Integrative systems biology: an attempt to describe a simple weed

doi:10.1016/j.pbi.2012.01.004

Current Opinion in Plant Biology

Volume 15, Issue 2, April 2012, Pages 162-167

https://doi.org/10.1016/j.pbi.2012.01.004 Get rights and content

Genome-scale studies hold great promise for revealing novel plant biology. Because of the complexity of these techniques, numerous considerations need to be made before embarking on a study. Here we focus on the Arabidopsis model system because of the wealth of available genome-scale data. Many approaches are available that provide genome-scale information regarding the state of a given organism (e.g. genomics, epigenomics, transcriptomics, proteomics, metabolomics interactomics, ionomics, phenomics, etc.). Integration of all of these types of data will be necessary for a comprehensive description of Arabidopsis. In this review we propose that ‘triangulation’ among transcriptomics, proteomics and metabolomics is a meaningful approach for beginning this integrative analysis and uncovering a systems level perspective of Arabidopsis biology.

Highlights

► Genome-scale studies are now regularly performed in Arabidopsis thaliana. ► Transcriptomics, proteomics and metabolomics provide a wealth of descriptive information. ► Integration of all genome-scale datasets will enable a systems-level understanding of Arabidopsis.

Introduction

The completion of the Arabidopsis genome sequence facilitated extraordinary progress toward understanding plant biology. In particular, complete genomic sequence data drove the development of genome-wide transcriptional approaches, such as microarrays. Genome-scale studies (hereafter -omics) include, but are not limited to, analysis of RNAs, proteins, and metabolites. Significant progress has been made annotating and determining the function of many Arabidopsis genes. However, a plant is not just the sum of its genes, but a complex system where gene product interactions result in emergent properties. Therefore, with the ultimate intention of studying the biology of the whole organism, it is important to frame the next long-term goals for plant scientists.

We propose that a key long-term goal is the integration of different genome-scale approaches. The first steps in this direction have already occurred although the tools for the integration, visualization, and modeling of -omics data are still at a relatively early stage [1•, 2]. In this review, we focus on gene expression, protein and metabolite profiling data, briefly introducing each of the individual approaches, and then highlighting recent efforts to integrate these -omics (Figure 1).

Section snippets

Omics technology development: transcriptomics, proteomics and metabolomics

Transcriptomics: The completion of the Arabidopsis genome sequence has facilitated whole genome transcriptomic (gene expression) studies. The development of microarray technology enabled the simultaneous examination of thousands of genes; thus providing a comprehensive view of gene activity. Microarray gene expression data now cover organs, tissues, cell-types and developmental events, as well as responses to a variety of environmental perturbations [3, 4, 5, 6••, 7, 8]. For profiling

Data integration from molecular information: the gene–protein–metabolite relationship

Transcriptomics–proteomics: As gene expression profiling and proteomic methods improve, data can be combined to achieve a better understanding of Arabidopsis as a system. One important aspect of future investigation will involve the identification of variably spliced transcripts and the discrete proteins they encode. Before next generation sequencing analysis, estimates of alternatively spliced genes based on EST analysis ranged from 22 to 30% [44, 45, 46, 47]. More recent information using

Conclusion and future prospectives

As the studies that are highlighted here demonstrate, the integration of multiple genomic-scale studies can reveal novel biology. A comprehensive systems-level understanding of Arabidopsis will require -omics methods to be integrated and combined [80, 81]. In the near future, each of these -omics approaches will be used in an integrative fashion to inform and validate the findings of other genome-scale projects. Proteomics has been used to predict metabolic activity in the roots and shoots of

Conflict of interests

The authors declare that they have no competing interests.

References and recommended reading

Papers of particular interest, published within the period of review, have been highlighted as:

• of special interest
•• of outstanding interest

Acknowledgments

We are grateful to the members of the Benfey lab for helpful comments. Work in our lab on this area is funded by grants from the NIH (R01 GM-43778 and P50-GM081883) and the NSF (IOS-1021619). LML is funded by a fellowship from the Jane Coffin Childs Fund for Medical Research.

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¹: These authors contributed equally to this work.

View full text

Integrative systems biology: an attempt to describe a simple weed

Highlights

Introduction

Section snippets

Omics technology development: transcriptomics, proteomics and metabolomics

Data integration from molecular information: the gene–protein–metabolite relationship

Conclusion and future prospectives

Conflict of interests

References and recommended reading

Acknowledgments

Nat Genet

Nat Rev Genet

Science

Proteomics

J Proteomics

Plant Metabol

Nat Protoc

Plant Physiol

Proteomics

J Proteomics

Plant Cell

Plant J

Trends Plant Sci

Plant Physiol

Web-queryable large-scale data sets for hypothesis generation in plant biology

Plant Cell

A systems view of responses to nutritional cues in Arabidopsis: toward a paradigm shift for predictive network modeling

Plant Physiol

A gene expression map of the Arabidopsis root

Science

A high-resolution root spatiotemporal map reveals dominant expression patterns

Science

Cell identity mediates the response of Arabidopsis roots to abiotic stress

Science

Cell identity regulators link development and stress responses in the Arabidopsis root

Dev Cell

Gene expression map of the Arabidopsis shoot apical meristem stem cell niche

Proc Natl Acad Sci USA

Finding the fifth base: genome-wide sequencing of cytosine methylation

Genome Res

Applications of next-generation sequencing technologies in functional genomics

Genomics

Sampling the Arabidopsis transcriptome with massively parallel pyrosequencing

Plant Physiol

SNP discovery via 454 transcriptome sequencing

Plant J

Genome-wide mapping of alternative splicing in Arabidopsis thaliana

Genome Res

Highly integrated single-base resolution maps of the epigenome in Arabidopsis

Cell

High-resolution experimental and computational profiling of tissue-specific known and novel miRNAs in Arabidopsis

Genome Res

Comprehensive proteomics

Curr Opin Biotechnol

The Arabidopsis thaliana 2-D gel mitochondrial proteome: refining the value of reference maps for assessing protein abundance, contaminants and post-translational modifications

Proteomics

Plant proteomics update (2007–2008): second-generation proteomic techniques, an appropriate experimental design, and data analysis to fulfill MIAPE standards, increase plant proteome coverage and expand biological knowledge

J Proteomics

Mass spectrometry-based proteomics

Nature

Generating and navigating proteome maps using mass spectrometry

Nat Rev Mol Cell Biol

Analysis of shotgun proteomics and RNA profiling data from Arabidopsis thaliana chloroplasts

J Proteome Res

Proteome of plant peroxisomes: new perspectives on the role of these organelles in cell biology

Proteomics

Arabidopsis thaliana as a model organism for plant proteome research

J Proteomics

Evidence for network evolution in an Arabidopsis interactome map

Science

Independently evolved virulence effectors converge onto hubs in a plant immune system network

Science

Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry

Nat Protoc

Recent applications of NMR spectroscopy in plant metabolomics

FEBS J

Mass spectrometry-based metabolomics

Mass Spectrom Rev