A multi-omic single-cell landscape of cellular diversification in the developing human cerebral cortex.

The vast neuronal diversity in the human neocortex is vital for high-order brain functions, necessitating elucidation of the regulatory mechanisms underlying such unparalleled diversity. However, recent studies have yet to comprehensively reveal the diversity of neurons and the molecular logic of neocortical origin in humans at single-cell resolution through profiling transcriptomic or epigenomic landscapes, owing to the application of unimodal data alone to depict exceedingly heterogeneous populations of neurons. In this study, we generated a comprehensive compendium of the developing human neocortex by simultaneously profiling gene expression and open chromatin from the same cell. We computationally reconstructed the differentiation trajectories of excitatory projection neurons of cortical origin and inferred the regulatory logic governing lineage bifurcation decisions for neuronal diversification. We demonstrated that neuronal diversity arises from progenitor cell lineage specificity and postmitotic differentiation at distinct stages. Our data paves the way for understanding the primarily coordinated regulatory logic for neuronal diversification in the neocortex.

Altered chromatin topologies caused by balanced chromosomal translocation lead to central iris hypoplasia.

Despite the advent of genomic sequencing, molecular diagnosis remains unsolved in approximately half of patients with Mendelian disorders, largely due to unclarified functions of noncoding regions and the difficulty in identifying complex structural variations. In this study, we map a unique form of central iris hypoplasia in a large family to 6q15-q23.3 and 18p11.31-q12.1 using a genome-wide linkage scan. Long-read sequencing reveals a balanced translocation t(6;18)(q22.31;p11.22) with intergenic breakpoints. By performing Hi-C on induced pluripotent stem cells from a patient, we identify two chromatin topologically associating domains spanning across the breakpoints. These alterations lead the ectopic chromatin interactions between APCDD1 on chromosome 18 and enhancers on chromosome 6, resulting in upregulation of APCDD1. Notably, APCDD1 is specifically localized in the iris of human eyes. Our findings demonstrate that noncoding structural variations can lead to Mendelian diseases by disrupting the 3D genome structure and resulting in altered gene expression.

PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics.

Computational methods have been proposed to leverage spatially resolved transcriptomic data, pinpointing genes with spatial expression patterns and delineating tissue domains. However, existing approaches fall short in uniformly quantifying spatially variable genes (SVGs). Moreover, from a methodological viewpoint, while SVGs are naturally associated with depicting spatial domains, they are technically dissociated in most methods. Here, we present a framework (PROST) for the quantitative recognition of spatial transcriptomic patterns, consisting of (i) quantitatively characterizing spatial variations in gene expression patterns through the PROST Index; and (ii) unsupervised clustering of spatial domains via a self-attention mechanism. We demonstrate that PROST performs superior SVG identification and domain segmentation with various spatial resolutions, from multicellular to cellular levels. Importantly, PROST Index can be applied to prioritize spatial expression variations, facilitating the exploration of biological insights. Together, our study provides a flexible and robust framework for analyzing diverse spatial transcriptomic data.

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To investigate the diversity and community structure of gut microbiome of the invasive species, Achatina fulica, along an urbanization gradient, we collected 30 A. fulica samples from five parks in the urban, suburban, and rural areas of Xiamen City. Using full-length 16S rRNA gene sequencing performed by the third generation PacBio sequencing platform, we analyzed the community characteristics of gut microbiome and soil microbiome in different habitats. We found a significant disparity between the composition of gut microbiome of A. fulica and that of the soil microbiome in their habitats. Furthermore, the gut microbiome of A. fulica were more sensitive to urbanization. The microbial α-diversity indices (Sobs, Chao, Shannon indices) in the soil of A. fulica habitats were consistently higher than those within their guts. Despite the similar ß-diversity indices of microbial communities in urban, suburban, and rural soils, we found a significant discrepancy in gut microbiome composition. Urbanization significantly influenced A. fulica gut microbiome composition. Gut microbiome of A. fulica in urban and suburban regions primarily consisted of Enterobacteriaceae, Xanthomonadaceae, and Mycoplasmataceae, while that in rural areas chiefly composed of Streptococcaceae and Paenibacillaceae. The diversity and abundance of potential human pathogenic bacteria within the gut microbiome of A. fulica significantly increased in urban environments, suggesting that urbanization escalated the risk of A. fulica transmitting potential pathogens.

Single-cell RNA-sequencing identifies various proportions of excitatory and inhibitory neurons in cultured human fetal brain cortical tissues.

Introduction: Cortical neural progenitor cells possess the capacity to differentiate into both excitatory and inhibitory neurons. However, the precise proportions in which these progenitor cells differentiate remain unclear. Methods: Human fetal prefrontal cortical tissues were collected at various fetal stages and cultured in vitro. Bulk and single-cell RNA sequencing techniques were employed to analyze the resulting neuronal cell types, cell proportions, and the expression levels of cell-type marker genes. Results: The culture of fetal prefrontal cortex tissues obtained at gestation weeks 11 and 20 predominantly consisted of excitatory and inhibitory neurons, respectively. This abrupt transition in cell proportions was primarily driven by the differential lineage specificity of neural progenitors in the fetal cortical tissues at distinct stages of fetal brain development. Additionally, it was observed that the transcriptional profiles of cultured fetal cortical tissues were strongly influenced by the presence of FGF2. Discussion: This study presents a novel strategy to obtain excitatory and inhibitory neuronal cells from the culture of fetal cortical tissues. The findings shed light on the mechanisms underlying neurogenesis and provide an approach that might contribute to future research investigating the pathophysiology of various neural disorders.

A DNA tumor virus globally reprograms host 3D genome architecture to achieve immortal growth.

Epstein-Barr virus (EBV) immortalization of resting B lymphocytes (RBLs) to lymphoblastoid cell lines (LCLs) models human DNA tumor virus oncogenesis. RBL and LCL chromatin interaction maps are compared to identify the spatial and temporal genome architectural changes during EBV B cell transformation. EBV induces global genome reorganization where contact domains frequently merge or subdivide during transformation. Repressed B compartments in RBLs frequently switch to active A compartments in LCLs. LCLs gain 40% new contact domain boundaries. Newly gained LCL boundaries have strong CTCF binding at their borders while in RBLs, the same sites have much less CTCF binding. Some LCL CTCF sites also have EBV nuclear antigen (EBNA) leader protein EBNALP binding. LCLs have more local interactions than RBLs at LCL dependency factors and super-enhancer targets. RNA Pol II HiChIP and FISH of RBL and LCL further validate the Hi-C results. EBNA3A inactivation globally alters LCL genome interactions. EBNA3A inactivation reduces CTCF and RAD21 DNA binding. EBNA3C inactivation rewires the looping at the CDKN2A/B and AICDA loci. Disruption of a CTCF site at AICDA locus increases AICDA expression. These data suggest that EBV controls lymphocyte growth by globally reorganizing host genome architecture to facilitate the expression of key oncogenes.

Exhaustion­like dysfunction of T and NKT cells in an X­linked severe combined immunodeficiency patient with maternal engraftment by single­cell analysis.

Maternal engraftment is frequently present in X­linked severe combined immunodeficiency (X­SCID) patients caused by pathogenic mutations in IL2GR. However, the functional status of the engrafted cells remains unclear because of the difficulty in separately evaluating the function of the maternal and autologous cells. The present study reported an X­SCID patient with a de novo c.677C>T (p.R226H) variant in exon 5 of IL2RG, exhibiting recurrent and persistent infections from 3­months­old. After the male patient suffering recurrent pneumonia and acute hematogenous disseminated tuberculosis when 13­months­old, single­cell RNA sequencing was applied to characterize the transcriptome landscape of his bone marrow mononuclear cells (BMMNCs). A novel bioinformatic analysis strategy was designed to discriminate maternal and autologous cells at single­cell resolution. The maternal engrafted cells consisted primarily of T, NKT and NK cells and the patient presented with the coexistence of autologous cells of these cell types. When compared respectively with normal counterparts, both maternal and autologous T and NKT cells increased the transcription of some important cytokines (GZMB, PRF1 and NKG7) against infections, but decreased the expression of a number of key transcription factors (FOS, JUN, TCF7 and LEF1) related to lymphocyte activation, proliferation and differentiation. Notably, the expression of multiple inhibitory factors (LAG3, CTLA4 and HAVCR2) were substantially enhanced in the T and NKT cells of both origins. In conclusion, both maternal and autologous T and NKT cells exhibited exhaustion­like dysfunction in this X­SCID patient suffering recurrent and persistent infections.

The primordial differentiation of tumor-specific memory CD8+ T cells as bona fide responders to PD-1/PD-L1 blockade in draining lymph nodes.

Blocking PD-1/PD-L1 signaling transforms cancer therapy and is assumed to unleash exhausted tumor-reactive CD8+ T cells in the tumor microenvironment (TME). However, recent studies have also indicated that the systemic tumor-reactive CD8+ T cells may respond to PD-1/PD-L1 immunotherapy. These discrepancies highlight the importance of further defining tumor-specific CD8+ T cell responders to PD-1/PD-L1 blockade. Here, using multiple preclinical tumor models, we revealed that a subset of tumor-specific CD8+ cells in the tumor draining lymph nodes (TdLNs) was not functionally exhausted but exhibited canonical memory characteristics. TdLN-derived tumor-specific memory (TTSM) cells established memory-associated epigenetic program early during tumorigenesis. More importantly, TdLN-TTSM cells exhibited superior anti-tumor therapeutic efficacy after adoptive transfer and were characterized as bona fide responders to PD-1/PD-L1 blockade. These findings highlight that TdLN-TTSM cells could be harnessed to potentiate anti-tumor immunotherapy.

Spatial transcriptomics prediction from histology jointly through Transformer and graph neural networks.

The rapid development of spatial transcriptomics allows the measurement of RNA abundance at a high spatial resolution, making it possible to simultaneously profile gene expression, spatial locations of cells or spots, and the corresponding hematoxylin and eosin-stained histology images. It turns promising to predict gene expression from histology images that are relatively easy and cheap to obtain. For this purpose, several methods are devised, but they have not fully captured the internal relations of the 2D vision features or spatial dependency between spots. Here, we developed Hist2ST, a deep learning-based model to predict RNA-seq expression from histology images. Around each sequenced spot, the corresponding histology image is cropped into an image patch and fed into a convolutional module to extract 2D vision features. Meanwhile, the spatial relations with the whole image and neighbored patches are captured through Transformer and graph neural network modules, respectively. These learned features are then used to predict the gene expression by following the zero-inflated negative binomial distribution. To alleviate the impact by the small spatial transcriptomics data, a self-distillation mechanism is employed for efficient learning of the model. By comprehensive tests on cancer and normal datasets, Hist2ST was shown to outperform existing methods in terms of both gene expression prediction and spatial region identification. Further pathway analyses indicated that our model could reserve biological information. Thus, Hist2ST enables generating spatial transcriptomics data from histology images for elucidating molecular signatures of tissues.

The niche-specialist and age-related oral microbial ecosystem: crosstalk with host immune cells in homeostasis.

Although characterization of the baseline oral microbiota has been discussed, the current literature seems insufficient to draw a definitive conclusion on the interactions between the microbes themselves or with the host. This study focuses on the spatial and temporal characteristics of the oral microbial ecosystem in a mouse model and its crosstalk with host immune cells in homeostasis. The V3V4 regions of the 16S rRNA gene of 20 samples from four niches (tongue, buccal mucosa, keratinized gingiva and hard palate) and 10 samples from two life stages (adult and old) were analysed. Flow cytometry (FCM) was used to investigate the resident immune cells. The niche-specialist and age-related communities, characterized based on the microbiota structure, interspecies communications, microbial functions and interactions with immune cells, were addressed. The phylum Firmicutes was the major component in the oral community. The microbial community profiles at the genus level showed that the relative abundances of the genera Bacteroides, Lactobacillus and Porphyromonas were enriched in the gingiva. The abundance of the genera Streptococcus, Faecalibaculum and Veillonella was increased in palatal samples, while the abundance of Neisseria and Bradyrhizobium was enriched in buccal samples. The genera Corynebacterium, Stenotrophomonas, Streptococcus and Fusobacterium were proportionally enriched in old samples, while Prevotella and Lacobacillus were enriched in adult samples. Network analysis showed that the genus Lactobacillus performed as a central node in the buccal module, while in the gingiva module, the central nodes were Nesterenkonia and Hydrogenophilus. FCM showed that the proportion of Th1 cells in the tongue samples (38.18 % [27.03-49.34 %]) (mean [range]) was the highest. The proportion of γδT cells in the buccal mucosa (25.82 % [22.1-29.54 %]) and gingiva (20.42 % [18.31-22.53 %]) samples was higher (P<0.01) than those in the palate (14.18 % [11.69-16.67 %]) and tongue (9.38 % [5.38-13.37 %] samples. The proportion of Th2 (31.3 % [16.16-46.44 %]), Th17 (27.06 % [15.76-38.36 %]) and Treg (29.74 % [15.71-43.77 %]) cells in the old samples was higher than that in the adult samples (P<0.01). Further analysis of the interplays between the microbiomes and immune cells indicated that Th1 cells in the adult group, nd Th2, Th17 and Treg cells in the old group were the main immune factors strongly associated with the oral microbiota. For example, Th2, Th17 and Treg cells showed a significantly positive correlation with age-related microorganisms such as Sphingomonas, Streptococcus and Acinetobacter, while Th1 cells showed a negative correlation. Another positive correlation occurred between Th1 cells and several commensal microbiomes such as Lactobacillus, Jeotgalicoccus and Sporosarcina. Th2, Th17 and Treg cells showed the opposite trend. Together, our findings identify the niche-specialist and age-related characteristics of the oral microbial ecosystem and the potential associations between the microbiomes and the mucosal immune cells, providing critical insights into mucosal microbiology.

Genome-Wide Histone H3K27 Acetylation Profiling Identified Genes Correlated With Prognosis in Papillary Thyroid Carcinoma.

Thyroid carcinoma (TC) is the most common endocrine malignancy, and papillary TC (PTC) is the most frequent subtype of TC, accounting for 85-90% of all the cases. Aberrant histone acetylation contributes to carcinogenesis by inducing the dysregulation of certain cancer-related genes. However, the histone acetylation landscape in PTC remains elusive. Here, we interrogated the epigenomes of PTC and benign thyroid nodule (BTN) tissues by applying H3K27ac chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) along with RNA-sequencing. By comparing the epigenomic features between PTC and BTN, we detected changes in H3K27ac levels at active regulatory regions, identified PTC-specific super-enhancer-associated genes involving immune-response and cancer-related pathways, and uncovered several genes that associated with disease-free survival of PTC. In summary, our data provided a genome-wide landscape of histone modification in PTC and demonstrated the role of enhancers in transcriptional regulations associated with prognosis of PTC.

Histone chaperone CAF-1 promotes HIV-1 latency by leading the formation of phase-separated suppressive nuclear bodies.

HIV-1 latency is a major obstacle to achieving a functional cure for AIDS. Reactivation of HIV-1-infected cells followed by their elimination via immune surveillance is one proposed strategy for eradicating the viral reservoir. However, current latency-reversing agents (LRAs) show high toxicity and low efficiency, and new targets are needed to develop more promising LRAs. Here, we found that the histone chaperone CAF-1 (chromatin assembly factor 1) is enriched on the HIV-1 long terminal repeat (LTR) and forms nuclear bodies with liquid-liquid phase separation (LLPS) properties. CAF-1 recruits epigenetic modifiers and histone chaperones to the nuclear bodies to establish and maintain HIV-1 latency in different latency models and primary CD4+ T cells. Three disordered regions of the CHAF1A subunit are important for phase-separated CAF-1 nuclear body formation and play a key role in maintaining HIV-1 latency. Disruption of phase-separated CAF-1 bodies could be a potential strategy to reactivate latent HIV-1.

ChIA-PIPE: A fully automated pipeline for comprehensive ChIA-PET data analysis and visualization.

ChIA-PET (chromatin interaction analysis with paired-end tags) enables genome-wide discovery of chromatin interactions involving specific protein factors, with base pair resolution. Interpretation of ChIA-PET data requires a robust analytic pipeline. Here, we introduce ChIA-PIPE, a fully automated pipeline for ChIA-PET data processing, quality assessment, visualization, and analysis. ChIA-PIPE performs linker filtering, read mapping, peak calling, and loop calling and automates quality control assessment for each dataset. To enable visualization, ChIA-PIPE generates input files for two-dimensional contact map viewing with Juicebox and HiGlass and provides a new dockerized visualization tool for high-resolution, browser-based exploration of peaks and loops. To enable structural interpretation, ChIA-PIPE calls chromatin contact domains, resolves allele-specific peaks and loops, and annotates enhancer-promoter loops. ChIA-PIPE also supports the analysis of other related chromatin-mapping data types.

3D-GNOME 2.0: a three-dimensional genome modeling engine for predicting structural variation-driven alterations of chromatin spatial structure in the human genome.

Structural variants (SVs) that alter DNA sequence emerge as a driving force involved in the reorganisation of DNA spatial folding, thus affecting gene transcription. In this work, we describe an improved version of our integrated web service for structural modeling of three-dimensional genome (3D-GNOME), which now incorporates all types of SVs to model changes to the reference 3D conformation of chromatin. In 3D-GNOME 2.0, the default reference 3D genome structure is generated using ChIA-PET data from the GM12878 cell line and SVs data are sourced from the population-scale catalogue of SVs identified by the 1000 Genomes Consortium. However, users may also submit their own structural data to set a customized reference genome structure, and/or a custom input list of SVs. 3D-GNOME 2.0 provides novel tools to inspect, visualize and compare 3D models for regions that differ in terms of their linear genomic sequence. Contact diagrams are displayed to compare the reference 3D structure with the one altered by SVs. In our opinion, 3D-GNOME 2.0 is a unique online tool for modeling and analyzing conformational changes to the human genome induced by SVs across populations. It can be freely accessed at https://3dgnome.cent.uw.edu.pl/.

Chromatin topology reorganization and transcription repression by PML-RARα in acute promyeloid leukemia.

BACKGROUND: Acute promyeloid leukemia (APL) is characterized by the oncogenic fusion protein PML-RARα, a major etiological agent in APL. However, the molecular mechanisms underlying the role of PML-RARα in leukemogenesis remain largely unknown. RESULTS: Using an inducible system, we comprehensively analyze the 3D genome organization in myeloid cells and its reorganization after PML-RARα induction and perform additional analyses in patient-derived APL cells with native PML-RARα. We discover that PML-RARα mediates extensive chromatin interactions genome-wide. Globally, it redefines the chromatin topology of the myeloid genome toward a more condensed configuration in APL cells; locally, it intrudes RNAPII-associated interaction domains, interrupts myeloid-specific transcription factors binding at enhancers and super-enhancers, and leads to transcriptional repression of genes critical for myeloid differentiation and maturation. CONCLUSIONS: Our results not only provide novel topological insights for the roles of PML-RARα in transforming myeloid cells into leukemia cells, but further uncover a topological framework of a molecular mechanism for oncogenic fusion proteins in cancers.

Methods for comparative ChIA-PET and Hi-C data analysis.

The three-dimensional architecture of chromatin in the nucleus is important for genome regulation and function. Advanced high-throughput sequencing-based methods have been developed for capturing chromatin interactions (Hi-C, genome-wide chromosome conformation capture) or enriching for those involving a specific protein (ChIA-PET, chromatin interaction analysis with paired-end tag sequencing). There is widespread interest in utilizing and interpreting ChIA-PET and Hi-C. We review methods for comparative ChIA-PET and Hi-C data analysis and visualization. The topics reviewed include: downloading ChIA-PET and Hi-C data from the ENCODE and 4DN portals; processing ChIA-PET data using ChIA-PIPE; processing Hi-C data using Juicer or distiller and cooler; viewing 2D contact maps using Juicebox or Higlass; viewing peaks, loops, and domains using BASIC Browser; annotating convergent and tandem CTCF loops.

Correction to: Spatial chromatin architecture alteration by structural variations in human genomes at the population scale.

Following publication of the original article [1], it was noticed that the incorrect Fig. 2 and Fig. 3. were processed during production. It was also noticed that Fig. 4a was processed with a superfluous "1e7" symbol in the upper right corner.

Spatial chromatin architecture alteration by structural variations in human genomes at the population scale.

BACKGROUND: The number of reported examples of chromatin architecture alterations involved in the regulation of gene transcription and in disease is increasing. However, no genome-wide testing has been performed to assess the abundance of these events and their importance relative to other factors affecting genome regulation. This is particularly interesting given that a vast majority of genetic variations identified in association studies are located outside coding sequences. This study attempts to address this lack by analyzing the impact on chromatin spatial organization of genetic variants identified in individuals from 26 human populations and in genome-wide association studies. RESULTS: We assess the tendency of structural variants to accumulate in spatially interacting genomic segments and design an algorithm to model chromatin conformational changes caused by structural variations. We show that differential gene transcription is closely linked to the variation in chromatin interaction networks mediated by RNA polymerase II. We also demonstrate that CTCF-mediated interactions are well conserved across populations, but enriched with disease-associated SNPs. Moreover, we find boundaries of topological domains as relatively frequent targets of duplications, which suggest that these duplications can be an important evolutionary mechanism of genome spatial organization. CONCLUSIONS: This study assesses the critical impact of genetic variants on the higher-order organization of chromatin folding and provides insight into the mechanisms regulating gene transcription at the population scale, of which local arrangement of chromatin loops seems to be the most significant. It provides the first insight into the variability of the human 3D genome at the population scale.

The Tandem Duplicator Phenotype Is a Prevalent Genome-Wide Cancer Configuration Driven by Distinct Gene Mutations.

The tandem duplicator phenotype (TDP) is a genome-wide instability configuration primarily observed in breast, ovarian, and endometrial carcinomas. Here, we stratify TDP tumors by classifying their tandem duplications (TDs) into three span intervals, with modal values of 11 kb, 231 kb, and 1.7 Mb, respectively. TDPs with ∼11 kb TDs feature loss of TP53 and BRCA1. TDPs with ∼231 kb and ∼1.7 Mb TDs associate with CCNE1 pathway activation and CDK12 disruptions, respectively. We demonstrate that p53 and BRCA1 conjoint abrogation drives TDP induction by generating short-span TDP mammary tumors in genetically modified mice lacking them. Lastly, we show how TDs in TDP tumors disrupt heterogeneous combinations of tumor suppressors and chromatin topologically associating domains while duplicating oncogenes and super-enhancers.