Atlas-scale single-cell DNA methylation profiling with sciMETv3.

Single-cell methods to assess DNA methylation have not achieved the same level of cell throughput per experiment compared to other modalities, with large-scale datasets requiring extensive automation, time, and other resources. Here, we describe sciMETv3, a combinatorial indexing-based technique that enables atlas-scale libraries to be produced in a single experiment. To reduce the sequencing burden, we demonstrate the compatibility of sciMETv3 with capture techniques to enrich regulatory regions, as well as the ability to leverage enzymatic conversion, which can yield higher library diversity.

Single-cell DNA methylation analysis tool Amethyst reveals distinct noncanonical methylation patterns in human glial cells.

Single-cell sequencing technologies have revolutionized biomedical research by enabling deconvolution of cell type-specific properties in highly heterogeneous tissue. While robust tools have been developed to handle bioinformatic challenges posed by single-cell RNA and ATAC data, options for emergent modalities such as methylation are much more limited, impeding the utility of results. Here we present Amethyst, a comprehensive R package for atlas-scale single-cell methylation sequencing data analysis.

sciMET-cap: high-throughput single-cell methylation analysis with a reduced sequencing burden.

DNA methylation is a key component of the mammalian epigenome, playing a regulatory role in development, disease, and other processes. Robust, high-throughput single-cell DNA methylation assays are now possible (sciMET); however, the genome-wide nature of DNA methylation results in a high sequencing burden per cell. Here, we leverage target enrichment with sciMET to capture sufficient information per cell for cell type assignment using substantially fewer sequence reads (sciMET-cap).

sciMET-cap: High-throughput single-cell methylation analysis with a reduced sequencing burden.

DNA methylation is a key component of the mammalian epigenome, playing a regulatory role in development, disease, and other processes. Robust, high-throughput single-cell DNA methylation assays are now possible (sciMET); however, the genome-wide nature of DNA methylation results in a high sequencing burden per cell. Here, we leverage target enrichment with sciMET to capture sufficient information per cell for cell type assignment using substantially fewer sequence reads (sciMET-cap).

GLUT1 is associated with sphingolipid-organized, cholesterol-independent domains in L929 mouse fibroblast cells.

Glucose is a preferred metabolite in most mammalian cells, and proper regulation of uptake is critical for organism homeostasis. The glucose transporter 1 (GLUT1) is responsible for glucose uptake in a wide variety of cells and appears to be regulated in a tissue specific manner. Therefore, a better understanding of GLUT1 regulation within its various cellular environments is essential for developing therapeutic strategies to treat disorders associated with glucose homeostasis.

Mitochondria, ER, and nuclear membrane defects reveal early mechanisms for upper motor neuron vulnerability with respect to TDP-43 pathology.

Insoluble aggregates containing TDP-43 are widely observed in the diseased brain, and defined as "TDP-43 pathology" in a spectrum of neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS), Alzheimer's disease and ALS with frontotemporal dementia. Here we report that Betz cells of patients with TDP-43 pathology display a distinct set of intracellular defects especially at the site of nuclear membrane, mitochondria and endoplasmic reticulum (ER). Numerous TDP-43 mouse models have been generated to discern the cellular and molecular basis of the disease, but mechanisms of neuronal vulnerability remain unknown.