Christine M. Disteche

Nucleoli, nuclear speckles and other compartments regulate transcription, RNA processing, and chromatin organization within the nucleus, yet the relationship of their morphology to developmental gene expression programs in vivo is poorly understood. Here, we develop a high-throughput Visual Cell Sorting (VCS) workflow for fixed cells and nuclei that combines antibody-based photoconversion; GPU-accelerated, real-time image analysis; and three-level single-cell combinatorial indexing RNA-seq (sci-RNA-seq3) to link nuclear compartment morphology to single-nucleus transcriptomes at embryo scale. We use VCS to analyze and sort over 1 million mouse embryo-derived nuclei by nucleolar, nuclear speckle, or nuclear size and construct a transcriptional atlas annotated with nuclear compartment phenotypes. Nuclear compartment size varies both between and within lineages and is shaped by proliferation and differentiation. In extracellular matrix protein-producing cell types such as fibroblasts, chondrocytes, and osteoblasts, nucleolar enlargement is uncoupled from cell cycle, and in erythroid cells exhibit a sharp nucleolar contraction preceding cell-cycle exit. We identify a 41-gene transcriptional signature whose expression tracks nucleolar size, enriched for ribosome biogenesis, mitochondrial metabolism, unfolded protein response, stress granule, and ubiquitin–proteasome pathway components. We used this nucleolar transcriptional signature to annotate mouse, zebrafish and human developmental atlases with nucleolar size information, revealing a conserved coupling between nucleolar activity and proteostasis programs. Our work establishes Visual Cell Sorting as a scalable platform for mapping image-based phenotypes to molecular programs; details the relationship between nuclear compartment phenotypes and development; and provides a transcriptional signature to estimate nucleolar size from existing single-cell datasets.

Nucleoli, nuclear speckles and other compartments regulate transcription, RNA processing, and chromatin organization within the nucleus, yet the relationship of their morphology to developmental gene expression programs in vivo is poorly understood. Here, we develop a high-throughput Visual Cell Sorting (VCS) workflow for fixed cells and nuclei that combines antibody-based photoconversion; GPU-accelerated, real-time image analysis; and three-level single-cell combinatorial indexing RNA-seq (sci-RNA-seq3) to link nuclear compartment morphology to single-nucleus transcriptomes at embryo scale. We use VCS to analyze and sort over 1 million mouse embryo-derived nuclei by nucleolar, nuclear speckle, or nuclear size and construct a transcriptional atlas annotated with nuclear compartment phenotypes. Nuclear compartment size varies both between and within lineages and is shaped by proliferation and differentiation. In extracellular matrix protein-producing cell types such as fibroblasts, chondrocytes, and osteoblasts, nucleolar enlargement is uncoupled from cell cycle, and in erythroid cells exhibit a sharp nucleolar contraction preceding cell-cycle exit. We identify a 41-gene transcriptional signature whose expression tracks nucleolar size, enriched for ribosome biogenesis, mitochondrial metabolism, unfolded protein response, stress granule, and ubiquitin–proteasome pathway components. We used this nucleolar transcriptional signature to annotate mouse, zebrafish and human developmental atlases with nucleolar size information, revealing a conserved coupling between nucleolar activity and proteostasis programs. Our work establishes Visual Cell Sorting as a scalable platform for mapping image-based phenotypes to molecular programs; details the relationship between nuclear compartment phenotypes and development; and provides a transcriptional signature to estimate nucleolar size from existing single-cell datasets.

Common sex chromosome aneuploidies (SCAs) often present with cognitive and cardiovascular dysfunction in humans. To address SCA effects on gene expression and DNA methylation in relevant cell types, we differentiated neural precursor cells (NPCs) and cardiomyocytes (CMs) from human induced pluripotent stem cells (hiPSCs) with different numbers of sex chromosomes, including isogenic and independent lines. As expected, the expression of genes that escape X inactivation (escapees) mostly increases with the number of inactive X chromosomes (Xi). However, allelic analysis shows dampening of escapees specifically on the Xi in XXY compared to XX in both NPCs and CMs, revealing a novel type of dosage compensation in SCA. In contrast, Y-linked gene expression is higher in XXY versus XY NPCs, but the opposite is observed in CMs. This may explain the greater number of differentially expressed autosomal genes in NPCs versus CMs with an added Y chromosome, while effects of added X chromosomes are similar between cell types. Concordantly, changes in autosomal DNA methylation are mainly driven by the presence of a Y chromosome. These findings highlight the cell-type specificity of sex-linked and autosomal gene regulation in SCA conditions.

Klinefelter syndrome (47,XXY; KS) impacts neurodevelopment. Furthermore, KS is associated with widespread alterations in the epigenome and transcriptome. Whether these epigenetic and transcriptomic alterations can be linked to the neurocognitive phenotype remains to be elucidated. We performed a comprehensive, integrative analysis of the neurocognitive profile and the methylome in blood from males with KS (n = 65) and male controls (n = 63) (Cohort 1). The results were validated in a second cohort of males with KS (n = 22) and male controls (n = 16) in which transcriptome data was also available (Cohort 2). The findings were further validated in neural precursor cells derived from human induced pluripotent stem cells from 47,XXY (n = 3) and 46,XY (n = 3) amniotic cells. In cohort 1, we identified five CG-sites within the TRAK1 gene which were hypomethylated in males with KS compared to male controls. TRAK1 hypomethylation was positively correlated with several neurocognitive variables among males with KS. In cohort 2, we identified a similar methylation pattern and demonstrated that the methylation levels at the five CG-sites were correlated with a high expression level of a specific short TRAK1 transcript (ENST00000341421.7). Neural precursor cells (NPCs) established from 47,XXY amniotic cells also exhibited hypomethylation at the five CG-sites and strong upregulation of ENST00000341421.7 compared to NPCs established from 46,XY amniotic cells. In conclusion, we demonstrate that the DNA methylation level at specific CG-sites within TRAK1 , a gene highly expressed in the brain, is correlated with the neurocognitive phenotype of KS, implying a possible epigenetic underpinning for the observed neurocognitive impairments in KS.

The emergence of single-cell time-series data sets enables modeling of changes in various types of cellular profiles over time. However, because of 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 multicondition and multimodal single-cell profiles across time. Sunbear can be used to impute single-cell temporal profile changes, align multi–data set and multimodal profiles across time, and extrapolate single-cell profiles in a missing modality. We apply Sunbear to reveal sex-biased transcription during mouse embryonic development and predict dynamic relationships between epigenetic priming and transcription for cells in which multimodal profiles are unavailable. Sunbear thus enables the projection of single-cell time-series snapshots to multimodal and multicondition views of cellular trajectories.

Background: Genes that escape X-chromosome inactivation (XCI) in female somatic cells vary in number and levels of escape among mammalian species and tissues, potentially contributing to species- and tissue-specific sex differences. CTCF, a master chromatin conformation regulator, is enriched at escape regions and may play an important role in regulating escape, but the molecular mechanisms remain elusive. Results: CTCF binding profiles and epigenetic features were systematically examined at escape genes (escapees) using mouse allelic systems with skewed XCI to distinguish the inactive X (Xi) and active X (Xa) chromosomes. We found that six constitutive and two facultative escapees are located inside 30-800 kb domains marked by convergent arrays of CTCF binding sites, consistent with the formation of chromatin loops. Facultative escapees show clear differences in CTCF binding depending on their XCI status in specific cell types/tissues. In addition, sets of strong and in some cases divergent CTCF binding sites located at the boundary between an escapee and its adjacent neighbors subject to XCI would also help insulate domains. Indeed, deletion but not inversion of a CTCF binding site at the boundary between the facultative escapee Car5b and its silent neighbor Siah1b results in a dramatic reduction of Car5b escape. This is associated with reduced CTCF and cohesin binding, which indicates loss of looping and insulation and is supported by 3C combined with Hi-C analysis. In addition, enrichment in the repressive mark H3K27me3 invades the Car5b domain in deleted cells, consistent with loss of expression from the Xi. In contrast, cells with an inversion of the CTCF binding site retain CTCF and cohesin binding, as well as looping, in line with persistence of escape. Interestingly, the levels of escape increase in cells with deletion of either Dxz4, which disrupts the Xi-specific compact 3D structure, or Firre, which results in lower H3K27me3 enrichment on the Xi, indicating that the structural and epigenetic features of the Xi constrain escape from XCI in wild type conditions. Conclusions: Taken together, our findings support the idea that escape from XCI in female somatic cells is modulated by both the topological insulation of domains via CTCF binding and the surrounding heterochromatin environment.

Background: 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. KDM6A mutations have been implicated in congenital disorders such as Kabuki Syndrome, as well as in sex differences in development and cancer. Methods: Kdm6a was knocked out (KO) using CRISPR/Cas9 gene editing in hybrid female mouse embryonic stem (ES) cells derived either from a 129 × Mus castaneus (cast) cross or a BL6 x cast cross. In one of the lines a transcriptional stop signal inserted in Tsix results in completely skewed X silencing upon differentiation. The effects of both homozygous and heterozygous Kdm6a KO on Xist expression during the onset of XCI were measured by RT-PCR and RNA-FISH. Changes in gene expression and in H3K27me3 enrichment were investigated using allele-specific RNA-seq and Cut&Run, respectively. KDM6A binding to the Xist gene was characterized by Cut&Run. Results: We observed impaired upregulation of Xist and reduced coating of the Xi during early stages of differentiation in Kdm6a KO cells, both homozygous and heterozygous, suggesting a threshold effect of KDM6A. This was associated with aberrant overexpression of genes from the Xi after differentiation, indicating loss of X inactivation potency. Consistent with KDM6A having a direct role in Xist regulation, we found that the histone demethylase binds to the Xist promoter and KO cells show an increase in H3K27me3 at Xist, consistent with reduced expression. Conclusions: These results reveal a novel female-specific role for the X-linked histone demethylase, KDM6A in the initiation of XCI through histone demethylase-dependent activation of Xist during early differentiation. Plain language summary: X chromosome inactivation is a female-specific mechanism that evolved to balance sex-linked gene dosage between females (XX) and males (XY) by silencing one X chromosome in females. X inactivation begins with the upregulation of the long noncoding RNA Xist on the future inactive X chromosome. While most genes become silenced on the inactive X chromosome some genes escape inactivation and thus have higher expression in females compared to males, suggesting that escape genes may have female-specific functions. One such gene encodes the histone demethylase KDM6A which function is to turn on gene expression by removing repressive histone modifications. In this study, we investigated the role of KDM6A in the regulation of Xist expression during the onset of X inactivation. We found that KDM6A binds to the Xist gene to remove repressive histone marks and facilitate its expression in early development. Indeed, depletion of KDM6A prevents upregulation of Xist due to abnormal persistence of repressive histone modifications. In turn, this results in aberrant overexpression of genes from the inactive X chromosome. Our findings point to a novel mechanism of Xist regulation during the initiation of X inactivation, which may lead to new avenues of treatment to alleviate congenital disorders such as Kabuki syndrome and sex-biased immune disorders where X-linked gene dosage is perturbed.

RNA molecules form complex networks of molecular interactions that are central to their function and to cellular architecture. But these interaction networks are difficult to probe in situ. Here, we introduce Oligonucleotide-mediated proximity-interactome MAPping (O-MAP), a method for elucidating the biomolecules near an RNA of interest, within its native context. O-MAP uses RNA-fluorescence in situ hybridization-like oligonucleotide probes to deliver proximity-biotinylating enzymes to a target RNA in situ, enabling nearby molecules to be enriched by streptavidin pulldown. This induces exceptionally precise biotinylation that can be easily optimized and ported to new targets or sample types. Using the noncoding RNAs 47S, 7SK and Xist as models, we develop O-MAP workflows for discovering RNA-proximal proteins, transcripts and genomic loci, yielding a multiomic characterization of these RNAs’ subcellular compartments and new regulatory interactions. O-MAP requires no genetic manipulation, uses exclusively off-the-shelf parts and requires orders of magnitude fewer cells than established methods, making it accessible to most laboratories.

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.