Multi-condition and multi-modal temporal profile inference during mouse embryonic development.

The emergence of single-cell time-series datasets enables modeling of changes in various types of cellular profiles over time. However, due to the disruptive nature of single-cell measurements, it is impossible to capture the full temporal trajectory of a particular cell. Furthermore, single-cell profiles can be collected at mismatched time points across different conditions (e.g., sex, batch, disease) and data modalities (e.g., scRNA-seq, scATAC-seq), which makes modeling challenging. Here we propose a joint modeling framework, Sunbear, for integrating multi-condition and multi-modal single-cell profiles across time. Sunbear can be used to impute single-cell temporal profile changes, align multi-dataset and multi-modal profiles across time, and extrapolate single-cell profiles in a missing modality. We applied Sunbear to reveal sex-biased transcription during mouse embryonic development and predict dynamic relationships between epigenetic priming and transcription for cells in which multi-modal profiles are unavailable. Sunbear thus enables the projection of single-cell time-series snapshots to multi-modal and multi-condition views of cellular trajectories.

A single-cell time-lapse of mouse prenatal development from gastrula to birth.

The house mouse (Mus musculus) is an exceptional model system, combining genetic tractability with close evolutionary affinity to humans1,2. Mouse gestation lasts only 3 weeks, during which the genome orchestrates the astonishing transformation of a single-cell zygote into a free-living pup composed of more than 500 million cells. Here, to establish a global framework for exploring mammalian development, we applied optimized single-cell combinatorial indexing3 to profile the transcriptional states of 12.4 million nuclei from 83 embryos, precisely staged at 2- to 6-hour intervals spanning late gastrulation (embryonic day 8) to birth (postnatal day 0). From these data, we annotate hundreds of cell types and explore the ontogenesis of the posterior embryo during somitogenesis and of kidney, mesenchyme, retina and early neurons. We leverage the temporal resolution and sampling depth of these whole-embryo snapshots, together with published data4-8 from earlier timepoints, to construct a rooted tree of cell-type relationships that spans the entirety of prenatal development, from zygote to birth. Throughout this tree, we systematically nominate genes encoding transcription factors and other proteins as candidate drivers of the in vivo differentiation of hundreds of cell types. Remarkably, the most marked temporal shifts in cell states are observed within one hour of birth and presumably underlie the massive physiological adaptations that must accompany the successful transition of a mammalian fetus to life outside the womb.

Cross-species imputation and comparison of single-cell transcriptomic profiles.

Cross-species comparison and prediction of gene expression profiles are important to understand regulatory changes during evolution and to transfer knowledge learned from model organisms to humans. Single-cell RNA-seq (scRNA-seq) profiles enable us to capture gene expression profiles with respect to variations among individual cells; however, cross-species comparison of scRNA-seq profiles is challenging because of data sparsity, batch effects, and the lack of one-to-one cell matching across species. Moreover, single-cell profiles are challenging to obtain in certain biological contexts, limiting the scope of hypothesis generation. Here we developed Icebear, a neural network framework that decomposes single-cell measurements into factors representing cell identity, species, and batch factors. Icebear enables accurate prediction of single-cell gene expression profiles across species, thereby providing high-resolution cell type and disease profiles in under-characterized contexts. Icebear also facilitates direct cross-species comparison of single-cell expression profiles for conserved genes that are located on the X chromosome in eutherian mammals but on autosomes in chicken. This comparison, for the first time, revealed evolutionary and diverse adaptations of X-chromosome upregulation in mammals.

KDM6A facilitates Xist upregulation at the onset of X inactivation.

X chromosome inactivation (XCI) is a female-specific process in which one X chromosome is silenced to balance X-linked gene expression between the sexes. XCI is initiated in early development by upregulation of the lncRNA Xist on the future inactive X (Xi). A subset of X-linked genes escape silencing and thus have higher expression in females, suggesting female-specific functions. One of these genes is the highly conserved gene Kdm6a , which encodes a histone demethylase that removes methyl groups at H3K27 to facilitate gene expression. Here, we investigate the role of KDM6A in the regulation of Xist . We observed impaired upregulation of Xist during early stages of differentiation in hybrid mouse ES cells following CRISPR/Cas9 knockout of Kdm6a . This is associated with reduced Xist RNA coating of the Xi, suggesting diminished XCI potency. Indeed, Kdm6a knockout results in aberrant overexpression of genes from the Xi after differentiation. KDM6A binds to the Xist promoter and knockout cells show an increase in H3K27me3 at Xist . These results indicate that KDM6A plays a role in the initiation of XCI through histone demethylase-dependent activation of Xist during early differentiation.

Spatial and temporal organization of the genome: Current state and future aims of the 4D nucleome project.

The four-dimensional nucleome (4DN) consortium studies the architecture of the genome and the nucleus in space and time. We summarize progress by the consortium and highlight the development of technologies for (1) mapping genome folding and identifying roles of nuclear components and bodies, proteins, and RNA, (2) characterizing nuclear organization with time or single-cell resolution, and (3) imaging of nuclear organization. With these tools, the consortium has provided over 2,000 public datasets. Integrative computational models based on these data are starting to reveal connections between genome structure and function. We then present a forward-looking perspective and outline current aims to (1) delineate dynamics of nuclear architecture at different timescales, from minutes to weeks as cells differentiate, in populations and in single cells, (2) characterize cis-determinants and trans-modulators of genome organization, (3) test functional consequences of changes in cis- and trans-regulators, and (4) develop predictive models of genome structure and function.

CTCF-mediated insulation and chromatin environment modulate Car5b escape from X inactivation.

Background: The number and escape levels of genes that escape X chromosome inactivation (XCI) in female somatic cells vary among tissues and cell types, potentially contributing to specific sex differences. Here we investigate the role of CTCF, a master chromatin conformation regulator, in regulating escape from XCI. CTCF binding profiles and epigenetic features were systematically examined at constitutive and facultative escape genes using mouse allelic systems to distinguish the inactive X (Xi) and active X (Xa) chromosomes. Results: We found that escape genes are located inside domains flanked by convergent arrays of CTCF binding sites, consistent with the formation of loops. In addition, strong and divergent CTCF binding sites often located at the boundaries between escape genes and adjacent neighbors subject to XCI would help insulate domains. Facultative escapees show clear differences in CTCF binding dependent on their XCI status in specific cell types/tissues. Concordantly, deletion but not inversion of a CTCF binding site at the boundary between the facultative escape gene Car5b and its silent neighbor Siah1b resulted in loss of Car5b escape. Reduced CTCF binding and enrichment of a repressive mark over Car5b in cells with a boundary deletion indicated loss of looping and insulation. In mutant lines in which either the Xi-specific compact structure or its H3K27me3 enrichment was disrupted, escape genes showed an increase in gene expression and associated active marks, supporting the roles of the 3D Xi structure and heterochromatic marks in constraining levels of escape. Conclusion: Our findings indicate that escape from XCI is modulated both by looping and insulation of chromatin via convergent arrays of CTCF binding sites and by compaction and epigenetic features of the surrounding heterochromatin.

Aneuploidy effects on human gene expression across three cell types.

Aneuploidy syndromes impact multiple organ systems but understanding of tissue-specific aneuploidy effects remains limited-especially for the comparison between peripheral tissues and relatively inaccessible tissues like brain. Here, we address this gap in knowledge by studying the transcriptomic effects of chromosome X, Y, and 21 aneuploidies in lymphoblastoid cell lines, fibroblasts and iPSC-derived neuronal cells (LCLs, FCL, and iNs, respectively). We root our analyses in sex chromosome aneuploidies, which offer a uniquely wide karyotype range for dosage effect analysis. We first harness a large LCL RNA-seq dataset from 197 individuals with one of 6 sex chromosome dosages (SCDs: XX, XXX, XY, XXY, XYY, and XXYY) to i) validate theoretical models of SCD sensitivity and ii) define an expanded set of 41 genes that show obligate dosage sensitivity to SCD and are all in cis (i.e., reside on the X or Y chromosome). We then use multiple complementary analyses to show that cis effects of SCD in LCLs are preserved in both FCLs (n = 32) and iNs (n = 24), whereas trans effects (i.e., those on autosomal gene expression) are mostly not preserved. Analysis of additional datasets confirms that the greater cross-cell type reproducibility of cis vs. trans effects is also seen in trisomy 21 cell lines. These findings i) expand our understanding of X, Y, and 21 chromosome dosage effects on human gene expression and ii) suggest that LCLs may provide a good model system for understanding cis effects of aneuploidy in harder-to-access cell types.

A single-cell transcriptional timelapse of mouse embryonic development, from gastrula to pup.

The house mouse, Mus musculus, is an exceptional model system, combining genetic tractability with close homology to human biology. Gestation in mouse development lasts just under three weeks, a period during which its genome orchestrates the astonishing transformation of a single cell zygote into a free-living pup composed of >500 million cells. Towards a global framework for exploring mammalian development, we applied single cell combinatorial indexing (sci-*) to profile the transcriptional states of 12.4 million nuclei from 83 precisely staged embryos spanning late gastrulation (embryonic day 8 or E8) to birth (postnatal day 0 or P0), with 2-hr temporal resolution during somitogenesis, 6-hr resolution through to birth, and 20-min resolution during the immediate postpartum period. From these data (E8 to P0), we annotate dozens of trajectories and hundreds of cell types and perform deeper analyses of the unfolding of the posterior embryo during somitogenesis as well as the ontogenesis of the kidney, mesenchyme, retina, and early neurons. Finally, we leverage the depth and temporal resolution of these whole embryo snapshots, together with other published data, to construct and curate a rooted tree of cell type relationships that spans mouse development from zygote to pup. Throughout this tree, we systematically nominate sets of transcription factors (TFs) and other genes as candidate drivers of the in vivo differentiation of hundreds of mammalian cell types. Remarkably, the most dramatic shifts in transcriptional state are observed in a restricted set of cell types in the hours immediately following birth, and presumably underlie the massive changes in physiology that must accompany the successful transition of a placental mammal to extrauterine life.

Oligonucleotide-directed proximity-interactome mapping (O-MAP): A unified method for discovering RNA-interacting proteins, transcripts and genomic loci in situ.

Throughout biology, RNA molecules form complex networks of molecular interactions that are central to their function, but remain challenging to investigate. Here, we introduce Oligonucleotide-mediated proximity-interactome MAPping (O-MAP), a straightforward method for elucidating the biomolecules near an RNA of interest, within its native cellular context. O-MAP uses programmable oligonucleotide probes to deliver proximity-biotinylating enzymes to a target RNA, enabling nearby molecules to be enriched by streptavidin pulldown. O-MAP induces exceptionally precise RNA-localized in situ biotinylation, and unlike alternative methods it enables straightforward optimization of its targeting accuracy. Using the 47S pre-ribosomal RNA and long noncoding RNA Xist as models, we develop O-MAP workflows for unbiased discovery of RNA-proximal proteins, transcripts, and genomic loci. This revealed unexpected co-compartmentalization of Xist and other chromatin-regulatory RNAs and enabled systematic characterization of nucleolar-chromatin interactions across multiple cell lines. O-MAP is portable to cultured cells, organoids, and tissues, and to RNAs of various lengths, abundances, and sequence composition. And, O-MAP requires no genetic manipulation and uses exclusively off-the-shelf parts. We therefore anticipate its application to a broad array of RNA phenomena.

Sex-biased and parental allele-specific gene regulation by KDM6A.

BACKGROUND: KDM6A is a demethylase encoded by a gene with female-biased expression due to escape from X inactivation. Its main role is to facilitate gene expression through removal of the repressive H3K27me3 mark, with evidence of some additional histone demethylase-independent functions. KDM6A mutations have been implicated in congenital disorders such as Kabuki Syndrome, as well as in sex differences in cancer. METHODS: Kdm6a was knocked out using CRISPR/Cas9 gene editing in F1 male and female mouse embryonic stem cells (ES) derived from reciprocal crosses between C57BL6 x Mus castaneus. Diploid and allelic RNA-seq analyses were done to compare gene expression between wild-type and Kdm6a knockout (KO) clones. The effects of Kdm6a KO on sex-biased gene expression were investigated by comparing gene expression between male and female ES cells. Changes in H3K27me3 enrichment and chromatin accessibility at promoter regions of genes with expression changes were characterized by ChIP-seq and ATAC-seq followed by diploid and allelic analyses. RESULTS: We report that Kdm6a KO in male and female embryonic stem (ES) cells derived from F1 hybrid mice cause extensive gene dysregulation, disruption of sex biases, and specific parental allele effects. Among the dysregulated genes are candidate genes that may explain abnormal developmental features of Kabuki syndrome caused by KDM6A mutations in human. Strikingly, Kdm6a knockouts result in a decrease in sex-biased expression and in preferential downregulation of the maternal alleles of a number of genes. Most promoters of dysregulated genes show concordant epigenetic changes including gain of H3K27me3 and loss of chromatin accessibility, but there was less concordance when considering allelic changes. CONCLUSIONS: Our study reveals new sex-related roles of KDM6A in the regulation of developmental genes, the maintenance of sex-biased gene expression, and the differential expression of parental alleles.

Systematic reconstruction of cellular trajectories across mouse embryogenesis.

Mammalian embryogenesis is characterized by rapid cellular proliferation and diversification. Within a few weeks, a single-cell zygote gives rise to millions of cells expressing a panoply of molecular programs. Although intensively studied, a comprehensive delineation of the major cellular trajectories that comprise mammalian development in vivo remains elusive. Here, we set out to integrate several single-cell RNA-sequencing (scRNA-seq) datasets that collectively span mouse gastrulation and organogenesis, supplemented with new profiling of ~150,000 nuclei from approximately embryonic day 8.5 (E8.5) embryos staged in one-somite increments. Overall, we define cell states at each of 19 successive stages spanning E3.5 to E13.5 and heuristically connect them to their pseudoancestors and pseudodescendants. Although constructed through automated procedures, the resulting directed acyclic graph (TOME (trajectories of mammalian embryogenesis)) is largely consistent with our contemporary understanding of mammalian development. We leverage TOME to systematically nominate transcription factors (TFs) as candidate regulators of each cell type's specification, as well as 'cell-type homologs' across vertebrate evolution.

Single-cell landscape of nuclear configuration and gene expression during stem cell differentiation and X inactivation.

BACKGROUND: Mammalian development is associated with extensive changes in gene expression, chromatin accessibility, and nuclear structure. Here, we follow such changes associated with mouse embryonic stem cell differentiation and X inactivation by integrating, for the first time, allele-specific data from these three modalities obtained by high-throughput single-cell RNA-seq, ATAC-seq, and Hi-C. RESULTS: Allele-specific contact decay profiles obtained by single-cell Hi-C clearly show that the inactive X chromosome has a unique profile in differentiated cells that have undergone X inactivation. Loss of this inactive X-specific structure at mitosis is followed by its reappearance during the cell cycle, suggesting a "bookmark" mechanism. Differentiation of embryonic stem cells to follow the onset of X inactivation is associated with changes in contact decay profiles that occur in parallel on both the X chromosomes and autosomes. Single-cell RNA-seq and ATAC-seq show evidence of a delay in female versus male cells, due to the presence of two active X chromosomes at early stages of differentiation. The onset of the inactive X-specific structure in single cells occurs later than gene silencing, consistent with the idea that chromatin compaction is a late event of X inactivation. Single-cell Hi-C highlights evidence of discrete changes in nuclear structure characterized by the acquisition of very long-range contacts throughout the nucleus. Novel computational approaches allow for the effective alignment of single-cell gene expression, chromatin accessibility, and 3D chromosome structure. CONCLUSIONS: Based on trajectory analyses, three distinct nuclear structure states are detected reflecting discrete and profound simultaneous changes not only to the structure of the X chromosomes, but also to that of autosomes during differentiation. Our study reveals that long-range structural changes to chromosomes appear as discrete events, unlike progressive changes in gene expression and chromatin accessibility.

X-factors in human disease: impact of gene content and dosage regulation.

The gene content of the X and Y chromosomes has dramatically diverged during evolution. The ensuing dosage imbalance within the genome of males and females has led to unique chromosome-wide regulatory mechanisms with significant and sex-specific impacts on X-linked gene expression. X inactivation or silencing of most genes on one X chromosome chosen at random in females profoundly affects the manifestation of X-linked diseases, as males inherit a single maternal allele, while females express maternal and paternal alleles in a mosaic manner. An additional complication is the existence of genes that escape X inactivation and thus are ubiquitously expressed from both alleles in females. The mosaic nature of X-linked gene expression and the potential for escape can vary between individuals, tissues, cell types and stages of life. Our understanding of the specialized nature of X-linked genes and of the multilayer epigenetic regulation that influence their expression throughout the organism has been helped by molecular studies conducted by tissue-specific and single-cell-specific approaches. In turn, the definition of molecular events that control X silencing has helped develop new approaches for the treatment of some X-linked disorders. This review focuses on the peculiarities of the X chromosome genetic content and epigenetic regulation in shaping the manifestation of congenital and acquired X-linked disorders in a sex-specific manner.

X-chromosome regulation and sex differences in brain anatomy.

Humans show reproducible sex-differences in cognition and psychopathology that may be contributed to by influences of gonadal sex-steroids and/or sex-chromosomes on regional brain development. Gonadal sex-steroids are well known to play a major role in sexual differentiation of the vertebrate brain, but far less is known regarding the role of sex-chromosomes. Our review focuses on this latter issue by bridging together two literatures that have to date been largely disconnected. We first consider "bottom-up" genetic and molecular studies focused on sex-chromosome gene content and regulation. This literature nominates specific sex-chromosome genes that could drive developmental sex-differences by virtue of their sex-biased expression and their functions within the brain. We then consider the complementary "top down" view, from magnetic resonance imaging studies that map sex- and sex chromosome effects on regional brain anatomy, and link these maps to regional gene-expression within the brain. By connecting these top-down and bottom-up approaches, we emphasize the potential role of X-linked genes in driving sex-biased brain development and outline key goals for future work in this field.

Trans- and cis-acting effects of Firre on epigenetic features of the inactive X chromosome.

Firre encodes a lncRNA involved in nuclear organization. Here, we show that Firre RNA expressed from the active X chromosome maintains histone H3K27me3 enrichment on the inactive X chromosome (Xi) in somatic cells. This trans-acting effect involves SUZ12, reflecting interactions between Firre RNA and components of the Polycomb repressive complexes. Without Firre RNA, H3K27me3 decreases on the Xi and the Xi-perinucleolar location is disrupted, possibly due to decreased CTCF binding on the Xi. We also observe widespread gene dysregulation, but not on the Xi. These effects are measurably rescued by ectopic expression of mouse or human Firre/FIRRE transgenes, supporting conserved trans-acting roles. We also find that the compact 3D structure of the Xi partly depends on the Firre locus and its RNA. In common lymphoid progenitors and T-cells Firre exerts a cis-acting effect on maintenance of H3K27me3 in a 26 Mb region around the locus, demonstrating cell type-specific trans- and cis-acting roles of this lncRNA.

Unsupervised manifold alignment for single-cell multi-omics data.

Integrating single-cell measurements that capture different properties of the genome is vital to extending our understanding of genome biology. This task is challenging due to the lack of a shared axis across datasets obtained from different types of single-cell experiments. For most such datasets, we lack corresponding information among the cells (samples) and the measurements (features). In this scenario, unsupervised algorithms that are capable of aligning single-cell experiments are critical to learning an in silico co-assay that can help draw correspondences among the cells. Maximum mean discrepancy-based manifold alignment (MMD-MA) is such an unsupervised algorithm. Without requiring correspondence information, it can align single-cell datasets from different modalities in a common shared latent space, showing promising results on simulations and a small-scale single-cell experiment with 61 cells. However, it is essential to explore the applicability of this method to larger single-cell experiments with thousands of cells so that it can be of practical interest to the community. In this paper, we apply MMD-MA to two recent datasets that measure transcriptome and chromatin accessibility in ~2000 single cells. To scale the runtime of MMD-MA to a more substantial number of cells, we extend the original implementation to run on GPUs. We also introduce a method to automatically select one of the user-defined parameters, thus reducing the hyperparameter search space. We demonstrate that the proposed extensions allow MMD-MA to accurately align state-of-the-art single-cell experiments.

Sci-Hi-C: A single-cell Hi-C method for mapping 3D genome organization in large number of single cells.

The highly dynamic nature of chromosome conformation and three-dimensional (3D) genome organization leads to cell-to-cell variability in chromatin interactions within a cell population, even if the cells of the population appear to be functionally homogeneous. Hence, although Hi-C is a powerful tool for mapping 3D genome organization, this heterogeneity of chromosome higher order structure among individual cells limits the interpretive power of population based bulk Hi-C assays. Moreover, single-cell studies have the potential to enable the identification and characterization of rare cell populations or cell subtypes in a heterogeneous population. However, it may require surveying relatively large numbers of single cells to achieve statistically meaningful observations in single-cell studies. By applying combinatorial cellular indexing to chromosome conformation capture, we developed single-cell combinatorial indexed Hi-C (sci-Hi-C), a high throughput method that enables mapping chromatin interactomes in large number of single cells. We demonstrated the use of sci-Hi-C data to separate cells by karytoypic and cell-cycle state differences and to identify cellular variability in mammalian chromosomal conformation. Here, we provide a detailed description of method design and step-by-step working protocols for sci-Hi-C.