Transcriptomic and epigenomic dynamics associated with development of human iPSC-derived GABAergic interneurons

Abstract GABAergic interneurons (GINs) are a heterogeneous population of inhibitory neurons that collectively contribute to the maintenance of normal neuronal excitability and network activity. Identification of the genetic regulatory elements and transcription factors that contribute toward GIN function may provide new insight into the pathways underlying proper GIN activity while also indicating potential therapeutic targets for GIN-associated disorders, such as schizophrenia and epilepsy. In this study, we examined the temporal changes in gene expression and chromatin accessibility during GIN development by performing transcriptomic and epigenomic analyses on human induced pluripotent stem cell-derived neurons at 22, 50 and 78 days (D) post-differentiation. We observed 13 221 differentially accessible regions (DARs) of chromatin that associate with temporal changes in gene expression at D78 and D50, relative to D22. We also classified families of transcription factors that are increasingly enriched at DARs during differentiation, indicating regulatory networks that likely drive GIN development. Collectively, these data provide a resource for examining the molecular networks regulating GIN functionality.

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Rewiring of the Transcription Factor Network in Acute Myeloid Leukemia

Cancer Informatics ◽

10.1177/1176935119859863 ◽

2019 ◽

Vol 18 ◽

pp. 117693511985986 ◽

Cited By ~ 1

Author(s):

Salam A Assi ◽

Constanze Bonifer ◽

Peter N Cockerill

Keyword(s):

Gene Expression ◽

Acute Myeloid Leukemia ◽

Transcription Factors ◽

Myeloid Leukemia ◽

Regulatory Networks ◽

Regulatory Elements ◽

Genes Encoding ◽

Myeloid Development ◽

Mitogen Activated Protein ◽

Acute Myeloid

Acute myeloid leukemia (AML) is a highly heterogeneous cancer associated with different patterns of gene expression determined by the nature of their DNA mutations. These mutations mostly act to deregulate gene expression by various mechanisms at the level of the nucleus. By performing genome-wide epigenetic profiling of cis-regulatory elements, we found that AML encompasses different mutation-specific subclasses associated with the rewiring of the gene regulatory networks that drive differentiation into different directions away from normal myeloid development. By integrating epigenetic profiles with gene expression and chromatin conformation data, we defined pathways within gene regulation networks that were differentially rewired within each mutation-specific subclass of AML. This analysis revealed 2 major classes of AML: one class defined by mutations in signaling molecules that activate AP-1 via the mitogen-activated protein (MAP) kinase pathway and a second class defined by mutations within genes encoding transcription factors such as RUNX1/CBFβ and C/EBPα. By identifying specific DNA motifs protected from DNase I digestion at cis-regulatory elements, we were able to infer candidate transcription factors bound to these motifs. These integrated analyses allowed the identification of AML subtype-specific core regulatory networks that are required for AML development and maintenance, which could now be targeted in personalized therapies.

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Endocannabinoid system in the neurodevelopment of GABAergic interneurons: implications for neurological and psychiatric disorders

Reviews in the Neurosciences ◽

10.1515/revneuro-2020-0134 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Chang-geng Song ◽

Xin Kang ◽

Fang Yang ◽

Wan-qing Du ◽

Jia-jia Zhang ◽

...

Keyword(s):

Psychiatric Disorders ◽

Endocannabinoid System ◽

Autism Spectrum ◽

Network Activity ◽

Inhibitory Neurons ◽

Gabaergic Interneurons ◽

Neural Stem Progenitor Cells ◽

The Central Nervous System ◽

Interneuron Development

Abstract In mature mammalian brains, the endocannabinoid system (ECS) plays an important role in the regulation of synaptic plasticity and the functioning of neural networks. Besides, the ECS also contributes to the neurodevelopment of the central nervous system. Due to the increase in the medical and recreational use of cannabis, it is inevitable and essential to elaborate the roles of the ECS on neurodevelopment. GABAergic interneurons represent a group of inhibitory neurons that are vital in controlling neural network activity. However, the role of the ECS in the neurodevelopment of GABAergic interneurons remains to be fully elucidated. In this review, we provide a brief introduction of the ECS and interneuron diversity. We focus on the process of interneuron development and the role of ECS in the modulation of interneuron development, from the expansion of the neural stem/progenitor cells to the migration, specification and maturation of interneurons. We further discuss the potential implications of the ECS and interneurons in the pathogenesis of neurological and psychiatric disorders, including epilepsy, schizophrenia, major depressive disorder and autism spectrum disorder.

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Tailoring Cardiac Synthetic Transcriptional Modulation Towards Precision Medicine

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.783072 ◽

2022 ◽

Vol 8 ◽

Author(s):

Eric Schoger ◽

Sara Lelek ◽

Daniela Panáková ◽

Laura Cecilia Zelarayán

Keyword(s):

Gene Expression ◽

Precision Medicine ◽

Single Cell ◽

Regulatory Networks ◽

Transcriptional Control ◽

Regulatory Elements ◽

Comprehensive Overview ◽

Endogenous Gene ◽

Cell Technologies ◽

Organ Systems

Molecular and genetic differences between individual cells within tissues underlie cellular heterogeneities defining organ physiology and function in homeostasis as well as in disease states. Transcriptional control of endogenous gene expression has been intensively studied for decades. Thanks to a fast-developing field of single cell genomics, we are facing an unprecedented leap in information available pertaining organ biology offering a comprehensive overview. The single-cell technologies that arose aided in resolving the precise cellular composition of many organ systems in the past years. Importantly, when applied to diseased tissues, the novel approaches have been immensely improving our understanding of the underlying pathophysiology of common human diseases. With this information, precise prediction of regulatory elements controlling gene expression upon perturbations in a given cell type or a specific context will be realistic. Simultaneously, the technological advances in CRISPR-mediated regulation of gene transcription as well as their application in the context of epigenome modulation, have opened up novel avenues for targeted therapy and personalized medicine. Here, we discuss the fast-paced advancements during the recent years and the applications thereof in the context of cardiac biology and common cardiac disease. The combination of single cell technologies and the deep knowledge of fundamental biology of the diseased heart together with the CRISPR-mediated modulation of gene regulatory networks will be instrumental in tailoring the right strategies for personalized and precision medicine in the near future. In this review, we provide a brief overview of how single cell transcriptomics has advanced our knowledge and paved the way for emerging CRISPR/Cas9-technologies in clinical applications in cardiac biomedicine.

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Synthetic gene regulatory networks in the opportunistic human pathogen Streptococcus pneumoniae

10.1101/834689 ◽

2019 ◽

Cited By ~ 1

Author(s):

Robin A. Sorg ◽

Clement Gallay ◽

Jan-Willem Veening

Keyword(s):

Gene Expression ◽

Streptococcus Pneumoniae ◽

Regulatory Networks ◽

Expression Patterns ◽

Combinatorial Libraries ◽

Regulatory Elements ◽

Expression Control ◽

Gene Expression Control

AbstractStreptococcus pneumoniae can 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 in S. 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 and IMPLY gates. Finally, 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, paving the way for in vivo investigations of the importance of gene expression control on the pathogenicity of S. pneumoniae.

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Identifying genetic modulators of the connectivity between transcription factors and their transcriptional targets

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1517140113 ◽

2016 ◽

Vol 113 (13) ◽

pp. E1835-E1843 ◽

Cited By ~ 8

Author(s):

Mina Fazlollahi ◽

Ivor Muroff ◽

Eunjee Lee ◽

Helen C. Causton ◽

Harmen J. Bussemaker

Keyword(s):

Gene Expression ◽

Transcription Factors ◽

Gene Regulatory Networks ◽

Regulatory Networks ◽

Target Genes ◽

Regulation Of Gene Expression ◽

Nonsynonymous Mutation ◽

Gene Regulatory ◽

Genetic Modulators

Regulation of gene expression by transcription factors (TFs) is highly dependent on genetic background and interactions with cofactors. Identifying specific context factors is a major challenge that requires new approaches. Here we show that exploiting natural variation is a potent strategy for probing functional interactions within gene regulatory networks. We developed an algorithm to identify genetic polymorphisms that modulate the regulatory connectivity between specific transcription factors and their target genes in vivo. As a proof of principle, we mapped connectivity quantitative trait loci (cQTLs) using parallel genotype and gene expression data for segregants from a cross between two strains of the yeast Saccharomyces cerevisiae. We identified a nonsynonymous mutation in the DIG2 gene as a cQTL for the transcription factor Ste12p and confirmed this prediction empirically. We also identified three polymorphisms in TAF13 as putative modulators of regulation by Gcn4p. Our method has potential for revealing how genetic differences among individuals influence gene regulatory networks in any organism for which gene expression and genotype data are available along with information on binding preferences for transcription factors.

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Hierarchical Transcriptional Control of the LuxR Quorum-Sensing Regulon of Vibrio harveyi

Journal of Bacteriology ◽

10.1128/jb.00047-20 ◽

2020 ◽

Vol 202 (14) ◽

Author(s):

Ryan R. Chaparian ◽

Alyssa S. Ball ◽

Julia C. van Kessel

Keyword(s):

Gene Expression ◽

Transcription Factors ◽

Quorum Sensing ◽

Cell Density ◽

Regulatory Networks ◽

Vibrio Harveyi ◽

Sugar Transport ◽

Content Type ◽

Second Tier

ABSTRACT In vibrios, quorum sensing controls hundreds of genes that are required for cell density-specific behaviors including bioluminescence, biofilm formation, competence, secretion, and swarming motility. The central transcription factor in the quorum-sensing pathway is LuxR/HapR, which directly regulates ∼100 genes in the >400-gene regulon of Vibrio harveyi. Among these directly controlled genes are 15 transcription factors, which we predicted would comprise the second tier in the hierarchy of the LuxR regulon. We confirmed that LuxR binds to the promoters of these genes in vitro and quantified the extent of LuxR activation or repression of transcript levels. Transcriptome sequencing (RNA-seq) indicates that most of these transcriptional regulators control only a few genes, with the exception of MetJ, which is a global regulator. The genes regulated by these transcription factors are predicted to be involved in methionine and thiamine biosynthesis, membrane stability, RNA processing, c-di-GMP degradation, sugar transport, and other cellular processes. These data support a hierarchical model in which LuxR directly regulates 15 transcription factors that drive the second level of the gene expression cascade to influence cell density-dependent metabolic states and behaviors in V. harveyi. IMPORTANCE Quorum sensing is important for survival of bacteria in nature and influences the actions of bacterial groups. In the relatively few studied examples of quorum-sensing-controlled genes, these genes are associated with competition or cooperation in complex microbial communities and/or virulence in a host. However, quorum sensing in vibrios controls the expression of hundreds of genes, and their functions are mostly unknown or uncharacterized. In this study, we identify the regulators of the second tier of gene expression in the quorum-sensing system of the aquaculture pathogen Vibrio harveyi. Our identification of regulatory networks and metabolic pathways controlled by quorum sensing can be extended and compared to other Vibrio species to understand the physiology, ecology, and pathogenesis of these organisms.

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What functional genomics has taught us about transcriptional regulation in malaria parasites

Briefings in Functional Genomics ◽

10.1093/bfgp/elz004 ◽

2019 ◽

Vol 18 (5) ◽

pp. 290-301 ◽

Cited By ~ 3

Author(s):

Christa G Toenhake ◽

Richárd Bártfai

Keyword(s):

Gene Expression ◽

Transcription Factors ◽

Life Cycle ◽

Functional Genomics ◽

Expression Patterns ◽

Regulatory Elements ◽

Complex Life Cycle ◽

Malaria Parasites ◽

Gene Regulatory

Abstract Malaria parasites are characterized by a complex life cycle that is accompanied by dynamic gene expression patterns. The factors and mechanisms that regulate gene expression in these parasites have been searched for even before the advent of next generation sequencing technologies. Functional genomics approaches have substantially boosted this area of research and have yielded significant insights into the interplay between epigenetic, transcriptional and post-transcriptional mechanisms. Recently, considerable progress has been made in identifying sequence-specific transcription factors and DNA-encoded regulatory elements. Here, we review the insights obtained from these efforts including the characterization of core promoters, the involvement of sequence-specific transcription factors in life cycle progression and the mapping of gene regulatory elements. Furthermore, we discuss recent developments in the field of functional genomics and how they might contribute to further characterization of this complex gene regulatory network.

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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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MODELING NONLINEAR GENE REGULATORY NETWORKS FROM TIME SERIES GENE EXPRESSION DATA

Journal of Bioinformatics and Computational Biology ◽

10.1142/s0219720008003746 ◽

2008 ◽

Vol 06 (05) ◽

pp. 961-979 ◽

Cited By ~ 15

Author(s):

ANDRÉ FUJITA ◽

JOÃO RICARDO SATO ◽

HUMBERTO MIGUEL GARAY-MALPARTIDA ◽

MARI CLEIDE SOGAYAR ◽

CARLOS EDUARDO FERREIRA ◽

...

Keyword(s):

Gene Expression ◽

Time Series ◽

Gene Regulatory Networks ◽

Regulatory Networks ◽

Expression Profiles ◽

A Priori ◽

Molecular Networks ◽

Biological Knowledge ◽

Vector Autoregressive ◽

Gene Regulatory

In cells, molecular networks such as gene regulatory networks are the basis of biological complexity. Therefore, gene regulatory networks have become the core of research in systems biology. Understanding the processes underlying the several extracellular regulators, signal transduction, protein–protein interactions, and differential gene expression processes requires detailed molecular description of the protein and gene networks involved. To understand better these complex molecular networks and to infer new regulatory associations, we propose a statistical method based on vector autoregressive models and Granger causality to estimate nonlinear gene regulatory networks from time series microarray data. Most of the models available in the literature assume linearity in the inference of gene connections; moreover, these models do not infer directionality in these connections. Thus, a priori biological knowledge is required. However, in pathological cases, no a priori biological information is available. To overcome these problems, we present the nonlinear vector autoregressive (NVAR) model. We have applied the NVAR model to estimate nonlinear gene regulatory networks based entirely on gene expression profiles obtained from DNA microarray experiments. We show the results obtained by NVAR through several simulations and by the construction of three actual gene regulatory networks (p53, NF-κB, and c-Myc) for HeLa cells.

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Identifying Transcription Regulatory Elements in the Human and Mouse Genomes Using Tissue-specific Gene Expression Profiles

Journal of Integrative Bioinformatics ◽

10.1515/jib-2007-59 ◽

2007 ◽

Vol 4 (2) ◽

pp. 1-23

Author(s):

Amitava Karmaker ◽

Kihoon Yoon ◽

Mark Doderer ◽

Russell Kruzelock ◽

Stephen Kwek

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Transcription Factors ◽

Binding Sites ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Regulatory Elements ◽

Specific Gene ◽

Tissue Specific Gene ◽

Human And Mouse

Summary Revealing the complex interaction between trans- and cis-regulatory elements and identifying these potential binding sites are fundamental problems in understanding gene expression. The progresses in ChIP-chip technology facilitate identifying DNA sequences that are recognized by a specific transcription factor. However, protein-DNA binding is a necessary, but not sufficient, condition for transcription regulation. We need to demonstrate that their gene expression levels are correlated to further confirm regulatory relationship. Here, instead of using a linear correlation coefficient, we used a non-linear function that seems to better capture possible regulatory relationships. By analyzing tissue-specific gene expression profiles of human and mouse, we delineate a list of pairs of transcription factor and gene with highly correlated expression levels, which may have regulatory relationships. Using two closely-related species (human and mouse), we perform comparative genome analysis to cross-validate the quality of our prediction. Our findings are confirmed by matching publicly available TFBS databases (like TRANFAC and ConSite) and by reviewing biological literature. For example, according to our analysis, 80% and 85.71% of the targets genes associated with E2F5 and RELB transcription factors have the corresponding known binding sites. We also substantiated our results on some oncogenes with the biomedical literature. Moreover, we performed further analysis on them and found that BCR and DEK may be regulated by some common transcription factors. Similar results for BTG1, FCGR2B and LCK genes were also reported.

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