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Kouno, T.

Publications and source records attributed to Kouno, T..

17 recordsLinked to original sources

The human RNA-DNA interactome is cell type-specific and dynamic

More than twenty years ago, the FANTOM consortium uncovered that mammalian genomes are pervasively transcribed, revealing multitudes of RNAs with unknown functions. A subset of these transcripts has since then been linked to transcriptional control and to chromatin organization via their ability to interact with DNA, suggesting that chromatin-associated RNAs could be key players in genome regulation. Although recent technological advances now enable the mapping of genome-wide RNA-DNA contacts, a lack of analyses integrating these methods with other genomic features and across multiple cellular contexts hinders our comprehensive understanding of the principles underlying RNA-DNA interactions and of their biological importance. As part of the FANTOM6 project, we thus generated RNA-DNA interaction maps in 16 different human cell types, then combined these contacts with multiple layers of other genomic data to investigate how patterns of interaction between RNA and DNA relate to chromatin organization and function. We show that the RNA-DNA interactome is highly dynamic yet reproducibly organized in cell-type specific networks, constituted of a great diversity of interactions that vary in function of their distance, the nature of their sources and the chromatin state of their targets. In particular, we detected numerous regulatory elements that exhibit marked changes in activity when differentially bound by transcripts, implying that thousands of RNA-DNA interactions can play a mechanistic role in gene expression. This regulatory function correlates with RNA-protein interactions and significantly associates with cell type-relevant and disorder-related traits. In addition to providing essential resources for future research in RNA-mediated chromatin regulation, cellular biology and human diseases, our study thus establishes the RNA-DNA interactome as a new genome regulatory layer that defines and maintains cellular identity and behavior.

genomics↗

Chromatin organizer ASCL1 governs gene programs in thymic epithelial cells, defining immunological self

Immunological self-tolerance depends on medullary thymic epithelial cells (mTECs), which express a broad repertoire of self-antigens to support negative selection of autoreactive T cells and the development of regulatory T cells. Although the autoimmune regulator AIRE is essential for this process, additional factors are required to establish the full mTEC gene expression program. Because thymoma is frequently associated with autoimmunity, implicating defective thymic tolerance, we performed single-cell RNA sequencing of TECs from thymoma patients and identified the transcription factor ASCL1 as selectively downregulated in tumor mTECs. Deletion of Ascl1 in mouse TECs resulted in spontaneous autoimmunity without inducing thymic tumorigenesis. Transcriptomic and chromatin accessibility analyses revealed that ASCL1 influences mTEC gene expression programs and is associated with corresponding changes in chromatin accessibility. Genetic interaction analyses further suggested that ASCL1 activity in immature mTECs modulates the AIRE dependency of gene expression in mature mTECs. Together, these findings identify ASCL1 as a key regulator of mTEC function and central tolerance, providing insight into mechanisms that safeguard immune homeostasis and whose disruption may contribute to autoimmune disease.

immunology↗

A genome-wide, machine learning-guided exploration of the cis-regulatory code involved in neuronal differentiation

Gene expression is controlled by proximal and distal cis-regulatory elements (CREs), containing DNA motifs bound by various transcription factors (TFs). Other sequence features, such as specific k-mers or low complexity regions, have also been implicated [1-3]. However, in a dynamic biological process such as cell differentiation, we lack an understanding of how the transcriptional activity of CREs progressively change and what sequence features underlie these transitions, which may reflect common and/or coordinated regulatory processes. Here, we use single-cell ATAC-seq and RNA-seq to follow, at a genome scale, CREs along differentiation of induced pluripotent stem cells into cortical neurons and develop a method to automatically identify the diversity of CRE profiles and their underlying sequence features. We propose a machine-learning guided clustering algorithm, STOIC (Statistical learning TO Inform Clustering), that jointly learns an unsupervised clustering of the CREs in the space of the activity profiles and a supervised predictor associated with each cluster in the DNA-sequence space. STOIC is specifically designed to provide readily interpretable results. We show that the method identifies CRE profiles associated with highly predictive sequence features and outperforms methods solely concerned with co-activity clustering on this task. Orthogonal data collected in the same settings link the inferred CRE clusters to specific enhancer or promoter signatures. Furthermore, we show that the DNA features unveiled by STOIC reflect biologically relevant regulators and offer a valuable basis to dissect elements of the cisregulatory grammar. Finally, we demonstrate the general applicability of STOIC by analyzing five bulk CAGE datasets of human cells responding to various treatments.

bioinformatics↗

CFC-seq: identification of full-length capped RNAs unveil enhancer-derived transcription

Long-read sequencing has transformed transcriptome profiling, yet capturing full-length, non-polyadenylated transcripts like enhancer RNAs (eRNAs) remains challenging. Here, we introduce CFC-seq, combining cap-trapping and in vitro poly(A)-tailing to sequence poly(A) and non-poly(A) RNAs with precise transcription start site. Paired with our assembler, SALA, we identified 39,425 novel transcriptional units, including [~]24,000 eRNAs. Our data reveal a distinct genomic code governing eRNA fate dictated by core promoter architecture. CpG-island enhancers show high chromatin connectivity but yield short, exosome-sensitive RNAs. Conversely, TATA-box enhancers systematically co-opt LTR retrotransposons to inherit structural motifs that produce long, stable, and spliced RNAs. Mechanistically, the pioneer factor NF-Y activates these viral elements to license transcription, balanced by TEAD4 activity across a dual-gear regulatory axis. Finally, non-poly(A) eRNAs terminate via exosome-associated processing at structural-depleted cleavage zones. This comprehensive annotation links enhancer sequence architecture to RNA fate, providing a new transformative framework for decoding the functional human genome. HighlightsO_LIExpanded genomic architecture: CFC-seq unmasks a hidden layer of human transcriptome, identifying 39,425 novel transcriptional units with high-confidence TSS support, including [~]24,000 eRNAs. C_LIO_LITSS-first assembler: We introduce SALA, a specialized long-read assembler that prioritizes authentic 5 Cap-trapped ends to accurately reconstruct the TSS-resolved transcript models. C_LIO_LIGenomic code of eRNA fate: CGI enhancers drive short and exosome-sensitive transcripts associated with repressive H3K27me3 mark and high chromatin connectivity. TATA-box enhancers produce cell-type-specific, long, stable, and frequently spliced eRNAs. C_LIO_LIEvolutionary co-option of retrotransposons: A major fraction of TATA-box eRNAs originate from LTR retrotransposons, providing a direct mechanism for integration of viral elements into the human regulatory landscape. C_LIO_LIA dual-gear pioneering axis: The pioneer factor NF-Y activates unprimed LTR-TATA enhancers to license transcription independent of histone acetylation cascades, operating in parallel with TEAD4-mediated activation. C_LIO_LIStructural determinants of eRNA termination: Non-poly(A) eRNA TES features a secondary structure depletion zone that coordinates pol II termination and calibrates exosome-mediated turnover. C_LI

genomics↗

Single-cell analysis of human diversity in circulating immune cells

Lack of diversity and proportionate representation in genomics datasets and databases contributes to inequity in healthcare outcomes globally1,2. The relationships of human diversity with biological and biomedical phenotypes are pervasive3, yet remain understudied, particularly in a single-cell genomics context. Here we present the Asian Immune Diversity Atlas (AIDA), a multi-national single-cell RNA-sequencing (scRNA-seq) healthy reference atlas of human immune cells. AIDA comprises 1,265,624 circulating immune cells from 619 healthy donors and 6 controls, spanning 7 population groups across 5 countries. AIDA is one of the largest healthy blood datasets in terms of number of cells, and also the most diverse in terms of number of population groups. Though population groups are frequently compared at the continental level, we identified a pervasive impact of sub-continental diversity on cellular and molecular properties of immune cells. These included cell populations and genes implicated in disease risk and pathogenesis as well as those relevant for diagnostics. We detected single-cell signatures of human diversity not apparent at the level of cell types, as well as modulation of the effects of age and sex by self-reported ethnicity. We discovered functional genetic variants influencing cell type-specific gene expression, including context-dependent effects, which were under-represented in analyses of non-Asian population groups, and which helped contextualise disease-associated variants. We validated our findings using multiple independent datasets and cohorts. AIDA provides fundamental insights into the relationships of human diversity with immune cell phenotypes, enables analyses of multi-ancestry disease datasets, and facilitates the development of precision medicine efforts in Asia and beyond.

genomics↗

A single-cell atlas of transcribed cis-regulatory elements in the human genome

Transcribed cis-regulatory elements (tCREs), such as promoters and enhancers, are fundamental to modulate gene expression and define cell identity. The detailed mapping of tCREs at single-cell resolution is essential for understanding the regulatory mechanisms that govern cellular functions. Prior tCRE catalogs, limited by bulk analysis, have often overlooked cellular heterogeneity. We have constructed a tCRE atlas using single-cell 5-RNA-seq, capturing over 340,000 single-cells from 23 human tissues and annotating more than 175,000 tCREs, substantially enhancing the scope and granularity of existing cis-regulatory element annotations in the human genome. This atlas unveils patterns of gene regulation, revealing connections between broadly expressed promoters and cell type-specific distal tCREs. Assessing trait heritability at single-cell resolution with a novel tCRE module-based approach, we uncovered the nuanced trait-gene regulatory relationships across a continuum of cell populations, offering insights beyond traditional gene-level and bulk-sample analyses. Our study bridges the gap between gene regulation and trait heritability, underscoring the potential of single-cell analysis to elucidate the genetic foundations of complex traits. These insights set the stage for future research to investigate the impact of genetic variations on diseases at the individual level, advancing the understanding of cellular and molecular basis of trait heritability.

genomics↗

CiDRE+ M2c macrophages hijacked by SARS-CoV-2 cause COVID-19 severity

Infection of the lungs with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via the angiotensin I converting enzyme 2 (ACE2) receptor induces a type of systemic inflammation known as a cytokine storm. However, the precise mechanisms involved in severe coronavirus disease 2019 (COVID-19) pneumonia are unknown. Here, we show that interleukin-10 (IL-10) changed normal alveolar macrophages into ACE2-expressing M2c-type macrophages that functioned as spreading vectors for SARS-CoV-2 infection. The depletion of alveolar macrophages and blockade of IL-10 attenuated SARS-CoV-2 pathogenicity. Furthermore, genome-wide association and quantitative trait locus analyses identified novel mRNA transcripts in human patients, COVID-19 infectivity enhancing dual receptor (CiDRE), which has unique synergistic effects within the IL-10-ACE2 system in M2c-type macrophages. Our results demonstrate that alveolar macrophages stimulated by IL-10 are key players in severe COVID-19. Collectively, CiDRE expression levels are potential risk factors that predict COVID-19 severity, and CiDRE inhibitors might be useful as COVID-19 therapies. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=195 HEIGHT=200 SRC="FIGDIR/small/510331v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1e96c82org.highwire.dtl.DTLVardef@1d2dc32org.highwire.dtl.DTLVardef@7689d1org.highwire.dtl.DTLVardef@520d17_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

The high-throughput perturbation of long non-coding RNA reveals functional features in stem cells and across cell-types

Within the scope of FANTOM6 consortium, we perform a large-scale knockdown of 200 long non-coding RNAs (lncRNAs) in human induced pluripotent stem (iPS) cells, and systematically characterize their roles in self-renewal and pluripotency. We find 36 lncRNAs (18%) exhibiting cell growth inhibition From the knockdown of 123 lncRNAs with transcriptome profiling, 36 lncRNAs (29.3%) show molecular phenotypes. Integrating the molecular phenotypes with chromatin-interaction assays further reveals cis- and trans-interacting partners as potential primary targets. Additionally, cell type enrichment analysis identifies lncRNAs associated with pluripotency while the knockdown of LINC02595, CATG00000090305.1 and RP11-148B6.2 modulates colony formation of iPS cells. We compare our results with previously published fibroblasts phenotyping data and find that 2.9% of the lncRNAs exhibit consistent cell growth phenotype, whereas we observe 58.3% agreement in molecular phenotypes. This highlights molecular phenotyping is more comprehensive in revealing affected pathways.

genomics↗

Autism in a dish: ES cell models of autism with copy number variations reveal cell-type-specific vulnerability

Human genetics has identified numerous single nucleotide variations (SNVs) and copy number variations (CNVs) associated with autism spectrum disorders (ASD) and other psychiatric disorders. However, the lack of standardized biological resources impedes understanding of the common pathophysiology of ASD. Here, using next-generation chromosome engineering based on the CRISPR/Cas9 system, we established a biological resource including 65 genetically modified mouse embryonic stem cell (mESC) lines as genetic models of human SNVs and CNVs. To illustrate cell-type and CNV specific molecular features of ASD, we performed single-cell RNA sequencing (37,397 cells in total), morphological, and physiological analyses using 12 representative cell lines with CNVs highly associated with ASD. These results uncover gene ontology (GO) terms, canonical pathways, upstream regulators, and related neuropsychiatric disorders in a cell-type and CNV specific manner.

neuroscience↗

Microglia integration into human midbrain organoids leads to increased neuronal maturation and functionality.

The human brain is a complex, three-dimensional structure. To better recapitulate brain complexity, recent efforts have focused on the development of human specific midbrain organoids. Human iPSC-derived midbrain organoids consist of differentiated and functional neurons, which contain active synapses, as well as astrocytes and oligodendrocytes. However, the absence of microglia, with their ability to remodel neuronal networks and phagocytose apoptotic cells and debris, represents a major disadvantage for the current midbrain organoid systems. Additionally, neuro-inflammation related disease modeling is not possible in the absence of microglia. So far, no studies about the effects of human iPSC-derived microglia on midbrain organoid neural cells have been published. Here we describe an approach to derive microglia from human iPSCs and integrate them into iPSC-derived midbrain organoids. Using single nuclear RNA Sequencing, we provide a detailed characterization of microglia in midbrain organoids as well as the influence of their presence on the other cells of the organoids. Furthermore, we describe the effects that microglia have on cell death and oxidative stress- related gene expression. Finally, we show that microglia in midbrain organoids affect synaptic remodeling and increase neuronal excitability. Altogether, we show a more suitable system to further investigate brain development, as well as neurodegenerative diseases and neuro- inflammation. Main Points- Macrophage precursors can be efficiently co-cultured with midbrain organoids, they integrate into the tissue and differentiate into microglia in 3D. - Organoids containing microglia have a smaller size and show a down-regulation of oxidative stress-related genes. - Organoids co-cultured with microglia show differences in genes related to synaptic remodeling and action potential, as well as a more spontaneous action potential firing.

neuroscience↗

Profiling of transcribed cis-regulatory elements in single cells

Profiling of cis-regulatory elements (CREs, mostly promoters and enhancers) in single cells allows the interrogation of the cell-type and cell-state-specific contexts of gene regulation and genetic predisposition to diseases. Here we demonstrate single-cell RNA-5'end-sequencing (sc-end5-seq) methods can detect transcribed CREs (tCREs), enabling simultaneous quantification of gene expression and enhancer activities in a single assay at no extra cost. We showed enhancer RNAs can be detected using sc-end5-seq methods with either random or oligo(dT) priming. To analyze tCREs in single cells, we developed SCAFE (Single Cell Analysis of Five-prime Ends) to identify genuine tCREs and analyze their activities (https://github.com/chung-lab/scafe). As compared to accessible CRE (aCRE, based on chromatin accessibility), tCREs are more accurate in predicting CRE interactions by co-activity, more sensitive in detecting shifts in alternative promoter usage and more enriched in diseases heritability. Our results highlight additional dimensions within sc-end5-seq data which can be used for interrogating gene regulation and disease heritability.

genomics↗

LESR2 is a lymphatic endothelial-specific lncRNA that governs cell proliferation and migration through KLF4 and SEMA3C

Recent studies have revealed the importance of long noncoding RNAs (lncRNAs) as tissue-specific regulators of gene expression. There is ample evidence that distinct types of vasculature undergo tight transcriptional control to preserve their structure, identity, and functions. We determined, for the first time, the global lineage-specific lncRNAome of human dermal blood and lymphatic endothelial cells (BECs and LECs), combining RNA-Seq and CAGE-Seq. A subsequent genome-wide antisense oligonucleotide-knockdown screen of a robust set of BEC- and LEC-specific lncRNAs identified LETR1 as a critical gatekeeper of the global LEC transcriptome. Deep RNA-DNA, RNA-protein, and phenotype rescue analyses revealed that LETR1 acts as a nuclear trans-acting lncRNA modulating, via key epigenetic factors, the expression of essential target genes, including KLF4 and SEMA3C, governing the growth and migratory ability of LECs. Together, our study provides new evidence supporting the intriguing concept that every cell type expresses precise lncRNA signatures to control lineage-specific regulatory programs.

genomics↗

Brainstem organoids from human pluripotent stem cells contain neural crest population

The brainstem controls heartbeat, blood pressure and respiration, which are life-sustaining functions, therefore, disorders of the brainstem can be lethal. Brain organoids derived from human pluripotent stem cells recapitulate the course of human brain development and are expected to be useful for medical research on central nervous system disorders. However, existing organoid models have limitations, hampering the elucidation of diseases affecting specific components of the brain. Here, we developed a method to generate human brainstem organoids (hBSOs), containing neural crest stem cells as well as midbrain/hindbrain progenitors, noradrenergic and cholinergic neurons, and dopaminergic neurons, demonstrated by specific electrophysiological signatures. Single-cell RNA sequence analysis, together with proteomics and electrophysiology, revealed that the cellular population in these organoids was similar to that of the human brainstem and neural crest, which raises the possibility of making use of hBSOs in grafting for transplantation, efficient drug screenings and modeling the neural crest diseases.

developmental biology↗

Single-cell transcriptomics reveals expansion of cytotoxic CD4 T-cells in supercentenarians

Supercentenarians, people who have reached 110 years of age, are a great model of healthy aging. Their characteristics of delayed onset of age-related diseases and compression of morbidity imply that their immune system remains functional. Here we performed single-cell transcriptome analysis of 61,202 peripheral blood mononuclear cells (PBMCs), derived from seven supercentenarians and five younger controls. We identified a marked increase of cytotoxic CD4 T-cells (CD4 CTLs) coupled with a substantial reduction of B-cells as a novel signature of supercentenarians. Furthermore, single-cell T-cell receptor sequencing of two supercentenarians revealed that CD4 CTLs had accumulated through massive clonal expansion, with the most frequent clonotypes accounting for 15% to 35% of the entire CD4 T-cell population. The CD4 CTLs exhibited substantial heterogeneity in their degree of cytotoxicity as well as a nearly identical transcriptome to that of CD8 CTLs. This indicates that CD4 CTLs utilize the transcriptional program of the CD8 lineage while retaining CD4 expression. Our study reveals that supercentenarians have unique characteristics in their circulating lymphocytes, which may represent an essential adaptation to achieve exceptional longevity by sustaining immune responses to infections and diseases.\n\nSignificanceExceptionally long-lived people such as supercentenarians tend to spend their entire lives in good health, implying that their immune system remains active to protect against infections and tumors. However, their immunological condition has been largely unexplored. We profiled thousands of circulating immune cells from supercentenarians at single-cell resolution, and identified a large number of CD4 T-cells that have cytotoxic features. This characteristic is very unique to supercentenarians, because generally CD4 T-cells have helper, but not cytotoxic, functions under physiological conditions. We further profiled their T-cell receptors, and revealed that the cytotoxic CD4 T-cells were accumulated through clonal expansion. The conversion of helper CD4 T-cells to a cytotoxic variety might be an adaptation to the late stage of aging.

immunology↗

Decoding neuronal diversity by single-cell Convert-seq

The conversion of cell fates is controlled by hierarchical gene regulatory networks (GRNs) that induce remarkable alterations in cellular and transcriptome states. The identification of key regulators within these networks from myriad of candidate genes, however, poses a major research challenge. Here we present Convert-seq, combining single-cell RNA sequencing (scRNA-seq) and pooled ectopic gene expression with a new strategy to discriminate sequencing reads derived from exogenous and endogenous transcripts. We demonstrate Convert-seq by associating hundreds of single cells during reprogramming of human fibroblasts to induced neurons (iN) with exogenous and endogenous transcriptional signatures. Convert-seq identified GRNs modulating the emergence of developmental trajectories and predicted combinatorial activation of exogenous transcription factors controlling iN subtype specification. Functional validation of iN subtypes generated by novel combinations of exogenous transcription factors establish Convert-seq as a broadly applicable workflow to rapidly identify key transcription factors and GRNs orchestrating the reprogramming of virtually any cell type.

neuroscience↗

C1 CAGE detects transcription start sites and enhancer activity at single-cell resolution

Single-cell transcriptomic profiling is a powerful tool to explore cellular heterogeneity. However, most of these methods focus on the 3-end of polyadenylated transcripts and provide only a partial view of the transcriptome. We introduce C1 CAGE, a method for the detection of transcript 5-ends with an original sample multiplexing strategy in the C1 microfluidic system. We first quantified the performance of C1 CAGE and found it as accurate and sensitive as other methods in C1 system. We then used it to profile promoter and enhancer activities in the cellular response to TGF-{beta} of lung cancer cells and discovered subpopulations of cells differing in their response. We also describe enhancer RNA dynamics revealing transcriptional bursts in subsets of cells with transcripts arising from either strand within a single-cell in a mutually exclusive manner, which was validated using single molecule fluorescence in-situ hybridization.

genomics↗

Single-cell transcriptomes of fluorescent, ubiquitination-based cell cycle indicator cells

We used a transgenic HeLa cell line that reports cell cycle phases through fluorescent, ubiquitination-based cell cycle indicators (Fucci), to produce a reference dataset of more than 270 curated single cells. Microscopic images were taken from each cell followed by RNA-sequencing, so that single-cell expression data is associated to the fluorescence intensity of the Fucci probes in the same cell. We developed an open data management and quality control workflow that enables users to replicate the processing of the sequence and microscopic image data that we deposited in public repositories. The workflow outputs a table with metadata, that is the starting point for further studies on these data. Beyond its use for cell cycle studies, We also expect that our workflow can be adapted to other single-cell projects using a similar combination of sequencing data and fluorescence measurements.

genomics↗