Advances in Plant Proteomics toward Improvement of Crop Productivity and Stress Resistance

Abstract

Challenges in the plant breeding programs for crop improvement must be increasingly focused on genomic sequences of model crops. Presently attention has been focused on linking genomic and transcriptomic data to the spatial and temporal expression, biological function, and functional network of proteins. Understanding the complex and dynamic plant proteomes is crucial to target and identify proteins and their modification that may contribute to crop improvement. In agriculture, crops are subjected to abiotic and biotic stress. The occurrence of multiple stresses affecting crop growth, yield, and physiological traits can cause plants to activate intricate metabolic pathways involved in specific programming of gene expression. In response to stress, plants activate specific cellular programs that result in the accumulation of protective proteins based on metabolism and development. To achieve this, plants experience dramatic changes in their gene expression programs. The modulation of gene expression is operated by several families of transcription factors (TFs) and by signal-sensing networks of phosphorylation/dephosphorylation events and other post-transitional modifications (PTMs) that can stabilize TFs or target them for degradation. Quantitative protein profiles, profiles of regulatory modifications, and protein interaction networks have been widely used for crop proteome analysis. Proteomic programs contribute to the analysis of advanced mapping populations such as hybrid doubled haploid lines, near-isogenic lines, and recombinant inbred lines, which further verify the correlations between responsive quantitative trait loci and stress-tolerant phenotypes. Utilization of large proteomic data for crop improvement is a challenging task, but interdisciplinary approaches with robust bioinformatics tools will enable the development of crops with increased productivity.

Topics & Concepts