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accession-icon GSE102972
Transcriptional response to a prime/boost vaccination of chickens with three vaccine variants based on HA DNA and Pichia-produced HA protein
  • organism-icon Gallus gallus
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Chicken Gene 1.1 ST Array (chigene11st)

Description

Broilers were immunized with three variants of subunit vaccines, based on the hemagglutinin (HA) DNA and Pichia-produced HA protein from H5N1 virus, in comparison to the control group, which was administered an empty vector (pCI). Gene expression changes in the spleens of chickens were investigated at 7 day post booster dose.

Publication Title

Transcriptional response to a prime/boost vaccination of chickens with three vaccine variants based on HA DNA and Pichia-produced HA protein.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon SRP145502
AmpliSeq Transcriptome Analysis of Human Alveolar and Monocyte-Derived Macrophages Over Time in Response to Mycobacterium tuberculosis infection
  • organism-icon Homo sapiens
  • sample-icon 48 Downloadable Samples
  • Technology Badge IconIon Torrent Proton

Description

Human alveolar macrophages (HAM) are primary bacterial niche and immune response cells during Mycobacterium tuberculosis (M.tb) infection, and human blood monocyte-derived macrophages (MDM) are a model for investigating M.tb-macrophage interactions. Here, we use a targeted RNA-Seq method to measure transcriptome-wide changes in RNA expression patterns of freshly obtained HAM (used within 6 h) and 6 day cultured MDM upon M.tb infection over time (2, 24 and 72 h), in both uninfected and infected cells from three donors each. The Ion AmpliSeqâ„¢ Transcriptome Human Gene Expression Kit (AmpliSeq) uses primers targeting 18,574 mRNAs and 2,228 non-coding RNAs (ncRNAs) for a total of 20,802 transcripts. AmpliSeqTM yields highly precise and reproducible gene expression profiles (R2 >0.99). Taking advantage of AmpliSeq's reproducibility, we establish well-defined quantitative RNA expression patterns of HAM versus MDM, including significant M.tb-inducible genes, in networks and pathways that differ in part between MDM and HAM. A similar number of expressed genes are detected at all time-points between uninfected MDM and HAM, in common pathways including inflammatory and immune functions, but canonical pathway differences also exist. In particular, at 2 h, multiple genes relevant to the immune response are preferentially expressed in either uninfected HAM or MDM, while the HAM RNA profiles approximate MDM profiles over time in culture, highlighting the unique RNA expression profile of freshly obtained HAM. MDM demonstrate a greater transcriptional response than HAM upon M.tb infection, with 2 to >10 times more genes up- or down-regulated. The results identify key genes involved in cellular responses to M.tb in two different human macrophage types. Follow-up bioinformatics analysis indicates that approximately 30% of response genes have expression quantitative trait loci (eQTLs in GTEx), common DNA variants that can influence host gene expression susceptibility or resistance to M.tb, illustrated with the TREM1 gene cluster and IL-10. Overall design: Assessment of transcriptome profiles from cells infected with Mycobacterium tuberculosis using AmpliSeq.

Publication Title

AmpliSeq transcriptome analysis of human alveolar and monocyte-derived macrophages over time in response to Mycobacterium tuberculosis infection.

Sample Metadata Fields

Specimen part, Treatment, Subject, Time

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accession-icon SRP055413
Allele-selective Transcriptome Recruitment to Polysomes Primed for Translation: Protein-coding and Noncoding RNAs, and RNA Isoforms
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIonTorrentProton

Description

Purpose: mRNA translation into protein is highly regulated, but the role of mRNA isoforms, noncoding RNAs (ncRNAs), and genetic variants has yet to be systematically studied. Using high-throughput sequencing (RNA-seq), we have measured cellular levels of mRNAs and ncRNAs, and their isoforms, in lymphoblast cell lines (LCL) and in polysomal fractions, the latter shown to yield strong correlations of mRNAs with expressed protein levels. Analysis of allelic RNA ratios at heterozygous SNPs served to reveal genetic factors in ribosomal loading. Methods: RNA-seq was performed on cytosolic extracts and polysomal fractions (3 ribosomes or more) from three lymphoblastoid cell lines. As each RNA fraction was amplified (NuGen kit), and relative contributions from various RNA classes differed between cytosol and polysomes, the fraction of any given RNA species loaded onto polysomes was difficult to quantitate. Therefore, we focused on relative recovery of the various RNA classes and rank order of single RNAs compared to total RNA. Results: RNA-seq of coding and non-coding RNAs (including microRNAs) in three LCLs revealed significant differences in polysomal loading of individual RNAs and isoforms, and between RNA classes. Moreover, correlated distribution between protein-coding and non-coding RNAs suggests possible interactions between them. Allele-selective RNA recruitment revealed strong genetic influence on polysomal loading for multiple RNAs. Allelic effects can be attributed to generation of different RNA isoforms before polysomal loading or to differential loading onto polysomes, the latter defining a direct genetic effect on translation. Several variants and genes identified by this approach are also associated with RNA expression and clinical phenotypes in various databases. Conclusions: These results provide a novel approach using complete transcriptome RNA-seq to study polysomal RNA recruitment and regulatory variants affecting protein translation. Overall design: cells from 3 samples were grown to 5x105 cells/mL density in T75 tissue culture flask and harvested, total RNA and polysome bound RNA was sequenced by Ion Proton

Publication Title

Allele-Selective Transcriptome Recruitment to Polysomes Primed for Translation: Protein-Coding and Noncoding RNAs, and RNA Isoforms.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP069869
Gene expression profiling of Drosophila melanogaster 30 minutes after alcohol exposure
  • organism-icon Drosophila melanogaster
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

We sequenced mRNA extracted from heads of a D. melanogaster population that was sedated with a stream of ethanol saturated vapor, 30 minutes before RNA extraction; and from an age-matched untreated control group. Differential gene expression between the two groups was calculated and reported. Overall design: Examination of mRNA levels in heads of D. melanogaster adult females after ethanol exposure was performed using next generation sequencing (NGS) technology.

Publication Title

Alcohol resistance in Drosophila is modulated by the Toll innate immune pathway.

Sample Metadata Fields

Cell line, Treatment, Subject

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accession-icon GSE87493
Gene expression in blood of obese pediatric patients
  • organism-icon Homo sapiens
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Differences between groups of children with obesity and healthy controls.

Publication Title

Looking for new diagnostic tools and biomarkers of hypertension in obese pediatric patients.

Sample Metadata Fields

Specimen part, Disease

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accession-icon GSE22207
Identification of promoter sequence elements involved in specific recognition by the S subunit of bacterial RNA polymerase.
  • organism-icon Escherichia coli str. k-12 substr. mg1655
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix E. coli Genome 2.0 Array (ecoli2)

Description

Promoter recognition by bacterial RNA polymerase is mediated by subunits, which assemble transiently to RNA polymerase core enzyme (E) during transcription initiation. subunits drive transcription of specific sets of genes by allowing RNA polymerase to interact with different promoter sequences. However, 70, the housekeeping subunit, and S, an alternative subunit mainly active during slow growth and in response to cellular stresses, appear to recognize almost identical promoter sequences, raising the question of how promoter selectivity is achieved in the bacterial cell. To identify sequence determinants for selective promoter recognition, we performed a run-off/microarray experiment (ROMA): in vitro transcription experiments were carried out with RNA polymerase saturated either with 70 (E70) or with S (ES) using the whole Escherichia coli genome as DNA template, and transcript levels were determined by microarray analysis. We found that several genes associated with bacterial growth (e.g., ribosomal operons) were transcribed more efficiently by E70. In contrast, ES transcribed preferentially genes involved in stress responses, secondary metabolism, as well as regulatory RNAs and intergenic regions with yet unknown function. Genes preferentially recognized in vitro by ES showed reduced expression in ES -deficient mutant strain of E. coli. Sequence comparison of E70- versus ES dependent promoters confirms that the presence of a -35 sequence and the relative location of UP elements affect promoter interaction with either form of RNA polymerase, and suggests that a G/C bias in the -2/+1 nucleotides would favour efficient promoter recognition by E70.

Publication Title

In vitro transcription profiling of the σS subunit of bacterial RNA polymerase: re-definition of the σS regulon and identification of σS-specific promoter sequence elements.

Sample Metadata Fields

Disease

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accession-icon GSE32472
Oxygen induced complication of prematurity: from experimental data to prevention strategy
  • organism-icon Homo sapiens
  • sample-icon 298 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

A prospective study was conducted in the Neonatal Intensive Care Unit of the University Children's hospital between September 1, 2008 and November 30, 2010. The entry criteria were (1) preterm birth below 32 weeks gestational age, (2) birthweight<1500g (VLBW). During the follow-up period, bronchopulmonary dysplasia (BPD) was diagnosed in 68 (61%) infants, including 40 (36%) children with mild disease, 13 (12%) with moderate and 15 (13%) with severe BPD. Forty-three babies served as a control group (no BPD).

Publication Title

Gene expression profiling in preterm infants: new aspects of bronchopulmonary dysplasia development.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE69421
Genetic background of immune complications
  • organism-icon Homo sapiens
  • sample-icon 51 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Differencies between groups between pre and post haematopoietic stem cell transplantation children

Publication Title

Genetic Background of Immune Complications after Allogeneic Hematopoietic Stem Cell Transplantation in Children.

Sample Metadata Fields

Specimen part, Disease stage

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accession-icon GSE35700
Expression data from low R:FR - JA crosstalk in Arabidopsis
  • organism-icon Arabidopsis thaliana
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Low reduced red:far-red ratio [R:FR] signaling through phytochromes induces shade avoidance responses, including petiole elongation. Jasmonic acid-mediated defense against herbivores and pathogens is inhibited under these conditions.

Publication Title

Low red/far-red ratios reduce Arabidopsis resistance to Botrytis cinerea and jasmonate responses via a COI1-JAZ10-dependent, salicylic acid-independent mechanism.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE77806
Role of root-specific transcription factor MYB72 in regulation of Pseudomonas fluorescens WCS417-mediated changes in gene expression in roots of Arabidopsis thaliana
  • organism-icon Arabidopsis thaliana
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Selected soil-borne rhizobacteria can trigger an induced systemic resistance (ISR) that is effective against a broad spectrum of pathogens. In Arabidopsis thaliana, the root-specific transcription factor MYB72 is required for the onset of ISR, but is also associated with plant survival under conditions of iron deficiency. Here we investigated the role of MYB72 in both processes. To identify MYB72 target genes, we analyzed the root transcriptomes of wild-type Col-0, mutant myb72, and complemented 35S:FLAG-MYB72/myb72 plants in response to ISR-inducing Pseudomonas fluorescens WCS417. Five WCS417-inducible genes were misregulated in myb72 and complemented in 35S:FLAG-MYB72/myb72. Amongst these, we uncovered -glucosidase BGLU42 as a novel component of the ISR signaling pathway. Overexpression of BGLU42 resulted in constitutive disease resistance, whereas bglu42 was defective in ISR. Furthermore, we found 195 genes to be constitutively upregulated in MYB72-overexpressing roots in the absence of WCS417. Many of these encode enzymes involved in the production of iron-mobilizing phenolic metabolites under conditions of iron deficiency. We provide evidence that BGLU42 is required for their release into the rhizosphere. Together, this work highlights a thus far unidentified link between the ability of beneficial rhizobacteria to stimulate systemic immunity and mechanisms induced by iron deficiency in host plants.

Publication Title

β-Glucosidase BGLU42 is a MYB72-dependent key regulator of rhizobacteria-induced systemic resistance and modulates iron deficiency responses in Arabidopsis roots.

Sample Metadata Fields

Specimen part

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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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