Shayler DWH, Stachelek K, Cambier L, Lee S, Bai J, Bhat B, Reid MW, Weisenberger DJ, Aparicio JG, Kim Y, Singh M, Bay M, Thornton ME, Doyle EK, Fouladian Z, Erberich SG, Grubbs BH, Bonaguidi MA, Craft CM, Singh HP, Cobrinik D. (2025) Identification and characterization of early human photoreceptor states and cell-state-specific retinoblastoma-related features. eLife 13:RP101918. [article]
The retina is a light-sensitive neural tissue that lines the back of the eye, comprised of retinal cells that are essential for vision. All human retinal cells, subclassed as cone or rod photoreceptors, are generated in the womb. Abnormalities in retinal cell development can cause vision-threating disorders, such as retinal dystrophies and retinoblastoma, an early childhood retina cancer. Interestingly, human cone photoreceptors – but not rod photoreceptors – serve as the cell-of-origin in retinoblastoma. Understanding normal retinal development is critical to improving prevention and treatment of these conditions.
Researchers at the Children’s Hospital Los Angeles aimed to identify and characterize the early development of cone and rod photoreceptors using full-length single-cell RNA sequencing, a method that enables identification of RNA isoforms – alternative versions of gene transcripts that help shape cell identity and function – of around 8,000 genes in each developing retinal cell. This approach offers a more detailed portrait of retinal development than previous methods, allowing precise resolution of cell states and identification of cell-type-specific regulatory networks and transcript isoforms to better understand why cone cells can be susceptible to retinoblastoma development. David Cobrinik, MD, PhD, and colleagues determined that early-stage cone photoreceptors (cone precursors) exhibit transcriptomic features similar to retinoblastoma cells – the cell type that gives rise to retinoblastoma. Cone precursors co-express both cone- and rod-associated genes but preferentially express cone-specific RNA isoforms, mirroring retinoblastoma cells. Notably, cone precursors had high expression of SYK, a protein implicated in cancer biology, which may contribute to retinoblastoma initiation following the loss of the RB1 tumor suppressor gene.
Further analysis identified distinct maturation trajectories among cone and rod precursors, characterized by differences in transcription factor expression and selective expression of RNA isoforms. These findings demonstrate how photoreceptors develop over time and highlight the maturing cone precursor’s intrinsic susceptibility to oncogenic transformation.
Cone-related GNAT2 and rod-related NR2E3 RNA co-expression in human cone precursors.
(A, B) Tiled composite fluorescence image of FW14 retinal section after immunofluorescence staining of RXRγ and NR2E3 and RNA FISH of GNAT2 and NR2E3 (A) and diagram of the same section indicating the most peripheral (i.e., youngest and least mature) and most central (i.e., oldest and most mature) rods and cones (B). Scale bar in A = 500 µm. Boxes indicate regions further evaluated. (C, D). Quantitation of (C) outermost and (D) middle (i.e. sub-outermost) NBL photoreceptor precursors expressing combinations of RXRγ and NR2E3 proteins and GNAT2 and NR2E3 RNAs (n.b., italics are used for RNAs, non-italics for proteins). (E) Patterns of GNAT2 and NR2E3 RNA and RXRγ and NR2E3 protein expression inferred from in situ hybridization and immunofluorescence staining. RXRγ is expressed in the outermost NBL starting in the far periphery, consistent with cone precursors, and in middle NBL cells, starting more centrally, consistent with rod precursors. GNAT2 and NR2E3 RNA co-expression in outermost NBL cells lacked NR2E3 protein, representing putative cone precursors. RXRγ+ retinal ganglion cells in the inner NBL and ganglion cell layer are not shown.
Overall, this study provides a high-resolution map of human photoreceptor development and uncovers molecular features that may predispose cone precursors to retinoblastoma. These insights could inform future strategies to prevent or treat retinal diseases in children and young adults.
Source – Newswise
Shayler DWH, Stachelek K, Cambier L, Lee S, Bai J, Bhat B, Reid MW, Weisenberger DJ, Aparicio JG, Kim Y, Singh M, Bay M, Thornton ME, Doyle EK, Fouladian Z, Erberich SG, Grubbs BH, Bonaguidi MA, Craft CM, Singh HP, Cobrinik D. (2025) Identification and characterization of early human photoreceptor states and cell-state-specific retinoblastoma-related features. eLife 13:RP101918. [article]
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The retina is a light-sensitive neural tissue that lines the back of the eye, comprised of retinal cells that are essential for vision. All human retinal cells, subclassed as cone or rod photoreceptors, are generated in the womb. Abnormalities in retinal cell development can cause vision-threating disorders, such as retinal dystrophies and retinoblastoma, an early childhood retina cancer. Interestingly, human cone photoreceptors – but not rod photoreceptors – serve as the cell-of-origin in retinoblastoma. Understanding normal retinal development is critical to improving prevention and treatment of these conditions.
Researchers at the Children’s Hospital Los Angeles aimed to identify and characterize the early development of cone and rod photoreceptors using full-length single-cell RNA sequencing, a method that enables identification of RNA isoforms – alternative versions of gene transcripts that help shape cell identity and function – of around 8,000 genes in each developing retinal cell. This approach offers a more detailed portrait of retinal development than previous methods, allowing precise resolution of cell states and identification of cell-type-specific regulatory networks and transcript isoforms to better understand why cone cells can be susceptible to retinoblastoma development. David Cobrinik, MD, PhD, and colleagues determined that early-stage cone photoreceptors (cone precursors) exhibit transcriptomic features similar to retinoblastoma cells – the cell type that gives rise to retinoblastoma. Cone precursors co-express both cone- and rod-associated genes but preferentially express cone-specific RNA isoforms, mirroring retinoblastoma cells. Notably, cone precursors had high expression of SYK, a protein implicated in cancer biology, which may contribute to retinoblastoma initiation following the loss of the RB1 tumor suppressor gene.
Further analysis identified distinct maturation trajectories among cone and rod precursors, characterized by differences in transcription factor expression and selective expression of RNA isoforms. These findings demonstrate how photoreceptors develop over time and highlight the maturing cone precursor’s intrinsic susceptibility to oncogenic transformation.
Cone-related GNAT2 and rod-related NR2E3 RNA co-expression in human cone precursors.
(A, B) Tiled composite fluorescence image of FW14 retinal section after immunofluorescence staining of RXRγ and NR2E3 and RNA FISH of GNAT2 and NR2E3 (A) and diagram of the same section indicating the most peripheral (i.e., youngest and least mature) and most central (i.e., oldest and most mature) rods and cones (B). Scale bar in A = 500 µm. Boxes indicate regions further evaluated. (C, D). Quantitation of (C) outermost and (D) middle (i.e. sub-outermost) NBL photoreceptor precursors expressing combinations of RXRγ and NR2E3 proteins and GNAT2 and NR2E3 RNAs (n.b., italics are used for RNAs, non-italics for proteins). (E) Patterns of GNAT2 and NR2E3 RNA and RXRγ and NR2E3 protein expression inferred from in situ hybridization and immunofluorescence staining. RXRγ is expressed in the outermost NBL starting in the far periphery, consistent with cone precursors, and in middle NBL cells, starting more centrally, consistent with rod precursors. GNAT2 and NR2E3 RNA co-expression in outermost NBL cells lacked NR2E3 protein, representing putative cone precursors. RXRγ+ retinal ganglion cells in the inner NBL and ganglion cell layer are not shown.
Overall, this study provides a high-resolution map of human photoreceptor development and uncovers molecular features that may predispose cone precursors to retinoblastoma. These insights could inform future strategies to prevent or treat retinal diseases in children and young adults.
Source – Newswise
Shayler DWH, Stachelek K, Cambier L, Lee S, Bai J, Bhat B, Reid MW, Weisenberger DJ, Aparicio JG, Kim Y, Singh M, Bay M, Thornton ME, Doyle EK, Fouladian Z, Erberich SG, Grubbs BH, Bonaguidi MA, Craft CM, Singh HP, Cobrinik D. (2025) Identification and characterization of early human photoreceptor states and cell-state-specific retinoblastoma-related features. eLife 13:RP101918. [article]
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RNAmel simplifies RNA sequencing data analysis with a reproducible, integrated platform
Heart failure reshapes bone marrow to create inflammation-related immune memory
Overlooked DNA regions surrounding ‘microexons’ hold missing pieces of autism’s genetic puzzle
RiboBA improves detection of hidden protein-coding regions using ribosome profiling
An anti-senescence gene may fight spinal disc deterioration
Scientists identify the neuroblastoma cells that signal poor outcomes
Novel biosensor uses DNA ‘barcodes’ to uncover disease signals in cells
CellART extracts single-cell information from high-resolution spatial transcriptomics
Cell2space restores spatial context to single-cell RNA sequencing data
Urine test may improve bladder cancer diagnosis and guide treatment decisions
DeCoRE – a computational method to resolve RNA structural heterogeneity from RNA structure probing data by direct RNA sequencing
Tracing 700 million years of cell evolution
How should biological replicates be handled in long-read RNA sequencing?
RNA-Seq reveals a new way the developing heart controls its growth
The Human RNome Project Consortium seeks to publish first-ever complete sequence of the body’s RNA
scFlowReport brings multiple single-cell RNA sequencing analyses into one workflow
Long-read RNA sequencing reveals how neurons choose alternative RNA endings
DeOPUS improves cell-type estimates from bulk RNA sequencing
ResolVI improves accuracy in spatial transcriptomics analysis
RNA sequencing reveals transcriptional allele differences in prostate cancer stem cells
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