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Homo sapiens
135 Downloadable Samples
NextSeq 500
Description
Multiple myeloma (MM), a plasma cell (PC) malignancy, is the second most common blood cancer. Despite extensive research, disease heterogeneity within and between patients is poorly characterized, hampering efforts for early diagnosis and improved treatments. Here, we apply single cell RNA-seq to study the heterogeneity of 40 individuals along the MM progression spectrum. We define malignant PC at single cell resolution, demonstrating high inter-patient variability that can be explained by expression of known MM drivers and additional putative factors. Within newly diagnosed patients, we identify extensive sub-clonal structures for 10/29 patients. In asymptomatic patients with early disease and in minimal residual disease post-treatment, we detect tumor PC for a subset of the patients, with the same drivers of active myeloma. Single cell analysis of rare circulating tumor cells (CTC) allows detection of malignant PC, which reflect the BM disease. Our work establishes scRNA-seq for dissecting blood malignancies and devising detailed molecular characterization of tumor cells in symptomatic and asymptomatic patients. Overall design: The study includes 29 newly diagnosed patients with plasma cell neoplasms and 11 control donors, for which bone marrow plasma cells were single cell sorted by FACS, and their mRNA sequenced. For 11 patients, targeted genomic DNA panel analysis for myeloma was performed.
Publication Title
Single cell dissection of plasma cell heterogeneity in symptomatic and asymptomatic myeloma.
Sample Metadata Fields
Specimen part, Treatment, Subject
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- Homo sapiens
- 13 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 a healthy individual and were infected ex vivo with Salmonella enterica serovar Typhimurium or with PBS as control. Monocytes and NKT cells were sorted from naïve and infected PBMCs. RNA was extracted 4 hours post infection.
Publication Title
Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.
Sample Metadata Fields
Subject
View Samples- Homo sapiens
- 12 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: Frozen PBMCs from healthy individual were defrosted and infectd ex vivo with Salmonella enterica serovar Typhimurium.
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
- 300 Downloadable Samples
Affymetrix Human Exon 1.0 ST Array [HuEx_1_0_st_v2.na29.hg18.RefSeq-core (huex10st)
Description
We assessed genome-wide expression of available pretreatment specimens from CLL patients enrolled in REACH, a study of fludarabine and cyclophosphamide FC or R-FC (addition of rituximab to FC) in relapsed CLL, to understand the disease heterogeneity and explore genes that may be prognostic or predictive of benefit from R-FC treatment. REACH (NCT00090051) was registered at www.clinicaltrials.gov.
Publication Title
PTK2 expression and immunochemotherapy outcome in chronic lymphocytic leukemia.
Sample Metadata Fields
Specimen part, Disease stage, Subject
View Samples
GSE60304- Rattus norvegicus
- 59 Downloadable Samples
- Illumina ratRef-12 v1.0 expression beadchip
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Expression profiling associates blood and brain glucocorticoid receptor signaling with trauma-related individual differences in both sexes.
Sample Metadata Fields
Sex, Specimen part
View Samples- Rattus norvegicus
- 29 Downloadable Samples
- Illumina ratRef-12 v1.0 expression beadchip
Description
Delineating the molecular basis of individual differences in the stress response is critical to understanding the pathophysiology and treatment of posttraumatic stress disorder (PTSD). In this study, 7 d after predator-scent-stress (PSS) exposure, male and female rats were classified into vulnerable (i.e., PTSD-like) and resilient (i.e.,minimally affected) phenotypes on the basis of their performance on a variety of behavioral measures. Genome-wide expression profiling in blood and two limbic brain regions (amygdala and hippocampus), followed by quantitative PCR validation, was performed in these two groups of animals, as well as in an unexposed control group. Differentially expressed genes were identified in blood and brain associated with PSS-exposure and with distinct behavioral profiles postexposure. There was a small but significant between-tissue overlap (421%) for the genes associated with exposure-related individual differences, indicating convergent gene expression in both sexes. To uncover convergent signaling pathways across tissue and sex, upstream activated/deactivated transcription factorswere first predicted for each tissue and then the respective pathways were identified. Glucocorticoid receptor (GR) signaling was the only convergent pathway associatedwith individual differences when using the most stringent statistical threshold.
Publication Title
Expression profiling associates blood and brain glucocorticoid receptor signaling with trauma-related individual differences in both sexes.
Sample Metadata Fields
Sex, Specimen part
View Samples- Rattus norvegicus
- 30 Downloadable Samples
- Illumina ratRef-12 v1.0 expression beadchip
Description
Delineating the molecular basis of individual differences in the stress response is critical to understanding the pathophysiology and treatment of posttraumatic stress disorder (PTSD). In this study, 7 d after predator-scent-stress (PSS) exposure, male and female rats were classified into vulnerable (i.e., PTSD-like) and resilient (i.e.,minimally affected) phenotypes on the basis of their performance on a variety of behavioral measures. Genome-wide expression profiling in blood and two limbic brain regions (amygdala and hippocampus), followed by quantitative PCR validation, was performed in these two groups of animals, as well as in an unexposed control group. Differentially expressed genes were identified in blood and brain associated with PSS-exposure and with distinct behavioral profiles postexposure. There was a small but significant between-tissue overlap (421%) for the genes associated with exposure-related individual differences, indicating convergent gene expression in both sexes. To uncover convergent signaling pathways across tissue and sex, upstream activated/deactivated transcription factorswere first predicted for each tissue and then the respective pathways were identified. Glucocorticoid receptor (GR) signaling was the only convergent pathway associatedwith individual differences when using the most stringent statistical threshold.
Publication Title
Expression profiling associates blood and brain glucocorticoid receptor signaling with trauma-related individual differences in both sexes.
Sample Metadata Fields
Sex, Specimen part
View Samples- Arabidopsis thaliana
- 23 Downloadable Samples
- Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)
Description
A prominent enzyme in organellar RNA metabolism is the exoribonuclease polynucleotide phosphorylase (PNPase), whose reversible activity is governed by the nucleotides diphosphate-inorganic phosphate ratio. In Chlamydomonas reinhardtii, PNPase regulates chloroplast transcript accumulation in response to phosphorus (P) starvation, and PNPase expression is repressed by the response regulator PSR1 under these conditions. Here, we investigated the role of PNPase in the Arabidopsis (Arabidopsis thaliana) P deprivation response by comparing wild-type and pnp mutant plants with respect to their morphology, metabolite profiles, and transcriptomes. We found that P-deprived pnp mutants develop aborted clusters of lateral roots, which are characterized by decreased auxin responsiveness and cell division, and exhibit cell death at the root tips. Electron microscopy revealed that the collapse of root organelles is enhanced in the pnp mutant under P deprivation and occurred with low frequency under P-replete conditions. Global analyses of metabolites and transcripts were carried out to understand the molecular bases of these altered P deprivation responses. We found that the pnp mutant expresses some elements of the deprivation response even when grown on a full nutrient medium, including altered transcript accumulation, although its total and inorganic P contents are not reduced. The pnp mutation also confers P status-independent responses, including but not limited to stress responses. Taken together, our data support the hypothesis that the activity of the chloroplast PNPase is involved in plant acclimation to P availability and that it may help maintain an appropriate balance of P metabolites even under normal growth conditions.
Publication Title
Abnormal physiological and molecular mutant phenotypes link chloroplast polynucleotide phosphorylase to the phosphorus deprivation response in Arabidopsis.
Sample Metadata Fields
Age, Specimen part, Treatment
View Samples