RESUMEN
Spinal cord injury (SCI) is a debilitating condition with an estimated 18,000 new cases annually in the United States. The field has accepted and adopted standardized databases such as the Open Data Commons for Spinal Cord Injury (ODC-SCI) to aid in broader analyses, but these currently lack high-throughput data despite the availability of nearly 6000 samples from over 90 studies available in the Sequence Read Archive. This limits the potential for large datasets to enhance our understanding of SCI-related mechanisms at the molecular and cellular level. Therefore, we have developed a protocol for processing RNA-Seq samples from high-throughput sequencing experiments related to SCI resulting in both raw and normalized data that can be efficiently mined for comparisons across studies, as well as homologous discovery across species. We have processed 1196 publicly available RNA-Seq samples from 50 bulk RNA-Seq studies across nine different species, resulting in an SQLite database that can be used by the SCI research community for further discovery. We provide both the database as well as a web-based front-end that can be used to query the database for genes of interest, differential gene expression, genes with high variance, and gene set enrichments.
RESUMEN
Spinal cord injury (SCI) is a debilitating disease resulting in an estimated 18,000 new cases in the United States on an annual basis. Significant behavioral research on animal models has led to a large amount of data, some of which has been catalogued in the Open Data Commons for Spinal Cord Injury (ODC-SCI). More recently, high throughput sequencing experiments have been utilized to understand molecular mechanisms associated with SCI, with nearly 6,000 samples from over 90 studies available in the Sequence Read Archive. However, to date, no resource is available for efficiently mining high throughput sequencing data from SCI experiments. Therefore, we have developed a protocol for processing RNA-Seq samples from high-throughput sequencing experiments related to SCI resulting in both raw and normalized data that can be efficiently mined for comparisons across studies as well as homologous discovery across species. We have processed 1,196 publicly available RNA-seq samples from 50 bulk RNA-Seq studies across nine different species, resulting in an SQLite database that can be used by the SCI research community for further discovery. We provide both the database as well as a web-based front-end that can be used to query the database for genes of interest, differential gene expression, genes with high variance, and gene set enrichments.
RESUMEN
Reduced muscle mass and increased fatiguability are major complications after spinal cord injury (SCI), and often hinder the rehabilitation efforts of patients. Such detriments to the musculoskeletal system, and the concomitant reduction in level of activity, contribute to secondary complications such as cardiovascular disease, diabetes, bladder dysfunction and liver damage. As a result of decreased weight-bearing capacity after SCI, muscles undergo morphological, metabolic, and contractile changes. Recent studies have shown that exercise after SCI decreases muscle wasting and reduces the burden of secondary complications. Here, we describe RNA sequencing data for detecting chronic transcriptomic changes in the rat soleus after SCI at two levels of injury severity, under conditions of restricted in-cage activity and two methods of applied exercise, swimming or shallow water walking. We demonstrate that the sequenced data are of good quality and show a high alignment rate to the Rattus norvegicus reference assembly (Rn6). The raw data, along with UCSC Genome Browser tracks created to facilitate exploration of gene expression, are available in the NCBI Gene Expression Omnibus (GEO; GSE129694).
