Time course of gene expression during mouse skeletal muscle hypertrophy

Abstract

The purpose of this study was to perform a comprehensive transcriptome analysis during skeletal muscle hypertrophy to identify signaling pathways that are operative throughout the hypertrophic response. Global gene expression patterns were determined from microarray results on days 1, 3, 5, 7, 10, and 14 during plantaris muscle hypertrophy induced by synergist ablation in adult mice. Principal component analysis and the number of differentially expressed genes (cutoffs ≥2-fold increase or ≥50% decrease compared with control muscle) revealed three gene expression patterns during overload-induced hypertrophy: early (1 day), intermediate (3, 5, and 7 days), and late (10 and 14 days) patterns. Based on the robust changes in total RNA content and in the number of differentially expressed genes, we focused our attention on the intermediate gene expression pattern. Ingenuity Pathway Analysis revealed a downregulation of genes encoding components of the branched-chain amino acid degradation pathway during hypertrophy. Among these genes, five were predicted by Ingenuity Pathway Analysis or previously shown to be regulated by the transcription factor Kruppel-like factor-15, which was also downregulated during hypertrophy. Moreover, the integrin-linked kinase signaling pathway was activated during hypertrophy, and the downregulation of muscle-specific micro-RNA-1 correlated with the upregulation of five predicted targets associated with the integrin-linked kinase pathway. In conclusion, we identified two novel pathways that may be involved in muscle hypertrophy, as well as two upstream regulators (Kruppel-like factor-15 and micro-RNA-1) that provide targets for future studies investigating the importance of these pathways in muscle hypertrophy.

Keywords: ILK signaling; KLF15; branched-chain amino acid; micro-RNA-1; transcriptome.

Fig. 1.

A two-dimensional principal component analysis (PCA) mapping of the variance in gene expression during hypertrophy. The distribution of each group along the first component (x-axis, PC #1) suggested that the imposition of synergist ablation had the greatest effect on gene expression variability (43.7%). The distribution of groups along the second component (y-axis, PC #2) indicated that the length of time that synergist ablation was applied had the second greatest influence on the variability of gene expression (24.5%).

Fig. 2.

Number of differentially expressed genes in response to mechanical overload. The genes initially selected by Partek Genomics Suite from a twofold increase or a 50% decrease in gene expression compared with control non-overloaded muscle were then uploaded in Ingenuity Pathway Analysis software. This software filtered the mapped genes, which were associated with skeletal muscle analysis. d1–d14, Days 1–14 after surgery, respectively.

Fig. 3.

Canonical pathways associated with skeletal muscle in response to mechanical overload. The top statistically significant canonical pathways were identified from IPA, using a right-tailed Fisher's exact and a P value <0.001 [-log(P value) > 3]. The pathways presented represent the pathways specific to the early (d1), intermediate (d3–d7), and late (d10–d14) gene expression patterns, and those pathways identified across all three patterns. The numbers represent the numbers of either upregulated (↑) or downregulated (↓) genes associated with a specific pathway. iNOS, inducible nitric oxide synthase; PPAR, peroxisome proliferator-activated receptor signaling; VDR, vitamin D receptor; RXR, retinoid X receptor; ILK, integrin-linked kinase; LXR, liver X receptor.

Fig. 4.

Schematic representation of the valine degradation pathway from the differentially regulated genes in response to 3–7 days of mechanical overload. This pathway was adapted from the pathway determined by Ingenuity Pathway Analysis. The genes bolded are predicted targets of KLF15 (Kruppel-like factor-15). The gene expression determined by microarray and the gene names are presented in Table 1.

Fig. 5.

Quantitative PCR of expression of genes involved in the valine degradation pathway. KLF15 was predicted to be an upstream regulator of BCAT2 (branched-chain amino acid transaminase 2) and EHHDAH (enoyl-CoA, hydratase/3-hydroxyacyl CoA dehydrogenase). All results are expressed as the means ± SE (n = 6 at each time point). *Significantly different from the control non-overloaded muscle (d0).

Fig. 6.

Schematic representation of the ILK signaling and its putative regulation by the micro-RNA-1 (miR-1). This pathway was adapted from the pathway determined by Ingenuity Pathway Analysis and represents the main genes differentially regulated in response to 3–7 days of mechanical overload. The gene expression of these components of ILK signaling was determined by microarray and is presented in Table 2. As shown in Table 2, the gene expression of two members of insulin receptor substrate (IRS) family, IRS1 and SH2B2, is decreased and increased, respectively (represented by green in the figure). The gene expression of some components of myosin is either increased or decreased (represented by green in the figure; gene expression presented in Table 2). The genes designated in purple are predicted targets of miR-1. ECM, extracellular matrix; PARVA, parvin-α; RTK, receptor tyrosine kinase; PI3K, phosphoinositide 3-kinase; GSK3, glycogen synthase kinase 3; FN1, fibronectin 1; SNAI2, snail homolog 2; CTN-β, β-catenin; CCND1, cyclin D1; MYC, v-myc myelocytomatosis viral oncogene homolog.

Fig. 7.

Quantitative PCR of expression of miR-1 and genes involved in the ILK signaling pathway (PARVA and SNAI2). miR-1 was predicted by targetScan algorithm to bind PARVA and SNAI2. All results are expressed as means ± SE (n = 6 at each time point). *Significantly different from the control non-overloaded muscle (d0).