RETrace: simultaneous retrospective lineage tracing and methylation profiling of single cells
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA561201 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10008000_1.fastq.gz | Fastqsanger.gz | |||
| SRR10008000_2.fastq.gz | Fastqsanger.gz | |||
| SRR10008100_1.fastq.gz | Fastqsanger.gz | |||
| SRR10008100_2.fastq.gz | Fastqsanger.gz | |||
| SRR10008001_1.fastq.gz | Fastqsanger.gz |
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Project description:Retrospective lineage tracing harnesses naturally occurring mutations in cells to elucidate single cell development. Common single-cell phylogenetic fate mapping methods have utilized highly mutable microsatellite loci found within the human genome. Such methods were limited by the introduction of in vitro noise through polymerase slippage inherent in DNA amplification, which we characterized to be approximately 10-100× higher than the in vivo replication mutation rate. Here, we present RETrace, a method for simultaneously capturing both microsatellites and methylation-informative cytosines to characterize both lineage and cell type, respectively, from the same single cell. An important unique feature of RETrace was the introduction of linear amplification of microsatellites in order to reduce in vitro amplification noise. We further coupled microsatellite capture with single-cell reduced representation bisulfite sequencing (scRRBS), to measure the CpG methylation status on the same cell for cell type inference. When compared to existing retrospective lineage tracing methods, RETrace achieved higher accuracy (88% triplet accuracy from an ex vivo HCT116 tree) at a higher cell division resolution (lowering the required number of cell division difference between single cells by approximately 100 divisions). Simultaneously, RETrace demonstrated the ability to capture on average 150,000 unique CpGs per single cell in order to accurately determine cell type. We further formulated additional developments that would allow high-resolution mapping on microsatellite-stable cells or tissues with RETrace. Overall, we present RETrace as a foundation for multi-omics lineage mapping and cell typing of single cells.
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