Deciphering and Prediction of Transcriptome Dynamics under Fluctuating Field Conditions

Abstract

Determining the drivers of gene expression patterns is more straightforward in laboratory conditions than in the complex fluctuating environments where organisms typically live. We gathered transcriptome data from the leaves of rice plants in a paddy field along with the corresponding meteorological data and used them to develop statistical models for the endogenous and external influences on gene expression. Our results indicate that the transcriptome dynamics are predominantly governed by endogenous diurnal rhythms, ambient temperature, plant age, and solar radiation. The data revealed diurnal gates for environmental stimuli to influence transcription and pointed to relative influences exerted by circadian and environmental factors on different metabolic genes. The model also generated predictions for the influence of changing temperatures on transcriptome dynamics. We anticipate that our models will help translate the knowledge amassed in laboratories to problems in agriculture and that our approach to deciphering the transcriptome fluctuations in complex environments will be applicable to other organisms.

Predicting Gene Function from Uncontrolled Expression Variation among Individual Wild-Type Arabidopsis Plants

“…Although the use of natural variation on the genotype level has become mainstream in recent years, e.g. in genome-wide association studies and expression quantitative-trait-locus (eQTL) analyses (Kliebenstein, 2009;Nayak et al, 2009;Chan et al, 2011;Cubillos et al, 2012;Weigel, 2012), the potential use of natural variation in gene expression triggered by variations in environmental conditions has only recently begun to gather attention (Nagano et al, 2012;Richards et al, 2012). In most species, natural variation other than on the genotype level is still considered a nuisance rather than a potential asset.…”

HsfB2b-mediated repression ofPRR7directs abiotic stress responses of the circadian clock

“…Brief pulses (from minutes to hours, depending on the intensity) result in acute responses from the clock. Importantly, the severity of such responses is time-dependent and gated by the oscillator (12)(13)(14). Longer durations of zeitgeber change can function as an entrainment signal and generally follow the diurnal pattern of the light-dark cycle.…”

Forecasting flowering phenology under climate warming by modelling the regulatory dynamics of flowering-time genes

“…Recently, the molecular genetics underpinning temperature responses has been uncovered in laboratory-based model systems [6][7][8] . Considering the threat to global biodiversity, the application of ample molecular genetic data in the laboratory to real environmental problems outside the laboratory offers advantages for the genetically informed assessment of ecosystem vulnerability to climate change 9,10 . Despite its critical importance, our understanding of the molecular mechanism underlying the rapid phenological changes observed in nature is limited.…”