WebQTL
 
   |    Home    |    Search    |    Help    |    News    |    References    |    Policies    |    Links    |    Welcome! Login   

Data Set Group: (B6 x BTBR)F2-ob/ob Liver mRNA M430 (Jul04) modify this page

Data Set: (B6 x BTBR)F2-ob/ob Liver mRNA M430 (Jul04) MAS5 modify this page
GN Accession: GN38
GEO Series: No Geo series yet
Title:
Organism: Mouse (mm10)
Group: B6BTBRF2
Tissue: Liver mRNA
Dataset Status: Public
Platforms: Affy Mouse Genome 430A, 430B, 430A 2.0 (GPL339,GPL340)
Normalization: MAS5
Contact Information
Hong Lan
University of Wisconsin
433 Babcock Drive
Madison, WI 53706 USA
Tel. 608 262-3040
attie@biochem.wisc.edu
Website
Download datasets and supplementary data files

Specifics of this Data Set:
None

Summary:

This August 2005 data freeze provides estimates of mRNA expression in adult liver from a selected set of 60 F2 animals generated by crossing strain C57BL/6J-ob/+ with BTBR and then intercrossing the F1-ob/+ progeny. The F2 progeny included, in a total of 350 progeny, 110 ob/ob progeny homozygous for the obese (ob) allele of leptin (Lep) on Chr 6. Sixty of the ob/ob progeny were selected for expression assays. This selection means that the data set is not useful for defining QTLs on Chr 6. Array data were generated at the University of Wisconsin by Alan Attie and colleagues. This data release accompanies the paper of Lan and colleagues (in submission, 2005). A set of 24 complementary phenotypes such as body weight, blood chemistry, and rtPCR results, are also available for these animals and an additional set of 50 F2s (see Phenotypes database. Samples were hybridized to 60 pairs of Affymetrix M430A and B arrays. This particular data set was processed using the RMA normalization method. To simplify comparison among transforms, RMA values of each array were adjusted to an average of 8 units and a standard deviation of two units.



About the cases used to generate this set of data:
The F2-ob/ob mice were chosen from a mapping panel that we created to map diabetes related physiological phenotypes (Stoehr et al. 2000). About 110 of these F2-ob/ob mice were also used to map mRNA abundance traits derived by quantitative real-time RT-PCR (Lan et al. 2003). The sixty F2-ob/ob mice that were used to generate microarray-derived mRNA abundance traits were selected from the 110 mice based on a selective phenotyping algorithm (Jin et al. 2004). The F2-ob/ob mice were housed at weaning at the University of Wisconsin-Madison animal care facility on a 12-h light/dark cycle. Mice were provided Purina Formulab Chow 5008 (6.5% fat) and acidified water ad libitum. Mice were killed at 14 weeks of age by CO2 asphyxiation after a 4-hour fast. The livers, along with other tissues, were immediately foil wrapped and frozen in liquid nitrogen, and subsequently transferred to -80 °C freezers for storage.


About the tissue used to generate this set of data:

Liver samples were taken from 29 male and 31 females. Total RNA was isolated with RNAzol Reagent (Tel-Test, Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer's protocol. The extracted RNA was purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for concentration. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. RNA samples were converted to cDNA, and then biotin-labeled cRNA according to Affymetrix Expression Analysis Technical Manual. The labeled samples were hybridized to the M430A, and subsequently the M430B array. The hybridization, washing and scanning steps were carried out by Hong Lan using the Affymetrix core facility at the Gene Expression Center of University of Wisconsin-Madison.



About the array platform:

Affymetrix Mouse Genome 430A and 430B array pairs: The 430A and B array pairs collectively consist of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (some are variant transcipts and many are duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequence as the 430 2.0 series. However, roughy 75000 probes differ between those on A and B arrays and those on the 430 2.0.

Liver samples were assayed individually using 60 M430A and B Affymetrix oligonucleotide microarray pairs. Each array ID is denoted by a 10-letter code: the first three letters represent the F2-ob/ob mouse ID number, the fourth letter (either A or B) denotes M430A or M430B arrays, and the last six letters represent the date the array was scanned (MMDDYY).
All 120 M430A and B arrays used in this project were purchased at one time and had the same Affymetrix lot number. The table below lists the arrays by Animal ID, sex, and ArrayID.

Animal ID

sex

MOE430A ArrayID

MOE430B ArrayID

2

M

002A100203

002B100503

12

M

012A100203

012B100503

22

M

022A100203

022B100503

44

M

044A100203

044B100503

46

M

046A100203

046B100503

61

M

061A100203

061B100503

100

M

100A100303

100B100503

105

F

105A100303

105B100503

111

F

111A100303

111B100503

123

M

123A100303

123B100503

156

F

156A100303

156B100503

165

M

165A100303

165B100503

167

M

167A100303

167B100503

173

M

173A100303

173B100503

186

F

186A100203

186B100503

190

F

190A100303

190B100503

194

M

194A100303

194B100503

200

F

200A100303

200B100503

207

F

207A100303

207B100503

209

F

209A100203

209B100503

212

F

212A100303

212B100503

223

M

223A100303

223B100503

224

M

224A100303

224B100503

253

F

253A100303

253B100503

254

F

254A100603

254B100703

260

F

260A100603

260B100703

264

F

264A100603

264B100703

310

F

310A100603

310B100703

317

M

317A100603

317B100703

318

F

318A100603

318B100703

324

F

324A100603

324B100703

327

F

327A100603

327B100703

343

M

343A100603

343B100703

416

M

416A100603

416B100703

419

F

419A100603

419B100703

438

M

438A100603

438B100703

440

M

440A100603

440B100803

455

M

455A100603

455B100803

458

F

458A100603

458B100803

472

M

472A100603

472B100803

474

F

474A100603

474B100803

479

F

479A100603

479B100803

484

F

484A100603

484B100803

486

F

486A100603

486B100803

489

F

489A100603

489B100803

493

F

493A100603

493B100803

499

M

499A100603

499B100803

513

M

513A100603

513B100803

517

M

517A100703

517B100803

523

M

523A100703

523B100803

549

M

549A100703

549B100803

553

F

553A100703

553B100803

554

F

554A100703

554B100803

559

F

559A100703

559B100803

560

F

560A100703

560B100803

566

M

566A100703

566B100803

608

F

608A100703

608B100803

615

F

615A100703

615B100803

617

M

617A100703

617B100803

620

M

620A100703

620B100803



About data values and data processing:
Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
  • Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
  • Step 2: We took the log base 2 of each cell.
  • Step 3: We computed the Z scores for each cell.
  • Step 4: We multiplied all Z scores by 2.
  • Step 5: 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 6a: The 430A and 430B GeneChips include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the two GeneChips to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
  • Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
Probe set data from the .CHP file: The expression data were generated using MAS5. The same simple steps described above were also applied to these values. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
The 60 mice were each genotyped at 194 MIT microsatellite markers an average of approximately 10 cM (and always < 30 cM) apart across the entire genome (Y chromsome, excepted). The genotyping error-check routine implemented within R/qtl (Broman et al. 2003) showed no likely errors at p <0.01 probability.


Notes:

This text file originally generated by RWW and Alan Attie, July 2, 2004. Updated by RWW, Aug 20, 5, 2004; April 7, 2005; August 20, 2005.



Experiment Type:


Contributor:


Citation:

Lan H, Chen M, Byers JE, Yandell BS, Stapleton DS, Mata CM, Mui ET, Flowers MT, Schueler KL, Malnly KF, Williams RW, Kendziorski CM, Attie AD (2005) Combined expression trait correlations and expression quantitative trait locus mapping. Submitted, Aug. 2005.

Broman KW, Wu H, Sen S, Churchill GA (2003) R/qtl: QTL mapping in experimental crosses. Bioinformatics 19: 889-890.

Irizarry RA, Bolstad BM, Collin F, Cope LM, Hobbs B, Speed TP (2003) Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res 31: e15.

Jin C, Lan H, Attie AD, Churchill GA, Bulutuglo D, Yanell BS (2004) Selective phenotyping for increased efficiency in genetic mapping studies. Genetics 168:2285-2293.

Lan H, Stoehr JP, Nadler ST, Schueler KL, Yandel BS, Attie AD (2003) Dimension reduction for mapping mRNA abundance as quantitative traits. Genetics 164: 1607-1614.

Stoehr JP, Nadler ST, Schueler KL, Rabaglia ME, Yandell BS, Metz SA, Attie AD (2000) Genetic obesity unmasks nonlinear interactions between murine type 2 diabetes susceptibility loci. Diabetes 49: 1946-1954.

Zhang L, Miles MF, Aldape KD (2003) A model of molecular interactions on short oligonucleotide microarrays. Nat Biotechnol 21: 818-821.



Data source acknowledgment:
This project was supported in part by NIH/NIDDK 5803701, NIH/NIDDK 66369-01 and American Diabetes Association 7-03-IG-01 to Alan D. Attie, USDA CSREES grants to the University of Wisconsin-Madison to Brian S. Yandell, and HHMI grant A-53-1200-4 to Christina Kendziorski.
B6BTBRF2 Liver Database. All of the original (B6 x BTBR)F2-ob/ob liver mRNA M430AB array data were generated by Hong Lan and Alan Attie at The University of Wisconsin-Madison. For contact and citations and other information on these data sets, please review the INFO pages and contact Drs. Alan Attie, Christina Kendziorski, and Brian Yandell regarding use of this data set in publications or projects.


Study Id:
10

CITG Web services initiated January, 1994 as Portable Dictionary of the Mouse Genome; June 15, 2001 as WebQTL; and Jan 5, 2005 as GeneNetwork. This site is currently operated by Rob Williams, Pjotr Prins, Zachary Sloan, Arthur Centeno. Design and code by Pjotr Prins, Zach Sloan, Arthur Centeno, Danny Arends, Christian Fischer, Sam Ockman, Lei Yan, Xiaodong Zhou, Christian Fernandez, Ning Liu, Rudi Alberts, Elissa Chesler, Sujoy Roy, Evan G. Williams, Alexander G. Williams, Kenneth Manly, Jintao Wang, and Robert W. Williams, colleagues. Python Powered Registered with Nif
GeneNetwork support from:
  • The UT Center for Integrative and Translational Genomics
  • NIGMS Systems Genetics and Precision Medicine project (R01 GM123489, 2017-2021)
  • NIDA NIDA Core Center of Excellence in Transcriptomics, Systems Genetics, and the Addictome (P30 DA044223, 2017-2022)
  • NIA Translational Systems Genetics of Mitochondria, Metabolism, and Aging (R01AG043930, 2013-2018)
  • NIAAA Integrative Neuroscience Initiative on Alcoholism (U01 AA016662, U01 AA013499, U24 AA013513, U01 AA014425, 2006-2017)
  • NIDA, NIMH, and NIAAA (P20-DA 21131, 2001-2012)
  • NCI MMHCC (U01CA105417), NCRR, BIRN, (U24 RR021760)
    Join GeneNetwork Mailing List
    It took 0.062 second(s) for lily.uthsc.edu to generate this page