Gene Expression Networks

Abstract

‘Gene expression network’ is the term used to describe the interplay, simple or complex, between two or more gene products in performing a specific cellular function. Although the delineation of such networks is complicated by the existence of multiple and subtle types of interaction between gene products, the use of high‐throughput functional genomics techniques and mathematical modeling provides a powerful approach to deciphering expression networks and revealing the molecular mechanisms of cell growth and function.

Keywords: DNA arrays; functional genomics; gene expression networks; modifier genes; pleiotropy

Figure 1.

Schematic of the hedgehog‐wingless feedback loop that controls parasegment boundary formation in Drosophila embryos. Secreted Hedgehog protein Hh is produced by the Engrailed‐expressing En cells in the anterior compartment of each parasegment. Hedgehog protein signals across the future parasegment boundary to the posterior cells of the next parasegment, where it binds to patched receptors (Ptc), which are complexed to another transmembrane molecule, smoothened (Smo). This complex, which also acts to restrict the diffusion of Hedgehog, signals via a transcription factor Ci to activate the expression of wingless (wg) and patched. Wingless protein is secreted and signals, via its own receptor, Drosophilafrizzled2 (Frz) and signal transduction pathway, back to the original cell in the adjacent parasegment, where it maintains hedgehog expression. Thus hedgehog not only maintains its own expression via feedback through wingless (i), but also maintains the expression of its receptor, patched (ii), thus ensuring reception and limiting diffusion. (From Shimeld with permission.)

Figure 2.

‘Receptor conversion model’ of cytokine pleiotropy. In one instance, a cytokine acts on the cells (target cell A) that express a specific receptor. Alternatively, a complex composed of the cytokine and a soluble form of its receptor subunit can act on the cells (target cell B) that express only a receptor subunit and do not respond to the cytokine alone. In this way, the complex acts to provide an alternate target cell on which the original cytokine cannot act and thereby the complex exerts completely different biological actions. (From Hirano with permission.)

Figure 3.

‘Orchestrating model’ of cytokine pleiotropy, in which distinct cytoplasmic regions of a cytokine or growth factor receptor simultaneously generate contradictory signals. In this particular example, gp130‐induced growth signals can be dissected into at least two parts: one is required for G1 to S and S to G2/M cell cycle transitions, and the other required for antiapoptosis. gp130 stimulation induces macrophage differentiation and growth arrest in M1 cells. STAT3 (signal transducers and activators of transcription 3) activation is essential for such events. When STAT3 activation is suppressed, gp130 induces growth‐enhancing signals through the tyrosine residue required for mitogen‐activated protein kinase (MAPK) activation. gp130‐induced neurite outgrowth in PC12 cells is dependent on MAPK activation, while STAT3 activation is inhibitory. Tumor necrosis factor (TNF) induces apoptosis through the activation of the caspase cascade, while it induces antiapoptotic signals through activation of nuclear factor‐κB (NF‐κB). Arrow indicates a positive signal; dotted line indicates a negative signal. The resulting chaotic situation could be orchestrated by a conductor to effect a directed biological change according to the balance of the signals, thus bringing order from the chaos. SHP‐2: src homology 2‐containing tyrosine phosphatase; Grb2: an adaptor protein; Cdc25a: Cell division cycle gene 25A; c‐myb: Cellular homologue of retroviral oncogene v‐myb; c‐myc: Cellular homologue of retroviral oncogene v‐myc; FADD: Fas‐associated death domain; G1: Gap1 phase of cell cycle; G2/M: Gap2/Mitosis checkpoint of cell cycle; Gab: Grb2‐associated protein; gp130: Glycoprotein130; IkB: Inhibitor of NF‐kappaB; IKK: Inhibitor KappaB kinase; MAPK: mitogen‐activated protein kinase; NIK: NF‐kappaB‐inducing kinase; p21: (also known as Waf1 and Cip1), a cyclin‐dependent protein kinase inhibitory protein; p27: PI‐3K: phosphatidylinositol‐3 kinase; p19(INK4d): a cyclin‐dependent kinase inhibitor; S: Synthesis phase of cell cycle; SOS: Son of sevenless, a Ras/Rac guanine nucleotide exchange factor; TNFR1: Tumor necrosis factor receptor 1; TRADD: TNFR1‐associated death domain; TRAF2: TNF receptor‐associated factor 2. (From Hirano with permission.)

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Further Reading

Brown KD, Barlow C and Wynshaw‐Boris A (1999) Multiple ATM‐dependent pathways: an explanation for pleiotropy. American Journal of Human Genetics 64: 46–50.

D'Haeseleer P, Liang S and Somogyi R (2000) Genetic network inference: from co‐expression clustering to reverse engineering. Bioinformatics 16: 707–726.

Dipple KM and McCabe ER (2000) Modifier genes convert ‘simple’ Mendelian disorders to complex traits. Molecular Genetics and Metabolism 71: 43–50.

Houlston RS and Tomlinson IP (1998) Modifier genes in humans: strategies for identification. European Journal of Human Genetics 6: 80–88.

Huang S (1999) Gene expression profiling, genetic networks, and cellular states: an integrating concept for tumorigenesis and drug discovery. Journal of Molecular Medicine 77: 469–480.

Livesey FJ, Furukawa T, Steffen MA, Church GM and Cepko CL (2000) Microarray analysis of the transcriptional network controlled by the photoreceptor homeobox gene Crx. Current Biology 10: 301–310.

Sanchez‐Cuenca J, Martin JC, Pellicer A and Simon C (1999) Cytokine pleiotropy and redundancy – gp130 cytokines in human implantation. Immunology Today 20: 57–59.

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Smolen P, Baxter DA and Byrne JH (2000) Modeling transcriptional control in gene networks – methods, recent results, and future directions. Bulletin of Mathematical Biology 62: 247–292.

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Web Links

Gene Ontology Consortium (GO) The goal of the Gene Ontology Consortium is to produce a dynamic controlled vocabulary that can be applied to all organisms, even as knowledge of gene and protein roles in cells is accumulating and changing. The three organizing principles of the Gene Ontology Consortium are molecular function (the tasks performed by individual gene products; examples are transcription factor and DNA helicase), biological process (broad biological goals, such as mitosis or purine metabolism, that are accomplished by ordered assemblies of molecular functions) and cellular component (subcellular structures, locations, and macromolecular complexes; examples include nucleus, telomere, and origin recognition complex). The GO database provided such data on numerous genes from several model species. http://www.geneontology.org/

neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease)(NF1); LocusID: 4763. LocusLink: http://www.ncbi.nlm.nih.gov/LocusLink/LocRpt.cgi?l=4763

neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease)(NF1); MIM number: 162200. OMIM: http://www3.ncbi.nlm.nih.gov/htbin‐post/Omim/dispmim?162200

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Rockett, John C, and Dix, David J(Jul 2006) Gene Expression Networks. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1038/npg.els.0005280]