Assessing the translational landscape of myogenic differentiation by ribosome profiling. Issue 9 (14th April 2015)

• Record Type: Journal Article
• Authors: de Klerk, Eleonora; Fokkema, Ivo F.A.C.; Thiadens, Klaske A.M.H.; Goeman, Jelle J.; Palmblad, Magnus; den Dunnen, Johan T.; von Lindern, Marieke; 't Hoen, Peter A.C.
• Is Part Of: Nucleic acids research. Volume 43:Issue 9(2015)
• Page Start: 4408
• Page End: 4428
• Publication Date: 2015-04-14
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkv281
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: The formation of skeletal muscles is associated with drastic changes in protein requirements known to be safeguarded by tight control of gene transcription and mRNA processing. The contribution of regulation of mRNA translation during myogenesis has not been studied so far. We monitored translation during myogenic differentiation of C2C12 myoblasts, using a simplified protocol for ribosome footprint profiling. Comparison of ribosome footprints to total RNA showed that gene expression is mostly regulated at the transcriptional level. However, a subset of transcripts, enriched for mRNAs encoding for ribosomal proteins, was regulated at the level of translation. Enrichment was also found for specific pathways known to regulate muscle biology. We developed a dedicated pipeline to identify translation initiation sites (TISs) and discovered 5333 unannotated TISs, providing a catalog of upstream and alternative open reading frames used during myogenesis. We identified 298 transcripts with a significant switch in TIS usage during myogenesis, which was not explained by alternative promoter usage, as profiled by DeepCAGE. Also these transcripts were enriched for ribosomal protein genes. This study demonstrates that differential mRNA translation controls protein expression of specific subsets of genes during myogenesis. Experimental protocols, analytical workflows, tools and data are available through public repositories (http://lumc.github.io/ribosome-profiling-analysis-framework/ ).