Peroxisome Proliferator-activated Receptor γ Coactivator-1 α Isoforms Selectively Regulate Multiple Splicing Events on Target Genes.

Martínez-Redondo V, Jannig PR, Correia JC, Ferreira DM, Cervenka I, Lindvall JM, Sinha I, Izadi M, Pettersson-Klein AT, Agudelo LZ, Gimenez-Cassina A, Brum PC, Dahlman-Wright K, Ruas JL

J. Biol. Chem. 291 (29) 15169-15184 [2016-07-15; online 2016-05-28]

Endurance and resistance exercise training induces specific and profound changes in the skeletal muscle transcriptome. Peroxisome proliferator-activated receptor γ coactivator-1 α (PGC-1α) coactivators are not only among the genes differentially induced by distinct training methods, but they also participate in the ensuing signaling cascades that allow skeletal muscle to adapt to each type of exercise. Although endurance training preferentially induces PGC-1α1 expression, resistance exercise activates the expression of PGC-1α2, -α3, and -α4. These three alternative PGC-1α isoforms lack the arginine/serine-rich (RS) and RNA recognition motifs characteristic of PGC-1α1. Discrete functions for PGC-1α1 and -α4 have been described, but the biological role of PGC-1α2 and -α3 remains elusive. Here we show that different PGC-1α variants can affect target gene splicing through diverse mechanisms, including alternative promoter usage. By analyzing the exon structure of the target transcripts for each PGC-1α isoform, we were able to identify a large number of previously unknown PGC-1α2 and -α3 target genes and pathways in skeletal muscle. In particular, PGC-1α2 seems to mediate a decrease in the levels of cholesterol synthesis genes. Our results suggest that the conservation of the N-terminal activation and repression domains (and not the RS/RNA recognition motif) is what determines the gene programs and splicing options modulated by each PGC-1α isoform. By using skeletal muscle-specific transgenic mice for PGC-1α1 and -α4, we could validate, in vivo, splicing events observed in in vitro studies. These results show that alternative PGC-1α variants can affect target gene expression both quantitatively and qualitatively and identify novel biological pathways under the control of this system of coactivators.

Bioinformatics Support and Infrastructure [Collaborative]

Bioinformatics Support, Infrastructure and Training [Collaborative]

PubMed 27231350

DOI 10.1074/jbc.M115.705822

Crossref 10.1074/jbc.M115.705822

pii: M115.705822
pmc: PMC4946932

Publications 9.5.0