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SRP055569
Homo sapiens
643 Downloadable Samples
NextSeq500
Description
Single cell transcriptomics has emerged as a powerful approach to dissecting phenotypic heterogeneity in complex, unsynchronized cellular populations. However, many important biological questions demand quantitative analysis of large numbers of individual cells. Hence, new tools are urgently needed for efficient, inexpensive, and parallel manipulation of RNA from individual cells. We report a simple microfluidic platform for trapping single cell lysates in sealed, picoliter microwells capable of “printing” RNA on glass or capturing RNA on polymer beads. To demonstrate the utility of our system for single cell transcriptomics, we developed a highly scalable technology for genome-wide, single cell RNA-Seq. The current implementation of our device is pipette-operated, profiles hundreds of individual cells in parallel with library preparation costs of ~$0.10-$0.20/cell, and includes five lanes for simultaneous experiments. We anticipate that this system will ultimately serve as a general platform for large-scale single cell transcriptomics, compatible with both imaging and sequencing readouts.!Series_type = Expression profiling by high throughput sequencing Overall design: A microfluidic device that pairs sequence-barcoded mRNA capture beads with individual cells was used to barcode cDNA from individual cells which was then pre-amplified by in vitro transcription in a pool and converted into an Illumina RNA-Seq library. Libraries were generated from ~600 individual cells in parallel and extensive analysis was done on 396 cells from the U87 and MCF10a cell lines and from ~500 individual cells with extensive analysis on 247 cells from the U87 and WI-38 cell lines. Sequencing was done on the 3''-end of the transcript molecules. The first read contains cell-identifying barcodes that were present on the capture bead and the second read contains a unique molecular identifier (UMI) barcode, a lane-identifying barcode, and then the sequence of the transcript.
Publication Title
Scalable microfluidics for single-cell RNA printing and sequencing.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 381 Downloadable Samples
- Illumina HiSeq 2500
Description
With the aim of understanding how Treg cells in highly vascularized tissues are related to Treg cells in other organs, we performed RNA-seq analysis of bulk Treg and Tconv cells isolated from liver, blood, spleen, and the liver-draining portal lymph node. This revealed a clear separation of cell transcriptomes by both tissue and Treg/Tconv identity, with cells from the liver falling between blood- and spleen-derived cells. Compared to splenic Treg cells, hepatic Treg cells were enriched for genes related to proliferation and activation, and genes encoding chemokine and cytokine receptors. Overall design: RNA was extracted from FACS-purified Tconv and Treg cells from various tissues of Foxp3Thy1.1 mice. Each sample contains cells pooled from 3 mice. 2 cell types from each of 4 tissues x 3 replicates = 24 samples.
Publication Title
CD49b defines functionally mature Treg cells that survey skin and vascular tissues.
Sample Metadata Fields
Sex, Age, Specimen part, Cell line, Subject
View Samples- Mus musculus
- 89 Downloadable Samples
- Illumina HiSeq 2500
Description
While unique subsets of Treg cells have been described in some non-lymphoid tissues, their relationship to Treg cells in secondary lymphoid organs and circulation remains unclear. We have identified a recirculating and highly suppressive effector Treg cell subset that expresses the a2 integrin, CD49b, and exhibits a unique tissue distribution. To identify genes and pathways enriched in CD49b+ Treg cells, we performed RNA-seq of splenic CD49b+ and CD49b- Treg cells that were of otherwise similar activation status based on expression of CD44 and CD62L. This revealed that splenic CD49b+ Treg cells express genes related to migration and activation, but are relatively depleted of genes whose expression is TCR-dependent in Treg cells. These results shed light on the identity and development of a functionally potent subset of mature effector Treg cells that recirculates through and surveys peripheral tissues. Overall design: RNA was extracted from FACS-purified splenic Tconv and Treg cells of different activation states from Foxp3GFP mice. 2 CD4+ T-cell lineages x 3 activation states x 4 replicates. There is no sample 3 (RNA was degraded); there are 23 samples in total.
Publication Title
CD49b defines functionally mature Treg cells that survey skin and vascular tissues.
Sample Metadata Fields
Sex, Age, Specimen part, Cell line, Subject
View Samples- Homo sapiens
- 31 Downloadable Samples
Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
We developed a computational framework that integrates chromosomal copy number and gene expression data for detecting aberrations that promote cancer progression. We demonstrate the utility of this framework using a melanoma dataset. Our analysis correctly identified known drivers of melanoma and predicted multiple novel tumor dependencies. Two dependencies, TBC1D16 and RAB27A, confirmed empirically, suggest that abnormal regulation of protein trafficking contributes to proliferation in melanoma. Together, these results demonstrate the ability of integrative Bayesian approaches to identify novel candidate drivers with biological, and possibly therapeutic, importance in cancer.
Publication Title
An integrated approach to uncover drivers of cancer.
Sample Metadata Fields
Cell line
View Samples- Mus musculus
- 2 Downloadable Samples
- Illumina HiSeq 2500
Description
While unique subsets of Treg cells have been described in some non-lymphoid tissues, their relationship to Treg cells in secondary lymphoid organs and circulation remains unclear. We have identified a short-lived effector Treg cell subset that expresses the a2 integrin, CD49b, and exhibits a unique tissue distribution. Projection of the CD49b+ Treg signature onto the Treg phenotypic landscape as inferred by single-cell RNA-seq analysis, placed these cells at the apex of the Treg developmental trajectory. These results shed light on the identity and development of a functionally potent subset of mature effector Treg cells that recirculate through and survey peripheral tissues. Overall design: Single-cell RNA-seq libraries (10x Genomics) were prepared from FACS-purified Tconv and Treg cells from pooled spleens of Foxp3GFP mice.
Publication Title
CD49b defines functionally mature Treg cells that survey skin and vascular tissues.
Sample Metadata Fields
Sex, Age, Specimen part, Subject
View Samples- Mus musculus
- 18 Downloadable Samples
- Illumina HiSeq 4000
Description
Immune checkpoint blockade is able to achieve durable responses in a subset of patients, however we lack a satisfying comprehension of the underlying mechanisms of anti-CTLA-4 and anti-PD-1 induced tumor rejection. To address these issues we utilized mass cytometry to comprehensively profile the effects of checkpoint blockade on tumor immune infiltrates in human melanoma and murine tumor models. These analyses reveal a spectrum of tumor infiltrating T cell populations that are highly similar between tumor models and indicate that checkpoint blockade targets only specific subsets of tumor infiltrating T cell populations. Anti-PD-1 predominantly induces the expansion of specific tumor infiltrating exhausted-like CD8 T cell subsets. In contrast, anti-CTLA-4 induces the expansion of an ICOS+ Th1-like CD4 effector population in addition to engaging specific subsets of exhausted-like CD8 T cells. Thus, our findings indicate that anti-CTLA-4 and anti-PD-1 checkpoint blockade induced immune responses are driven by distinct cellular mechanisms. Overall design: RNA profiles of a subset of tumor infiltrating T cell populations in anti-PD-1, anti-CTLA-r and control mice were generated by RNA sequencing, using Illumina HiSeq 4000. Mouse mutation background was assessed by whole exome sequencing data
Publication Title
Distinct Cellular Mechanisms Underlie Anti-CTLA-4 and Anti-PD-1 Checkpoint Blockade.
Sample Metadata Fields
Specimen part, Cell line, Subject
View Samples- Homo sapiens
- 82 Downloadable Samples
- IlluminaHiSeq2000
Description
Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations, translocations, and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole genome shRNA “dropout screens” on 77 breast cancer cell lines. Using a new hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify novel vulnerabilities in breast cancer, including new candidate “drivers,” and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, novel effects of existing anti-cancer drugs, and new opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer, and PIK3CA mutations as a resistance determinant for BET-inhibitors. Additional formatted data can be found at http://neellab.github.io/bfg/. Code and tutorials for the siMEM algorithm can be found at http://neellab.github.io/simem/. Overall design: RNA-Seq expression profiling of 82 breast cancer cell lines without replicates or control samples
Publication Title
Functional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 16 Downloadable Samples
- Illumina HiSeq 4000
Description
To comprehensively delineate the ontogeny of an organ system, we generated 112,217 single- cell transcriptomes representing all endoderm populations within the mouse embryo until midgestation. We employed graph-based approaches to model differentiating cells for spatio- temporal characterization of developmental trajectories. Our analysis reveals the detailed architecture of the emergence of the first (primitive or extra-embryonic) endodermal population and pluripotent epiblast. We uncover an unappreciated relationship between descendants of these lineages, before the onset of gastrulation, suggesting that mixing of extra-embryonic and embryonic endoderm cells occurs more than once during mammalian development. We map the trajectories of endoderm cells as they acquire embryonic versus extra-embryonic fates, and their spatial convergence within the gut endoderm; revealing them to be globally similar but retaining aspects of their lineage history. We observe the regionalized localization of cells along the forming gut tube, reflecting their extra-embryonic or embryonic origin, and their coordinate patterning into organ-specific territories along the anterior-posterior axis. Overall design: Total RNA was extracted from bulk tissue and dissociated cells of 13ss (~E8.75) gut tubes, from bulk tissue from anterior, anterior-midgut, midgut-posterior and posterior sections of 13ss gut tubes, as well as from extra-embryonic visceral endoderm and embryonic visceral endoderm of E7.5 embryos (see also table in section: Bulk RNA processing). The Trizol method (Invitrogen) was used for RNA extraction.
Publication Title
The emergent landscape of the mouse gut endoderm at single-cell resolution.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 168 Downloadable Samples
- Illumina HiSeq 4000, Illumina HiSeq 2500
Description
Knowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We created an immune map of breast cancer using single-cell RNA-seq data from 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph node. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous phenotypic expansions specific to the tumor microenvironment. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer, with important implications for characterizing tumor-infiltrating immune cells. Overall design: Single-cell RNA sequencing was performed on eight donors using the InDrop v2 protocol. For each donor populations of CD45+ immune cells were assayed for trancriptome-wide RNA-sequence. At least one replicate was taken for each donor.
Publication Title
Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 29 Downloadable Samples
- NextSeq 500, Illumina HiSeq 2500
Description
Knowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We created an immune map of breast cancer using single-cell RNA-seq data from 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph node. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous phenotypic expansions specific to the tumor microenvironment. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer, with important implications for characterizing tumor-infiltrating immune cells. Overall design: Single-cell RNA sequencing was performed on three patients using the 10x genomics TCR profiling kits. For each patient, populations of T-cells were assayed for both TCR sequence and trancriptome-wide RNA-sequence. Two donors have a replicate experiment.
Publication Title
Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment.
Sample Metadata Fields
Specimen part, Subject
View Samples