Robust enhancer-gene regulation identified by single-cell transcriptomes and epigenomes

Single cell multiome analysis of the bovine placenta identifies gene regulatory networks in trophoblast differentiation†

A central determinant of successful reproduction is pregnancy establishment and maintenance that relies on proper development of the conceptus (embryo/fetus and associated extraembryonic membranes including the placenta). Pregnancy loss in cattle can be caused by inadequate development and differentiation of the placenta. However, the cellular and molecular mechanisms regulating bovine placenta development and, particularly, trophoblast differentiation are not well understood. Recent single-cell RNA-seq analyses revealed dynamic changes in cell populations and gene expression patterns during bovine placental development. Here, the chromatin accessibility landscape across diverse cell populations was determined in the developing (Day 40) and mature (Day 170) bovine placenta using the 10X Genomics multiome (snRNA-seq and snATAC-seq) platform. Analyses revealed distinct trophoblast, mesenchyme, endothelial, immune, and epithelial cell populations characterized by unique gene expression and chromatin accessibility signatures. ATAC-seq peaks defined open chromatin regions, facilitating the identification of transcription factor binding sites and candidate gene regulatory networks involved with trophoblast differentiation. Several transcription factors, known for their involvement in trophoblast differentiation in other mammalian species, were identified as candidate regulators of uninucleate to binucleate trophoblast differentiation. This study adds to our foundational understanding of gene regulation and expression in the placenta, offering insights into the mechanisms governing pregnancy loss in cattle.

Cis-Regulation of the CFTR Gene in Pancreatic Cells

Genome organization is essential for precise spatial and temporal gene expression and relies on interactions between promoters and distal cis-regulatory elements (CREs), which constitute ~8% of the human genome. For the cystic fibrosis transmembrane conductance regulator (CFTR) gene, tissue-specific expression, especially in the pancreas, remains poorly understood. Unraveling its regulation could clarify the clinical heterogeneity observed in cystic fibrosis and CFTR-related disorders. To understand the role of 3D chromatin architecture in establishing tissue-specific expression of the CFTR gene, we mapped chromatin interactions and epigenomic regulation in Capan-1 pancreatic cells. Candidate CREs are validated by luciferase reporter assay and CRISPR knock-out. We identified active CREs not only around the CFTR gene but also outside the topologically associating domain (TAD). We demonstrate the involvement of multiple CREs upstream and downstream of the CFTR gene and reveal a cooperative effect of the -44 kb, -35 kb, +15.6 kb, and +37.7 kb regions, which share common predicted transcription factor (TF) motifs. We also extend our analysis to compare 3D chromatin conformation in intestinal and pancreatic cells, providing valuable insights into the tissue specificity of CREs in regulating CFTR gene expression.

Chromatin State Maps of Blood Pressure-Relevant Renal Segments Reveal Potential Regulatory Role for SNPs

BACKGROUND

Hypertension or elevated blood pressure (BP) is a worldwide clinical challenge and the leading primary risk factor for kidney dysfunctions, heart failure, and cerebrovascular disease. The kidney is a central regulator of BP by maintaining sodium-water balance. Multiple genome-wide association studies revealed that BP is a heritable quantitative trait, modulated by several genetic, epigenetic, and environmental factors. The SNPs identified in genome-wide association studies predominantly (>95%) reside within noncoding genomic regions, making it difficult to understand how they regulate BP. Given the central role of the kidney in regulating BP, we hypothesized that chromatin-accessible regions in renal tissue would be enriched for BP-associated single nucleotide polymorphisms.

METHODS

We manually dissected 2 important kidney segments that maintain the sodium-water balance: proximal tubules and medullary thick ascending limbs from the human and rat kidneys. To delineate their chromatin and transcriptomic profiles, we performed the assay for transposase-accessible chromatin and RNA sequencing, respectively.

RESULTS

The chromatin accessibility maps revealed the shared and unique cis-regulatory elements that modulate the chromatin accessibility in proximal tubule and medullary thick ascending limbs of humans and rats. We developed a visualization tool to compare the cross-species epigenomic maps to identify potential regulatory targets for hypertension pathogenesis. We also identified a significant enrichment of BP-associated single nucleotide polymorphisms (1064 for human proximal tubule and 1172 for human medullary thick ascending limbs) within accessible chromatin regions of both segments, including rs1173771 and rs1421811 at the NPR3 locus and rs1800470 at the TGFb1 locus.

CONCLUSIONS

Collectively, this study lays a foundation for interrogating how intergenic single nucleotide polymorphisms may regulate polygenic traits such as BP.

GEEES: inferring cell-specific gene-enhancer interactions from multi-modal single-cell data

MOTIVATION

Gene-enhancer interactions are central to transcriptional regulation. Current multi-modal single-cell datasets that profile transcriptome and chromatin accessibility simultaneously in a single cell are yielding opportunities to infer gene-enhancer associations in a cell type specific manner. Computational efforts for such multi-modal single-cell datasets thus far focused on methods for identification and refinement of cell types and trajectory construction. While initial attempts for inferring gene-enhancer interactions have emerged, these have not been evaluated against benchmark datasets that materialized from bulk genomic experiments. Furthermore, existing approaches are limited to inferring gene-enhancer associations at the level of grouped cells as opposed to individual cells, thereby ignoring regulatory heterogeneity among the cells.

RESULTS

We present a new approach, GEEES for "Gene EnhancEr IntEractions from Multi-modal Single Cell Data," for inferring gene-enhancer associations at the single-cell level using multi-modal single-cell transcriptome and chromatin accessibility data. We evaluated GEEES alongside several multivariate regression-based alternatives we devised and state-of-the-art methods using a large number of benchmark datasets, providing a comprehensive assessment of current approaches. This analysis revealed significant discrepancies between gold-standard interactions and gene-enhancer associations derived from multi-modal single-cell data. Notably, incorporating gene-enhancer distance into the analysis markedly improved performance across all methods, positioning GEEES as a leading approach in this domain. While the overall improvement in performance metrics by GEEES is modest, it provides enhanced cell representation learning which can be leveraged for more effective downstream analysis. Furthermore, our review of existing experimentally driven benchmark datasets uncovers their limited concordance, underscoring the necessity for new high-throughput experiments to validate gene-enhancer interactions inferred from single-cell data.

AVAILABILITY AND IMPLEMENTATION

https://github.com/keleslab/GEEES.

Enhlink infers distal and context-specific enhancer-promoter linkages

Enhlink is a computational tool for scATAC-seq data analysis, facilitating precise interrogation of enhancer function at the single-cell level. It employs an ensemble approach incorporating technical and biological covariates to infer condition-specific regulatory DNA linkages. Enhlink can integrate multi-omic data for enhanced specificity, when available. Evaluation with simulated and real data, including multi-omic datasets from the mouse striatum and novel promoter capture Hi-C data, demonstrate that Enhlink outperfoms alternative methods. Coupled with eQTL analysis, it identified a putative super-enhancer in striatal neurons. Overall, Enhlink offers accuracy, power, and potential for revealing novel biological insights in gene regulation.

Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain

Cytosine DNA methylation is essential in brain development and is implicated in various neurological disorders. Understanding DNA methylation diversity across the entire brain in a spatial context is fundamental for a complete molecular atlas of brain cell types and their gene regulatory landscapes. Here we used single-nucleus methylome sequencing (snmC-seq3) and multi-omic sequencing (snm3C-seq)1 technologies to generate 301,626 methylomes and 176,003 chromatin conformation-methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell taxonomy with 4,673 cell groups and 274 cross-modality-annotated subclasses. We identified 2.6 million differentially methylated regions across the genome that represent potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide spatial transcriptomics data validated the association of spatial epigenetic diversity with transcription and improved the anatomical mapping of our epigenetic datasets. Furthermore, chromatin conformation diversities occurred in important neuronal genes and were highly associated with DNA methylation and transcription changes. Brain-wide cell-type comparisons enabled the construction of regulatory networks that incorporate transcription factors, regulatory elements and their potential downstream gene targets. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a whole-brain SMART-seq2 dataset. Our study establishes a brain-wide, single-cell DNA methylome and 3D multi-omic atlas and provides a valuable resource for comprehending the cellular-spatial and regulatory genome diversity of the mouse brain.

Droplet-based single-cell joint profiling of histone modifications and transcriptomes

We previously reported Paired-Tag, a combinatorial indexing-based method that can simultaneously map histone modifications and gene expression at single-cell resolution at scale. However, the lengthy procedure of Paired-Tag has hindered its general adoption in the community. To address this bottleneck, we developed a droplet-based Paired-Tag protocol that is faster and more accessible than the previous method. Using cultured mammalian cells and primary brain tissues, we demonstrate its superior performance at identifying candidate cis-regulatory elements and associating their dynamic chromatin state to target gene expression in each constituent cell type in a complex tissue.