Nuclear gene proximity and protein interactions shape transcript covariations in mammalian single cells

3D chromatin architecture, BRD4, and Mediator have distinct roles in regulating genome-wide transcriptional bursting and gene network

Discontinuous transcription is evolutionarily conserved and a fundamental feature of gene regulation; yet, the exact mechanisms underlying transcriptional bursting are unresolved. Analyses of bursting transcriptome-wide have focused on the role of cis-regulatory elements, but other factors that regulate this process remain elusive. We applied mathematical modeling to single-cell RNA sequencing data to infer bursting dynamics transcriptome-wide under multiple conditions to identify possible molecular mechanisms. We found that Mediator complex subunit 26 (MED26) primarily regulates frequency, MYC regulates burst size, while cohesin and Bromodomain-containing protein 4 (BRD4) can modulate both. Despite comparable effects on RNA levels among these perturbations, acute depletion of MED26 had the most profound impact on the entire gene regulatory network, acting downstream of chromatin spatial architecture and without affecting TATA box-binding protein (TBP) recruitment. These results indicate that later steps in the initiation of transcriptional bursts are primary nodes for integrating gene networks in single cells.

Molecular models of bidirectional promoter regulation

Approximately 11% of human genes are transcribed by a bidirectional promoter (BDP), defined as two genes with <1 kb between their transcription start sites. Despite their evolutionary conservation and enrichment for housekeeping genes and oncogenes, the regulatory role of BDPs remains unclear. BDPs have been suggested to facilitate gene coregulation and/or decrease expression noise. This review discusses these potential regulatory functions through the context of six prospective underlying mechanistic models: a single nucleosome free region, shared transcription factor/regulator binding, cooperative negative supercoiling, bimodal histone marks, joint activation by enhancer(s), and RNA-mediated recruitment of regulators. These molecular mechanisms may act independently and/or cooperatively to facilitate the coregulation and/or decreased expression noise predicted of BDPs.

Cohesin prevents cross-domain gene coactivation

The contrast between the disruption of genome topology after cohesin loss and the lack of downstream gene expression changes instigates intense debates regarding the structure-function relationship between genome and gene regulation. Here, by analyzing transcriptome and chromatin accessibility at the single-cell level, we discover that, instead of dictating population-wide gene expression levels, cohesin supplies a general function to neutralize stochastic coexpression tendencies of cis-linked genes in single cells. Notably, cohesin loss induces widespread gene coactivation and chromatin co-opening tens of million bases apart in cis. Spatial genome and protein imaging reveals that cohesin prevents gene co-bursting along the chromosome and blocks spatial mixing of transcriptional hubs. Single-molecule imaging shows that cohesin confines the exploration of diverse enhancer and core promoter binding transcriptional regulators. Together, these results support that cohesin arranges nuclear topology to control gene coexpression in single cells.

Rapid adaptation of cellular metabolic rate to the MicroRNA complements of mammals and its relevance to the evolution of endothermy

The metabolic efficiency of mammalian cells depends on the attenuation of intrinsic translation noise by microRNAs. We devised a metric of cellular metabolic rate (cMR), rMR/Mexp optimally fit to the number of microRNA families (mirFam), that is robust to variation in mass and sensitive to body temperature (Tb), consistent with the heat dissipation limit theory of Speakman and Król (2010). Using mirFam as predictor, an Ornstein-Uhlenbeck process of stabilizing selection, with an adaptive shift at the divergence of Boreoeutheria, accounted for 95% of the variation in cMR across mammals. Branchwise rates of evolution of cMR, mirFam and Tb concurrently increased 6- to 7-fold at the divergence of Boreoeutheria, independent of mass. Cellular MR variation across placental mammals was also predicted by the sum of model conserved microRNA-target interactions, revealing an unexpected degree of integration of the microRNA-target apparatus into the energy economy of the mammalian cell.

Diffusion-enhanced characterization of 3D chromatin structure reveals its linkage to gene regulatory networks and the interactome

The interactome networks at the DNA, RNA, and protein levels are crucial for cellular functions, and the diverse variations of these networks are heavily involved in the establishment of different cell states. We have developed a diffusion-based method, Hi-C to geometry (CTG), to obtain reliable geometric information on the chromatin from Hi-C data. CTG produces a consistent and reproducible framework for the 3D genomic structure and provides a reliable and quantitative understanding of the alterations of genomic structures under different cellular conditions. The genomic structure yielded by CTG serves as an architectural blueprint of the dynamic gene regulatory network, based on which cell-specific correspondence between gene-gene and corresponding protein-protein physical interactions, as well as transcription correlation, is revealed. We also find that gene fusion events are significantly enriched between genes of short CTG distances and are thus close in 3D space. These findings indicate that 3D chromatin structure is at least partially correlated with downstream processes such as transcription, gene regulation, and even regulatory networking through affecting protein-protein interactions.

New insights into the centrosome-associated spliceosome components as regulators of ciliogenesis and tissue identity

Biomolecular condensates are membrane-less assemblies of proteins and nucleic acids. Centrosomes are biomolecular condensates that play a crucial role in nuclear division, cytoskeletal remodeling, and cilia formation in animal cells. Spatial omics technology is providing new insights into the dynamic exchange of spliceosome components between the nucleus and the centrosome/cilium. Intriguingly, centrosomes are emerging as cytoplasmic sites for information storage, enriched with RNA molecules and RNA-processing proteins. Furthermore, growing evidence supports the view that nuclear spliceosome components assembled at the centrosome function as potential coordinators of splicing subprograms, pluripotency, and cell differentiation. In this article, we first discuss the current understanding of the centrosome/cilium complex, which controls both stem cell differentiation and pluripotency. We next explore the molecular mechanisms that govern splicing factor assembly and disassembly around the centrosome and examine how RNA processing pathways contribute to ciliogenesis. Finally, we discuss numerous unresolved compelling questions regarding the centrosome-associated spliceosome components and transcript variants within the cytoplasm as sources of RNA-based secondary messages in the regulation of cell identity and cell fate determination. This article is categorized under: RNA-Based Catalysis > RNA Catalysis in Splicing and Translation RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes RNA Processing > Splicing Regulation/Alternative Splicing RNA Processing > RNA Processing.

Genes enriched in A/T-ending codons are co-regulated and conserved across mammals

Codon usage influences gene expression distinctly depending on the cell context. Yet, the importance of codon bias in the simultaneous turnover of specific groups of protein-coding genes remains to be investigated. Here, we find that genes enriched in A/T-ending codons are expressed more coordinately in general and across tissues and development than those enriched in G/C-ending codons. tRNA abundance measurements indicate that this coordination is linked to the expression changes of tRNA isoacceptors reading A/T-ending codons. Genes with similar codon composition are more likely to be part of the same protein complex, especially for genes with A/T-ending codons. The codon preferences of genes with A/T-ending codons are conserved among mammals and other vertebrates. We suggest that this orchestration contributes to tissue-specific and ontogenetic-specific expression, which can facilitate, for instance, timely protein complex formation.

Synthetic analysis of chromatin tracing and live-cell imaging indicates pervasive spatial coupling between genes

The role of the spatial organization of chromosomes in directing transcription remains an outstanding question in gene regulation. Here, we analyze two recent single-cell imaging methodologies applied across hundreds of genes to systematically analyze the contribution of chromosome conformation to transcriptional regulation. Those methodologies are (1) single-cell chromatin tracing with super-resolution imaging in fixed cells; and (2) high-throughput labeling and imaging of nascent RNA in living cells. Specifically, we determine the contribution of physical distance to the coordination of transcriptional bursts. We find that individual genes adopt a constrained conformation and reposition toward the centroid of the surrounding chromatin upon activation. Leveraging the variability in distance inherent in single-cell imaging, we show that physical distance - but not genomic distance - between genes on individual chromosomes is the major factor driving co-bursting. By combining this analysis with live-cell imaging, we arrive at a corrected transcriptional correlation of [Formula: see text] for genes separated by < 400 nm. We propose that this surprisingly large correlation represents a physical property of human chromosomes and establishes a benchmark for future experimental studies.

Genes that are Used Together are More Likely to be Fused Together in Evolution by Mutational Mechanisms: A Bioinformatic Test of the Used-Fused Hypothesis

Cases of parallel or recurrent gene fusions in evolution as well as in genetic disease and cancer are difficult to explain, because unlike point mutations, they can require the repetition of a similar configuration of multiple breakpoints rather than the repetition of a single point mutation. The used-together-fused-together hypothesis holds that genes that are used together repeatedly and persistently in a specific context are more likely to undergo fusion mutation in the course of evolution for mechanistic reasons. This hypothesis offers to explain gene fusion in both evolution and disease under one umbrella. Using bioinformatic data, we tested this hypothesis against alternatives, including that all gene pairs can fuse by random mutation, but among pairs thus fused, those that had interacted previously are more likely to be favored by selection. Results show that across multiple measures of gene interaction, human genes whose orthologs are fused in one or more species are more likely to interact with each other than random pairs of genes of the same genomic distance between pair members; that an overlap exists between genes that fused in the course of evolution in non-human species and genes that undergo fusion in human cancers; and that across six primate species studied, fusions predominate over fissions and exhibit substantial evolutionary parallelism. Together, these results support the used-together-fused-together hypothesis over its alternatives. Multiple implications are discussed, including the relevance of mutational mechanisms to the evolution of genome organization, to the distribution of fitness effects of mutation, to evolutionary parallelism and more.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11692-022-09579-9.

Human variation in population-wide gene expression data predicts gene perturbation phenotype

Population-scale datasets of healthy individuals capture genetic and environmental factors influencing gene expression. The expression variance of a gene of interest (GOI) can be exploited to set up a quasi loss- or gain-of-function "in population" experiment. We describe here an approach, huva (human variation), taking advantage of population-scale multi-layered data to infer gene function and relationships between phenotypes and expression. Within a reference dataset, huva derives two experimental groups with LOW or HIGH expression of the GOI, enabling the subsequent comparison of their transcriptional profile and functional parameters. We demonstrate that this approach robustly identifies the phenotypic relevance of a GOI allowing the stratification of genes according to biological functions, and we generalize this concept to almost 16,000 genes in the human transcriptome. Additionally, we describe how huva predicts monocytes to be the major cell type in the pathophysiology of STAT1 mutations, evidence validated in a clinical cohort.

Shared regulation and functional relevance of local gene co-expression revealed by single cell analysis

Most human genes are co-expressed with a nearby gene. Previous studies have revealed this local gene co-expression to be widespread across chromosomes and across dozens of tissues. Yet, so far these studies used bulk RNA-seq, averaging gene expression measurements across millions of cells, thus being unclear if this co-expression stems from transcription events in single cells. Here, we leverage single cell datasets in >85 individuals to identify gene co-expression across cells, unbiased by cell-type heterogeneity and benefiting from the co-occurrence of transcription events in single cells. We discover >3800 co-expressed gene pairs in two human cell types, induced pluripotent stem cells (iPSCs) and lymphoblastoid cell lines (LCLs) and (i) compare single cell to bulk RNA-seq in identifying local gene co-expression, (ii) show that many co-expressed genes – but not the majority – are composed of functionally related genes and (iii) using proteomics data, provide evidence that their co-expression is maintained up to the protein level. Finally, using single cell RNA-sequencing (scRNA-seq) and single cell ATAC-sequencing (scATAC-seq) data for the same single cells, we identify gene-enhancer associations and reveal that >95% of co-expressed gene pairs share regulatory elements. These results elucidate the potential reasons for co-expression in single cell gene regulatory networks and warrant a deeper study of shared regulatory elements, in view of explaining disease comorbidity due to affecting several genes. Our in-depth view of local gene co-expression and regulatory element co-activity advances our understanding of the shared regulatory architecture between genes.

Using single-cell data from cell lines, the co-expression of genes and co-activity of regulatory elements is analyzed, providing insight into shared architecture and regulation between genes.

Cotranslational Mechanisms of Protein Biogenesis and Complex Assembly in Eukaryotes

The formation of protein complexes is crucial to most biological functions. The cellular mechanisms governing protein complex biogenesis are not yet well understood, but some principles of cotranslational and posttranslational assembly are beginning to emerge. In bacteria, this process is favored by operons encoding subunits of protein complexes. Eukaryotic cells do not have polycistronic mRNAs, raising the question of how they orchestrate the encounter of unassembled subunits. Here we review the constraints and mechanisms governing eukaryotic co- and posttranslational protein folding and assembly, including the influence of elongation rate on nascent chain targeting, folding, and chaperone interactions. Recent evidence shows that mRNAs encoding subunits of oligomeric assemblies can undergo localized translation and form cytoplasmic condensates that might facilitate the assembly of protein complexes. Understanding the interplay between localized mRNA translation and cotranslational proteostasis will be critical to defining protein complex assembly in vivo.

Modeling microRNA-driven post-transcriptional regulation using exon-intron split analysis in pigs

The contribution of microRNAs (miRNAs) to mRNA post-transcriptional regulation has often been explored by the post hoc selection of downregulated genes and determining whether they harbor binding sites for miRNAs of interest. This approach, however, does not discriminate whether these mRNAs are also downregulated at the transcriptional level. Here, we have characterized the transcriptional and post-transcriptional changes in mRNA expression in two porcine tissues: gluteus medius muscle of fasted and fed Duroc gilts and adipose tissue of lean and obese Duroc-Göttingen minipigs. Exon-intron split analysis of RNA-seq data allowed us to identify downregulated mRNAs with high post-transcriptional signals in fed or obese states, and we assessed whether they harbor binding sites for upregulated miRNAs in any of these two physiological states. We found 26 downregulated mRNAs with high post-transcriptional signals in the muscle of fed gilts and 21 of these were predicted targets of miRNAs upregulated in fed pigs. For adipose tissue, 44 downregulated mRNAs in obese minipigs displayed high post-transcriptional signals, and 25 of these were predicted targets of miRNAs upregulated in the obese state. These results suggest that the contribution of miRNAs to mRNA repression is more prominent in the skeletal muscle system. Finally, we identified several genes that may play relevant roles in the energy homeostasis of the pig skeletal muscle (DKK2 and PDK4) and adipose (SESN3 and ESRRG) tissues. By differentiating transcriptional from post-transcriptional changes in mRNA expression, exon-intron split analysis provides a valuable view of the regulation of gene expression, complementary to canonical differential expression analyses.

The limits of human microRNA annotation have been met

Over the last few years, the number of microRNAs in the human genome has become a controversially debated issue. Several publications reported thousands of putative novel microRNAs not included in the curated microRNA gene database MirGeneDB and the repository miRBase. Recently, by using sequencing of ∼300 human tissues and cell lines, the human RNA atlas, an expanded inventory of human RNA annotations, was published, reporting thousands of putative microRNAs. We, the developers of established microRNA prediction tools and hosts of MirGeneDB, raise concerns about the frequently applied prediction and functional validation strategies, briefly discussing the drawbacks of false positive detections. By means of quantifying well-established biogenesis-derived features, we show that the reported novel microRNAs essentially represent false-positives and argue that the human microRNA complement, at about 550 microRNA genes, is already near complete. Output of available tools must be curated as false predictions will misguide scientists looking for biomarkers or therapeutic targets.

A Deep Insight Into Regulatory T Cell Metabolism in Renal Disease: Facts and Perspectives

Kidney disease encompasses a complex set of diseases that can aggravate or start systemic pathophysiological processes through their complex metabolic mechanisms and effects on body homoeostasis. The prevalence of kidney disease has increased dramatically over the last two decades. CD4⁺CD25⁺ regulatory T (Treg) cells that express the transcription factor forkhead box protein 3 (Foxp3) are critical for maintaining immune homeostasis and preventing autoimmune disease and tissue damage caused by excessive or unnecessary immune activation, including autoimmune kidney diseases. Recent studies have highlighted the critical role of metabolic reprogramming in controlling the plasticity, stability, and function of Treg cells. They are also likely to play a vital role in limiting kidney transplant rejection and potentially promoting transplant tolerance. Metabolic pathways, such as mitochondrial function, glycolysis, lipid synthesis, glutaminolysis, and mammalian target of rapamycin (mTOR) activation, are involved in the development of renal diseases by modulating the function and proliferation of Treg cells. Targeting metabolic pathways to alter Treg cells can offer a promising method for renal disease therapy. In this review, we provide a new perspective on the role of Treg cell metabolism in renal diseases by presenting the renal microenvironment、relevant metabolites of Treg cell metabolism, and the role of Treg cell metabolism in various kidney diseases.

baredSC: Bayesian approach to retrieve expression distribution of single-cell data

Background

The number of studies using single-cell RNA sequencing (scRNA-seq) is constantly growing. This powerful technique provides a sampling of the whole transcriptome of a cell. However, sparsity of the data can be a major hurdle when studying the distribution of the expression of a specific gene or the correlation between the expressions of two genes.

Results

We show that the main technical noise associated with these scRNA-seq experiments is due to the sampling, i.e., Poisson noise. We present a new tool named baredSC, for Bayesian Approach to Retrieve Expression Distribution of Single-Cell data, which infers the intrinsic expression distribution in scRNA-seq data using a Gaussian mixture model. baredSC can be used to obtain the distribution in one dimension for individual genes and in two dimensions for pairs of genes, in particular to estimate the correlation in the two genes’ expressions. We apply baredSC to simulated scRNA-seq data and show that the algorithm is able to uncover the expression distribution used to simulate the data, even in multi-modal cases with very sparse data. We also apply baredSC to two real biological data sets. First, we use it to measure the anti-correlation between Hoxd13 and Hoxa11, two genes with known genetic interaction in embryonic limb. Then, we study the expression of Pitx1 in embryonic hindlimb, for which a trimodal distribution has been identified through flow cytometry. While other methods to analyze scRNA-seq are too sensitive to sampling noise, baredSC reveals this trimodal distribution.

Conclusion

baredSC is a powerful tool which aims at retrieving the expression distribution of few genes of interest from scRNA-seq data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04507-8.

Regulatory mechanisms ensuring coordinated expression of functionally related genes

Coordinated spatiotemporal expression of large sets of genes is required for the development and homeostasis of organisms. To achieve this goal, organisms use myriad strategies where they form operons, utilize bidirectional promoters, cluster genes, share enhancers among genes by DNA looping, and form topologically associated domains and transcriptional condensates. Coexpression achieved by these different strategies is hypothesized to have functional importance in minimizing gene expression variability, establishing dosage balance to ensure stoichiometry of protein complexes, and minimizing accumulation of toxic intermediate metabolites. By combining gene-editing tools with computational modeling, recent studies tested the advantages of adjacent genes located in pairs and clusters. We propose that with the advancement of gene editing, single-cell sequencing, and imaging tools, one could readily test the functional importance of different coexpression strategies in a variety of biological processes.

Regulation of gene expression via translational buffering

Translation of an mRNA represents a critical step during the expression of protein-coding genes. As mechanisms governing post-transcriptional regulation of gene expression are progressively unveiled, it is becoming apparent that transcriptional programs are not fully reflected in the proteome. Herein, we highlight a previously underappreciated post-transcriptional mode of regulation of gene expression termed translational buffering. In principle, translational buffering opposes the impact of alterations in mRNA levels on the proteome. We further describe three types of translational buffering: compensation, which maintains protein levels e.g. across species or individuals; equilibration, which retains pathway stoichiometry; and offsetting, which acts as a reversible mechanism that maintains the levels of selected subsets of proteins constant despite genetic alteration and/or stress-induced changes in corresponding mRNA levels. While mechanisms underlying compensation and equilibration have been reviewed elsewhere, the principal focus of this review is on the less-well understood mechanism of translational offsetting. Finally, we discuss potential roles of translational buffering in homeostasis and disease.