A Gene-Phenotype Network Based on Genetic Variability for Drought Responses Reveals Key Physiological Processes in Controlled and Natural Environments

Abstract

Identifying the connections between molecular and physiological processes underlying the diversity of drought stress responses in plants is key for basic and applied science. Drought stress response involves a large number of molecular pathways and subsequent physiological processes. Therefore, it constitutes an archetypical systems biology model. We first inferred a gene-phenotype network exploiting differences in drought responses of eight sunflower (Helianthus annuus) genotypes to two drought stress scenarios. Large transcriptomic data were obtained with the sunflower Affymetrix microarray, comprising 32423 probesets, and were associated to nine morpho-physiological traits (integrated transpired water, leaf transpiration rate, osmotic potential, relative water content, leaf mass per area, carbon isotope discrimination, plant height, number of leaves and collar diameter) using sPLS regression. Overall, we could associate the expression patterns of 1263 probesets to six phenotypic traits and identify if correlations were due to treatment, genotype and/or their interaction. We also identified genes whose expression is affected at moderate and/or intense drought stress together with genes whose expression variation could explain phenotypic and drought tolerance variability among our genetic material. We then used the network model to study phenotypic changes in less tractable agronomical conditions, i.e. sunflower hybrids subjected to different watering regimes in field trials. Mapping this new dataset in the gene-phenotype network allowed us to identify genes whose expression was robustly affected by water deprivation in both controlled and field conditions. The enrichment in genes correlated to relative water content and osmotic potential provides evidence of the importance of these traits in agronomical conditions.

Promises and challenges of eco-physiological genomics in the field: tests of drought responses in switchgrass

“…For example, photosynthesis and energy production genes dominated the greenhouse experiment, whereas metabolism biosynthesis and stress response genes were less abundant. Similar observations have previously been reported in sunflower (Rengel et al, 2012) among other species. In contrast, longer term drought treatments disproportionally induced genes involved in other biological processes, such as membrane biogenesis, redox mechanisms, cellular biosynthesis, and metabolism (Table IV; Supplemental Tables S2, and S3; Des Marais et al 2012).…”

“…Methods to emulate field-like conditions in the laboratory or greenhouse settings have been developed as an alternative to traditional soil water dry-downs (Harb et al, 2010); however, even factorial combinations of stressors (Suzuki et al, 2014) may fail to capture the complex interplay of environmental variables experienced in the field. Furthermore, while it is crucial to relate findings of field studies with those performed under controlled conditions, only a few studies have been published that compare physiological traits and gene expression data in drought treatments in both field and greenhouse conditions (but see Rengel et al, 2012;Marchand et al, 2013).…”

Genotypic Variability in Carbon Isotope Discrimination and Water Use Efficiency among Recombinant Inbred Lines of Sunflower (Helianthus annuus L.)

“…It can be analyzed that different scales of water deficit treatment had been proven different availability of water in pots and in the soil. The phenomenon of this result is related to the observation that initially noticed by Farquhar, Ehleringer, & Hubick (1989) and reported by several authors (Brendel et al, 2008;Marguerit, Brendel, Lebon, Van Leeuwen, & Ollat, 2012;Rengel et al, 2012;Tardieu & Tuberosa, 2010), accordingly CID variation in the patterns of water use will likely be dependent on whether adjacent plants within a community are competing for the same limiting resource. It can be argued that efficient use of a resource, such as water, may only be adaptive if plants exert some control over the rates of soil water extraction from the soil volume in which their roots are located.…”

Systems biology approaches to study the molecular effects of caloric restriction and polyphenols on aging processes

“…For instance, Montastier and collaborators have recently performed a multistage analysis using both single and multi-omics networks to show metabolic alterations occurring during weight change in response to CR (Montastier et al 2015). To do so, they first inferred a partial correlation network for each -omics level and then constructed multi-omics networks linking each pairs of data type using regularized canonical correlation analysis, which successfully infers a gene/phenotype network (Rengel et al 2012). They then merged single and multiomics networks together and performed module detection analyses.…”