Tissue-specific gene expression in obese hyperglycemic mice
Mahmoud Ahmed,
Omar Elashkar,
Jong Youl Lee,
Eun Ae Jeong,
Kyung Eun Kim,
Gu Seob Roh,
Deok Ryong Kim
Affiliations
Mahmoud Ahmed
Department of Biochemistry and Convergence Medical Science, Institute of Health Sciences, College of Medicine, Gyeongsang National University
Omar Elashkar
Department of Biochemistry and Convergence Medical Science, Institute of Health Sciences, College of Medicine, Gyeongsang National University
Jong Youl Lee
Department of Anatomy and Convergence Medical Science, Bio Anti-aging Medical Research Center, Institute of Health Sciences, College of Medicine, Gyeongsang National University
Eun Ae Jeong
Department of Anatomy and Convergence Medical Science, Bio Anti-aging Medical Research Center, Institute of Health Sciences, College of Medicine, Gyeongsang National University
Kyung Eun Kim
Department of Anatomy and Convergence Medical Science, Bio Anti-aging Medical Research Center, Institute of Health Sciences, College of Medicine, Gyeongsang National University
Gu Seob Roh
Department of Anatomy and Convergence Medical Science, Bio Anti-aging Medical Research Center, Institute of Health Sciences, College of Medicine, Gyeongsang National University
Deok Ryong Kim
Department of Biochemistry and Convergence Medical Science, Institute of Health Sciences, College of Medicine, Gyeongsang National University
Ob/ob mice are leptin-deficient animals with uninhibited food intake and susceptibility to gain weight and develop type 2 diabetes. The mice have been used to study obesity and diabetes. We generated a dataset of different tissue gene expressions from wild-type and ob/ob mice with a normal diet (ND) or high-fat diet (HFD). The gene expression was profiled at a genome-scale using RNA-seq. We deposited the raw data to the short read archive and the processed data to the gene expression omnibus. In this manuscript, we describe generating the dataset and technical validation of the gene expression profiles. We assessed the quality of the reads, alignment, and the quantification of gene expression. We found that the tissue of origin explained the most variance between samples. Non-coding features differed in their contribution to the mice profiles. Gene expression profiles diverged between the experimental groups. To sum, this dataset can be used to study tissue-specific gene expression in weight gain susceptible mice and the response to HFD.