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accession-icon GSE12826
Zebrafish 24hpf mutant sk8 gene expression
  • organism-icon Danio rerio
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Zebrafish Genome Array (zebrafish)

Description

The production of functional mRNA involves multiple steps including transcription initiation, elongation, and termination. spt5 encodes a conserved essential transcription elongation factor that controls RNAPII processivity in vitro and co-localizes with RNAPII in vivo.

Publication Title

Identification of Spt5 target genes in zebrafish development reveals its dual activity in vivo.

Alternate Accession IDs

E-GEOD-12826

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP059850
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of GMP)
  • organism-icon Mus musculus
  • sample-icon 123 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Alternate Accession IDs

GSE70240

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP059903
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq from CMP)
  • organism-icon Mus musculus
  • sample-icon 85 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Alternate Accession IDs

GSE70236

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP059844
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of bone marrow lineage-negative Sca1+ CD117+ cells)
  • organism-icon Mus musculus
  • sample-icon 88 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Alternate Accession IDs

GSE70244

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP059848
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Gfi1-/- GMP)
  • organism-icon Mus musculus
  • sample-icon 71 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Alternate Accession IDs

GSE70239

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP059873
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Irf8 KO GMP)
  • organism-icon Mus musculus
  • sample-icon 63 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Alternate Accession IDs

GSE70242

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP071150
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Gfi1-/- Irf8-/- GMP)
  • organism-icon Mus musculus
  • sample-icon 47 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Alternate Accession IDs

GSE78907

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP059847
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Gfi1-GFP GMP)
  • organism-icon Mus musculus
  • sample-icon 38 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Alternate Accession IDs

GSE70238

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP059904
Using single-cell RNA-Seq for unbiased analysis of developmental hierarchies (single cell RNA Seq of Irf8-GFP GMP)
  • organism-icon Mus musculus
  • sample-icon 37 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single cell RNA seq and bioinformatic analysis is used to characterize myeloid differentiation to uncover novel transcriptional networks and key drivers of hematoipoietic development Overall design: Single cell RNA seq of different hematopoietic populations integrated with Chip seq involving multiple markers

Publication Title

Single-cell analysis of mixed-lineage states leading to a binary cell fate choice.

Alternate Accession IDs

GSE70241

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP057586
Unbiased evaluation of cell-free amniotic fluid transcriptome of term and preterm infants to detect fetal maturity
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Objective: Amniotic fluid (AF) is a proximal fluid to the fetus containing higher amounts of cell-free fetal RNA/DNA than maternal serum, thereby making it a promising source for novel biomarker discovery of fetal development and maturation. Our aim was to compare AF transcriptomic profiles at different time points in pregnancy to demonstrate unique genetic signatures that would serve as potential biomarkers indicative of fetal maturation. Methods: We isolated AF RNA from 16 women at different time points in pregnancy: 4 from 18-24 weeks, 6 from 34-36 weeks, and 6 from at 39-40 weeks. RNA-sequencing was performed on cell-free RNA. Gene expression and splicing analyses were performed in conjunction with cell-type and pathway inference.  Results: Sample-level analysis at different time points in pregnancy yielded a strong correlation with cell types found in the intrauterine environment and fetal respiratory, digestive and external barrier tissues of the fetus, using high-confidence cellular molecular markers. While some genes and splice variants were present throughout pregnancy, an abundant number of transcripts were uniquely expressed at different time points in pregnancy and associated with distinct fetal co-morbidities (respiratory distress and gavage feeding), indicating fetal immaturity. Conclusions: The AF transcriptome exhibits unique cell- and organ-selective expression patterns at different time points in pregnancy that can potentially identify fetal organ maturity and predict neonatal morbidity. Developing novel biomarkers indicative of the maturation of multiple organ systems can improve upon our current methods of fetal maturity testing which focus solely on the lung, and better inform obstetrical decisions regarding delivery timing. Overall design: RNA-Seq from cell-free was used to idenitfy mRNA transcripts indicative of overall fetal maturity.

Publication Title

Systems biology evaluation of cell-free amniotic fluid transcriptome of term and preterm infants to detect fetal maturity.

Alternate Accession IDs

GSE68180

Sample Metadata Fields

No sample metadata fields

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