Introduction

Control of neurogenesis in progenitor cells of the developing CNS involves an elaborate interplay between negative and positive regulators. Neurogenic bHLH factors such as Ascl1 and Neurog2 induce neural progenitors to undergo terminal neurogenic divisions, while inhibitory factors such as components of the Notch pathway and NFI family transcription factors promote proliferative divisions and gliogenesis (Hufnagel et al. 2013; Keeley et al. 2023; Yaron et al. 2006; Clark et al. 2019; Lyu et al. 2021). Studies in species such as zebrafish that undergo injury-induced neurogenesis by reprogramming of endogenous glial cells find that this process requires both upregulation of neurogenic factors and downregulation of inhibitory factors (Fausett, Gumerson, and Goldman 2008; Briona et al. 2015; Lyu et al. 2023). This has recently inspired many studies aimed at inducing neurogenic competence in mammalian glia by selectively targeting these factors (Jorstad et al. 2017; Hoang et al. 2020; Todd et al. 2022, 2021; Le et al. 2025, 2024).

One factor that has attracted considerable interest is the RNA binding protein and splicing regulator Ptbp1, which is widely expressed in non-neuronal cells, including both neural progenitors and glia (Lilleväli, Kulla, and Ord 2001; Boutz et al. 2007). It has been reported that Ptbp1 acts as a broad inhibitor of neuronal-specific splicing (Boutz et al. 2007; Ling et al. 2016), and inhibits maturation of miR-124a, which strongly promotes neurogenesis (Makeyev et al. 2007), while its paralog Ptbp2 promotes neuronal-specific splicing (Licatalosi et al. 2012; Li et al. 2014). It was also proposed that Ptbp1 acts as a master regulator of developmental neurogenesis in the CNS (Shibasaki et al. 2013). This then inspired studies which used Ptbp1 knockdown to attempt to reprogram glia into functional neurons. While it was reported that Ptbp1 knockdown in vivo induced robust generation of functional retinal ganglion cells from Müller glia (Zhou et al. 2020), as well as functional dopaminergic neurons from midbrain astrocytes (Qian et al. 2020), attempts to replicate these results by other groups were unsuccessful (L.-L. Wang et al. 2021; Hoang et al. 2023, 2022; Chen et al. 2022; Xie, Zhou, and Chen 2022). Notably, genetic loss of function of Ptbp1 coupled with scRNA-Seq analysis failed to observe either loss of expression of glial-specific genes or induction of neuron-specific genes in mutant glia (Hoang et al. 2023, 2022).

This result raises questions about previous claims about the central role of Ptbp1 in controlling developmental neurogenesis. Previous functional studies of the role of Ptbp1 in neuronal development were primarily conducted in vitro using RNAi to interrogate Ptbp1 function (Spellman, Llorian, and Smith 2007; Zheng et al. 2012; Linares et al. 2015). The few in vivo studies of Ptbp1 function in developing CNS have also almost exclusively used RNAi, and generally report modest and inconsistent phenotypes (X. Zhang et al. 2016). Conventional Ptbp1 homozygous mutants are lethal, precluding direct analysis of its role in developmental neurogenesis (Shibayama et al. 2009). While one study reported accelerated cortical neurogenesis in Ptbp1 heterozygotes (Shibasaki et al. 2013), these effects were also quite modest and difficult to interpret, given the broader role of Ptbp1 in early embryonic development.

The retina is a highly accessible and tractable model for the study of CNS neurogenesis and cell fate specification (Ptito, Bleau, and Bouskila 2021), and conditional mutagenesis allows selective loss of function of any gene of interest in retinal progenitors without affecting viability (Sauer 1998). We sought to use this approach to investigate the role of Ptbp1 in regulating neurogenesis and cell fate specification in developing retina. While we observe changes in RNA splicing and a moderate acceleration of retinal development as measured by bulk RNA-Seq, we do not observe any changes in proliferation or neurogenesis during retinal development, or changes in the cell type composition of Ptbp1-deficient retinas. Furthermore, we observe only modest changes in gene expression in adult mutant retina using scRNA-Seq analysis. These results demonstrate that Ptbp1 is fully dispensable for retinal development.

Results

Ptbp1 mRNA is primarily expressed in retinal progenitors and Müller glia

To examine the expression patterns of Ptbp1 and Ptbp2 in developing and adult neuroretina, we analyzed scRNA-Seq datasets from mouse and human retina that had been previously generated by our lab (Clark et al. 2019; Lu et al. 2020). We observe robust expression of Ptbp1 mRNA in primary retinal progenitors and Müller glia of both species, with weaker expression in neurogenic progenitors, and little expression detectable in neurons at any developmental age. In contrast, Ptbp2 is expressed in both progenitors and neurons, although with somewhat higher expression in retinal ganglion and amacrine cells (Fig. S1a). We observe that Ptbp1 is expressed in primary progenitors at all developmental ages between E12 and P8 in mice and 9 and 20 gestational weeks in humans, although expression levels are moderately increased at later stages of neurogenesis (Fig. S1b).

Chx10-Cre;Ptbp1^lox/lox mice show loss of Ptbp1 immunoreactivity in developing and mature retina

To selectively disrupt Ptbp1 function in retinal progenitors, we generated Chx10-Cre;Ptbp1^lox/lox mice. In these mice, Cre recombinase is expressed broadly in retinal progenitors from the beginning of neurogenesis onwards (Rowan and Cepko 2004), allowing efficient deletion of the conditional mutant allele of Ptbp1 (Shibasaki et al. 2013) (Fig. 1a). Mutant mice were born at expected Mendelian ratios and showed no gross defects in retinal morphology. To confirm efficient deletion of Ptbp1 in retinal progenitors, we performed immunohistochemistry for Ptbp1 at E14, P1, and P30 in both control Chx10-Cre;Ptbp1^+/l+ and homozygous mutant Chx10-Cre;Ptbp1^lox/lox mice (Fig. 1b-d). At all stages, we observed a loss of Ptbp1 protein expression in retinal progenitors and Müller glia, with a more than ten-fold reduction in the number of immunoreactive Müller glia observed at P30 (Fig. 1e). At both E14 and P1, we also observed a variable level of immunoreactivity in cells in the ganglion cell layer in control mice, which was also seen in Chx10-Cre;Ptbp1^lox/lox mice, suggesting that this may represent crossreactivity with an unknown epitope. This ganglion cell layer staining was not observed at P30, however. This demonstrates that Ptbp1 is efficiently and selectively deleted in retinal progenitors from early stages of neurogenesis.

Figure 1.

Embryonic Chx10-Cre;Ptbp1^lox/lox mice show shifts in temporal identity, increased expression of genes specific to photoreceptors, and altered patterns of RNA splicing

To further investigate the effects of Ptbp1 deletion on embryonic progenitors, we conducted bulk RNA-Seq on whole retina from E16 wildtype, Chx10-Cre;Ptbp1^lox/+, and Chx10-Cre;Ptbp1^lox/lox retinas. A comparison of heterozygous Chx10-Cre;Ptbp1^lox/+and homozygous Chx10-Cre;Ptbp1^lox/lox mutants identified 2075 genes that were significantly differentially expressed (Fig. 2a, Extended Data 1). As expected, homozygotes showed a loss of Ptbp1 expression along with a compensatory upregulation of Ptbp2, as has previously been observed following selective disruption of Ptbp1 in mature Müller glia (Hoang et al. 2022) (Fig. 2b). In addition, we observed a modest increase in expression of multiple genes specific to both rods and cone photoreceptors – including Opn1sw and Rcvrn – as well as altered expression of multiple genes selectively expressed in either early or late-stage RPCs (Clark et al. 2019; Lu et al. 2020; Lyu et al. 2021). For instance, the early-stage RPC-specific genes Sfrp2 and Foxp1 were downregulated, while late-stage RPC-enriched genes such as Sox8, Nfix, and Hes5 were upregulated (Fig. 2b). Gene Ontology (GO) enrichment analysis likewise showed significant upregulation of genes involved in photoreceptor cell development and genes controlling synaptic function (Fig. 2c). However, immunohistochemical analysis does not detect any clear changes in the expression of HuC/D+NeuN, Otx2 or Opn1sw in Chx10-Cre;Ptbp1^lox/loxhomozygous mutants relative to Chx10-Cre;Ptbp1^+/l+ control at either E14 or P0, and the number of Otx2-positive cells at P0 was not altered (Fig. S2). This implies that while at the transcriptional level retinal development in embryonic Ptbp1 mutants appears to be moderately accelerated, based on higher expression of both markers of late-stage retinal progenitors and photoreceptors, this does not result in an increase in number of photoreceptors at this stage.

Figure 2.

In light of the established role of Ptbp1 in regulating RNA splicing in non-neuronal cells, we analyzed splicing differences in Ptbp1-deficient retinas using our dataset. We identified 864 differential percent-spliced-in (PSI) events, including changes in retained introns, alternative 5′ or 3′ splice site usage, mutually exclusive exons, and exon skipping—consistent with the known role of Ptbp1 as a splicing repressor (Fig. 2d–e, Extended Data 1) (Vuong et al. 2016; Yap et al. 2012). To assess whether these splicing changes reflect neuronal or rod photoreceptor maturation, we compared our differential splicing events to those observed in adult neurons and rods (Ling et al. 2020). We found that 8 splicing events (7%) known to be enriched in central nervous system neurons and 19 events (35%) specific to rods overlapped with the splicing changes observed in Ptbp1-deficient retinas. (Fig. 2f, Extended Data 1). Notably, splicing patterns in Ptbp1-deficient retinas showed stronger correlation with Thy1-positive neurons— which exhibit low Ptbp1 expression—and minimal overlap with microglia and auditory hair cells, the adult cell types with the highest Ptbp1 levels (Fig. S3).

Chx10-Cre;Ptbp1^lox/lox mice show no changes in retinal progenitor proliferation or neurogenesis

To determine whether retinal progenitor-specific loss of function of Ptbp1 resulted in a depletion of retinal progenitors, we conducted EdU labeling to quantify the number of cells in S-phase in P0 retina (Fig. 3a). We did not observe any significant differences in the number of EdU-positive cells between wildtype controls and Chx10-Cre;Ptbp1^lox/loxmice (Fig. 2b,c). To determine whether loss of function of Ptbp1 influenced cell type specification in developing retina, we conducted immunostaining for a range of cell type-specific markers in control and Chx10-Cre;Ptbp1^lox/lox mice (Fig. 4). Although Ptbp1 immunoreactivity was lost in homozygous mutant retinas (Fig. 4a), we did not observe any significant changes in the numbers of distribution of Sox9-positive Müller glia (Fig. 4b,f), HuC/D-positive amacrine and ganglion cells (Fig. 4c,f), Otx2-positive bipolar cells and photoreceptors (Fig. 4c,f), Rbpms-positive retinal ganglion cells (Fig. 4d,f), or cone arrestin-positive cone photoreceptors (Fig. 4e,f). Taken together, these findings show that Ptbp1 loss of function induces neither precocious cell cycle exit nor affects normal levels and patterns of developmental neurogenesis and cell fate specification.

Figure 3.

Figure 4.

Adult Chx10-Cre;Ptbp1^lox/lox mice show only modest changes in gene expression in the retina

Despite the lack of any obvious defects in proliferation or cell fate specification in Ptbp1-deficient retinas, it nonetheless remained possible that this mutant might generate more subtle defects that are detectable using single-cell RNA-Seq analysis of whole retina. We therefore generated scRNA-Seq libraries from both P30 Chx10-Cre;Ptbp1^+/l+ and Chx10-Cre;Ptbp1^lox/lox mice. No changes in the identity or composition of any retinal cell type were observed (Fig. 5a-c). A modest number of genes in rod and cone photoreceptors, as well as bipolar neurons, showed statistically significant changes in gene expression (Fig. S4, Extended Data 2). A subset of phototransduction (Pde6g, Guca1a, Pdc, Rcvrn), photoreceptor-specific structural components (Rom1), and rod-specific transcription factors Nrl and Nr2e3, all showed modest but significant increases in expression in rods, while transcription factors such as Otx2 and Prdm1, which are more prominently expressed in immature photoreceptors, showed significantly reduced expression. Cone photoreceptors showed increased expression of some phototransduction components (Pde6c, Rcvrn, Guca1a) and decreased expression of others (Arr3).

Figure 5.

The largest number of differentially-expressed genes were observed in Müller glia (Fig. 5d). Several of the most strongly upregulated genes – notably including Ptbp2, Fxyd6, Mt1, and Mt3 – were previously found to be upregulated by selective loss of function of Ptbp1 in mature Müller glia in Glast-CreER;Ptbp1^lox/lox mice, with nearly a third of all significantly downregulated genes shared between both mutants (Hoang et al. 2022)(Fig. 5e, Extended Data 2). However, no significant changes in canonical markers of Müller glia such as Sox9, Apoe, Glul, or Rlbp1 were observed (Fig. 5f).

Discussion

Previous studies have reported that Ptbp1 acts in neural progenitors in the CNS as a master repressor of neuronal fate (Shibasaki et al. 2013; Hu et al. 2018). If this were the case, we would expect that Ptbp1 loss of function in early development would rapidly lead to precocious cell cycle exit and reduction in the number of progenitor cells. As a result, we would expect to observe an overrepresentation of early-born cell types such as retinal ganglion cells and cone photoreceptors at the expense of late-born cell types such as bipolar interneurons and, in particular, Müller glia. However, we observe that while Ptbp1 is robustly expressed in both retinal progenitors and mature glia, as in other CNS regions, loss of Ptbp1 function in early-stage retinal progenitors does not induce any significant developmental defects. Despite efficient and widespread loss of Ptbp1 expression from E14 onwards, we do not observe any changes in progenitor proliferation, retinal cell type composition, or expression of canonical Müller glia marker genes in mature retina. The changes in gene expression that are observed in adult Ptbp1-deficient retinas are quite modest, although increased levels of several photoreceptor-specific genes are observed. This is consistent with previous studies showing that Ptbp1 knockdown enhances photoreceptor-specific splicing of a subset of alternatively spliced genes (Ling et al. 2020), and implies that this may indirectly increase expression of a subset of rod-specific genes.

At E16, however, homozygous Ptbp1 mutants do show changes in gene expression consistent with previously reported functions. These retinas show increased expression of Ptbp2, the neuronally-enriched paralog of Ptbp1, along with increased expression of genes specific to late-stage progenitors and photoreceptor precursors. Furthermore, Ptbp1 mutants exhibit altered RNA splicing and inclusion of a subset of exons specific to rod photoreceptor. While this is apparently consistent with reports that developmental loss of Ptbp1 function promotes neurogenesis by inducing a neuronal-like splicing pattern in neural progenitors (Hu et al. 2018; Shibasaki et al. 2013; Vuong et al. 2016; Boutz et al. 2007), this does not result in changes in either progenitor proliferation or any change in retinal cell type composition in either the developing or adult retina. This argues against the idea that Ptbp1 loss simply accelerates the timing of neurogenesis, as there is no evidence for increased photoreceptor production or altered proliferation in embryonic or neonatal retina. An alternative interpretation would be that Ptbp1 loss of function leads to the precocious formation of ectopic neurons which rapidly undergo cell death. Further studies will be needed to resolve this question.

Following closely behind studies that fail to show any role for Ptbp1 in regulating glia-to-neuron reprogramming in adult CNS (L.-L. Wang et al. 2021; Hoang et al. 2023, 2022; Chen et al. 2022), these findings call into question previous models that place Ptbp1 in a central position in controlling developmental neurogenesis. The reason for this discrepancy is not entirely clear. Previous studies using knockdown may have been complicated by off-target effects (Jackson et al. 2003), and conditions for in vitro analysis may have accurately replicated conditions in the native CNS. Alternatively, upregulation of the widely expressed paralog Ptbp2 may have compensated for developmental defects resulting from Ptbp1 loss of function. Generation of conditional double mutant mice will be necessary to definitively exclude this possibility. Regardless, this study demonstrates that Ptbp1 is dispensable for the process of retinal neurogenesis and cell fate specification, and we anticipate that this will likely hold for other CNS regions.

Methods

Mice

Mice were raised and housed in a climate-controlled pathogen-free facility on a 14/10 h light/dark cycle. Mice used in this study were Chx10-Cre (JAX #005105) Ptbp1^lox/lox mice carrying loxP sites that flank the promoter and 1st exon of Ptbp1 were generated as described previously (Shibayamaetal.,2009). Chx10-Cre;Ptbp1^lox/loxmice were generated by crossing Chx10-Cre with conditional Ptbp1^lox/lox mice. Maintenance and experimental procedures performed on mice were in accordance with the protocol approved by the Institutional Animal Care and Use Committee (IACUC) at the Johns Hopkins School of Medicine under protocol number MO22M22.

EdU treatment

Chx10-Cre control and Chx10-Cre;Ptbp1^lox/lox neonatal mice were administered EdU (Abcam, #ab146186) via subcutaneous injection at P0 [10-20 μl of PBS (5 mg/ml)]. Retinas were collected two hours post EdU injection for analysis.

Immunohistochemistry and imaging

Collection and immunohistochemical analysis of retinas were performed as described previously (Hoang et al., 2020). Briefly, mouse eye globes were fixed in 4% paraformaldehyde (ElectronMicroscopySciences, #15710) for 1 h at 4°C. Retinas were dissected in 1x PBS and incubated in 30% sucrose overnight at 4°C.

Retinas were then embedded in OCT (VWR, #95057-838), cryosectioned at 16 μm thickness, and stored at −20°C. Sections were dried for 30 min in a 37°C incubator and washed 3 x 5 min with 0.1% TritonX-100 in PBS (PBST). EdU labeling was performed by using Click-iT EdU kit (ThermoFisher, #C10340) following the manufacturer’s instructions. Sections were then incubated in 10% Horse Serum (ThermoFisher, #26050070), 0.4% TritonX-100 in 1x PBS (blocking buffer) for 2 h at room temperature (RT) and then incubated with primary antibodies in the blocking buffer overnight at 4°C. Primary antibodies used in this study were: rabbit anti-Ptbp1 (1:200, Invitrogen, #PA3-81297), rabbit anti-Ptbp1 (1:200, ABclonal, #A6107), rabbit anti-RBPMS (1:200,Proteintech, #151871-AP), rabbit anti-cone arrestin (1:200, Millipore Sigma, #AB15282), goat anti-OTX2 (1:200, R&D Systems, #AF1979), mouse anti-HuC/D (1:200, ThermoFisher Scientific, #A21271), mouse anti-NeuN (1:200, SigmaAldrich, #MAB377), rabbit anti-SOX9 (1:200, SigmaAldrich, #AB5535) and chicken anti-GFP (1:400, ThermoFisher Scientific, #A10262). An equal mixture of anti-HuC/D and NeuN antibodies was used to detect amacrine and ganglion cells.

Sections were washed 3 x 5 min with PBST to remove excess primary antibodies and were incubated in secondary antibodies in blocking buffer for 2 h at RT. Sections were then counterstained with DAPI in PBST, washed 3 x 5 min in PBST and mounted with ProLong Gold Antifade Mountant (Invitrogen, #P36935) under coverslips (VWR, #,48404-453), air-dried, and stored at 4°C. Fluorescent images were captured using a Zeiss LSM 700 confocal microscope.

Cell quantification and statistical analysis

Ptbp1-positive, Sox9-positive, HuC/D/Neun-positive, Otx2-positive, Rbpms-positive, and ArrestinC-positive cells were counted in total from 300µM sections per retina. For cell proliferation quantification, EdU-positive cells were counted from 300µM sections per retina. Each data point in the bar graphs was calculated from an individual retina. All cell quantification data were graphed and analyzed using GraphPad Prism 10. Multiple unpaired t tests were used for analysis between samples of multiple groups. In all tests, values of p <0.05 were considered to indicate significance.

Retinal cell dissociation

Briefly, one female mouse per genotype was euthanized by CO2. Retinas were dissected in fresh ice-cold PBS and retinal cells were dissociated using Papain Dissociation System (LK003150,Worthington). Dissociated cells were resuspended in ice-cold HBAG buffer containing 9.8mL HibernateA (BrainBits, #HALF500), 200mL B27 (ThermoFisher, #17504044), 20mL GlutaMAX (ThermoFisher, #35050061) and 0.5U/mL RNAse inhibitor. Cells were filtered through a 50mm filter. Cell count and viability were determined by using 0.4% Trypan blue.

Bulk RNA-sequencing library preparation

Retinas were dissected from E16 mice embryos and stored at –80C. Frozen retinal tissue was pooled into 7 samples by genotype: wildtype (WT (6 pooled retinas)); heterozygous Ptbp1 mutant Chx10-Cre;Ptbp1^lox/+ (Het1 (5 pooled retinas), Het2 (5 pooled retinas), Het3 (6 pooled retinas)); and homozygous Ptbp1 mutant ((KO1 (4 pooled retinas), KO2 (4 pooled retinas), and KO3 (6 pooled retinas)). RNA was extracted using the RNeasey Micro Plus kit (Qiagen). Illumina Stranded mRNA Prep Ligation kit was used for bulk RNA library preparation. Libraries were sequenced on the Illumina NovaSeq X.

Single-cell RNA-sequencing (scRNA-seq) library preparation

scRNA-seq were prepared on dissociated retinal cells using the 10X Genomics Chromium Single Cell 3’ Reagents Kit v3.1 (10X Genomics, Pleasanton, CA). Libraries were constructed following the manufacturer’s instructions and were sequenced using the Illumina NovaSeq 6000. The sequencing data were aligned to the mm10 reference genome and a cell-by-gene matrix was generated using the Cell Ranger 7.0.1 pipeline (10X Genomics).

ScRNA-seq data analysis

ScRNA-seq of control Chx10-Cre;Ptbp1^+/+ and homozygous mutant Chx10-Cre;Ptbp1^lox/lox mice were analyzed using the Seurat package (Hao et al. 2021). Briefly, cells were filtered to retain those with more than 200 and fewer than 5,000 detected genes, more than 700 and fewer than 10,000 total transcripts, and less than 20% mitochondrial gene content. The data were normalized using the default log-normalization parameters, the top 4000 highly variable features were identified, and data were scaled while regressing out mitochondrial gene content. Principal component analysis (PCA) was then performed on the variable genes followed by louvain clustering and UMAP visualization using the top 12 principal components. Expression of key marker genes within each cell cluster were used to confirm the appropriate assignment of cell types. Differentially expressed genes between groups were determined using the Wilcoxon rank sum test. The clusterProfiler R package was used to perform gene ontology enrichment analysis of biological processes found in the differentially expressed gene lists (Yu et al. 2012).

Bulk RNA-seq analysis

Reads were processed using the rMATS-turbo pipeline (Y. Wang et al. 2024), which performs alignment with STAR and custom splice junction counts. Alignments were generated using the GRCm38 mouse genome (Release M10) with GENCODE annotation. Gene-level counts were then extracted from the resulting BAM files using featureCounts, and differential gene expression was analyzed with the DESeq2 package in R (Liao, Smyth, and Shi 2014; Love, Huber, and Anders 2014). Comparisons between Ptbp1 heterozygous (Het) and knockout (KO) samples identified differentially expressed genes based on an absolute log2 fold change greater than 0.263 (representing at least a 20% change in expression) and an adjusted p-value below 0.05. We incorporated publicly available bulk RNA-seq datasets for comparative analysis, including embryonic day 16 retina (E16: GSM2720095, GSM2720096), postnatal day 28 retina (P28: GSM2720111, GSM2720112), Thy1-positive neurons (GSM2392791), astrocytes (GSM1269903, GSM1269904, microglia (GSM1269913, GSM1269914), hair cells (GSM1602228, GSM1602229), and heart tissue (GSM1223635) (Brooks et al. 2019; Yang et al. 2017; Y. Zhang et al. 2014; Cai et al. 2015; Giudice et al. 2014). Hair cells and heart tissue samples were chosen as examples of high and low Ptbp1 expression, respectively, based on data from ASCOT (Ling et al. 2020). We generated a Pearson correlation matrix to assess overall sample similarity. Splicing differences were evaluated using filtered rMATS output, applying the following thresholds: read coverage ≥ 15, minimum PSI = 0.05, maximum PSI = 0.95, significant FDR (sigFDR) ≤ 0.05, |ΔPSI| ≥ 0.10, background FDR (bgFDR) ≤ 0.5, and background within-group ΔPSI ≤ 0.2. For the E16 and P28 retina datasets, we used more relaxed filters (read coverage ≥ 0, PSI between 0.01 and 0.99) to ensure inclusion of lower-abundance events. Splicing events specific to rods and various neuronal subtypes were queried from the ASCOT supplementary files and visually inspected using the UCSC Genome Browser to assess their presence in bulk RNA-seq datasets. This analysis followed the approach described in previous studies (Carmen-Orozco et al. 2024; Ling et al. 2020).

Data availability

All raw RNA-Seq and scRNA-Seq data are publicly available through the Gene Expression Omnibus under accession numbers GSE300588 and GSE300607. Analysis scripts used in this study are accessible at: https://github.com/csanti88/ptbp1_2025. Bulk RNA-seq and other tissue track plots visualizations are available at: https://genome.ucsc.edu/s/roggercarmen/Ptbp1KO_Retina

Figure supplements

Figure S1.

Figure S2.

Figure S3.

Figure S4.

Acknowledgements

This work was supported by NIH grant R01EY036173 to S.B.

Additional files

Extended Dataset 1. Bulk RNA-Seq analysis. Table of 2075 differentially expressed genes between heterozygous Chx10-Cre;Ptbp1^lox/l+ and homozygous Chx10-Cre;Ptbp1^lox/loxmutants identified by bulk RNA-Seq at E16.5, table of 864 differential splicing changes, and table of adult neuronal and rod enriched splicing events that overlap with the differential splicing events in the bulk RNA-Seq dataset.

Extended Dataset 2. scRNA-Seq analysis. Proportions of cell types in the Ptbp1-Ctrl and Ptbp1-KO scRNA-Seq datasets. Table of differentially expressed genes between Chx10-Cre;Ptbp1^+/+ control and homozygous Chx10-Cre;Ptbp1^lox/lox mutants identified by scRNA-Seq in adult retina for Mϋller glia (496), bipolar cells (433), amacrine cells (138), rod photoreceptor (345) and cone photoreceptor cells (74) with adjusted p-value of 0.05. Positive avg_log2FC scores represent upregulated genes within the Ptbp1-KO sample.

Additional information

Funding

National Eye Institute (R01EY036173)