Epigenomic Profiling and Single-Nucleus-RNA-Seq Reveal Cis-Regulatory Elements in Human Retina, Macula and RPE and Non-Coding Genetic Variation

Abstract

Cis-regulatory elements (CREs) orchestrate the dynamic and diverse transcriptional programs that assemble the human central nervous system (CNS) during development and maintain its function throughout life. Genetic variation within CREs plays a central role in phenotypic variation in complex traits including the risk of developing disease. However, the cellular complexity of the human brain has largely precluded the identification of functional regulatory variation within the human CNS. We took advantage of the retina, a well-characterized region of the CNS with reduced cellular heterogeneity, to establish a roadmap for characterizing regulatory variation in the human CNS. This comprehensive resource of tissue-specific regulatory elements, transcription factor binding, and gene expression programs in three regions of the human visual system (retina, macula, retinal pigment epithelium/choroid) reveals features of regulatory element evolution that shape tissue-specific gene expression programs and defines the regulatory elements with the potential to contribute to mendelian and complex disorders of human vision.

North Carolina macular dystrophy: phenotypic variability and computational analysis of disease-implicated non-coding variants

“…Although a number of non-coding genetic variants have been associated with NCMD, our understanding of the molecular pathology of this condition remains incomplete. The recent emergence of comprehensive functional genomic datasets from adult and fetal human tissues 21,22,27 has enabled in-depth analysis of non-coding changes like the ones implicated in this disorder. We found that all NCMD-causing variants fall within enhancer elements that appear to be active during development and to be linked to the retinal transcription factor PRDM13 .…”

“…As eyeIntegration does not contain data on macula, PRDM13 expression was also estimated from three macula RNA-seq samples included in the GEO dataset GSE137311. 27 In short, the raw reads were quantified using salmon 42 (according to the same protocol used to build the eyeIntegration dataset) and the value in TPM (transcripts per million) was calculated using tximport to merge reads to the gene level with the “lengthScaledTPM” option. The source code for this pipeline can be found at: www.githubdavemcg.com/EiaDBuild/.…”

“…24 Raw ATAC-seq and H3K27ac ChIP-seq reads from macular and retinal tissue were obtained from a publicly-available dataset (GEO accession: GSE137311). 27 The data were then processed using a consistent pipeline. The raw reads were trimmed for quality and adaptor content using the fastp tool with default quality control options.…”

“…Publicly-available chromatin accessibility (ATAC-seq and H3K27ac ChIP-seq) datasets from macula and retina were utilized. 27 The Hi-C data recommended and provided by Fulco et al 24 were also used; these consist of a Hi-C profile that was averaged over a number of cell types. With this input, ABC did not yield any predictions for the regions spanning the location of NCMD-implicated variants.…”

“…However, it remains possible that tissue- and context-specific data are required in some cases as the 3-dimensional conformation of the genome shows some plasticity during development. 26 Although epigenomic datasets from various eye tissues are becoming increasingly available, 27 there have been no systematic efforts to characterize enhancers that contribute to human vision.…”