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accession-icon GSE52626
Expression data from longissimus dorsi of backcross Iberian x Landrace individuals
  • organism-icon Sus scrofa
  • sample-icon 101 Downloadable Samples
  • Technology Badge Icon Affymetrix Porcine Genome Array (porcine)

Description

The integration of the results of QTL fine-mapping with microarray expression data offers a promising tool for understanding the genetic mechanisms influencing complex traits as fatty acid composition in pigs. The expression level of each probe may be treated as a quantitative trait and the marker genotypes used to map loci with regulatory effect on the gene expression level (eQTL)

Publication Title

Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data.

Sample Metadata Fields

Sex, Age

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accession-icon GSE10898
Transcriptome architecture across tissues in the pig
  • organism-icon Sus scrofa
  • sample-icon 63 Downloadable Samples
  • Technology Badge Icon Affymetrix Porcine Genome Array (porcine)

Description

Artificial selection has resulted in animal breeds with extreme phenotypes. As an organism is made up of many different tissues and organs, each with its own genetic programme, it is pertinent to ask what are the relative contributions of breed or sex when assessed across tissues.

Publication Title

Transcriptome architecture across tissues in the pig.

Sample Metadata Fields

Age

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accession-icon GSE52012
Analysis of porcine adipose tissue transcriptome reveals differences in de novo fatty acid synthesis in pigs with divergent muscle fatty acid composition
  • organism-icon Sus scrofa
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Porcine Genome Array (porcine)

Description

In pigs, adipose tissue is one of the principal organs involved in the regulation of lipid metabolism. It is particulary involved in the overall fatty acid synthesis with consequences in other lipid-target organs such as muscles and the liver. With this in mind, we have used massive, parallel high-throughput sequencing technologies to characterize the porcine adipose tissue transcriptome architecture in six Iberian x Landrace crossbred pigs showing extreme phenotypes for intramuscular fatty acid composition (three per group). High-throughput RNA sequencing was used to generate a whole characterization of adipose tissue (backfat) transcriptome. A total of 4,130 putative unannotated protein-coding sequences were identified in the 20% of reads which mapped in intergenic regions. Furthermore, 36% of the unmapped reads were represented by interspersed repeats, SINEs being the most abundant elements. Differential expression analyses identified 396 candidate genes among divergent animals for intramuscular fatty acid composition. Sixty-two percent of these genes (247/396) presented higher expression in the group of pigs with higher content of intramuscular SFA and MUFA, while the remaining 149 showed higher expression in the group with higher content of PUFA. Pathway analysis related these genes to biological functions and canonical pathways controlling lipid and fatty acid metabolisms. In concordance with the phenotypic classification of animals, the major metabolic pathway differentially modulated between groups was de novo lipogenesis, the group with more PUFA being the one that showed lower expression of lipogenic genes. These results will help in the identification of genetic variants at loci that affect fatty acid composition traits. The implications of these results range from the improvement of porcine meat quality traits to the application of the pig as an animal model of human metabolic diseases.

Publication Title

Analysis of porcine adipose tissue transcriptome reveals differences in de novo fatty acid synthesis in pigs with divergent muscle fatty acid composition.

Sample Metadata Fields

Sex, Specimen part

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accession-icon SRP067181
Transcriptome sequencing of porcine liver samples
  • organism-icon Sus scrofa
  • sample-icon 26 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Identification of genes and causal mutations regulating growth and fatness traits in pig. Overall design: Transcriptome sequencing of 10 liver samples of two groups of divergent pigs for growth and fatness.

Publication Title

Using RNA-Seq SNP data to reveal potential causal mutations related to pig production traits and RNA editing.

Sample Metadata Fields

Sex, Age, Specimen part, Subject

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accession-icon GSE38588
Liver transcriptome profile in pigs with extreme phenotypes of intramuscular fatty acid composition
  • organism-icon Sus scrofa
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Porcine Genome Array (porcine)

Description

The liver transcriptomes of two female groups (High and Low) with phenotypically extreme intramuscular fatty acid composition were sequenced using RNA-Seq [accn: SRA053452, subid: 86092, Bioproject: PRJNA168072]. A total of 146 and 180 unannotated protein-coding genes were identified in intergenic regions for the L and H groups, respectively. In addition, a range of 5.8 to 7.3% of repetitive elements was found, with SINEs being the most abundant elements. The expression in liver of 186 (L) and 270 (H) lncRNAs was also detected. The higher reproducibility of the RNA-Seq data was validated by RT-qPCR and porcine expression microarrays, therefore showing a strong correlation between RT-qPCR and RNA-Seq data (ranking from 0.79 to 0.96), as well as between microarrays and RNA-Seq (r=0.72). A differential expression analysis between H and L animals identified 55 genes differentially-expressed between groups. Pathways analysis revealed that these genes belong to biological functions, canonical pathways and three gene networks related to lipid and fatty acid metabolism. In concordance with the phenotypic classification, the pathways analysis inferred that linolenic and arachidonic acids metabolism was altered between extreme individuals. In addition, a connection was observed among the top three networks, hence suggesting that these genes are interconnected and play an important role in lipid and fatty acid metabolism.

Publication Title

Liver transcriptome profile in pigs with extreme phenotypes of intramuscular fatty acid composition.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE65882
Identification of genes involved with P. aeruginosa biofilms
  • organism-icon Pseudomonas aeruginosa
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Contribution of stress responses to antibiotic tolerance in Pseudomonas aeruginosa biofilms.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE65870
Identification of genes involved with P. aeruginosa biofilm antibiotic resistance by microarray analysis
  • organism-icon Pseudomonas aeruginosa
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

Microarray analysis was used to identify changes in the level of transcription of genes in P. aeruginosa drip flow biofilms in response to ciprofloxacin and tobramycin exposure. This data was evaluated and used to select strains that carry transposon mutations in genes that might play a role in antibiotic tolerance of biofilms. The strains were evaluated for defects in biofilm tolerance.

Publication Title

Contribution of stress responses to antibiotic tolerance in Pseudomonas aeruginosa biofilms.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE65869
Identification of genes induced in P. aeruginosa biofilms by microarray analysis
  • organism-icon Pseudomonas aeruginosa
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

Transcriptome analysis was applied to characterize the physiological activities of Psuedomonas aeruginosa cells grown for three days in drip flow biofilm reactors when compared to the activities of P. aeruginosa grown planktonically to exponential phase in the same media. Here, rather than examining the effect of an individual gene on biofilm antibiotic tolerance, we used a transcriptomics approach to identify regulons and groups of related genes that are induced during biofilm growth of Pseudomonas aeruginosa. We then tested for statistically significant overlap between the biofilm-induced genes and independently compiled gene lists corresponding to stress responses and other putative antibiotic protective mechanisms. This data was evaluated and used to select strains that carry transposon mutations in genes that might play a role in antibiotic tolerance of biofilms. The strains were evaluated for defects in biofilm tolerance.

Publication Title

Contribution of stress responses to antibiotic tolerance in Pseudomonas aeruginosa biofilms.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE42214
Wheat drought responses
  • organism-icon Triticum aestivum
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Wheat Genome Array (wheat)

Description

Three wheat genotypes were exposed to water stress and root tissue collected for expression analysis

Publication Title

Introgression of novel traits from a wild wheat relative improves drought adaptation in wheat.

Sample Metadata Fields

Specimen part

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accession-icon GSE22164
Physiology of Pseudomonas aeruginosa in Biofilms Revealed by Comparative Transcriptomic Analysis.
  • organism-icon Pseudomonas aeruginosa
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

Abstract: Transcriptome analysis was applied to characterize the physiological activities of Pseudomonas aeruginosa grown for three days in drip-flow biofilm reactors. Conventional applications of transcriptional profiling often compare two paired data sets that differ in a single experimentally controlled variable. In contrast this study obtained the transcriptome of a single biofilm state, ranked transcript signals to make the priorities of the population manifest, and compared rankings for a priori identified physiological marker genes between the biofilm and published data sets.

Publication Title

Physiology of Pseudomonas aeruginosa in biofilms as revealed by transcriptome analysis.

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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