Project description:These data include RNA-seq, circRNA-seq, and small RNA-seq of transcriptome, Ribo-seq of translatome and protein protein binary interactions by recombination-based library vs. library yeast-2-hybrid throughout the lifecycle of the maize inbred line B73.
Project description:The pathogenesis of Colorectal cancer (CRC) metastasis remains unclear.We collect clinical data from our center and use Integrative omics to analyze and predict candidate biomarkers of colorectal cancer and distant metastasis.
Project description:we conducted integrative multiple levels of omics data including transcriptome, phosphoproteome, proteome and metabolome in different time-course of sepsis-associated liver dysfunction (SALD). This is the first trial to suggest the statistical pathway of integrative multi-omics data in sepsis. Given the increasing number of studies collecting multi-omics data but limited overview of the methodological framework for integrative analyses (Liu, Ding et al. 2013, Petersen, Zeilinger et al. 2014, Shah, Bonder et al. 2015), integrative approach in sepsis with liver dysfunction in this study will provide novel insights into the development of sepsis and ultimately offer new tools for overcoming the present diagnostic limitation. Therefore, a combined multi-omics dataset will give better accessibility of adoption in disease, and insight to identify the promising candidates for therapeutic strategies.
Project description:We constructed a comprehensive multi-omics map of the molecular effects of fluoxetine (an SSRI antidepressant), in 27 rat brain regions. We profiled gene expression (bulk RNA-seq, 210 datasets) and chromatin state (bulk chromatin immunoprecipitation sequencing (ChIP-seq) for the histone marker H3K27ac, 100 datasets) in a broad, unbiased panel of 27 brain regions across the entire rodent brain, in naive and fluoxetine-treated animals. We complemented this approach with single-cell RNA-seq (scRNA-seq) analysis of two brain regions. Using diverse integrative data analysis techniques we characterized the complex and multifaceted effects of fluoxetine on region-specific and cell-type-specific gene regulatory networks and pathways. Remarkably, we observed profound molecular changes across the brain (>4,000 differentially expressed genes and differentially acetylated ChIP-seq peaks each) that were highly region-dependent. We leveraged this atlas to identify fluoxetine-moduated genes and gene-regulatory loci, predict enriched motifs that suggest potential upstream regulators, and validate global mechanisms of fluoxetine action.
Project description:We constructed a comprehensive multi-omics map of the molecular effects of fluoxetine (an SSRI antidepressant), in 27 rat brain regions. We profiled gene expression (bulk RNA-seq, 210 datasets) and chromatin state (bulk chromatin immunoprecipitation sequencing (ChIP-seq) for the histone marker H3K27ac, 100 datasets) in a broad, unbiased panel of 27 brain regions across the entire rodent brain, in naive and fluoxetine-treated animals. We complemented this approach with single-cell RNA-seq (scRNA-seq) analysis of two brain regions. Using diverse integrative data analysis techniques we characterized the complex and multifaceted effects of fluoxetine on region-specific and cell-type-specific gene regulatory networks and pathways. Remarkably, we observed profound molecular changes across the brain (>4,000 differentially expressed genes and differentially acetylated ChIP-seq peaks each) that were highly region-dependent. We leveraged this atlas to identify fluoxetine-moduated genes and gene-regulatory loci, predict enriched motifs that suggest potential upstream regulators, and validate global mechanisms of fluoxetine action.
Project description:Intestinal organoids accurately recapitulate epithelial homeostasis in vivo, thereby representing a powerful in vitro system to investigate lineage specification and cellular differentiation. Here, we applied a multi-omics framework on stem cell-enriched and stem cell-depleted mouse intestinal organoids to obtain a holistic view of the molecular mechanisms that drive differential gene expression during adult intestinal stem cell differentiation. Our data revealed a global rewiring of the transcriptome and proteome between intestinal stem cells and enterocytes, with the majority of dynamic protein expression being transcription-driven. Integrating absolute mRNA and protein copy numbers revealed post-transcriptional regulation of gene expression. Probing the epigenetic landscape identified a large number of cell-type-specific regulatory elements, which revealed Hnf4g as a major driver of enterocyte differentiation. In summary, by applying an integrative systems biology approach, we uncovered multiple layers of gene expression regulation, which contribute to lineage specification and plasticity of the mouse small intestinal epithelium.
Project description:We constructed a comprehensive multi-omics map of the molecular effects of fluoxetine (an SSRI antidepressant) in 27 rat brain regions. We profiled gene expression (bulk RNA-seq, 210 datasets) and chromatin state (bulk chromatin immunoprecipitation sequencing (ChIP-seq) for the histone marker H3K27ac, 100 datasets) in a broad, unbiased panel of 27 brain regions across the entire rodent brain, in naive and fluoxetine-treated animals. We complemented this approach with single-cell RNA-seq (scRNA-seq) analysis of two brain regions (20 datasets). Remarkably, in the single-cell RNA-seq profiling we observed profound changes in the transcripts of hippocampal dorDG and venDG (~500 DEGs in specific cell types). Using diverse integrative data analysis techniques we characterized the complex and multifaceted effects of fluoxetine on region-specific and cell-type-specific gene regulatory networks and pathways. We leveraged this atlas to identify fluoxetine-modulated genes and gene-regulatory loci, predict enriched motifs that suggest potential upstream regulators, and validate global mechanisms of fluoxetine action.