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SRP058569
Mus musculus
20 Downloadable Samples
Description
Aging at the cellular level is driven by changes in gene activity and epigenetic state that are only partially understood. We performed a comprehensive epigenomic analysis of the pancreatic ß cell, key player in glucose homeostasis and diabetes, in adolescent and very old mice. Globally, we observe a general methylation drift resulting in an overall more leveled methylome, suggesting that the maintenance of highly differential methylation patterns becomes compromised with advanced age. Importantly, we discover targeted changes in the methylation status of ß cell proliferation and function genes that go against the global methylation drift, are specific to ß cells, and correlate with repression of the proliferation program and activation of metabolic regulators. These targeted alterations frequently occur at distal cis-regulator elements, and are associated with specific chromatin marks and transcription factor occupancy in young ß cells. Strikingly, we find the insulin secretory response to glucose much improved in mature ß cells in mice, as predicted by the changes in methylome and transcriptome and in contrast to the decline in function observed in aged human ß cells. Thus, aging of terminally differentiated cells in mammals is not always coupled to functional decline. Overall design: RNA-seq was done on 3 biological replicas from old and three from young beta cells. each sample originated from a pool of 5-10 mic.e H3K27me3 ChIP-seq was done with two replicas for old mice (pool of 4-7 mice) and the rest of the ChIPseq (H3K4me1, H3K27ac and young H3K27me3) was sone with one sample (pool of few mice). BIS-seq was done on one sample from a pool of 10 young mice and one sample of a pool of old mice (18-22 months old)
Publication Title
Aging-Dependent Demethylation of Regulatory Elements Correlates with Chromatin State and Improved β Cell Function.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 6 Downloadable Samples
- Illumina HiSeq 2500
Description
The sensory epithelium of cochleas and vestibules of mice were compared. The two tissues are quite similar in structure, but have distinct roles in hearing and balance. By comparing their gene expression, we hoped to identify key regulators of differentiation. Overall design: Cochlear and vestibular sensory epithelium was dissected from 20 inner ears of 10 P0 C57Bl/6J mice, generating 2.4 and 1.5 µg of total RNA, respectively. 450 ng RNA from each sample was used to create libraries with the TruSeq Stranded mRNA Sample Prep Kit (Illumina), followed by high-throughput sequencing at 100 bp paired end (PE) at the Technion Genome Center, Haifa, Israel. Six samples were generated, 3 cochlear and 3 vestibular, for sequencing in triplicate.
Publication Title
Computational analysis of mRNA expression profiling in the inner ear reveals candidate transcription factors associated with proliferation, differentiation, and deafness.
Sample Metadata Fields
Sex, Specimen part, Cell line, Subject
View Samples- Mus musculus
- 384 Downloadable Samples
- Illumina HiSeq 2500
Description
The interaction between a pathogen and a host is a highly dynamic process in which both agents activate complex programs. Here, we introduce a single-cell RNA-Seq method (scDual-Seq) that simultaneously captures both host and pathogen transcriptomes and use it to study the process of infection of individual mouse macrophages with the intracellular pathogen Salmonella typhimurium. Among the infected macrophages, we found three subpopulations and we show evidence for a linear progression through these subpopulations, supporting a model in which these three states correspond to consecutive stages of infection. Overall design: 96 single cells in 4 time point of infection (0,2.5,4,8 hours after infection)
Publication Title
scDual-Seq: mapping the gene regulatory program of Salmonella infection by host and pathogen single-cell RNA-sequencing.
Sample Metadata Fields
Cell line, Subject, Time
View Samples- Mus musculus
- 96 Downloadable Samples
- Illumina HiSeq 2500
Description
The interaction between a pathogen and a host is a highly dynamic process in which both agents activate complex programs. Here, we introduce a single-cell RNA-Seq method (scDual-Seq) that simultaneously captures both host and pathogen transcriptomes and use it to study the process of infection of individual mouse macrophages with the intracellular pathogen Salmonella typhimurium. Among the infected macrophages, we found three subpopulations and we show evidence for a linear progression through these subpopulations, supporting a model in which these three states correspond to consecutive stages of infection. Overall design: 40 single cells, 6 ten cells bulk, 2 hundred cells bulk, in two time point of infection (0,4 hours after infection)
Publication Title
scDual-Seq: mapping the gene regulatory program of Salmonella infection by host and pathogen single-cell RNA-sequencing.
Sample Metadata Fields
Cell line, Subject, Time
View Samples- Mus musculus
- 5 Downloadable Samples
- Illumina HiSeq 2500
Description
The interaction between a pathogen and a host is a highly dynamic process in which both agents activate complex programs. Here, we introduce a single-cell RNA-Seq method (scDual-Seq) that simultaneously captures both host and pathogen transcriptomes and use it to study the process of infection of individual mouse macrophages with the intracellular pathogen Salmonella typhimurium. Among the infected macrophages, we found three subpopulations and we show evidence for a linear progression through these subpopulations, supporting a model in which these three states correspond to consecutive stages of infection. Overall design: a dilution series of mouse and salmonella RNA Please note that the samples are identical to GSM2729237-GSM2729241 and the RNA was extracted simultaneously. The only difference between them is the different protocol by which the libraries were made for sequencing (i.e. CEL-Seq2 or scDual-Seq).
Publication Title
scDual-Seq: mapping the gene regulatory program of Salmonella infection by host and pathogen single-cell RNA-sequencing.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 1113 Downloadable Samples
- Illumina HiSeq 2000, Illumina HiSeq 2500
Description
We successfully sequenced and annotated more than 400 cells from child, adult control, type 1 diabetes and type 2 diabetes donors. We detect donor-type specific transcript variation. We also report that cells from child donors have less defined gene signature. Cells from type 2 diabetes donors resemble juvenile cells in gene expression. Overall design: Cells from three adult controls (56, 74, 92), one donor with type 1 diabetes (91), two donors with type 2 diabetes (75, 143), and two child donors (40, 72) were sequenced. Numbers in parathesis indicates number of cells sequenced.
Publication Title
Single-Cell Transcriptomics of the Human Endocrine Pancreas.
Sample Metadata Fields
Specimen part, Subject
View Samples- Mus musculus
- 924 Downloadable Samples
- NextSeq 500
Description
We report RNA-seq of single nuclei isolated from the adult C57BL/6 male mouse Hippocampus region. Majority of the nuclei were isolated from 12 weeks old mice (4 different animal), with an additional set of nuclei from 3 months and 2 years old animals. In addition a set of GFP labeled nuclei driven by a VGAT promoter . Overall design: Microdissections of dentate gyrus, CA1 and CA2/3 regions of the Hippocampus were placed into ice-cold RNA-later for fixation and stored at 4°c overnight, then stored in -80°c. Nuclei were isolated by sucrose gradient centrifugation and kept on ice until sorting using Fluorescence Activated Cell Sorting (FACS) into 96 well plates containing RNA lysis buffer. Single nucleus RNA was first purified then derived cDNA libraries were generated following a modified Smart-seq2 protocol. For VGAT nuclei: high titer AAV1/2 of pAAV-EF1a-DIO-EYFP-KASH-WPRE-hGH-polyA was injected into dorsal and/or ventral Hippocampus, animals were sacrificed two weeks after injections, and GFP labeled nuclei were sorted into plates and processed as described above.
Publication Title
Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons.
Sample Metadata Fields
Age, Cell line, Subject
View Samples- Homo sapiens
- 24 Downloadable Samples
Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
MicroRNAs (miRs) function primarily as post-transcriptional negative regulators of gene expression through binding to their mRNA targets. Reliable prediction of a miRs targets is a considerable bioinformatic challenge of great importance for inferring the miRs function. Sequence-based prediction algorithms have high false-positive rates, are not in agreement, and are not biological context specific. Here we introduce CoSMic (Context-Specific MicroRNA analysis), an algorithm that combines sequence-based prediction with miR and mRNA expression data. CoSMic differs from existing methodsit identifies miRs that play active roles in the specific biological system of interest and predicts with less false positives their functional targets. We applied CoSMic to search for miRs that regulate the migratory response of human mammary cells to epidermal growth factor (EGF) stimulation. Several such miRs, whose putative targets were significantly enriched by migration processes were identified. We tested three of these miRs experimentally, and showed that they indeed affected the migratory phenotype; we also tested three negative controls. In comparison to other algorithms CoSMic indeed filters out false positives and allows improved identification of context-specific targets. CoSMic can greatly facilitate miR research in general and, in particular, advance our understanding of individual miRs function in a specific context.
Publication Title
Context-specific microRNA analysis: identification of functional microRNAs and their mRNA targets.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 71 Downloadable Samples
- NextSeq 500
Description
During host-pathogen encounters, the complex interactions between different immune cell-types can determine the outcome of infection. Advances in single cell RNA-seq (scRNA-seq) allow to probe this complexity of immunity, and afforded the basis for deconvolution algorithms that infer cell-type compositions from bulk RNA-seq measurements. However, immune activation, an important aspect of immune surveillance, is not represented in current algorithms. Here, using scRNA-seq of human peripheral blood cells infected with Salmonella, we developed a novel deconvolution algorithm to infer dynamic immune states from bulk measurements. We applied our dynamic deconvolution algorithm both to cohorts of healthy individuals challenged ex vivo with Salmonella and to cohorts of tuberculosis patients during different stages of disease. We revealed cell-type specific immune responses associated not only with ex vivo infection phenotype but also with clinical disease stage. We propose that our approach provides a predictive power to identify risk for disease, and can be applied to comprehensively study human infection outcome. Overall design: PBMCs were isolated from 8 individuals bearing or not TLR10 polymorphism and were infected ex vivo with Salmonella enterica serovar Typhimurium. RNA was extracted before infection, 4 hours post infection and 8 hours post infection.
Publication Title
Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 62 Downloadable Samples
- NextSeq 500
Description
During host-pathogen encounters, the complex interactions between different immune cell-types can determine the outcome of infection. Advances in single cell RNA-seq (scRNA-seq) allow to probe this complexity of immunity, and afforded the basis for deconvolution algorithms that infer cell-type compositions from bulk RNA-seq measurements. However, immune activation, an important aspect of immune surveillance, is not represented in current algorithms. Here, using scRNA-seq of human peripheral blood cells infected with Salmonella, we developed a novel deconvolution algorithm to infer dynamic immune states from bulk measurements. We applied our dynamic deconvolution algorithm both to cohorts of healthy individuals challenged ex vivo with Salmonella and to cohorts of tuberculosis patients during different stages of disease. We revealed cell-type specific immune responses associated not only with ex vivo infection phenotype but also with clinical disease stage. We propose that our approach provides a predictive power to identify risk for disease, and can be applied to comprehensively study human infection outcome. Overall design: Whole-blood (WB) cells and PBMCs were isolated from 4 healthy individuals and were infected ex vivo with Salmonella enterica serovar Typhimurium or with PBS as control. RNA was extracted 4 hours later.
Publication Title
Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.
Sample Metadata Fields
Specimen part, Disease stage, Subject
View Samples