We present Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer. MACS empirically models the shift size of ChIP-Seq tags, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions. MACS compares favorably to existing ChIP-Seq peak-finding algorithms, and is freely available.

Bart Staels and his colleagues show that the transcription factor Rev-erb-α is highly expressed in oxidative muscle and, via loss- and gain-of-function experiments, including pharmacological activation, that it plays a key partin regulating the oxidative capacity of the muscle and exercise endurance. The nuclear receptor Rev-erb-α modulates hepatic lipid and glucose metabolism, adipogenesis and the inflammatory response in macrophages. We show here that Rev-erb-α is highly expressed in oxidative skeletal muscle and that its deficiency in muscle leads to reduced mitochondrial content and oxidative function, as well as upregulation of autophagy. These cellular effects resulted in both impaired mitochondrial biogenesis and increased clearance of this organelle, leading to compromised exercise capacity. On a molecular level, Rev-erb-α deficiency resulted in deactivation of the Lkb1-Ampk-Sirt1–Ppargc-1α signaling pathway. These effects were recapitulated in isolated fibers and in muscle cells after knockdown of the gene encoding Rev-erb-α, Nr1d1. In complementary experiments, Rev-erb-α overexpression in vitro increased the number of mitochondria and improved respiratory capacity, whereas muscle overexpression or pharmacological activation of Rev-erb-α in vivo increased exercise capacity. This study identifies Rev-erb-α as a pharmacological target that improves muscle oxidative function by modulating gene networks controlling mitochondrial number and function.

Peroxisome proliferator–activated receptors (PPARs) regulate energy metabolism and hence are therapeutic targets in metabolic diseases such as type 2 diabetes and non-alcoholic fatty liver disease. While they share anti-inflammatory activities, the PPAR isotypes distinguish themselves by differential actions on lipid and glucose homeostasis. In this Review we discuss the complementary and distinct metabolic effects of the PPAR isotypes together with the underlying cellular and molecular mechanisms, as well as the synthetic PPAR ligands that are used in the clinic or under development. We highlight the potential of new PPAR ligands with improved efficacy and safety profiles in the treatment of complex metabolic disorders.