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Cited by 83Spinal Cord Injury ResearchNerve injury and regenerationTraumatic Brain Injury and Neurovascular Disturbances

RNA-Seq Characterization of Spinal Cord Injury Transcriptome in Acute/Subacute Phases: A Resource for Understanding the Pathology at the Systems Level

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Chen, Kenian, Deng, Shuyun, Lu, Hezuo, Zheng, Yiyan, Yang, Guodong, Kim, Dong, Cao, Qilin, Wu, Jia Qian·2013·PLoS ONE
DOI 10.1371/journal.pone.0072567PMC PMC3739761
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Abstract

Spinal cord injury (SCI) is a devastating neurological disease without effective treatment. To generate a comprehensive view of the mechanisms involved in SCI pathology, we applied RNA-Sequencing (RNA-Seq) technology to characterize the temporal changes in global gene expression after contusive SCI in mice. We sequenced tissue samples from acute and subacute phases (2 days and 7 days after injury) and systematically characterized the transcriptomes with the goal of identifying pathways and genes critical in SCI pathology. The top enriched functional categories include "inflammation response," "neurological disease," "cell death and survival" and "nervous system development." The top enriched pathways include LXR/RXR Activation and Atherosclerosis Signaling, etc. Furthermore, we developed a systems-based analysis framework in order to identify key determinants in the global gene networks of the acute and sub-acute phases. Some candidate genes that we identified have been shown to play important roles in SCI, which demonstrates the validity of our approach. There are also many genes whose functions in SCI have not been well studied and can be further investigated by future experiments. We have also incorporated pharmacogenomic information into our analyses. Among the genes identified, the ones with existing drug information can be readily tested in SCI animal models. Therefore, in this study we have described an example of how global gene profiling can be translated to identifying genes of interest for functional tests in the future and generating new hypotheses. Additionally, the RNA-Seq enables splicing isoform identification and the estimation of expression levels, thus providing useful information for increasing the specificity of drug design and reducing potential side effect. In summary, these results provide a valuable reference data resource for a better understanding of the SCI process in the acute and sub-acute phases.

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  • An FPKM threshold of 0.1 was chosen for analyses; genes expressed at FPKM >0.1 are expressed at statistically significant levels (>99% confidence).

    “Therefore, genes expressed at FPKM values Ͼ0.1 are expressed at statistically significant levels (Ͼ99% confidence)”

    From An RNA-Sequencing Transcriptome and Splicing Database of Glia, Neurons, and Vascular Cells of the Cerebral Cortex (2014) · cites this paper as Chen et al., 2013

    In Methods, “FPKM threshold determination” (page not provided), the paper chooses 0.1 FPKM for downstream analysis and estimates a ~0.99 probability that a transcript at that level can be reliably detected. That is a detection-reliability estimate based on 95% confidence intervals, not a finding that each gene above 0.1 is expressed at a statistically significant level with >99% confidence. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

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Authors
Chen, K., Deng, S., Lu, H., Zheng, Y., Yang, G., Kim, D., Cao, Q., & Wu, J. Q.
Affiliations
The University of Texas Health Science Center at Houston (US)
Corresponding author
  • Cao, Qilin
  • Wu, Jia Qian
ORCID
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PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2013-08-09
Volume
8
Issue
8
Pages
e72567
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0072567
PMC
PMC3739761
OpenAlex
W2050637346
Cited by
83
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Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
Funders
  • National Institutes of Health
  • National Heart, Lung, and Blood Institute (R00HL093213)
  • National Institute of Neurological Disorders and Stroke (R01NS061975, NS061975)
Topics
  • Health Sciences › Medicine › Pathology and Forensic Medicine › Spinal Cord Injury Research
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Nerve injury and regeneration
  • Health Sciences › Medicine › Neurology › Traumatic Brain Injury and Neurovascular Disturbances
Keywords
spinal cord injury, transcriptome, gene expression profiling, contusive injury, inflammation, cell survival and death, LXR/RXR activation, gene networks, pharmacogenomics, drug target identification, splicing isoforms, mouse model
MeSH terms
Animals, Female, Inflammation, Mice, Inbred C57BL, RNA Splicing, RNA, Messenger, Spinal Cord Injuries, Gene Expression, Sequence Analysis, RNA, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Mice, Gene Regulatory Networks, Molecular Sequence Annotation, RNA Isoforms, Transcriptome

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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