Atlas-scale Single-cell DNA Methylation Profiling with sciMETv3

Abstract

Single-cell methods to assess DNA methylation have not yet achieved the same level of cell throughput compared to other modalities. Here, we describe sciMETv3, a combinatorial indexing-based technique that builds on our prior technology, sciMETv2. SciMETv3 achieves nearly a 100-fold improvement in cell throughput by increasing the index space while simultaneously reducing hands-on time and total costs per experiment. To reduce the sequencing burden of the assay, we demonstrate compatibility of sciMETv3 with capture techniques that enrich for regulatory regions, as well as the ability to leverage enzymatic conversion which can yield higher library diversity. We showcase the throughput of sciMETv3 by producing a >140k cell library from human middle frontal gyrus split across four multiplexed individuals using both Illumina and Ultima sequencing instrumentation. This library was prepared over two days by one individual and required no expensive equipment (e.g. a flow sorter, as required by sciMETv2). The same experiment produced an estimated 650k additional cells that were not sequenced, representing the power of sciMETv3 to meet the throughput needs of the most demanding atlas-scale projects. Finally, we demonstrate the compatibility of sciMETv3 with multimodal assays by introducing sciMET+ATAC, which will enable high-throughput exploration of the interplay between two layers of epigenetic regulation within the same cell, as well as the ability to directly integrate single-cell methylation datasets with existing single-cell ATAC-seq.