10 research outputs found

    Sfrp3 modulates stromal-epithelial crosstalk during mammary gland development by regulating Wnt levels

    Get PDF
    Mammary stroma is essential for epithelial morphogenesis and development. Indeed, postnatal mammary gland (MG) development is controlled locally by the repetitive and bi-directional cross-talk between the epithelial and the stromal compartment. However, the signalling pathways involved in stromal–epithelial communication are not entirely understood. Here, we identify Sfrp3 as a mediator of the stromal–epithelial communication that is required for normal mouse MG development. Using Drosophila wing imaginal disc, we demonstrate that Sfrp3 functions as an extracellular transporter of Wnts that facilitates their diffusion, and thus, their levels in the boundaries of different compartments. Indeed, loss of Sfrp3 in mice leads to an increase of ductal invasion and branching mirroring an early pregnancy state. Finally, we observe that loss of Sfrp3 predisposes for invasive breast cancer. Altogether, our study shows that Sfrp3 controls MG morphogenesis by modulating the stromal-epithelial cross-talk during pubertal development

    Transcription factor site dependencies in human, mouse and rat genomes

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>It is known that transcription factors frequently act together to regulate gene expression in eukaryotes. In this paper we describe a computational analysis of transcription factor site dependencies in human, mouse and rat genomes.</p> <p>Results</p> <p>Our approach for quantifying tendencies of transcription factor binding sites to co-occur is based on a binding site scoring function which incorporates dependencies between positions, the use of information about the structural class of each transcription factor (major/minor groove binder), and also considered the possible implications of varying GC content of the sequences. Significant tendencies (dependencies) have been detected by non-parametric statistical methodology (permutation tests). Evaluation of obtained results has been performed in several ways: reports from literature (many of the significant dependencies between transcription factors have previously been confirmed experimentally); dependencies between transcription factors are not biased due to similarities in their DNA-binding sites; the number of dependent transcription factors that belong to the same functional and structural class is significantly higher than would be expected by chance; supporting evidence from GO clustering of targeting genes. Based on dependencies between two transcription factor binding sites (second-order dependencies), it is possible to construct higher-order dependencies (networks). Moreover results about transcription factor binding sites dependencies can be used for prediction of groups of dependent transcription factors on a given promoter sequence. Our results, as well as a scanning tool for predicting groups of dependent transcription factors binding sites are available on the Internet.</p> <p>Conclusion</p> <p>We show that the computational analysis of transcription factor site dependencies is a valuable complement to experimental approaches for discovering transcription regulatory interactions and networks. Scanning promoter sequences with dependent groups of transcription factor binding sites improve the quality of transcription factor predictions.</p
    corecore