A Gene Regulatory Network Subcircuit Drives a Dynamic Pattern of Gene Expression

Division of Biology, 156-29, California Institute of Technology, Pasadena, CA 91125, USA.
Science (Impact Factor: 33.61). 12/2007; 318(5851):794-7. DOI: 10.1126/science.1146524
Source: PubMed


Early specification of endomesodermal territories in the sea urchin embryo depends on a moving torus of regulatory gene expression. We show how this dynamic patterning function is encoded in a gene regulatory network (GRN) subcircuit that includes the otx, wnt8, and blimp1 genes, the cis-regulatory control systems of which have all been experimentally defined. A cis-regulatory reconstruction experiment revealed that blimp1 autorepression accounts for progressive extinction of expression in the center of the torus, whereas its outward expansion follows reception of the Wnt8 ligand by adjacent cells. GRN circuitry thus controls not only static spatial assignment in development but also dynamic regulatory patterning.

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    • "This poor correlation is due in part to the following reasons. First, the regulatory mechanism of gene expression is much more complex than initially expected678. The genes are interacting with each other and regulated by a range of epigenetic alterations91011121314, suggesting the need to examine a panel of genes at the same time. "
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    ABSTRACT: Despite the recent advance of single-cell gene expression analyses, co-measurement of both genomic and transcriptional signatures at the single-cell level has not been realized. However such analysis is necessary in order to accurately delineate how genetic information is transcribed, expressed, and regulated to give rise to an enormously diverse range of cell phenotypes. Here we report on a microfluidics-facilitated approach that allows for controlled separation of cytoplasmic and nuclear contents of a single cell followed by on-chip amplification of genomic DNA and cytoplasmic mRNA. When coupled with off-chip polymerase chain reaction, gel electrophoresis and Sanger sequencing, a panel of genes and transcripts from the same single cell can be co-detected and sequenced. This platform is potentially an enabling tool to permit multiple genomic measurements performed on the same single cells and opens new opportunities to tackle a range of fundamental biology questions including non-genetic cell-to-cell variability, epigenetic regulation, and stem cell fate control. It also helps address clinical challenges such as diagnosing intra-tumor heterogeneity and dissecting complex cellular immune responses.
    Scientific Reports 09/2014; 4:6485. DOI:10.1038/srep06485 · 5.58 Impact Factor
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    • "Lastly, we identified two wnt genes in this subset (ID:115036; ID: 195613), both similar to wnt8 in other organisms. Wnt8 is among the earliest zygotically-expressed regulatory factor in the sea urchin, where it is responsible for patterning along the animal-vegetal axis [22,23]. Wnt8b expression in humans and mice is restricted to early brain development [24], and in the spider Achaearanea tepidariorum, wnt8 knockdowns affect expression of hairy, among others transcripts, and decrease formation of posterior body regions [25]. "
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    ABSTRACT: Background Nematostella vectensis, a burrowing sea anemone, has become a popular species for the study of cnidarian development. In previous studies, the expression of a variety of genes has been characterized during N. vectensis development with in situ mRNA hybridization. This has provided detailed spatial resolution and a qualitative perspective on changes in expression. However, little is known about broad transcriptome-level patterns of gene expression through time. Here we examine the expression of N. vectensis genes through the course of development with quantitative RNA-seq. We provide an overview of changes in the transcriptome through development, and examine the maternal to zygotic transition, which has been difficult to investigate with other tools. Results We measured transcript abundance in N. vectensis with RNA-seq at six time points in development: zygote (2 hours post fertilization (HPF)), early blastula (7 HPF), mid-blastula (12 HPF), gastrula (24 HPF), planula (5 days post fertilization (DPF)) and young polyp (10 DPF). The major wave of zygotic expression appears between 7–12 HPF, though some changes occur between 2–7 HPF. The most dynamic changes in transcript abundance occur between the late blastula and early gastrula stages. More transcripts are upregulated between the gastrula and planula than downregulated, and a comparatively lower number of transcripts significantly change between planula and polyp. Within the maternal to zygotic transition, we identified a subset of maternal factors that decrease early in development, and likely play a role in suppressing zygotic gene expression. Among the first genes to be expressed zygotically are genes whose proteins may be involved in the degradation of maternal RNA. Conclusions The approach presented here is highly complementary to prior studies on spatial patterns of gene expression, as it provides a quantitative perspective on a broad set of genes through time but lacks spatial resolution. In addition to addressing the problems identified above, our work provides an annotated matrix that other investigators can use to examine genes and developmental events that we do not examine in detail here.
    BMC Genomics 04/2013; 14(1):266. DOI:10.1186/1471-2164-14-266 · 3.99 Impact Factor
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    • "Wnt8 can infect the adjacent cells/territories with this circular bioinformation flow via diffusion. This flow is terminated due to blimp1 autorepression [8]. In the early development of the Drosophila embryo, Snail repressor activates the synthesis of Delta ligand in the ventral mesoderm via repressing the transcription of Tom, an inhibitor of the Delta, which is called a double-negative gate. "
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    ABSTRACT: Gene regulatory network (GRN) construction is a central task of systems biology. Integration of different data sources to infer and construct GRNs is an important consideration for the success of this effort. In this paper, we will discuss distinctive strategies of data integration for GRN construction. Basically, the process of integration of different data sources is divided into two phases: the first phase is collection of the required data and the second phase is data processing with advanced algorithms to infer the GRNs. In this paper these two phases are called "structural integration" and "analytic integration," respectively. Compared with the nonintegration strategies, the integration strategies perform quite well and have better agreement with the experimental evidence.
    The Scientific World Journal 12/2012; 2012(13):435257. DOI:10.1100/2012/435257 · 1.73 Impact Factor
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