Paper1: Single-cell genome-wide bisulfite sequencing for aeing epigenetic heterogeneity This paper report a single-cell bisulfite sequencing (scBS-seq) method that can be used to accurately measure DNA methylation at up to 48.4% of CpG sites.To minimize DNA lo from single cells, they developed a modification of post-bisulfite adaptor tagging.emerging evidence from immunofluorescence and locus-specific studies suggests that 5mC heterogeneity exists in ESCs.whether scBS-seq can reveal DNA methylation heterogeneity in single cells.12 MII, 12 2i ESC, 20 serum ESC and 7 negative control scBS-seq libraries was sequenced , and their bulk cell counterparts (pools of cells) on an Illumina HiSeq at relatively low sequencing depth .To investigate the reproducibility and accuracy of scBS-seq , bisulfite conversion efficiency was ≥97.7%, as aeed by analysis of non-CpG methylation .CpG sites in MIIs were overwhelmingly called methylated or unmethylated, which is consistent with a highly digitized output from single cells .As expected, global methylation of MIIs was highly homogeneous (33.1 ± 0.8%; ± s.d.) and 2i ESCs were hypomethylated compared to serum ESCs13.Yet both 2i ESCs and serum ESCs exhibited 5mC heterogeneity.Global 5mC levels measured in individual MIIs were slightly lower than in the bulk sample (39.0%), but merging all MII datasets resulted in 38.8% global methylation.To test the technical reproducibility of scBS-seq, the average pairwise concordance between individual CpGs acro single oocyte libraries was determined, which was 87.6% genome-wide (range, 85.3–88.9%) and 95.7% in unmethylated CpG islands (CGIs), a highly homogeneous genomic feature.CpG concordance in ESCs was lower (serum, 72.7%; 2i medium, 69.8%), which reflected the heterogeneity of these cells.At 2-kilobase (kb) resolution, and then observed high correlation between individual MIIs (average R = 0.92), and between individual MIIs and bulk.In addition, for each MII, obtained methylation information on an average of 61.5% of all CGIs (range, 46.3–82.7%).large-scale single-cell epigenetic analysis is achievable, and demonstrates that scBS-seq is a powerful approach to accurately measure 5mC acro genomes of single cells and to reveal 5mC heterogeneity in cell populations.Paper2:Maively Parallel Single-Cell RNA-Seq for Marker-Free Decomposition of Tiues into Cell Types Nowadays diection of tiues into mixtures of cellular subpopulations is currently challenging.In this paper they introduce an automated maively parallel single-cell RNA sequencing (RNA-seq) approach for analyzing in vivo transcriptional states in thousands of single cells.Combined with unsupervised claification algorithms, this facilitates ab initio cell-type characterization of splenic tiues.Cellular diversity is thereby approached through inference of variable and dynamic pathway activity rather than a fixed preprogrammed cell-type hierarchy.
Use this framework high cellular variance for a large number of genes has been observed, many of which are well known cell type–specific markers, suggesting that this attests for the high degree of heterogeneity within the splenic cell population and promoting the idea of claifying cells into subpopulations on the basis of covariation of such heterogeneous markers.This paper presented this framework for broad sampling of single-cell transcriptional states from tiues and demonstrated how it can be used to diect complex functions in a bottom-up fashion.MARS-seq can be readily applied to tiues and organs in normal and disease states to redefine their cell-type and cell-state compositions and link it to detailed genome-wide transcriptional profiling.Given the inherent stochasticity and heterogeneity of multicellular tiues, this approach can prove eential for understanding how in vivo biological function emerges from complex cell ensembles.Paper3: Maively parallel polymerase cloning and genome sequencing of single cells using nanoliter microwells
Genome sequencing of single cells has a variety of applications, including characterizing difficult-to-culture microorganisms and identifying somatic mutations in single cells from mammalian tiues.A major hurdle in this proce is the bias in amplifying the genetic material from a single cell, a procedure known as polymerase cloning.
the microwell displacement amplification system (MIDAS), a maively parallel polymerase cloning method in which single cells are randomly distributed into hundreds to thousands of nanoliter wells and their genetic material is simultaneously amplified for shotgun sequencing.MIDAS reduces amplification bias because polymerase cloning occurs in physically separated, nanoliter-scale reactors, facilitating the de novo aembly of near-complete microbial genomes from single Escherichia coli cells.In addition, MIDAS allowed us to detect single-copy number changes in primary human adult neurons at 1- to 2-Mb resolution.MIDAS has the potential to provide researchers with a powerful tool for many other applications, including high-coverage, end-to-end haplotyping of mammalian genomes or probing de novo CNV events at the single-cell level during the induction of pluripotency or stem cell differentiation.MIDAS allows for efficient high-throughput sequencing of a variety of organisms.This technology should help propel single-cell genomics, enhance our ability to identify diversity in multicellular organisms and lead to the discovery of a multitude of new organisms in various environments.paper4:Clonal evolution in breast cancer revealed by single nucleus genome sequencing Human breast cancers often display intratumour genomic heterogeneity.Recent data suggest that triple-negative breast cancers (TNBCs) may have increased clonal diversity and mutational evolution, but such inferences are difficult to make in bulk tiues.So this paper developed a whole-genome and exome single cell sequencing approach called nuc-seq that uses G2/M nuclei to achieve 91% mean coverage breadth.
The author applied this method to sequence single normal and tumour nuclei froman oestrogen-receptor-positive breast canceranda triple-negative ductal carcinoma.In parallel, they performed single nuclei copy number profiling.Our data show that aneuploid rearrangements occurred early in tumour evolution and remained highly stable as the tumour maes clonally expanded.In contrast, point mutations evolved radually, generating extensive clonal diversity. These findings have important implications for the diagnosis, therapeutic treatment and evolution of chemoresistance in breast cancer.And beyond cancer, these tools will have utility in microbiology, development, immunology and neuroscience and will lead to substantial improvements in their fundamental understanding of human diseases.
