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accession-icon SRP091680
Assessing characteristics of RNA amplification methods for single cell RNA sequencing
  • organism-icon Homo sapiens
  • sample-icon 124 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Illumina HiSeq 2500

Description

We conducted a large-scale control experiment to assess the transfer function of three scRNA-seq methods and factors modulating the function. Our approach was to dilute bulk total RNA (from a single source) to levels bracketing single-cell levels of total RNA (10 pg and 100 pg) in replicates and amplifying the RNA to levels sufficient for RNA sequencing. Overall design: We performed replicate transcriptome amplifications of Universal Human Reference RNA (UHR) and Human Brain Reference RNA (HBR) that were diluted to single-cell and ten-cell abundances (10 and 100 picograms (pg.) total RNA or ~200,000 and 2 million mRNA molecules, respectively) and were amplified using three single-cell RNA amplification methods. Methods included the antisense RNA IVT protocol (aRNA), a custom C1 SMARTer protocol (SmartSeq Plus) performed on a Fluidigm C1 96-well chip, and a modified NuGen Ovation RNA sequencing protocol (NuGen). Bulk ribo-depleted UHR and HBR RNA were sequenced and served as a reference. The general experimental scheme was consistent for all dilution replicates; however, there were differences across experimental groups in the specifics of experimental protocols, necessitated by particular methodologies. Because of these experimental differences, head-to-head comparison of methods is not appropriate and our goal is to provide quantitative analyses of factors affecting individual methods. Current results should be used in experimental planning, data analysis, and method optimization rather than as a performance test of any particular method. Detailed experimental design: Each collaborating center obtained reference RNA with the same lot number for Universal Human Reference (UHR) RNA (Agilent 740000, Lot 0006141415) and Human Brain Reference (HBR) (Ambion AM6050, Lot-105P055201A) and performed replicate amplification using a single amplification method, detailed below. SmartSeq Plus: Reference RNA was diluted to an intermediate stock solution by serial dilution. A final 1000-fold dilution occurred on the C1 chip, such that individual wells in a given batch contained 9.99 pg. sampled from a common intermediate dilution. ERCC spike-in RNA mix 1 (Ambion 4456740) was also added for a final mass of approximately 7 femtograms (fg.) per sample, a 4,000,000x dilution from stock. Samples for each source RNA were prepared in single batches. After amplification, cDNA from the entire C1 96-well plate was quantified using picogreen. C1 chips with an average yield of less than 3 nanograms were discarded. The top 15 reactor wells by cDNA concentration were selected as representative 10 pg. samples for sequencing library preparation. Another 50 wells were selected by the same criteria. These were pooled in sets of 10, generating 5 100 pg. samples for each HBR and UHR. All samples for a given source were prepared in a single sequencing library preparation batch using Nextera XT C1 protocol. NuGen: HBR samples were prepared in a single batch using amplification protocol 1, generating 4 10 pg. and 4 100 pg. amplified replicates. UHR samples were prepared in two batches, using either amplification protocol 1 or 2, generating 15 10 pg. and 11 100 pg. samples. A single sequencing library preparation was performed for each batch of samples using either Lucigen NxSeq or NuGen Ovation Rapid protocol. aRNA: Amplification was performed as previously described (Morris J, Singh JM, Eberwine JH. Transcriptome analysis of single cells. J. Vis. Exp. [Internet]. 2011; Available from: http://www.jove.com/video/2634/transcriptome-analysis-of-single-cells). HBR samples were prepared in 4 batches from separate dilutions of reference RNA, generating 19 10 pg. and 3 100 pg. amplified replicates. ERCC spike-ins were added to 5 of the 10 pg. replicates before amplification at a dilution of 4,000,000x from stock. UHR samples were diluted and amplified in 2 batches from separate dilutions of reference RNA, generating 12 10 pg. and 7 100 pg. amplified replicates. A single sequencing library preparation was performed using Illumina TruSeq Stranded mRNA protocol modified to begin with amplified aRNA. A small numbers of reads were assigned to ERCC transcripts in replicates from the batch where ERCCs had been added that did not have spike-ins added (average of 0.5% of the number of reads assigned in spiked samples). 18 additional HBR 10 pg. replicates were amplified using aRNA for protocol optimization experiments. These samples were treated separately and were excluded from primary analysis. Bulk UHR and HBR: For each reference RNA, three sequencing libraries were generated from bulk material at the same laboratory as the SmartSeq Plus replicates. Cytoplasmic and mitochondrial ribosomal RNA (rRNA) were depleted using Ribo-Zero Gold as part of Illumina TruSeq Stranded Total RNA protocol. Samples were sequenced on Illumina HiSeq 2000. Because of differences in experimental design, direct comparison across methods of precision and the effect of input RNA abundance is difficult. For example, input RNA amount as a factor have different meanings for the different amplification methods: for SmartSeq Plus, because 100pg samples were constructed by pooling 10 pg. samples after cDNA amplification, any resulting effects involve library construction, while for aRNA and NuGen resulting effects reflect both cDNA amplification steps and library steps.

Publication Title

Assessing characteristics of RNA amplification methods for single cell RNA sequencing.

Sample Metadata Fields

Subject

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accession-icon GSE24986
Response of A549 cells treated with Aspergillus fumigatus
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

PrtT-regulated proteins secreted by Aspergillus fumigatus activate MAPK signaling in exposed A549 lung cells leading to necrotic cell death.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE24984
Response of A549 cells treated with Aspergillus fumigatus [WT-GC_vs_PrtT-GC]
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Response of A549 cells treated with Aspergillus fumigatus wild type germinating conidia (WT_GC) or PrtT protease deficient mutant conidia (PrtT-GC) or inert acrylic 2-4 micron beads (Beads) for 8h

Publication Title

PrtT-regulated proteins secreted by Aspergillus fumigatus activate MAPK signaling in exposed A549 lung cells leading to necrotic cell death.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE24985
Response of A549 cells treated with Aspergillus fumigatus [WT-CF_vs_PrtT-CF]
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Response of A549 cells treated with Aspergillus fumigatus wild type culture filtrate (WT-CF) or PrtT protease deficient mutant culture filtrate (PrtT-CF) for 8h

Publication Title

PrtT-regulated proteins secreted by Aspergillus fumigatus activate MAPK signaling in exposed A549 lung cells leading to necrotic cell death.

Sample Metadata Fields

Specimen part, Cell line, Treatment

View Samples
accession-icon GSE24983
Response of A549 cells treated with Aspergillus fumigatus [WT-CF_vs_WT-GC]
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Response of A549 cells treated with Aspergillus fumigatus germinating conidia (WT-GC) or culture filtrate (WT-CF) for 8h

Publication Title

PrtT-regulated proteins secreted by Aspergillus fumigatus activate MAPK signaling in exposed A549 lung cells leading to necrotic cell death.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE28044
Expression data from non-malignant fallopian tube epithelium
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Microarrays were used to examine gene expression changes that may be present in the fallopian tube epithelium of morphologically normal BRCA1 mutation positive and negative subjects. Fallopian tube epithelia has been implicated as an early point of origin for serous carcninoma. By examining the early events present in the microenvironment of this tissue between BRCA1 mutation carriers and non-carriers, we hoped to elucidate mechanisms that may lead to the development of epithelial ovarian cancer.

Publication Title

Identification of abrogated pathways in fallopian tube epithelium from BRCA1 mutation carriers.

Sample Metadata Fields

Specimen part

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accession-icon SRP096589
Gene signature profiles in respiratory epithelium infected with nontuberculous mycobacteria
  • organism-icon Homo sapiens
  • sample-icon 44 Downloadable Samples
  • Technology Badge Icon

Description

The incidence of pulmonary nontuberculous mycobacterial (PNTM) disease is increasing, but host susceptibility factors are not fully understood. We infected air-liquid interface (ALI) primary respiratory epithelial cell cultures with Mycobacterium avium complex (MAC) or Mycobacterium abscessus (MAB) and performed transcriptome sequencing (RNA-Seq) to identify relevant gene expression differences. We used cells from 4 different donors in order to try to obtain generalizable data. The differentiated respiratory epithelial cells in ALI were infected with MAC or MAB at MOI of 100:1 or 1000:1, and RNA-seq was performed at 1 and 3 days after infection. We found downregulation of ciliary genes, including several identified with polymorphisms in previous PNTM cohorts. The cytokine IL-32, the superpathway of cholesterol biosynthesis and downstream targets within the IL-17 signaling pathway were all elevated. The integrin signaling pathway was more upregulated by MAB than MAC infection. Working with primary respiratory epithelial cells infected with nontuberculous mycobacteria at ALI, we identified ciliary function, cholesterol biosynthesis, chemokine production and the IL-17 pathway as major targets of host responses to infection. Some of these pathways may be amenable to therapeutic manipulation. Overall design: 44 strand-specific RNA libraries for high-throughput sequencing were prepared (samples from 4 different donors, 57F, 75M, 69F, and 42F, for each condition) using the TruSeq Stranded mRNA Sample Preparation Kit with 750ng of total RNA according to manufacturer's instructions.

Publication Title

Transcriptional Response of Respiratory Epithelium to Nontuberculous Mycobacteria.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP048798
Transcription factor Oct1 and its coactivator OCA-B are selectively required for CD4 memory T cell formation and function
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

Epigenetic changes are crucial for the generation of immunological memory1-4. Failure to generate or maintain these changes will result in poor memory responses. Similarly, augmenting or stabilizing the correct epigenetic states offers a potential method of enhancing immune memory. Yet the transcription factors that regulate these processes are poorly defined, as are the chromatin modifying complexes they recruit and the chromatin modifications they control. Using pathogen infection models and three different mouse models, including a new conditional allele, we find that the widely expressed transcription factor Oct15, and its cofactor OCA-B6,7, are selectively required the in vivo generation of functional CD4 memory. In vitro, both proteins are also required to maintain a poised state at the Il2 target locus in resting but previously stimulated CD4 T cells, and to generate robust Il2 expression upon restimulation. OCA-B is also required for the robust re-expression of other known targets including Il17a, and Ifng. We identify an underlying mechanism involving OCA-B recruitment of the histone lysine demethylase Jmjd1a8 to targets such as Il2 and Ifng. The findings pinpoint Oct1 and OCA-B as unanticipated mediators of CD4 T cell memory. Overall design: Examination of 4 different conditions in 2 genotypes

Publication Title

Oct1 and OCA-B are selectively required for CD4 memory T cell function.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE72359
p53 amplifies Toll-like receptor 5 response in MCF-7 cells
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Using gene expression profiling we characterize the global effect of p53 on the TLR5-mediated transcription in MCF7 cells. We found that combined activation of p53 and TLR5 pathways synergistically increases expression of over 200 genes, mostly associated with immunity and inflammation. The synergy was observed in several human cancer cells and primary lymphocytes.

Publication Title

p53 amplifies Toll-like receptor 5 response in human primary and cancer cells through interaction with multiple signal transduction pathways.

Sample Metadata Fields

Cell line

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accession-icon SRP035393
Widespread inhibition of post-transcriptional splicing shapes the cellular transcriptome following heat shock
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

Heat shock timecourse RNAseq, 3T3 cells

Publication Title

Widespread inhibition of posttranscriptional splicing shapes the cellular transcriptome following heat shock.

Sample Metadata Fields

No sample metadata fields

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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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