Project description:Long non-coding RNAs (lncRNAs) are emerging as important players in the regulation of several aspects of cellular biology. For a better comprehension of their function it is fundamental to determine their tissue or cell specificity and to identify their subcellular localization. In fact, the activity of lncRNAs may vary according to cell-type specific expression and subcellular localization. Myofibers are motor units of skeletal muscles characterized by great metabolic plasticity. How lncRNAs are expressed in different myofibers, participate to metabolism regulation, and are compartmentalized within a single myofiber is still unknown. We compiled a complete and integrated catalogue of lncRNAs expressed in skeletal muscle, associating the fiber-type specificity and subcellular location to each of them, demonstrating that many are altered when muscles changes myofiber composition and metabolism according to specific stimuli. We demonstrated that the lncRNA Pvt1, activated early during muscle atrophy, impacts mitochondrial respiration and morphology and affects mito/autophagy and myofiber size in vivo by binding specific DNA regions. This work corroborates the importance of lncRNAs in the regulation of metabolism and neuromuscular pathologies and offers a valuable resource to study the metabolism in single cells characterized by pronounced plasticity.
Project description:Background: skeletal muscle is a complex, versatile tissue composed of a variety of functionally diverse fiber types. Although the biochemical, structural and functional properties of myofibers have been the subject of intense investigation for the last decades, understanding molecular processes regulating fiber type diversity is still complicated by the heterogeneity of cell types present in the whole muscle organ. Methodology/Principal Findings: we have produced a first catalogue of genes expressed in mouse slow-oxidative (type 1) and fast-glycolytic (type 2B) fibers through transcriptome analysis at the single fiber level (microgenomics). Individual fibers were obtained from murine soleus and EDL muscles and initially classified by myosin heavy chain isoform content. Gene expression profiling on high density DNA oligonucleotide microarrays showed that both qualitative and quantitative improvements were achieved, compared to results with standard muscle homogenate. First, myofiber profiles were virtually free from non-muscle transcriptional activity. Second, thousands of muscle-specific genes were identified, leading to a better definition of gene signatures in the two fiber types as well as the detection of metabolic and signaling pathways that are differentially activated in specific fiber types. Several regulatory proteins showed preferential expression in slow myofibers. Discriminant analysis revealed novel genes that could be useful for fiber type functional classification. Conclusions/Significance: as gene expression analyses at the single fiber level significantly increased the resolution power, this innovative approach would allow a better understanding of the adaptive transcriptomic transitions occurring in myofibers under physiological and pathological conditions.
Project description:Background: skeletal muscle is a complex, versatile tissue composed of a variety of functionally diverse fiber types. Although the biochemical, structural and functional properties of myofibers have been the subject of intense investigation for the last decades, understanding molecular processes regulating fiber type diversity is still complicated by the heterogeneity of cell types present in the whole muscle organ. Methodology/Principal Findings: we have produced a first catalogue of genes expressed in mouse slow-oxidative (type 1) and fast-glycolytic (type 2B) fibers through transcriptome analysis at the single fiber level (microgenomics). Individual fibers were obtained from murine soleus and EDL muscles and initially classified by myosin heavy chain isoform content. Gene expression profiling on high density DNA oligonucleotide microarrays showed that both qualitative and quantitative improvements were achieved, compared to results with standard muscle homogenate. First, myofiber profiles were virtually free from non-muscle transcriptional activity. Second, thousands of muscle-specific genes were identified, leading to a better definition of gene signatures in the two fiber types as well as the detection of metabolic and signaling pathways that are differentially activated in specific fiber types. Several regulatory proteins showed preferential expression in slow myofibers. Discriminant analysis revealed novel genes that could be useful for fiber type functional classification. Conclusions/Significance: as gene expression analyses at the single fiber level significantly increased the resolution power, this innovative approach would allow a better understanding of the adaptive transcriptomic transitions occurring in myofibers under physiological and pathological conditions. EDL and soleus muscles were incubated with type I collagenase to dissociate intact myofibres that were separated under stereo microscope from the bulk of hyper contracted fibres. Isolated myofibres were divided in two parts: one was immersed in Laemmli buffer for fibre typing; the other was placed in RNA extraction buffer for RNA amplification. We analyzed the transcription profiles of 10 biological replicas of type 2B single muscle fibres from EDL and 10 biological replicas of type 1 single muscle fibres from soleus. Microarray competitive hybridizations were carried out against an artificial control with a balanced composition of type 1 and type 2B fibres (20 hybridizations). Each oligonucleotide is spotted in two replicates on the glass slide, so for every data two intra-slide replicas are present. The control was created as follows: three couples of soleus and EDL muscles were removed from 3 different mice and treated with collagenase. Total RNA was extracted separately from EDL and soleus muscles. By mixing about 1/3 RNA from EDL and 2/3 RNA from soleus muscles the control had approximately the same contributions of type 1 and type 2B fibres. Purified RNA samples from single fibres and from control were amplified twice using the Amino Allyl MessageAmpM-bM-^DM-" II aRNA Amplification Kit (Ambion).
Project description:In order to invetigate the impact of CpG methylation on gene expression, transcriptomic profiling using microarray were conducted on the fast and slow type myofibers.
Project description:Skeletal muscle myofibers, categorized into slow-twitch (type I) and fast-twitch (type II) fibers based on myosin heavy chain (MHC) isoforms, exhibit varying fatigue resistance and metabolic reliance. Type I myofibers are fatigue-resistant with high mitochondrial density and oxidative metabolism, while Type II myofibers fatigue quickly due to glycolytic metabolism and fewer mitochondria. Endurance training induces remodeling of myofiber and mitochondrial, increasing slow-twitch myofibers and enhancing mitochondrial oxidative capacity, improving muscle fitness. In our study, conducted using single-cell techniques, we delved deeply into the transcriptomic differences between type I and type IIb myofibers. In response to endurance training, type I myofibers exhibited heightened signals in essential adaptive responses, such as fatty acid oxidation, mitochondrial biogenesis, and protein synthesis, compared to type IIb myofibers. By analyzing untrained myofibers, we identified specific signaling pathways that explain the differences in their responses to endurance training. These findings provide nuanced insights into the molecular mechanisms governing endurance adaptations in fast and slow-twitch muscles, offering valuable guidance for tailored exercise routines and potential therapeutic interventions.
Project description:Fast and slow skeletal muscles show different characteristics and phenotypes. This data obtained from microarray includes the comparison of normal fast plantaris and slow soleus muscles of adult rats. Characters of slow muscle are strongly dependent on the level of muscular activity. Denervation silences the muscular activity. Therefore, we determined the effects of denervation on gene expression in slow soleus muscle of adult rats.
Project description:Fast and slow skeletal muscles show different characteristics and phenotypes. This data obtained from microarray includes the comparison of normal fast plantaris and slow soleus muscles of adult rats. Characters of slow muscle are strongly dependent on the level of muscular activity. Denervation silences the muscular activity. Therefore, we determined the effects of denervation on gene expression in slow soleus muscle of adult rats. Denervation was performed by transection (~5 mm) of left sciatic nerve at the gluteal level. No treatments were made in the normal control rats. Sampling of soleus and/or plantaris was performed in both normal and experimental groups 28 days after the surgery.
Project description:We performed the first quantitative proteomics analysis of differences between striated (fast) and catch (slow) adductor muscle in Yesso scallop (Patinopecten yessoensis), with the goal to uncover muscle specific genes and proteins, as well as enzymes of metabolic pathways in fast and slow adductor muscle of scallops. The present findings highlight the functional roles of muscle contractile proteins, calcium signaling pathways, membrane and extracellular matrix proteins, and glycogen metabolism involved in the different contractile and metabolic properties between fast and slow muscles. The present findings will help better understand the molecular basis underlying muscle contraction and its physiological regulation in invertebrates.
Project description:Comparing the gene expression profiles of slow and fast skeletal muscle (soleus VS FDB) with either amplified RNA (cRNA probes) or original mRNA (cDNA probes). The fidelity of mRNA amplification method in identifying the gene expression profiles of our samples were validated. Keywords: cell type comparison
Project description:The purpose of this study is to compare transcriptome profiles of one fast wilting and two slow wilting genotypes under low- and high- vapor pressure deficit Experiments: Five differential expression analyses were performed. 1. Differences within the Hutchesen line for slow and fast wilting; 2. Differences within the PI471938 line for slow and fast wilting; 3. Differences within the PI416937 line for slow and fast wilting; Differences between Hutchesen, PI471938 and PI416937 (regardless of pheotype); 5. Comparison between all lines and all pheotypes Methods: RNASeq data was generated using the Illumina HiSeq. Data passing quality control was processed as follows: Alignment to reference genome Gmax_109 using Tophat2 followed by the Tuxedo pipeline (cufflinks, cuffmerge, cuffdiff). Three cultivars, (wild-type Hutchesen and two parentla lines - PI471938 and PI416937; two conditions (normal and slow-wilting); two reps each for a total of 12 samples