Project description:Identification of factors regulating leaf inclination reveal a complex regulatory network of lamina joint development, however, the dynamic transcriptional programming of it remain to be elucidated. We used microarrays to detail the global gene expression profiles at different developmental stages of lamina joint and identified distinct classes of differentially expressed genes during this process, characterized the regulating factors of rice lamina joint development.
Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. DNA binding of TSC22D3 in Th17 cells compared to WCE
Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. Time course microarray data for Th17 differentiation, including Th0 control
Project description:Blood and cardiovascular development represent paradigms of embryonic organ formation, with increasingly specialised cells generated from early mesoderm. Here, we map the progression of mesoderm towards blood by single cell expression analysis of 3,934 cells, aiming to capture an entire embryo equivalent of cells with blood-forming potential at four sequential developmental stages. Using novel computational approaches, we reconstruct the developmental journey at single cell resolution, which reveals asynchrony of maturation and sequential waves of expression for major regulators. Considering transitions between individual cellular states, we synthesise executable transcriptional regulatory network models that recapitulate blood development. Using mouse embryos and embryonic stem cells, we validate model predictions by showing that Sox7 inhibits primitive erythropoiesis, and that Sox and Hox factors control early expression of Erg. We therefore demonstrate that single cell analysis of a developing organ coupled with novel computational approaches can reveal the transcriptional programs that control organogenesis. Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development
Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. RNA-seq of knockdown of 12 genes in Th17 cell differentiation
Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. Time course microarray data for Th17 differentiation, comparing IL23r-/- to WT
Project description:Human FOXP3+CD25+CD4+ regulatory T cells (Tregs) play a dominant role in the maintenance of immune homeostasis. Several genes are known to be important for murine Tregs, but for human Tregs the genes and underlying molecular networks controlling the suppressor function still largely remain unclear. We here performed a high-time-resolution dynamic analysis of the transcriptome during the very early phase of human Treg/ CD4+ T-effector cell activation. After constructing a correlation network specific for Tregs based on these dynamic data, we described a strategy to identify key genes by directly analyzing the constructed undirected correlation network. Six out of the top 10 ranked key hubs are known to be important for Treg function or involved in autoimmune diseases. Surprisingly, PLAU (the plasminogen activator urokinase) was among the 4 new key hubs. We here show that PLAU was critical for expression regulation of FOXP3, EOS and several other important Treg genes and the suppressor function of human Tregs. Moreover, we found Plau inhibits murine Treg development and but promotes the suppressive function. Further analysis unveils that PLAU is particularly important for memory Tregs and that PLAU mediates Treg suppressor function via STAT5 and ERK signaling pathways. Our study shows the potential for identifying novel key genes for complex dynamic biological processes using a network strategy based on high-time-resolution data, and highlights a critical role of PLAU in both human and murine Tregs. The construction of a dynamic correlation network of human Tregs provides a useful resource for the understanding of Treg function and human autoimmune diseases. The high-time-resolution time-series transcriptomic data during the very early phase of human Treg/Teff activation could be generally used for further mechanistic analysis of human Treg function. These data could be further used for biological network analysis, dynamic analysis, modeling by experimental researchers, bioinformaticians, computational biologists and systems biologists. We have measured the genome-wide expression of 38,500 genes (probes) by performing a high-time-resolution time-series analysis during the activation process of human regulatory T cells /CD4+ T-effector cells at 19 time points for the first 6h with an equal interval of 20 min. We have also overexpressed the GARP gene in human effector T cells and measured the genome-scale expression for the GARP-overexpressed cells and ThGFP cells at time point 0, 100 and 360min following activation. The stimulation source used in this work is a combination of anti-CD3/-CD28 Dynal beads with IL2 100U/ml.
Project description:Because chromatin determines whether information encoded in DNA is accessible to transcription factors, dynamic chromatin states in development may constrain how gene regulatory networks impart embryonic pattern. To determine the interplay between chromatin states and regulatory network function, we performed ATAC seq on Drosophila embryos over the period spanning the establishment of the segmentation network, comparing wild-type and mutant embryos in which all graded maternal patterning inputs are eliminated. While during the period between zygotic genome activation and gastrulation many regions maintain stable accessibility, cis-regulatory modules (CRMs) within the segmentation network undergo extensive patterning-dependent changes in accessibility. A component of the network, Odd-paired (opa), is necessary for pioneering accessibility of segmentation network CRMs. While opa is necessary to drive late opening of segmentation network cis-regulatory elements, competence for opa to pioneer is regulated over time. These results indicate that dynamic systems for chromatin regulation directly impact the interpretation of embryonic patterning information.
Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells.