Transcriptomic analysis of MYTHO in muscle

Gene Ontology analysis was performed on all significantly up- and downregulated genes upon MYTHO knockdown (161 and 53 genes, respectively), using Metascape (http://metascape.org). The gene-level signal intensities after SST-RMA normalization were used to generated heatmaps and hierarchical clustering using webtool Clustvis^{73 (link)}. FunRich software 3.1.4^{74 (link)} was used to generate a Venn diagram of upregulated genes obtained from the NCBI Gene Expression Omnibus (GEO): GSE48363 (GAS/plantaris muscle/cancer)^{75 (link)}, GSE63032 (GAS muscle/cancer cachexia)^{76 (link)} and GSE20103 (TA muscle /24 h STV)^{77 (link)}. For microarray data set, GEOexplorer (https://geoexplorer.rosalind.kcl.ac.uk)^{78 (link)}, was utilized to identify differentially expressed genes (adj p < 0.05 and fold change >1.25) across experimental conditions. We also analyzed Mytho (aka D230025D16Rik) mRNA levels (FDR < 0.05 and fold change >1.25) in GAS muscle of 8 and 28 months old wild-type mice (GSE145480) using SarcoAtlas (https://sarcoatlas.scicore.unibas.ch/)^{79 (link)}.
The RNA-seq data of TA muscles from healthy and myotonic dystrophy type 1 (DM1, aka Steinert disease) individuals were acquired from the Myotonic Dystrophy Deep Sequencing Data Repository (http://www.dmseq.org/) and GEO (GSE86356) repositories, respectively. DM1 patients were classified as mild, moderate, or severe^{80 (link)}. Mytho (aka C16ORF70) mRNA levels (transcripts per million, TPM) were analyzed in tibialis anterior muscle biopsies from control or DM1 patients using one-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger, and Yekutieli (p < 0.05 and q < 0.1 was considered statistically significant).