 accumulation

“…Thus, it is expected that an insufficient cold duration would affect flowering through the perturbation of perennial FLC upregulation. A mixed approach, including time series data and mathematical modelling, has been used to investigate the molecular mechanisms underlying the vernalisation process 14,20,21,24,[30][31][32][33] . We previously reported the seasonal dynamics of AhgFLC mRNA, H3K4me3, and H3K27me3 over 2 years in a natural population, and constructed mathematical models to analyse the properties of the regulatory system 24 .…”