Search for: All records

Abstract Background Titinopathies are inherited muscular diseases triggered by genetic mutations in the titin gene. Muscular dystrophy with myositis ( mdm ) is one such disease caused by a LINE repeat insertion, leading to exon skipping and an 83-amino acid residue deletion in the N2A-PEVK region of mouse titin. This region has been implicated in a number of titin—titin ligand interactions, hence are important for myocyte signaling and health. Mice with this mdm mutation develop a severe and progressive muscle degeneration. The range of phenotypic differences observed in mdm mice shows that the deletion of this region induces a cascade of transcriptional changes extending to numerous signaling pathways affected by the titin filament. Previous research has focused on correlating phenotypic differences with muscle function in mdm mice. These studies have provided understanding of the downstream physiological effects resulting from the mdm mutation but only provide insights on processes that can be physiologically observed and measured. We used differential gene expression (DGE) to compare the transcriptomes of extensor digitorum longus (EDL), psoas and soleus muscles from wild-type and mdm mice to develop a deeper understand of these tissue-specific responses. Results The overall expression pattern observed shows a well-differentiated transcriptional signature in mdm muscles compared to wild type. Muscle-specific clusters observed within the mdm transcriptome highlight the level of variability of each muscle to the deletion. Differential gene expression and weighted gene co-expression network analysis showed a strong directional response in oxidative respiration-associated mitochondrial genes, which aligns with the poor shivering and non-shivering thermogenesis previously observed. Sln, which is a marker associated with shivering and non-shivering thermogenesis, showed the strongest expression change in fast-fibered muscles. No drastic changes in MYH expression levels were reported, which indicated an absence of major fiber-type switching events. Overall expression shifts in MYH isoforms, MARPs, and extracellular matrix associated genes demonstrated the transcriptional complexity associated with mdm mutation. The expression alterations in mitochondrial respiration and metabolism related genes in the mdm muscle dominated over other transcriptomic changes, and likely account for the late stage cellular responses in the mdm muscles. Conclusions We were able to demonstrate that the complex nature of mdm mutation extends beyond a simple rearrangement in titin gene. EDL, psoas and soleus exemplify unique response modes observed in skeletal muscles with mdm mutation. Our data also raises the possibility that failure to maintain proper energy homeostasis in mdm muscles may contribute to the pathogenesis of the degenerative phenotype in mdm mice. Understanding the full disease-causing molecular cascade is difficult using bulk RNA sequencing techniques due to intricate nature of the disease. The development of the mdm phenotype is temporally and spatially regulated, hence future studies should focus on single fiber level investigations. 

Abstract Background Individual skeletal muscles have evolved to perform specific tasks based on their molecular composition. In general, muscle fibers are characterized as either fast-twitch or slow-twitch based on their myosin heavy chain isoform profiles. This approach made sense in the early days of muscle studies when SDS-PAGE was the primary tool for mapping fiber type. However, Next Generation Sequencing tools permit analysis of the entire muscle transcriptome in a single sample, which allows for more precise characterization of differences among fiber types, including distinguishing between different isoforms of specific proteins. We demonstrate the power of this approach by comparing the differential gene expression patterns of extensor digitorum longus (EDL), psoas, and soleus from mice using high throughput RNA sequencing. Results EDL and psoas are typically classified as fast-twitch muscles based on their myosin expression pattern, while soleus is considered a slow-twitch muscle. The majority of the transcriptomic variability aligns with the fast-twitch and slow-twitch characterization. However, psoas and EDL exhibit unique expression patterns associated with the genes coding for extracellular matrix, myofibril, transcription, translation, striated muscle adaptation, mitochondrion distribution, and metabolism. Furthermore, significant expression differences between psoas and EDL were observed in genes coding for myosin light chain, troponin, tropomyosin isoforms, and several genes encoding the constituents of the Z-disk. Conclusions The observations highlight the intricate molecular nature of skeletal muscles and demonstrate the importance of utilizing transcriptomic information as a tool for skeletal muscle characterization. 

Abstract The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO—a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations—evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)—mechanistic models of molecular “pathways” (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.