Systems Genetics of Environmental Response in the Mature Wheat Embryo

Abstract

Quantitative phenotypic traits are influenced by genetic and environmental variables as well as the interaction between the two. Underlying genetic · environment interaction is the influence that the surrounding environment exerts on gene expression. Perturbation of gene expression by environmental factors manifests itself in alterations to gene co-expression networks and ultimately in phenotypic plasticity. Comparative gene co-expression networks have been used to uncover biological mechanisms that differentiate tissues or other biological factors. In this study, we have extended consensus and differential Weighted Gene Co-Expression Network Analysis to compare the influence of different growing environments on gene co-expression in the mature wheat (Triticum aestivum) embryo. This network approach was combined with mapping of individual gene expression QTL to examine the genetic control of environmentally static and variable gene expression. The approach is useful for gene expression experiments containing multiple environments and allowed for the identification of specific gene co-expression modules responsive to environmental factors. This procedure identified conserved coregulation of gene expression between environments related to basic developmental and cellular functions, including protein localization and catabolism, vesicle composition/trafficking, Golgi transport, and polysaccharide metabolism among others. Environmentally unique modules were found to contain genes with predicted functions in responding to abiotic and biotic environmental variables. These findings represent the first report using consensus and differential Weighted Gene Coexpression Network Analysis to characterize the influence of environment on coordinated transcriptional regulation. Q UANTITATIVE phenotypic traits are governed by genetics, environment, and interactions between the two (G·E). The extent of G·E for a particular trait in part determines heritability and our understanding of the underlying biology. Transcriptional regulation of genes plays a large role in the response of an organism to the environment, and this modulation of gene expression is itself genetically controlled and subject to G·E interactions (Landry et al. 2006;Li et al. 2006;Smith and Kruglyak 2008). A number of studies have used broad transcriptional profiling in segregating or natural populations to identify genetic loci that control gene expression, commonly referred to as genetical genomics or gene expression QTL (eQTL) mapping (Jansen and Nap 2001;Brem et al. 2002;Schadt et al. 2003;Brem and Kruglyak 2005;Zhang et al. 2011). In plants a number of studies have been conducted on a range of species including Arabidopsis thaliana, barley (Hordeum vulgare), maize (Zea mays), poplar (Populus spp.), and wheat (Triticum aestivum) (Decook et al. 2006;Jordan et al. 2007;Keurentjes et al. 2007;West et al. 2007;Potokina et al. 2008;Drost et al. 2010;Druka et al. 2010;Holloway et al. 2011;Zhang et al. 2011). Using a genetical genomics approach, gene expr...

A systems genetics approach reveals environment-dependent associations between SNPs, protein co-expression and drought-related traits in maize

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Systems genetics reveals a transcriptional network associated with susceptibility in the maize–grey leaf spot pathosystem

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Closing the Divide between Human Nutrition and Plant Breeding

“…There is evidence that both genetic and environmental heterogeneity can effectively redistribute the relative contributions of QTL, meaning that there could be a suite of constitutive QTL among others that are more transient, that is, only occurring in certain populations or combinations of environmental conditions (Holland, 2007;Messmer et al, 2009;Vargas et al, 2006). In mature wheat embryos, environment-specific gene expression networks were found to exhibit functions in pathogen response, RNA processing, and heat response (Munkvold et al, 2013). Even in the consensus network of genes, mostly housekeeping, showing correlated expression in both environments tested, none of the identified eQTL co-localized across the two environments.…”