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Data Set Group: MDC/CAS/ICL Peritoneal Fat 230A (Jun05) modify this page

Data Set: MDC/CAS/ICL Peritoneal Fat 230A (Jun05) RMA 2z+8 modify this page
GN Accession: GN75
GEO Series: No Geo series yet
Title:
Organism: Rat (rn6)
Group: HXBBXH
Tissue: Peritoneal Fat mRNA
Dataset Status: Public
Platforms: Affy Rat Genome 230A (GPL341)
Normalization: RMA
Contact Information
Timothy Aitman
Imperial College London
Imperial College London, South Kensington Campus, London SW7 2AZ
London, London 2AZ UK
Tel. 44 (0)20 3313 4253
t.aitman@imperial.ac.uk
Website
Download datasets and supplementary data files

Specifics of this Data Set:
None

Summary:

This June 2005 data set provides estimates of mRNA expression in normal peritoneal fat of 32 strains of rats. The set includes the hypertensive SHR strain, the normotensive BN strain, and 30 HXB/BXH recombinant inbred strains. Each strain was sampled in quadruplicate (6-week-old males). Animals and tissues were generated by Michal Pravenec and colleagues at the Czech Academy of Sciences (CAS). RNA samples were processed at the Max-Delbrück-Center for Molecular Medicine (MDC), Berlin-Buch, by Norbert Hubner and colleagues. Transcriptome mapping was carried out by Norbert Hubner, Timothy Aitman and colleagues at the MDC and the MRC Clinicial Sciences Centre, Imperial College London (ICL). Samples were hybridized individually to a total of 130 Affymetrix RAE230A array. This particular data set includes 124 arrays processed using the RMA protocol. RMA values of each array were adjusted to an average of 8 units and a standard deviation of 2 units (2ZPlus8). This data set complements the MAS5 data set exploited by Hubner and colleagues 2005. Download the particular transform in an Excel work book with both strain means and SEMs.

Genome-wide co-expression analysis in multiple tissues.

And see closely associate set of papers:

  1. Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease.
  2. Heritability and tissue specificity of expression quantitative trait loci.
  3. Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass.
  4. New insights into the genetic control of gene expression using a Bayesian multi-tissue approach.
  5. The genome sequence of the spontaneously hypertensive rat: Analysis and functional significance.
  6. A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.
  7. Integrated genomic approaches to identification of candidate genes underlying metabolic and cardiovascular phenotypes in the spontaneously hypertensive rat.
  8. Systems-level approaches reveal conservation of trans-regulated genes in the rat and genetic determinants of blood pressure in humans.


About the cases used to generate this set of data:
We have exploited a set of HXB/BXH recombinant inbred strains of rats generated over the past 20 years in Prague. The parental strains from which all HXB lines are derived are SHR (SHR/OlaIpcv or HSR = H) and Brown Norway (BN.Lx/Cub= B). These parental strains have been used extensively to study cardiovascular system physiology and genetics.

 

The HXB strains were generated by Michal Pravenec at the Institute of Physiology, Czech Academy of Sciences. The BXH strains were generated by Vladimir Kren (see Pravenec et al. 1989, 2004) at a similar animal facility at the Institute of Biology and Medical Genetics, 1st Medical Faculty, Charles University. These strains are at approximately the 60th generation of continuous inbreeding (F60).

Animals used in the transcriptome analyses of kidney and fat (Hübner and colleagues, 2005) were weaned at 4 weeks. Those born at the Charles University were transferred to the Institute of Physiology. Animals were reared on a commercial rat chow (ST-1 from VELAZ, Czech Republic). Four males were house per cage. Cages were made of polystyrene and have a floor size of 22 x 38 cm and height of 23 cm. The bedding was changed twice a week. Light cycle was 12:12 on-off. Vivarium rooms were maintained at 23 degrees C. Rats were sexually naive. All males used in the initial transcriptome studies (Hubner et al., 2005) were born between May and August 2002. They were sacrificed unfastged by rapid cervical dislocation between 9 and 10 AM, following an approved animal protocol (Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague; Animal Protection Law of the Czech Republic (311/1997).



About the tissue used to generate this set of data:
All tissues were collected at the age of 6 weeks. Peritoneal fat pads were rapidly dissected and cleaned extraneous tissue, inserted into a vial, and immersed in liquid nitrogen for storage until RNA extraction.
The table below lists 130 arrays by strain and sample identifier. Each array was hybridized with mRNA from a single young male rat. Six arrays marked with asterisks were eventually excluded.
Strain SampleID
BN BN1
BN BN2
BN BN3
BN BN5
BN BN6
BXH10 RI 10c-1
BXH10 RI 10c-2
BXH10 RI 10c-3
BXH10 RI 10c-5
BXH11 RI 11c-1
BXH11 RI 11c-2
BXH11 RI 11c-3
BXH11 RI 11c-4
BXH12 RI 12c-1
BXH12 RI 12c-2
BXH12 RI 12c-3
BXH12 RI 12c-4
BXH13 RI 13c-1
BXH13 RI 13c-2
BXH13 RI 13c-3
BXH13 RI 13c-4
BXH2 RI 02c-1
BXH2 RI 02c-2
BXH2 RI 02c-4
BXH2 RI 02c-5
BXH3 RI 03c-1
BXH3 RI 03c-2
BXH3 RI 03c-3
BXH3 RI 03c-4
BXH5 RI 05c-1
BXH5 RI 05c-2
BXH5 *RI 05c-3
BXH5 RI 05c-5
BXH6 RI 06c-1
BXH6 RI 06c-4
BXH6 RI 06c-5
BXH6 RI 06c-6
BXH8 RI 08c-2
BXH8 RI 08c-3
BXH8 RI 08c-4
BXH8 RI 08c-5
BXH9 RI 09c-1
BXH9 RI 09c-2
BXH9 RI 09c-4
BXH9 RI 09c-5
HXB1 RI 01-1
HXB1 RI 01-2
HXB1 RI 01-4
HXB1 RI 01-5
HXB10 RI 10-2
HXB10 RI 10-3
HXB10 RI 10-4
HXB10 RI 10-5
HXB15 RI 15-1
HXB15 RI 15-2
HXB15 RI 15-5
HXB15 RI 15-6
HXB17 RI 17-1
HXB17 RI 17-2
HXB17 *RI 17-3
HXB17 RI 17-4
HXB18 RI 18-1
HXB18 RI 18-2
HXB18 *RI 18-3
HXB18 RI 18-4
HXB2 RI 02-1
HXB2 RI 02-2
HXB2 RI 02-3
HXB2 RI 02-4
HXB20 RI 20-1
HXB20 RI 20-2
HXB20 *RI 20-3
HXB20 RI 20-4
HXB21 RI 21-1
HXB21 RI 21-2
HXB21 RI 21-3
HXB21 RI 21-4
HXB22 RI 22-1
HXB22 RI 22-2
HXB22 *RI 22-3
HXB22 RI 22-4
HXB23 RI 23-1
HXB23 RI 23-2
HXB23 RI 23-3
HXB23 RI 23-4
HXB24 RI 24-1
HXB24 RI 24-2
HXB24 RI 24-3
HXB24 RI 24-5
HXB25 RI 25-1
HXB25 RI 25-3
HXB25 RI 25-4
HXB25 RI 25-5
HXB26 RI 26-1
HXB26 RI 26-2
HXB26 *RI 26-3
HXB26 RI 26-4
HXB27 RI 27-1
HXB27 RI 27-2
HXB27 RI 27-3
HXB27 RI 27-4
HXB29 RI 29-1
HXB29 RI 29-2
HXB29 RI 29-4
HXB29 RI 29-5
HXB3 RI 03-1
HXB3 RI 03-2
HXB3 RI 03-3
HXB3 RI 03-4
HXB31 RI 31-1
HXB31 RI 31-2
HXB31 RI 31-3
HXB31 RI 31-4
HXB4 RI 04-1
HXB4 RI 04-2
HXB4 RI 04-3
HXB4 RI 04-4
HXB5 RI 05-1
HXB5 RI 05-2
HXB5 RI 05-3
HXB5 RI 05-4
HXB7 RI 07-1
HXB7 RI 07-2
HXB7 RI 07-3
HXB7 RI 07-4
HSR HSR1
HSR HSR2
HSR HSR6
HSR HSR7
HSR HSR8

*: These six arrays were excluded in the final strain summary data. See section of Quality Control for further explanation.



About the array platform:

Affymetrix 230A GeneChip: Expression data were generated using 230A array. The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Rat Genome Sequencing Consortium assembly.



About data values and data processing:

Probe and Probe set data: The original cell-level files (in text format) were downloaded from Array Express. These files were then converted to a standard Affymetrix CEL file (old MAS5 style) format using a Perl script written by Senhua Yu. These files were then processed as a large batch (either all 130 arrays or the final 124 arrays) using a custom quantile normalization program written by KF Manly. The output of this program automatically performs the log normalization and variance stabilization at the probe level. We then computed the mean and standard error for each strain using these normalized probe data.

Probe set data were generated starting with the raw Affymetrix CEL file described above (prior to any normalization) and were processed using the Robust Multichip Average (RMA) method (Irrizary et al. 2003).

This data set include further normalization to produce final estimates of expression that can be compared directly to the other transforms (average of 8 units and stabilized variance of 2 units within each array). Data were further transformed as follows:

  • Step 1: RMA values were generated as described above.
  • Step 2: We computed the Z scores for each probe set value for each array.
  • Step 3: We multiplied all Z scores by 2.
  • Step 4: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
  • Step 5: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. We have not corrected for background beyond the background correction implemented by Affymetrix.

All transformation steps were carried out by Senhua Yu at UTHSC.

About Quality Control Procedures:

RNA processing:RNA was extracted using Trizol reagent (Invitrogen) and purified using an RNeasy Mini kit from Qiagen. Double-stranded cDNA was generated without pooling. Fat samples were processed using the Enzo Diagnostics Bioarray High Yield RNA Transcript labeling kit. See Hubner et al. 2005 for additional detail. One-hundred and twenty eight samples passed RNA quality control assays.

Probe level QC: All 130 CEL files were collected into a single DataDesk 6.2 analysis file. Probe data from pairs of arrays were plotted and compared after quantile normalization. Six arrays were considered potential outliers (despite having passed RNA quality control) and in the interest of minimizing technical variance, a decision was made to withhold them from the calculation of strain means. The remaining 124 arrays were then quantile normalized again and reexamined in DataDesk to ensure reasonable colinearity of all final array data sets.

Strain assignment check: To confirm strain assignment we exploit a set of transcripts with near-Mendelian segregation patterns (search for "test Mendelian"). Strain means with both intermediate expression values AND unusually high error terms often indicate at a misassignment of a case to a particular strain. This error checking has identified 4 strains with possible errors in this data set.

 



Notes:

This approved text file originally generated by Robert Williams, Norbert Hubner, Michal Pravenec, Timothy Aitman, April 19, 2005. Updated by RWW, April 20, 2005; April 28, 2005. June 15, 2005 by RWW and SY; June 20 by RWW and NH.

 



Experiment Type:


Contributor:


Citation:


Data source acknowledgment:

This work was supported with funds to TJA by the MRC Clinical Sciences Centre, the British Heart Foundation, and the Wellcome Trust Cardiovascular Functional Genomics Intiative; to NH from the German Ministry for Science and Education (National Genome Research Network, NGFN); to MP and Vladimir Kren from the Grant Agency of the Czech Republic; to MP and TJA from the Wellcome Trust Collaborative Research Initiative grant, to Theodore W Kurtz from the NIH, to TWK and MP from a Fogarty International Research Collaboration Award. Microarrays were a generous donation of Affymetrix Inc. MP is an International Research Scholar of the Howard Hughes Medical Institute.



Study Id:
17

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