Project description:We measured genome-wide chromatin accessibility of embryonic stem cells derived from Diversity Outbred mice. We cultured cells in media with LIF + GSK3-beta inhibitor CHIR99021.
Project description:We measured genome-wide gene expression of embryonic stem cells derived from Diversity Outbred mice. We cultured cells in media with LIF + GSK3-beta inhibitor CHIR99021. All lines were passage 3-8 when RNA was collected. We obtained RNA-Seq from technical replicate cultures for three cell lines.
Project description:To understand the genetic regulation of gene expression and patterns of gene co-expression, we sequenced the transcriptome of the hippocampus of 258 Diversity Outbred (DO) mice of both sexes. DO mice (fourth and fifth generations of outcrossing) were sacrificed between 6-8 weeks of age and hippocampus dissected. Total hippocampal RNA was isolated using a TRIzol Plus RNA purification kit (Life Technologies) and mRNA sequencing library was prepared using a TruSeq kit (Illumina), both according to manufacturer's protocols. Paired-end 100bp reads were obtained using the Illumina HiSeq 2000.
Project description:Clinicians and researchers are turning towards precision medicine to treat and prevent obesity and diabetes, given the known contributions of genetics to these metabolic diseases and the wide variability reported in response to treatments. Animal models that incorporate the genetic diversity present in the human population may help discover novel genetic contributors to metabolic disease and test potential treatments. We characterized the Diversity Outbred (DO) mouse population as a model in which to study interindividual variability in metabolic disease and investigated the presence of metabolic subgroups within the population. Glucose metabolism was assessed in male Diversity Outbred (DO) mice after consumption of a high-fat diet for 14 weeks and profiled transcriptomic changes in liver, adipose, and muscle—key tissues involved in glucose homeostasis. To identify metabolic subgroups, we applied classification and regression tree analyses to metabolic phenotype measures as well as transcriptomic data. These findings suggest that DO mice exhibit a diversity of metabolic phenotypes that can be segmented into subgroups using a machine learning approach. The metabolic subgroups observed in the DO may be a useful for probing the phenotypic variability in metabolic disease observed in humans.
Project description:Purpose: To investigate the sex-dependence of liver transcriptome in Diversity Outbred (DO)-F1 mice Methods: Total RNA was extracted from snap-frozen liver using miRVana total RNA isolation kit (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s protocol. The quality and amount of liver RNA were evaluated using a Bioanalyzer (Agilent, Inc., Santa Clara, CA). The average RNA-integrity score for 162 DO-F1 liver samples was 9.01 ± 0.4. RNA samples from 85 females and 77 males were submitted to the UC Davis DNA Technologies Core at the Genome Center. The RNA-seq libraries were constructed from 1 µg total RNA after poly-A library preparation. To minimize technical variability, all samples were assigned to each lane and the pooled libraries were sequenced on two lanes of the Illumina NovaSeq 6000 sequencing (Illumina Inc., San Diego, CA, USA) to achieve paired-end reads of at least 25 million 150 bp. Only R1 was used in the analysis and only R1 was submitted. Results: Our results demonstrate the tremendous effects of sex on hepatic gene expression. In support of this, genetic loci associated with the transcripts frequently showed sex specificity. We revealed sex-specific candidate genes that were mapped to the quantitative trait loci for aortic lesion area and whose expression was regulated locally regulated via global liver transcriptome. Conclusions: Our study provide a valuable data resource to the research community and show that liver transcriptomic analysis identified diet- or strain-specific pathways to pathogenesis of metabolic syndrome.
Project description:SILAC based protein correlation profiling using size exclusion of protein complexes derived from Mus musculus tissues (Heart, Liver, Lung, Kidney, Skeletal Muscle, Thymus)