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Background: Eukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined chromatin state data (e.g., ChIP-seq, ATAC-seq, or DNase-seq) and RNA-seq data exist, they do not offer convenient usability, have limited support for large-scale data processing, and provide only minimal functionality for visually interpreting results.
Results: We developed TF-Prioritizer, an automated pipeline that prioritizes condition-specific TFs from multi-modal data and generates an interactive web report. We demonstrated its potential by identifying known TFs along with their target genes, as well as previously unreported TFs active in lactating mouse mammary glands. Additionally, we studied a variety of ENCODE data sets for cell lines K562 and MCF-7, including twelve histone modification ChIP-seq as well as ATAC-seq and DNase-seq datasets, where we observe and discuss assay-specific differences.
Conclusion: TF-Prioritizer accepts ATAC-seq, DNase-seq, or ChIP-seq and RNA-seq data as input and identifies TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.
Background Eukaryotic gene expression is controlled by cis-regulatory elements (CREs) including promoters and enhancers which are bound by transcription factors (TFs). Differential expression of TFs and their putative binding sites on CREs cause tissue and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and thus gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined ChIP-seq and RNA-seq data exist, they do not offer good usability, have limited support for large-scale data processing, and provide only minimal functionality for visual result interpretation.
Results We developed TF-Prioritizer, an automated java pipeline to prioritize condition-specific TFs derived from multi-modal data. TF-Prioritizer creates an interactive, feature-rich, and user-friendly web report of its results. To showcase the potential of TF-Prioritizer, we identified known active TFs (e.g., Stat5, Elf5, Nfib, Esr1), their target genes (e.g., milk proteins and cell-cycle genes), and newly classified lactating mammary gland TFs (e.g., Creb1, Arnt).
Conclusion TF-Prioritizer accepts ChIP-seq and RNA-seq data, as input and suggests TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.
Haematopoietic stem cells (HSCs) require the right composition of microRNAs (miR) for proper life-long balanced blood regeneration. Here we show a regulatory circuit that prevents excessive HSC self-renewal by upregulation of miR-193b upon self-renewal promoting thrombopoietin (TPO)-MPL-STAT5 signalling. In turn, miR-193b restricts cytokine signalling, by targeting the receptor tyrosine kinase c-KIT. We generated a miR-193b knockout mouse model to unravel the physiological function of miR-193b in haematopoiesis. MiR-193b−/− mice show a selective gradual enrichment of functional HSCs, which are fully competent in multilineage blood reconstitution upon transplantation. The absence of miR-193b causes an accelerated expansion of HSCs, without altering cell cycle or survival, but by decelerating differentiation. Conversely, ectopic miR-193b expression restricts long-term repopulating HSC expansion and blood reconstitution. MiR-193b-deficient haematopoietic stem and progenitor cells exhibit increased basal and cytokine-induced STAT5 and AKT signalling. This STAT5-induced microRNA provides a negative feedback for excessive signalling to restrict uncontrolled HSC expansion.
Cytokine-regulated GADD45G induces differentiation and lineage selection in hematopoietic stem cells
(2014)
The balance of self-renewal and differentiation in long-term repopulating hematopoietic stem cells (LT-HSC) must be strictly controlled to maintain blood homeostasis and to prevent leukemogenesis. Hematopoietic cytokines can induce differentiation in LT-HSCs; however, the molecular mechanism orchestrating this delicate balance requires further elucidation. We identified the tumor suppressor GADD45G as an instructor of LT-HSC differentiation under the control of differentiation-promoting cytokine receptor signaling. GADD45G immediately induces and accelerates differentiation in LT-HSCs and overrides the self-renewal program by specifically activating MAP3K4-mediated MAPK p38. Conversely, the absence of GADD45G enhances the self-renewal potential of LT-HSCs. Videomicroscopy-based tracking of single LT-HSCs revealed that, once GADD45G is expressed, the development of LT-HSCs into lineage-committed progeny occurred within 36 hr and uncovered a selective lineage choice with a severe reduction in megakaryocytic-erythroid cells. Here, we report an unrecognized role of GADD45G as a central molecular linker of extrinsic cytokine differentiation and lineage choice control in hematopoiesis.