Project description:Genome-wide DNA methylation and mRNA and the microRNA transcriptome profiling between oxidative and glycolytic skeletal muscles [miRNA-seq]
Project description:The three estrogen related receptors (ERRs) are regulators of oxidative metabolism in many cell types, yet their roles in skeletal muscle have not been elucidated. To address the roles and significance of ERRs for skeletal muscle mitochondria and muscle function, we generated mice lacking combinations of ERRs specifically in skeletal muscle. We then compared the impact of ERR loss on the transcriptomes of EDL and soleus, i.e., muscles rich in glycolytic or oxidative fibers, respectively. Our findings highlight an essential role of ERRs for skeletal muscle oxidative metabolism and identify broad classes of ERR-dependent gene programs in muscle. They also suggest a high degree of functional redundancy among muscle ERR isoforms for the protection of oxidative capacity, with ERR isoform-specific phenotypes being driven primarily, but not exclusively, by their relative levels in different muscles. To compare the relative contributions of ERRs for oxidative capacity in glycolytic and oxidative skeletal muscles, we generated mice lacking one or two ERRs specifically in skeletal muscle. We then performed gene expression profiling analysis using data obtained from RNA-seq of soleus and EDL muscles of WT and ERR KO mice .
Project description:Skeletal muscle were collected from pigs treated in the control group, the Lys deficiency group and the Lys rescue group. Then, the samples were analyzed by LC-MSMS.
Project description:Gene expression in Longissimus lumborum and Semimembranosus skeletal muscles in pig using the GenmascqChip (custom 15K Agilent microarray)
Project description:To obtain an overview of the transcriptome landscape in developing pig skeletal muscle, 81 high-quality transcriptome libraries that covered 27 developmental stages (3 biological replicates per stage) in pig skeletal muscle were produced by strand-specific rRNA-depleted total RNA sequencing (RNA-seq). We generated 8.59 billion paired-end reads (150 bp × 2) covering 1.24 Tb of sequence for RNA-seq.
