Genetics, Genomics and Metabolomics

Abstract

Metabolomics approaches enable the parallel assessment of the levels of a broad range of metabolites. They have been documented to have great value in phenotyping and diagnostic analyses in plants as well as showing great promise as a tool for bio-prospecting novel pharmaceuticals. These tools have recently been turned to evaluation of the natural variance apparent in metabolite composition both in the model species Arabidopsis thaliana and a range of crop species. Here, we describe exciting progress made in the identification of the genetic determinants of plant chemical composition, focusing on the application of various different metabolomics strategies. We focus on the integration of these data with those other high-throughput technologies and discuss the value of such approaches for gaining fundamental insights into metabolic and even cellular regulation. Finally, we discuss the fact that when considered from an applied perspective metabolomics represents an important addition to the tools currently employed in genomicsassisted selection for crop improvement.

Plant Metabolomics in a Nutshell: Potential and Future Challenges

“…In contrast to the other '-omics' approaches, which are focused on DNA sequencing (genomics), gene expression analysis (transcriptomics) and proteins (proteomics), the major challenge for complementary, untargeted metabolomics approaches is related to the huge diversity of molecules present, their different physico-chemical properties and their dynamic range (Makkar et al, 2007;Cevallos-Cevallos et al, 2009;Fernie & Keurentjes, 2011). This chemical complexity within just the smaller molecules, involving both the basic structures as well as their different combinations of functional groups such as hydroxyls, carboxyls, amines, etc.…”

“…This chemical complexity within just the smaller molecules, involving both the basic structures as well as their different combinations of functional groups such as hydroxyls, carboxyls, amines, etc. has been well documented (Saito et al, 2006;Fernie & Keurentjes, 2011). This complexity is also both the primary reason for our desire to develop metabolomics approaches in the first place, as well as being the primary reason why we shall unlikely ever succeed in obtaining a truly holistic overview of the complete metabolite profile of a plant (Hall, 2006).…”

“…LC-MS in positive/negative modes; GC-MS of both natural volatiles and non volatiles, NMR, etc. ), which we may also later wish to combine with complementary genetic/genomic information (such as QTL or SNP data) or even macro-phenotypic information, the whole area of data integration or data fusion is developing rapidly (Fernie & Keurentjes, 2011;Moing et al, 2011;Tikunov et al, 2010). Through these data fusion approaches, we are gradually gaining a better ability to link differences at the molecular level to those at the level of the phenotype.…”

“…These changes can be of great importance but in a phenotypically, non-visible way. Random mutation approaches often involve genes of no predicted function and hence, a complementary, non-targeted metabolite screening approach is a very suitable starting point for pinning gene function to an enzymatic or structural role in the molecular organization of a cell (Hall, 2006;Fernie & Keurentjes, 2011).…”

“…The link between genotype and (metabolic) phenotype is also an area of growing interest and while Arabidopsis has here, once again a starring role (Keurentjes et al, 2006;Keurentjes, 2009), other species such as tomato and melon are also proving interesting experimental subjects (Biais et al, 2009;Fernie & Keurentjes, 2011;Moing et al, 2011), particularly regarding fleshy fruit tissues that Arabidopsis cannot cover . Now that the genome of Arabidopsis has been drafted, widespread use of natural variants (e.g.…”