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Series GSE101900 Query DataSets for GSE101900
Status Public on Jul 26, 2017
Title In vivo Monitoring of Transcriptional Dynamics After Lower-Limb Muscle Injury Enables Quantitative Classification of Healing
Organism Mus musculus
Experiment type Expression profiling by high throughput sequencing
Summary Traumatic lower-limb musculoskeletal injuries are pervasive amongst athletes and the military and typically an individual returns to activity prior to fully healing, increasing a predisposition for additional injuries and chronic pain. Monitoring healing progression after a musculoskeletal injury typically involves different types of imaging but these approaches suffer from several disadvantages. Isolating and profiling transcripts from the injured site would abrogate these shortcomings and provide enumerative insights into the regenerative potential of an individual’s muscle after injury. In this study, a traumatic injury was administered to a mouse model and healing progression was examined from 3 hours to 1 month using high-throughput RNA-Sequencing (RNA-Seq). Comprehensive dissection of the genome-wide datasets revealed the injured site to be a dynamic, heterogeneous environment composed of multiple cell types and thousands of genes undergoing significant expression changes in highly regulated networks. Four independent approaches were used to determine the set of genes, isoforms, and genetic pathways most characteristic of different time points post-injury and two novel approaches were developed to classify injured tissues at different time points. These results highlight the possibility to quantitatively track healing progression in situ via transcript profiling using high- throughput sequencing.
 
Overall design RNA-Seq time couse of muscle injury healing with controls
 
Contributor(s) Ricke DO, Aguilar C
Citation(s) 26381351
Submission date Jul 26, 2017
Last update date May 15, 2019
Contact name Darrell Orlyn Ricke
E-mail(s) Darrell.Ricke@ll.mit.edu
Phone 1-781-981-8323
Organization name MIT Lincoln Laboratory
Department Group 48 Bioengineering Systems & Technology
Lab Bioinformatics
Street address 244 Wood Street
City Lexington
State/province MA
ZIP/Postal code 02421-6426
Country USA
 
Platforms (1)
GPL11002 Illumina Genome Analyzer IIx (Mus musculus)
Samples (92)
GSM2718225 03h_10_Right
GSM2718226 03h_11_Left
GSM2718227 03h_11_Right
Relations
BioProject PRJNA395895
SRA SRP113605

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SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE101900_Mouse_Healing_RNA-Seq.xlsx 30.3 Mb (ftp)(http) XLSX
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Raw data are available in SRA
Processed data are available on Series record

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