HyDrop: droplet-based scATAC-seq and scRNA-seq using dissolvable hydrogel beads

biorxiv(2021)

引用 2|浏览21
暂无评分
摘要
Single-cell RNA-seq and single-cell ATAC-seq technologies are being used extensively to create cell type atlases for a wide range of organisms, tissues, and disease processes. To increase the scale of these atlases, lower the cost, and allow for more specialized multi-ome assays, custom droplet microfluidics may provide complementary solutions to commercial setups. We developed HyDrop, a flexible and generic droplet microfluidic platform encompassing three protocols. The first protocol involves creating dissolvable hydrogel beads with custom oligos that can be released in the droplets. In the second protocol, we demonstrate the use of these beads for HyDrop-ATAC, a low-cost non-commercial scATAC-seq protocol in droplets. After validating HyDrop-ATAC, we applied it to flash-frozen mouse cortex and generated 8,502 high-quality single-cell chromatin accessibility profiles in a single run. In the third protocol, we adapt both the reaction chemistry and the capture sequence of the barcoded hydrogel bead to capture mRNA, and demonstrate a significant improvement in throughput and sensitivity compared to previous open-source droplet-based scRNA-seq assays (Drop-seq and inDrop). Similarly, we applied HyDrop-RNA to flash-frozen mouse cortex and generated 9,508 single-cell transcriptomes closely matching reference single-cell gene expression data. Finally, we leveraged HyDrop-RNA’s high capture rate to analyse a small population of FAC-sorted neurons from the Drosophila brain, confirming the protocol’s applicability to low-input samples and small cells. HyDrop is currently capable of generating single-cell data in high throughput and at a reduced cost compared to commercial methods, and we envision that HyDrop can be further developed to be compatible with novel (multi-) omics protocols. ### Competing Interest Statement The authors have declared no competing interest.
更多
查看译文
关键词
dissolvable hydrogel beads,droplet-based,scatac-seq,scrna-seq
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要