Analysis Of UMI-ATAC-seq Data And Exploration Of Plant Single Cell ATAC-seq Technique

Transcriptional regulation has been the focus of research in the life sciences.ATACseq is widely used to identify open chromatin regions and transcription factor binding sites because of its high efficiency and low technology noise.Both applications require precise quantification of the Tn5 insertion events.However,the necessity of PCR amplification during library construction makes it impossible to distinguish whether the identical sequenced fragments were generated by PCR amplification or by coincidentally different Tn5 insertion events,which could introduce bias into subsequent data analysis.However,bulk ATAC-seq dilutes cell type-specific information,measures only the average chromatin accessibility of cell populations and is unable to measure the degree of chromatin accessibility in different cell types.The commercial single-cell ATAC-seq platform makes it possible to study transcriptional regulatory networks at the single-cell level,but factors such as its high costs and mammalian reagents limit its application in the plant field.In order to investigate plant growth and development in further detail,there is an urgent demand for a single-cell ATAC-seq platform in the plant field.Here,we report a UMI-ATAC-seq technique by incorporating UMIs with standard Tru Seq sequencing adapters into standard ATAC-seq procedures.The results show that the incorporation of the UMI can also yield high quality sequencing data.Most of the saved fragments are from highly open regions of the genome,some of which are from regions with copy number variations or errors in genome assembly,such as r DNA and telomeres.In addition,the saved fragments are significantly assisted in identifying footprint.At the same threshold,the UMI-based deduplication dataset can identify up to 50% more transcription factor footprints compared to conventional coordinate deduplication.Most importantly,the footprint scores of the UMI dataset were generally improved,with the IGV showing a clearer pattern of concavity in the footprints identified by the UMI dataset and broad overlap with known transcription factor binding sites.In addition,based on the UMIATAC-seq protocol,we have initially established a high-throughput sequencing platform for single-cell ATAC-seq in plants using combinatorial indexing and flow cytometry sorting and named it mps-ATAC-seq.We obtained 6,528 cells using rice young panicles with different genotypes.It was found that the inserted fragment size had a nucleosome distribution pattern,and the TSS enrichment score was 14.The FRi P maintained at 0.6,but there was some contamination between cells.After filtering,16 clusters were identified,and preliminary annotation of the four possible major cell types in rice young panicles.The mps-ATAC-seq was shown to be theoretically feasible,but some further experimental condition modification is required to obtain high quality data.This study demonstrates that the optimized chromatin accessibility sequencing UMIATAC-seq has improved both chromatin accessibility quantification and transcription factor footprinting,and also preliminarily establishes the mps-ATAC-seq technology platform and explores its feasibility.The UMI-ATAC-seq and mps-ATAC-seq platforms in this study are significant for constructing transcriptional regulatory networks and characterizing the growth and development of plants.