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Dharmat, R.

Publications and source records attributed to Dharmat, R..

2 recordsLinked to original sources

Epigenetic adaptation prolongs photoreceptor survival during retinal degeneration

Neural degenerative diseases often display a progressive loss of cells as a stretched exponential distribution. The mechanisms underlying the survival of a subset of genetically identical cells in a population beyond what is expected by chance alone remains unknown. To gain mechanistic insights underlying prolonged cellular survival, we used Spata7 mutant mice as a model and performed single-cell transcriptomic profiling of retinal tissue along the time course of photoreceptor degeneration. Intriguingly, rod cells that survive beyond the initial rapid cell apoptosis phase progressively acquire a distinct transcriptome profile. In these rod cells, expression of photoreceptor-specific phototransduction pathway genes is downregulated while expression of other retinal cell type-specific marker genes is upregulated. These transcriptomic changes are achieved by modulation of the epigenome and changes of the chromatin state at these loci, as indicated by immunofluorescence staining and single-cell ATAC-seq. Consistent with this model, when induction of the repressive epigenetic state is blocked by in vivo histone deacetylase inhibition, all photoreceptors in the mutant retina undergo rapid degeneration, strongly curtailing the stretched exponential distribution. Our study reveals an intrinsic mechanism by which neural cells progressively adapt to genetic stress to achieve prolonged survival through epigenomic regulation and chromatin state modulation.

neuroscience↗

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

Gene expression profiling is an effective way to provide insights into cell function. However, for heterogeneous tissues, bulk RNA-Seq can only provide the average gene expression profile for all cells from the tissue, making the interpretation of the sequencing result challenging. Single-cell RNA-seq, on the other hand, generates transcriptomic profiles of individual cell and cell types, making it a powerful method to decode the heterogeneity in complex tissues. The retina is a heterogeneous tissue composed of multiple cell types with distinct functions. Here we report the first single-nuclei RNA-seq transcriptomic study on human neural retinal tissue to identify transcriptome profile for individual cell types. Six retina samples from three healthy donors were profiled and RNA-seq data with high quality was obtained for 4730 single nuclei. All seven major cell types were observed from the dataset and signature genes for each cell type were identified by differential gene express analysis. The gene expression of the macular and peripheral retina was compared at the cell type level, showing significant improvement from previous bulk RNA-seq studies. Furthermore, our dataset showed improved power in prioritizing genes associated with human retinal diseases compared to both mouse single-cell RNA-seq and human bulk RNA-seq results. In conclusion, we demonstrated that feasibility of obtaining single cell transcriptome from human frozen tissues to provide additional insights that is missed by either the human bulk RNA-seq or the animal models.

genomics↗