Project description:SNPs affecting disease risk often reside in non-coding genomic regions. Here we show that SNPs are highly enriched at mouse strain-selective adipose tissue binding sites for PPARγ, a nuclear receptor for antidiabetic drugs. Many such SNPs alter binding motifs for PPARγ or cooperating factors, and functionally regulate nearby genes whose expression is strain-selective and imbalanced in heterozygous F1 mice. Moreover, genetically-determined binding of PPARγ accounts for mouse strain-specific transcriptional effects of TZD drugs, providing proof-of- concept for personalized medicine related to nuclear receptor genomic occupancy. In human fat, motif-altering SNPs cause differential PPARγ binding, provide a molecular mechanism for some expression quantitative trait loci, and are risk factors for dysmetabolic traits in genome- wide association studies. One PPARγ motif-altering SNP is associated with HDL levels and other metabolic syndrome parameters. Thus, natural genetic variation in PPARγ genomic occupancy determines individual disease risk and drug response. Comparison of 5 RNA-seq experiments between 2 strains of mice differing in diet and fat depot. One of the experiments was evaluation of the response to a drug Rosiglitazone. Our RNA-seq data comprises primarily of 4 main experiments: The first experiment consists of samples taken from 2 strains of mice and their F1 progeny The samples are all taken from the same depot and when the mice were fed the same chow diet The second experiment has 2 parts, the first one involves samples taken from the 2 strains from the same eWAT depot when they were kept on a Low Fat Diet (LFD) This first part serves as a control for the second one in which the mice were treated with a drug, rosiglitazone in conjunction with a LFD The third experiment consists of samples taken from mice being fed on LFD. The samples are taken from the eWAT depot for both the strains. The fourth experiment consists of samples taken from mice being fed on LFD. The samples are taken from the iWAT depot for both the strains. We also have a solitary sample from a GRO-seq experiment which was done on eWAT in a B6 strain of mice being fed a LFD eWAT: epididymal White Adipose Tissue iWAT: inguinal White Adipose Tissue LFD-12w: mice were fed a control low fat diet (Research Diet D12450B) chow: mice were fed standard rodent chow Diet LFD w/rosiglitazone: Drug rosiglitazone (Cayman Chemicals) was incorporated into low fat diet D12450B by Research Diets at 36mg/kg of diet. Mice received control low fat diet for 10 weeks (age 6-16 weeks), and the rosiglitazone-containing diet versus control diet for the final 2 weeks (until sacrifice at 18 weeks) LFD control for rosi: mice were fed a control low fat diet (Research Diet D12450B)

Project description:We used Fancd2-/- mice to understand its mechanism of action. Transcriptome analysis of cKit+ Sca1+ Lin- (KSL) cells discovered that only four genes changed their expression levels significantly after chronic OXM administration in both Fancd2−/− and wild-type mice: mKi67 and Cenpf were up-regualted by 1.4 fold; Spp1 and Oasl2 were significantly down-regulated by 10.5 and 1.5 fold, respectively. Both mKi67 and Cenpf genes are cell cycle-regulated genes and proliferation markers. Their up-regulation was consistent with our observation in flow cytometry analysis that oxymetholone stimulated the proliferation of hematopoietic stem and progenitor cells. RNAseq analysis showed no effects on mTert mRNA expression with chronic androgen therapy, but instead suggested down-regulation of Spp1 and Oasl2 as an important mechanism for the drug’s action. Our RNAseq analysis also revealed that Fancd2−/− KSL cells showed clear changes in mRNA expression profiles compared to wild-type controls: 430 genes were down-regulated by more than 1.5 fold, whereas 159 genes were up-regulated. Gene ontology analysis revealed key pathways to be significantly altered in Fancd2−/− KSL cells. Besides the abnormal cell cycle status expected from our earlier flow cytometry analysis, surprisingly we noticed that a group of genes involved in immune responses and inflammation, comprising Cfp (Properdin), Socs2, Ccr1, Ccr2, Ccr5, Chga (Chromogranin A), Ifi30 (Interferon Gamma-Inducible Protein 30), Lgmn, Txn, and Sell (selectin L), were up-regulated in Fancd2−/− KSL cells. We therefore hypothesize that some genes up-regulated in FA HSPCs may be part of an innate immune response to DNA damage. In addition, whole bone marrow cells were also analyzed in parallel with KSL cells. As compared to whole bone marrow cells, the genes enriched in KSL cells in wild-type mice were listed in details in the corresponding publication. This information can be a good resource for the future gene expression analysis of HSPCs. Finally, we compared the gene expression profiles of early progenitors between OXM-treated and placebo-treated mice. There were no significant differences at all in gene expression between OXM-treated wild-type erythroid progenitors and their placebo-treated wild-type counterparts, with no genes displaying an expression change higher than 1.2 fold. Importantly, no up-regulation of EPO-inducible genes such as Socs1, Socs2, Socs3, and Cish was seen in wild-type mice treated with OXM. Furthermore, there was no differential expression of the well-known EPO target transferrin receptor or any other major players of the Epo-R signaling network such as Bcl2l1, Cdc25a, Btg3, Ccnd2, Lyl1, Pim3, and Tnfrsf13c. These results indicate that EPO might not play a role in the action of OXM in the erythroid lineage. The goal of this study is to investigate gene expression changes in Fancd2 knockout mice in response to oxymetholone treatment. The study focuses on two bone marrow cell populations: cKit+ Sca1+ Lin- cells (representing hematopoietic stem and progenitor cells) and Ter119+/CD71high/FSChigh cells (representing proerythroblasts and basophilic erythroblasts). Both populations were sorted twice by FACS to ensure the purity. Cells of interest were collected in Trizol and RNA was isolated using RNAeasy mini prep kit. mRNAs were positively selected using oligo(dT)- Dynobeads and treated with DNase I. RNAseq libraries were then constructed using Illumina TruSeq RNA Sample Prep Kit and sequenced as 51 base-length reads on an Illumina HiSeq 2000 genome analyzer. For KSL libraries, each sample represented total mRNA isolated from pooled KSL cells of 5 individual mice; for basophilic erythroblast libraries, each library represented total mRNA isolated from basophilic erythroblasts of one individual mouse; for whole bone marrow libraries, each sample represented a combined library originally from 5 individual mice. All reads were mapped to the mouse reference genome (version mm9) using Bowtie short read aligner software (http://bowtie-bio.sf.net). Most of the data analysis was performed using EdgeR GLM algorithms. For the comparison of oxymetholone KSL libraries vs placebo KSL libraries, more stringent pair-wise comparisons were used to keep a consistent flow cytometric setting among each pair. The common gene list was the one shared by all three comparisons: COM17 vs HSC_101b, HSC_13 vs HSC_18, and HSC_23 vs QZ_35 for Fancd2−/− KSL cells; HSC_3 vs QZ_36, HSC_22 vs HSC_24, and COM15 vs COM16 for wild-type KSL cells. Data-mining and pathway analysis were carried out with the MetaCore integrated software suite (Thomson Reuters, New York, USA).

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Genetic Variation Determines PPARγ Function and Antidiabetic Drug Response In Vivo

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