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. 2006 Nov;7(6):333-41.
doi: 10.2174/138920206778948718.

Understanding the dynamic behavior of genetic regulatory networks by functional decomposition

Affiliations

Understanding the dynamic behavior of genetic regulatory networks by functional decomposition

William Longabaugh et al. Curr Genomics. 2006 Nov.

Abstract

A number of mechanistic and predictive genetic regulatory networks (GRNs) comprising dozens of genes have already been characterized at the level of cis-regulatory interactions. Reconstructions of networks of 100's to 1000's of genes and their interactions are currently underway. Understanding the organizational and functional principles underlying these networks is probably the single greatest challenge facing genomics today. We review the current approaches to deciphering large-scale GRNs and discuss some of their limitations. We then propose a bottom-up approach in which large-scale GRNs are first organized in terms of functionally distinct GRN building blocks of one or a few genes. Biological processes may then be viewed as the outcome of functional interactions among these simple, well-characterized functional building blocks. We describe several putative GRN functional building blocks and show that they can be located within GRNs on the basis of their interaction topology and additional, simple and experimentally testable constraints.

Keywords: Genetic regulatory networks; systems biology; transcriptional regulation; visualization.

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Figures

Fig. (1)
Fig. (1)
Example of a large-scale genetic regulatory network (GRN) diagram viewed as a homogenous, automatically laid out graph of interacting genes and proteins. Zoomed in view of a portion of the network is shown in the inset. Lack of space, time and functional information makes the network diagram difficult to decipher.
Fig. (2)
Fig. (2)
The CRN regulating galactose uptake in yeast. The constitutively expressed transcription activator Gal4p binds to the promoters of GAL genes. In the absence of galactose, the represser Gal80p blocks the activation domain of Gal4p. In the presence of intracellular galactose. the signal transducer Gal3p is activated, which sequesters Gal80p in the cytoplasm, leading to transcription of the GAL genes. The signal transducer gal3 and the represser gal80 are basally expressed in non-induced, non-glucose-repressed conditions. Lines terminating in arrowheads denote positive regulation. Lines terminating in bars denote repression. Gene symbols denote transcription. For enzymatic interactions, the relevant enzymes arc indicated next to each line. The double ellipses denote Gal4p dimers. See main text for references.
Fig. (3)
Fig. (3)
The yeast galactose utilization network derived from high-throughput global assays. Shaded background boxes in the cytosol delineate the known metabolic pathways. Transcription factors in the nucleus are represented by diamonds (genes within the grey box are the regulatory genes in Fig. 2). All other proteins (circles) arc located according to their sub-cellular localizations (plasma membrane, cytosol and nucleus). Colors (not shown) can be used to indicate increase, decrease and no significant change in gene expression when the carbon source is changed from raffinose to galactose (see (12] for color). The three numbered squares shown at the right represent complexes. Numbers preceded with BM mark functionally clustered biomodules. Short black arrows indicate communication between the modules.
Fig. (4)
Fig. (4)
Some proposed GRN functional building blocks. See text for detailed descriptions.
Fig. (5)
Fig. (5)
Parameter values for which a pair of mutually repressing genes will act as a mutual exclusion switch (adapted from [48]). So long as the repressive interactions of the two genes are greater than first order, a large range of parameter values (between the two dotted boundaries marked) results in robust switch-like behavior. The example boundaries shown are calculated assuming a Hill-function for the repressive interactions. In this case, the Hill coefficient stands in for cooperative binding on DNA and/or cooperative complex formation prior to DNA binding. Boundaries for Hill coefficients of 2, 3 and 4 are shown. The larger the degree of cooperativity, the more robust the mutual exclusion switch (larger area enclosed by the dotted boundaries).
Fig. (6)
Fig. (6)
Occurrences of putative functional building blocks in the GRN underlying endomesoderm specification in the embryo of the sea urchin Strongylocentrotus purpuratus. Each occurrence is indicated by a rounded bounding box. Box colors identify different types of functional building blocks. Green: single-gene intra-cellular positive feedback latches. Orange: a multi-gene intra-cellular positive feedback latch. Dark blue: inter-cellular positive feedback latch (the community effect) mediated by Wnt8 signaling. Cyan: instances of negative auto-regulation. foxA expression is oscillatory (Oliver! P, Tu Q, Walton K, Davidson EH and McClay DR, manuscript in preparation). The expression patterns of the other auto-repressive genes are consistent with the ‘single pulse’ functional building block. Purple: signal mediated toggle switches mediated via β-catenin and TCF/LEF in Wnt signaling and Su(H) in Notch signaling. Red: the alx1-gcm mutual exclusion operator. Alx1 is on in the PMC domain and off in the mesoderm. Gcm is on in the mesoderm and off in the PMC. Yellow: the pmar1 gradient detection/analogue to digital switch. Pmar1 represses an uncharacterized repressor which in turn represses es, delta, nrs, alx1, tbr and ets1. Each short horizontal line from which a bent arrow extends to indicate transcription represents the cis-regulatory element that is responsible for expression of the gene named in the domain shown. The arrows and barred lines indicate the normal function of the gene (activation or repression) as deduced from changes in transcript levels in perturbation experiments. Red diamonds indicate that a cis-regulatory element, which controls relevant expression has been isolated. Green diamonds indicate reported experimental evidence validates expected target site. The rectangles in the lower tier of the diagram show downstream differentiation genes. Dashed lines indicate inferred or possibly indirect relationships. Arrows inserted in arrow tails indicate intercellular signaling interactions. Large open ovals represent cytoplasmic biochemical interactions at the protein level. Sec [4] for a detailed description.

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References

    1. Davidson EH, Erwin DH. Gene regulatory networks and the evolution of animal body plans. Science. 2006;311:796–800. - PubMed
    1. Li S, Armstrong CM, Bertin N, Ge H, Milstein S, Boxem M, Vidalain PO, Han JD, Chesneau A, Hao T, Goldberg DS, Li N, Martinez M, Rual JF, Lamesch P, Xu L, Tewari M, Wong SL, Zhang LV, Berriz GF, Jacotot L, Vaglio P, Reboul J, Hirozane–Kishikawa T, Li Q, Gabel HW, Elewa A, Baumgartner B, Rose DJ, Yu H, Bosak S, Sequerra R, Fraser A, Mango SE, Saxton WM, Strome S, Van Den Heuvel S, Piano F, Vandenhaute J, Sardet C, Gerstein M, Doucette-Stamm L, Gunsalus KC, Harper JW, Cusick ME, Roth FP, Hill DE, Vidal M. A map of the interactome network of the metazoan C. elegans. Science. 2004;303:540–3. - PMC - PubMed
    1. Deplancke B, Mukhopadhyay A, Ao W, Elewa AM, Grove CA, Martinez NJ, Sequerra R, Doucette-Stamm L, Reece-Hoyes JS, Hope IA, Tissenbaum HA, Mango SE, Walhout AJ. A gene-centered C. elegans protein-DNA interaction network. Cell. 2006;125:1193–205. - PubMed
    1. Davidson EH. The Regulatory Genome: Gene Regulatory Networks in Development and Evolution. Elsevier; 2006.
    1. Ihmels J, Bergmann S, Barkai N. Defining transcription modules using large-scale gene expression data. Bioinformatics. 2004;20:1993–2003. - PubMed

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