Genome-wide mapping of DNase I hypersensitive sites in rare cell populations using single-cell DNase sequencing

Emerging Approaches to Profile Accessible Chromatin from Formalin-Fixed Paraffin-Embedded Sections

Nucleosomes are non-uniformly distributed across eukaryotic genomes, with stretches of 'open' chromatin strongly associated with transcriptionally active promoters and enhancers. Understanding chromatin accessibility patterns in normal tissue and how they are altered in pathologies can provide critical insights to development and disease. With the advent of high-throughput sequencing, a variety of strategies have been devised to identify open regions across the genome, including DNase-seq, MNase-seq, FAIRE-seq, ATAC-seq, and NicE-seq. However, the broad application of such methods to FFPE (formalin-fixed paraffin-embedded) tissues has been curtailed by the major technical challenges imposed by highly fixed and often damaged genomic material. Here, we review the most common approaches for mapping open chromatin regions, recent optimizations to overcome the challenges of working with FFPE tissue, and a brief overview of a typical data pipeline with analysis considerations.

Single-cell sequencing technology applied to epigenetics for the study of tumor heterogeneity

BACKGROUND

Previous studies have traditionally attributed the initiation of cancer cells to genetic mutations, considering them as the fundamental drivers of carcinogenesis. However, recent research has shed light on the crucial role of epigenomic alterations in various cell types present within the tumor microenvironment, suggesting their potential contribution to tumor formation and progression. Despite these significant findings, the progress in understanding the epigenetic mechanisms regulating tumor heterogeneity has been impeded over the past few years due to the lack of appropriate technical tools and methodologies.

RESULTS

The emergence of single-cell sequencing has enhanced our understanding of the epigenetic mechanisms governing tumor heterogeneity by revealing the distinct epigenetic layers of individual cells (chromatin accessibility, DNA/RNA methylation, histone modifications, nucleosome localization) and the diverse omics (transcriptomics, genomics, multi-omics) at the single-cell level. These technologies provide us with new insights into the molecular basis of intratumoral heterogeneity and help uncover key molecular events and driving mechanisms in tumor development.

CONCLUSION

This paper provides a comprehensive review of the emerging analytical and experimental approaches of single-cell sequencing in various omics, focusing specifically on epigenomics. These approaches have the potential to capture and integrate multiple dimensions of individual cancer cells, thereby revealing tumor heterogeneity and epigenetic features. Additionally, this paper outlines the future trends of these technologies and their current technical limitations.

Transcription factor TCF-1 regulates the functions, but not the development, of lymphoid tissue inducer subsets in different tissues

Lymphoid tissue inducer (LTi) cells, a subset of innate lymphoid cells (ILCs), play an essential role in the formation of secondary lymphoid tissues. However, the regulation of the development and functions of this ILC subset is still elusive. In this study, we report that the transcription factor T cell factor 1 (TCF-1), just as GATA3, is indispensable for the development of non-LTi ILC subsets. While LTi cells are still present in TCF-1-deficient mice, the organogenesis of Peyer's patches (PPs), but not of lymph nodes, is impaired in these mice. LTi cells from different tissues have distinct gene expression patterns, and TCF-1 regulates the expression of lymphotoxin specifically in PP LTi cells. Mechanistically, TCF-1 may directly and/or indirectly regulate Lta, including through promoting the expression of GATA3. Thus, the TCF-1-GATA3 axis, which plays an important role during T cell development, also critically regulates the development of non-LTi cells and tissue-specific functions of LTi cells.

LangMoDHS: A deep learning language model for predicting DNase I hypersensitive sites in mouse genome

DNase I hypersensitive sites (DHSs) are a specific genomic region, which is critical to detect or understand cis-regulatory elements. Although there are many methods developed to detect DHSs, there is a big gap in practice. We presented a deep learning-based language model for predicting DHSs, named LangMoDHS. The LangMoDHS mainly comprised the convolutional neural network (CNN), the bi-directional long short-term memory (Bi-LSTM) and the feed-forward attention. The CNN and the Bi-LSTM were stacked in a parallel manner, which was helpful to accumulate multiple-view representations from primary DNA sequences. We conducted 5-fold cross-validations and independent tests over 14 tissues and 4 developmental stages. The empirical experiments showed that the LangMoDHS is competitive with or slightly better than the iDHS-Deep, which is the latest method for predicting DHSs. The empirical experiments also implied substantial contribution of the CNN, Bi-LSTM, and attention to DHSs prediction. We implemented the LangMoDHS as a user-friendly web server which is accessible at http:/www.biolscience.cn/LangMoDHS/. We used indices related to information entropy to explore the sequence motif of DHSs. The analysis provided a certain insight into the DHSs.

Chromatin Dynamics in Digestive System Cancer: Commander and Regulator

Digestive system tumors have a poor prognosis due to complex anatomy, insidious onset, challenges in early diagnosis, and chemoresistance. Epidemiological statistics has verified that digestive system tumors rank first in tumor-related death. Although a great number of studies are devoted to the molecular biological mechanism, early diagnostic markers, and application of new targeted drugs in digestive system tumors, the therapeutic effect is still not satisfactory. Epigenomic alterations including histone modification and chromatin remodeling are present in human cancers and are now known to cooperate with genetic changes to drive the cancer phenotype. Chromatin is the carrier of genetic information and consists of DNA, histones, non-histone proteins, and a small amount of RNA. Chromatin and nucleosomes control the stability of the eukaryotic genome and regulate DNA processes such as transcription, replication, and repair. The dynamic structure of chromatin plays a key role in this regulatory function. Structural fluctuations expose internal DNA and thus provide access to the nuclear machinery. The dynamic changes are affected by various complexes and epigenetic modifications. Variation of chromatin dynamics produces early and superior regulation of the expression of related genes and downstream pathways, thereby controlling tumor development. Intervention at the chromatin level can change the process of cancer earlier and is a feasible option for future tumor diagnosis and treatment. In this review, we introduced chromatin dynamics including chromatin remodeling, histone modifications, and chromatin accessibility, and current research on chromatin regulation in digestive system tumors was also summarized.

Advances and applications of single-cell omics technologies in plant research

Single-cell sequencing approaches reveal the intracellular dynamics of individual cells and answer biological questions with high-dimensional catalogs of millions of cells, including genomics, transcriptomics, chromatin accessibility, epigenomics, and proteomics data across species. These emerging yet thriving technologies have been fully embraced by the field of plant biology, with a constantly expanding portfolio of applications. Here, we introduce the current technical advances used for single-cell omics, especially single-cell genome and transcriptome sequencing. Firstly, we overview methods for protoplast and nucleus isolation and genome and transcriptome amplification. Subsequently, we use well-executed benchmarking studies to highlight advances made through the application of single-cell omics techniques. Looking forward, we offer a glimpse of additional hurdles and future opportunities that will introduce broad adoption of single-cell sequencing with revolutionary perspectives in plant biology.

Single-Cell Sequencing: Current Applications in Precision Onco-Genomics and Cancer Therapeutics

Simple Summary

Single-cell sequencing technologies are growing, advancing, and supporting new opportunities to better understand cancer. A variety of technologies are available that analyze the human transcriptome, genome, epigenome, and proteome, enabling integrated datasets. As a result, these integrated datasets contribute to new mechanistic insights and areas with therapeutic potential. This review summarizes the various single-cell sequencing techniques and provides examples of recent high-impact findings from the utilization of these technologies. Additionally, the translational relevance of these technologies and their use in clinical trials is described, along with the future potential for novel findings using these innovative methods.

Abstract

Single-cell sequencing encompasses a variety of technologies that evaluate cells at the genomic, transcriptomic, epigenomic, and proteomic levels. Each of these levels can be split into additional techniques that enable specific and optimized sequencing for a specialized purpose. At the transcriptomic level, single-cell sequencing has been used to understand immune-malignant cell networks, as well as differences between primary versus metastatic tumors. At the genomic and epigenomic levels, single-cell sequencing technology has been used to study genetic mutations involved in tumor evolution or the reprogramming of regulatory elements present in metastasized disease, respectively. Lastly, at the proteomic level, single-cell sequencing has been used to identify biomarkers important for predicting patient prognosis, as well as biomarkers essential for evaluating optimal treatment strategies. Integrated databases and atlases, as a result of large sequencing experiments, provide a vast array of information that can be applied to various studies and accessed by researchers to further answer scientific questions. This review summarizes recent, high-impact literature covering these aspects, as well as single-cell sequencing in the translational setting. Specifically, we review the potential that single-cell sequencing has in the clinic and its implementation in current clinical studies.

Genome-wide cancer-specific chromatin accessibility patterns derived from archival processed xenograft tumors

Chromatin accessibility states that influence gene expression and other nuclear processes can be altered in disease. The constellation of transcription factors and chromatin regulatory complexes in cells results in characteristic patterns of chromatin accessibility. The study of these patterns in tissues has been limited because existing chromatin accessibility assays are ineffective for archival formalin-fixed, paraffin-embedded (FFPE) tissues. We have developed a method to efficiently extract intact chromatin from archival tissue via enhanced cavitation with a nanodroplet reagent consisting of a lipid shell with a liquid perfluorocarbon core. Inclusion of nanodroplets during the extraction of chromatin from FFPE tissues enhances the recovery of intact accessible and nucleosome-bound chromatin. We show that the addition of nanodroplets to the chromatin accessibility assay formaldehyde-assisted isolation of regulatory elements (FAIRE), does not affect the accessible chromatin signal. Applying the technique to FFPE human tumor xenografts, we identified tumor-relevant regions of accessible chromatin shared with those identified in primary tumors. Further, we deconvoluted non-tumor signal to identify cellular components of the tumor microenvironment. Incorporation of this method of enhanced cavitation into FAIRE offers the potential for extending chromatin accessibility to clinical diagnosis and personalized medicine, while also enabling the exploration of gene regulatory mechanisms in archival samples.

A plate-based single-cell ATAC-seq workflow for fast and robust profiling of chromatin accessibility

Profiling chromatin accessibility at the single-cell level provides critical information about cell type composition and cell-to-cell variation within a complex tissue. Emerging techniques for the interrogation of chromatin accessibility in individual cells allow investigation of the fundamental mechanisms that lead to the variability of different cells. This protocol describes a fast and robust method for single-cell chromatin accessibility profiling based on the assay for transposase-accessible chromatin using sequencing (ATAC-seq). The method combines up-front bulk Tn5 tagging of chromatin with flow cytometry to isolate single nuclei or cells. Reagents required to generate sequencing libraries are added to the same well in the plate where cells are sorted. The protocol described here generates data of high complexity and excellent signal-to-noise ratio and can be combined with index sorting for in-depth characterization of cell types. The whole experimental procedure can be finished within 1 or 2 d with a throughput of hundreds to thousands of nuclei, and the data can be processed by the provided computational pipeline. The execution of the protocol only requires basic techniques and equipment in a molecular biology laboratory with flow cytometry support.

[Advances in the application of affinity separation for analyzing protein ubiquitination]

蛋白质泛素化是真核生物最普遍、最复杂的翻译后修饰方式之一,在细胞的信号转导、生长、发育、代谢等生命过程中发挥着重要作用。泛素化过程的失调则与神经退行性疾病、炎症反应、癌症等重大疾病的发生发展密切相关。分析和研究蛋白质泛素化的结构与功能,可望为认识生命、探索疾病调控内在规律和发现新的诊断策略提供重要信息。生命体系的高度复杂性,泛素化修饰位点、结构类型的多变和多样性,时空动态变化等特点给蛋白质泛素化分析研究带来了巨大的挑战。亲和分离以其高选择性成为泛素化蛋白质结构与功能研究的有力工具。免疫亲和分离法基于抗原-抗体相互作用,是最为经典的分离分析方法,已广泛应用于泛素化蛋白质或肽段的富集分离。源于天然泛素受体的泛素结合结构域(ubiquitin binding domains, UBDs)可与泛素或多聚泛素链相互作用。UBDs和基于此发展起来的串联泛素结合实体(tandem ubiquitin-binding entities, TUBEs)已成为蛋白质泛素化功能研究的热门识别分子。各种多肽类化合物的发展也为蛋白质泛素化的结构和功能解析提供新工具。此外,多种亲和识别配基的联合使用,在蛋白质泛素化修饰的高特异性、高灵敏度分析中展现了独特的优势,为认识生命体内的泛素化修饰提供了重要保障。该文对亲和分离方法在蛋白质泛素化修饰分析中的应用及进展进行了综述。

Multiplex indexing approach for the detection of DNase I hypersensitive sites in single cells

Single cell chromatin accessibility assays reveal epigenomic variability at cis-regulatory elements among individual cells. We previously developed a single-cell DNase-seq assay (scDNase-seq) to profile accessible chromatin in a limited number of single cells. Here, we report a novel indexing strategy to resolve single-cell DNase hypersensitivity profiles based on bulk cell analysis. This new technique, termed indexing single-cell DNase sequencing (iscDNase-seq), employs the activities of terminal DNA transferase (TdT) and T4 DNA ligase to add unique cell barcodes to DNase-digested chromatin ends. By a three-layer indexing strategy, it allows profiling genome-wide DHSs for >15 000 single-cells in a single experiment. Application of iscDNase-seq to human white blood cells accurately revealed specific cell types and inferred regulatory transcription factors (TF) specific to each cell type. We found that iscDNase-seq detected DHSs with specific properties related to gene expression and conservation missed by scATAC-seq for the same cell type. Also, we found that the cell-to-cell variation in accessibility computed using iscDNase-seq data is significantly correlated with the cell-to-cell variation in gene expression. Importantly, this correlation is significantly higher than that between scATAC-seq and scRNA-seq, suggesting that iscDNase-seq data can better predict the cellular heterogeneity in gene expression compared to scATAC-seq. Thus, iscDNase-seq is an attractive alternative method for single-cell epigenomics studies.

UniPath: a uniform approach for pathway and gene-set based analysis of heterogeneity in single-cell epigenome and transcriptome profiles

Recent advances in single-cell open-chromatin and transcriptome profiling have created a challenge of exploring novel applications with a meaningful transformation of read-counts, which often have high variability in noise and drop-out among cells. Here, we introduce UniPath, for representing single-cells using pathway and gene-set enrichment scores by a transformation of their open-chromatin or gene-expression profiles. The robust statistical approach of UniPath provides high accuracy, consistency and scalability in estimating gene-set enrichment scores for every cell. Its framework provides an easy solution for handling variability in drop-out rate, which can sometimes create artefact due to systematic patterns. UniPath provides an alternative approach of dimension reduction of single-cell open-chromatin profiles. UniPath's approach of predicting temporal-order of single-cells using their pathway enrichment scores enables suppression of covariates to achieve correct order of cells. Analysis of mouse cell atlas using our approach yielded surprising, albeit biologically-meaningful co-clustering of cell-types from distant organs. By enabling an unconventional method of exploiting pathway co-occurrence to compare two groups of cells, our approach also proves to be useful in inferring context-specific regulations in cancer cells. Available at https://reggenlab.github.io/UniPathWeb/.

Chromatin Regulation in Development: Current Understanding and Approaches

The regulation of mammalian stem cell fate during differentiation is complex and can be delineated across many levels. At the chromatin level, the replacement of histone variants by chromatin-modifying proteins, enrichment of specific active and repressive histone modifications, long-range gene interactions, and topological changes all play crucial roles in the determination of cell fate. These processes control regulatory elements of critical transcriptional factors, thereby establishing the networks unique to different cell fates and initiate waves of distinctive transcription events. Due to the technical challenges posed by previous methods, it was difficult to decipher the mechanism of cell fate determination at early embryogenesis through chromatin regulation. Recently, single-cell approaches have revolutionised the field of developmental biology, allowing unprecedented insights into chromatin structure and interactions in early lineage segregation events during differentiation. Here, we review the recent technological advancements and how they have furthered our understanding of chromatin regulation during early differentiation events.

Chromatin accessibility profiling methods

Chromatin accessibility, or the physical access to chromatinized DNA, is a widely studied characteristic of the eukaryotic genome. As active regulatory DNA elements are generally 'accessible', the genome-wide profiling of chromatin accessibility can be used to identify candidate regulatory genomic regions in a tissue or cell type. Multiple biochemical methods have been developed to profile chromatin accessibility, both in bulk and at the single-cell level. Depending on the method, enzymatic cleavage, transposition or DNA methyltransferases are used, followed by high-throughput sequencing, providing a view of genome-wide chromatin accessibility. In this Primer, we discuss these biochemical methods, as well as bioinformatics tools for analysing and interpreting the generated data, and insights into the key regulators underlying developmental, evolutionary and disease processes. We outline standards for data quality, reproducibility and deposition used by the genomics community. Although chromatin accessibility profiling is invaluable to study gene regulation, alone it provides only a partial view of this complex process. Orthogonal assays facilitate the interpretation of accessible regions with respect to enhancer-promoter proximity, functional transcription factor binding and regulatory function. We envision that technological improvements including single-molecule, multi-omics and spatial methods will bring further insight into the secrets of genome regulation.

Single-Cell Multi-Omics and Its Prospective Application in Cancer Biology

In recent years, the emergence of single-cell omics technologies, which can profile genomics, transcriptomics, epigenomics, and proteomics, has provided unprecedented insights into characteristics of cancer, enabling higher resolution and accuracy to decipher the cellular and molecular mechanisms relating to tumorigenesis, evolution, metastasis, and immune responses. Single-cell multi-omics technologies, which are developed based on the combination of multiple single-cell mono-omics technologies, can simultaneously analyze RNA expression, single nucleotide polymorphism, epigenetic modification, or protein abundance, enabling the in-depth understanding of gene expression regulatory mechanisms. In this review, the state-of-the-art single-cell multi-omics technologies are summarized and the prospects of their application in cancer biology are discussed.

Genome-wide profiling of nucleosome position and chromatin accessibility in single cells using scMNase-seq

Nucleosome organization is important for chromatin compaction and accessibility. Profiling nucleosome positioning genome-wide in single cells provides critical information to understand the cell-to-cell heterogeneity of chromatin states within a cell population. This protocol describes single-cell micrococcal nuclease sequencing (scMNase-seq), a method for detecting genome-wide nucleosome positioning and chromatin accessibility simultaneously from a small number of cells or single cells. To generate scMNase-seq libraries, single cells are isolated by FACS sorting, lysed and digested by MNase. DNA is purified, end-repaired and ligated to Y-shaped adaptors. Following PCR amplification with indexing primers, the subnucleosome-sized (fragments with a length of ≤80 bp) and mononucleosome-sized (fragments with a length between 140 and 180 bp) DNA fragments are recovered and sequenced on Illumina HiSeq platforms. On average, 0.5-1 million unique mapped reads are obtained for each single cell. The mononucleosome-sized DNA fragments precisely define genome-wide nucleosome positions in single cells, while the subnucleosome-sized DNA fragments provide information on chromatin accessibility. Library preparation of scMNase-seq takes only 2 d, requires only standard molecular biology techniques and does not require sophisticated laboratory equipment. Processing of high-throughput sequencing data requires basic bioinformatics skills and uses publicly available bioinformatics software.

Genomic methods in profiling DNA accessibility and factor localization

Recent advancements in next-generation sequencing technologies and accompanying reductions in cost have led to an explosion of techniques to examine DNA accessibility and protein localization on chromatin genome-wide. Generally, accessible regions of chromatin are permissive for factor binding and are therefore hotspots for regulation of gene expression; conversely, genomic regions that are highly occupied by histone proteins are not permissive for factor binding and are less likely to be active regulatory regions. Identifying regions of differential accessibility can be useful to uncover putative gene regulatory regions, such as enhancers, promoters, and insulators. In addition, DNA-binding proteins, such as transcription factors that preferentially bind certain DNA sequences and histone proteins that form the core of the nucleosome, play essential roles in all DNA-templated processes. Determining the genomic localization of chromatin-bound proteins is therefore essential in determining functional roles, sequence motifs important for factor binding, and regulatory networks controlling gene expression. In this review, we discuss techniques for determining DNA accessibility and nucleosome positioning (DNase-seq, FAIRE-seq, MNase-seq, and ATAC-seq) and techniques for detecting and functionally characterizing chromatin-bound proteins (ChIP-seq, DamID, and CUT&RUN). These methods have been optimized to varying degrees of resolution, specificity, and ease of use. Here, we outline some advantages and disadvantages of these techniques, their general protocols, and a brief discussion of their development. Together, these complimentary approaches have provided an unparalleled view of chromatin architecture and functional gene regulation.

The transcription factor TCF-1 enforces commitment to the innate lymphoid cell lineage

Innate lymphoid cells (ILCs) play important functions in immunity and tissue homeostasis, but their development is poorly understood. Through the use of single-cell approaches, we examined the transcriptional and functional heterogeneity of ILC progenitors, and studied the precursor-product relationships that link the subsets identified. This analysis identified two successive stages of ILC development within T cell factor 1-positive (TCF-1⁺) early innate lymphoid progenitors (EILPs), which we named 'specified EILPs' and 'committed EILPs'. Specified EILPs generated dendritic cells, whereas this potential was greatly decreased in committed EILPs. TCF-1 was dispensable for the generation of specified EILPs, but required for the generation of committed EILPs. TCF-1 used a pre-existing regulatory landscape established in upstream lymphoid precursors to bind chromatin in EILPs. Our results provide insight into the mechanisms by which TCF-1 promotes developmental progression of ILC precursors, while constraining their dendritic cell lineage potential and enforcing commitment to ILC fate.

Unveiling the gene regulatory landscape in diseases through the identification of DNase I-hypersensitive sites

DNase I-hypersensitive sites (DHSs) serve key roles in the regulation of gene transcription as markers of cis-regulatory elements (CREs). Recent advances in next-generation sequencing have enabled the genome-wide location and annotation of DHSs in a variety of cells. Numerous studies have confirmed that DHSs are involved in several processes in cell fate decision and development. DHSs have also been indicated in cancer and inherited diseases as driver distal regulatory elements. Here, the definition of DHSs is reviewed, in addition to high-throughput methods of DHS identification. Furthermore, the function of DHSs in gene expression is probed. The roles of DHSs in disease occurrence are also reviewed and discussed. Concomitant advances in the identification of essential roles of DHSs will assist in disclosing the underlying molecular mechanisms, supplementing gene transcription and enlarging the molecular basis of DHS-related bioprocesses, phenotypes, distinct traits and diseases.

The national blueprint for pregnancy/birth longitudinal cohorts to study factor VIII immunogenicity: NHLBI State of the Science (SOS) Workshop on factor VIII inhibitors

INTRODUCTION

Patients with haemophilia can develop inhibitors to exogenous coagulation factors. Some patients are tolerant to factor, while those who develop inhibitors do so early in life. Genetics and environmental factors are known to contribute to inhibitor risk. However, it is not yet possible to predict inhibitor formation or treatment responsiveness in individuals. We hypothesize that factors in the antenatal/neonatal period inform inhibitor risk development.

AIM

To consider the design of longitudinal studies beginning in the antenatal/neonatal period and the use of new technologies to better understand haemophilia inhibitors.

METHODS

A working group was formed for the NHLBI State of the Science Workshop: Factor VIII Inhibitors: Generating a National Blueprint for Future Research to solicit input from the US haemophilia community and international collaborators to consider design of pregnancy/birth longitudinal cohorts that leverage -omics, existing phenotypic data, and in silico modelling to study inhibitors.

RESULTS

An antenatal/neonatal longitudinal cohort should begin with enrolment of pregnant genetic carriers of haemophilia and span the at-risk period for inhibitor development in the child. Data and samples from the mother, placenta, neonate and young child can be obtained that are amenable to existing assays, genomics and other -omics studies. Data can inform in silico prediction and mathematical models.

CONCLUSION

A longitudinal study beginning before birth offers the unique opportunity to study factors that influence inhibitor development prior to exposure. Advances in -omics and computational biology can study complex phenotypes in this rare disease. This study could be accomplished through interdisciplinary efforts and patient community engagement.

Deep learning for DNase I hypersensitive sites identification

Background

The DNase I hypersensitive sites (DHSs) are associated with the cis-regulatory DNA elements. An efficient method of identifying DHSs can enhance the understanding on the accessibility of chromatin. Despite a multitude of resources available on line including experimental datasets and computational tools, the complex language of DHSs remains incompletely understood.

Methods

Here, we address this challenge using an approach based on a state-of-the-art machine learning method. We present a novel convolutional neural network (CNN) which combined Inception like networks with a gating mechanism for the response of multiple patterns and longterm association in DNA sequences to predict multi-scale DHSs in Arabidopsis, rice and Homo sapiens.

Results

Our method obtains 0.961 area under curve (AUC) on Arabidopsis, 0.969 AUC on rice and 0.918 AUC on Homo sapiens.

Conclusions

Our method provides an efficient and accurate way to identify multi-scale DHSs sequences by deep learning.

Defining Cell Identity with Single-Cell Omics

Cells are a fundamental unit of life, and the ability to study the phenotypes and behaviors of individual cells is crucial to understanding the workings of complex biological systems. Cell phenotypes (epigenomic, transcriptomic, proteomic, and metabolomic) exhibit dramatic heterogeneity between and within the different cell types and states underlying cellular functional diversity. Cell genotypes can also display heterogeneity throughout an organism, in the form of somatic genetic variation-most notably in the emergence and evolution of tumors. Recent technical advances in single-cell isolation and the development of omics approaches sensitive enough to reveal these aspects of cell identity have enabled a revolution in the study of multicellular systems. In this review, we discuss the technologies available to resolve the genomes, epigenomes, transcriptomes, proteomes, and metabolomes of single cells from a wide variety of living systems.

Chromatin reprogramming in breast cancer

Reprogramming of the chromatin landscape is a critical component to the transcriptional response in breast cancer. Effects of sex hormones such as estrogens and progesterone have been well described to have a critical impact on breast cancer proliferation. However, the complex network of the chromatin landscape, enhancer regions and mode of function of steroid receptors (SRs) and other transcription factors (TFs), is an intricate web of signaling and functional processes that is still largely misunderstood at the mechanistic level. In this review, we describe what is currently known about the dynamic interplay between TFs with chromatin and the reprogramming of enhancer elements. Emphasis has been placed on characterizing the different modes of action of TFs in regulating enhancer activity, specifically, how different SRs target enhancer regions to reprogram chromatin in breast cancer cells. In addition, we discuss current techniques employed to study enhancer function at a genome-wide level. Further, we have noted recent advances in live cell imaging technology. These single-cell approaches enable the coupling of population-based assays with real-time studies to address many unsolved questions about SRs and chromatin dynamics in breast cancer.

Single-Cell (Multi)omics Technologies

Single-cell multiomics technologies typically measure multiple types of molecule from the same individual cell, enabling more profound biological insight than can be inferred by analyzing each molecular layer from separate cells. These single-cell multiomics technologies can reveal cellular heterogeneity at multiple molecular layers within a population of cells and reveal how this variation is coupled or uncoupled between the captured omic layers. The data sets generated by these techniques have the potential to enable a deeper understanding of the key biological processes and mechanisms driving cellular heterogeneity and how they are linked with normal development and aging as well as disease etiology. This review details both established and novel single-cell mono- and multiomics technologies and considers their limitations, applications, and likely future developments.

The Peripheral and Intratumoral Immune Cell Landscape in Cancer Patients: A Proxy for Tumor Biology and a Tool for Outcome Prediction

Functional systemic and local immunity is required for effective anti-tumor responses. In addition to an active engagement with cancer cells and tumor stroma, immune cells can be affected and are often found to be dysregulated in cancer patients. The impact of tumors on local and systemic immunity can be assessed using a variety of approaches ranging from low-dimensional analyses that are performed on large patient cohorts to multi-dimensional assays that are technically and logistically challenging and are therefore confined to a limited sample size. Many of these strategies have been established in recent years leading to exciting findings. Not only were analyses of immune cells in tumor patients able to predict the clinical course of the disease and patients' survival, numerous studies also detected changes in the immune landscape that correlated with responses to novel immunotherapies. This review will provide an overview of established and novel tools for assessing immune cells in tumor patients and will discuss exemplary studies that utilized these techniques to predict patient outcomes.