Tracing the origin of hair follicle stem cells.

Tissue stem cells are generated from a population of embryonic progenitors through organ-specific morphogenetic events1,2. Although tissue stem cells are central to organ homeostasis and regeneration, it remains unclear how they are induced during development, mainly because of the lack of markers that exclusively label prospective stem cells. Here we combine marker-independent long-term 3D live imaging and single-cell transcriptomics to capture a dynamic lineage progression and transcriptome changes in the entire epithelium of the mouse hair follicle as it develops. We found that the precursors of different epithelial lineages were aligned in a 2D concentric manner in the basal layer of the hair placode. Each concentric ring acquired unique transcriptomes and extended to form longitudinally aligned, 3D cylindrical compartments. Prospective bulge stem cells were derived from the peripheral ring of the placode basal layer, but not from suprabasal cells (as was previously suggested3). The fate of placode cells is determined by the cell position, rather than by the orientation of cell division. We also identified 13 gene clusters: the ensemble expression dynamics of these clusters drew the entire transcriptional landscape of epithelial lineage diversification, consistent with cell lineage data. Combining these findings with previous work on the development of appendages in insects4,5, we describe the 'telescope model', a generalized model for the development of ectodermal organs in which 2D concentric zones in the placode telescope out to form 3D longitudinally aligned cylindrical compartments.

Chromatin remodeler CHD7 regulates the stem cell identity of human neural progenitors.

Multiple congenital disorders often present complex phenotypes, but how the mutation of individual genetic factors can lead to multiple defects remains poorly understood. In the present study, we used human neuroepithelial (NE) cells and CHARGE patient-derived cells as an in vitro model system to identify the function of chromodomain helicase DNA-binding 7 (CHD7) in NE-neural crest bifurcation, thus revealing an etiological link between the central nervous system (CNS) and craniofacial anomalies observed in CHARGE syndrome. We found that CHD7 is required for epigenetic activation of superenhancers and CNS-specific enhancers, which support the maintenance of the NE and CNS lineage identities. Furthermore, we found that BRN2 and SOX21 are downstream effectors of CHD7, which shapes cellular identities by enhancing a CNS-specific cellular program and indirectly repressing non-CNS-specific cellular programs. Based on our results, CHD7, through its interactions with superenhancer elements, acts as a regulatory hub in the orchestration of the spatiotemporal dynamics of transcription factors to regulate NE and CNS lineage identities.

Enhanced transcriptional heterogeneity mediated by NF-κB super-enhancers.

The transcription factor NF-κB, which plays an important role in cell fate determination, is involved in the activation of super-enhancers (SEs). However, the biological functions of the NF-κB SEs in gene control are not fully elucidated. We investigated the characteristics of NF-κB-mediated SE activity using fluorescence imaging of RelA, single-cell transcriptome and chromatin accessibility analyses in anti-IgM-stimulated B cells. The formation of cell stimulation-induced nuclear RelA foci was abolished in the presence of hexanediol, suggesting an underlying process of liquid-liquid phase separation. The gained SEs induced a switch-like expression and enhanced cell-to-cell variability in transcriptional response. These properties were correlated with the number of gained cis-regulatory interactions, while switch-like gene induction was associated with the number of NF-κB binding sites in SE. Our study suggests that NF-κB SEs have an important role in the transcriptional regulation of B cells possibly through liquid condensate formation consisting of macromolecular interactions.

Maternal epigenetic factors in embryonic and postnatal development.

Maternal factors present in oocytes and surrounding granulosa cells influence early development of embryos. In this study, we searched for epigenetic regulators that are expressed in oocytes and/or granulosa cells. Some of the 120 epigenetic regulators examined were expressed specifically in oocytes and/or granulosa cells. When their expression was examined in young versus aged oocytes or granulosa cells, many were significantly up- or downregulated in aged cells. The maternal role of six genes in development was investigated by generating oocyte-specific knock-out (MKO) mice. Two genes (Mllt10, Kdm2b) did not show maternal effects on later development, whereas maternal effects were evident for Kdm6a, Kdm4a, Prdm3, and Prdm16 for MKO female mice. Offspring from Kdm6a MKO mice underwent perinatal lethality at a higher rate. Pups derived from Prdm3;Prdm16 double MKO showed a higher incidence of postnatal death. Finally, embryos derived from Kdm4a MKO mice showed early developmental defects as early as the peri-implantation stage. These results suggest that many of maternal epigenetic regulators undergo differential expression upon aging. Some, such as Kdm4a, Kdm6a, Prdm3, and Prdm16, have maternal role in later embryonic or postnatal development.

Sctensor detects many-to-many cell-cell interactions from single cell RNA-sequencing data.

BACKGROUND: Complex biological systems are described as a multitude of cell-cell interactions (CCIs). Recent single-cell RNA-sequencing studies focus on CCIs based on ligand-receptor (L-R) gene co-expression but the analytical methods are not appropriate to detect many-to-many CCIs. RESULTS: In this work, we propose scTensor, a novel method for extracting representative triadic relationships (or hypergraphs), which include ligand-expression, receptor-expression, and related L-R pairs. CONCLUSIONS: Through extensive studies with simulated and empirical datasets, we have shown that scTensor can detect some hypergraphs that cannot be detected using conventional CCI detection methods, especially when they include many-to-many relationships. scTensor is implemented as a freely available R/Bioconductor package.

WormTensor: a clustering method for time-series whole-brain activity data from C. elegans.

BACKGROUND: In the field of neuroscience, neural modules and circuits that control biological functions have been found throughout entire neural networks. Correlations in neural activity can be used to identify such neural modules. Recent technological advances enable us to measure whole-brain neural activity with single-cell resolution in several species including [Formula: see text]. Because current neural activity data in C. elegans contain many missing data points, it is necessary to merge results from as many animals as possible to obtain more reliable functional modules. RESULTS: In this work, we developed a new time-series clustering method, WormTensor, to identify functional modules using whole-brain activity data from C. elegans. WormTensor uses a distance measure, modified shape-based distance to account for the lags and the mutual inhibition of cell-cell interactions and applies the tensor decomposition algorithm multi-view clustering based on matrix integration using the higher orthogonal iteration of tensors (HOOI) algorithm (MC-MI-HOOI), which can estimate both the weight to account for the reliability of data from each animal and the clusters that are common across animals. CONCLUSION: We applied the method to 24 individual C. elegans and successfully found some known functional modules. Compared with a widely used consensus clustering method to aggregate multiple clustering results, WormTensor showed higher silhouette coefficients. Our simulation also showed that WormTensor is robust to contamination from noisy data. WormTensor is freely available as an R/CRAN package https://cran.r-project.org/web/packages/WormTensor .

A common epigenetic mechanism across different cellular origins underlies systemic immune dysregulation in an idiopathic autism mouse model.

Immune dysregulation plays a key role in the pathogenesis of autism. Changes occurring at the systemic level, from brain inflammation to disturbed innate/adaptive immune in the periphery, are frequently observed in patients with autism; however, the intrinsic mechanisms behind them remain elusive. We hypothesize a common etiology may lie in progenitors of different types underlying widespread immune dysregulation. By single-cell RNA sequencing (sc-RNA seq), we trace the developmental origins of immune dysregulation in a mouse model of idiopathic autism. It is found that both in aorta-gonad-mesonephros (AGM) and yolk sac (YS) progenitors, the dysregulation of HDAC1-mediated epigenetic machinery alters definitive hematopoiesis during embryogenesis and downregulates the expression of the AP-1 complex for microglia development. Subsequently, these changes result in the dysregulation of the immune system, leading to gut dysbiosis and hyperactive microglia in the brain. We further confirm that dysregulated immune profiles are associated with specific microbiota composition, which may serve as a biomarker to identify autism of immune-dysregulated subtypes. Our findings elucidate a shared mechanism for the origin of immune dysregulation from the brain to the gut in autism and provide new insight to dissecting the heterogeneity of autism, as well as the therapeutic potential of targeting immune-dysregulated autism subtypes.

Local states of chromatin compaction at transcription start sites control transcription levels.

The 'open' and 'compact' regions of chromatin are considered to be regions of active and silent transcription, respectively. However, individual genes produce transcripts at different levels, suggesting that transcription output does not depend on the simple open-compact conversion of chromatin, but on structural variations in chromatin itself, which so far have remained elusive. In this study, weakly crosslinked chromatin was subjected to sedimentation velocity centrifugation, which fractionated the chromatin according to its degree of compaction. Open chromatin remained in upper fractions, while compact chromatin sedimented to lower fractions depending on the level of nucleosome assembly. Although nucleosomes were evenly detected in all fractions, histone H1 was more highly enriched in the lower fractions. H1 was found to self-associate and crosslinked to histone H3, suggesting that H1 bound to H3 interacts with another H1 in an adjacent nucleosome to form compact chromatin. Genome-wide analyses revealed that nearly the entire genome consists of compact chromatin without differences in compaction between repeat and non-repeat sequences; however, active transcription start sites (TSSs) were rarely found in compact chromatin. Considering the inverse correlation between chromatin compaction and RNA polymerase binding at TSSs, it appears that local states of chromatin compaction determine transcription levels.

Developmental excitation-inhibition imbalance underlying psychoses revealed by single-cell analyses of discordant twins-derived cerebral organoids.

Despite extensive genetic and neuroimaging studies, detailed cellular mechanisms underlying schizophrenia and bipolar disorder remain poorly understood. Recent progress in single-cell RNA sequencing (scRNA-seq) technologies enables identification of cell-type-specific pathophysiology. However, its application to psychiatric disorders is challenging because of methodological difficulties in analyzing human brains and the confounds due to a lifetime of illness. Brain organoids derived from induced pluripotent stem cells (iPSCs) of the patients are a powerful avenue to investigate the pathophysiological processes. Here, we generated iPSC-derived cerebral organoids from monozygotic twins discordant for psychosis. scRNA-seq analysis of the organoids revealed enhanced GABAergic specification and reduced cell proliferation following diminished Wnt signaling in the patient, which was confirmed in iPSC-derived forebrain neuronal cells. Two additional monozygotic twin pairs discordant for schizophrenia also confirmed the excess GABAergic specification of the patients' neural progenitor cells. With a well-controlled genetic background, our data suggest that unbalanced specification of excitatory and inhibitory neurons during cortical development underlies psychoses.

Context-dependent wiring of Sox2 regulatory networks for self-renewal of embryonic and trophoblast stem cells.

Sox2 is a transcription factor required for the maintenance of pluripotency. It also plays an essential role in different types of multipotent stem cells, raising the possibility that Sox2 governs the common stemness phenotype. Here we show that Sox2 is a critical downstream target of fibroblast growth factor (FGF) signaling, which mediates self-renewal of trophoblast stem cells (TSCs). Sustained expression of Sox2 together with Esrrb or Tfap2c can replace FGF dependency. By comparing genome-wide binding sites of Sox2 in embryonic stem cells (ESCs) and TSCs combined with inducible knockout systems, we found that, despite the common role in safeguarding the stem cell state, Sox2 regulates distinct sets of genes with unique functions in these two different yet developmentally related types of stem cells. Our findings provide insights into the functional versatility of transcription factors during embryogenesis, during which they can be recursively utilized in a variable manner within discrete network structures.

Millefy: visualizing cell-to-cell heterogeneity in read coverage of single-cell RNA sequencing datasets.

BACKGROUND: Read coverage of RNA sequencing data reflects gene expression and RNA processing events. Single-cell RNA sequencing (scRNA-seq) methods, particularly "full-length" ones, provide read coverage of many individual cells and have the potential to reveal cellular heterogeneity in RNA transcription and processing. However, visualization tools suited to highlighting cell-to-cell heterogeneity in read coverage are still lacking. RESULTS: Here, we have developed Millefy, a tool for visualizing read coverage of scRNA-seq data in genomic contexts. Millefy is designed to show read coverage of all individual cells at once in genomic contexts and to highlight cell-to-cell heterogeneity in read coverage. By visualizing read coverage of all cells as a heat map and dynamically reordering cells based on diffusion maps, Millefy facilitates discovery of "local" region-specific, cell-to-cell heterogeneity in read coverage. We applied Millefy to scRNA-seq data sets of mouse embryonic stem cells and triple-negative breast cancers and showed variability of transcribed regions including antisense RNAs, 3 ' UTR lengths, and enhancer RNA transcription. CONCLUSIONS: Millefy simplifies the examination of cellular heterogeneity in RNA transcription and processing events using scRNA-seq data. Millefy is available as an R package (https://github.com/yuifu/millefy) and as a Docker image for use with Jupyter Notebook (https://hub.docker.com/r/yuifu/datascience-notebook-millefy).

Cell type-specific transcriptome analysis unveils secreted signaling molecule genes expressed in apical epithelial cap during appendage regeneration.

Wound epidermis (WE) and the apical epithelial cap (AEC) are believed to trigger regeneration of amputated appendages such as limb and tail in amphibians by producing certain secreted signaling molecules. To date, however, only limited information about the molecular signatures of these epidermal structures is available. Here we used a transgenic Xenopus laevis line harboring the enhanced green fluorescent protein (egfp) gene under control of an es1 gene regulatory sequence to isolate WE/AEC cells by performing fluorescence-activated cell sorting during the time course of tail regeneration (day 1, day 2, day 3 and day 4 after amputation). Time-course transcriptome analysis of these isolated WE/AEC cells revealed that more than 8,000 genes, including genes involved in signaling pathways such as those of reactive oxygen species, fibroblast growth factor (FGF), canonical and non-canonical Wnt, transforming growth factor ß (TGF ß) and Notch, displayed dynamic changes of their expression during tail regeneration. Notably, this approach enabled us to newly identify seven secreted signaling molecule genes (mdk, fstl, slit1, tgfß1, bmp7.1, angptl2 and egfl6) that are highly expressed in tail AEC cells. Among these genes, five (mdk, fstl, slit1, tgfß1 and bmp7.1) were also highly expressed in limb AEC cells but the other two (angptl2 and egfl6) are specifically expressed in tail AEC cells. Interestingly, there was no expression of fgf8 in tail WE/AEC cells, whose expression and pivotal role in limb AEC cells have been reported previously. Thus, we identified common and different properties between tail and limb AEC cells.

Strategies for Converting RNA to Amplifiable cDNA for Single-Cell RNA Sequencing Methods.

This review describes the features of molecular biology techniques for single-cell RNA sequencing (scRNA-seq), including methods developed in our laboratory. Existing scRNA-seq methods require the conversion of first-strand cDNA to amplifiable cDNA followed by whole-transcript amplification. There are three primary strategies for this conversion: poly-A tagging, template switching, and RNase H-DNA polymerase I-mediated second-strand cDNA synthesis for in vitro transcription. We discuss the merits and limitations of these strategies and describe our Reverse Transcription with Random Displacement Amplification technology that allows for direct first-strand cDNA amplification from RNA without the need for conversion to an amplifiable cDNA. We believe that this review provides all users of single-cell transcriptome technologies with an understanding of the relationship between the quantitative performance of various methods and their molecular features.

SCODE: an efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation.

MOTIVATION: The analysis of RNA-Seq data from individual differentiating cells enables us to reconstruct the differentiation process and the degree of differentiation (in pseudo-time) of each cell. Such analyses can reveal detailed expression dynamics and functional relationships for differentiation. To further elucidate differentiation processes, more insight into gene regulatory networks is required. The pseudo-time can be regarded as time information and, therefore, single-cell RNA-Seq data are time-course data with high time resolution. Although time-course data are useful for inferring networks, conventional inference algorithms for such data suffer from high time complexity when the number of samples and genes is large. Therefore, a novel algorithm is necessary to infer networks from single-cell RNA-Seq during differentiation. RESULTS: In this study, we developed the novel and efficient algorithm SCODE to infer regulatory networks, based on ordinary differential equations. We applied SCODE to three single-cell RNA-Seq datasets and confirmed that SCODE can reconstruct observed expression dynamics. We evaluated SCODE by comparing its inferred networks with use of a DNaseI-footprint based network. The performance of SCODE was best for two of the datasets and nearly best for the remaining dataset. We also compared the runtimes and showed that the runtimes for SCODE are significantly shorter than for alternatives. Thus, our algorithm provides a promising approach for further single-cell differentiation analyses. AVAILABILITY AND IMPLEMENTATION: The R source code of SCODE is available at https://github.com/hmatsu1226/SCODE. CONTACT: hirotaka.matsumoto@riken.jp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Polysaccharide hydrolase of the hadal zone amphipods Hirondellea gigas.

Hirondellea species are common inhabitants in the hadal region deeper than 7,000 m. We found that Hirondellea gigas thrived in the Challenger Deep possessed polysaccharide hydrolases as digestive enzymes. To obtain various enzymes of other H. gigas, we captured amphipods from the Japan Trench, and Izu-Ogasawara (Bonin) Trench. A phylogenetic analysis based on the cytochrome oxidase I gene showed close relationships among amphipods, despite the geographic distance between the localities. However, several differences in enzymatic properties were observed in these H. gigas specimens. We also carried out RNA sequencing of H. gigas from the Izu-Ogasawara Trench. The cellulase gene of H. gigas was highly homologous to cellobiohydrolase of Glucosyl Hydrolase family 7 (GH7). On the other hand, enzymatic properties of H. gigas's cellulase were different from those of typical GH7 cellobiohydrolase. Thus, these results indicate that hadal-zone amphipod can be good candidates as the new enzyme resource.

MeSH ORA framework: R/Bioconductor packages to support MeSH over-representation analysis.

BACKGROUND: In genome-wide studies, over-representation analysis (ORA) against a set of genes is an essential step for biological interpretation. Many gene annotation resources and software platforms for ORA have been proposed. Recently, Medical Subject Headings (MeSH) terms, which are annotations of PubMed documents, have been used for ORA. MeSH enables the extraction of broader meaning from the gene lists and is expected to become an exhaustive annotation resource for ORA. However, the existing MeSH ORA software platforms are still not sufficient for several reasons. RESULTS: In this work, we developed an original MeSH ORA framework composed of six types of R packages, including MeSH.db, MeSH.AOR.db, MeSH.PCR.db, the org.MeSH.XXX.db-type packages, MeSHDbi, and meshr. CONCLUSIONS: Using our framework, users can easily conduct MeSH ORA. By utilizing the enriched MeSH terms, related PubMed documents can be retrieved and saved on local machines within this framework.

Id4, a new candidate gene for senile osteoporosis, acts as a molecular switch promoting osteoblast differentiation.

Excessive accumulation of bone marrow adipocytes observed in senile osteoporosis or age-related osteopenia is caused by the unbalanced differentiation of MSCs into bone marrow adipocytes or osteoblasts. Several transcription factors are known to regulate the balance between adipocyte and osteoblast differentiation. However, the molecular mechanisms that regulate the balance between adipocyte and osteoblast differentiation in the bone marrow have yet to be elucidated. To identify candidate genes associated with senile osteoporosis, we performed genome-wide expression analyses of differentiating osteoblasts and adipocytes. Among transcription factors that were enriched in the early phase of differentiation, Id4 was identified as a key molecule affecting the differentiation of both cell types. Experiments using bone marrow-derived stromal cell line ST2 and Id4-deficient mice showed that lack of Id4 drastically reduces osteoblast differentiation and drives differentiation toward adipocytes. On the other hand knockdown of Id4 in adipogenic-induced ST2 cells increased the expression of Ppargamma2, a master regulator of adipocyte differentiation. Similar results were observed in bone marrow cells of femur and tibia of Id4-deficient mice. However the effect of Id4 on Ppargamma2 and adipocyte differentiation is unlikely to be of direct nature. The mechanism of Id4 promoting osteoblast differentiation is associated with the Id4-mediated release of Hes1 from Hes1-Hey2 complexes. Hes1 increases the stability and transcriptional activity of Runx2, a key molecule of osteoblast differentiation, which results in an enhanced osteoblast-specific gene expression. The new role of Id4 in promoting osteoblast differentiation renders it a target for preventing the onset of senile osteoporosis.

Single-cell transcriptomics uncovers EGFR signaling-mediated gastric progenitor cell differentiation in stomach homeostasis.

Defects in gastric progenitor cell differentiation are associated with various gastric disorders, including atrophic gastritis, intestinal metaplasia, and gastric cancer. However, the mechanisms underlying the multilineage differentiation of gastric progenitor cells during healthy homeostasis remain poorly understood. Here, using a single-cell RNA sequencing method, Quartz-Seq2, we analyzed the gene expression dynamics of progenitor cell differentiation toward pit cell, neck cell, and parietal cell lineages in healthy adult mouse corpus tissues. Enrichment analysis of pseudotime-dependent genes and a gastric organoid assay revealed that EGFR-ERK signaling promotes pit cell differentiation, whereas NF-κB signaling maintains gastric progenitor cells in an undifferentiated state. In addition, pharmacological inhibition of EGFR in vivo resulted in a decreased number of pit cells. Although activation of EGFR signaling in gastric progenitor cells has been suggested as one of the major inducers of gastric cancers, our findings unexpectedly identified that EGFR signaling exerts a differentiation-promoting function, not a mitogenic function, in normal gastric homeostasis.