Versatile genomics platform for unbiased analysis of chromatin-associated RNAs and nascent transcripts

SUMMARY Aging and neurodegenerative diseases, such as Alzheimer’s disease and related dementias (AD/ADRD), are associated with alterations in nuclear structure, chromatin dysregulation, genome instability, and transcriptome changes. Chromatin associated RNAs (caRNAs), like long-noncoding RNAs (lncRNAs) and nascent RNAs, are intimately associated with the regulation and maintenance of genome organization and transcription. Restoration of normal nuclear and chromatin structure can increase longevity and mitigate disease markers, highlighting the potential of further research into mechanisms that regulate these processes to advance the treatment of AD/ADRD and aging related pathologies. caRNAs likely play important precursor roles in age- related changes to nuclear and chromatin structure, but no high-throughput methods exist to characterize caRNAs including lncRNAs, nascent mRNAs, and other nuclear RNAs. RNA immunoprecipitation and sequencing (RIP-seq) methods currently used to study target-associated RNAs require large inputs and are impractical for studying these nuclear RNAs, which are often cell type specific, restricted to specific nuclear compartments, and/or short-lived. Thus, new high-performance genomic technologies that can be leveraged to study caRNAs are necessary to enable the next generation of research for aging and age-related diseases, including identification of novel biomarkers and accelerated therapeutic development. Here, EpiCypher is partnering with Dr. Kami Ahmad (Fred Hutchinson Cancer Center) to develop Reverse Transcribe & Tagmentation (RT&Tag™), a new approach to identify caRNAs including nascent RNA transcripts at targeted features to accelerate aging and AD/ADRD research. The central innovation of this project is using an immunotethering-based approach for in situ targeted tagmentation of caRNAs. We are also developing novel spike-in controls for assay optimization and technical performance monitoring. Furthermore, these spike-ins will enable standardized data normalization and cross experiment comparisons, methods not always available or used in other RNA profiling methods. In Phase I equivalent studies, we successfully developed RT&Tag and applied it to identify histone PTM-associated polyadenylated (polyA) RNAs in multiple cell types. We demonstrated that RT&Tag is highly robust, requiring far less input material (500x fewer cells) and sequencing depth (6x fewer reads) than RIP-seq. In Phase II, we will design novel RNA-associated dNuc controls (RNA-dNucs) that are compatible with RT&Tag and apply them to perform rigorous optimization of RT&Tag for analysis of polyA caRNAs (Aim 1). Next, we will extend RT&Tag application by optimizing a workflow to capture nascent and non-polyA transcripts (Aim 2). Following, we will integrate data analysis pipelines for aligning RNA reads in a user-friendly bioinformatics portal and prepare for commercial launch of RT&Tag (Aim 3). Market availability of RT&Tag kits and services will transform the study of aging and AD/ADRD by providing a key tool to elucidate the link between caRNAs, epigenetic dysregulation, and aberrant gene expression.