Gain of gene regulatory network interconnectivity at the origin of vertebrates

AbstractSignaling pathways control a large number of gene regulatory networks (GRNs) during animal development, acting as major tools for body plan formation1. Remarkably, in contrast to the large number of transcription factors present in animal genomes, only a few of these pathways operate during development2. Moreover, most of them are largely conserved along metazoan evolution3. How evolution has generated a vast diversity of animal morphologies with such a limited number of tools is still largely unknown. Here we show that gain of interconnectivity between signaling pathways, and the GRNs they control, may have played a critical contribution to the origin of vertebrates. We perturbed the retinoic acid, Wnt, FGF and Nodal signaling pathways during gastrulation in amphioxus and zebrafish and comparatively examined its effects in gene expression and cis-regulatory elements (CREs). We found that multiple developmental genes gain response to these pathways through novel CREs in the vertebrate lineage. Moreover, in contrast to amphioxus, many of these CREs are highly interconnected and respond to multiple pathways in zebrafish. Furthermore, we found that vertebrate-specific cell types are more enriched in highly interconnected genes than those tissues with more ancestral origin. Thus, the increase of CREs in vertebrates integrating inputs from different signaling pathways probably contributed to gene expression complexity and the formation of new cell types and morphological novelties in this lineage.

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Synthetic gene-regulatory networks in the opportunistic human pathogenStreptococcus pneumoniae

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1920015117 ◽

2020 ◽

Vol 117 (44) ◽

pp. 27608-27619 ◽

Cited By ~ 1

Author(s):

Robin A. Sorg ◽

Clement Gallay ◽

Laurye Van Maele ◽

Jean-Claude Sirard ◽

Jan-Willem Veening

Keyword(s):

Gene Expression ◽

Virulence Factor ◽

Gene Regulatory Networks ◽

Regulatory Networks ◽

Combinatorial Libraries ◽

Regulatory Elements ◽

Synthetic Gene ◽

Expression Control ◽

Gene Expression Control ◽

Gene Regulatory

Streptococcus pneumoniaecan cause disease in various human tissues and organs, including the ear, the brain, the blood, and the lung, and thus in highly diverse and dynamic environments. It is challenging to study how pneumococci control virulence factor expression, because cues of natural environments and the presence of an immune system are difficult to simulate in vitro. Here, we apply synthetic biology methods to reverse-engineer gene expression control inS. pneumoniae. A selection platform is described that allows for straightforward identification of transcriptional regulatory elements out of combinatorial libraries. We present TetR- and LacI-regulated promoters that show expression ranges of four orders of magnitude. Based on these promoters, regulatory networks of higher complexity are assembled, such as logic AND gates and IMPLY gates. We demonstrate single-copy genome-integrated toggle switches that give rise to bimodal population distributions. The tools described here can be used to mimic complex expression patterns, such as the ones found for pneumococcal virulence factors. Indeed, we were able to rewire gene expression of the capsule operon, the main pneumococcal virulence factor, to be externally inducible (YES gate) or to act as an IMPLY gate (only expressed in absence of inducer). Importantly, we demonstrate that these synthetic gene-regulatory networks are functional in an influenza A virus superinfection murine model of pneumonia, paving the way for in vivo investigations of the importance of gene expression control on the pathogenicity ofS. pneumoniae.

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Mapping gene regulatory networks of primary CD4+T cells using single-cell genomics and genome engineering

10.1101/678060 ◽

2019 ◽

Cited By ~ 1

Author(s):

Rachel E. Gate ◽

Min Cheol Kim ◽

Andrew Lu ◽

David Lee ◽

Eric Shifrut ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

Gene Regulatory Networks ◽

Regulatory Networks ◽

Genome Engineering ◽

Regulatory Elements ◽

Mapping Gene ◽

Gene Regulatory ◽

Novel Interactions

AbstractGene regulatory programs controlling the activation and polarization of CD4+T cells are incompletely mapped and the interindividual variability in these programs remain unknown. We sequenced the transcriptomes of ~160k CD4+T cells from 9 donors following pooled CRISPR perturbation targeting 140 regulators. We identified 134 regulators that affect T cell functionalization, includingIRF2as a positive regulator of Th2polarization. Leveraging correlation patterns between cells, we mapped 194 pairs of interacting regulators, including known (e.g.BATFandJUN) and novel interactions (e.g.ETS1andSTAT6). Finally, we identified 80 natural genetic variants with effects on gene expression, 48 of which are modified by a perturbation. In CD4+T cells, CRISPR perturbations can influencein vitropolarization and modify the effects oftransandcisregulatory elements on gene expression.

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TRAP-based allelic translation efficiency imbalance analysis to identify genetic regulation of ribosome occupancy in specific cell types in vivo

10.1101/2020.08.24.265389 ◽

2020 ◽

Author(s):

Yating Liu ◽

Anthony D. Fischer ◽

Celine L. St. Pierre ◽

Juan F. Macias-Velasco ◽

Heather A. Lawson ◽

...

Keyword(s):

Gene Expression ◽

Genetic Regulation ◽

Transcript Abundance ◽

Cell Types ◽

Regulatory Elements ◽

Model Organisms ◽

Specific Cell ◽

Translation Efficiency ◽

Mrna Levels

AbstractThe alteration of gene expression due to variations in the sequences of transcriptional regulatory elements has been a focus of substantial inquiry in humans and model organisms. However, less is known about the extent to which natural variation contributes to post-transcriptional regulation. Allelic Expression Imbalance (AEI) is a classical approach for studying the association of specific haplotypes with relative changes in transcript abundance. Here, we piloted a new TRAP based approach to associate genetic variation with transcript occupancy on ribosomes in specific cell types, to determine if it will allow examination of Allelic Translation Imbalance (ATI), and Allelic Translation Efficiency Imbalance, using as a test case mouse astrocytes in vivo. We show that most changes of the mRNA levels on ribosomes were reflected in transcript abundance, though ∼1.5% of transcripts have variants that clearly alter loading onto ribosomes orthogonally to transcript levels. These variants were often in conserved residues and altered sequences known to regulate translation such as upstream ORFs, PolyA sites, and predicted miRNA binding sites. Such variants were also common in transcripts showing altered abundance, suggesting some genetic regulation of gene expression may function through post-transcriptional mechanisms. Overall, our work shows that naturally occurring genetic variants can impact ribosome occupancy in astrocytes in vivo and suggests that mechanisms may also play a role in genetic contributions to disease.

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Inference of cell-type specific imprinted regulatory elements and genes during human neuronal differentiation

10.1101/2021.10.04.463060 ◽

2021 ◽

Author(s):

Dan Liang ◽

Nil Aygün ◽

Nana Matoba ◽

Folami Ideraabdullah ◽

Michael I Love ◽

...

Keyword(s):

Gene Expression ◽

Neural Progenitor Cells ◽

Association Studies ◽

Cpg Islands ◽

Uniparental Disomy ◽

Cell Types ◽

Regulatory Elements ◽

Imprinted Genes ◽

Specific Cell ◽

Cell Type

Genomic imprinting results in gene expression biased by parental chromosome of origin and occurs in genes with important roles during human brain development. However, the cell-type and temporal specificity of imprinting during human neurogenesis is generally unknown. By detecting within-donor allelic biases in chromatin accessibility and gene expression that are unrelated to cross-donor genotype, we inferred imprinting in both primary human neural progenitor cells (phNPCs) and their differentiated neuronal progeny from up to 85 donors. We identified 43/20 putatively imprinted regulatory elements (IREs) in neurons/progenitors, and 133/79 putatively imprinted genes in neurons/progenitors. Though 10 IREs and 42 genes were shared between neurons and progenitors, most imprinting was only detected within specific cell types. In addition to well-known imprinted genes and their promoters, we inferred novel IREs and imprinted genes. We found IREs overlapped with CpG islands more than non-imprinted regulatory elements. Consistent with DNA methylation-based regulation of imprinted expression, some putatively imprinted regulatory elements also overlapped with differentially methylated regions on the maternal germline. Finally, we identified a progenitor-specific putatively imprinted gene overlap with copy number variation that is associated with uniparental disomy-like phenotypes. Our results can therefore be useful in interpreting the function of variants identified in future parent-of-origin association studies.

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Functional Inference of Gene Regulation using Single-Cell Multi-Omics

10.1101/2021.07.28.453784 ◽

2021 ◽

Author(s):

Vinay K Kartha ◽

Fabiana M Duarte ◽

Yan Hu ◽

Sai Ma ◽

Jennifer G Chew ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Regulatory Networks ◽

Immunological Response ◽

Cell Types ◽

Regulatory Elements ◽

Chromatin Accessibility ◽

Human Blood Cells ◽

Functional Inference ◽

Omic Data

Cells require coordinated control over gene expression when responding to environmental stimuli. Here, we apply scATAC-seq and scRNA-seq in resting and stimulated human blood cells. Collectively, we generate ~91,000 single-cell profiles, allowing us to probe the cis -regulatory landscape of immunological response across cell types, stimuli and time. Advancing tools to integrate multi-omic data, we develop FigR - a framework to computationally pair scATAC-seq with scRNA-seq cells, connect distal cis -regulatory elements to genes, and infer gene regulatory networks (GRNs) to identify candidate TF regulators. Utilizing these paired multi-omic data, we define Domains of Regulatory Chromatin (DORCs) of immune stimulation and find that cells alter chromatin accessibility prior to production of gene expression at time scales of minutes. Further, the construction of the stimulation GRN elucidates TF activity at disease-associated DORCs. Overall, FigR enables the elucidation of regulatory interactions across single-cell data, providing new opportunities to understand the function of cells within tissues.

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Expression pattern determines regulatory logic

PLoS ONE ◽

10.1371/journal.pone.0244864 ◽

2021 ◽

Vol 16 (1) ◽

pp. e0244864

Author(s):

Carlos Mora-Martinez

Keyword(s):

Gene Expression ◽

Gene Regulatory Networks ◽

Dna Sequences ◽

In Silico ◽

Regulatory Networks ◽

Expression Patterns ◽

Cell Types ◽

Evolutionary Strategy ◽

Specific Gene ◽

Gene Regulatory

Large amounts of effort have been invested in trying to understand how a single genome is able to specify the identity of hundreds of cell types. Inspired by some aspects of Caenorhabditis elegans biology, we implemented an in silico evolutionary strategy to produce gene regulatory networks (GRNs) that drive cell-specific gene expression patterns, mimicking the process of terminal cell differentiation. Dynamics of the gene regulatory networks are governed by a thermodynamic model of gene expression, which uses DNA sequences and transcription factor degenerate position weight matrixes as input. In a version of the model, we included chromatin accessibility. Experimentally, it has been determined that cell-specific and broadly expressed genes are regulated differently. In our in silico evolved GRNs, broadly expressed genes are regulated very redundantly and the architecture of their cis-regulatory modules is different, in accordance to what has been found in C. elegans and also in other systems. Finally, we found differences in topological positions in GRNs between these two classes of genes, which help to explain why broadly expressed genes are so resilient to mutations. Overall, our results offer an explanatory hypothesis on why broadly expressed genes are regulated so redundantly compared to cell-specific genes, which can be extrapolated to phenomena such as ChIP-seq HOT regions.

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Chromatin three-dimensional interactions mediate genetic effects on gene expression

Science ◽

10.1126/science.aat8266 ◽

2019 ◽

Vol 364 (6439) ◽

pp. eaat8266 ◽

Cited By ~ 62

Author(s):

O. Delaneau ◽

M. Zazhytska ◽

C. Borel ◽

G. Giannuzzi ◽

G. Rey ◽

...

Keyword(s):

Gene Expression ◽

Regulatory Networks ◽

Three Dimensional ◽

Cell Types ◽

Regulatory Elements ◽

Genetic Effects ◽

Chromatin Organization ◽

Regulatory Domains ◽

Regulatory Variants ◽

Cis And Trans

Studying the genetic basis of gene expression and chromatin organization is key to characterizing the effect of genetic variability on the function and structure of the human genome. Here we unravel how genetic variation perturbs gene regulation using a dataset combining activity of regulatory elements, gene expression, and genetic variants across 317 individuals and two cell types. We show that variability in regulatory activity is structured at the intra- and interchromosomal levels within 12,583 cis-regulatory domains and 30 trans-regulatory hubs that highly reflect the local (that is, topologically associating domains) and global (that is, open and closed chromatin compartments) nuclear chromatin organization. These structures delimit cell type–specific regulatory networks that control gene expression and coexpression and mediate the genetic effects of cis- and trans-acting regulatory variants on genes.

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An Integrative Developmental Genomics and Systems Biology Approach to Identify an In Vivo Sox Trio-Mediated Gene Regulatory Network in Murine Embryos

BioMed Research International ◽

10.1155/2017/8932583 ◽

2017 ◽

Vol 2017 ◽

pp. 1-16 ◽

Cited By ~ 3

Author(s):

Wenqing Jean Lee ◽

Sumantra Chatterjee ◽

Sook Peng Yap ◽

Siew Lan Lim ◽

Xing Xing ◽

...

Keyword(s):

Systems Biology ◽

Gene Regulatory Network ◽

Regulatory Network ◽

Regulatory Networks ◽

Cell Types ◽

Specific Cell ◽

Morpholino Knockdown ◽

Cell Type Specific ◽

Gene Regulatory

Embryogenesis is an intricate process involving multiple genes and pathways. Some of the key transcription factors controlling specific cell types are the Sox trio, namely, Sox5, Sox6, and Sox9, which play crucial roles in organogenesis working in a concerted manner. Much however still needs to be learned about their combinatorial roles during this process. A developmental genomics and systems biology approach offers to complement the reductionist methodology of current developmental biology and provide a more comprehensive and integrated view of the interrelationships of complex regulatory networks that occur during organogenesis. By combining cell type-specific transcriptome analysis and in vivo ChIP-Seq of the Sox trio using mouse embryos, we provide evidence for the direct control of Sox5 and Sox6 by the transcriptional trio in the murine model and by Morpholino knockdown in zebrafish and demonstrate the novel role of Tgfb2, Fbxl18, and Tle3 in formation of Sox5, Sox6, and Sox9 dependent tissues. Concurrently, a complete embryonic gene regulatory network has been generated, identifying a wide repertoire of genes involved and controlled by the Sox trio in the intricate process of normal embryogenesis.

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Genetic determinants of chromatin accessibility in T cell activation across humans

10.1101/090241 ◽

2016 ◽

Cited By ~ 2

Author(s):

Rachel E. Gate ◽

Christine S. Cheng ◽

Aviva P. Aiden ◽

Atsede Siba ◽

Marcin Tabaka ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

T Cell ◽

T Cell Activation ◽

Genetic Variants ◽

Cell Activation ◽

Cell Types ◽

Regulatory Elements ◽

Specific Cell ◽

Accessible Chromatin

AbstractOver 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) and RNA-seq profiles from activated CD4+ T cells of up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, in patterns consistent with the 3D organization of chromosomes measured by in situ Hi-C in T cells. 15% of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak through disrupting binding sites for transcription factors important for T cell differentiation and activation. These ATAC quantitative trait nucleotides (ATAC-QTNs) have the largest effects on co-accessible peaks, are associated with gene expression from the same aliquot of cells, are rarely affecting core binding motifs, and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis- regulatory elements, in isolation or in concert, to influence gene expression in primary immune cells that play a key role in many human diseases.

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Causal gene regulatory network inference using enhancer activity as a causal anchor

10.1101/311167 ◽

2018 ◽

Author(s):

Deepti Vipin ◽

Lingfei Wang ◽

Guillaume Devailly ◽

Tom Michoel ◽

Anagha Joshi

Keyword(s):

Gene Expression ◽

Regulatory Networks ◽

Cell Types ◽

Expression Data ◽

Cell Type ◽

Causal Gene ◽

High Confidence ◽

Enhancer Activity ◽

Enhancer Rna ◽

Gene Regulatory

AbstractMotivationTranscription control plays a crucial role in establishing a unique gene expression signature for each of the hundreds of mammalian cell types. Though gene expression data has been widely used to infer the cellular regulatory networks, the methods mainly infer correlations rather than causality. We propose that a causal inference framework successfully used for eQTL data can be extended to infer causal regulatory networks using enhancers as causal anchors and enhancer RNA expression as a readout of enhancer activity.ResultsWe developed statistical models and likelihood-ratio tests to infer causal gene regulatory networks using enhancer RNA (eRNA) expression information as a causal anchor and applied the framework to eRNA and transcript expression data from the FANTOM consortium. Predicted causal targets of transcription factors (TFs) in mouse embryonic stem cells, macrophages and erythroblastic leukemia overlapped significantly with experimentally validated targets from ChIP-seq and perturbation data. We further improved the model by taking into account that some TFs might act in a quantitative, dosage-dependent manner, whereas others might act predominantly in a binary on/off fashion. We predicted TF targets from concerted variation of eRNA and TF and target promoter expression levels within a single cell type as well as across multiple cell types. Importantly, TFs with high-confidence predictions were largely different between these two analyses, demonstrating that variability within a cell type is highly relevant for target prediction of cell type specific factors. Finally, we generated a compendium of high-confidence TF targets across diverse human cell and tissue types.AvailabilityMethods have been implemented in the Findr software, available at https://github.com/lingfeiwang/[email protected], [email protected]

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