ReviewProteomics of model and crop plant species: Status, current limitations and strategic advances for crop improvement☆
Graphical abstract
Introduction
Following the sequencing of the model plant species Arabidopsis thaliana [1], genomes of important crops including rice, potato, maize, tomato and soybean [2], [3], [4], [5], [6] as well as genomes of so-called orphan crops such as sorghum, millet and cassava [7], [8], [9] have been released into public databases [10]. Despite the currently limited annotation of most crop genomes, the availability of genome sequences now provides new opportunities to study crop traits and stress responses using rapidly expanding OMICS technologies. Although model plants have significantly advanced our understanding of plant responses to biotic and abiotic stresses [11], [12], molecular investigations of crop system responses to biotic and abiotic stress remain essential to understand specificity and phenotypic diversity.
During the last decade, microarray and subsequent next-generation sequencing (NGS) technologies (reviewed in [13], [14]) have been extensively used to characterize crop transcriptomes and to investigate their molecular responses to various stress conditions. In particular, NGS technologies that are now providing access to gene sequence diversity can be combined with expression profiles of sequenced and un-sequenced crop species [15]. However, gene expression data alone do not reveal the full complexity of molecular responses to perturbations. In addition to transcription control, translation of mRNA into proteins and protein modifications are important additional regulatory mechanisms that control the intensity and specificity of plant responses to perturbations. Molecular systems biology and bioinformatics studies of various organisms have revealed that transcript levels do not always correlate with protein quantity [16], [17], [18], [19]. Thus, protein accumulation cannot be readily inferred from transcript data. While transcript data can also provide insights into production of protein variants [20], [21], identification and quantitation of post-translational modifications (PTMs) of proteins are only possible using advanced proteomics approaches [22].
Translational proteomics is being considered a meaningful way of proteomics research with the main objective of delivering useful applications to address and possibly solve societal problems [23]. In the specific case of plants, translational proteomics intends to improve crop tolerance to biotic and abiotic stresses, to achieve yield stability in agricultural production, to advance sustainable development of plant-based bioenergy feedstocks, and to optimize food safety as well as food quality controls. In order to achieve these objectives, plant proteomics is shifting increasingly from model plants to crops.
Here we review our current knowledge of proteomes from the model plant Arabidopsis thaliana and the model crop Oryza sativa, in research topics relevant to crop improvement. Based on those achievements, we consider future developments and strategic advances that crop proteomics could take to generate novel insight useful for crop improvement.
Section snippets
Proteomics advances in model plants
The term “proteomics” was first used in the late 1990s [24]. Proteomics generates a comprehensive description of proteins in organisms and allows the characterization of protein level modulation and modifications in response to perturbations. Proteomics encompasses, among others, protein profiling, protein quantification, post-translation modifications as well as protein/protein interactions [25].
Initially, plant proteome analysis was largely a qualitative approach describing protein profiles
Translational plant proteomics towards crop improvement
Translational plant proteomics applies and extends knowledge gained from proteomics on both model and crop plants into practical applications benefiting society. Proteomics studies of model and crop plants have been extensively reviewed [23], [118], [119]. Recent developments in shotgun quantitative proteomics (see above) have substantially extended proteome coverage and protein quantitation data of several crop species. Such proteomics studies of crops have significant potential of translation
Crop proteomics: current limitations and strategic advances
Similar to current applications of proteomics in farm animals [135], e.g., to establish the neutraceutical properties of the milk proteome [136] or to monitor the in vivo performances of livestock animals [137], there is also increasing use of proteomics in crop plants to facilitate breeding or to understand the basis of increased yield in hybrids. With few exceptions, however, protein identification in most crop species at present cannot take advantage of fully sequenced genomes with high
Facilitating information from crop systems and natural diversity using proteomics
Arabidopsis continues to be useful for much of basic plant biology research [179] and currently has the highest plant proteome coverage [180], but it is not a suitable model for many aspects and traits specific to crops. Initiatives to promote tomato as a model for fruit development [181], potato for tuber formation [182], foxtail millet for C4 photosynthesis and bioenergy grasses [183], [184], alfalfa and soybean for nodulation [185], [186] will benefit from the deployment of proteomics
Conclusion
Proteomics has greatly advanced our understanding of proteome composition, modulation and modification in model plant systems, and crop research is now rapidly taking advantage of proteomics pipelines as well. While crop proteome data are needed for understanding traits and responses to biological perturbations that are specific to crop systems, good examples of how this information can be integrated into advanced breeding strategies are still few. This will change, however, with the increasing
Acknowledgement
We gratefully acknowledge the support of our work by ETH Zurich. E.L. is supported by the Brazilian Swiss Joint Research Programme (BSJRP) EUPHORIAWATT project and a fellowship from the PLANT FELLOWS programme. I.Z. is supported by a Sawiris scholarship.
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This article is part of a Special Issue entitled: Translational Plant Proteomics.