EGRINs (Environmental Gene Regulatory Influence Networks) in Rice That Function in the Response to Water Deficit, High Temperature, and Agricultural Environments

Abstract

Environmental gene regulatory influence networks (EGRINs) coordinate the timing and rate of gene expression in response to environmental signals. EGRINs encompass many layers of regulation, which culminate in changes in accumulated transcript levels. Here, we inferred EGRINs for the response of five tropical Asian rice (Oryza sativa) cultivars to high temperatures, water deficit, and agricultural field conditions by systematically integrating time-series transcriptome data, patterns of nucleosome-free chromatin, and the occurrence of known cis-regulatory elements. First, we identified 5447 putative target genes for 445 transcription factors (TFs) by connecting TFs with genes harboring known cis-regulatory motifs in nucleosomefree regions proximal to their transcriptional start sites. We then used network component analysis to estimate the regulatory activity for each TF based on the expression of its putative target genes. Finally, we inferred an EGRIN using the estimated transcription factor activity (TFA) as the regulator. The EGRINs include regulatory interactions between 4052 target genes regulated by 113 TFs. We resolved distinct regulatory roles for members of the heat shock factor family, including a putative regulatory connection between abiotic stress and the circadian clock. TFA estimation using network component analysis is an effective way of incorporating multiple genome-scale measurements into network inference.

Evolutionary and ecological functional genomics, from lab to the wild

“… The maturation of in natura gene expression studies in an evolutionary and ecological functional genomics (EEFG)‐type framework, as illustrated by representative studies. Stylized and re‐drawn key findings for (a) single transcript ( FLC ) expression in natura (Aikawa et al ., ), (b) whole transcriptome changes throughout developmental growth of Arabidopsis thaliana in the field (Richards et al ., ), and (c) constructed environmental gene regulatory influence networks from transcriptome and chromatin accessibility data (Wilkins et al ., ). These selected studies highlight the transition to a systems biology approach in an EEFG‐type framework.…”

“…Timing in these field transcriptome studies provides a snapshot of the different dimensions of physiological development and even evolution. Molecular mechanisms governing the physiological responses vary across seasons, time‐points within a season and even within a given day (Nagano et al ., ; Plessis et al ., ; Wilkins et al ., ). For example, differences in flowering time can reflect on differences in photoperiod sensitivity or vernalization requirements between genotypes (Des Marais et al ., ; Torres et al ., ).…”

“…The development of systems biology has also provided the opportunity to use transcriptome data, in conjunction with other data types (Bonneau et al ., ), to infer key regulatory networks that display the genetic underpinnings of plant responses to the environment. Such regulatory networks include environmental gene regulatory influence networks (EGRINs; Wilkins et al ., ; Figure ), as well as other representations of gene regulatory modules reacting to environmental signals (Nagano et al ., ; Plessis et al ., ; Fournier‐Level et al ., ; Des Marais et al ., ; Miao et al ., ).…”

Gene regulatory network reconstruction using single-cell RNA sequencing of barcoded genotypes in diverse environments

“…Subsequent work has enhanced this approach by selecting regulators for each gene more effectively , incorporating orthogonal data types that can be used to generate constraints on network structure (Greenfield et al, 2013) , and explicitly estimating latent biophysical parameters including transcription factor activity (Arrieta-Ortiz et al, 2015;Fu et al, 2011) and mRNA decay rates . We have successfully applied this approach to construct GRNs from gene expression data acquired from variation across time, conditions, and genotypes in microbes (Arrieta-Ortiz et al, 2015; , plants (Wilkins et al, 2016) , and mammalian cells (Ciofani et al, 2012; .…”

Field of Genes: Uncovering EGRINs (Environmental Gene Regulatory Influence Networks) in Rice That Function during High-Temperature and Drought Stress

“…Since EGRINs affect chromatin availability in multiple regions of the genes they regulate, Sullivan et al (2014) used changes in chromatin accessibility and the identification of transcription factor footprints, rather than changes in gene expression, to identify putative stressresponsive transcriptional networks in Arabidopsis thaliana. Wilkins et al (2016) went one step further by combining chromatin accessibility analysis with coexpression data and network inference algorithms to uncover EGRINs in drought-and heat-stressed rice (Oryza sativa), a major crop whose yields are threatened by climate change. Specifically, the authors investigated the responses of five tropical Asian rice cultivars to hightemperature and water-stress conditions using both hydroponically grown plants in a controlled environment and plants that were naturally exposed to stress conditions in the field (see figure).…”