refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 12454 results
Sort by

Filters

Technology

Platform

accession-icon GSE36013
Gene-level expression data from Oryza sativa.indica (mock-treated or blast pathogen treated resistant rice line and susceptible rice line )
  • organism-icon Oryza sativa
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

In this dataset, we include the expression data obtained from untreated and blast pathogen treated rice seedlings using a variety of blast resistant rice line H4, as well as the susceptible rice line Zhonger-Ruanzhan. These data are used to obtain 4087 genes that are differentially expressed in response to blast pathogen in both of rice lines,as well as 717 genes that are differentially expressed between different lines both in the moch-treated and the blast treated.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE74412
Expression data from the process of chilling stress causing Alternaria alternata infection and leading to cotton leaf senescence
  • organism-icon Gossypium hirsutum
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Cotton Genome Array (cotton)

Description

Cotton premature leaf senescence often occurred with an increasing frequency in many cotton growing areas and caused serious reduction in yield and quality of cotton has been one of the impontant factors that restrict severely the production of cotton.Our laboratory studies showed chilling stress is the key factor that induced A. alternatia infection, caused Alternaria disease and then lead to cotton leaf senescence, but the molecular mechanism of cotton premature leaf senscence is still unclear.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE62158
Dynamic transcriptome analysis and volatile profiling of Gossypium hirsutum in response to the cotton bollworm Helicoverpa armigera
  • organism-icon Gossypium hirsutum
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Cotton Genome Array (cotton)

Description

Cotton seeds (Gossypium hirsutum cv. CCRI12) were grown in a growth chamber under 29/25C temperature and a 16:8 h light:dark cycle, and water was added every two days. All plants were used in experiments at the 6-7 fully expanded true leaf stage, which occurred 5-6 weeks after sowing. Cotton bollworm (CBW; Helicoverpa armigera) larvae were reared on an artificial diet and maintained at 27 2C, 75 10% relative humidity, and 14:10 h light:dark in the laboratory. For insect treatment, seven H. armigera larvae (third instars) were placed on a group of three plants, which were kept within plastic bags (30 40 cm), until time of harvest, with samples for each time point maintained separately. Undamaged plants maintained under the same conditions were used as controls. Cotton leaves from control plants and plants exposed to H. armigera were harvested at 6 h, 12 h, 24 h, and 48 h after onset of herbivory. For each treatment group and time point, cotton leaves were harvested from the three plants per treatment group and flash frozen in liquid nitrogen. For each time point, three replicate treatments and controls were performed.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE33204
DNA microarray data from transgenic rice Huahui 1 (HH1) and its parent Minghui 63 (MH63)
  • organism-icon Oryza sativa
  • sample-icon 58 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

DNA microarray analysis has been proved to be an effective method in investigating unintended effects in genetically modified (GM) crops. But the distribution of differentially expressed genes in GM crops remains unclear. So the results of microarray analysis might be invalid for assessment of unintended effects if differentially expressed genes are extremely distributed. We used microarrays to study the distribution pattern of differentially expressed genes in HH1 at different developmental stages and environmental conditions.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE33203
DNA microarray data from transgenic rice KMD and its parent XS11
  • organism-icon Oryza sativa
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

KMD is genetically engenered to be highly resistant to lepidopteran pests through expressing a synthetic cry1Ab gene and its parent non-transgenic rice is Xiushui 11 (XS11). Many unintended effects have been discovered in KMD. We used microarrays to study the molecular basis for unintended effects of KMD rice.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE46086
DNA microarray data from root of transgenic rice Huahui 1 (HH1) and its parent Minghui 63 (MH63)
  • organism-icon Oryza sativa
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

DNA microarray analysis has been proved to be an effective method in investigating unintended effects in genetically modified (GM) crops. However, unintended effects of GM plants in leaves through DNA microarray analysis has many researches, but research of unintended effects of GM plants of the underground portion has few. In this study, DNA microarray analysis was used to detect DEG in underground portions between transgenic rice HH1 and its non-transgenic control MH63.

Publication Title

No associated publication

Sample Metadata Fields

Age, Specimen part

View Samples
accession-icon GSE54310
expression data from 14 tissues of maize
  • organism-icon Zea mays
  • sample-icon 40 Downloadable Samples
  • Technology Badge Icon Affymetrix Maize Genome Array (maize)

Description

The genes specifically express in some tissue may usually play an important role in the development of the tissue. At vegetative growth stage, some genes may up-regulated to promote the nutrition absorbtion and transportation. However during the reproductive stage, some genes may up-regulated to regulate the flowering and seed development.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE17526
Transcriptional responses of Escherichia coli rpoS- BW25113 vs. wild-type BW25113 under 15% ethanol shock in log phase
  • organism-icon Escherichia coli
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix E. coli Genome 2.0 Array (ecoli2)

Description

RpoS, an alternative sigma factor, is critical for stress response in Escherichia coli.RpoS also acts as a global regulator for stress control of gene expression, and actually dose so in log stage and stationary stage.

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE17465
Transcriptional profile of Escherichia coli K12 strain JM109 harboring pMG1 and pMG1-IrrE under 1M NaCl shock
  • organism-icon Escherichia coli
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix E. coli Genome 2.0 Array (ecoli2)

Description

IrrE is a unique gene in Deinococcus, which is the switch of DNA repair and celluar surival network. Expressing IrrE enhanced the salt tolence in E. coli. To understand the effect of IrrE to E. coli during salt shock, we constructed the IrrE-expressing plasmid pMG1-IrrE. And pMG1 is the empty vector used as a control.

Publication Title

No associated publication

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE16567
Genome-wide transcriptome analysis of two maize inbred lines under drought stress during the seedling stage
  • organism-icon Zea mays
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix Maize Genome Array (maize)

Description

To understand the transcriptome changes during drought tolerance in maize, the drought-tolerant line Han21 and drought-sensitive line Ye478, which show substantial differences in drought tolerance at the seedling stage, were selected for this study. Using the GeneChip Maize Genome Arrays, we applied genome-wide gene expression analysis to the two genotypes under gradual drought stress and re-watering. We identified 2172 common regulated transcripts in both lines under drought stress, with 1084 common up-regulated transcripts and 1088 common down-regulated transcripts. Among the 2172 transcripts, 58 potential protein kinases and 117 potential transcription factors were identified. The potential components of the ABA signaling pathway were identified from the common regulated transcripts. We also identified 940 differentially regulated transcripts between the two lines. Among the 940 transcripts, the differential expression levels of 29 transporters and 15 cell wall-related transcripts may contribute to the different tolerances of the two lines. Additionally, we found that the drought-responsive genes in the tolerant Han21 line recovered more quickly when the seedlings were re-watered, and 311 transcripts in the tolerant Han21 line were exclusively up-regulated at the re-watering stage compared to the control and stress conditions. Our study provides a global characterization of two maize inbred lines during drought stress and re-watering and will be valuable for further study of the molecular mechanisms of drought tolerance in maize.

Publication Title

Genome-wide transcriptome analysis of two maize inbred lines under drought stress.

Sample Metadata Fields

Specimen part

View Samples
...

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

Powered by Alex's Lemonade Stand Foundation

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.

BSD 3-Clause LicensePrivacyTerms of UseContact