Drought Stress Research in Crops Using -Omics Approaches: mRNA Seq and Proteomics in the Spot Light

We apply different models to phenotype plant biodiversity in response to a changing environment and to get insight into tolerance mechanisms. The power of -omic methods tends to be lost in crops due to the lack of genomic information or the complexity of the genome. Though technologies evolve. We are developing methods to further improve the identification rate of both RNA-seq and quantitative label free proteomics. From a pioneering drought experiment on banana, we assess that mRNA-seq was able to visualize 18*10E6 reads belonging to 37577 different genes, with a dynamic range of ~5 orders of magnitude. The proteome analysis (QExactive/50cm-UPLC-column/6h-gradient) was able to quantify 150*10E3 peptides, with a dynamic range of ~6 orders of magnitude. The bottle neck for proteomics is the identification of the peptides and reconstruction into proteins. Due to low abundance, only 30% of the peptides was selected for MSMS with an identification rate of 16% (1891 different proteins). The expression of 1045 genes could be characterized by both RNA-seq and proteomics, 846 were unique for proteomics and 36532 for RNA-seq. Quantitatively, 342 proteins (18%) and 3638 mRNAs (10%) were considered as differential. Eleven were in common. Analysis of an unsequenced genotype relies on the presence of a reference genome, existing libraries and on de novo sequencing/assembly. There is only a small overlap between both methods, starting again the debate about correlations between mRNA and protein. We conclude that both methods are extremely useful to characterize the phenotype of different genotypes and map allelic variations.