High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors.

Single-cell nanopore sequencing of full-length mRNAs transforms single-cell multi-omics studies. However, challenges include high sequencing errors and dependence on short-reads and/or barcode whitelists. To address these, we develop scNanoGPS to calculate same-cell genotypes (mutations) and phenotypes (gene/isoform expressions) without short-read nor whitelist guidance. We apply scNanoGPS onto 23,587 long-read transcriptomes from 4 tumors and 2 cell-lines. Standalone, scNanoGPS deconvolutes error-prone long-reads into single-cells and single-molecules, and simultaneously accesses both phenotypes and genotypes of individual cells. Our analyses reveal that tumor and stroma/immune cells express distinct combination of isoforms (DCIs). In a kidney tumor, we identify 924 DCI genes involved in cell-type-specific functions such as PDE10A in tumor cells and CCL3 in lymphocytes. Transcriptome-wide mutation analyses identify many cell-type-specific mutations including VEGFA mutations in tumor cells and HLA-A mutations in immune cells, highlighting the critical roles of different mutant populations in tumors. Together, scNanoGPS facilitates applications of single-cell long-read sequencing technologies.

Anaplastic transformation in thyroid cancer revealed by single-cell transcriptomics.

The deadliest anaplastic thyroid cancer (ATC) often transforms from indolent differentiated thyroid cancer (DTC); however, the complex intratumor transformation process is poorly understood. We investigated an anaplastic transformation model by dissecting both cell lineage and cell fate transitions using single-cell transcriptomic and genetic alteration data from patients with different subtypes of thyroid cancer. The resulting spectrum of ATC transformation included stress-responsive DTC cells, inflammatory ATC cells (iATCs), and mitotic-defective ATC cells and extended all the way to mesenchymal ATC cells (mATCs). Furthermore, our analysis identified 2 important milestones: (a) a diploid stage, in which iATC cells were diploids with inflammatory phenotypes and (b) an aneuploid stage, in which mATCs gained aneuploid genomes and mesenchymal phenotypes, producing excessive amounts of collagen and collagen-interacting receptors. In parallel, cancer-associated fibroblasts showed strong interactions among mesenchymal cell types, macrophages shifted from M1 to M2 states, and T cells reprogrammed from cytotoxic to exhausted states, highlighting new therapeutic opportunities for the treatment of ATC.

Delineating genotypes and phenotypes of individual cells from long-read single cell transcriptomes.

Single-cell nanopore sequencing of full-length mRNAs (scNanoRNAseq) is transforming singlecell multi-omics studies. However, challenges include computational complexity and dependence on short-read curation. To address this, we developed a comprehensive toolkit, scNanoGPS to calculate same-cell genotypes-phenotypes without short-read guidance. We applied scNanoGPS onto 23,587 long-read transcriptomes from 4 tumors and 2 cell lines. Standalone, scNanoGPS accurately deconvoluted error-prone long-reads into single-cells and single-molecules. Further, scNanoGPS simultaneously accessed both phenotypes (expressions/isoforms) and genotypes (mutations) of individual cells. Our analyses revealed that tumor and stroma/immune cells often expressed significantly distinct combinations of isoforms (DCIs). In a kidney tumor, we identified 924 genes with DCIs involved in cell-type-specific functions such as PDE10A in tumor cells and CCL3 in lymphocytes. Moreover, transcriptome-wide mutation analyses identified many cell-type-specific mutations including VEGFA mutations in tumor cells and HLA-A mutations in immune cells, highlighting critical roles of different populations in tumors. Together, scNanoGPS facilitates applications of single-cell long-read sequencing.

Single-cell analysis of human glioma and immune cells identifies S100A4 as an immunotherapy target.

A major rate-limiting step in developing more effective immunotherapies for GBM is our inadequate understanding of the cellular complexity and the molecular heterogeneity of immune infiltrates in gliomas. Here, we report an integrated analysis of 201,986 human glioma, immune, and other stromal cells at the single cell level. In doing so, we discover extensive spatial and molecular heterogeneity in immune infiltrates. We identify molecular signatures for nine distinct myeloid cell subtypes, of which five are independent prognostic indicators of glioma patient survival. Furthermore, we identify S100A4 as a regulator of immune suppressive T and myeloid cells in GBM and demonstrate that deleting S100a4 in non-cancer cells is sufficient to reprogram the immune landscape and significantly improve survival. This study provides insights into spatial, molecular, and functional heterogeneity of glioma and glioma-associated immune cells and demonstrates the utility of this dataset for discovering therapeutic targets for this poorly immunogenic cancer.

Wnt/ß-catenin-mediated p53 suppression is indispensable for osteogenesis of mesenchymal progenitor cells.

The developmental origins of mesenchymal progenitor cells (MPCs) and molecular machineries regulating their fate and differentiation are far from defined owing to their complexity. Osteoblasts and adipocytes are descended from common MPCs. Their fates are collectively determined by an orchestra of pathways in response to physiological and external cues. The canonical Wnt pathway signals MPCs to commit to osteogenic differentiation at the expense of adipogenic fate. In contrast to ß-catenin, p53's anti-osteogenic function is much less understood. Both activities are thought to be achieved through targeting Runx2 and/or Osterix (Osx, Sp7) transcription. Precisely, how Osx activity is dictated by ß-catenin or p53 is not clarified and represents a knowledge gap that, until now, has largely been taken for granted. Using conditional lineage-tracing mice, we demonstrated that chondrocytes gave rise to a sizable fraction of MPCs, which served as progenitors of chondrocyte-derived osteoblasts (Chon-ob). Wnt/ß-catenin activity was only required at the stage of chondrocyte-derived mesenchymal progenitor (C-MPC) to Chon-ob differentiation. ß-catenin- C-MPCs lost osteogenic ability and favored adipogenesis. Mechanistically, we discovered that p53 activity was elevated in ß-catenin- MPCs including ß-catenin- C-MPCs and deleting p53 from the ß-catenin- MPCs fully restored osteogenesis. While high levels of p53 were present in the nuclei of ß-catenin- MPCs, Osx was confined to the cytoplasm, implying a mechanism that did not involve direct p53-Osx interaction. Furthermore, we found that p53's anti-osteogenic activity was dependent on its DNA-binding ability. Our findings identify chondrocytes as an additional source for MPCs and indicate that Wnt/ß-catenin discretely regulates chondrocyte to C-MPC and the subsequent C-MPC to osteoblast developments. Most of all we unveil a previously unrecognized functional link between ß-catenin and p53, placing p53's negative role in the context of Wnt/ß-catenin signaling-induced MPC osteogenic differentiation.

MEDALT: single-cell copy number lineage tracing enabling gene discovery.

We present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles, and a statistical routine named lineage speciation analysis (LSA), whichty facilitates discovery of fitness-associated alterations and genes from SCCN lineage trees. MEDALT appears more accurate than phylogenetics approaches in reconstructing copy number lineage. From data from 20 triple-negative breast cancer patients, our approaches effectively prioritize genes that are essential for breast cancer cell fitness and predict patient survival, including those implicating convergent evolution.The source code of our study is available at https://github.com/KChen-lab/MEDALT .

Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes.

Single-cell transcriptomic analysis is widely used to study human tumors. However, it remains challenging to distinguish normal cell types in the tumor microenvironment from malignant cells and to resolve clonal substructure within the tumor. To address these challenges, we developed an integrative Bayesian segmentation approach called copy number karyotyping of aneuploid tumors (CopyKAT) to estimate genomic copy number profiles at an average genomic resolution of 5 Mb from read depth in high-throughput single-cell RNA sequencing (scRNA-seq) data. We applied CopyKAT to analyze 46,501 single cells from 21 tumors, including triple-negative breast cancer, pancreatic ductal adenocarcinoma, anaplastic thyroid cancer, invasive ductal carcinoma and glioblastoma, to accurately (98%) distinguish cancer cells from normal cell types. In three breast tumors, CopyKAT resolved clonal subpopulations that differed in the expression of cancer genes, such as KRAS, and signatures, including epithelial-to-mesenchymal transition, DNA repair, apoptosis and hypoxia. These data show that CopyKAT can aid in the analysis of scRNA-seq data in a variety of solid human tumors.

SCOPIT: sample size calculations for single-cell sequencing experiments.

BACKGROUND: In single cell DNA and RNA sequencing experiments, the number of cells to sequence must be decided before running an experiment, and afterwards, it is necessary to decide whether sufficient cells were sampled. These questions can be addressed by calculating the probability of sampling at least a defined number of cells from each subpopulation (cell type or cancer clone). RESULTS: We developed an interactive web application called SCOPIT (Single-Cell One-sided Probability Interactive Tool), which calculates the required probabilities using a multinomial distribution (www.navinlab.com/SCOPIT). In addition, we created an R package called pmultinom for scripting these calculations. CONCLUSIONS: Our tool for fast multinomial calculations provide a simple and intuitive procedure for prospectively planning single-cell experiments or retrospectively evaluating if sufficient numbers of cells have been sequenced. The web application can be accessed at navinlab.com/SCOPIT.

MYB-activated models for testing therapeutic agents in adenoid cystic carcinoma.

OBJECTIVE: There are no effective systemic therapies for adenoid cystic cancer (ACC) and lack of tumor lines and mouse models have hindered drug development.We aim to develop MYB-activated models for testing new therapeutic agents. MATERIALS AND METHODS: We studied new ACC patient-derived xenograft (PDX) models and generated a matched cell line from one patient. In addition, we generated a genetically-engineered MYB-NFIB mouse model (GEMM) that was crossed with Ink4a+/-/Arf+/- mice to study tumor spectrum and obtain tumor lines. Using human and murine ACC-like tumor lines, we analyzed MYB expression by RNA-Seq and immunoblot and tested efficacy of new MYB inhibitors. RESULTS: We detected MYB-NFIB transcripts in both UFH1 and UFH2 PDX and observed tumor inhibition by MYB depletion using shRNA in vivo. We observed rapid loss of MYB expression when we cultured UFH1 in vitro, but were able to generate a UFH2 tumor cell line that retained MYB expression for 6 months. RNA-Seq expression detected an ACC-like mRNA signature in PDX samples and we confirmed an identical KMT2A/MLL variant in UFH2 PDX, matched cell line, and primary biopsy. Although the predominant phenotype of the MYB-NFIB GEMM was B-cell leukemia, we also generated a MYB-activated ACC-like mammary tumor cell line. We observed tumor inhibition using a novel MYB peptidomimetic in both human and murine tumor models. CONCLUSIONS: We generated and studied new murine and human MYB-activated tumor samples and detected growth inhibition with MYB peptidomimetics. These data provide tools to define treatment strategies for patients with advanced MYB-activated ACC.

GSK3ß regulates epithelial-mesenchymal transition and cancer stem cell properties in triple-negative breast cancer.

BACKGROUND: Triple-negative breast cancers (TNBCs), which lack receptors for estrogen, progesterone, and amplification of epidermal growth factor receptor 2, are highly aggressive. Consequently, patients diagnosed with TNBCs have reduced overall and disease-free survival rates compared to patients with other subtypes of breast cancer. TNBCs are characterized by the presence of cancer cells with mesenchymal properties, indicating that the epithelial to mesenchymal transition (EMT) plays a major role in the progression of this disease. The EMT program has also been implicated in chemoresistance, tumor recurrence, and induction of cancer stem cell (CSC) properties. Currently, there are no targeted therapies for TNBC, and hence, it is critical to identify the novel targets to treat TNBC. METHODS: A library of compounds was screened for their ability to inhibit EMT in cells with mesenchymal phenotype as assessed using the previously described Z-cad reporters. Of the several drugs tested, GSK3ß inhibitors were identified as EMT inhibitors. The effects of GSK3ß inhibitors on the properties of TNBC cells with a mesenchymal phenotype were assessed using qRT-PCR, flow cytometry, western blot, mammosphere, and migration and cell viability assays. Publicly available datasets also were analyzed to examine if the expression of GSK3ß correlates with the overall survival of breast cancer patients. RESULTS: We identified a GSK3ß inhibitor, BIO, in a drug screen as one of the most potent inhibitors of EMT. BIO and two other GSK3ß inhibitors, TWS119 and LiCl, also decreased the expression of mesenchymal markers in several different cell lines with a mesenchymal phenotype. Further, inhibition of GSK3ß reduced EMT-related migratory properties of cells with mesenchymal properties. To determine if GSK3ß inhibitors target mesenchymal-like cells by affecting the CSC population, we employed mammosphere assays and profiled the stem cell-related cell surface marker CD44+/24- in cells after exposure to GSK3ß inhibitors. We found that GSK3ß inhibitors indeed decreased the CSC properties of cell types with mesenchymal properties. We treated cells with epithelial and mesenchymal properties with GSK3ß inhibitors and found that GSK3ß inhibitors selectively kill cells with mesenchymal attributes while sparing cells with epithelial properties. We analyzed patient data to identify genes predictive of poor clinical outcome that could serve as novel therapeutic targets for TNBC. The Wnt signaling pathway is critical to EMT, but among the various factors known to be involved in Wnt signaling, only the higher expression of GSK3ß correlated with poorer overall patient survival. CONCLUSIONS: Taken together, our data demonstrate that GSK3ß is a potential target for TNBCs and suggest that GSK3ß inhibitors could serve as selective inhibitors of EMT and CSC properties for the treatment of a subset of aggressive TNBC. GSK3ß inhibitors should be tested for use in combination with standard-of-care drugs in preclinical TNBC models.

Restructuring of the Gut Microbiome by Intermittent Fasting Prevents Retinopathy and Prolongs Survival in db/db Mice.

Intermittent fasting (IF) protects against the development of metabolic diseases and cancer, but whether it can prevent diabetic microvascular complications is not known. In db/db mice, we examined the impact of long-term IF on diabetic retinopathy (DR). Despite no change in glycated hemoglobin, db/db mice on the IF regimen displayed significantly longer survival and a reduction in DR end points, including acellular capillaries and leukocyte infiltration. We hypothesized that IF-mediated changes in the gut microbiota would produce beneficial metabolites and prevent the development of DR. Microbiome analysis revealed increased levels of Firmicutes and decreased Bacteroidetes and Verrucomicrobia. Compared with db/db mice on ad libitum feeding, changes in the microbiome of the db/db mice on IF were associated with increases in gut mucin, goblet cell number, villi length, and reductions in plasma peptidoglycan. Consistent with the known modulatory effects of Firmicutes on bile acid (BA) metabolism, measurement of BAs demonstrated a significant increase of tauroursodeoxycholate (TUDCA), a neuroprotective BA, in db/db on IF but not in db/db on AL feeding. TGR5, the TUDCA receptor, was found in the retinal primary ganglion cells. Expression of TGR5 did not change with IF or diabetes. However, IF reduced retinal TNF-α mRNA, which is a downstream target of TGR5 activation. Pharmacological activation of TGR5 using INT-767 prevented DR in a second diabetic mouse model. These findings support the concept that IF prevents DR by restructuring the microbiota toward species producing TUDCA and subsequent retinal protection by TGR5 activation.

Chemoresistance Evolution in Triple-Negative Breast Cancer Delineated by Single-Cell Sequencing.

Triple-negative breast cancer (TNBC) is an aggressive subtype that frequently develops resistance to chemotherapy. An unresolved question is whether resistance is caused by the selection of rare pre-existing clones or alternatively through the acquisition of new genomic aberrations. To investigate this question, we applied single-cell DNA and RNA sequencing in addition to bulk exome sequencing to profile longitudinal samples from 20 TNBC patients during neoadjuvant chemotherapy (NAC). Deep-exome sequencing identified 10 patients in which NAC led to clonal extinction and 10 patients in which clones persisted after treatment. In 8 patients, we performed a more detailed study using single-cell DNA sequencing to analyze 900 cells and single-cell RNA sequencing to analyze 6,862 cells. Our data showed that resistant genotypes were pre-existing and adaptively selected by NAC, while transcriptional profiles were acquired by reprogramming in response to chemotherapy in TNBC patients.

Multiclonal Invasion in Breast Tumors Identified by Topographic Single Cell Sequencing.

Ductal carcinoma in situ (DCIS) is an early-stage breast cancer that infrequently progresses to invasive ductal carcinoma (IDC). Genomic evolution has been difficult to delineate during invasion due to intratumor heterogeneity and the low number of tumor cells in the ducts. To overcome these challenges, we developed Topographic Single Cell Sequencing (TSCS) to measure genomic copy number profiles of single tumor cells while preserving their spatial context in tissue sections. We applied TSCS to 1,293 single cells from 10 synchronous patients with both DCIS and IDC regions in addition to exome sequencing. Our data reveal a direct genomic lineage between in situ and invasive tumor subpopulations and further show that most mutations and copy number aberrations evolved within the ducts prior to invasion. These results support a multiclonal invasion model, in which one or more clones escape the ducts and migrate into the adjacent tissues to establish the invasive carcinomas.

Integrative genome analysis of somatic p53 mutant osteosarcomas identifies Ets2-dependent regulation of small nucleolar RNAs by mutant p53 protein.

TP53 is the most frequently mutated gene in human cancer. Many mutant p53 proteins exert oncogenic gain-of-function (GOF) properties that contribute to metastasis, but the mechanisms mediating these functions remain poorly defined in vivo. To elucidate how mutant p53 GOF drives metastasis, we developed a traceable somatic osteosarcoma mouse model that is initiated with either a single p53 mutation (p53R172H) or p53 loss in osteoblasts. Our study confirmed that p53 mutant mice developed osteosarcomas with increased metastasis as compared with p53-null mice. Comprehensive transcriptome RNA sequencing (RNA-seq) analysis of 16 tumors identified a cluster of small nucleolar RNAs (snoRNAs) that are highly up-regulated in p53 mutant tumors. Regulatory element analysis of these deregulated snoRNA genes identified strong enrichment of a common Ets2 transcription factor-binding site. Homozygous deletion of Ets2 in p53 mutant mice resulted in strong down-regulation of snoRNAs and reversed the prometastatic phenotype of mutant p53 but had no effect on osteosarcoma development, which remained 100% penetrant. In summary, our studies identify Ets2 inhibition as a potential therapeutic vulnerability in p53 mutant osteosarcomas.

Nanogrid single-nucleus RNA sequencing reveals phenotypic diversity in breast cancer.

Single cell RNA sequencing has emerged as a powerful tool for resolving transcriptional diversity in tumors, but is limited by throughput, cost and the ability to process archival frozen tissue samples. Here we develop a high-throughput 3' single-nucleus RNA sequencing approach that combines nanogrid technology, automated imaging, and cell selection to sequence up to ~1800 single nuclei in parallel. We compare the transcriptomes of 485 single nuclei to 424 single cells in a breast cancer cell line, which shows a high concordance (93.34%) in gene levels and abundance. We also analyze 416 nuclei from a frozen breast tumor sample and 380 nuclei from normal breast tissue. These data reveal heterogeneity in cancer cell phenotypes, including angiogenesis, proliferation, and stemness, and a minor subpopulation (19%) with many overexpressed cancer genes. Our studies demonstrate the utility of nanogrid single-nucleus RNA sequencing for studying the transcriptional programs of tumor nuclei in frozen archival tissue samples.Single cell RNA sequencing is a powerful tool for understanding cellular diversity but is limited by cost, throughput and sample preparation. Here the authors use nanogrid technology with integrated imaging to sequence thousands of cancer nuclei in parallel from fresh or frozen tissue.

Immunodeficiency in Pancreatic Adenocarcinoma with Diabetes Revealed by Comparative Genomics.

Purpose: Pancreatic adenocarcinomas (PAAD) often are not diagnosed until their late stages, leaving no effective treatments. Currently, immunotherapy provides a promising treatment option against this malignancy. However, a set of immunotherapy agents benefit patients with many types of cancer, but not PAAD. Sharing the origin in the same organ, diabetes and PAAD tend to occur concurrently. We aimed to identify the impact of diabetes on immunotherapy of PAAD by conducting a comparative genomics analysis.Experimental Design: We analyzed level 3 PAAD genomics data (RNAseq, miRNAseq, DNA methylation, somatic copy number, and somatic mutation) from The Cancer Genome Atlas (TCGA) and Firehose. The differential molecular profiles in PAAD with/out diabetes were performed by the differential gene expression, pathway analysis, epigenetic regulation, somatic copy-number alteration, and somatic gene mutation.Results: Differential gene expression analysis revealed a strong enrichment of immunogenic signature genes in diabetic individuals, including PD-1 and CTLA4, that were currently targetable for immunotherapy. Pathway analysis further implied that diabetic individuals were defective in immune modulation genes. Somatic copy-number aberration (SCNA) analysis showed a higher frequency of amplification and deletion occurred in the cohort without diabetes. Integrative analysis revealed strong association between differential gene expression, and epigenetic regulations, however, seemed not affected by SCNAs. Importantly, our somatic mutation analysis showed that the occurrence of diabetes in PAAD was associated with a large set of gene mutations encoding genes participating in immune modulation.Conclusions: Our analysis reveals the impact of diabetes on immunodeficiency in PAAD patients and provides novel insights into new therapeutic opportunities. Clin Cancer Res; 23(20); 6363-73. ©2017 AACR.

Single-cell DNA sequencing reveals a late-dissemination model in metastatic colorectal cancer.

Metastasis is a complex biological process that has been difficult to delineate in human colorectal cancer (CRC) patients. A major obstacle in understanding metastatic lineages is the extensive intra-tumor heterogeneity at the primary and metastatic tumor sites. To address this problem, we developed a highly multiplexed single-cell DNA sequencing approach to trace the metastatic lineages of two CRC patients with matched liver metastases. Single-cell copy number or mutational profiling was performed, in addition to bulk exome and targeted deep-sequencing. In the first patient, we observed monoclonal seeding, in which a single clone evolved a large number of mutations prior to migrating to the liver to establish the metastatic tumor. In the second patient, we observed polyclonal seeding, in which two independent clones seeded the metastatic liver tumor after having diverged at different time points from the primary tumor lineage. The single-cell data also revealed an unexpected independent tumor lineage that did not metastasize, and early progenitor clones with the "first hit" mutation in APC that subsequently gave rise to both the primary and metastatic tumors. Collectively, these data reveal a late-dissemination model of metastasis in two CRC patients and provide an unprecedented view of metastasis at single-cell genomic resolution.

Tumor evolution: Linear, branching, neutral or punctuated?

Intratumor heterogeneity has been widely reported in human cancers, but our knowledge of how this genetic diversity emerges over time remains limited. A central challenge in studying tumor evolution is the difficulty in collecting longitudinal samples from cancer patients. Consequently, most studies have inferred tumor evolution from single time-point samples, providing very indirect information. These data have led to several competing models of tumor evolution: linear, branching, neutral and punctuated. Each model makes different assumptions regarding the timing of mutations and selection of clones, and therefore has different implications for the diagnosis and therapeutic treatment of cancer patients. Furthermore, emerging evidence suggests that models may change during tumor progression or operate concurrently for different classes of mutations. Finally, we discuss data that supports the theory that most human tumors evolve from a single cell in the normal tissue. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.

Punctuated copy number evolution and clonal stasis in triple-negative breast cancer.

Aneuploidy is a hallmark of breast cancer; however, knowledge of how these complex genomic rearrangements evolve during tumorigenesis is limited. In this study, we developed a highly multiplexed single-nucleus sequencing method to investigate copy number evolution in patients with triple-negative breast cancer. We sequenced 1,000 single cells from tumors in 12 patients and identified 1-3 major clonal subpopulations in each tumor that shared a common evolutionary lineage. For each tumor, we also identified a minor subpopulation of non-clonal cells that were classified as metastable, pseudodiploid or chromazemic. Phylogenetic analysis and mathematical modeling suggest that these data are unlikely to be explained by the gradual accumulation of copy number events over time. In contrast, our data challenge the paradigm of gradual evolution, showing that the majority of copy number aberrations are acquired at the earliest stages of tumor evolution, in short punctuated bursts, followed by stable clonal expansions that form the tumor mass.

Highly multiplexed targeted DNA sequencing from single nuclei.

Single-cell DNA sequencing methods are challenged by poor physical coverage, high technical error rates and low throughput. To address these issues, we developed a single-cell DNA sequencing protocol that combines flow-sorting of single nuclei, time-limited multiple-displacement amplification (MDA), low-input library preparation, DNA barcoding, targeted capture and next-generation sequencing (NGS). This approach represents a major improvement over our previous single nucleus sequencing (SNS) Nature Protocols paper in terms of generating higher-coverage data (>90%), thereby enabling the detection of genome-wide variants in single mammalian cells at base-pair resolution. Furthermore, by pooling 48-96 single-cell libraries together for targeted capture, this approach can be used to sequence many single-cell libraries in parallel in a single reaction. This protocol greatly reduces the cost of single-cell DNA sequencing, and it can be completed in 5-6 d by advanced users. This single-cell DNA sequencing protocol has broad applications for studying rare cells and complex populations in diverse fields of biological research and medicine.