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accession-icon SRP067124
Comparative analysis of single-cell RNA sequencing methods
  • organism-icon Mus musculus
  • sample-icon 743 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500, Illumina HiSeq 2000, Illumina HiSeq 1500

Description

Single-cell RNA sequencing (scRNA-seq) offers new possibilities to address biological and medical questions. However, systematic comparisons of the performance of diverse scRNA-seq protocols are lacking. We generated data from 583 mouse embryonic stem cells to evaluate six prominent scRNA-seq methods: CEL-seq2, Drop-seq, MARS-seq, SCRB-seq, Smart-seq and Smart-seq2. While Smart-seq2 detected the most genes per cell and across cells, CEL-seq2, Drop-seq, MARS-seq and SCRB-seq quantified mRNA levels with less amplification noise due to the use of unique molecular identifiers (UMIs). Power simulations at different sequencing depths showed that Drop-seq is more cost-efficient for transcriptome quantification of large numbers of cells, while MARS-seq, SCRB-seq and Smart-seq2 are more efficient when analyzing fewer cells. Our quantitative comparison offers the basis for an informed choice among six prominent scRNA-seq methods and provides a framework for benchmarking further improvements of scRNA-seq protocols. Overall design: J1 mESC in two replicates per library preparation method.

Publication Title

A systematic evaluation of single cell RNA-seq analysis pipelines.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP108854
zUMIs: a fast and flexible pipeline for RNA sequencing data with UMIs
  • organism-icon Homo sapiens
  • sample-icon 81 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 1500

Description

Background Single-cell RNA-sequencing (scRNA-seq) experiments typically analyze hundreds or thousands of cells after amplification of the cDNA. The high throughput is made possible by the early introduction of sample-specific bar codes (BCs), and the amplification bias is alleviated by unique molecular identifiers (UMIs). Thus, the ideal analysis pipeline for scRNA-seq data needs to efficiently tabulate reads according to both BC and UMI. Findings zUMIs is a pipeline that can handle both known and random BCs and also efficiently collapse UMIs, either just for exon mapping reads or for both exon and intron mapping reads. If BC annotation is missing, zUMIs can accurately detect intact cells from the distribution of sequencing reads. Another unique feature of zUMIs is the adaptive downsampling function that facilitates dealing with hugely varying library sizes but also allows the user to evaluate whether the library has been sequenced to saturation. To illustrate the utility of zUMIs, we analyzed a single-nucleus RNA-seq dataset and show that more than 35% of all reads map to introns. Also, we show that these intronic reads are informative about expression levels, significantly increasing the number of detected genes and improving the cluster resolution. Conclusions zUMIs flexibility makes if possible to accommodate data generated with any of the major scRNA-seq protocols that use BCs and UMIs and is the most feature-rich, fast, and user-friendly pipeline to process such scRNA-seq data. Overall design: HEK293T cells were sequenced using the mcSCRB-seq protocol (Bagnoli et al., 2017)

Publication Title

zUMIs - A fast and flexible pipeline to process RNA sequencing data with UMIs.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP067154
Sequencing Universal Human Reference RNA by Smart-seq and early barcoding library preparation methods
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq1500

Description

Many library preparation methods are available for gene expression quantification. Here, we sequenced and analysed Universal Human Reference RNA (UHRR) prepared using Smart-Seq2, TruSeq (public data) and a protocol using unique molecular identifiers (UMIs) that all include the ERCC spike-in mRNAs to investigate the effects of amplification bias on expression quantification. Overall design: UHRR 10 and 12 replicates for Smart-seq2 and UMI-seq library preparation methods, respectively.

Publication Title

The impact of amplification on differential expression analyses by RNA-seq.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP049391
Next-Generation Sequencing Analysis Reveals Differential Expression Profiles of miRNA-mRNA Target Pairs in KSHV-Infected Cells [mRNA-Seq]
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

This SuperSeries is composed of the SubSeries listed below. Purpose: Kaposi’s sarcoma (KS)-associated herpesvirus (KSHV) causes several lymphoproliferative disorders, including KS, a common AIDS-associated malignancy. Cellular and viral microRNAs (miRNAs) have been shown to play important roles in regulating the expression of genes in oncogenesis. Herpesviruses, including KSHV, encode for miRNAs that are involved in angiogenesis, inflammation and apoptosis. A better knowledge of the miRNA-mediated pathways that regulate KSHV infection is therefore essential for an improved understanding of viral infection and pathogenesis. Methods: In this study, we used deep sequencing to analyze miRNA, both viral and human, and mRNA expression in KS tumor-derived human cells. Results: This approach revealed 153 differentially expressed human miRNAs between KSHV-positive and -negative cells. Differential expression of eight miRNAs was independently confirmed by qRT-PCR. We additionally showed that a majority (~73%) of KSHV-regulated miRNAs are down-regulated, including most members of the 14q32 miRNA cluster. Specifically, human miR-409-3p, which is known to target the pro-angiogenic growth factor angiogenin and the inflammation marker fibrinogen-beta, was significantly down-regulated in KSHV-infected cells based on deep sequencing and qRT-PCR. Despite this substantial down-regulation of cellular miRNAs, hsa-miR-708-5p was significantly up-regulated by KSHV and has been shown to directly inhibit pro-apoptotic protease Caspase-2. Finally, we evaluated to what extent there was an inverse correlation between miRNA and mRNA expression levels. Using filtered datasets, we identified relevant canonical pathways that were significantly enriched. Conclusion: Taken together, our data demonstrate that most human miRNAs affected by KSHV are repressed and our findings highlight the relevance of studying the post-transcriptional gene regulation of miRNAs for KSHV-associated malignancies. Overall design: Refer to individual Series. 6 samples analyzed (one cell type). Two experimental conditions: uninfected vs. chronically KSHV-infected cells (n=3). Two sequencing platforms: microRNA-Seq and mRNA-Seq.

Publication Title

Next-Generation Sequencing Analysis Reveals Differential Expression Profiles of MiRNA-mRNA Target Pairs in KSHV-Infected Cells.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP027508
Impact of genomic polymorphisms on the repertoire of human MHC class I-associated peptides
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

We developed a novel approach combining next generation sequencing, bioinformatics and mass spectrometry to assess the impact of non-MHC polymorphisms on the repertoire of MHC I-associated peptides (MIPs). We compared the genomic landscape of MIPs eluted from B lymphoblasts of two MHC-identical siblings and determined that MIPs mirror the genomic frequency of non-synonymous polymorphisms but they behave as recessive traits at the surface level. Moreover, we showed that 11.7% of the MIP coding exome is polymorphic at the population level. Our method provides fundamental insights into the relation between the genomic self and the immune self and accelerates the discovery of polymorphic MIPs (also known as minor histocompatibility antigens), which play a major role in allo-immune responses. Overall design: RNA-seq of human B lymphoblasts derived from peripheral blood mononuclear cells from 2 HLA-identical female siblings.

Publication Title

Impact of genomic polymorphisms on the repertoire of human MHC class I-associated peptides.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE8772
KINK-1, a novel small-molecule inhibitor of IKKbeta, enhances susceptibility of melanoma cells to antitumoral treatment
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Interference with chemoresistance to enhance the efficacy of chemotherapeutics may be of great utility for cancer therapy. We have identified KINK-1 (Kinase Inhibitor of NF-kappaB-1), a highly selective small-molecule IKKkappa inhibitor, as a potent suppressor of both constitutive and induced NF-kappaB activity in melanoma cells. While KINK-1 profoundly diminished various NF-kappaB-dependent gene products regulating proliferation, cytokine production or anti-apoptotic responses, the compound by itself showed little antiproliferative or pro-apoptotic activity on the cellular level. However, its combination with some cytostatics markedly enhanced their antitumoral activities in vitro, and doxorubicin-induced NF-kappaB activation, a mechanism implicated in chemoresistance, was abrogated by KINK-1. In addition, when KINK-1 was combined with doxorubicin in an in vivo melanoma model, experimental metastasis was significantly diminished as compared to either treatment alone. Induction of chemoresistance by KINK-1 in vivo was not observed. Thus, KINK-1 or related substances might increase the susceptibility of tumors to chemotherapy.

Publication Title

KINK-1, a novel small-molecule inhibitor of IKKbeta, and the susceptibility of melanoma cells to antitumoral treatment.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE72518
Gene expression profiling of M0, M1 and M2a macrophages after 7 days of culture
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The relative contribution of polarized macrophages to the maintenance of tolerance is unknown. We examined their roles by in vivo adoptive transfer immunotherapy of M0, M1 and M2a macrophages as pre-treatment of colitis. In other experiments, M2a macrophages were used as pre-treatment or treatment of established colitis followed by immunotherapy with nTreg cells. Survival, weight gain, tissue infiltration, iTreg and Th17 cell development, T cell activation, and the frequency of proinflammatory cytokines were used as outcome measurements. Pre-treatment with M2a but not M1 macrophages increased the development of iTreg and Th17 cells. M2a macrophages used as pre-treatment or in treatment of established colitis allowed for successful therapy with nTreg cells.

Publication Title

Alternatively Activated Macrophages Boost Induced Regulatory T and Th17 Cell Responses during Immunotherapy for Colitis.

Sample Metadata Fields

Age, Specimen part

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accession-icon SRP176670
G1E cells infected with control (HMD empty vector), human GATA1, or human GATA1 mutant cDNA
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

G1E cells infected with control (HMD empty vector), human GATA1, or human GATA1 mutant cDNA Overall design: 3 Biological replicates per condition for RNA-seq

Publication Title

Impaired human hematopoiesis due to a cryptic intronic <i>GATA1</i> splicing mutation.

Sample Metadata Fields

Cell line, Subject

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accession-icon E-MEXP-1269
Transcription profiling by array of three human multiple myeloma cell lines treated with 5-aza-2-deoxycytidine and/or trichostatin A
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

To identify epigenetically silenced genes in multiple myeloma (MM) cell lines and to determine the effects of 5-aza-2-deoxycytidine and trichostatin A on gene expression. We treated 3 multiple myeloma cell lines (MM1, NCI-H929, U266) with 5-aza-2-deoxycytidine and/or trichostatin A.

Publication Title

Genome-wide transcriptional response to 5-aza-2'-deoxycytidine and trichostatin a in multiple myeloma cells.

Sample Metadata Fields

Specimen part, Disease, Cell line

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accession-icon GSE35543
Gene expression profiling of in vitro derived induced and natural FOXP3+ regulatory T cells and ex-iTreg cells in the mouse
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Induced Treg (iTreg) cells are essential for tolerance and can be used therapeutically, yet their stability in vivo and mechanisms of suppression are unresolved. Here, we used a treatment model of colitis to examine the role of autologous IL-10 in iTreg cell function. Mice treated with IL-10+/+ iTreg cells in combination with IL-10/ natural Treg (nTreg) cells survived and gained weight, even though iTreg cells were numerically disadvantaged and comprised just ~20% of all Treg cells in treated mice. Notably, ~85% of the transferred iTreg cells lost Foxp3 expression (ex-iTreg) but retained a portion of the iTreg transcriptome which failed to limit their pathogenic potential. The TCR repertoires of iTreg and ex-iTreg cells exhibited almost no overlap, which indicates that the two populations are clonally unrelated and maintained by different selective pressures. These data demonstrate a potent and critical role for iTreg cell produced IL-10 that can supplant the IL-10 produced by nTreg cells and compensate for the inherent instability of the iTreg population.

Publication Title

IL-10 produced by induced regulatory T cells (iTregs) controls colitis and pathogenic ex-iTregs during immunotherapy.

Sample Metadata Fields

Treatment

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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