Data Set Group2: SUH BXD Liver Affy Mouse Gene 1.0 ST (Jun11)

Data Set: SUH BXD Liver CCl4-treated Affy Mouse Gene 1.0 ST (Jun11) RMA GN Accession: GN325 GEO Series: No Geo series yet Title: Systems genetics of liver fibrosis: identification of fibrogenic and expression quantitative trait loci in the BXD murine reference population Organism: Mouse (Mus musculus, mm10) Group: BXD Tissue: Liver mRNA Dataset Status: Public Platforms: Affy Mouse Gene 1.0 ST (GPL6246) Normalization: RMA

Contact Information Frank Lammert Saarland University Homburg (SUH) Kirrberger Straße 100 Homburg, Germany Tel. 06841/16-23201 frank.lammert@uks.eu Website Download datasets and supplementary data files GN325_MeanDataAnnotated_rev081815.txt (N/A) GN325_StdError_rev081815.txt (N/A)

Specifics of this Data Set:

None

Summary:

Saarland University Homburg (SUH) Carbon Tetrachloride-Treated BXD Mouse Affymetrix Mouse Gene 1.0 ST Array data set This experimental liver gene expression data set (~100 Affymetrix exon-type arrays), was generated by Frank Lammert, Sonja Hillebrandt, Rabea Hall, and colleagues at the Saarland University Medical Center in Homburg, Germany. This work is part of the German Network for Systems Genetics (GeNeSys). Expression data after carbon tetrachloride treatment (CCl4, also known as Halon, Freon, carbon tet, or tetrachloromethane) were generated using RNA sample from 30 BXD strains, both parental strains (C57BL/6J, DBA/2J), and B6D2 F1 hybrids. The great majority of cases were females and were treated with carbon tetrachloride injections over a six week period. Three arrays were run for each strain using independent liver samples. PURPOSE: The overall goal of the project is to understand the etiology of liver fibrogenesis using carbon tetracholoride as a toxin and inducer of liver disease. Liver fibrogenesis, or scarring of the liver, is the common end-stage of chronic liver diseases, in particular after chronic viral infections. In Germany along complications associated with liver fibrosis cause approximately 10,000 deaths per year. In the past decade key molecular pathomechanisms of hepatic fibrogenesis due to chronic viral infections have been identified. Activated hepatic stellate cells (HSCs) drive the process of de novo deposition of abnormal extracellular matrix, which is modulated by complex interactions between cytokines, receptors, and matrix components. Several studies have demonstrated that the course and progression of the fibrogenic response to chronic liver injury is highly variability among individuals. This marked variabilityhas been attributed to etiology, age, gender, and environmental factors. In humans these genetic disease fibrosis predisposition factors have not yet to be studied systematically. Our group recently identified a gene variant that contributes to liver fibrogenesis by using QTL mapping in an experimental crosses between fibrosis-susceptible and resistant strains of mice (Hillebrandt et al., 2005). We demonstrated that sequence differences in the HC gene that encodes complement factor C5 (also known as hemolytic complement), are responsible for this strain difference. Common haplotype-tagging polymorphisms of the human HC gene were shown to be associated with advanced fibrosis in chronic hepatitis C virus infection. Thus, the mouse analysis led to the identification of an unknown gene underlying human susceptibility to liver fibrosis, supporting the idea that HC has a causal role in chronic inflammatory disorders and organ fibrogenesis across species. As part of the GeNeSys program we have studied liver fibrogenesis in the BXD family of strains as a model for chronic liver injury. This expression data set is used to map complex genetic traits that modulate gene expression and determine gene networks during liver fibrogenesis in GRPs. The following assays are complete or are in progress: Liver fibrosis studies: Phenotyping protocols include standard histology, morphometry, biochemical quantification of hepatic collagen contents, serum surrogate markers of fibrosis, immunohistochemistry, and expression profiling of proinflammatory and profibrogenic genes by qRT-PCR and Affymetrix microarrays (this data set). Characterization of liver cells: Liver immune cell fractions will be isolated and sorted according to SOPs developed in the Lammert laboratory. In addition, in cooperation with the technology platforms of the HepatoSys Network of Excellence, we will characterize primary HSCs that play critical roles in liver fibrogenesis with respect to proinflammatory responses during chronic liver inflammation. PROTOCOL for carbon tetrachloride (CCl4) treatment (parental strains, F1, and BXD lines). Animals were injected with CCl4 (12 x 0.7 mg/kg ip) over a 6-week period on days 1 and 4 of each week. Intraperitoneal injections were begun between the ages of 6-8 weeks. Animals were sacrificed after 6 weeks of treatment at 12 to 14 weeks of age. Untreated control mice from only the two parental strains were also sacrificed at 12-14 weeks of age

About the cases used to generate this set of data:

About the tissue used to generate this set of data:

Tissue: Livers were snap frozen in liquid nitrogen immediately after harvesting. RNA was extracted and submitted to the UTHSC Molecular Resource Core for expression profiling. Expression data were generated by Lorne Rose, William Taylor and colleagues. Data were entered into GeneNetwork by Arthur Centeno, June 17, 2011. Data were quality controlled by R. W. Williams.

About the array platform:

About data values and data processing:

QC Results: This data set consists of expression data for 33 strains. A total of 166 probe sets are associated with LOD scores above 10 and the highest linkage score of 22 for Rpl3 (probe set 10430669). Strain distribution patterns of eQTLs with a Mendelian expression pattern match those of their closest markers perfectly, verifying that there are no errors of strain assignment in this data set. Analysis of XIST probe set 1060617 confirms that most strains are purely female. However, only males were available for BXD1 and BXD6. BXD28 and BXD33 data are based on the average of two female samples and one male sample. All other strains are purely female. Data were analyzed by Rabea Hall and Dr. Frank Lammert at the Universitätsklinikum des Saarlandes in Homburg, Germany. Contacts: rabea.hall at uks.eu, Rabea.Hall at uniklinikum-saarland.de, and frank.lammert at uks.eu Table updated 7-19-2011 Index Sample ID Strain ID Treatment 1 504 B6D2F1 CCl4 2 506 B6D2F1 CCl4 3 508 B6D2F1 CCl4 4 414 C57BL/6J CCl4 5 488 C57BL/6J CCl4 6 489 C57BL/6J CCl4 7 B6J1 C57BL/6J untreated control 8 B6J2 C57BL/6J untreated control 9 B6J3 C57BL/6J untreated control 10 449 DBA/2J CCl4 11 450 DBA/2J CCl4 12 451 DBA/2J CCl4 13 219.1 DBA/2J untreated control 14 219.2 DBA/2J untreated control 15 219.3 DBA/2J untreated control 16 276 BXD1 CCl4 17 278 BXD1 CCl4 18 279 BXD1 CCl4 19 353 BXD2 CCl4 20 357 BXD2 CCl4 21 358 BXD2 CCl4 22 272 BXD6 CCl4 23 273 BXD6 CCl4 24 274 BXD6 CCl4 25 405 BXD11 CCl4 26 406 BXD11 CCl4 27 408 BXD11 CCl4 28 239 BXD12 CCl4 29 240 BXD12 CCl4 30 241 BXD12 CCl4 31 553 BXD13 CCl4 32 554 BXD13 CCl4 33 555 BXD13 CCl4 34 249 BXD14 CCl4 35 250 BXD14 CCl4 36 288 BXD14 CCl4 37 191 BXD19 CCl4 38 644 BXD19 CCl4 39 645 BXD19 CCl4 40 442 BXD24a CCl4 41 443 BXD24a CCl4 42 444 BXD24a CCl4 43 216 BXD27 CCl4 44 218 BXD27 CCl4 45 290 BXD27 CCl4 46 28 BXD28 CCl4 47 71 BXD28 CCl4 48 129 BXD28 CCl4 49 219 BXD31 CCl4 50 220 BXD31 CCl4 51 231 BXD31 CCl4 52 549 BXD32 CCl4 53 550 BXD32 CCl4 54 551 BXD32 CCl4 55 139 BXD33 CCl4 56 140 BXD33 CCl4 57 559 BXD33 CCl4 58 132 BXD34 CCl4 59 146 BXD34 CCl4 60 147 BXD34 CCl4 61 293 BXD39 CCl4 62 597 BXD39 CCl4 63 599 BXD39 CCl4 64 154 BXD40 CCl4 65 570 BXD40 CCl4 66 572 BXD40 CCl4 67 361 BXD42 CCl4 68 362 BXD42 CCl4 69 373 BXD42 CCl4 70 428 BXD43 CCl4 71 429 BXD43 CCl4 72 556 BXD43 CCl4 73 472 BXD51 CCl4 74 473 BXD51 CCl4 75 474 BXD51 CCl4 76 533 BXD55 CCl4 77 534 BXD55 CCl4 78 535 BXD55 CCl4 79 519 BXD62 CCl4 80 520 BXD62 CCl4 81 521 BXD62 CCl4 82 463 BXD65 CCl4 83 464 BXD65 CCl4 84 465 BXD65 CCl4 85 327 BXD69 CCl4 86 346 BXD69 CCl4 87 347 BXD69 CCl4 88 614 BXD73 CCl4 89 616 BXD73 CCl4 90 619 BXD73 CCl4 91 395 BXD75 CCl4 92 482 BXD75 CCl4 93 483 BXD75 CCl4 94 317 BXD87 CCl4 95 319 BXD87 CCl4 96 322 BXD87 CCl4 97 374 BXD90 CCl4 98 388 BXD90 CCl4 99 389 BXD90 CCl4 100 402 BXD96 CCl4 101 403 BXD96 CCl4 102 404 BXD96 CCl4 103 584 BXD98 CCl4 104 585 BXD98 CCl4 105 607 BXD98 CCl4

Notes:

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Contributor:

Citation:

Data source acknowledgment:

Study Id:

109

• 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)