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Data Set Group: JAX DBA/2J Monocyte RNA-Seq modify this page

Data Set: JAX DBA/2J Monocyte 1 vs PBMC RNA-Seq (Jun19) modify this page
GN Accession: GN878
GEO Series: No GEO Series yet
Title: Inhibition of monocyte-like cell extravasation protects from neurodegeneration in DBA/2J glaucoma
Organism: Mouse (mm10)
Group: JAX-D2-Mono-RNA-Seq
Tissue: Retina Single-cell RNA-Seq
Dataset Status: Public
Platforms: Illumina ScriptSeq RNA-Seq v2
Normalization: RNA-seq
Contact Information
Pete Williams
The Jackson Laboratory
600 Main Street
Bar Harbor, Maine 04609 USA
Tel. 207-288-1472
Download datasets and supplementary data files

Specifics of this Data Set:
JAX DBA/2J Monocyte 1 vs PBMC RNA-Seq (Jun19)


Glaucoma is characterized by the progressive dysfunction and loss of retinal ganglion cells. Recent work in animal models suggests that a critical neuroinflammatory event damages retinal ganglion cell axons in the optic nerve head during ocular hypertensive injury. We previously demonstrated that monocyte-like cells enter the optic nerve head in an ocular hypertensive mouse model of glaucoma (DBA/2 J), but their roles, if any, in mediating axon damage remain unclear.


About the cases used to generate this set of data:

About the tissue used to generate this set of data:

About the array platform:

About data values and data processing:

RNA-sequencing and analysis

Monocytes from single optic nerve heads or from peripheral blood (restrained cheek bleed) were FAC sorted into 100 μl buffer RLT + 1% βME and frozen at − 80 °C until further processing. Samples were defrosted on ice and homogenized by syringe in RLT Buffer (total volume 300 μl). Total RNA was isolated using RNeasy micro kits as according to manufacturer’s protocols (Qiagen) including the optional DNase treatment step, and quality was assessed using an Agilent 2100 Bioanalyzer. The concentration was determined using a Ribogreen Assay from Invitrogen. Amplified dscDNA libraries were created using a Nugen Ovation RNA-seq System V2 and a primer titration was performed to remove primer dimers from the sample to allow sample inputs as low as 50 pg RNA. The SPIA dscDNA was sheared to 300 bp in length using a Diogenode Disruptor. Quality control was performed using an Agilent 2100 Bioanalyzer and a DNA 1000 chip assay. Library size produced was analysed using qPCR using the Library Quantitation kit/Illumina GA /ABI Prism (Kapa Biosystems). Libraries were barcoded, pooled, and sequenced 6 samples per lane on a HiSeq 2000 sequencer (Illumina) giving a depth of 30–35 million reads per sample.

Following RNA-sequencing samples were subjected to quality control analysis by a custom quality control python script. Reads with 70% of their bases having a base quality score ≥ 30 were retained for further analysis. Read alignment was performed using TopHat v 2.0.7 [34] and expression estimation was performed using HTSeq [35] with supplied annotations and default parameters against the DBA/2 J mouse genome (build-mm10). Bamtools v 1.0.2 [36] were used to calculate the mapping statistics. Differential gene expression analysis between groups was performed using edgeR v 3.10.5 [37] following, batch correction using RUVSeq, the removal of outlier samples and lowly expressed genes by removing genes with less than five reads in more than two samples. Normalization was performed using the trimmed mean of M values (TMM). Unsupervised HC was performed in R (1-cor, Spearman’s rho). Following preliminary analysis, 1 sample was removed as an outlier. Adjustment for multiple testing was performed using false discovery rate (FDR). Genes were considered to be significantly differentially expression at a false discovery rate (FDR; q) of q < 0.05. Pathway analysis was performed in R, IPA (Ingenuity Pathway Analysis, Qiagen), and using publically available tools (see Results).


Experiment Type:

To understand the function of these infiltrating monocyte-like cells, we used RNA-sequencing to profile their transcriptomes. Based on their pro-inflammatory molecular signatures, we hypothesized and confirmed that monocyte-platelet interactions occur in glaucomatous tissue. Furthermore, to test monocyte function we used two approaches to inhibit their entry into the optic nerve head: (1) treatment with DS-SILY, a peptidoglycan that acts as a barrier to platelet adhesion to the vessel wall and to monocytes, and (2) genetic targeting of Itgam (CD11b, an immune cell receptor that enables immune cell extravasation).



Williams, P.A., Braine, C.E., Kizhatil, K. et al. Inhibition of monocyte-like cell extravasation protects from neurodegeneration in DBA/2J glaucoma.Mol Neurodegeneration 14, 6 (2019) https://doi.org/10.1186/s13024-018-0303-3

Data source acknowledgment:

The Authors would like to thank Electron Microscopy, Flow Cytometry, Histology, and Gene Expression Services at The Jackson Laboratory, Rick Libby for careful reading of the manuscript and discussion, Mimi de Vries for assistance with organizing and mouse colonies, Brynn Cardozo and Trip Freeburg for colony maintenance, Jocelyn Thomas for blood collections, Philipp Tauber for assistance with immunofluorescence, and Amy Bell for intraocular pressure measurements.

EY011721 (SWMJ), EY021525 (GRH). Pete Williams is supported by the Karolinska Institutet in the form of a Board of Research Faculty Funded Career Position. Simon John is an Investigator of HHMI.

Study Id:

CITG Web services initiated January, 1994 as Portable Dictionary of the Mouse Genome; June 15, 2001 as WebQTL; and Jan 5, 2005 as GeneNetwork. This site is currently operated by Rob Williams, Pjotr Prins, Zachary Sloan, Arthur Centeno. Design and code by Pjotr Prins, Zach Sloan, Arthur Centeno, Danny Arends, Christian Fischer, Sam Ockman, Lei Yan, Xiaodong Zhou, Christian Fernandez, Ning Liu, Rudi Alberts, Elissa Chesler, Sujoy Roy, Evan G. Williams, Alexander G. Williams, Kenneth Manly, Jintao Wang, and Robert W. Williams, colleagues. Python Powered Registered with Nif
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  • NIA Translational Systems Genetics of Mitochondria, Metabolism, and Aging (R01AG043930, 2013-2018)
  • NIAAA Integrative Neuroscience Initiative on Alcoholism (U01 AA016662, U01 AA013499, U24 AA013513, U01 AA014425, 2006-2017)
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