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Single-cell analysis of the cellular heterogeneity and interactions in the injured mouse spinal cord

Updated May 16, 2023

The wound healing process that occurs after spinal cord injury is critical for maintaining tissue homeostasis and limiting tissue damage, but eventually results in a scar-like environment that is not conducive to regeneration and repair. A better understanding of this dichotomy is critical to developing effective therapeutics that target the appropriate pathobiology, but a major challenge has been the large cellular heterogeneity that results in immensely complex cellular interactions. In this study, we used single-cell RNA sequencing to assess virtually all cell types that comprise the mouse spinal cord injury site. In addition to discovering novel subpopulations, we used expression values of receptor-ligand pairs to identify signaling pathways that are predicted to regulate specific cellular interactions during angiogenesis, gliosis, and fibrosis. Our dataset is a valuable resource that provides novel mechanistic insight into the pathobiology of not only spinal cord injury but also other traumatic disorders of the CNS.

Jae K LeeUniversity of MiamiJLee22@med.miami.edu
Lindsay M Milich1
James S Choi1
Christine Ryan1
Susana R Cerqueira1
Sofia Benavides1
Stephanie L Yahn1
Pantelis Tsoulfas1
Jae K Lee1
1University of Miami
Ida Zucchi

To reference this project, please use the following link:

https://explore.data.humancellatlas.org/projects/e6773550-c1a6-4949-8643-1a3154cf2670
None
INSDC Project Accessions:GEO Series Accessions:INSDC Study Accessions:

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Analysis Portals

None

Project Label

Milich2021MouseSpinal

Species

Mus musculus

Sample Type

specimens

Anatomical Entity

spinal cord

Organ Part

Unspecified

Selected Cell Types

Unspecified

Disease Status (Specimen)

2 disease statuses

Disease Status (Donor)

2 disease statuses

Development Stage

adult

Library Construction Method

2 library construction methods

Nucleic Acid Source

single cell

Paired End

false

Analysis Protocol

matrix_generation

File Format

5 file formats

Cell Count Estimate

66.2k

Donor Count

16
fastq.gz112 file(s)mtx.gz1 file(s)tsv.gz4 file(s)txt.gz10 file(s)xlsx1 file(s)