Lena Christiansen

Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing

Chromatin state and the single cell Identifying the chromatin state of any single cell, which may or may not have a different function or represent different stages relative to others collected within any single culture, experiment, or tissue, has been challenging. Cusanovitch et al. skirted previously identified technological limitations to identify regions of accessible chromatin at single-cell resolution. Combinatorial cellular indexing, a strategy for multiplex barcoding of thousands of single cells per experiment, was successfully used to investigate the genome-wide chromatin accessibility landscape in each of over 15,000 single cells. Science, this issue p. 910 Combinatorial indexing can identify chromatin states at single-cell resolution. Technical advances have enabled the collection of genome and transcriptome data sets with single-cell resolution. However, single-cell characterization of the epigenome has remained challenging. Furthermore, because cells must be physically separated before biochemical processing, conventional single-cell preparatory methods scale linearly. We applied combinatorial cellular indexing to measure chromatin accessibility in thousands of single cells per assay, circumventing the need for compartmentalization of individual cells. We report chromatin accessibility profiles from more than 15,000 single cells and use these data to cluster cells on the basis of chromatin accessibility landscapes. We identify modules of coordinately regulated chromatin accessibility at the level of single cells both between and within cell types, with a scalable method that may accelerate progress toward a human cell atlas.

Sequencing thousands of single-cell genomes with combinatorial indexing

Single-cell genome sequencing has proven valuable for the detection of somatic variation, particularly in the context of tumor evolution. Current technologies suffer from high library construction costs, which restrict the number of cells that can be assessed and thus impose limitations on the ability to measure heterogeneity within a tissue. Here, we present single-cell combinatorial indexed sequencing (SCI-seq) as a means of simultaneously generating thousands of low-pass single-cell libraries for detection of somatic copy-number variants. We constructed libraries for 16,698 single cells from a combination of cultured cell lines, primate frontal cortex tissue and two human adenocarcinomas, and obtained a detailed assessment of subclonal variation within a pancreatic tumor.

The cis -regulatory dynamics of embryonic development at single-cell resolution

Understanding how gene regulatory networks control the progressive restriction of cell fates is a long-standing challenge. Recent advances in measuring gene expression in single cells are providing new insights into lineage commitment. However, the regulatory events underlying these changes remain unclear. Here we investigate the dynamics of chromatin regulatory landscapes during embryogenesis at single-cell resolution. Using single-cell combinatorial indexing assay for transposase accessible chromatin with sequencing (sci-ATAC-seq), we profiled chromatin accessibility in over 20,000 single nuclei from fixed Drosophila melanogaster embryos spanning three landmark embryonic stages: 2–4 h after egg laying (predominantly stage 5 blastoderm nuclei), when each embryo comprises around 6,000 multipotent cells; 6–8 h after egg laying (predominantly stage 10–11), to capture a midpoint in embryonic development when major lineages in the mesoderm and ectoderm are specified; and 10–12 h after egg laying (predominantly stage 13), when each of the embryo’s more than 20,000 cells are undergoing terminal differentiation. Our results show that there is spatial heterogeneity in the accessibility of the regulatory genome before gastrulation, a feature that aligns with future cell fate, and that nuclei can be temporally ordered along developmental trajectories. During mid-embryogenesis, tissue granularity emerges such that individual cell types can be inferred by their chromatin accessibility while maintaining a signature of their germ layer of origin. Analysis of the data reveals overlapping usage of regulatory elements between cells of the endoderm and non-myogenic mesoderm, suggesting a common developmental program that is reminiscent of the mesendoderm lineage in other species. We identify 30,075 distal regulatory elements that exhibit tissue-specific accessibility. We validated the germ-layer specificity of a subset of these predicted enhancers in transgenic embryos, achieving an accuracy of 90%. Overall, our results demonstrate the power of shotgun single-cell profiling of embryos to resolve dynamic changes in the chromatin landscape during development, and to uncover the cis-regulatory programs of metazoan germ layers and cell types.

Haplotype phasing of whole human genomes using bead-based barcode partitioning in a single tube

Haplotype-resolved genome sequencing promises to unlock a wealth of information in population and medical genetics. However, for the vast majority of genomes sequenced to date, haplotypes have not been determined because of cumbersome haplotyping workflows that require fractions of the genome to be sequenced in a large number of compartments. Here we demonstrate barcode partitioning of long DNA molecules in a single compartment using “on-bead” barcoded tagmentation. The key to the method that we call “contiguity preserving transposition” sequencing on beads (CPTv2-seq) is transposon-mediated transfer of homogenous populations of barcodes from beads to individual long DNA molecules that get fragmented at the same time (tagmentation). These are then processed to sequencing libraries wherein all sequencing reads originating from each long DNA molecule share a common barcode. Single-tube, bulk processing of long DNA molecules with ∼150,000 different barcoded bead types provides a barcode-linked read structure that reveals long-range molecular contiguity. This technology provides a simple, rapid, plate-scalable and automatable route to accurate, haplotype-resolved sequencing, and phasing of structural variants of the genome.

C ontiguity- P reserving T ransposition Seq uencing (CPT-Seq) for Genome-Wide Haplotyping, Assembly, and Single-Cell ATAC-Seq

Most genomes to date have been sequenced without taking into account the diploid nature of the genome. However, the distribution of variants on each individual chromosome can (1) significantly impact gene regulation and protein function, (2) have important implications for analyses of population history and medical genetics, and (3) be of great value for accurate interpretation of medically relevant genetic variation. Here, we describe a comprehensive and detailed protocol for an ultra fast (<3 h library preparation), cost-effective, and scalable haplotyping method, named Contiguity Preserving Transposition sequencing or CPT-seq (Amini et al., Nat Genet 46(12):1343-1349, 2014). CPT-seq accurately phases >95 % of the whole human genome in Mb-scale phasing blocks. Additionally, the same workflow can be used to aid de novo assembly (Adey et al., Genome Res 24(12):2041-2049, 2014), detect structural variants, and perform single cell ATAC-seq analysis (Cusanovich et al., Science 348(6237):910-914, 2015).

Joint profiling of chromatin accessibility and gene expression in thousands of single cells

Single-cell chromatin and RNA analysis Single-cell analyses have begun to provide insight into the differences among and within the individual cells that make up a tissue or organism. However, technological barriers owing to the small amount of material present in each single cell have prevented parallel analyses. Cao et al. present sci-CAR, a pooled barcode method that jointly analyzes both the RNA transcripts and chromatin profiles of single cells. By applying sci-CAR to lung adenocarcinoma cells and mouse kidney tissue, the authors demonstrate precision in assessing expression and genome accessibility at a genome-wide scale. The approach provides an improvement over bulk analysis, which can be confounded by differing cellular subgroups. Science, this issue p. 1380 A technique termed sci-CAR can assess both chromatin accessibility and RNA transcription at the single-cell level. Although we can increasingly measure transcription, chromatin, methylation, and other aspects of molecular biology at single-cell resolution, most assays survey only one aspect of cellular biology. Here we describe sci-CAR, a combinatorial indexing–based coassay that jointly profiles chromatin accessibility and mRNA (CAR) in each of thousands of single cells. As a proof of concept, we apply sci-CAR to 4825 cells, including a time series of dexamethasone treatment, as well as to 11,296 cells from the adult mouse kidney. With the resulting data, we compare the pseudotemporal dynamics of chromatin accessibility and gene expression, reconstruct the chromatin accessibility profiles of cell types defined by RNA profiles, and link cis-regulatory sites to their target genes on the basis of the covariance of chromatin accessibility and transcription across large numbers of single cells.

Construction of thousands of single cell genome sequencing libraries using combinatorial indexing

Single cell genome sequencing has proven to be a valuable tool for the detection of somatic variation, particularly in the context of tumor evolution and neuronal heterogeneity. Current technologies suffer from high per-cell library construction costs which restrict the number of cells that can be assessed, thus imposing limitations on the ability to quantitatively measure genomic heterogeneity within a tissue. Here, we present Single cell Combinatorial Indexed Sequencing (SCI-seq) as a means of simultaneously generating thousands of low-pass single cell libraries for the purpose of somatic copy number variant detection. In total, we constructed libraries for 16,698 single cells from a combination of cultured cell lines, frontal cortex tissue from Macaca mulatta, and two human adenocarcinomas. This novel technology provides the opportunity for low-cost, deep characterization of somatic copy number variation in single cells, providing a foundational knowledge across both healthy and diseased tissues.