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Glycine max
22 Downloadable Samples
Illumina HiScanSQ
Description
Phytophthora root and stem rot (PRR) of soybean, caused by Phytophthora sojae, is effectively controlled by Rps genes in soybean. Rps genes are race-specific, yet the mechanism of resistance, as well as susceptibility, remains largely unclear. Taking advantage of RNA-seq technology, we sequenced the transcriptomes of 10 near isogenic lines (NIL), each with a unique Rps gene, and the recurrent susceptible parent 'Williams'. A total of 4330 differentially expressed genes (DEGs) were identified in 'Williams' while 2075 to 5499 DEGs were identified in each NIL. Comparisons between the NILs and 'Williams' allowed classification of two major groups of DEGs of interest: incompatible reaction associated genes (IRAGs) and compatible reaction associated genes (CRAGs). Hierarchical cluster analysis divided NILs into three clusters: Cluster I (Rps1-a), Cluster II (Rps1-b, 1-c and 1-k) and Cluster III (Rps3-a, 3-b, 3-c, 4, 5, and 6). Heatmap analysis, along with GO analysis suggested that the diversity of clusters for NILs were likely due to variation of the number of DEGs and the intensity of gene expression, rather than functional differentiation. Further analysis suggested that transcription factors might play pivotal role in determination of the cluster pattern, and that WRKY family were strongly associated with incompatible reactions. Analysis of IRAGs and CRAGs with putative functions suggested that the regulation of many phytohormone signaling pathways were associated with incompatible or compatible interactions with potential crosstalk between each other. As such, our study provides an in depth view of both incompatible and compatible interactions between soybean and P. sojae, which provides further insight into the mechanisms involved in host-pathogen interactions. Overall design: 22 samples were sequenced, 11 inoculated with P. sojae, the other 11 were mock-inoculated
Publication Title
Molecular response to the pathogen Phytophthora sojae among ten soybean near isogenic lines revealed by comparative transcriptomics.
Sample Metadata Fields
Specimen part, Subject
View Samples- Mus musculus
- 15 Downloadable Samples
Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Three-dimensional (3D) culture of hepatocytes leads to improved and prolonged synthetic and metabolic functions, but the underlying molecular mechanisms were unknown. In order to investigate the molecular mechanisms underlying 3D cell-cell interactions in maintaining hepatocyte differentiated functions ex vivo, microarray analyses were performed on primary mouse hepatocytes cultured either as monolayers on tissue culture dishes (TCD) or as 3D aggregates in rotating wall vessel (RWV) bioreactors.
Publication Title
Molecular mechanisms underlying the enhanced functions of three-dimensional hepatocyte aggregates.
Sample Metadata Fields
Sex
View Samples- Arabidopsis thaliana
- 8 Downloadable Samples
- Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)
Description
Analysis of the abh1 mutant Arabidopsis plants following treatment with 50 uM abscisic acid (ABA). ABH1 encodes the large (80kDa) subunit of the nuclear mRNA cap binding complex and affects early ABA signal transduction events (Hugouvieux et al., 2001, Cell 106, 477).
Publication Title
mRNA cap binding proteins: effects on abscisic acid signal transduction, mRNA processing, and microarray analyses.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 8 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Essential fatty acids (FA) are not only energy-rich molecules; they are also an important component of the membrane bilayer and recently have been implicated in induction of fatty acid synthase (FAS) and other genes. Using gene chip analysis, we have found that arachidonic acid (AA), an omega-6 fatty acid, induced 11 genes that are regulated by NFkappaB. We verified gene induction by omega-6 fatty acids including COX2, IKBA, NFKB, GMCSF, IL1B, CXCL1, TNFA, IL6, LTA, IL8, PPARG, and ICAM1 using qRTPCR. PGE2 synthesis was increased within 5min of addition of AA. Analysis of upstream signal transduction showed that within 5min of FA addition, phophatidylinositol 3-kinase (PI3K) was significantly activated followed by activation of Akt at 30min. ERK1 and 2, p38, and SAPK/JNK were not phosphorylated after omega-6 FA addition. Thirty minutes after FA addition, we found a significant 3-fold increase in translocation of NFkappaB transcription factor to the nucleus. Addition of non-steroidal anti-inflammatory drug (NSAID) caused a decrease in cox-2 protein synthesis, PGE2 synthesis as well as inhibition of PI3K activation. We have previously shown that AA induced proliferation is also blocked (P<0.001) by PI3K inhibitor LY294002. LY294002 also significantly inhibited the AA induced gene expression of COX2, IL1B, GMCSF, and ICAM1. Taken together, the data suggests that AA via conversion to PGE2 plays an important role in stimulation of growth related genes and proliferation via PI3K signaling and NFkappaB translocation to the nucleus.
Publication Title
Arachidonic acid activates phosphatidylinositol 3-kinase signaling and induces gene expression in prostate cancer.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 6 Downloadable Samples
- Illumina HiSeq 2500
Description
We report the application of RNA-seq analysis for high-throughput profiling of murine lungs infected with Aspergillus fumigatus. We compared the lung transcription of wildtype murine lungs and lungs from mice deficient in metabolic cytokine adiponectin. Overall design: Examination of 2 different mice strain and comparison of lung transcripts in response to Aspergillus fumigatus infection.
Publication Title
The Metabolic Cytokine Adiponectin Inhibits Inflammatory Lung Pathology in Invasive Aspergillosis.
Sample Metadata Fields
Specimen part, Cell line, Subject
View Samples- Mus musculus
- 288 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
A circadian gene expression atlas in mammals: implications for biology and medicine.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 288 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
To characterize the role of the circadian clock in mouse physiology and behavior, we used RNA-seq and DNA arrays to quantify the transcriptomes of 12 mouse organs over time. We found 43% of all protein coding genes showed circadian rhythms in transcription somewhere in the body, largely in an organ-specific manner. In most organs, we noticed the expression of many oscillating genes peaked during transcriptional rush hours preceding dawn and dusk. Looking at the genomic landscape of rhythmic genes, we saw that they clustered together, were longer, and had more spliceforms than nonoscillating genes. Systems-level analysis revealed intricate rhythmic orchestration of gene pathways throughout the body. We also found oscillations in the expression of more than 1,000 known and novel noncoding RNAs (ncRNAs). Supporting their potential role in mediating clock function, ncRNAs conserved between mouse and human showed rhythmic expression in similar proportions as protein coding genes. Importantly, we also found that the majority of best-selling drugs and World Health Organization essential medicines directly target the products of rhythmic genes. Many of these drugs have short half-lives and may benefit from timed dosage. In sum, this study highlights critical, systemic, and surprising roles of the mammalian circadian clock and provides a blueprint for advancement in chronotherapy.
Publication Title
A circadian gene expression atlas in mammals: implications for biology and medicine.
Sample Metadata Fields
Specimen part
View Samples- Drosophila melanogaster
- 46 Downloadable Samples
- Affymetrix Drosophila Genome 2.0 Array (drosophila2)
Description
Immunosenescence, the age-related decline in immune system function, is a general hallmark of aging. While much is known about the cellular and physiological changes that accompany immunosenescence, we know very little about the genetic influences on this phenomenon.
Publication Title
Age-specific variation in immune response in Drosophila melanogaster has a genetic basis.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Drosophila melanogaster
- 24 Downloadable Samples
- Illumina Genome Analyzer IIx
Description
RNAseq transcriptional profiling of Drosophila brains from wildtype, and period loss-of-function animals with time points taken over two days. Overall design: 2 days of brain collection, time points at ZT0, ZT6, ZT12, and ZT18; wildtype and per0 flies. 10-12 brains per time point.
Publication Title
Deep sequencing the circadian and diurnal transcriptome of Drosophila brain.
Sample Metadata Fields
Specimen part, Subject, Time
View Samples
GSE15050- Escherichia coli
- 11 Downloadable Samples
- Affymetrix E. coli Genome 2.0 Array (ecoli2)
Description
The ability to respond to stress is at the core of an organisms survival. The hormones epinephrine and norepinephrine play a central role in stress responses in mammals, which require the synchronized interaction of the whole neuroendocrine system. Bacteria also sense and respond to epinephrine and norepinephrine as a means to gauge the metabolic and immune state of the host. Mammalian adrenergic receptors are G-coupled protein receptors (GPCRs), bacteria, however, sense these hormones through histidine sensor kinases (HKs). HKs autophosphorylate in response to multiple signals and transfer this phosphate to response regulators (RRs). Two bacterial adrenergic receptors have been identified in EHEC, QseC and QseE, with QseE being downstream of QseC in this signaling cascade. We mapped the QseC signaling cascade in the deadly pathogen enterohemorrhagic E. coli (EHEC), which exploits this signaling system to promote disease. Through QseC, EHEC activates expression of metabolic, virulence and stress response genes, synchronizing the cell response to these stress hormones. Coordination of these responses is achieved by QseC phosphorylating three of the thirty two EHEC RRs. The QseB RR, which is QseCs cognate RR, activates the flagella regulon which controls bacteria motility and chemotaxis. The QseF RR, which is phosphorylated by the QseE adrenergic sensor, coordinates expression of virulence genes involved in formation of lesions in the intestinal epithelia by EHEC, and the bacterial SOS stress response. The third RR, KdpE, controls potassium uptake, osmolarity response, and also the formation of lesions in the intestine. Adrenergic regulation of bacterial gene expression shares several parallels with mammalian adrenergic signaling having profound effects in the whole organism. Understanding adrenergic regulation of a bacterial cell is a powerful approach to study the underlying mechanisms of stress and cellular survival.
Publication Title
The QseC adrenergic signaling cascade in Enterohemorrhagic E. coli (EHEC).
Sample Metadata Fields
No sample metadata fields
View Samples