iSCORE-PD: an isogenic stem cell collection to research Parkinson's Disease.

Parkinson's disease (PD) is a neurodegenerative disorder caused by complex genetic and environmental factors. Genome-edited human pluripotent stem cells (hPSCs) offer the uniique potential to advance our understanding of PD etiology by providing disease-relevant cell-types carrying patient mutations along with isogenic control cells. To facilitate this experimental approach, we generated a collection of 55 cell lines genetically engineered to harbor mutations in genes associated with monogenic PD (SNCA A53T, SNCA A30P, PRKN Ex3del, PINK1 Q129X, DJ1/PARK7 Ex1-5del, LRRK2 G2019S, ATP13A2 FS, FBXO7 R498X/FS, DNAJC6 c.801 A>G+FS, SYNJ1 R258Q/FS, VPS13C A444P, VPS13C W395C, GBA1 IVS2+1). All mutations were generated in a fully characterized and sequenced female human embryonic stem cell (hESC) line (WIBR3; NIH approval number NIHhESC-10-0079) using CRISPR/Cas9 or prime editing-based approaches. We implemented rigorous quality controls, including high density genotyping to detect structural variants and confirm the genomic integrity of each cell line. This systematic approach ensures the high quality of our stem cell collection, highlights differences between conventional CRISPR/Cas9 and prime editing and provides a roadmap for how to generate gene-edited hPSCs collections at scale in an academic setting. We expect that our isogenic stem cell collection will become an accessible platform for the study of PD, which can be used by investigators to understand the molecular pathophysiology of PD in a human cellular setting.

High-throughput scNMT protocol for multiomics profiling of single cells from mouse brain and pancreatic organoids.

Single-cell nucleosome, methylome, and transcriptome (scNMT) sequencing is a recently developed method that allows multiomics profiling of single cells. In this scNMT protocol, we describe profiling of cells from mouse brain and pancreatic organoids, using liquid handling platforms to increase throughput from 96-well to 384-well plate format. Our approach miniaturizes reaction volumes and incorporates the latest Smart-seq3 protocol to obtain higher numbers of detected genes and genomic DNA (gDNA) CpGs per cell. We outline normalization steps to optimally distribute per-cell sequencing depth. For complete details on the use and execution of this protocol, please refer to Clark (2019), Clark et al. (2018), and Clark et al., 2018, Hagemann-Jensen et al., 2020a, Hagemann-Jensen et al., 2020b.