Comparative analysis based on transcriptomics and metabolomics data reveal differences between emmer and durum wheat in response to nitrogen starvation

Abstract

Glutamate 28 2 Summary 29Mounting evidence indicates the key role of Nitrogen (N) on diverse processes in plant, including not 30 only yield but also development and defense. Using a combined transcriptomics and metabolomics 31 approach, we studied the response of seedlings to N starvation of two different tetraploid wheat 32 genotypes from the two main domesticated subspecies, emmer (Triticum turgidum ssp. dicoccum) 33 and durum wheat (Triticum turgidum ssp. durum). We found that durum wheat exhibits broader and 34 stronger response in comparison to emmer as evidenced by the analysis of the differential expression 35 pattern of both genes and metabolites and gene enrichment analysis. Emmer and durum wheat showed 36 major differences in the responses to N starvation for transcription factor families. While emmer 37 showed differential reduction in the levels of primary metabolites to N starvation, durum wheat 38 exhibited increased levels of most metabolites, including GABA as an indicator of metabolic 39 imbalance. The correlation-based networks including the differentially expressed genes and 40 metabolites revealed tighter regulation of metabolism in durum wheat in comparison to emmer, as 41 evidenced by the larger number of significant correlations. We also found that glutamate and GABA 42 had highest values of centrality in the metabolic correlation network, suggesting their critical role in 43 the genotype-specific response to N starvation of emmer and durum wheat, respectively. Moreover, 44 this finding indicates that there might be contrasting strategies associated to GABA and Glutamate 45 signaling modulating shoot vs root growth in the two different wheat subspecies. 47Availability and uptake of nitrogen (N) is considered a major driver of growth (Lea and Azevedo, 48 2006). Indeed, N is an essential nutrient for all organisms, including plants, and is required for the 49 biosynthesis of macromolecules, such as proteins, nucleic acids, and chlorophyll, and for the synthesis 50 of many secondary metabolites with different roles in adaptation and signaling (Miller et al., 2007). 51As a result, N deficiency (limited availability) and starvation (complete absence) dramatically affects 52 plant growth and metabolism (Obata and Fernie, 2012). 53However, only 30-50% of supplied N is taken up by crops (Raun and Johnson, 1999), and the 54 remainder is lost by denitrification or leaching into terrestrial ecosystems, causing eutrophication and 55 contamination of drinking water (Cassman et al., 2003). Therefore, plant breeding efforts should be 56 combined with improvement of crop management towards a more efficient use of N also to limit the 57 use of fossil energy and environmental pollution (Ayadi et al., 2014; Ruisi et al., 2015). Towards this 58 key objective, it is necessary to understand how plants react and cope with low N availability and 59 identify the molecular basis of the natural genetic variation for adaptation to low N conditions. 60Understanding the molecular mechanisms underlying the variation ...

Network-based strategies in metabolomics data analysis and interpretation: from molecular networking to biological interpretation

“…Despite the familiarity of this representation of a metabolic network in the sense of metabolic pathways, networks are a much broader concept, useful for not only visualizing but also analyzing the global structure of any dataset that can be represented as nodes connected by a specific feature. Such data can be analyzed via several parameters in the field of graph theory and unravel mechanisms and structures beyond the direct interaction between neighboring nodes [1][2][3]. The combined analysis of several organisms including eukaryotes, bacteria and archea, for example, revealed a common feature of metabolism through its organization in a scale-free topology [4,5].…”