Metabolic fingerprinting of Arabidopsis thaliana accessions

Abstract

In the post-genomic era much effort has been put on the discovery of gene function using functional genomics. Despite the advances achieved by these technologies in the understanding of gene function at the genomic and proteomic level, there is still a big genotype-phenotype gap. Metabolic profiling has been used to analyze organisms that have already been characterized genetically. However, there is a small number of studies comparing the metabolic profile of different tissues of distinct accessions. Here, we report the detection of over 14,000 and 17,000 features in inflorescences and leaves, respectively, in two widely used Arabidopsis thaliana accessions. A predictive Random Forest Model was developed, which was able to reliably classify tissue type and accession of samples based on LC-MS profile. Thereby we demonstrate that the morphological differences among A. thaliana accessions are reflected also as distinct metabolic phenotypes within leaves and inflorescences.

An evolving computational platform for biological mass spectrometry: workflows, statistics and data mining with MASSyPup64

“…The results of affected metabolic pathways are congruent with the previously reported statistical analyses ( Sotelo-Silveira et al, 2015 ). But taking into account the Variable Importance for the classification of the inflorescence profiles according to their accession, now allows a statistically supported ranking of putatively involved pathways.…”

“…To gain biological knowledge, these features need to be identified and integrated into metabolic pathways. Recently we reported the metabolic fingerprinting of the Arabidopsis thaliana accessions (‘ecotypes’) Columbia (“Col-0”) and Wassilewskija (“Ws-3”), based on extracts of leaves and inflorescence ( Sotelo-Silveira et al, 2015 ). In this example, we re-process the reduced datasets of the inflorescence samples and try to identify possibly distinct pathways between the inflorescence samples of the two accessions.…”

Genomic history of the origin and domestication of common bean unveils its closest sister species

“…To establish a phenotypic discrimination of the species, other than morphological traits, we used high-throughput, non-targeted mass fingerprinting [40, 41]. Combining direct-injection electrospray mass spectrometry (DIESI-MS) and hierarchical cluster analysis (HCA), we constructed metabolic profiles of P. vulgaris , P. pseudovulgaris , and P. coccineus accessions from young trifoliate leaves (Fig.…”

Association analysis of phenotypic and metabolomic changes in Arabidopsis accessions and their F₁ hybrids affected by different photoperiod and sucrose supply

“…Metabolomic analysis can aid in the development of standardization methods for understanding natural variation and/or various environmental conditions regarding plant growth (Kusano et al 2007b;Meyer et al 2007;Sato and Yanagisawa 2014;Soltis and Kliebenstein 2015;Sotelo-Silveira et al 2015;Sulpice et al 2009;Tamura et al 2018). According to recent studies of plant metabolic processes, metabolic profiling has shown a close link between biomass accumulation and metabolites, as both negative and positive correlations (Meyer et al 2007;Sulpice et al 2009).…”

“…Most studies have focused on analyzing natural variation under limited growth conditions or on an accession under various growth conditions (Meyer et al 2007;Sato and Yanagisawa 2014;Seaton et al 2018;Sotelo-Silveira et al 2015;Weckwerth et al 2004). Therefore, expanding research to understand fully functional systems is required (Soltis and Kliebenstein 2015).…”