Metabolomics, metabolic diversity and genetic variation in crops

Abstract

The metabolome represents a critical aspect of a plant's physiology, growth characteristics and, ultimately, economic value. Metabolic changes underpin plant development and responses to applied stresses, whilst quality traits in many important crops and ornamental plants are dependent on metabolic composition. It is also frequently reasoned that metabolic information reflects biological endpoints more accurately than transcript or protein analysis. As such, the science of metabolomics has proven to be of increasing popularity in assessing genotypic and phenotypic diversity in plants, in defining biochemical changes associated with developmental changes during plant growth and, increasingly, in compositional comparisons. The postulated value of this metabolic information resides primarily in its potential to support breeding and selection of novel yield-enhanced and nutritionally improved crops. Plants display remarkable genetic plasticity which has served to facilitate the development of an extraordinary range of genetically distinct and metabolically diverse cultivars for any given plant species. Despite concerns regarding potential loss of genetic diversity through domestication, genetic resources still exist through wild and exotic germplasms. Additionally, emerging biotechnological approaches such as RNAi silencing and the transgenic modification of regulatory genes offer new and fascinating opportunities for enhancing diversity and eliciting trait improvements. This review is intended to promote the view that metabolomics, through comparative assessments of metabolic diversity in domesticated and non-domesticated plants, and through evaluations of the compositional impact of metabolic engineering efforts can support breeding programmes designed to elicit trait improvements.

A metabolite profiling approach to follow the sprouting process of mung beans (Vigna radiata)

“…Understanding these metabolic interactions is a major goal in systems biology (Saito and Matsuda 2010) and is suggested to assist in the elucidation of plant functional genomics (Fiehn et al 2000). Metabolite profiling is also considered to provide valuable data for breeding-driven metabolic engineering of nutritionally important metabolites in crops (Hall et al 2008) and thus as a tool to improve their agronomic and nutritional characteristics (Dixon et al 2006;Harrigan et al 2007). …”

Metabolômica: Definições, Estado-Da-Arte E Aplicações Representativas

“…232 Em uma busca rápida nas bases de dados de periódicos é possível encontrar nos últimos dezessete anos mais de 100 artigos de revisão na área, em diversas aplicações. [233][234][235][236][237][238][239] Dentre estas revisões, destacam-se algumas com enfoque em estudos de alterações ambientais 71,77 e genéticas, [240][241][242] resposta ao estresse, [243][244][245] saúde e tratamento de doenças, [246][247][248] ecologia e evolução, 63,76 agricultura, 249,250 bem como trabalhos dedicados à metabolômica com uso de compostos isotópicos, 251,252 que auxiliam na elucidação de rotas e melhoram a identificação e quantificação de metabólitos. Também são frequentemente encontrados estudos envolvendo mais de uma abordagem ômica, como proteômica e transcriptômica.…”

Metabolomics for measuring phytochemicals, and assessing human and animal responses to phytochemicals, in food science

“…Phenotypic diversity within a species is required for successful plant breeding [22] and consequently, plant breeders are concerned with both maintaining diversity within germplasm collections used for breeding, and ensuring that a desired trait is sufficiently heritable, before attempting to breed for it. Furthermore, the genetic and metabolite diversity found between domesticated and wild relatives provides resources for breeders to introduce new traits into commercial cultivars [23]. The phenotype of an individual genotype is related to its metabolome.…”

“…As suggested by Giovannoni [32] and Harrigan et al [23], the application of metabolomic approaches to measure metabolite diversity will lead to a better understanding of the biology underpinning important plant foodquality traits. However, combining genetic information (genetic maps) with metabolite data sets appears to hold even more promise, especially when the target traits are complex and vary in a quantitative manner as defined by quantitative trait loci (QTL) [33].…”