Project description:Advances in single-cell genomics enable commensurate improvements in methods for uncovering lineage relations among individual cells. Current sequencing based methods for cell lineage analysis depend on low resolution bulk analysis or rely on extensive single cell sequencing which is not scalable and could be biased by functional dependencies. Here we show an integrated biochemical-computational platform for generic single-cell lineage analysis that is retrospective, cost-effective and scalable. It consists of a biochemical-computational pipeline that inputs individual cells, produces targeted single-cell sequencing data and uses it to generate a lineage tree of the input cells. We validated the platform by applying it to cells sampled from an ex vivo grown tree and analyzed its feasibility landscape by computer simulations. We conclude that the platform may serve as a generic tool for lineage analysis and thus pave the way towards large-scale human cell lineage discovery.
Project description:We developed a new single cell sequencing method to simultaneously sequence methylome and transcriptome for mouse DRG neurons Integrative analysis of transcription and methylation at single cell level
Project description:Single cell genome, DNA methylome, and transcriptome sequencing has been achieved separately. However, to analyze the regulation of RNA expression by genetic and epigenetic factors within an individual cell, it is necessary to analyze these omics simultaneously from the same single cell. Here we developed a single cell triple omics sequencing technique- scTrio-seq, to analyze the genome, DNA methylome, and transcriptome concurrently of a mammalian cell. 6 single human HepG2 cell line cells were sequenced using the newly developed scTrio-seq, other 2 HepG2 cells were sequenced using scRNA-seq and other 2 HepG2 cells were sequenced using scRRBS as technique control. 6 single mouse embryonic stem cells (mESCs) were sequenced using the newly developted scTrio-seq. Meanwhile, two scRNA-seq and two scRRBS were also completed using two mESCs separately. 26 single cells from hepatocellular carcinoma were sequenced using scTrio-seq to analyze the regulation relations between three omics of cancer cells.
Project description:We combined the Single-probe single cell MS(SCMS) experimental technique with a bioinformatics software package, SinCHet-MS (Single Cell Heterogeneity for Mass Spectrometry), to characterize changes of tumor heterogeneity, quantify cell subpopulations, and prioritize the metabolite biomarkers of each subpopulation.
