Article
Plant gene expression in the age of systems biology: integrating transcriptional and post-transcriptional events.
Department of Biological Sciences, State University of New York at Albany, 1400 Washington Ave, Albany, NY 12222, USA.
Trends in Plant Science (impact factor:
11.05).
08/2005;
10(7):347-53.
DOI:10.1016/j.tplants.2005.05.004
pp.347-53
Source: PubMed
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Citations (0)
- Cited In (7)
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Chapter: Systems Biology: a promising tool to study abiotic stress responses
01/2011: pages 163-172; , ISBN: 9781608050581 -
Article: Target genes of the MADS transcription factor SEPALLATA3: integration of developmental and hormonal pathways in the Arabidopsis flower.
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ABSTRACT: The molecular mechanisms by which floral homeotic genes act as major developmental switches to specify the identity of floral organs are still largely unknown. Floral homeotic genes encode transcription factors of the MADS-box family, which are supposed to assemble in a combinatorial fashion into organ-specific multimeric protein complexes. Major mediators of protein interactions are MADS-domain proteins of the SEPALLATA subfamily, which play a crucial role in the development of all types of floral organs. In order to characterize the roles of the SEPALLATA3 transcription factor complexes at the molecular level, we analyzed genome-wide the direct targets of SEPALLATA3. We used chromatin immunoprecipitation followed by ultrahigh-throughput sequencing or hybridization to whole-genome tiling arrays to obtain genome-wide DNA-binding patterns of SEPALLATA3. The results demonstrate that SEPALLATA3 binds to thousands of sites in the genome. Most potential target sites that were strongly bound in wild-type inflorescences are also bound in the floral homeotic agamous mutant, which displays only the perianth organs, sepals, and petals. Characterization of the target genes shows that SEPALLATA3 integrates and modulates different growth-related and hormonal pathways in a combinatorial fashion with other MADS-box proteins and possibly with non-MADS transcription factors. In particular, the results suggest multiple links between SEPALLATA3 and auxin signaling pathways. Our gene expression analyses link the genomic binding site data with the phenotype of plants expressing a dominant repressor version of SEPALLATA3, suggesting that it modulates auxin response to facilitate floral organ outgrowth and morphogenesis. Furthermore, the binding of the SEPALLATA3 protein to cis-regulatory elements of other MADS-box genes and expression analyses reveal that this protein is a key component in the regulatory transcriptional network underlying the formation of floral organs.PLoS Biology 05/2009; 7(4):e1000090. · 11.45 Impact Factor -
Chapter: Systems Biology: A Promising Tool to Study Abiotic Stress Responses
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ABSTRACT: Plant abiotic stress responses are a major yield-limiting factor in agriculture and thereby in the production of food, feed and fibre. Recent technology developments allow studies of such stress responses at a global molecular scale using omics data (metabolome, proteome, transcriptome and more). Significant progress has been made in statistical, mathematical and informatics driven analysis of omics data. Genes, proteins and metabolites can now be classified, categorized and linked at a genomic scale, and network-based analysis of various biological processes is becoming reality. However, in order to gain a complete overview of all processes and active networks in each cell type of the plant at all developmental stages and under all types of environmental variation, data production needs to become feasible at a significantly more massive scale. Systems biology studies the organization of system components and their networks, with the idea that unique properties of a system can only be observed through study of the system as a whole. A system-based analysis can involve multiple scales, ranging from single cells, tissues, organs to whole organisms. One of the foundations of systems biology is the analysis of networks of interacting and interdependent components that produce the system's unique properties. Network analysis provides intuitive ways for omics data visualization, as it reduces the intrinsic complexity of such data. In this chapter we discuss systems biology as a promising tool to study plant stress responses. We list various network and visualization tools available to biologists, to help them analyse high throughput omics data sets. OMICS AND DATA INTEGRATION The success of technology development able to study the diversity and quantities of molecules at a genomic scale has resulted in a wide proliferation of terms ending with the suffix –ome, referring to a comprehensive number of observations of a certain type of data. The availability of entirely sequenced genomes (which can be used to predict genes, mRNAs and proteins) has subsequently spawned technology development to enable proteomics ("all" proteins), transcriptomics ("all" transcripts), interactomics ("all" interactions between biomolecules) and metabolomics ("all" metabolites). The term subsequently was introduced to cover other data types like phenomics (all the phenotypes related to gene mutants) or bibliomics (the study of complete literature on a biological topic), just to name a few. Omics technologies strive for completeness in high throughput mode, producing vast amounts of data. The advent of high throughput techniques and high throughput sequencing and analysis methods has improved our understanding of the structure and function of many components participating at the cellular level. It will soon be possible to get a whole eukaryotic plant genome of moderate size (<1 Gb) sequenced for less than one thousand Euros [1]. Developments in techniques like mass spectrometry, microarrays, NMR, and next generation sequencing technologies have helped in discovering new proteins and transcripts and have resulted in generatation of copious amounts of data. These data can be in the form of large amounts of numbers reflecting colour intensity readings in microarrays, or character strings reflecting formatted or unformatted text describing biological annotations, their functional annotations or experimental observations. It is difficult for a biologist to make sense of all these data and relate them to a particular component or interaction. This situation has created a great need for data integration and management [2] (Fig. 1). WHY SYSTEMS BIOLOGY?01/2011: pages 163-172; , ISBN: 978-1-60805-058-1
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Keywords
'virtual plant'
accomplishing
conserved
coupling
different kingdoms
eukaryotic gene expression
extensive mechanistic
fundamental principle
general mRNA biogenesis reactions
inner workings
mRNA biogenesis
plant 'mRNA factory'
plant-specific functions
plants
