Retinal proteome profiling of inherited retinal degeneration across three different mouse models suggests common drug targets in retinitis pigmentosa
Data files
Sep 03, 2025 version files 7.83 MB
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pathDDA_P23H.csv
3.94 KB
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pathDDA_Rd10_CLR.csv
13.36 KB
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pathDDA_Rd10_DR.csv
6.82 KB
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pathDDA_RPE65_KO.csv
8.97 KB
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pathDIA_P23H.csv
26.23 KB
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pathDIA_Rd10_DR.csv
20.20 KB
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protDDA_P23H.csv
1.14 MB
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protDDA_Rd10_CLR.csv
695.72 KB
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protDDA_Rd10_DR.csv
1.15 MB
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protDDA_RPE65_KO.csv
733.97 KB
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protDIA_P23H.csv
2.50 MB
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protDIA_Rd10_DR.csv
1.50 MB
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README.md
13.29 KB
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UCI_DDA_P23H_cohort_1.csv
2.34 KB
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UCI_DDA_rd10_CLR_cohort_1.csv
2.30 KB
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UCI_DDA_rd10_DR_cohort_2.csv
1.70 KB
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UCI_DDA_Rpe65-KO_cohort_1.csv
1.10 KB
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UEF_DIA_P23H_cohort_2.csv
1.93 KB
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UEF_DIA_rd10_DR_cohort_3.csv
1.74 KB
Abstract
Inherited retinal degenerations (IRDs) are a leading cause of blindness among the population of young people in the developed world. Approximately half of IRDs initially manifest as a gradual loss of night vision and visual fields, characteristic of retinitis pigmentosa (RP). Due to challenges in genetic testing and the large heterogeneity of mutations underlying RP, targeted gene therapies are an impractical large-scale solution in the foreseeable future. For this reason, identifying key pathophysiological pathways in IRDs that could be targets for mutation-agnostic and disease-modifying therapies (DMTs) is warranted. In this study, we investigated the retinal proteome of three distinct IRD mouse models, in comparison to sex- and age-matched wild-type mice. Specifically, we used the Pde6βRd10 (rd10) and RhoP23H/WT (P23H) mouse models of autosomal recessive and autosomal dominant RP, respectively, as well as the Rpe65^-/-^ mouse model of Leber's congenital amaurosis type 2 (LCA2). The mice were housed at two distinct institutions and analyzed using LC-MS in three separate facilities/instruments following data-dependent and data-independent acquisition modes. This cross-institutional and multi-methodological approach signifies the reliability and reproducibility of the results. The large-scale profiling of the retinal proteome, coupled with in vivo electroretinography recordings, provided us with a reliable basis for comparing the disease phenotypes and severity. Despite evident inflammation, cellular stress, and downscaled phototransduction observed consistently across all three models, the underlying pathologies of RP and LCA2 displayed many differences, sharing only four general KEGG pathways. The opposite is true for the two RP models in which we identify remarkable convergence in proteomic phenotype, even though the mechanism of primary rod death in rd10 and P23H mice is different. Our data highlights the cAMP and cGMP second-messenger signaling pathways as potential targets for therapeutic intervention. The proteomic data are curated and made publicly available, facilitating the discovery of universal therapeutic targets for RP.
Dataset DOI: 10.5061/dryad.c2fqz61pc
Description of the data and file structure
Files and variables
This dataset is showing all proteins identified in indicated group of samples, combined by genotype/group.
Files (data generated at UCI, US):
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protDDA_Rd10_DR.csv
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protDDA_Rd10_CLR.csv
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protDDA_P23H.csv
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protDDA_RPE65_KO.csv
Variables:
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P23H_het_M - heterozygous mice for P23H mutation in Rhodopsin, Male
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P23H_het_F - heterozygous mice for P23H mutation in Rhodopsin, Female
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Rd10_M - A mouse genotype with a point mutation in the Pde6b gene, leading to progressive photoreceptor (especially rod) degeneration, used as a model for retinitis pigmentosa, Male
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Rd10_F - A mouse genotype with a point mutation in the Pde6b gene, leading to progressive photoreceptor (especially rod) degeneration, used as a model for retinitis pigmentosa, Female
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Rd10_M_DR - A mouse genotype with a point mutation in the Pde6b gene, leading to progressive photoreceptor (especially rod) degeneration, used as a model for retinitis pigmentosa, Male, Dark Reared
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Rd10_F_DR - A mouse genotype with a point mutation in the Pde6b gene, leading to progressive photoreceptor (especially rod) degeneration, used as a model for retinitis pigmentosa, Female, Dark Reared
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RPE65_M - Mice lack functional RPE65, leading to impaired visual cycle, absence of 11-cis-retinal, and progressive retinal degeneration, Male
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RPE65_F - Mice lack functional RPE65, leading to impaired visual cycle, absence of 11-cis-retinal, and progressive retinal degeneration, Female
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WT_M - wild type mice, Male
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WT_F - wild type mice, Female
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Razor...unique.peptides
Number of peptides used for quantification: unique to the protein or shared with a minimal number of proteins ("razor" peptides).
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Unique.peptides
Number of peptides that are unique to a single protein group (not shared with others).
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Sequence.coverage....
Percentage of the protein sequence covered by all identified peptides.
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Unique...razor.sequence.coverage....
Sequence coverage based only on unique and razor peptides.
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Unique.sequence.coverage....
Sequence coverage based only on unique peptides.
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Mol..weight..kDa.
Molecular weight of the protein in kilodaltons (kDa).
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Q.value
Adjusted p-value (false discovery rate); measures the confidence of protein/peptide identification.
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Score
A scoring value indicating the quality or confidence of peptide/protein identification (algorithm-dependent).
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Intensity
Total signal intensity of the peptides matched to a protein; often used for quantification.
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iBAQ.peptides
Number of theoretically observable peptides used in iBAQ (intensity-Based Absolute Quantification) calculation.
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MS.MS.count
Number of tandem MS (MS/MS) spectra that have been assigned to peptides from the protein — indicates identification confidence.
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Protein.IDs
List of all protein identifiers (e.g., UniProt IDs) associated with a protein group detected in the experiment.
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Majority.protein.IDs
The main (majority) protein ID(s) among the group — used as a representative identifier for the protein group.
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Protein.names
Common or descriptive names of the proteins (from databases like UniProt).
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Gene.names
Standard gene symbols corresponding to the proteins (e.g., ACTB, GAPDH).
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WT_vs_P23H_logFC
Log₂ fold change of protein abundance between two conditions — here, wild-type (WT) vs. P23H (likely a disease model or mutant). Positive = upregulated in P23H; negative = downregulated.
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id
Unique identifier for each row (protein group) in the dataset, usually automatically generated by the analysis software.
Files: data generated at UEF, Finland
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protDIA_Rd10_DR.csv
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protDIA_P23H.csv
Variables
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P23H_het_M - heterozygous mice for P23H mutation in Rhodopsin, Male
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P23H_het_F - heterozygous mice for P23H mutation in Rhodopsin, Female
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Rd10_M_DR - A mouse genotype with a point mutation in the Pde6b gene, leading to progressive photoreceptor (especially rod) degeneration, used as a model for retinitis pigmentosa, Male, Dark Reared
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Rd10_F_DR - A mouse genotype with a point mutation in the Pde6b gene, leading to progressive photoreceptor (especially rod) degeneration, used as a model for retinitis pigmentosa, Female, Dark Reared
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WT_M - wild type mice, Male
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WT_F - wild type mice, Female
Statistical comparison columns:
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WT_vs_(GENOTYPE)_AveExpr
Average expression level of the protein across all samples (usually log₂-transformed intensity).
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WT_vs_(GENOTYPE)_t
t-statistic from differential expression analysis between WT and P23H groups — reflects the strength and direction of change.
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WT_vs_(GENOTYPE)_P.Value
Raw p-value indicating the probability that the observed difference is due to chance.
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WT_vs_(GENOTYPE)_adj.P.Val
Adjusted p-value (e.g., FDR) correcting for multiple testing — used to assess significance more reliably.
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WT_vs_(GENOTYPE)_B
B-statistic or log-odds that a protein is differentially expressed (higher = more likely DE); used in limma-based analyses.
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WT_vs_(GENOTYPE)_-log(P.Value)
Negative log₁₀ of the p-value — larger values indicate stronger statistical significance (e.g., for volcano plots).
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WT_vs_(GENOTYPE)_-log(adj.P.Val)
Negative log₁₀ of the adjusted p-value — used similarly to emphasize significance after correction.
Protein information columns:
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Protein.Group
Identifier for a group of proteins that cannot be distinguished based on peptides (typically grouped by shared peptides).
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Protein.Ids
UniProt or database accession numbers for proteins in the group.
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Protein.Names
Common or descriptive names of the proteins in the group.
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Genes
Gene symbols associated with the proteins (e.g., RHO, GAPDH).
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WT_vs_(GENOTYPE)_logFC
Log₂ fold change in protein abundance between (GENOTYPE) and WT.
Positive = higher in (GENOTYPE)
Negative = lower in (GENOTYPE)
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First.Protein.Description
Detailed description of the first (or main) protein in the group — includes functional annotation, organism, etc.
This dataset is showing all pathways identified in indicated group of samples, combined by genotype/group.
Files
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pathDIA_P23H.csv - data generated at UEF, Finland
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pathDIA_Rd10_DR.csv - data generated at UEF, Finland
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pathDDA_RPE65_KO.csv - data generated at UCI, US
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pathDDA_P23H.csv - data generated at UCI, US
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pathDDA_Rd10_DR.csv - data generated at UCI, US
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pathDDA_Rd10_CLR.csv - data generated at UCI, US
Variables
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ID
Identifier of the pathway or term (e.g., KEGG ID, GO term ID).
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Description
Name or description of the pathway or biological term (e.g., "Apoptosis", "Oxidative phosphorylation").
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ProteinRatio
Proportion of differentially expressed proteins (DEPs) from your dataset found in the pathway:
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BgRatio
Background ratio — proportion of proteins associated with the pathway in the background (e.g., whole proteome):
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pvalue
Raw p-value from statistical test (e.g., hypergeometric test) indicating enrichment significance.
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p.adjust
Adjusted p-value (e.g., using Benjamini-Hochberg correction) to control for multiple comparisons.
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qvalue
False discovery rate (FDR) estimate — similar to p.adjust, used to assess significance while accounting for multiple testing.
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geneID of included DEPs
List of gene symbols or IDs for the differentially expressed proteins included in the pathway.
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Count
Number of DEPs from your dataset found in the pathway.
This dataset describes characteristics of each group of samples, combined by genotype/group.
Files
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UCI_DDA_Rpe65-KO_cohort_1.csv - animals at UCI, USA
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UEF_DIA_P23H_cohort_2.csv - animals at UEF, Finland
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UCI_DDA_P23H_cohort_1.csv - animals at UCI, USA
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UEF_DIA_rd10_DR_cohort_3.csv - animals at UEF, Finland
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UCI_DDA_rd10_DR_cohort_2.csv - animals at UCI, USA
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UCI_DDA_rd10_CLR_cohort_1.csv - animals at UCI, USA
Variables
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Mouse ID
Unique identifier assigned to each individual mouse.
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File name
Name of the associated data file (e.g., raw data, image, or analysis file) for that mouse.
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Genotype
Genetic makeup of the mouse (e.g., WT for wild-type, or a specific mutation like P23H).
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Sex
Biological sex of the mouse (Male or Female).
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DOB
Date of Birth — the day the mouse was born.
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Euthanasia date
The date the mouse was euthanized (sacrificed for analysis).
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Euthanasia Method
The procedure used for euthanasia (e.g., CO₂ inhalation, cervical dislocation).
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Euthanasia age (days)
Age of the mouse at the time of euthanasia, calculated in days.
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Housing light condition
Description of the lighting environment in which the mouse was housed (e.g., 12:12 light-dark cycle, constant darkness).
Access information
All files generated during the proteomic analysis
| Dataset | Dataset identifier | Direct Link |
|---|---|---|
| UCI_DDA_P23H_cohort 1 | PXD052547 | https://www.ebi.ac.uk/pride/archive/projects/PXD052547 |
| UCI_DDA_rd10_DR_cohort 2 | PXD052549 | https://www.ebi.ac.uk/pride/archive/projects/PXD052549 |
| UCI_DDA_Rpe65-/- cohort 1 | PXD052554 | https://www.ebi.ac.uk/pride/archive/projects/PXD052554 |
| UCI_DDA_rd10_CLR_cohort 1 | PXD052555 | https://www.ebi.ac.uk/pride/archive/projects/PXD052555 |
| UEF_DIA_rd10_DR_cohort 3 | PXD052698 | https://panoramaweb.org/3IRD_rd10.url |
| UEF_DIA_P23H_cohort 2 | PXD052598 | https://panoramaweb.org/3IRD.url |
Animal Models and Study Design
We used three different mouse models of inherited retinal degenerative diseases (IRD) to discover retinal proteomic changes that are common to retinal degeneration (RD). The models used in this study were B6.CXB1-Pde6brd10/J (RRID: IMSR_JAX:004,297, referred to as rd10), B6.129S6(Cg)-Rhotm1.1Kpal/J (RRID: IMSR_JAX:017,628, referred to as P23H), mouse models of recessive and autosomal dominant retinitis pigmentosa (RP), respectively (18, 19), and B6.129-Rpe65tm1Tmr/J (RRID: IMSR_JAX:035,329, referred to as Rpe65−/−) model of Leber congenital amaurosis type 2 (LCA2) which was a kind gift from Dr Michael Redmond (National Institutes of Health) (20). The rd10 colony was kept as a homozygote. Age- and sex-matched C57BL/6J mice (RRID: IMSR_JAX:000,664) were used as controls. P23H heterozygote mice were bred with C57BL/6J mice, yielding P23H heterozygote and wild-type (WT) littermates. To get Rpe65−/− and their WT littermate mice, we bred heterozygote Rpe65+/− mice together. Only WT and homozygote offspring were used in this study. Several cohorts of mice were raised, and their retinal samples were collected at two different institutions: the University of California, Irvine (UCI) and the University of Eastern Finland (UEF) over the years 2019 to 2021 and 2023, respectively (Table 1). Mice were given water and standard feed ad libitum at both institutions. Retinal proteome analysis was conducted using liquid chromatography-tandem mass spectrometry (LC-MS/MS), employing data-dependent acquisition (DDA) or data-independent acquisition (DIA) modes. Mice reared P0-P29 in DR and in CLR (vivarium) P29-P38.
