Transcript isoforms of Reep6 have distinct functions in the retina.

Much of the complexity of the eukaryotic cell transcriptome is due to the alternative splicing of mRNA. However, knowledge on how transcriptome complexity is translated into functional complexity remains limited. For example, although different isoforms of a gene may show distinct temporal and spatial expression patterns, it is largely unknown whether these isoforms encode proteins with distinct functions matching their expression pattern. In this report, we investigated the function and relationship of the two isoforms of Reep6, namely Reep6.1 and Reep6.2, in rod photoreceptor cells. These two isoforms result from the alternative splicing of exon 5 and show mutually exclusive expression patterns. Reep6.2 is the canonical isoform that is expressed in non-retinal tissues, whereas Reep6.1 is the only expressed isoform in the adult retina. The Reep6.1 isoform-specific knockout mouse, Reep6E5/E5, is generated by deleting exon 5 and a homozygous deletion phenotypically displayed a rod degeneration phenotype comparable to a Reep6 full knockout mouse, indicating that the Reep6.1 isoform is essential for the rod photoreceptor cell survival. Consistent with the results obtained from a loss-of-function experiment, overexpression of Reep6.2 failed to rescue the rod degeneration phenotype of Reep6 knockout mice whereas overexpression of Reep6.1 does lead to rescue. These results demonstrate that, consistent with the expression pattern of the isoform, Reep6.1 has rod-specific functions that cannot be substituted by its canonical isoform. Our findings suggested that a strict regulation of splicing is required for the maintenance of photoreceptor cells.

Clinical presentation, treatment, and genetic and histopathological analysis of juvenile cataracts and secondary glaucoma in a rhesus macaque (Macaca mulatta).

This report describes the clinical and histological findings, genetic study, and treatment in a 1.3-year-old rhesus macaque with bilateral cataracts and unilateral secondary glaucoma. Intravitreal injection of gentamicin decreased the intraocular pressure from 56 to <2 mm Hg. A putative genetic cause of the cataracts was not identified.

Ceramide synthase TLCD3B is a novel gene associated with human recessive retinal dystrophy.

PURPOSE: Previous studies suggest that ceramide is a proapoptotic lipid as high levels of ceramides can lead to apoptosis of neuronal cells, including photoreceptors. However, no pathogenic variant in ceramide synthases has been identified in human patients and knockout of various ceramide synthases in mice has not led to photoreceptor degeneration. METHODS: Exome sequencing was used to identify candidate disease genes in patients with vision loss as confirmed by standard evaluation methods, including electroretinography (ERG) and optical coherence tomography. The vision loss phenotype in mice was evaluated by ERG and histological analyses. RESULTS: Here we have identified four patients with cone-rod dystrophy or maculopathy from three families carrying pathogenic variants in TLCD3B. Consistent with the phenotype observed in patients, the Tlcd3bKO/KO mice exhibited a significant reduction of the cone photoreceptor light responses, thinning of the outer nuclear layer, and loss of cone photoreceptors across the retina. CONCLUSION: Our results provide a link between loss-of-function variants in a ceramide synthase gene and human retinal dystrophy. Establishment of the Tlcd3b knockout murine model, an in vivo photoreceptor cell degeneration model due to loss of a ceramide synthase, will provide a unique opportunity in probing the role of ceramide in survival and function of photoreceptor cells.

Knockout of mouse receptor accessory protein 6 leads to sperm function and morphology defects†.

Receptor accessory protein 6 (REEP6) is a member of the REEP/Ypt-interacting protein family that we recently identified as essential for normal endoplasmic reticulum homeostasis and protein trafficking in the retina of mice and humans. Interestingly, in addition to the loss of REEP6 in our knockout (KO) mouse model recapitulating the retinal degeneration of humans with REEP6 mutations causing retinitis pigmentosa (RP), we also found that male mice are sterile. Herein, we characterize the infertility caused by loss of Reep6. Expression of both Reep6 mRNA transcripts is present in the testis; however, isoform 1 becomes overexpressed during spermiogenesis. In vitro fertilization assays reveal that Reep6 KO spermatozoa are able to bind the zona pellucida but are only able to fertilize oocytes lacking the zona pellucida. Although spermatogenesis appears normal in KO mice, cauda epididymal spermatozoa have severe motility defects and variable morphological abnormalities, including bent or absent tails. Immunofluorescent staining reveals that REEP6 expression first appears in stage IV tubules within step 15 spermatids, and REEP6 localizes to the connecting piece, midpiece, and annulus of mature spermatozoa. These data reveal an important role for REEP6 in sperm motility and morphology and is the first reported function for a REEP protein in reproductive processes. Additionally, this work identifies a new gene potentially responsible for human infertility and has implications for patients with RP harboring mutations in REEP6.

Metal chelator EGCG attenuates Fe(III)-induced conformational transition of α-synuclein and protects AS-PC12 cells against Fe(III)-induced death.

The fibrillation and aggregation of α-synuclein (AS), along with the conformational transition from random coil to ß-sheet, are the critical steps in the development of Parkinson's disease (PD). It is acknowledged that iron accumulation in the brain may lead to the fibrillation of AS. However, (-)-epigallocatechin gallate (EGCG) can penetrate the blood-brain barrier, chelate metal ions, and inhibit the fibrillation of amyloid proteins. Therefore, EGCG is warranted to be investigated for its potential to cure amyloid-related diseases. In the present work, we sought to study the effects of EGCG on Fe(III)-induced fibrillation of AS on both molecular and cellular levels. We demonstrate that Fe(III) interacts with the amino residue of Tyr and Ala of AS, then accelerates the fibrillation of AS, and increases intracellular reactive oxygen species (ROS) in the AS transduced-PC12 cells (AS-PC12 cells). However, EGCG significantly inhibits this process by chelating Fe(III) and protects AS-PC12 cells against the toxicity induced by ROS and ß-sheet-enriched AS fibrils. These findings yield useful information that EGCG might be a promising drug to prevent and treat the neurodegenerative diseases.

The crystal structure of red fluorescent protein TagRFP-T reveals the mechanism of its superior photostability.

The red fluorescent protein variant TagRFP-T has greatly improved photostability over its parent molecule, TagRFP, but the underlying mechanism leading to this improvement is to date unknown. The 1.95 Å resolution crystallographic structure of TagRFP-T showed that its chromophore exists as a mixture of cis and trans coplanar isomers in roughly equal proportions. Interestingly, both isomers are able to fluoresce, a property that has never been observed in any other fluorescent protein. We propose a "circular restoration model" for TagRFP-T to explain its superior photostability: There are four co-existing chromophore states (cis/trans protonated/ionized state) that can be driven by light to transform from one state into another. This model also explains how TagRPF-T essentially eliminates the temporary dark state (reversible photobleaching).

Structural insights on the catalytic site protection of human carbonyl reductase 1 by glutathione.

The NADPH-dependent human carbonyl reductase 1 (hCBR1), a member of the short-chain dehydrogenase/reductase protein family, plays an important role in the ubiquitous metabolism of endogenous and xenobiotic carbonyl containing compounds. Glutathione (GSH) is also a cofactor of hCBR1, however, its role in the carbonyl reductase function of the enzyme is still unclear. In this study, we presented the crystal structure of hCBR1 in complex with GSH, in the absence of its substrates or inhibitors. Interestingly, we found that the GSH molecule presents in a configuration quite different from that was previously reported when substrate is binding to hCBR1. Our structure indicates that GSH contributes to the substrate selectivity of hCBR1 and protects the catalytic center of hCBR1 through a switch-like mechanism. The isothermal titration calorimetry and enzymology data shows that GSH directly binding with hCBR1 when there's no substrate exist. The enzymology data also shows GSH protects NADPH being attacked by oxidative small molecules. This is the first time that GSH is found to demonstrate such functions as a co-enzyme. Our crystal structure succeeds in providing critical insights into the substrate selectivity of hCBR1 and the interaction between hCBR1 and GSH.

Interpretable Spatial Gradient Analysis for Spatial Transcriptomics Data.

Cellular anatomy and signaling vary across niches, which can induce gradated gene expressions in subpopulations of cells. Such spatial transcriptomic gradient (STG) makes a significant source of intratumor heterogeneity and can influence tumor invasion, progression, and response to treatment. Here we report Local Spatial Gradient Inference (LSGI), a computational framework that systematically identifies spatial locations with prominent, interpretable STGs from spatial transcriptomic (ST) data. To achieve so, LSGI scrutinizes each sliding window employing non-negative matrix factorization (NMF) combined with linear regression. With LSGI, we demonstrated the identification of spatially proximal yet opposite directed pathway gradients in a glioblastoma dataset. We further applied LSGI to 87 tumor ST datasets reported from nine published studies and identified both pan-cancer and tumor-type specific pathways with gradated expression patterns, such as epithelial mesenchymal transition, MHC complex, and hypoxia. The local gradients were further categorized according to their association to tumor-TME (tumor microenvironment) interface, highlighting the pathways related to spatial transcriptional intratumoral heterogeneity. We conclude that LSGI enables highly interpretable STG analysis which can reveal novel insights in tumor biology from the increasingly reported tumor ST datasets.

Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles.

Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy (ACT), have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA sequencing (RNA-seq) datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.

Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles.

Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy, have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA-seq datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.

Integrating genetic regulation and single-cell expression with GWAS prioritizes causal genes and cell types for glaucoma.

Primary open-angle glaucoma (POAG), characterized by retinal ganglion cell death, is a leading cause of irreversible blindness worldwide. However, its molecular and cellular causes are not well understood. Elevated intraocular pressure (IOP) is a major risk factor, but many patients have normal IOP. Colocalization and Mendelian randomization analysis of >240 POAG and IOP genome-wide association study (GWAS) loci and overlapping expression and splicing quantitative trait loci (e/sQTLs) in 49 GTEx tissues and retina prioritizes causal genes for 60% of loci. These genes are enriched in pathways implicated in extracellular matrix organization, cell adhesion, and vascular development. Analysis of single-nucleus RNA-seq of glaucoma-relevant eye tissues reveals that the POAG and IOP colocalizing genes and genome-wide associations are enriched in specific cell types in the aqueous outflow pathways, retina, optic nerve head, peripapillary sclera, and choroid. This study nominates IOP-dependent and independent regulatory mechanisms, genes, and cell types that may contribute to POAG pathogenesis.

Pathway centric analysis for single-cell RNA-seq and spatial transcriptomics data with GSDensity.

Advances in single-cell technology have enabled molecular dissection of heterogeneous biospecimens at unprecedented scales and resolutions. Cluster-centric approaches are widely applied in analyzing single-cell data, however they have limited power in dissecting and interpreting highly heterogenous, dynamically evolving data. Here, we present GSDensity, a graph-modeling approach that allows users to obtain pathway-centric interpretation and dissection of single-cell and spatial transcriptomics (ST) data without performing clustering. Using pathway gene sets, we show that GSDensity can accurately detect biologically distinct cells and reveal novel cell-pathway associations ignored by existing methods. Moreover, GSDensity, combined with trajectory analysis can identify curated pathways that are active at various stages of mouse brain development. Finally, GSDensity can identify spatially relevant pathways in mouse brains and human tumors including those following high-order organizational patterns in the ST data. Particularly, we create a pan-cancer ST map revealing spatially relevant and recurrently active pathways across six different tumor types.

Spatial organization of the mouse retina at single cell resolution by MERFISH.

The visual signal processing in the retina requires the precise organization of diverse neuronal types working in concert. While single-cell omics studies have identified more than 120 different neuronal subtypes in the mouse retina, little is known about their spatial organization. Here, we generated the single-cell spatial atlas of the mouse retina using multiplexed error-robust fluorescence in situ hybridization (MERFISH). We profiled over 390,000 cells and identified all major cell types and nearly all subtypes through the integration with reference single-cell RNA sequencing (scRNA-seq) data. Our spatial atlas allowed simultaneous examination of nearly all cell subtypes in the retina, revealing 8 previously unknown displaced amacrine cell subtypes and establishing the connection between the molecular classification of many cell subtypes and their spatial arrangement. Furthermore, we identified spatially dependent differential gene expression between subtypes, suggesting the possibility of functional tuning of neuronal types based on location.

Single-cell multiomics of the human retina reveals hierarchical transcription factor collaboration in mediating cell type-specific effects of genetic variants on gene regulation.

BACKGROUND: Systematic characterization of how  genetic variation modulates gene regulation in a cell type-specific context is essential for understanding complex traits. To address this question, we profile gene expression and chromatin accessibility in cells from healthy retinae of 20 human donors through single-cell multiomics and genomic sequencing. RESULTS: We map eQTL, caQTL, allelic-specific expression, and allelic-specific chromatin accessibility in major retinal cell types. By integrating these results, we identify and characterize regulatory elements and genetic variants effective on gene regulation in individual cell types. The majority of identified sc-eQTLs and sc-caQTLs display cell type-specific effects, while the cis-elements containing genetic variants with cell type-specific effects are often accessible in multiple cell types. Furthermore, the transcription factors whose binding sites are perturbed by genetic variants tend to have higher expression levels in the cell types where the variants exert their effects, compared to the cell types where the variants have no impact. We further validate our findings with high-throughput reporter assays. Lastly, we identify the enriched cell types, candidate causal variants and genes, and cell type-specific regulatory mechanism underlying GWAS loci. CONCLUSIONS: Overall, genetic effects on gene regulation are highly context dependent. Our results suggest that cell type-dependent genetic effect is driven by precise modulation of both trans-factor expression and chromatin accessibility of cis-elements. Our findings indicate hierarchical collaboration among transcription factors plays a crucial role in mediating cell type-specific effects of genetic variants on gene regulation.

A multi-omics atlas of the human retina at single-cell resolution.

Cell classes in the human retina are highly heterogeneous with their abundance varying by several orders of magnitude. Here, we generated and integrated a multi-omics single-cell atlas of the adult human retina, including more than 250,000 nuclei for single-nuclei RNA-seq and 137,000 nuclei for single-nuclei ATAC-seq. Cross-species comparison of the retina atlas among human, monkey, mice, and chicken revealed relatively conserved and non-conserved types. Interestingly, the overall cell heterogeneity in primate retina decreases compared with that of rodent and chicken retina. Through integrative analysis, we identified 35,000 distal cis-element-gene pairs, constructed transcription factor (TF)-target regulons for more than 200 TFs, and partitioned the TFs into distinct co-active modules. We also revealed the heterogeneity of the cis-element-gene relationships in different cell types, even from the same class. Taken together, we present a comprehensive single-cell multi-omics atlas of the human retina as a resource that enables systematic molecular characterization at individual cell-type resolution.

DeMixSC: a deconvolution framework that uses single-cell sequencing plus a small benchmark dataset for improved analysis of cell-type ratios in complex tissue samples.

Bulk deconvolution with single-cell/nucleus RNA-seq data is critical for understanding heterogeneity in complex biological samples, yet the technological discrepancy across sequencing platforms limits deconvolution accuracy. To address this, we introduce an experimental design to match inter-platform biological signals, hence revealing the technological discrepancy, and then develop a deconvolution framework called DeMixSC using the better-matched, i.e., benchmark, data. Built upon a novel weighted nonnegative least-squares framework, DeMixSC identifies and adjusts genes with high technological discrepancy and aligns the benchmark data with large patient cohorts of matched-tissue-type for large-scale deconvolution. Our results using a benchmark dataset of healthy retinas suggest much-improved deconvolution accuracy. Further analysis of a cohort of 453 patients with age-related macular degeneration supports the broad applicability of DeMixSC. Our findings reveal the impact of technological discrepancy on deconvolution performance and underscore the importance of a well-matched dataset to resolve this challenge. The developed DeMixSC framework is generally applicable for deconvolving large cohorts of disease tissues, and potentially cancer.

A novel stop codon mutation of TSPAN12 gene in Chinese patients with familial exudative vitreoretinopathy.

BACKGROUND: Familial exudative vitreoretinopathy (FEVR) is a group of inherited eye diseases characterized by premature arrest of retinal vessel development. The purpose of our study was to characterize the genetic causes and clinical features in eight Chinese families with FEVR using next-generation sequencing (NGS) technology. MATERIALS AND METHODS: Eight families with FEVR were included in genetic and clinical analyses. We screened the proband and the parents in eight pedigrees with FEVR using targeted NGS approach and in silico analysis to determine the causative mutation for their family's phenotype. RESULTS: Four cases (4/8, 50.0%) were confirmed to harbor mutations in known genes, including 3 novel mutations and one previously reported mutation. Among the detected mutations, TSPAN12 accounted for 75% (3/4). We identified a novel stop codon of TSPAN12, a heterozygous missense mutation NM_012338.4:c.633T>A, NP_036470.1:p.Tyr211Ter involved in highly conserved residues in the proband. Retrospective analysis of its clinical manifestation showed that the mutant carrier presented mild clinical features. CONCLUSIONS: We found the novel stop codon mutation p.Tyr211Ter in the TSPAN12, which creates a milder phenotype. Discovery of this novel mutation expands the mutation spectrum of TSPAN12, and would be valuable for future genetic disease diagnosis.

Bi-order multimodal integration of single-cell data.

Integration of single-cell multiomics profiles generated by different single-cell technologies from the same biological sample is still challenging. Previous approaches based on shared features have only provided approximate solutions. Here, we present a novel mathematical solution named bi-order canonical correlation analysis (bi-CCA), which extends the widely used CCA approach to iteratively align the rows and the columns between data matrices. Bi-CCA is generally applicable to combinations of any two single-cell modalities. Validations using co-assayed ground truth data and application to a CAR-NK study and a fetal muscle atlas demonstrate its capability in generating accurate multimodal co-embeddings and discovering cellular identity.

Stratified Test Accurately Identifies Differentially Expressed Genes Under Batch Effects in Single-Cell Data.

Analyzing single-cell sequencing data from large cohorts is challenging. Discrepancies across experiments and differences among participants often lead to omissions and false discoveries in differentially expressed genes. We find that the Van Elteren test, a stratified version of the widely used Wilcoxon rank-sum test, elegantly mitigates the problem. We also modified the common language effect size to supplement this test, further improving its utility. On both simulated and real patient data we show the ability of Van Elteren test to control for false positives and false negatives. A comprehensive assessment using receiver operating characteristic (ROC) curve shows that Van Elteren test achieves higher sensitivity and specificity on simulated datasets, compared with nine state-of-the-art differential expression analysis methods. The effect size also estimates the differences between cell types more accurately.

Single-nuclei RNA-seq on human retinal tissue provides improved transcriptome profiling.

Single-cell RNA-seq is a powerful tool in decoding the heterogeneity in complex tissues by generating transcriptomic profiles of the individual cell. Here, we report a single-nuclei RNA-seq (snRNA-seq) transcriptomic study on human retinal tissue, which is composed of multiple cell types with distinct functions. Six samples from three healthy donors are profiled and high-quality RNA-seq data is obtained for 5873 single nuclei. All major retinal cell types are observed and marker genes for each cell type are identified. The gene expression of the macular and peripheral retina is compared to each other at cell-type level. Furthermore, our dataset shows an improved power for prioritizing genes associated with human retinal diseases compared to both mouse single-cell RNA-seq and human bulk RNA-seq results. In conclusion, we demonstrate that obtaining single cell transcriptomes from human frozen tissues can provide insight missed by either human bulk RNA-seq or animal models.