Plant proteomics: from genome sequencing to proteome databases and repositories

Proteomics and plant biology: contributions to date and a look towards the next decade

INTRODUCTION

This review presents the view of the author, that is opinionable and even speculative, on the field of proteomics, its application to plant biology knowledge, and translation to biotechnology. Written in a more academic than scientific style, it is based on past original and review articles by the author´s group, and those published by leading scientists in the last two years.

AREAS COVERED

Starting with a general definition and references to historical milestones, it covers sections devoted to the different platforms employed, the plant biology discourse in the protein language, challenges and future prospects, ending with the author opinion.

EXPERT OPINION

In 25 years, five proteomics platform generations have appeared. We are now moving from proteomics to Systems Biology. While feasible with model organisms, proteomics of orphan species remains challenging. Proteomics, even in its simplest approach, sheds light on plant biological processes, central dogma, and molecular bases of phenotypes of interest, and it can be translated to areas such as food traceability and allergen detection. Proteomics should be validated and optimized to each experimental system, objectives, and hypothesis. It has limitations, artifacts, and biases. We should not blindly accept proteomics data and just create a list of proteins, networks, and avoid speculative biological interpretations. From the hundred to thousand proteins identified and quantified, it is important to obtain a focus and validate some of them, otherwise it is merely. We are starting to have the protein pieces, so let, from now, build the proteomics and biological puzzle.

PhytoTypeDB: a database of plant protein inter-cultivar variability and function

Despite a fast-growing number of available plant genomes, available computational resources are poorly integrated and provide only limited access to the underlying data. Most existing databases focus on DNA/RNA data or specific gene families, with less emphasis on protein structure, function and variability. In particular, despite the economic importance of many plant accessions, there are no straightforward ways to retrieve or visualize information on their differences. To fill this gap, we developed PhytoTypeDB (http://phytotypedb.bio.unipd.it/), a scalable database containing plant protein annotations and genetic variants from resequencing of different accessions. The database content is generated by an integrated pipeline, exploiting state-of-the-art methods for protein characterization requiring only the proteome reference sequence and variant calling files. Protein names for unknown proteins are inferred by homology for over 95% of the entries. Single-nucleotide variants are visualized along with protein annotation in a user-friendly web interface. The server offers an effective querying system, which allows to compare variability among different species and accessions, to generate custom data sets based on shared functional features or to perform sequence searches. A documented set of exposed RESTful endpoints make the data accessible programmatically by third-party clients.

A year (2014-2015) of plants in Proteomics journal. Progress in wet and dry methodologies, moving from protein catalogs, and the view of classic plant biochemists

The present review is an update of the previous one published in Proteomics 2015 Reviews special issue [Jorrin-Novo, J. V. et al., Proteomics 2015, 15, 1089-1112] covering the July 2014-2015 period. It has been written on the bases of the publications that appeared in Proteomics journal during that period and the most relevant ones that have been published in other high-impact journals. Methodological advances and the contribution of the field to the knowledge of plant biology processes and its translation to agroforestry and environmental sectors will be discussed. This review has been organized in four blocks, with a starting general introduction (literature survey) followed by sections focusing on the methodology (in vitro, in vivo, wet, and dry), proteomics integration with other approaches (systems biology and proteogenomics), biological information, and knowledge (cell communication, receptors, and signaling), ending with a brief mention of some other biological and translational topics to which proteomics has made some contribution.

Big Data in Plant Science: Resources and Data Mining Tools for Plant Genomics and Proteomics

In modern plant biology, progress is increasingly defined by the scientists' ability to gather and analyze data sets of high volume and complexity, otherwise known as "big data". Arguably, the largest increase in the volume of plant data sets over the last decade is a consequence of the application of the next-generation sequencing and mass-spectrometry technologies to the study of experimental model and crop plants. The increase in quantity and complexity of biological data brings challenges, mostly associated with data acquisition, processing, and sharing within the scientific community. Nonetheless, big data in plant science create unique opportunities in advancing our understanding of complex biological processes at a level of accuracy without precedence, and establish a base for the plant systems biology. In this chapter, we summarize the major drivers of big data in plant science and big data initiatives in life sciences with a focus on the scope and impact of iPlant, a representative cyberinfrastructure platform for plant science.