Transcriptional Network Analysis in Muscle Reveals AP-1 as a Partner of PGC-1α in the Regulation of the Hypoxic Gene Program

Abstract

Skeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here, we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor ␥ coactivator 1␣ (PGC-1␣), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1␣ and gene expression upon PGC-1␣ overexpression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto-underestimated number of transcription factor partners involved in mediating PGC-1␣ action. In particular, principal component analysis of TFBSs at PGC-1␣ binding regions predicts that, besides the well-known role of the estrogenrelated receptor ␣ (ERR␣), the activator protein 1 complex (AP-1) plays a major role in regulating the PGC-1␣-controlled gene program of the hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1␣.

Paracrine cross-talk between skeletal muscle and macrophages in exercise by PGC-1α-controlled BNP

“…The high transcript levels of BNP in C2C12 myotubes overexpressing PGC-1α strongly suggest that BNP is indeed regulated by PGC-1α. To further elucidate the epistasis between these two genes, the BNP promoter region was scanned for potential PGC-1α response elements based on previous work on the PGC-1α-controlled transcriptional network in muscle cells12. The activator protein-1 (AP-1) transcription factor protein complex, which binds to Fos-Jun-like motifs, has two predicted binding sites in the genomic region flanking the BNP transcriptional start site (TSS), and is co-activated by PGC-1α12.…”

“…To further elucidate the epistasis between these two genes, the BNP promoter region was scanned for potential PGC-1α response elements based on previous work on the PGC-1α-controlled transcriptional network in muscle cells12. The activator protein-1 (AP-1) transcription factor protein complex, which binds to Fos-Jun-like motifs, has two predicted binding sites in the genomic region flanking the BNP transcriptional start site (TSS), and is co-activated by PGC-1α12. Accordingly, siRNA-based silencing of Fos and Jun strongly reduces the ability of PGC-1α to induce BNP expression12.…”

DNA methylation directs genomic localization of Mbd2 and Mbd3 in embryonic stem cells

“…Several differences in study design may help explain some of the discrepancies between our previous studies and those reported by Baubec et al First, whereas endogenous Mbd3 was examined in ChIP studies performed in Yildirim et al, the bio-tagged Mbd3 in Baubec et al was overexpressed [see Figure S1F from Baubec et al (2013)]. Since overexpression of proteins can promote promiscuous binding as assayed by ChIP (Baresic et al, 2014; Fernandez et al., 2003), it is possible some of the peaks of Mbd3 binding identified by this method are non-physiological. Second, all Mbd3 isoforms were immunoprecipitated in the Yildirim study, rather than the single largest isoform examined in Baubec et al Third, whereas Yildirim et al examined Mbd3 binding to promoter-proximal regions of genes, Baubec et al focused mainly on a subset of LMRs and ICPs.…”

ARMADA: Using motif activity dynamics to infer gene regulatory networks from gene expression data

“…After the initial presentation of MARA and its application to inferring the core regulatory network of a differentiating human cell line [11], MARA has since been applied to a large number of different mammalian systems [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] and extended to model genome-wide chromatin marks in terms of epigenetic motif activities [28]. Remarkably, in all these systems, MARA's predictions of key regulators and their interactions were subsequently confirmed by experimental validation.…”