| Literature DB >> 34267212 |
Bethany R Kondiles1,2, Haichao Wei3,4, Lesley S Chaboub2, Philip J Horner2, Jia Qian Wu5,6,7, Steve I Perlmutter8.
Abstract
Spinal cord injury disrupts ascending and descending neural signals causing sensory and motor dysfunction. Neuromodulation with electrical stimulation is used in both clinical and research settings to induce neural plasticity and improve functional recovery following spinal trauma. However, the mechanisms by which electrical stimulation affects recovery remain unclear. In this study we examined the effects of cortical electrical stimulation following injury on transcription at several levels of the central nervous system. We performed a unilateral, incomplete cervical spinal contusion injury in rats and delivered stimulation for one week to the contralesional motor cortex to activate the corticospinal tract and other pathways. RNA was purified from bilateral subcortical white matter and 3 levels of the spinal cord. Here we provide the complete data set in the hope that it will be useful for researchers studying electrical stimulation as a therapy to improve recovery from the deficits associated with spinal cord injury.Entities:
Year: 2021 PMID: 34267212 PMCID: PMC8282877 DOI: 10.1038/s41597-021-00953-4
Source DB: PubMed Journal: Sci Data ISSN: 2052-4463 Impact factor: 6.444
Fig. 1Experimental Design and Timeline. (a) Schematic detailing location of electrodes implanted into motor cortex to activate corticospinal neurons (illustrated in red). Hemi-contusion injuries at cervical level 4 disrupted the function of the CST and other pathways (orange oval). Regions 1–5 were isolated for RNA purification. (b) Animals first sustained a unilateral cervical injury, then were implanted with stimulating electrodes 14 days later. Stimulation lasted for one week in two animals; two control animals received no stimulation. Following RNA extraction, purification, and sequencing, the workflow included quality control.
The summary of RNA-Seq statistics.
| Sample | Read1 No. | Read1 Length | Read1 Mapping Rate | Read2 Mapping Rate | RIN Scores |
|---|---|---|---|---|---|
| Control1_region1 | 53,792,745 | 51 | 92.70% | 88.60% | 9.6 |
| Control1_region2 | 56,315,463 | 51 | 93.60% | 89.70% | 9.6 |
| Control1_region3 | 59,005,995 | 51 | 92.90% | 88.70% | 9.3 |
| Control1_region4 | 59,208,539 | 51 | 92.30% | 88.40% | 9.5 |
| Control1_region5 | 52,613,415 | 51 | 93.00% | 88.50% | 10 |
| Control2_region1 | 64,115,161 | 51 | 92.70% | 88.80% | 9.3 |
| Control2_region2 | 56,948,286 | 51 | 94.00% | 89.60% | 9 |
| Control2_region3 | 60,970,792 | 51 | 91.80% | 87.60% | 8.9 |
| Control2_region4 | 53,463,239 | 51 | 93.50% | 89.50% | 9.2 |
| Control2_region5 | 56,028,200 | 51 | 90.40% | 86.60% | 9.6 |
| Treatment1_region1 | 61,564,749 | 51 | 93.10% | 88.70% | 8.6 |
| Treatment1_region2 | 60,636,797 | 51 | 93.50% | 89.30% | 9 |
| Treatment1_region3 | 55,606,216 | 51 | 90.60% | 86.90% | 9.5 |
| Treatment1_region4 | 57,935,339 | 51 | 93.30% | 89.00% | 9.8 |
| Treatment1_region5 | 58,486,827 | 51 | 93.00% | 88.90% | 9.6 |
| Treatment2_region1 | 59,223,921 | 51 | 90.70% | 86.80% | 9.6 |
| Treatment2_region2 | 56,893,902 | 51 | 92.60% | 88.40% | 9.6 |
| Treatment2_region3 | 56,653,588 | 51 | 92.40% | 88.00% | 9.5 |
| Treatment2_region4 | 59,414,002 | 51 | 93.10% | 89.30% | 9.2 |
| Treatment2_region5 | 60,840,758 | 51 | 92.10% | 88.30% | 9.8 |
The mapping rate of read1 or read2 was ranked from 86.6% to 94.0%. The RIN scores for all samples of the RNA-Seq library were more than 8.6.
Fig. 2MultiQC summary plot of FastQC quality assessment for the raw FASTQ sequence data in all samples. (a) The distribution of the mean quality value per base in sequencing reads. (b) The distribution of the mean quality scores per sequence (x-axis). (c) The distribution of guanine-cytosine (GC) content for all sequences, shown as the percentage of reads with specific GC values from 1–100%.
Fig. 3The identification of RNA-Seq data in all samples. (a) The distribution of gene expression values of all samples. The X-axis represents log2-transformed quantile normalized FPKM values. (b) 3D plot of PCA using the 10% of genes with the largest CVs of transformed FPKM values across all samples. Grouping of correlated samples is indicated by color-shaded ovals. Data points are labeled by rat number and region number. For example, R04_1 is region 1 from rat 04. Rats R04 and R05 were unstimulated control animals; rats R10 and R11 received stimulation.
Fig. 4Genome browser views displaying gene expression levels. Gene expressing tracks displaying Lgals3, Cd44, and Gpnmb in Region 1 (a) and Trpv1 in Region 5 (b) of two control and two treatment samples.
| Measurement(s) | RNA |
| Technology Type(s) | RNA sequencing |
| Factor Type(s) | motor cortex electrical stimulation |
| Sample Characteristic - Organism | Rattus norvegicus |