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Proteomes. 2018 Jun 3;6(2). pii: E27. doi: 10.3390/proteomes6020027.

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World.

Author information

1
Institute for Biomedical Technologies-National Research Council; F.lli Cervi 93, 20090 Segrate, Milan, Italy. dario.disilvestre@itb.cnr.it.
2
Institute for Biomedical Technologies-National Research Council; F.lli Cervi 93, 20090 Segrate, Milan, Italy. andrea.bergamaschi2@studenti.unipr.it.
3
Institute for Biomedical Technologies-National Research Council; F.lli Cervi 93, 20090 Segrate, Milan, Italy. edobellini92@gmail.com.
4
Institute for Biomedical Technologies-National Research Council; F.lli Cervi 93, 20090 Segrate, Milan, Italy. pierluigi.mauri@itb.cnr.it.

Abstract

The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.

KEYWORDS:

PPI; network; plants; proteomics; systems biology; topology

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