Project description:We used scRNA-seq to examine cell type allometry in asexual planarians. We profiled 28,738 single cell transcriptomes of planarian of 3 different sizes categories: small (S), medium (M) and large (L). We detected changes in cell type frequency and gene expression patterns in planarian of different sizes, capturing regulatory programs of distinct cell types in response to allometric scaling.
Project description:We used scRNA-seq to examine serotonergic function in asexual planarians. We profiled 47,292 single cell transcriptomes of planarian of 3 different RNAi categories: gfp(RNAi), lhx1/5-1(RNAi) and pitx(RNAi). We detected changes in cell type frequency and gene expression patterns in planarian of different knock-down conditions, capturing regulatory programs of distinct cell types in response to loss of serotonergic function.
Project description:Understanding the molecular and cellular processes involved in lung epithelial regeneration may fuel the development of therapeutic approaches for lung diseases. We combine mouse models allowing diphtheria toxin-mediated damage of specific epithelial cell types and parallel GFP-labeling of functionally dividing cells with single-cell transcriptomics to characterize the regeneration of the distal lung. We uncover cell types, including Krt13+ basal and Krt15+ club cells, detect an intermediate cell state between basal and goblet cells, reveal goblet cells as actively dividing progenitor cells, and provide evidence that adventitial fibroblasts act as supporting cells in epithelial regeneration. We also show that diphtheria toxin-expressing cells can persist in the lung, express specific inflammatory factors, and transcriptionally resemble a previously undescribed population in the lungs of COVID-19 patients. Our study provides a comprehensive single-cell atlas of the distal lung that characterizes early transcriptional and cellular responses to concise epithelial injury, encompassing proliferation, differentiation, and cell-to-cell interactions.
Project description:Single-cell transcriptomics (scRNA-seq) has revolutionized our understanding of cell types and states in various contexts, such as development and disease. Most methodology relies on poly(A) enrichment to selectively capture protein-coding polyadenylated transcripts, intending to exclude ribosomal transcripts that constitute >80% of the transcriptome. However, it is common for ribosomal transcripts to sneak into the library, which can add significant background by flooding libraries with irrelevant sequences. The challenge of amplifying all RNA transcripts from a single cell has motivated the development of new technologies to optimize retrieval of transcripts of interest. This problem is notable in planarians, where we find that 16S ribosomal transcripts were widely enriched (20-80%) across single-cell methods. Therefore, we adapted the Depletion of Abundant Sequences by Hybridization (DASH) to the standard 10X scRNA-seq protocol. We designed single-guide RNAs tiling the 16S sequence for CRISPR-mediated degradation, and subsequently generated untreated and DASH-treated datasets from the same libraries to enable a side-by-side comparison of the effects of DASH. DASH specifically removes 16S sequences without off-target removal of other genes. By assessing the cell barcodes shared by both libraries, DASH-treated cells have consistently higher complexity given the same amount of reads, which allows the detection of a rare cell cluster and more differentially expressed genes. In conclusion, DASH can be easily integrated into existing sequencing protocols and customized to deplete any unwanted transcripts.