MuscleDBs
Contents
Introduction
Skeletal muscles have indispensable functions in human body and also possess prominent regenerative ability. The rapid emergence of Next Generation Sequencing (NGS) data in recent years offers us an unprecedented perspective to understand gene regulatory networks governing skeletal muscle development and regeneration. However, the data from public NGS database are often in raw data format or processed with different procedures, causing obstacles to make full use of them (Yuan et al., 2019) [1]. Herein, we have integrated all information about current databases developed to represent disparate and heterogeneous omics data (with a focus on transcriptomics data) generated for skeletal muscle in different species.
Databases
MuscleDB
The Hughes (UMSL) and Esser (Univ. of Kentucky School of Medicine) labs are assembling a database of muscle tissue gene expression in mice and rat. They profiled global gene expression using RNA-sequencing from different muscle tissues, including 8 unique skeletal muscle tissues. In this repository, authors are developing a web-based platform to explore, visualize, and share these data build on a Shiny dashboard. This data set, MuscleDB, reveals extensive transcriptional diversity, with greater than 50% of transcripts differentially expressed among skeletal muscle tissues. Developers detected mRNA expression of hundreds of putative myokines that may underlie the endocrine functions of skeletal muscle. Authors were able to identify candidate genes that may drive tissue specialization, including Smarca4,Vegfa, and Myostatin (Terry et al., 2018 [2]). This resource allow investigators to perform analyses such as generating muscle-specific Cre-recombinase mouse strains for genetically manipulating specific muscle groups. Most importantly, these data provides the foundation for computational modeling of transcription factor networks, a method authors believe will uncover the genetic mechanisms that establish and maintain muscle specialization.
GeneXX
GeneXX has been developed as a new web-based resource to facilitate exploration of skeletal muscle gene responses to exercise (Reibe et al., 2018 [3]). Users can enter any human gene of interest, (e.g., PPARGC1A) and immediately observe log-fold change values, adjusted P values (q value), and the time point post exercise at which the transcript was measured, with color- and shape-coded symbols to indicate statistical significance and sex of participants, respectively. Also included are PubMed scores and a short summary about the gene of interest from the NCBI gene site. The main feature of geneXX is that it provides an accessible and instant insight into the response of a particular gene of interest to exercise in human skeletal muscle. To demonstrate its utility, authors carried out a meta-analysis on the included data sets and show transcript changes in skeletal muscle that persist regardless of sex, exercise mode, and duration, some of which have had minimal attention in the context of exercise.
SKmDB
MGS resource
NeuroMuscleDB
[Human Skeletal Muscle Proteome Project]
SkeletalVis
Summarized table of the databases
Database | Short description | Data type | Functionality | Statistics | Current status | Reference |
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MuscleDB is a project that uses unbiased RNA sequencing (RNA-seq) to profile global mRNA expression in a wide array of smooth, cardiac, and skeletal muscle tissues from mice and rats. |
Expression profiling by high throughput sequencing. |
User can filter the database search by: |
126 samples, 17 mouse tissues (all from males), 2 female rat tissues, 2 male rat tissues. Six replicates for each tissue; each replicate is 3 individual samples pooled. For mouse tissues, 3 are smooth muscle, 3 are cardiac muscle and 11 are skeletal muscle. For male and female rat samples, both tissues are skeletal. |
The beta-version is alive. The last update is 2 years ago. |
Terry et al., 2018 [2] | |
GeneXX is an online tool for the exploration of transcript changes in skeletal muscle associated with exercise. |
Expression profiling by microarray (Illumina, Affymetrix, or Agilent) and high throughput sequencing (Illumina HiSeq 2000). |
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Reibe et al., 2018 [3] |
Table1. Summarized table of the databases with transcriptomics data generated for skeletal muscle in different species.
References
- Yuan J, Zhou J, Wang H, and Sun H. SKmDB: an integrated database of next generation sequencing information in skeletal muscle. Bioinformatics. 2019 Mar 1;35(5):847-855. DOI:10.1093/bioinformatics/bty705 |
- Terry EE, Zhang X, Hoffmann C, Hughes LD, Lewis SA, Li J, Wallace MJ, Riley LA, Douglas CM, Gutierrez-Monreal MA, Lahens NF, Gong MC, Andrade F, Esser KA, and Hughes ME. Transcriptional profiling reveals extraordinary diversity among skeletal muscle tissues. Elife. 2018 May 29;7. DOI:10.7554/eLife.34613 |
- Reibe S, Hjorth M, Febbraio MA, and Whitham M. GeneXX: an online tool for the exploration of transcript changes in skeletal muscle associated with exercise. Physiol Genomics. 2018 May 1;50(5):376-384. DOI:10.1152/physiolgenomics.00127.2017 |