Mus musculus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA389818 | ENA |
REPOSITORIES: ENA
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Project description:High-throughput single-cell RNA-seq methods assign limited unique molecular identifier (UMI) counts as gene expression values to single cells from shallow sequence reads and detect limited gene counts. We thus developed a high-throughput single-cell RNA-seq method, Quartz-Seq2, to overcome these issues. Our improvements in several of the reaction steps of Quartz-Seq2 allow us to effectively convert initial reads to UMI counts (at a rate of 30%–50%). To demonstrate the power of Quartz-Seq2, we analyzed transcriptomes from a cell population of in vitro embryonic stem cells and an in vivo stromal vascular fraction with a limited number of sequence reads. Preprint: http://www.biorxiv.org/content/early/2017/07/21/159384
2017-07-20 | GSE99866 | GEO
Project description:We developed SCAN-seq2, a high-throughput and highly sensitive single-cell RNA sequencing method based on the TGS platform. Our study demonstrated that SCAN-seq2 improves upon the previous method, SCAN-seq, in terms of sensitivity and throughput. By using reference-guided assembly of single-cell data, we were able to identify thousands of novel full-length RNA isoforms, including cell type-specific expression patterns of pseudogenes. We also accurately determined V(D)J rearrangement events in T and B cells. Lastly, we found that treatment of HepG2 and Hela cells with the spliceosome inhibitor Isoginkgetin (IGG) resulted in a subpopulation of cells with distinct apoptosis features. Our study provides a promising new tool for single-cell transcriptome research. The source code for SCAN-seq2 data analysis pipelines is available at https://github.com/liuzhenyu-yyy/SCAN-seq2 .
2022-11-15 | GSE203561 | GEO
Project description:Single-cell DNA methylome profiling has enabled the study of epigenomic heterogeneity in complex tissues and during cellular reprogramming. However, broader applications of the method have been impeded by the modest quality of sequencing libraries. Here we report snmC-seq2, which provides improved read mapping, reduced artificial reads, enhanced throughput, and increased library complexity compared to snmC-seq. snmC-seq2 is an efficient strategy suited for large scale single-cell epigenomic studies.
2018-09-20 | GSE112471 | GEO
Project description:The rise in throughput and quality of long-read sequencing should allow unambiguous identification of full-length transcript isoforms. However, its application to single-cell RNA-seq has been limited by throughput and expense. Here we develop and characterize long-read Split-seq (LR-Split-seq), which uses combinatorial barcoding to sequence single cells with long reads. Applied to the C2C12 myogenic system, LR-split-seq associates isoforms to cell types with relative economy and design flexibility. We find widespread evidence of changing isoform expression during differentiation including alternative transcription start sites (TSS) and/or alternative internal exon usage. LR-Split-seq provides an affordable method for identifying cluster-specific isoforms in single cells.
2021-03-12 | GSE168776 | GEO
Project description:Chromatin profiling in single cells has been extremely challenging and almost exclusively limited to histone proteins. In cases where single cell methods have shown promise, many require highly specialized equipment or cell type specific protocols and are relatively low throughput. Here, we combine the advantages of tagmentation, linear amplification and combinatorial indexing to produce a high throughput single cell DNA binding site mapping method that is simple, inexpensive and capable of multiplexing several independent samples per experiment. Targeted Insertion of Promoters (TIP-seq) uses Tn5 fused to protein A to insert a T7 RNA polymerase promoter adjacent to a chromatin protein of interest. Linear amplification of flanking DNA with T7 polymerase prior to sequencing library preparation provides ~10-fold higher unique reads per single cell compared to other methods. We apply TIP-seq to map histone modifications, RNA Polymerase II (RNAPII) and transcription factor CTCF binding sites in single human and mouse cells.
2021-11-10 | GSE188512 | GEO
Project description:To accelerate previous RNA structure probing approaches, which focus on analyzing one RNA sequence at a time, we have developed FragSeq, a high-throughput RNA structure probing method that uses high-throughput RNA sequencing to identify single-stranded RNA (ssRNA) regions from fragments generated by nuclease P1, which is specific for single-stranded nucleic acids. In the accompanying study, we show that we can accurately and simultaneously map ssRNA regions in multiple non-coding RNAs with known structure in experiments probing the entire mouse nuclear transcriptome. We carried out probing in two cell types to assess reproducibility. We also identified and experimentally validated structured regions in ncRNAs never previously probed.
2010-11-07 | GSE24622 | GEO
Project description:Single-cell transcriptomics requires a method that is sensitive, accurate, and reproducible. Here, we present CEL-Seq2, a modified version of our CEL-Seq method, with three-fold higher sensitivity, lower costs, and less hands-on time. We also implemented CEL-Seq2 on Fluidigm’s C1 system, thereby providing its first single-cell, on-chip barcoding method, and detected gene expression changes accompanying the progression through the cell cycle in mouse fibroblast cells. We also compare with Smart-Seq to demonstrate CEL-Seq2’s increased sensitivity relative to other available methods. Collectively, the improvements make CEL-Seq2 uniquely suited to single-cell RNA-Seq analysis in terms of economics, resolution, and ease of use
2016-04-08 | GSE78779 | GEO
Project description:Cleavage Under Targets & Tagmentation (CUT&Tag) is an antibody-directed in situ chromatin profiling strategy that is rapidly replacing precipitation-based methods. The efficiency of the method enabled chromatin profiling in single cells but is limited by the numbers of cells that can be profiled. Here, we describe a combinatorial barcoding strategy for CUT&Tag that harnesses a nanowell dispenser for simple, high-resolution high-throughput single-cell chromatin profiling. We describe a pipeline for single-cell indexed CUT&Tag (sciCUT&Tag) that uses SNPs to facilitate doublet-cell removal and minimize batch effects. We illustrate the optimized protocol by analysis of mouse and human cell lines, as well as human peripheral blood mononuclear cells. We have also used sciCUT&Tag for simultaneous profiling of multiple chromatin epitopes in single cells. The reduced cost, improved resolution and scalability of sciCUT&Tag make it an attractive platform to profile chromatin features in single cells.
2023-07-13 | GSE224579 | GEO
Project description:Gene expression profiling of very few or even single cells is of particular interest in many applications. However, detection of a large number of mRNA sequences from a small number of cells is limited by the sensitivity of available methods. High-throughput multiplex reverse transcription followed by PCR amplification (RT-PCR) has much to offer to these studies due to its inherent sensitivity, efficiency and cost-effectiveness. A multiplex RT-PCR based high-throughput gene profiling system is described in this communication. With this system >1000 different mRNA species can be amplified in a single tube to a detectable amount. By using specially designed PCR primers, the long-standing low specificity problem associated with high-throughput gene expression profiling has been solved. Amplified sequences are then resolved by microarray with probes that only hybridize to sequences amplified from mRNA. The method is so sensitive that mRNA in single cells can be reliably detected. Differentially expressed genes identified with the high-throughput approach in the breast cancer cell line, MCF-7, and its drug resistant variant, MCF-7/AdrR, could be validated by a different method. The approach may greatly facilitate the analysis of combinatorial expression of known genes in any cells in many important applications with a limited amount of RNA. Keywords: drug resistence
2007-06-01 | GSE5920 | GEO
Project description:Background: Rare cell subtypes can profoundly impact the course of human health and disease, yet their presence within a sample is often missed with bulk molecular analysis. Single-cell analysis tools such as FACS, FISH-FC and single-cell barcode-based sequencing can investigate cellular heterogeneity; however, they have significant limitations that impede their ability to identify and transcriptionally characterize many rare cell subpopulations. Results: PCR-activated cell sorting (PACS) is a novel cytometry method that uses single-cell TaqMan PCR reactions performed in microfluidic droplets to identify and isolate cell subtypes with high-throughput. Here, we extend this method and demonstrate that PACS enables high-dimensional molecular profiling on TaqMan-targeted cells. Using a random priming RNA-Seq strategy, we obtained high-fidelity transcriptome measurements following PACS-sorting of prostate cancer cells from a heterogeneous population. The sequencing data revealed prostate cancer gene expression profiles that were obscured in the unsorted populations. Single-cell expression analysis with PACS was subsequently used to confirm a number of the differentially expressed genes identified with RNA sequencing. Conclusions: PACS requires minimal sample processing, uses readily available TaqMan assays and can isolate cell subtypes with high sensitivity. We have now validated a method for performing next-generation sequencing on mRNA obtained from PACS isolated cells. This capability makes PACS well suited for transcriptional profiling of rare cells from complex populations to obtain maximal biological insight into cell states and behaviors.
2016-04-22 | GSE80551 | GEO