The ubiquitous cellular heterogeneity underlying many organism-level phenotypes raises questions about what factors drive this heterogeneity and how these complex heterogeneous systems evolve. Here, we use single-cell expression data from a Prairie rattlesnake (Crotalus viridis) venom gland to evaluate hypotheses for signaling networks underlying snake venom regulation and the degree to which different venom gene families have evolutionarily recruited distinct regulatory architectures. Our findings suggest that snake venom regulatory systems have evolutionarily co-opted trans-regulatory factors from extracellular signal-regulated kinase and unfolded protein response pathways that specifically coordinate expression of distinct venom toxins in a phased sequence across a single population of secretory cells. This pattern of co-option results in extensive cell-to-cell variation in venom gene expression, even between tandemly duplicated paralogs, suggesting this regulatory architecture has evolved to circumvent cellular constraints. While the exact nature of such constraints remains an open question, we propose that such regulatory heterogeneity may circumvent steric constraints on chromatin, cellular physiological constraints (e.g., endoplasmic reticulum stress or negative protein–protein interactions), or a combination of these. Regardless of the precise nature of these constraints, this example suggests that, in some cases, dynamic cellular constraints may impose previously unappreciated secondary constraints on the evolution of gene regulatory networks that favors heterogeneous expression.more » « less
- NSF-PAR ID:
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Genome Biology and Evolution
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Understanding how regulatory mechanisms evolve is critical for understanding the processes that give rise to novel phenotypes. Snake venom systems represent a valuable and tractable model for testing hypotheses related to the evolution of novel regulatory networks, yet the regulatory mechanisms underlying venom production remain poorly understood. Here, we use functional genomics approaches to investigate venom regulatory architecture in the prairie rattlesnake and identify cis -regulatory sequences (enhancers and promoters), trans -regulatory transcription factors, and integrated signaling cascades involved in the regulation of snake venom genes. We find evidence that two conserved vertebrate pathways, the extracellular signal-regulated kinase and unfolded protein response pathways, were co-opted to regulate snake venom. In one large venom gene family (snake venom serine proteases), this co-option was likely facilitated by the activity of transposable elements. Patterns of snake venom gene enhancer conservation, in some cases spanning 50 million yr of lineage divergence, highlight early origins and subsequent lineage-specific adaptations that have accompanied the evolution of venom regulatory architecture. We also identify features of chromatin structure involved in venom regulation, including topologically associated domains and CTCF loops that underscore the potential importance of novel chromatin structure to coevolve when duplicated genes evolve new regulatory control. Our findings provide a model for understanding how novel regulatory systems may evolve through a combination of genomic processes, including tandem duplication of genes and regulatory sequences, cis -regulatory sequence seeding by transposable elements, and diverse transcriptional regulatory proteins controlled by a co-opted regulatory cascade.more » « less
Gene regulatory networks define regulatory relationships between transcription factors and target genes within a biological system, and reconstructing them is essential for understanding cellular growth and function. Methods for inferring and reconstructing networks from genomics data have evolved rapidly over the last decade in response to advances in sequencing technology and machine learning. The scale of data collection has increased dramatically; the largest genome-wide gene expression datasets have grown from thousands of measurements to millions of single cells, and new technologies are on the horizon to increase to tens of millions of cells and above.
In this work, we present the Inferelator 3.0, which has been significantly updated to integrate data from distinct cell types to learn context-specific regulatory networks and aggregate them into a shared regulatory network, while retaining the functionality of the previous versions. The Inferelator is able to integrate the largest single-cell datasets and learn cell-type-specific gene regulatory networks. Compared to other network inference methods, the Inferelator learns new and informative Saccharomyces cerevisiae networks from single-cell gene expression data, measured by recovery of a known gold standard. We demonstrate its scaling capabilities by learning networks for multiple distinct neuronal and glial cell types in the developing Mus musculus brain at E18 from a large (1.3 million) single-cell gene expression dataset with paired single-cell chromatin accessibility data.
Availability and implementation
The inferelator software is available on GitHub (https://github.com/flatironinstitute/inferelator) under the MIT license and has been released as python packages with associated documentation (https://inferelator.readthedocs.io/).
Supplementary data are available at Bioinformatics online.
null (Ed.)Epithelial-to-mesenchymal transition (EMT) plays an important role in many biological processes during development and cancer. The advent of single-cell transcriptome sequencing techniques allows the dissection of dynamical details underlying EMT with unprecedented resolution. Despite several single-cell data analysis on EMT, how cell communicates and regulates dynamics along the EMT trajectory remains elusive. Using single-cell transcriptomic datasets, here we infer the cell–cell communications and the multilayer gene–gene regulation networks to analyze and visualize the complex cellular crosstalk and the underlying gene regulatory dynamics along EMT. Combining with trajectory analysis, our approach reveals the existence of multiple intermediate cell states (ICSs) with hybrid epithelial and mesenchymal features. Analyses on the time-series datasets from cancer cell lines with different inducing factors show that the induced EMTs are context-specific: the EMT induced by transforming growth factor B1 (TGFB1) is synchronous, whereas the EMTs induced by epidermal growth factor and tumor necrosis factor are asynchronous, and the responses of TGF-β pathway in terms of gene expression regulations are heterogeneous under different treatments or among various cell states. Meanwhile, network topology analysis suggests that the ICSs during EMT serve as the signaling in cellular communication under different conditions. Interestingly, our analysis of a mouse skin squamous cell carcinoma dataset also suggests regardless of the significant discrepancy in concrete genes between in vitro and in vivo EMT systems, the ICSs play dominant role in the TGF-β signaling crosstalk. Overall, our approach reveals the multiscale mechanisms coupling cell–cell communications and gene–gene regulations responsible for complex cell-state transitions.more » « less
INTRODUCTION Neurons are by far the most diverse of all cell types in animals, to the extent that “cell types” in mammalian brains are still mostly heterogeneous groups, and there is no consensus definition of the term. The Drosophila optic lobes, with approximately 200 well-defined cell types, provides a tractable system with which to address the genetic basis of neuronal type diversity. We previously characterized the distinct developmental gene expression program of each of these types using single-cell RNA sequencing (scRNA-seq), with one-to-one correspondence to the known morphological types. RATIONALE The identity of fly neurons is determined by temporal and spatial patterning mechanisms in stem cell progenitors, but it remained unclear how these cell fate decisions are implemented and maintained in postmitotic neurons. It was proposed in Caenorhabditis elegans that unique combinations of terminal selector transcription factors (TFs) that are continuously expressed in each neuron control nearly all of its type-specific gene expression. This model implies that it should be possible to engineer predictable and complete switches of identity between different neurons just by modifying these sustained TFs. We aimed to test this prediction in the Drosophila visual system. RESULTS Here, we used our developmental scRNA-seq atlases to identify the potential terminal selector genes in all optic lobe neurons. We found unique combinations of, on average, 10 differentially expressed and stably maintained (across all stages of development) TFs in each neuron. Through genetic gain- and loss-of-function experiments in postmitotic neurons, we showed that modifications of these selector codes are sufficient to induce predictable switches of identity between various cell types. Combinations of terminal selectors jointly control both developmental (e.g., morphology) and functional (e.g., neurotransmitters and their receptors) features of neurons. The closely related Transmedullary 1 (Tm1), Tm2, Tm4, and Tm6 neurons (see the figure) share a similar code of terminal selectors, but can be distinguished from each other by three TFs that are continuously and specifically expressed in one of these cell types: Drgx in Tm1, Pdm3 in Tm2, and SoxN in Tm6. We showed that the removal of each of these selectors in these cell types reprograms them to the default Tm4 fate. We validated these conversions using both morphological features and molecular markers. In addition, we performed scRNA-seq to show that ectopic expression of pdm3 in Tm4 and Tm6 neurons converts them to neurons with transcriptomes that are nearly indistinguishable from that of wild-type Tm2 neurons. We also show that Drgx expression in Tm1 neurons is regulated by Klumpfuss, a TF expressed in stem cells that instructs this fate in progenitors, establishing a link between the regulatory programs that specify neuronal fates and those that implement them. We identified an intronic enhancer in the Drgx locus whose chromatin is specifically accessible in Tm1 neurons and in which Klu motifs are enriched. Genomic deletion of this region knocked down Drgx expression specifically in Tm1 neurons, leaving it intact in the other cell types that normally express it. We further validated this concept by demonstrating that ectopic expression of Vsx (visual system homeobox) genes in Mi15 neurons not only converts them morphologically to Dm2 neurons, but also leads to the loss of their aminergic identity. Our results suggest that selector combinations can be further sculpted by receptor tyrosine kinase signaling after neurogenesis, providing a potential mechanism for postmitotic plasticity of neuronal fates. Finally, we combined our transcriptomic datasets with previously generated chromatin accessibility datasets to understand the mechanisms that control brain wiring downstream of terminal selectors. We built predictive computational models of gene regulatory networks using the Inferelator framework. Experimental validations of these networks revealed how selectors interact with ecdysone-responsive TFs to activate a large and specific repertoire of cell surface proteins and other effectors in each neuron at the onset of synapse formation. We showed that these network models can be used to identify downstream effectors that mediate specific cellular decisions during circuit formation. For instance, reduced levels of cut expression in Tm2 neurons, because of its negative regulation by pdm3 , controls the synaptic layer targeting of their axons. Knockdown of cut in Tm1 neurons is sufficient to redirect their axons to the Tm2 layer in the lobula neuropil without affecting other morphological features. CONCLUSION Our results support a model in which neuronal type identity is primarily determined by a relatively simple code of continuously expressed terminal selector TFs in each cell type throughout development. Our results provide a unified framework of how specific fates are initiated and maintained in postmitotic neurons and open new avenues to understanding synaptic specificity through gene regulatory networks. The conservation of this regulatory logic in both C. elegans and Drosophila makes it likely that the terminal selector concept will also be useful in understanding and manipulating the neuronal diversity of mammalian brains. Terminal selectors enable predictive cell fate reprogramming. Tm1, Tm2, Tm4, and Tm6 neurons of the Drosophila visual system share a core set of TFs continuously expressed by each cell type (simplified). The default Tm4 fate is overridden by the expression of a single additional terminal selector to generate Tm1 ( Drgx ), Tm2 ( pdm3 ), or Tm6 ( SoxN ) fates.more » « less
Lin, Xiaorong (Ed.)ABSTRACT In filamentous fungi, asexual development involves cellular differentiation and metabolic remodeling leading to the formation of intact asexual spores. The development of asexual spores (conidia) in Aspergillus is precisely coordinated by multiple transcription factors (TFs), including VosA, VelB, and WetA. Notably, these three TFs are essential for the structural and metabolic integrity, i.e., proper maturation, of conidia in the model fungus Aspergillus nidulans . To gain mechanistic insight into the complex regulatory and interdependent roles of these TFs in asexual sporogenesis, we carried out multi-omics studies on the transcriptome, protein-DNA interactions, and primary and secondary metabolism employing A. nidulans conidia. RNA sequencing and chromatin immunoprecipitation sequencing analyses have revealed that the three TFs directly or indirectly regulate the expression of genes associated with heterotrimeric G-protein signal transduction, mitogen-activated protein (MAP) kinases, spore wall formation and structural integrity, asexual development, and primary/secondary metabolism. In addition, metabolomics analyses of wild-type and individual mutant conidia indicate that these three TFs regulate a diverse array of primary metabolites, including those in the tricarboxylic acid (TCA) cycle, certain amino acids, and trehalose, and secondary metabolites such as sterigmatocystin, emericellamide, austinol, and dehydroaustinol. In summary, WetA, VosA, and VelB play interdependent, overlapping, and distinct roles in governing morphological development and primary/secondary metabolic remodeling in Aspergillus conidia, leading to the production of vital conidia suitable for fungal proliferation and dissemination. IMPORTANCE Filamentous fungi produce a vast number of asexual spores that act as efficient propagules. Due to their infectious and/or allergenic nature, fungal spores affect our daily life. Aspergillus species produce asexual spores called conidia; their formation involves morphological development and metabolic changes, and the associated regulatory systems are coordinated by multiple transcription factors (TFs). To understand the underlying global regulatory programs and cellular outcomes associated with conidium formation, genomic and metabolomic analyses were performed in the model fungus Aspergillus nidulans . Our results show that the fungus-specific WetA/VosA/VelB TFs govern the coordination of morphological and chemical developments during sporogenesis. The results of this study provide insights into the interdependent, overlapping, or distinct genetic regulatory networks necessary to produce intact asexual spores. The findings are relevant for other Aspergillus species such as the major human pathogen Aspergillus fumigatus and the aflatoxin producer Aspergillus flavus .more » « less