Precise modulation of transcription factor levels identifies features underlying dosage sensitivity

The evolution of developmental biology through conceptual and technological revolutions

Developmental biology-the study of the processes by which cells, tissues, and organisms develop and change over time-has entered a new golden age. After the molecular genetics revolution in the 80s and 90s and the diversification of the field in the early 21st century, we have entered a phase when powerful technologies provide new approaches and open unexplored avenues. Progress in the field has been accelerated by advances in genomics, imaging, engineering, and computational biology and by emerging model systems ranging from tardigrades to organoids. We summarize how revolutionary technologies have led to remarkable progress in understanding animal development. We describe how classic questions in gene regulation, pattern formation, morphogenesis, organogenesis, and stem cell biology are being revisited. We discuss the connections of development with evolution, self-organization, metabolism, time, and ecology. We speculate how developmental biology might evolve in an era of synthetic biology, artificial intelligence, and human engineering.

Trans-eQTL hotspots shape complex traits by modulating cellular states

Regulatory genetic variation shapes gene expression, providing an important mechanism connecting DNA variation and complex traits. The causal relationships between gene expression and complex traits remain poorly understood. Here, we integrated transcriptomes and 46 genetically complex growth traits in a large cross between two strains of the yeast Saccharomyces cerevisiae. We discovered thousands of genetic correlations between gene expression and growth, suggesting potential functional connections. Local regulatory variation was a minor source of these genetic correlations. Instead, genetic correlations tended to arise from multiple independent trans-acting regulatory loci. Trans-acting hotspots that affect the expression of numerous genes accounted for particularly large fractions of genetic growth variation and of genetic correlations between gene expression and growth. Genes with genetic correlations were enriched for similar biological processes across traits, but with heterogeneous direction of effect. Our results reveal how trans-acting regulatory hotspots shape complex traits by altering cellular states.

Transcriptome-wide characterization of genetic perturbations

Single cell CRISPR screens such as Perturb-seq enable transcriptomic profiling of genetic perturbations at scale. However, the data produced by these screens are often noisy due to cost and technical constraints, limiting power to detect true effects with conventional differential expression analyses. Here, we introduce TRanscriptome-wide Analysis of Differential Expression (TRADE), a statistical framework which estimates the transcriptome-wide distribution of true differential expression effects from noisy gene-level measurements. Within TRADE, we derive multiple novel, interpretable statistical metrics, including the "transcriptome-wide impact", an estimator of the overall transcriptional effect of a perturbation which is stable across sampling depths. We analyze new and published large-scale Perturb-seq datasets to show that many true transcriptional effects are not statistically significant, but detectable in aggregate with TRADE. In a genome-scale Perturb-seq screen, we find that a typical gene perturbation affects an estimated 45 genes, whereas a typical essential gene perturbation affects over 500 genes. An advantage of our approach is its ability to compare the transcriptomic effects of genetic perturbations across contexts and dosages despite differences in power. We use this ability to identify perturbations with cell-type dependent effects and to find examples of perturbations where transcriptional responses are not only larger in magnitude, but also qualitatively different, as a function of dosage. Lastly, we expand our analysis to case/control comparison of gene expression for neuropsychiatric conditions, finding that transcriptomic effect correlations are greater than genetic correlations for these diagnoses. TRADE lays an analytic foundation for the systematic comparison of genetic perturbation atlases, as well as differential expression experiments more broadly.

Exploring penetrance of clinically relevant variants in over 800,000 humans from the Genome Aggregation Database

Incomplete penetrance, or absence of disease phenotype in an individual with a disease-associated variant, is a major challenge in variant interpretation. Studying individuals with apparent incomplete penetrance can shed light on underlying drivers of altered phenotype penetrance. Here, we investigate clinically relevant variants from ClinVar in 807,162 individuals from the Genome Aggregation Database (gnomAD), demonstrating improved representation in gnomAD version 4. We then conduct a comprehensive case-by-case assessment of 734 predicted loss of function variants (pLoF) in 77 genes associated with severe, early-onset, highly penetrant haploinsufficient disease. We identified explanations for the presumed lack of disease manifestation in 701 of the variants (95%). Individuals with unexplained lack of disease manifestation in this set of disorders rarely occur, underscoring the need and power of deep case-by-case assessment presented here to minimize false assignments of disease risk, particularly in unaffected individuals with higher rates of secondary properties that result in rescue.

Mapping genes for human face shape: exploration of univariate phenotyping strategies

Human facial shape, while strongly heritable, involves both genetic and structural complexity, necessitating precise phenotyping for accurate assessment. Common phenotyping strategies include simplifying 3D facial features into univariate traits such as anthropometric measurements (e.g., inter-landmark distances), unsupervised dimensionality reductions (e.g., principal component analysis (PCA) and auto-encoder (AE) approaches), and assessing resemblance to particular facial gestalts (e.g., syndromic facial archetypes). This study provides a comparative assessment of these strategies in genome-wide association studies (GWASs) of 3D facial shape. Specifically, we investigated inter-landmark distances, PCA and AE-derived latent dimensions, and facial resemblance to random, extreme, and syndromic gestalts within a GWAS of 8,426 individuals of recent European ancestry. Inter-landmark distances exhibit the highest SNP-based heritability as estimated via LD score regression, followed by AE dimensions. Conversely, resemblance scores to extreme and syndromic facial gestalts display the lowest heritability, in line with expectations. Notably, the aggregation of multiple GWASs on facial resemblance to random gestalts reveals the highest number of independent genetic loci. This novel, easy-to-implement phenotyping approach holds significant promise for capturing genetically relevant morphological traits derived from complex biomedical imaging datasets, and its applications extend beyond faces. Nevertheless, these different phenotyping strategies capture different genetic influences on craniofacial shape. Thus, it remains valuable to explore these strategies individually and in combination to gain a more comprehensive understanding of the genetic factors underlying craniofacial shape and related traits.

Author Summary

Advancements linking variation in the human genome to phenotypes have rapidly evolved in recent decades and have revealed that most human traits are influenced by genetic variants to at least some degree. While many traits, such as stature, are straightforward to acquire and investigate, the multivariate and multipartite nature of facial shape makes quantification more challenging. In this study, we compared the impact of different facial phenotyping approaches on gene mapping outcomes. Our findings suggest that the choice of facial phenotyping method has an impact on apparent trait heritability and the ability to detect genetic association signals. These results offer valuable insights into the importance of phenotyping in genetic investigations, especially when dealing with highly complex morphological traits.

Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage

Deep learning approaches have made significant advances in predicting cell type-specific chromatin patterns from the identity and arrangement of transcription factor (TF) binding motifs. However, most models have been applied in unperturbed contexts, precluding a predictive understanding of how chromatin state responds to TF perturbation. Here, we used transfer learning to train and interpret deep learning models that use DNA sequence to predict, with accuracy approaching experimental reproducibility, how the concentration of two dosage-sensitive TFs (TWIST1, SOX9) affects regulatory element (RE) chromatin accessibility in facial progenitor cells. High-affinity motifs that allow for heterotypic TF co-binding and are concentrated at the center of REs buffer against quantitative changes in TF dosage and strongly predict unperturbed accessibility. In contrast, motifs with low-affinity or homotypic binding distributed throughout REs lead to sensitive responses with minimal contributions to unperturbed accessibility. Both buffering and sensitizing features show signatures of purifying selection. We validated these predictive sequence features using reporter assays and showed that a biophysical model of TF-nucleosome competition can explain the sensitizing effect of low-affinity motifs. Our approach of combining transfer learning and quantitative measurements of the chromatin response to TF dosage therefore represents a powerful method to reveal additional layers of the cis-regulatory code.

CUX1 regulates human hematopoietic stem cell chromatin accessibility via the BAF complex

CUX1 is a homeodomain-containing transcription factor that is essential for the development and differentiation of multiple tissues. CUX1 is recurrently mutated or deleted in cancer, particularly in myeloid malignancies. However, the mechanism by which CUX1 regulates gene expression and differentiation remains poorly understood, creating a barrier to understanding the tumor-suppressive functions of CUX1. Here, we demonstrate that CUX1 directs the BAF chromatin remodeling complex to DNA to increase chromatin accessibility in hematopoietic cells. CUX1 preferentially regulates lineage-specific enhancers, and CUX1 target genes are predictive of cell fate in vivo. These data indicate that CUX1 regulates hematopoietic lineage commitment and homeostasis via pioneer factor activity, and CUX1 deficiency disrupts these processes in stem and progenitor cells, facilitating transformation.

Recalibrating differential gene expression by genetic dosage variance prioritizes functionally relevant genes

Differential expression (DE) analysis is a widely used method for identifying genes that are functionally relevant for an observed phenotype or biological response. However, typical DE analysis includes selection of genes based on a threshold of fold change in expression under the implicit assumption that all genes are equally sensitive to dosage changes of their transcripts. This tends to favor highly variable genes over more constrained genes where even small changes in expression may be biologically relevant. To address this limitation, we have developed a method to recalibrate each gene's differential expression fold change based on genetic expression variance observed in the human population. The newly established metric ranks statistically differentially expressed genes not by nominal change of expression, but by relative change in comparison to natural dosage variation for each gene. We apply our method to RNA sequencing datasets from rare disease and in-vitro stimulus response experiments. Compared to the standard approach, our method adjusts the bias in discovery towards highly variable genes, and enriches for pathways and biological processes related to metabolic and regulatory activity, indicating a prioritization of functionally relevant driver genes. With that, our method provides a novel view on DE and contributes towards bridging the existing gap between statistical and biological significance. We believe that this approach will simplify the identification of disease causing genes and enhance the discovery of therapeutic targets.

Non-linear transcriptional responses to gradual modulation of transcription factor dosage

Genomic loci associated with common traits and diseases are typically non-coding and likely impact gene expression, sometimes coinciding with rare loss-of-function variants in the target gene. However, our understanding of how gradual changes in gene dosage affect molecular, cellular, and organismal traits is currently limited. To address this gap, we induced gradual changes in gene expression of four genes using CRISPR activation and inactivation. Downstream transcriptional consequences of dosage modulation of three master trans-regulators associated with blood cell traits (GFI1B, NFE2, and MYB) were examined using targeted single-cell multimodal sequencing. We showed that guide tiling around the TSS is the most effective way to modulate cis gene expression across a wide range of fold-changes, with further effects from chromatin accessibility and histone marks that differ between the inhibition and activation systems. Our single-cell data allowed us to precisely detect subtle to large gene expression changes in dozens of trans genes, revealing that many responses to dosage changes of these three TFs are non-linear, including non-monotonic behaviours, even when constraining the fold-changes of the master regulators to a copy number gain or loss. We found that the dosage properties are linked to gene constraint and that some of these non-linear responses are enriched for disease and GWAS genes. Overall, our study provides a straightforward and scalable method to precisely modulate gene expression and gain insights into its downstream consequences at high resolution.

Multifaceted effects on even-skipped transcriptional dynamics upon Krüppel dosage changes

Although fluctuations in transcription factor (TF) dosage are often well tolerated, TF dosage modulation can change the target gene expression dynamics and result in significant non-lethal developmental phenotypes. Using MS2/MCP-mediated quantitative live imaging in early Drosophila embryos, we analyzed how changing levels of the gap gene Krüppel (Kr) affects transcriptional dynamics of the pair-rule gene even-skipped (eve). Halving the Kr dosage leads to a transient posterior expansion of the eve stripe 2 and an anterior shift of stripe 5. Surprisingly, the most significant changes are observed in eve stripes 3 and 4, the enhancers of which do not contain Kr-binding sites. In Kr heterozygous embryos, both stripes 3 and 4 display narrower widths, anteriorly shifted boundaries and reduced mRNA production levels. We show that Kr dosage indirectly affects stripe 3 and 4 dynamics by modulating other gap gene dynamics. We quantitatively correlate moderate body segment phenotypes of Kr heterozygotes with spatiotemporal changes in eve expression. Our results indicate that nonlinear relationships between TF dosage and phenotypes underlie direct TF-DNA and indirect TF-TF interactions.

Crosstalk between chromatin, chromosomes, and epigenetics

The International Asilomar Chromatin, Chromosomes, and Epigenetics Conference was held online from 8 to 10 December 2022. Topics of this year's conference included chromosome dysregulation, genome integrity, nuclear organization, regulation of chromatin, epigenetics, transcription, and gene regulation in cell differentiation and disease. The meeting featured four keynote speakers, including Yamini Dalal (National Cancer Institute, USA), Meaghan Jones (University of Manitoba, Canada), Pedro Rocha (National Institute of Child Health and Human Development, USA), and Vincent Pasque (University of Leuven, Belgium). The meeting brought together scientists at all career stages to present and discuss their work in the fields of chromatin and epigenetics.

DNA-guided transcription factor cooperativity shapes face and limb mesenchyme

Transcription factors (TFs) can define distinct cellular identities despite nearly identical DNA-binding specificities. One mechanism for achieving regulatory specificity is DNA-guided TF cooperativity. Although in vitro studies suggest that it may be common, examples of such cooperativity remain scarce in cellular contexts. Here, we demonstrate how "Coordinator," a long DNA motif composed of common motifs bound by many basic helix-loop-helix (bHLH) and homeodomain (HD) TFs, uniquely defines the regulatory regions of embryonic face and limb mesenchyme. Coordinator guides cooperative and selective binding between the bHLH family mesenchymal regulator TWIST1 and a collective of HD factors associated with regional identities in the face and limb. TWIST1 is required for HD binding and open chromatin at Coordinator sites, whereas HD factors stabilize TWIST1 occupancy at Coordinator and titrate it away from HD-independent sites. This cooperativity results in the shared regulation of genes involved in cell-type and positional identities and ultimately shapes facial morphology and evolution.

Haploinsufficient Transcription Factors in Myeloid Neoplasms

Many transcription factors (TFs) function as tumor suppressor genes with heterozygous phenotypes, yet haploinsufficiency generally has an underappreciated role in neoplasia. This is no less true in myeloid cells, which are normally regulated by a delicately balanced and interconnected transcriptional network. Detailed understanding of TF dose in this circuitry sheds light on the leukemic transcriptome. In this review, we discuss the emerging features of haploinsufficient transcription factors (HITFs). We posit that: (a) monoallelic and biallelic losses can have distinct cellular outcomes; (b) the activity of a TF exists in a greater range than the traditional Mendelian genetic doses; and (c) how a TF is deleted or mutated impacts the cellular phenotype. The net effect of a HITF is a myeloid differentiation block and increased intercellular heterogeneity in the course of myeloid neoplasia.

Specifying cellular context of transcription factor regulons for exploring context-specific gene regulation programs

Understanding the role of transcription and transcription factors in cellular identity and disease, such as cancer and autoimmunity, is essential. However, comprehensive data resources for cell line-specific transcription factor-to-target gene annotations are currently limited. To address this, we developed a straightforward method to define regulons that capture the cell-specific aspects of TF binding and transcript expression levels. By integrating cellular transcriptome and transcription factor binding data, we generated regulons for four common cell lines comprising both proximal and distal cell line-specific regulatory events. Through systematic benchmarking involving transcription factor knockout experiments, we demonstrated performance on par with state-of-the-art methods, with our method being easily applicable to other cell types of interest. We present case studies using three cancer single-cell datasets to showcase the utility of these cell-type-specific regulons in exploring transcriptional dysregulation. In summary, this study provides a valuable tool and a resource for systematically exploring cell line-specific transcriptional regulations, emphasizing the utility of network analysis in deciphering disease mechanisms.

Fine-Tuning the Epigenetic Landscape: Chemical Modulation of Epigenome Editors

Epigenome editing has emerged as a powerful technique for targeted manipulation of the chromatin and transcriptional landscape, employing designer DNA binding domains fused with effector domains, known as epi-editors. However, the constitutive expression of dCas9-based epi-editors presents challenges, including off-target activity and lack of temporal resolution. Recent advancements of dCas9-based epi-editors have addressed these limitations by introducing innovative switch systems that enable temporal control of their activity. These systems allow precise modulation of gene expression over time and offer a means to deactivate epi-editors, thereby reducing off-target effects associated with prolonged expression. The development of novel dCas9 effectors regulated by exogenous chemical signals has revolutionized temporal control in epigenome editing, significantly expanding the researcher's toolbox. Here, we provide a comprehensive review of the current state of these cutting-edge systems and specifically discuss their advantages and limitations, offering context to better understand their capabilities.

Dosage amplification dictates oncogenic regulation by the NKX2-1 lineage factor in lung adenocarcinoma

Amplified oncogene expression is a critical and widespread driver event in cancer, yet our understanding of how amplification-mediated elevated dosage mediates oncogenic regulation is limited. Here, we find that the most significant focal amplification event in lung adenocarcinoma (LUAD) targets a lineage super-enhancer near the NKX2-1 lineage transcription factor. The NKX2-1 super-enhancer is targeted by focal and co-amplification with NKX2-1, and activation or repression controls NKX2-1 expression. We find that NKX2-1 is a widespread dependency in LUAD cell lines, where NKX2-1 pioneers enhancer accessibility to drive a lineage addicted state in LUAD, and NKX2-1 confers persistence to EGFR inhibitors. Notably, we find that oncogenic NKX2-1 regulation requires expression above a minimum dosage threshold-NKX2-1 dosage below this threshold is insufficient for cell viability, enhancer remodeling, and TKI persistence. Our data suggest that copy-number amplification can be a gain-of-function alteration, wherein amplification elevates oncogene expression above a critical dosage required for oncogenic regulation and cancer cell survival.

A C/ebpα isoform specific differentiation program in immortalized myelocytes

The transcription factor CCAAT-enhancer binding factor alpha (C/ebpα) is a master controller of myeloid differentiation that is expressed as long (p42) and short (p30) isoform. Mutations within the CEBPA gene selectively deleting p42 are frequent in human acute myeloid leukemia. Here we investigated the individual genomics and transcriptomics of p42 and p30. Both proteins bound to identical sites across the genome. For most targets, they induced a highly similar transcriptional response with the exception of a few isoform specific genes. Amongst those we identified early growth response 1 (Egr1) and tribbles1 (Trib1) as key targets selectively induced by p42 that are also underrepresented in CEBPA-mutated AML. Egr1 executed a program of myeloid differentiation and growth arrest. Oppositely, Trib1 established a negative feedback loop through activation of Erk1/2 kinase thus placing differentiation under control of signaling. Unexpectedly, differentiation elicited either by removal of an oncogenic input or by G-CSF did not peruse C/ebpα as mediator but rather directly affected the cell cycle core by upregulation of p21/p27 inhibitors. This points to functions downstream of C/ebpα as intersection point where transforming and differentiation stimuli converge and this finding offers a new perspective for therapeutic intervention.

Backup transcription factor binding sites protect human genes from mutations in the promoter

This study was designed to test the idea that the regulatory regions of human genes have evolved to be resistant to the effects of mutations in their primary function, the control of gene expression. It is proposed that the transcription factor/transcription factor binding site (TF/TFBS) pair having the greatest effect on control of a gene is the one with the highest abundance among the regulatory elements. Other pairs would have the same effect on gene expression and would predominate in the event of a mutation in the most abundant pair. It is expected that the overall regulatory design proposed here will be highly resistant to mutagenic change that would otherwise affect expression of the gene. The idea was tested beginning with a database of 42 human genes highly specific for expression in brain. For each gene, the five most abundant TF/TFBS pairs were identified and compared in their TFBS occupancy as measured by their ChIP-seq signal. A similar signal was observed and interpreted as evidence that the TF/TFBS pairs can substitute for one another. TF/TFBS pairs were also compared in their ability to substitute for one another in their effect on the level of gene expression. The study of brain specific genes was complemented with the same analysis performed with 31 human liver specific genes. Like the study of brain genes, the liver results supported the view that TF/TFBS pairs in liver specific genes can substitute for one another in the event of mutagenic damage. Finally, the TFBSs in the brain specific and liver specific gene populations were compared with each other with the goal of identifying any brain selective or liver selective TFBSs. Of the 89 TFBSs in the pooled population, 58 were found only in brain specific but not liver specific genes, 8 only in liver specific but not brain specific genes and 23 were found in both brain and liver specific genes. The results were interpreted to emphasize the large number of TFBS in brain specific genes.

Transcript accumulation rates in the early Caenorhabditis elegans embryo

Dynamic transcriptional changes are widespread in rapidly dividing developing embryos when cell fate decisions are made quickly. The Caenorhabditis elegans embryo overcomes these constraints partly through the rapid production of high levels of transcription factor mRNAs. Transcript accumulation rates for some developmental genes are known at single-cell resolution, but genome-scale measurements are lacking. We estimate zygotic mRNA accumulation rates from single-cell RNA sequencing data calibrated with single-molecule transcript imaging. Rapid transcription is common in the early C. elegans embryo with rates highest soon after zygotic transcription begins. High-rate genes are enriched for recently duplicated cell-fate regulators and share common genomic features. We identify core promoter elements associated with high rate and measure their contributions for two early endomesodermal genes, ceh-51 and sdz-31. Individual motifs modestly affect accumulation rates, suggesting multifactorial control. These results are a step toward estimating absolute transcription kinetics and understanding how transcript dosage drives developmental decisions.

A variegated model of transcription factor function in the immune system

Specific combinations of transcription factors (TFs) control the gene expression programs that underlie specialized immune responses. Previous models of TF function in immunocytes had restricted each TF to a single functional categorization [e.g., lineage-defining (LDTFs) vs. signal-dependent TFs (SDTFs)] within one cell type. Synthesizing recent results, we instead propose a variegated model of immunological TF function, whereby many TFs have flexible and different roles across distinct cell states, contributing to cell phenotypic diversity. We discuss evidence in support of this variegated model, describe contextual inputs that enable TF diversification, and look to the future to imagine warranted experimental and computational tools to build quantitative and predictive models of immunocyte gene regulatory networks.

Integrative approaches to study enhancer-promoter communication

The spatiotemporal control of gene expression in complex multicellular organisms relies on noncoding regulatory sequences such as enhancers, which activate transcription of target genes often over large genomic distances. Despite the advances in the identification and characterization of enhancers, the principles and mechanisms by which enhancers select and control their target genes remain largely unknown. Here, we review recent interdisciplinary and quantitative approaches based on emerging techniques that aim to address open questions in the field, notably how regulatory information is encoded in the DNA sequence, how this information is transferred from enhancers to promoters, and how these processes are regulated in time.

DNA-guided transcription factor cooperativity shapes face and limb mesenchyme

Transcription factors (TFs) can define distinct cellular identities despite nearly identical DNA-binding specificities. One mechanism for achieving regulatory specificity is DNA-guided TF cooperativity. Although in vitro studies suggest it may be common, examples of such cooperativity remain scarce in cellular contexts. Here, we demonstrate how 'Coordinator', a long DNA motif comprised of common motifs bound by many basic helix-loop-helix (bHLH) and homeodomain (HD) TFs, uniquely defines regulatory regions of embryonic face and limb mesenchyme. Coordinator guides cooperative and selective binding between the bHLH family mesenchymal regulator TWIST1 and a collective of HD factors associated with regional identities in the face and limb. TWIST1 is required for HD binding and open chromatin at Coordinator sites, while HD factors stabilize TWIST1 occupancy at Coordinator and titrate it away from HD-independent sites. This cooperativity results in shared regulation of genes involved in cell-type and positional identities, and ultimately shapes facial morphology and evolution.