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accession-icon ERP003460
Influence of RNA extraction methods and library selection schemes on RNA-seq data
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Background: Gene expression analysis by RNA sequencing is now widely used in a number of applications surveying the whole transcriptomes of cells and tissues. The recent introduction of ribosomal RNA depletion protocols, such as RiboZero, has extended the view of the polyadenylated transcriptome to the poly(A)- fraction of the RNA. However, substantial amounts of intronic transcriptional activity has been reported in RiboZero protocols, raising issues regarding their potential nuclear origin and the impact on the actual sequence depth in exonic regions. Method: Using HEK293 human cells as source material, we assessed here the impact of the two commonly used RNA extraction methods and of the library construction protocols (rRNA depletion versus mRNA) on 1) the relative abundance of intronic reads and 2) on the estimation of gene expression values. Results: We benchmarked the rRNA depletion-based sequencing with a specific analysis of the cytoplasmic and nuclear transcriptome fractions, suggesting that the large majority of the intronic reads correspond to unprocessed nuclear transcripts rather than to independent transcriptional units. We show that Qiagen or TRIzol extraction methods retain differentially nuclear RNA species, and that consequently, rRNA depletion-based RNA sequencing protocols are particularly sensitive to the extraction methods. Conclusions: We could show that the combination of Trizol-based RNA extraction with rRNA depletion sequencing protocols led to the largest fraction of intronic reads, after the sequencing of the nuclear transcriptome. We discuss here the impact of the various strategies on gene expression and alternative splicing estimation measures. Further, we propose guidelines and a double selection strategy for minimizing the expression biases, without loss of information.

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP062613
Mus musculus endothelium RNA-Seq with Nova2 KDs
  • organism-icon Mus musculus
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

To comprehensively identify AS events regulated by Nova2 in endothelium, we performed high-throughput RNA sequencing (RNA-Seq) of two biological replicates of Nova2 knockdown and control ECs.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Specimen part, Cell line

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accession-icon SRP073927
Laquinimod treated splenocyte samples in EAE and Naive mice
  • organism-icon Mus musculus
  • sample-icon 109 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

No description.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Specimen part, Cell line, Treatment

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accession-icon SRP117955
Early pridopidine treatment in YAC128 Huntington disease mice
  • organism-icon Mus musculus
  • sample-icon 35 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

RNAseq of YAC128 mice treated with pridopidine

Publication Title

No associated publication

Sample Metadata Fields

Sex, Age, Specimen part, Cell line, Treatment

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accession-icon SRP135819
Zea mays Transcriptome or Gene expression Ears Meristem FACS RNA-seq
  • organism-icon Zea mays
  • sample-icon 31 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

FACS RNAseq of transgenic lines pWUS and pYAB

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

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accession-icon SRP194257
Caenorhabditis elegans pathogenic learning confers multigenerational pathogen avoidance
  • organism-icon Caenorhabditis elegans
  • sample-icon 25 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Raw sequence reads are provided for RNA-seq of parental and transgenerational worms in which the P0 were treated with OP50 (control) or PA14.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Specimen part, Cell line

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accession-icon SRP151483
Caenorhabditis elegans strain:Bristol (N2) Raw sequence reads
  • organism-icon Caenorhabditis elegans
  • sample-icon 23 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Identifying transcriptional changes in adults, whose biology and behavior differsubstantially from developing animals, is important when evaluating adult phenotypes.Moreover, cell- and tissue-specific information is critical for understanding the biologyof multicellular animals. We used adult cell-specific isolation to identify thetranscriptomes of C. elegans'' major adult tissues (muscle, intestine, epidermis, andneurons).

Publication Title

No associated publication

Sample Metadata Fields

Sex, Specimen part, Cell line

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accession-icon SRP067305
Mus musculus RNA-SEQ raw sequence reads
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We evaluated the therapeutic activity of the modified U1 particles in a mouse model affected by severe spinal muscular atrophy. ExSpeU1 introduced by germline transgenesis efficiently rescued the phenotype increasing SMN2 exon 7 splicing, SMN protein production and radically extending the life span.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Cell line

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accession-icon SRP006674
ChipSeq of FoxP3 bound regions and mRNAseq data of human Treg and CD4+ Th cells
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerII

Description

Regulatory T-cells (Treg) play an essential role in the negative regulation of immune answers by developing an attenuated cytokine response that allows suppressing proliferation and effector function of T-cells (CD4+ Th). The transcription factor FoxP3 is responsible for the regulation of many genes involved in the Treg gene signature. Its ablation leads to severe immune deficiencies in human and mice. Recent developments in sequencing technologies have revolutionized the possibilities to gain insights into transcription factor binding by ChiP-Seq and into transcriptome analysis by mRNA-Seq. We combine FoxP3 ChiP-Seq and mRNA-Seq in order to understand the transcriptional differences between primary human CD4+ T helper and regulatory T-cells, as well as to study the role of FoxP3 in generating those differences. We show, that mRNA-Seq allows analyzing the transcriptomal landscape of T-cells including the expression of specific splice variants at much greater depth than previous approaches, whereas 50% of transcriptional regulation events have not been described before by using diverse array technologies.

Publication Title

Next-generation insights into regulatory T cells: expression profiling and FoxP3 occupancy in Human.

Sample Metadata Fields

No sample metadata fields

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accession-icon ERP005289
RNASeq analysis of embryonic day 13.5 mouse cerebral cortex from control and Pax6-deleted embryos
  • organism-icon Mus musculus
  • sample-icon 180 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Mice carrying embryos that were either Pax6fl/fl;Emx1CreER (experimental group) or Pax6fl/+;Emx1CreER (control group) were given tamoxifen on embryonic day 9.5 (E9.5) to induce Pax6 deletion. Embryos were harvested on E13.5, the cerebral cortices were removed and divided into rostral and caudal halves, and total RNA was extracted. Samples from littermates of the same genotype were pooled. Poly-A mRNA was purified and TruSeq RNA-Seq libraries were prepared and sequenced (100 base paired-end; Illumina, HiSeq v3).

Publication Title

No associated publication

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)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

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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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