The Correlation of mRNA and protein abundance in the developing maize leaf-

mRNA abundance is often used as proxy for protein abundance. However, vastly different correlations between transcriptomes and proteomes have been observed. In this talk, I will address an optimized workflow for transcriptome and proteome correlation and apply this towards development of the maize leaf. We compared large scale quantitative proteome and transcriptomes collected at specific stages along the developmental maize leaf blade gradient. Proteome data were based on label-free shotgun proteomics (spectral counting) and transcript data were based on RNA-seq using the same source materials, and were previously published (Li et al. 2010, Majeran et al. 2010).Transcript and protein abundance followed near normal distributions. Protein observability correlated to transcript abundance following a ‘lazy step function’. mRNA and protein abundance showed significant positive correlations (upto 0.8) in dependence of function and development. Correlations were much weaker in the leaf ‘sink-source’ transition zone’, i.e. the zone with massive investments in leaf chloroplast biogenesis and build-up of photosynthetic capacity. Clustering analyses of gene-specific protein-mRNA ratios revealed coordinated shifts in control points in gene expression along the leaf blade developmental gradient. Specific examples are discussed in the context of C4 photosynthesis, leaf development and sink-source transitions. This is the first large scale mRNA-protein correlation analysis in plants (maize) using label-free spectral counting for protein quantification and RNA-seq for mRNA abundance.