Arabidopsis root single-cell ATAC-seq using combinatorial indexing

Understanding how the epigenome control gene expression is a key question in biology. Recent advances in single-cell ATAC-seq technologies led to the discovery of cell-specific chromatin landscape that define their transcription programs. Plant tissues also contain multiple cell-types with specialized functions. However, the high equipment and reagent costs of commercial single-cell systems limit their applications. Here, we develop a low-cost single-cell ATAC-seq method based on combinatorial index and dual PCR barcoding without the need of any specialize equipment. To demonstrate the usefulness of this method, we generate sci-ATAC-seq profiles for 13,576 Arabidopsis root nuclei with an average of 12,784 unique Tn5 integrations per cell and 85% of Tn5 insertions localizing to discrete ACRs. Benchmark with scATAC-seq data generated by commercial platforms revealed that our method is capable of unbiased identification of cell type-specific chromatin accessibility with improved throughput, yield and efficiency. We also generate a chromatin accessibility and gene expression unified co-embedding by integrating single-cell ATAC-seq and RNA-seq data sets, and identified 24 cell clusters with unique transcription, chromatin and cis-regulatory element signatures. We anticipate that this robust method will be a valuable tool to study cell-specific epigenome as well as delineate developmental changes during plant growth and development.