While only recently developed, the ability to profile expression data in single cells (scRNA-Seq) has already led to several important studies and findings. However, this technology has also raised several new computational challenges. These include questions about the best methods for clustering scRNA-Seq data, how to identify unique group of cells in such experiments, and how to determine the state or function of specific cells based on their expression profile. To address these issues we develop and test a method based on neural networks (NN) for the analysis and retrieval of single cell RNA-Seq data. We tested various NN architectures, some of which incorporate prior biological knowledge, and used these to obtain a reduced dimension representation of the single cell expression data. We show that the NN method improves upon prior methods in both, the ability to correctly group cells in experiments not used in the training and the ability to correctly infer cell type or state by querying a database of tens of thousands of single cell profiles. Such database queries (which can be performed using our web server) will enable researchers to better characterize cells when analyzing heterogeneous scRNA-Seq samples.
BackgroundAbnormal activation of endochondral bone formation in soft tissues causes significant medical diseases associated with disability and pain. Hyperactive mutations in the bone morphogenetic protein (BMP) type 1 receptor ACVR1 lead to fibrodysplasia ossificans progressiva (FOP), a rare genetic disorder characterized by progressive ossification in soft tissues. However, the specific cellular mechanisms are unclear. In addition, the difficulty obtaining tissue samples from FOP patients and the limitations in mouse models of FOP hamper our ability to dissect the pathogenesis of FOP.MethodsTo address these challenges and develop a “disease model in a dish”, we created human induced pluripotent stem cells (iPS cells) derived from normal and FOP dermal fibroblasts by two separate methods, retroviral integration or integration-free episomal vectors. We tested if the ability to contribute to different steps of endochondral bone formation was different in FOP vs. control iPS cells.ResultsRemarkably, FOP iPS cells showed increased mineralization and enhanced chondrogenesis in vitro. The mineralization phenotypes could be suppressed with a small-molecule inhibitor of BMP signaling, DMH1. Our results indicate that the FOP ACVR1 R206H mutation favors chondrogenesis and increases mineral deposition in vitro.ConclusionsOur findings establish a FOP disease cell model for in vitro experimentation and provide a proof-of-concept for using human iPS cell models to understand human skeletal disorders.
BackgroundThe Activin A and bone morphogenetic protein (BMP) pathways are critical regulators of the immune system and of bone formation. Inappropriate activation of these pathways, as in conditions of congenital heterotopic ossification, are thought to activate an osteogenic program in endothelial cells. However, if and how this occurs in human endothelial cells remains unclear.MethodsWe used a new directed differentiation protocol to create human induced pluripotent stem cell (hiPSC)-derived endothelial cells (iECs) from patients with fibrodysplasia ossificans progressiva (FOP), a congenital disease of heterotopic ossification caused by an activating R206H mutation in the Activin A type I receptor (ACVR1). This strategy allowed the direct assay of the cell-autonomous effects of ACVR1 R206H in the endogenous locus without the use of transgenic expression. These cells were challenged with BMP or Activin A ligand, and tested for their ability to activate osteogenesis, extracellular matrix production, and differential downstream signaling in the BMP/Activin A pathways.ResultsWe found that FOP iECs could form in conditions with low or absent BMP4. These conditions are not normally permissive in control cells. FOP iECs cultured in mineralization media showed increased alkaline phosphatase staining, suggesting formation of immature osteoblasts, but failed to show mature osteoblastic features. However, FOP iECs expressed more fibroblastic genes and Collagen 1/2 compared to control iECs, suggesting a mechanism for the tissue fibrosis seen in early heterotopic lesions. Finally, FOP iECs showed increased SMAD1/5/8 signaling upon BMP4 stimulation. Contrary to FOP hiPSCs, FOP iECs did not show a significant increase in SMAD1/5/8 phosphorylation upon Activin A stimulation, suggesting that the ACVR1 R206H mutation has a cell type-specific effect. In addition, we found that the expression of ACVR1 and type II receptors were different in hiPSCs and iECs, which could explain the cell type-specific SMAD signaling.ConclusionsOur results suggest that the ACVR1 R206H mutation may not directly increase the formation of mature chondrogenic or osteogenic cells by FOP iECs. Our results also show that BMP can induce endothelial cell dysfunction, increase expression of fibrogenic matrix proteins, and cause differential downstream signaling of the ACVR1 R206H mutation. This iPSC model provides new insight into how human endothelial cells may contribute to the pathogenesis of heterotopic ossification.Electronic supplementary materialThe online version of this article (doi:10.1186/s13287-016-0372-6) contains supplementary material, which is available to authorized users.
A variety of genetic techniques have been devised to determine cell lineage relationships during tissue development. Some of these systems monitor cell lineages spatially and/or temporally without regard to gene expression by the cells, whereas others correlate gene expression with the lineage under study. The GAL4 Technique for Real-time and Clonal Expression (G-TRACE) system allows for rapid, fluorescent protein-based visualization of both current and past GAL4 expression patterns and is therefore amenable to genome-wide expression-based lineage screens. Here we describe the results from such a screen, performed by undergraduate students of the University of California, Los Angeles (UCLA) Undergraduate Research Consortium for Functional Genomics (URCFG) and high school summer scholars as part of a discovery-based education program. The results of the screen, which reveal novel expression-based lineage patterns within the brain, the imaginal disc epithelia, and the hematopoietic lymph gland, have been compiled into the G-TRACE Expression Database (GED), an online resource for use by the Drosophila research community. The impact of this discovery-based research experience on student learning gains was assessed independently and shown to be greater than that of similar programs conducted elsewhere. Furthermore, students participating in the URCFG showed considerably higher STEM retention rates than UCLA STEM students that did not participate in the URCFG, as well as STEM students nationwide.
Undergraduate students participating in the UCLA Undergraduate Research Consortium for Functional Genomics (URCFG) have conducted a two-phased screen using RNA interference (RNAi) in combination with fluorescent reporter proteins to identify genes important for hematopoiesis in Drosophila. This screen disrupted the function of approximately 3500 genes and identified 137 candidate genes for which loss of function leads to observable changes in the hematopoietic development. Targeting RNAi to maturing, progenitor, and regulatory cell types identified key subsets that either limit or promote blood cell maturation. Bioinformatic analysis reveals gene enrichment in several previously uncharacterized areas, including RNA processing and export and vesicular trafficking. Lastly, the participation of students in this course-based undergraduate research experience (CURE) correlated with increased learning gains across several areas, as well as increased STEM retention, indicating that authentic, student-driven research in the form of a CURE represents an impactful and enriching pedagogical approach.
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