Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing

Studying hematopoiesis using single-cell technologies

Hematopoiesis is probably the best-understood stem cell differentiation system; hematopoietic stem cell (HSC) transplantation represents the most widely used regenerative therapy. The classical view of lineage hierarchy in hematopoiesis is built on cell type definition system by a group of cell surface markers. However, the traditional model is facing increasing challenges, as many classical cell types are proved to be heterogeneous. Recently, the developments of new technologies allow genome, transcriptome, proteome, and epigenome analysis at the single-cell level. For the first time, we can study hematopoietic system at single-cell resolution on a multi-omic scale. Here, we review recent technical advances in single-cell analysis technology, as well as their current applications. We will also discuss the impact of single-cell technologies on both basic research and clinical application in hematology.

Improved genome sequencing using an engineered transposase

Background

Next-generation sequencing (NGS) has transformed genomic research by reducing turnaround time and cost. However, no major breakthrough has been made in the upstream library preparation methods until the transposase-based Nextera method was invented. Nextera combines DNA fragmentation and barcoding in a single tube reaction and therefore enables a very fast workflow to sequencing-ready DNA libraries within a couple of hours. When compared to the traditional ligation-based methods, transposed-based Nextera has a slight insertion bias.

Results

Here we present the discovery of a mutant transposase (Tn5-059) with a lowered GC insertion bias through protein engineering. We demonstrate Tn5-059 reduces AT dropout and increases uniformity of genome coverage in both bacterial genomes and human genome. We also observe higher library diversity generated by Tn5-059 when compared to Nextera v2 for human exomes, which leads to less sequencing and lower cost per genome. In addition, when used for human exomes, Tn5-059 delivers consistent library insert size over a range of input DNA, allowing up to a tenfold variance from the 50 ng input recommendation.

Conclusions

Enhanced DNA input tolerance of Tn5-059 can translate to flexibility and robustness of workflow. DNA input tolerance together with superior uniformity of coverage and lower AT dropouts extend the applications of transposase based library preps. We discuss possible mechanisms of improvements in Tn5-059, and potential advantages of using the new mutant in varieties of applications including microbiome sequencing and chromatin profiling.

Electronic supplementary material

The online version of this article (doi:10.1186/s12896-016-0326-1) contains supplementary material, which is available to authorized users.

Regulatory elements in molecular networks

Regulatory elements determine the connectivity of molecular networks and mediate a variety of regulatory processes ranging from DNA looping to transcriptional, posttranscriptional, and posttranslational regulation. This review highlights our current understanding of the different types of regulatory elements found in molecular networks with a focus on DNA regulatory elements. We highlight technical advances and current challenges for the mapping of regulatory elements at the genome-wide scale, and describe new computational methods to uncover these elements via reconstructing regulatory networks from large genomic datasets. WIREs Syst Biol Med 2017, 9:e1374. doi: 10.1002/wsbm.1374 For further resources related to this article, please visit the WIREs website.

Biologically Relevant Heterogeneity: Metrics and Practical Insights

Heterogeneity is a fundamental property of biological systems at all scales that must be addressed in a wide range of biomedical applications, including basic biomedical research, drug discovery, diagnostics, and the implementation of precision medicine. There are a number of published approaches to characterizing heterogeneity in cells in vitro and in tissue sections. However, there are no generally accepted approaches for the detection and quantitation of heterogeneity that can be applied in a relatively high-throughput workflow. This review and perspective emphasizes the experimental methods that capture multiplexed cell-level data, as well as the need for standard metrics of the spatial, temporal, and population components of heterogeneity. A recommendation is made for the adoption of a set of three heterogeneity indices that can be implemented in any high-throughput workflow to optimize the decision-making process. In addition, a pairwise mutual information method is suggested as an approach to characterizing the spatial features of heterogeneity, especially in tissue-based imaging. Furthermore, metrics for temporal heterogeneity are in the early stages of development. Example studies indicate that the analysis of functional phenotypic heterogeneity can be exploited to guide decisions in the interpretation of biomedical experiments, drug discovery, diagnostics, and the design of optimal therapeutic strategies for individual patients.

Contiguity-Preserving Transposition Sequencing (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).

Single cell analysis of the inner ear sensory organs

The inner ear is composed of a complex mixture of cells, which together allow organisms to hear and maintain balance. The cells in the inner ear, which undergo an extraordinary process of development, have only recently begun to be studied on an individual level. As it has recently become clear that individual cells, previously considered to be of uniform character, may differ dramatically from each other, the need to study cell-to-cell variation, along with distinct transcriptional and regulatory signatures, has taken hold in the scientific community. In conjunction with high-throughput technologies, attempts are underway to dissect the inter- and intra-cellular variability of different cell types and developmental states of the inner ear from a novel perspective. Single cell analysis of the inner ear sensory organs holds the promise of providing a significant boost in building an omics network that translates into a comprehensive understanding of the mechanisms of hearing and balance. These networks may uncover critical elements for trans-differentiation, regeneration and/or reprogramming, providing entry points for therapeutics of deafness and vestibular pathologies.

Establishing Chromatin Regulatory Landscape during Mouse Preimplantation Development

How the chromatin regulatory landscape in the inner cell mass cells is established from differentially packaged sperm and egg genomes during preimplantation development is unknown. Here, we develop a low-input DNase I sequencing (liDNase-seq) method that allows us to generate maps of DNase I-hypersensitive site (DHS) of mouse preimplantation embryos from 1-cell to morula stage. The DHS landscape is progressively established with a drastic increase at the 8-cell stage. Paternal chromatin accessibility is quickly reprogrammed after fertilization to the level similar to maternal chromatin, while imprinted genes exhibit allelic accessibility bias. We demonstrate that transcription factor Nfya contributes to zygotic genome activation and DHS formation at the 2-cell stage and that Oct4 contributes to the DHSs gained at the 8-cell stage. Our study reveals the dynamic chromatin regulatory landscape during early development and identifies key transcription factors important for DHS establishment in mammalian embryos.

Epigenetics of cell fate reprogramming and its implications for neurological disorders modelling

The reprogramming of human induced pluripotent stem cells (hiPSCs) proceeds in a stepwise manner with reprogramming factors binding and epigenetic composition changes during transition to maintain the epigenetic landscape, important for pluripotency. There arises a question as to whether the aberrant epigenetic state after reprogramming leads to epigenetic defects in induced stem cells causing unpredictable long term effects in differentiated cells. In this review, we present a comprehensive view of epigenetic alterations accompanying reprogramming, cell maintenance and differentiation as factors that influence applications of hiPSCs in stem cell based technologies. We conclude that sample heterogeneity masks DNA methylation signatures in subpopulations of cells and thus believe that beside a genetic evaluation, extensive epigenomic screening should become a standard procedure to ensure hiPSCs state before they are used for genome editing and differentiation into neurons of interest. In particular, we suggest that exploitation of the single-cell composition of the epigenome will provide important insights into heterogeneity within hiPSCs subpopulations to fast forward development of reliable hiPSC-based analytical platforms in neurological disorders modelling and before completed hiPSC technology will be implemented in clinical approaches.

Genome-wide epigenomic profiling for biomarker discovery

A myriad of diseases is caused or characterized by alteration of epigenetic patterns, including changes in DNA methylation, post-translational histone modifications, or chromatin structure. These changes of the epigenome represent a highly interesting layer of information for disease stratification and for personalized medicine. Traditionally, epigenomic profiling required large amounts of cells, which are rarely available with clinical samples. Also, the cellular heterogeneity complicates analysis when profiling clinical samples for unbiased genome-wide biomarker discovery. Recent years saw great progress in miniaturization of genome-wide epigenomic profiling, enabling large-scale epigenetic biomarker screens for disease diagnosis, prognosis, and stratification on patient-derived samples. All main genome-wide profiling technologies have now been scaled down and/or are compatible with single-cell readout, including: (i) Bisulfite sequencing to determine DNA methylation at base-pair resolution, (ii) ChIP-Seq to identify protein binding sites on the genome, (iii) DNaseI-Seq/ATAC-Seq to profile open chromatin, and (iv) 4C-Seq and HiC-Seq to determine the spatial organization of chromosomes. In this review we provide an overview of current genome-wide epigenomic profiling technologies and main technological advances that allowed miniaturization of these assays down to single-cell level. For each of these technologies we evaluate their application for future biomarker discovery. We will focus on (i) compatibility of these technologies with methods used for clinical sample preservation, including methods used by biobanks that store large numbers of patient samples, and (ii) automation of these technologies for robust sample preparation and increased throughput.

DNA methylation and chromatin accessibility profiling of mouse and human fetal germ cells

Chromatin remodeling is important for the epigenetic reprogramming of human primordial germ cells. However, the comprehensive chromatin state has not yet been analyzed for human fetal germ cells (FGCs). Here we use nucleosome occupancy and methylation sequencing method to analyze both the genome-wide chromatin accessibility and DNA methylome at a series of crucial time points during fetal germ cell development in both human and mouse. We find 116 887 and 137 557 nucleosome-depleted regions (NDRs) in human and mouse FGCs, covering a large set of germline-specific and highly dynamic regulatory genomic elements, such as enhancers. Moreover, we find that the distal NDRs are enriched specifically for binding motifs of the pluripotency and germ cell master regulators such as NANOG, SOX17, AP2γ and OCT4 in human FGCs, indicating the existence of a delicate regulatory balance between pluripotency-related genes and germ cell-specific genes in human FGCs, and the functional significance of these genes for germ cell development in vivo. Our work offers a comprehensive and high-resolution roadmap for dissecting chromatin state transition dynamics during the epigenomic reprogramming of human and mouse FGCs.

Understanding the genetic liability to schizophrenia through the neuroepigenome

The Psychiatric Genomics Consortium-Schizophrenia Workgroup (PGC-SCZ) recently identified 108 loci associated with increased risk for schizophrenia (SCZ). The vast majority of these variants reside within non-coding sequences of the genome and are predicted to exert their effects by affecting the mechanism of action of cis regulatory elements (CREs), such as promoters and enhancers. Although a number of large-scale collaborative efforts (e.g. ENCODE) have achieved a comprehensive mapping of CREs in human cell lines or tissue homogenates, it is becoming increasingly evident that many risk-associated variants are enriched for expression Quantitative Trait Loci (eQTLs) and CREs in specific tissues or cells. As such, data derived from previous research endeavors may not capture fully cell-type and/or region specific changes associated with brain diseases. Coupling recent technological advances in genomics with cell-type specific methodologies, we are presented with an unprecedented opportunity to better understand the genetics of normal brain development and function and, in turn, the molecular basis of neuropsychiatric disorders. In this review, we will outline ongoing efforts towards this goal and will discuss approaches with the potential to shed light on the mechanism(s) of action of cell-type specific cis regulatory elements and their putative roles in disease, with particular emphasis on understanding the manner in which the epigenome and CREs influence the etiology of SCZ.

ATAC-see reveals the accessible genome by transposase-mediated imaging and sequencing

Spatial organization of the genome plays a central role in gene expression, DNA replication, and repair. But current epigenomic approaches largely map DNA regulatory elements outside of the native context of the nucleus. Here we report assay of transposase-accessible chromatin with visualization (ATAC-see), a transposase-mediated imaging technology that employs direct imaging of the accessible genome in situ, cell sorting, and deep sequencing to reveal the identity of the imaged elements. ATAC-see revealed the cell-type-specific spatial organization of the accessible genome and the coordinated process of neutrophil chromatin extrusion, termed NETosis. Integration of ATAC-see with flow cytometry enables automated quantitation and prospective cell isolation as a function of chromatin accessibility, and it reveals a cell-cycle dependence of chromatin accessibility that is especially dynamic in G1 phase. The integration of imaging and epigenomics provides a general and scalable approach for deciphering the spatiotemporal architecture of gene control.

Dissecting stem cell differentiation using single cell expression profiling

Many assumptions about the way cells behave are based on analyses of populations. However, it is now widely recognized that even apparently pure populations can display a remarkable level of heterogeneity. This is particularly true in stem cell biology where it hinders our understanding of normal development and the development of strategies for regenerative medicine. Over the past decade technologies facilitating gene expression analysis at the single cell level have become widespread, providing access to rare cell populations and insights into population structure and function. Here we review the contributions of single cell biology to understanding stem cell differentiation so far, both as a new methodology for defining cell types and a tool for understanding the complexities of cellular decision-making.

Modeling heterogeneity in the pluripotent state: A promising strategy for improving the efficiency and fidelity of stem cell differentiation

Pluripotency can be considered a functional characteristic of pluripotent stem cells (PSCs) populations and their niches, rather than a property of individual cells. In this view, individual cells within the population independently adopt a variety of different expression states, maintained by different signaling, transcriptional, and epigenetics regulatory networks. In this review, we propose that generation of integrative network models from single cell data will be essential for getting a better understanding of the regulation of self-renewal and differentiation. In particular, we suggest that the identification of network stability determinants in these integrative models will provide important insights into the mechanisms mediating the transduction of signals from the niche, and how these signals can trigger differentiation. In this regard, the differential use of these stability determinants in subpopulation-specific regulatory networks would mediate differentiation into different cell fates. We suggest that this approach could offer a promising avenue for the development of novel strategies for increasing the efficiency and fidelity of differentiation, which could have a strong impact on regenerative medicine.

A comprehensive transcriptional map of primate brain development

The transcriptional underpinnings of brain development remain poorly understood, particularly in humans and closely related non-human primates. We describe a high-resolution transcriptional atlas of rhesus monkey (Macaca mulatta) brain development that combines dense temporal sampling of prenatal and postnatal periods with fine anatomical division of cortical and subcortical regions associated with human neuropsychiatric disease. Gene expression changes more rapidly before birth, both in progenitor cells and maturing neurons. Cortical layers and areas acquire adult-like molecular profiles surprisingly late in postnatal development. Disparate cell populations exhibit distinct developmental timing of gene expression, but also unexpected synchrony of processes underlying neural circuit construction including cell projection and adhesion. Candidate risk genes for neurodevelopmental disorders including primary microcephaly, autism spectrum disorder, intellectual disability, and schizophrenia show disease-specific spatiotemporal enrichment within developing neocortex. Human developmental expression trajectories are more similar to monkey than rodent, although approximately 9% of genes show human-specific regulation with evidence for prolonged maturation or neoteny compared to monkey.

Genetics and immunity in the era of single-cell genomics

Recent developments in the field of single-cell genomics (SCG) are changing our understanding of how functional phenotypes of cell populations emerge from the behaviour of individual cells. Some of the applications of SCG include the discovery of new gene networks and novel cell subpopulations, fine mapping of transcription kinetics, and the relationships between cell clonality and their functional phenotypes. Immunology is one of the fields that is benefiting the most from such advancements, providing us with completely new insights into mammalian immunity. In this review, we start by covering new immunological insights originating from the use of single-cell genomic tools, specifically single-cell RNA-sequencing. Furthermore, we discuss how new genetic study designs are starting to explain inter-individual variation in the immune response. We conclude with a perspective on new multi-omics technologies capable of integrating several readouts from the same single cell and how such techniques might push our biological understanding of mammalian immunity to a new level.

Defining cell types and states with single-cell genomics

A revolution in cellular measurement technology is under way: For the first time, we have the ability to monitor global gene regulation in thousands of individual cells in a single experiment. Such experiments will allow us to discover new cell types and states and trace their developmental origins. They overcome fundamental limitations inherent in measurements of bulk cell population that have frustrated efforts to resolve cellular states. Single-cell genomics and proteomics enable not only precise characterization of cell state, but also provide a stunningly high-resolution view of transitions between states. These measurements may finally make explicit the metaphor that C.H. Waddington posed nearly 60 years ago to explain cellular plasticity: Cells are residents of a vast “landscape” of possible states, over which they travel during development and in disease. Single-cell technology helps not only locate cells on this landscape, but illuminates the molecular mechanisms that shape the landscape itself. However, single-cell genomics is a field in its infancy, with many experimental and computational advances needed to fully realize its full potential.

Epigenomics and the structure of the living genome

Eukaryotic genomes are packaged into an extensively folded state known as chromatin. Analysis of the structure of eukaryotic chromosomes has been revolutionized by development of a suite of genome-wide measurement technologies, collectively termed “epigenomics.” We review major advances in epigenomic analysis of eukaryotic genomes, covering aspects of genome folding at scales ranging from whole chromosome folding down to nucleotide-resolution assays that provide structural insights into protein-DNA interactions. We then briefly outline several challenges remaining and highlight new developments such as single-cell epigenomic assays that will help provide us with a high-resolution structural understanding of eukaryotic genomes.

Genome-wide footprinting: ready for prime time?

High-throughput sequencing technologies have allowed many gene locus-level molecular biology assays to become genome-wide profiling methods. DNA-cleaving enzymes such as DNase I have been used to probe accessible chromatin. The accessible regions contain functional regulatory sites, including promoters, insulators and enhancers. Deep sequencing of DNase-seq libraries and computational analysis of the cut profiles have been used to infer protein occupancy in the genome at the nucleotide level, a method introduced as 'digital genomic footprinting'. The approach has been proposed as an attractive alternative to the analysis of transcription factors (TFs) by chromatin immunoprecipitation followed by sequencing (ChIP-seq), and in theory it should overcome antibody issues, poor resolution and batch effects. Recent reports point to limitations of the DNase-based genomic footprinting approach and call into question the scope of detectable protein occupancy, especially for TFs with short-lived chromatin binding. The genomics community is grappling with issues concerning the utility of genomic footprinting and is reassessing the proposed approaches in terms of robust deliverables. Here we summarize the consensus as well as different views emerging from recent reports, and we describe the remaining issues and hurdles for genomic footprinting.

Advancing haematopoietic stem and progenitor cell biology through single-cell profiling

Haematopoietic stem and progenitor cells (HSPCs) sit at the top of the haematopoietic hierarchy, and their fate choices need to be carefully controlled to ensure balanced production of all mature blood cell types. As cell fate decisions are made at the level of the individual cells, recent technological advances in measuring gene and protein expression in increasingly large numbers of single cells have been rapidly adopted to study both normal and pathological HSPC function. In this review we emphasise the importance of combining the correct computational models with single-cell experimental techniques, and illustrate how such integrated approaches have been used to resolve heterogeneities in populations, reconstruct lineage differentiation, identify regulatory relationships and link molecular profiling to cellular function.

An enduring role for quiescent stem cells

The intestine's ability to recover from catastrophic injury requires quiescent intestinal stem cells (q-ISCs). While rapidly cycling (Lgr5+) crypt base columnar (CBC) ISCs normally maintain the intestine, they are highly sensitive to pathological injuries (irradiation, inflammation) and must be restored by q-ISCs to sustain intestinal homeostasis. Despite clear relevance to human health, virtually nothing is known regarding the factors that regulate q-ISCs. A comprehensive understanding of these mechanisms would likely lead to targeted new therapies with profound therapeutic implications for patients with gastrointestinal conditions. We briefly review the current state of the literature, highlighting homeostatic mechanisms important for q-ISC regulation, listing key questions in the field, and offer strategies to address them. Developmental Dynamics 245:718-726, 2016. © 2016 Wiley Periodicals, Inc.

Whole-organism lineage tracing by combinatorial and cumulative genome editing

Multicellular systems develop from single cells through distinct lineages. However, current lineage-tracing approaches scale poorly to whole, complex organisms. Here, we use genome editing to progressively introduce and accumulate diverse mutations in a DNA barcode over multiple rounds of cell division. The barcode, an array of clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 target sites, marks cells and enables the elucidation of lineage relationships via the patterns of mutations shared between cells. In cell culture and zebrafish, we show that rates and patterns of editing are tunable and that thousands of lineage-informative barcode alleles can be generated. By sampling hundreds of thousands of cells from individual zebrafish, we find that most cells in adult organs derive from relatively few embryonic progenitors. In future analyses, genome editing of synthetic target arrays for lineage tracing (GESTALT) can be used to generate large-scale maps of cell lineage in multicellular systems for normal development and disease.

Single-cell gene expression profiling and cell state dynamics: collecting data, correlating data points and connecting the dots

Single-cell analyses of transcript and protein expression profiles-more precisely, single-cell resolution analysis of molecular profiles of cell populations-have now entered the center stage with widespread applications of single-cell qPCR, single-cell RNA-Seq and CyTOF. These high-dimensional population snapshot techniques are complemented by low-dimensional time-resolved, microscopy-based monitoring methods. Both fronts of advance have exposed a rich heterogeneity of cell states within uniform cell populations in many biological contexts, producing a new kind of data that has triggered computational analysis methods for data visualization, dimensionality reduction, and cluster (subpopulation) identification. The next step is now to go beyond collecting data and correlating data points: to connect the dots, that is, to understand what actually underlies the identified data patterns. This entails interpreting the 'clouds of points' in state space as a manifestation of the underlying molecular regulatory network. In that way control of cell state dynamics can be formalized as a quasi-potential landscape, as first proposed by Waddington. We summarize key methods of data acquisition and computational analysis and explain the principles that link the single-cell resolution measurements to dynamical systems theory.

Decoding transcriptional enhancers: Evolving from annotation to functional interpretation

Deciphering the intricate molecular processes that orchestrate the spatial and temporal regulation of genes has become an increasingly major focus of biological research. The differential expression of genes by diverse cell types with a common genome is a hallmark of complex cellular functions, as well as the basis for multicellular life. Importantly, a more coherent understanding of gene regulation is critical for defining developmental processes, evolutionary principles and disease etiologies. Here we present our current understanding of gene regulation by focusing on the role of enhancer elements in these complex processes. Although functional genomic methods have provided considerable advances to our understanding of gene regulation, these assays, which are usually performed on a genome-wide scale, typically provide correlative observations that lack functional interpretation. Recent innovations in genome editing technologies have placed gene regulatory studies at an exciting crossroads, as systematic, functional evaluation of enhancers and other transcriptional regulatory elements can now be performed in a coordinated, high-throughput manner across the entire genome. This review provides insights on transcriptional enhancer function, their role in development and disease, and catalogues experimental tools commonly used to study these elements. Additionally, we discuss the crucial role of novel techniques in deciphering the complex gene regulatory landscape and how these studies will shape future research.

Identification of plant transcription factor target sequences

Regulation of gene expression depends on specific cis-regulatory sequences located in the gene promoter regions. These DNA sequences are recognized by transcription factors (TFs) in a sequence-specific manner, and their identification could help to elucidate the regulatory networks that underlie plant physiological responses to developmental programs or to environmental adaptation. Here we review recent advances in high throughput methodologies for the identification of plant TF binding sites. Several approaches offer a map of the TF binding locations in vivo and of the dynamics of the gene regulatory networks. As an alternative, high throughput in vitro methods provide comprehensive determination of the DNA sequences recognized by TFs. These advances are helping to decipher the regulatory lexicon and to elucidate transcriptional network hierarchies in plants in response to internal or external cues. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.

Single-Cell Co-expression Analysis Reveals Distinct Functional Modules, Co-regulation Mechanisms and Clinical Outcomes

Co-expression analysis has been employed to predict gene function, identify functional modules, and determine tumor subtypes. Previous co-expression analysis was mainly conducted at bulk tissue level. It is unclear whether co-expression analysis at the single-cell level will provide novel insights into transcriptional regulation. Here we developed a computational approach to compare glioblastoma expression profiles at the single-cell level with those obtained from bulk tumors. We found that the co-expressed genes observed in single cells and bulk tumors have little overlap and show distinct characteristics. The co-expressed genes identified in bulk tumors tend to have similar biological functions, and are enriched for intrachromosomal interactions with synchronized promoter activity. In contrast, single-cell co-expressed genes are enriched for known protein-protein interactions, and are regulated through interchromosomal interactions. Moreover, gene members of some protein complexes are co-expressed only at the bulk level, while those of other complexes are co-expressed at both single-cell and bulk levels. Finally, we identified a set of co-expressed genes that can predict the survival of glioblastoma patients. Our study highlights that comparative analyses of single-cell and bulk gene expression profiles enable us to identify functional modules that are regulated at different levels and hold great translational potential.

Modeling the causal regulatory network by integrating chromatin accessibility and transcriptome data

Cell packs a lot of genetic and regulatory information through a structure known as chromatin, i.e. DNA is wrapped around histone proteins and is tightly packed in a remarkable way. To express a gene in a specific coding region, the chromatin would open up and DNA loop may be formed by interacting enhancers and promoters. Furthermore, the mediator and cohesion complexes, sequence-specific transcription factors, and RNA polymerase II are recruited and work together to elaborately regulate the expression level. It is in pressing need to understand how the information, about when, where, and to what degree genes should be expressed, is embedded into chromatin structure and gene regulatory elements. Thanks to large consortia such as Encyclopedia of DNA Elements (ENCODE) and Roadmap Epigenomic projects, extensive data on chromatin accessibility and transcript abundance are available across many tissues and cell types. This rich data offer an exciting opportunity to model the causal regulatory relationship. Here, we will review the current experimental approaches, foundational data, computational problems, interpretive frameworks, and integrative models that will enable the accurate interpretation of regulatory landscape. Particularly, we will discuss the efforts to organize, analyze, model, and integrate the DNA accessibility data, transcriptional data, and functional genomic regions together. We believe that these efforts will eventually help us understand the information flow within the cell and will influence research directions across many fields.

Single-cell epigenomics: powerful new methods for understanding gene regulation and cell identity

Emerging single-cell epigenomic methods are being developed with the exciting potential to transform our knowledge of gene regulation. Here we review available techniques and future possibilities, arguing that the full potential of single-cell epigenetic studies will be realized through parallel profiling of genomic, transcriptional, and epigenetic information.

Single-cell sequencing in stem cell biology

Cell-to-cell variation and heterogeneity are fundamental and intrinsic characteristics of stem cell populations, but these differences are masked when bulk cells are used for omic analysis. Single-cell sequencing technologies serve as powerful tools to dissect cellular heterogeneity comprehensively and to identify distinct phenotypic cell types, even within a 'homogeneous' stem cell population. These technologies, including single-cell genome, epigenome, and transcriptome sequencing technologies, have been developing rapidly in recent years. The application of these methods to different types of stem cells, including pluripotent stem cells and tissue-specific stem cells, has led to exciting new findings in the stem cell field. In this review, we discuss the recent progress as well as future perspectives in the methodologies and applications of single-cell omic sequencing technologies.

Intratumoral Heterogeneity of the Epigenome

Investigation into intratumoral heterogeneity (ITH) of the epigenome is in a formative stage. The patterns of tumor evolution inferred from epigenetic ITH and genetic ITH are remarkably similar, suggesting widespread co-dependency of these disparate mechanisms. The biological and clinical relevance of epigenetic ITH are becoming more apparent. Rare tumor cells with unique and reversible epigenetic states may drive drug resistance, and the degree of epigenetic ITH at diagnosis may predict patient outcome. This perspective presents these current concepts and clinical implications of epigenetic ITH, and the experimental and computational techniques at the forefront of ITH exploration.

4D nucleomes in single cells: what can computational modeling reveal about spatial chromatin conformation?

Genome-wide sequencing technologies enable investigations of the structural properties of the genome in various spatial dimensions. Here, we review computational techniques developed to model the three-dimensional genome in single cells versus ensembles of cells and assess their underlying assumptions. We further address approaches to study the spatio-temporal aspects of genome organization from single-cell data.

Cell type-specific epigenome profiling using affinity-purified nuclei

The development of a multicellular organism from a single zygote depends on the differentiation of progenitor cells to specialized cell types. The differentiation of these cell types is associated with changes in gene expression and the underlying chromatin landscape. To understand how these processes are regulated, it is desirable to understand how the chromatin features that constitute the epigenome differ between cell types at any given time during development. INTACT, a method for the cell type-specific purification of nuclei that can be used for the isolation of both RNA and chromatin, has emerged as a powerful tool to simultaneously study gene expression and chromatin profiles specifically in cell types of interest. In this review, we focus on the application of INTACT to different model organisms and discuss its potential for profiling cell types in their developmental context.

The mechanisms shaping the single-cell transcriptional landscape

Recent technological and computational advances in understanding the transcriptional and chromatin features of single cells have begun answering longstanding questions in the extent and impact of biological heterogeneity. Here, we outline the intrinsic and extrinsic mechanisms that underlie the transcriptional and functional diversity within superficially homogeneous populations, and we discuss how fascinating new studies have afforded novel insight into each mechanism. The studies are chosen in part to include initial reports of novel functional genomics tools where the eventual applications will clearly have profound impact on our understanding the dynamics of cell-to-cell transcriptional variation-from individual cells to whole organisms.

Smash and DASH with Cas9

DeRisi and colleagues present a creative application for Cas9 in vitro, using it to deplete unwanted sequence from DNA libraries. It seems plausible that the in vitro use of CRISPR/Cas9 has unrealized potential to revolutionize the practice of molecular biology well beyond genome editing.

Single-cell transcriptome sequencing: recent advances and remaining challenges

Single-cell RNA-sequencing methods are now robust and economically practical and are becoming a powerful tool for high-throughput, high-resolution transcriptomic analysis of cell states and dynamics. Single-cell approaches circumvent the averaging artifacts associated with traditional bulk population data, yielding new insights into the cellular diversity underlying superficially homogeneous populations. Thus far, single-cell RNA-sequencing has already shown great effectiveness in unraveling complex cell populations, reconstructing developmental trajectories, and modeling transcriptional dynamics. Ongoing technical improvements to single-cell RNA-sequencing throughput and sensitivity, the development of more sophisticated analytical frameworks for single-cell data, and an increasing array of complementary single-cell assays all promise to expand the usefulness and potential applications of single-cell transcriptomic profiling.

Understanding Spatial Genome Organization: Methods and Insights

The manner by which eukaryotic genomes are packaged into nuclei while maintaining crucial nuclear functions remains one of the fundamental mysteries in biology. Over the last ten years, we have witnessed rapid advances in both microscopic and nucleic acid-based approaches to map genome architecture, and the application of these approaches to the dissection of higher-order chromosomal structures has yielded much new information. It is becoming increasingly clear, for example, that interphase chromosomes form stable, multilevel hierarchical structures. Among them, self-associating domains like so-called topologically associating domains (TADs) appear to be building blocks for large-scale genomic organization. This review describes features of these broadly-defined hierarchical structures, insights into the mechanisms underlying their formation, our current understanding of how interactions in the nuclear space are linked to gene regulation, and important future directions for the field.

Spatial Organization of Epigenomes

The role of genome architecture in transcription regulation has become the focus of an increasing number of studies over the past decade. Chromatin organization can have a significant impact on gene expression by promoting or restricting the physical proximity between regulatory DNA elements. Given that any change in chromatin state has the potential to alter DNA folding and the proximity between control elements, the spatial organization of chromatin is inherently linked to its molecular composition. In this review, we explore how modulators of chromatin state and organization might keep gene expression in check. We discuss recent findings and present some of the less well-studied aspects of spatial genome organization such as chromatin dynamics and regulation by non-coding RNAs.

Characterization of chromatin accessibility with a transposome hypersensitive sites sequencing (THS-seq) assay

Chromatin accessibility captures in vivo protein-chromosome binding status, and is considered an informative proxy for protein-DNA interactions. DNase I and Tn5 transposase assays require thousands to millions of fresh cells for comprehensive chromatin mapping. Applying Tn5 tagmentation to hundreds of cells results in sparse chromatin maps. We present a transposome hypersensitive sites sequencing assay for highly sensitive characterization of chromatin accessibility. Linear amplification of accessible DNA ends with in vitro transcription, coupled with an engineered Tn5 super-mutant, demonstrates improved sensitivity on limited input materials, and accessibility of small regions near distal enhancers, compared with ATAC-seq.

A survey of best practices for RNA-seq data analysis

RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping. We highlight the challenges associated with each step. We discuss the analysis of small RNAs and the integration of RNA-seq with other functional genomics techniques. Finally, we discuss the outlook for novel technologies that are changing the state of the art in transcriptomics.

Epigenomic annotation of gene regulatory alterations during evolution of the primate brain

Although genome sequencing has identified numerous noncoding alterations between primate species, which of those are regulatory and potentially relevant to the evolution of the human brain is unclear. Here we annotated cis-regulatory elements (CREs) in the human, rhesus macaque and chimpanzee genomes using chromatin immunoprecipitation followed by sequencing (ChIP-seq) in different anatomical regions of the adult brain. We found high similarity in the genomic positioning of rhesus macaque and human CREs, suggesting that the majority of these elements were already present in a common ancestor 25 million years ago. Most of the observed regulatory changes between humans and rhesus macaques occurred before the ancestral separation of humans and chimpanzees, leaving a modest set of regulatory elements with predicted human specificity. Our data refine previous predictions and hypotheses on the consequences of genomic changes between primate species and allow the identification of regulatory alterations relevant to the evolution of the brain.

Cis-regulatory programs in the development and evolution of vertebrate paired appendages

Differential gene expression is the core of development, mediating the genetic changes necessary for determining cell identity. The regulation of gene activity by cis-acting elements (e.g., enhancers) is a crucial mechanism for determining differential gene activity by precise control of gene expression in embryonic space and time. Modifications to regulatory regions can have profound impacts on phenotype, and therefore developmental and evolutionary biologists have increasingly focused on elucidating the transcriptional control of genes that build and pattern body plans. Here, we trace the evolutionary history of transcriptional control of three loci key to vertebrate appendage development (Fgf8, Shh, and HoxD/A). Within and across these regulatory modules, we find both complex and flexible regulation in contrast with more fixed enhancers that appear unchanged over vast timescales of vertebrate evolution. The transcriptional control of vertebrate appendage development was likely already incredibly complex in the common ancestor of fish, implying that subtle changes to regulatory networks were more likely responsible for alterations in phenotype rather than the de novo addition of whole regulatory domains. Finally, we discuss the dangers of relying on inter-species transgenesis when testing enhancer function, and call for more controlled regulatory swap experiments when inferring the evolutionary history of enhancer elements.

Genome-wide detection of DNase I hypersensitive sites in single cells and FFPE tissue samples

DNase I hypersensitive sites (DHSs) provide important information on the presence of transcriptional regulatory elements and the state of chromatin in mammalian cells. Conventional DNase sequencing (DNase-seq) for genome-wide DHSs profiling is limited by the requirement of millions of cells. Here we report an ultrasensitive strategy, called single-cell DNase sequencing (scDNase-seq) for detection of genome-wide DHSs in single cells. We show that DHS patterns at the single-cell level are highly reproducible among individual cells. Among different single cells, highly expressed gene promoters and enhancers associated with multiple active histone modifications display constitutive DHS whereas chromatin regions with fewer histone modifications exhibit high variation of DHS. Furthermore, the single-cell DHSs predict enhancers that regulate cell-specific gene expression programs and the cell-to-cell variations of DHS are predictive of gene expression. Finally, we apply scDNase-seq to pools of tumour cells and pools of normal cells, dissected from formalin-fixed paraffin-embedded tissue slides from patients with thyroid cancer, and detect thousands of tumour-specific DHSs. Many of these DHSs are associated with promoters and enhancers critically involved in cancer development. Analysis of the DHS sequences uncovers one mutation (chr18: 52417839G>C) in the tumour cells of a patient with follicular thyroid carcinoma, which affects the binding of the tumour suppressor protein p53 and correlates with decreased expression of its target gene TXNL1. In conclusion, scDNase-seq can reliably detect DHSs in single cells, greatly extending the range of applications of DHS analysis both for basic and for translational research, and may provide critical information for personalized medicine.