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The quality and application of super-resolution fluorescence imaging greatly lie in the dyes’ properties, including photostability, brightness, and Stokes shift. Here we report a synergistic strategy to simultaneously improve such properties of regular fluorophores. Introduction of quinoxaline motif with fine-tuned electron density to conventional rhodamines generates new dyes with vibration structure and inhibited twisted-intramolecular-charge-transfer (TICT) formation synchronously, thus increasing the brightness and photostability while enlarging Stokes shift. The new fluorophore YL578 exhibits around twofold greater brightness and Stokes shift than its parental fluorophore, Rhodamine B. Importantly, in Stimulated Emission Depletion (STED) microscopy, YL578 derived probe possesses a superior photostability and thus renders threefold more frames than carbopyronine based probes (CPY-Halo and 580CP-Halo), known as photostable fluorophores for STED imaging. Furthermore, the strategy is well generalized to offer a new class of bright and photostable fluorescent probes with long Stokes shift (up to 136 nm) for bioimaging and biosensing. Super-resolution microscopy is a powerful tool for cellular studies but requires bright and stable fluorescent probes. Here, the authors report on a strategy to introduce quinoxaline motifs to conventional probes to make them brighter, more photostable, larger Stokes shift, and demonstrate the probes for biosensing applications.

Cell type-specific gene expression patterns and dynamics during development or in disease are controlled by cis-regulatory elements (CREs), such as promoters and enhancers. Distinct classes of CREs can be characterized by their epigenomic features, including DNA methylation, chromatin accessibility, combinations of histone modifications and conformation of local chromatin. Tremendous progress has been made in cataloguing CREs in the human genome using bulk transcriptomic and epigenomic methods. However, single-cell epigenomic and multi-omic technologies have the potential to provide deeper insight into cell type-specific gene regulatory programmes as well as into how they change during development, in response to environmental cues and through disease pathogenesis. Here, we highlight recent advances in single-cell epigenomic methods and analytical tools and discuss their readiness for human tissue profiling.In this Review, Preissl, Gaulton and Ren discuss single-cell epigenomic methods and data analysis tools, their readiness for profiling cis-regulatory elements in human tissues and the insight they can provide into dynamic, context-specific gene regulation.

J-aggregation, an effective strategy to extend wavelength, has been considered as a promising method for constructing NIR-II fluorophores. However, due to weak intermolecular interactions, conventional J-aggregates are easily decomposed into monomers in the biological environment. Although adding external carriers could help conventional J-aggregates stabilize, such methods still suffer from high-concentration dependence and are unsuitable for activatable probes design. Besides, these carriers-assisted nanoparticles are risky of disassembly in lipophilic environment. Herein, by fusing the precipitated dye (HPQ) which has orderly self-assembly structure, onto simple hemi-cyanine conjugated system, we construct a series of activatable, high-stability NIR-II-J-aggregates which overcome conventional J-aggregates carrier’s dependence and could in situ self-assembly in vivo. Further, we employ the NIR-II-J-aggregates probe HPQ-Zzh-B to achieve the long-term in situ imaging of tumor and precise tumor resection by NIR-II imaging navigation for reducing lung metastasis. We believe this strategy will advance the development of controllable NIR-II-J-aggregates and precise bioimaging in vivo. J-aggregation, is an effective strategy to extend the wavelength of organic NIR-II fluorescence dyes but weak intermolecular interactions often lead to decomposition of the aggregates in biological environment. Here, the authors demonstrate a series of activatable quinazoline derivatives which can self-assemble in vivo into highly stable NIR-IIJ-aggregates.

Genome-wide profiling of histone modifications can reveal not only the location and activity state of regulatory elements, but also the regulatory mechanisms involved in cell-type-specific gene expression during development and disease pathology. Conventional assays to profile histone modifications in bulk tissues lack single-cell resolution. Here we describe an ultra-high-throughput method, Paired-Tag, for joint profiling of histone modifications and transcriptome in single cells to produce cell-type-resolved maps of chromatin state and transcriptome in complex tissues. We used this method to profile five histone modifications jointly with transcriptome in the adult mouse frontal cortex and hippocampus. Integrative analysis of the resulting maps identified distinct groups of genes subject to divergent epigenetic regulatory mechanisms. Our single-cell multiomics approach enables comprehensive analysis of chromatin state and gene regulation in complex tissues and characterization of gene regulatory programs in the constituent cell types.Paired-Tag offers a multiomics assay for joint profiling of histone modifications and gene expression in single nuclei, and is applied to mouse frontal cortex and hippocampus for measuring cell-type-resolved chromatin state and transcriptome.

Genome-wide association studies (GWAS) have linked hundreds of thousands of sequence variants in the human genome to common traits and diseases. However, translating this knowledge into a mechanistic understanding of disease-relevant biology remains challenging, largely because such variants are predominantly in non-protein-coding sequences that still lack functional annotation at cell-type resolution. Recent advances in single-cell epigenomics assays have enabled the generation of cell type-, subtype- and state-resolved maps of the epigenome in heterogeneous human tissues. These maps have facilitated cell type-specific annotation of candidate cis-regulatory elements and their gene targets in the human genome, enhancing our ability to interpret the genetic basis of common traits and diseases.In this Review, Gaulton et al. discuss how single-cell epigenomic methods generate cell type-, subtype- and state-resolved maps of candidate cis-regulatory elements in heterogeneous human tissues that can help to interpret the genetic basis of common traits and diseases.

Constitutive promoters are used routinely to drive ectopic gene expression. Here, we carried out a systematic comparison of eight commonly used constitutive promoters (SV40, CMV, UBC, EF1A, PGK and CAGG for mammalian systems, and COPIA and ACT5C for Drosophila systems). We also included in the comparison the TRE promoter, which can be activated by the rtTA transcriptional activator in a doxycycline-inducible manner. To make our findings representative, we conducted the comparison in a variety of cell types derived from several species. We found that these promoters vary considerably from one another in their strength. Most promoters have fairly consistent strengths across different cell types, but the CMV promoter can vary considerably from cell type to cell type. At maximal induction, the TRE promoter is comparable to a strong constitutive promoter. These results should facilitate more rational choices of promoters in ectopic gene expression studies.

We report a molecular assay, Methyl-HiC, that can simultaneously capture the chromosome conformation and DNA methylome in a cell. Methyl-HiC reveals coordinated DNA methylation status between distal genomic segments that are in spatial proximity in the nucleus, and delineates heterogeneity of both the chromatin architecture and DNA methylome in a mixed population. It enables simultaneous characterization of cell-type-specific chromatin organization and epigenome in complex tissues.

The Warburg effect, which originally described increased production of lactate in cancer, is associated with diverse cellular processes such as angiogenesis, hypoxia, polarization of macrophages and activation of T cells. This phenomenon is intimately linked to several diseases including neoplasia, sepsis and autoimmune diseases 1 , 2 . Lactate, which is converted from pyruvate in tumour cells, is widely known as an energy source and metabolic by-product. However, its non-metabolic functions in physiology and disease remain unknown. Here we show that lactate-derived lactylation of histone lysine residues serves as an epigenetic modification that directly stimulates gene transcription from chromatin. We identify 28 lactylation sites on core histones in human and mouse cells. Hypoxia and bacterial challenges induce the production of lactate by glycolysis, and this acts as a precursor that stimulates histone lactylation. Using M1 macrophages that have been exposed to bacteria as a model system, we show that histone lactylation has different temporal dynamics from acetylation. In the late phase of M1 macrophage polarization, increased histone lactylation induces homeostatic genes that are involved in wound healing, including Arg1 . Collectively, our results suggest that an endogenous ‘lactate clock’ in bacterially challenged M1 macrophages turns on gene expression to promote homeostasis. Histone lactylation thus represents an opportunity to improve our understanding of the functions of lactate and its role in diverse pathophysiological conditions, including infection and cancer. The lactylation of lysine residues on histones in mammalian cells is stimulated by hypoxia and bacterial challenges, and increased histone lactylation induces genes involved in wound healing.

Key Points The integration of transcriptomic, genetic, genomic, epigenetic and network interaction data is crucial for a unified view of biological processes and to advance our understanding of human disease and biology. The genome sequence is a scaffold on which known annotations and experimental data can be assembled. It is useful to view these different levels of information together on a genome browser. Data integration can be used to identify functional elements in the genome, explore the function of genetic variation and improve understanding of gene regulation. Given large multidimensional data sets with minimal parameters, unsupervised learning techniques can be used to identify frequently occurring patterns in the data and therefore to suggest hypotheses. Carefully designed computational experiments for supervised integration can be used to test hypotheses on a global scale. Other supervised approaches, such as Bayesian networks, can also generate hypotheses of function. There are a range of online and stand-alone tools available to bench scientists for tackling large-scale data sets. Several analytical hurdles remain, which are being addressed by bioinformaticians. A huge range of genome-scale data sets — including genomic, epigenomic and transcriptomic information — are now available, and it is widely acknowledged that combining several data sets can provide important biological insights. However, there are practical, conceptual and computational challenges to data integration. Integrating results from diverse experiments is an essential process in our effort to understand the logic of complex systems, such as development, homeostasis and responses to the environment. With the advent of high-throughput methods — including genome-wide association (GWA) studies, chromatin immunoprecipitation followed by sequencing (ChIP–seq) and RNA sequencing (RNA–seq) — acquisition of genome-scale data has never been easier. Epigenomics, transcriptomics, proteomics and genomics each provide an insightful, and yet one-dimensional, view of genome function; integrative analysis promises a unified, global view. However, the large amount of information and diverse technology platforms pose multiple challenges for data access and processing. This Review discusses emerging issues and strategies related to data integration in the era of next-generation genomics.

Simultaneous profiling of transcriptome and chromatin accessibility within single cells is a powerful approach to dissect gene regulatory programs in complex tissues. However, current tools are limited by modest throughput. We now describe an ultra high-throughput method, Paired-seq, for parallel analysis of transcriptome and accessible chromatin in millions of single cells. We demonstrate the utility of Paired-seq for analyzing the dynamic and cell-type-specific gene regulatory programs in complex tissues by applying it to mouse adult cerebral cortex and fetal forebrain. The joint profiles of a large number of single cells allowed us to deconvolute the transcriptome and open chromatin landscapes in the major cell types within these brain tissues, infer putative target genes of candidate enhancers, and reconstruct the trajectory of cellular lineages within the developing forebrain.