Temporal and spatial transcriptional programs in murine kidney development

We have performed a systematic temporal and spatial expression profiling of the developing mouse kidney using Compugen long-oligonucleotide microarrays. The activity of 18,000 genes was monitored at 24-h intervals from 10.5-day-postcoitum (dpc) metanephric mesenchyme (MM) through to neonatal kidney, and a cohort of 3,600 dynamically expressed genes was identified. Early metanephric development was further surveyed by directly comparing RNA from 10.5 vs. 11.5 vs. 13.5dpc kidneys. These data showed high concordance with the previously published dynamic profile of rat kidney development (Stuart RO, Bush KT, and Nigam SK. Proc Natl Acad Sci USA 98: 5649-5654, 2001) and our own temporal data. Cluster analyses were used to identify gene ontological terms, functional annotations, and pathways associated with temporal expression profiles. Genetic network analysis was also used to identify biological networks that have maximal transcriptional activity during early metanephric development, highlighting the involvement of proliferation and differentiation. Differential gene expression was validated using whole mount and section in situ hybridization of staged embryonic kidneys. Two spatial profiling experiments were also undertaken. MM (10.5dpc) was compared with adjacent intermediate mesenchyme to further define metanephric commitment. To define the genes involved in branching and in the induction of nephrogenesis, expression profiling was performed on ureteric bud (GFP+) FACS sorted from HoxB7-GFP transgenic mice at 15.5dpc vs. the GFP- mesenchymal derivatives. Comparisons between temporal and spatial data enhanced the ability to predict function for genes and networks. This study provides the most comprehensive temporal and spatial survey of kidney development to date, and the compilation of these transcriptional surveys provides important insights into metanephric development that can now be functionally tested.

Differential use of signal peptides and membrane domains is a common occurrence in the protein output of transcriptional units

Membrane organization describes the orientation of a protein with respect to the membrane and can be determined by the presence, or absence, and organization within the protein sequence of two features: endoplasmic reticulum signal peptides and alpha-helical transmembrane domains. These features allow protein sequences to be classified into one of five membrane organization categories: soluble intracellular proteins, soluble secreted proteins, type I membrane proteins, type II membrane proteins, and multi- spanning membrane proteins. Generation of protein isoforms with variable membrane organizations can change a protein's subcellular localization or association with the membrane. Application of MemO, a membrane organization annotation pipeline, to the FANTOM3 Isoform Protein Sequence mouse protein set revealed that within the 8,032 transcriptional units ( TUs) with multiple protein isoforms, 573 had variation in their use of signal peptides, 1,527 had variation in their use of transmembrane domains, and 615 generated protein isoforms from distinct membrane organization classes. The mechanisms underlying these transcript variations were analyzed. While TUs were identified encoding all pairwise combinations of membrane organization categories, the most common was conversion of membrane proteins to soluble proteins. Observed within our highconfidence set were 156 TUs predicted to generate both extracellular soluble and membrane proteins, and 217 TUs generating both intracellular soluble and membrane proteins. The differential use of endoplasmic reticulum signal peptides and transmembrane domains is a common occurrence within the variable protein output of TUs. The generation of protein isoforms that are targeted to multiple subcellular locations represents a major functional consequence of transcript variation within the mouse transcriptome.

Structure and dynamics of a gene network model incorporating small RNAs

As advances in molecular biology continue to reveal additional layers of complexity in gene regulation, computational models need to incorporate additional features to explore the implications of new theories and hypotheses. It has recently been suggested that eukaryotic organisms owe their phenotypic complexity and diversity to the exploitation of small RNAs as signalling molecules. Previous models of genetic systems are, for several reasons, inadequate to investigate this theory. In this study, we present an artificial genome model of genetic regulatory networks based upon previous work by Torsten Reil, and demonstrate how this model generates networks with biologically plausible structural and dynamic properties. We also extend the model to explore the implications of incorporating regulation by small RNA molecules in a gene network. We demonstrate how, using these signals, highly connected networks can display dynamics that are more stable than expected given their level of connectivity.

Gene network and proteomic analyses of cardiac responses to pathological and physiological stress

Background—The molecular mechanisms underlying similarities and differences between physiological and pathological left ventricular hypertrophy (LVH) are of intense interest. Most previous work involved targeted analysis of individual signaling pathways or screening of transcriptomic profiles. We developed a network biology approach using genomic and proteomic data to study the molecular patterns that distinguish pathological and physiological LVH. Methods and Results—A network-based analysis using graph theory methods was undertaken on 127 genome-wide expression arrays of in vivo murine LVH. This revealed phenotype-specific pathological and physiological gene coexpression networks. Despite >1650 common genes in the 2 networks, network structure is significantly different. This is largely because of rewiring of genes that are differentially coexpressed in the 2 networks; this novel concept of differential wiring was further validated experimentally. Functional analysis of the rewired network revealed several distinct cellular pathways and gene sets. Deeper exploration was undertaken by targeted proteomic analysis of mitochondrial, myofilament, and extracellular subproteomes in pathological LVH. A notable finding was that mRNA–protein correlation was greater at the cellular pathway level than for individual loci. Conclusions—This first combined gene network and proteomic analysis of LVH reveals novel insights into the integrated pathomechanisms that distinguish pathological versus physiological phenotypes. In particular, we identify differential gene wiring as a major distinguishing feature of these phenotypes. This approach provides a platform for the investigation of potentially novel pathways in LVH and offers a freely accessible protocol (http://sites.google.com/site/cardionetworks) for similar analyses in other cardiovascular diseases.

Pichia pastoris regulates its gene-specific response to different carbon sources at the transcriptional, rather than the translational, level

Background: The methylotrophic, Crabtree-negative yeast Pichia pastoris is widely used as a heterologous protein production host. Strong inducible promoters derived from methanol utilization genes or constitutive glycolytic promoters are typically used to drive gene expression. Notably, genes involved in methanol utilization are not only repressed by the presence of glucose, but also by glycerol. This unusual regulatory behavior prompted us to study the regulation of carbon substrate utilization in different bioprocess conditions on a genome wide scale. Results: We performed microarray analysis on the total mRNA population as well as mRNA that had been fractionated according to ribosome occupancy. Translationally quiescent mRNAs were defined as being associated with single ribosomes (monosomes) and highly-translated mRNAs with multiple ribosomes (polysomes). We found that despite their lower growth rates, global translation was most active in methanol-grown P. pastoris cells, followed by excess glycerol- or glucose-grown cells. Transcript-specific translational responses were found to be minimal, while extensive transcriptional regulation was observed for cells grown on different carbon sources. Due to their respiratory metabolism, cells grown in excess glucose or glycerol had very similar expression profiles. Genes subject to glucose repression were mainly involved in the metabolism of alternative carbon sources including the control of glycerol uptake and metabolism. Peroxisomal and methanol utilization genes were confirmed to be subject to carbon substrate repression in excess glucose or glycerol, but were found to be strongly de-repressed in limiting glucose-conditions (as are often applied in fed batch cultivations) in addition to induction by methanol. Conclusions: P. pastoris cells grown in excess glycerol or glucose have similar transcript profiles in contrast to S. cerevisiae cells, in which the transcriptional response to these carbon sources is very different. The main response to different growth conditions in P. pastoris is transcriptional; translational regulation was not transcript-specific. The high proportion of mRNAs associated with polysomes in methanol-grown cells is a major finding of this study; it reveals that high productivity during methanol induction is directly linked to the growth condition and not only to promoter strength.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

The regulatory role of eNOS-derived nitric oxide on transcription in endothelial cells: Impact of S-nitrosylation on β-catenin signaling

Les cellules endothéliales forment une couche semi-perméable entre le sang et les organes. La prolifération, la migration et la polarisation des cellules endothéliales sont essentielles à la formation de nouveaux vaisseaux à partir de vaisseaux préexistants, soit l’angiogenèse. Le facteur de croissance de l’endothélium vasculaire (VEGF) peut activer la synthase endothéliale du monoxyde d’azote (eNOS) et induire la production de monoxyde d’azote (NO) nécessaire pour la régulation de la perméabilité vasculaire et l’angiogenèse. β- caténine est une composante essentielle du complexe des jonctions d’ancrage ainsi qu’un régulateur majeur de la voie de signalisation de Wnt/β-caténine dans laquelle elle se joint au facteur de transcription TCF/LEF et module l’expression de nombreux gènes, dont certains sont impliqués dans l’angiogenèse. La S-nitrosylation (SNO) est un mécanisme de régulation posttraductionnel des protéines par l’ajout d’un groupement nitroso au niveau de résidus cystéines. Le NO produit par eNOS peut induire la S-nitrosylation de la β−caténine au niveau des jonctions intercellulaires et moduler la perméabilité de l’endothélium. Il a d’ailleurs été montré que le NO peut contrôler l’expression génique par la transcription. Le but de cette thèse est d’établir le rôle du NO au sein de la transcription des cellules endothéliales, spécifiquement au niveau de l’activité de β-caténine. Le premier objectif était de déterminer si la SNO de la β-caténine affecte son activité transcriptionnelle. Nous avons montré que le NO inhibe l’activité transcriptionnelle de β- caténine ainsi que la prolifération des cellules endothéliales induites par l’activation de la voie Wnt/β-caténine. Il est intéressant de constater que le VEGF, qui induit la production de NO via eNOS, réprime l’expression de AXIN2 qui est un gène cible de Wnt s’exprimant suite à la i i stimulation par Wnt3a et ce, dépendamment de eNOS. Nous avons identifié que la cystéine 466 de la β-caténine est un résidu essentiel à la modulation répressive de son activité transcriptionnelle par le NO. Lorsqu’il est nitrosylé, ce résidu est responsable de la perturbation du complexe de transcription formé de β-caténine et TCF-4 ce qui inhibe la prolifération des cellules endothéliales induite par la stimulation par Wnt3a. Puisque le NO affecte la transcription, nous avons réalisé l’analyse du transcriptome afin d’obtenir une vue d’ensemble du rôle du NO dans l’activité transcriptionnelle des cellules endothéliales. L’analyse différentielle de l’expression des gènes de cellules endothéliales montre que la répression de eNOS par siRNA augmente l’expression de gènes impliqués au niveau de la polarisation tels que : PARD3A, PARD3B, PKCZ, CRB1 et TJ3. Cette analyse suggère que le NO peut réguler la polarisation des cellules et a permis d’identifier des gènes responsables de l’intégrité des cellules endothéliales et de la réponse immunitaire. De plus, l’analyse de voies de signalisation par KEGG montre que certains gènes modulés par l’ablation de eNOS sont enrichis dans de nombreuses voies de signalisation, notamment Ras et Notch qui sont importantes lors de la migration cellulaire et la différenciation des cellules de têtes et de tronc (tip/stalk). Le regroupement des gènes exprimés chez les cellules traitées au VEGF (déplétées de eNOS ou non) révèle que le NO peut affecter l’expression de gènes contribuant au processus angiogénique, dont l’attraction chimiotactique. Notre étude montre que le NO module la transcription des cellules endothéliales et régule l’expression des gènes impliqués dans l’angiogenèse et la fonction endothéliale.

The RGBarrier assay: the parallel study of gene regulatory element performance at defined chromosomal locations

Vertebrate genomes are organised into a variety of nuclear environments and chromatin states that have profound effects on the regulation of gene transcription. This variation presents a major challenge to the expression of transgenes for experimental research, genetic therapies and the production of biopharmaceuticals. The majority of transgenes succumb to transcriptional silencing by their chromosomal environment when they are randomly integrated into the genome, a phenomenon known as chromosomal position effect (CPE). It is not always feasible to target transgene integration to transcriptionally permissive “safe harbour” loci that favour transgene expression, so there remains an unmet need to identify gene regulatory elements that can be added to transgenes which protect them against CPE. Dominant regulatory elements (DREs) with chromatin barrier (or boundary) activity have been shown to protect transgenes from CPE. The HS4 element from the chicken beta-globin locus and the A2UCOE element from a human housekeeping gene locus have been shown to function as DRE barriers in a wide variety of cell types and species. Despite rapid advances in the profiling of transcription factor binding, chromatin states and chromosomal looping interactions, progress towards functionally validating the many candidate barrier elements in vertebrates has been very slow. This is largely due to the lack of a tractable and efficient assay for chromatin barrier activity. In this study, I have developed the RGBarrier assay system to test the chromatin barrier activity of candidate DREs at pre-defined isogenic loci in human cells. The RGBarrier assay consists in a Flp-based RMCE reaction for the integration of an expression construct, carrying candidate DREs, in a pre-characterised chromosomal location. The RGBarrier system involves the tracking of red, green and blue fluorescent proteins by flow cytometry to monitor on-target versus off-target integration and transgene expression. The analysis of the reporter (GFP) expression for several weeks gives a measure of the protective ability of each candidate elements from chromosomal silencing. This assay can be scaled up to test tens of new putative barrier elements in the same chromosomal context in parallel. The defined chromosomal contexts of the RGBarrier assays will allow for detailed mechanistic studies of chromosomal silencing and DRE barrier element action. Understanding these mechanisms will be of paramount importance for the design of specific solutions for overcoming chromosomal silencing in specific transgenic applications.

The regulatory role of eNOS-derived nitric oxide on transcription in endothelial cells: Impact of S-nitrosylation on β-catenin signaling

Les cellules endothéliales forment une couche semi-perméable entre le sang et les organes. La prolifération, la migration et la polarisation des cellules endothéliales sont essentielles à la formation de nouveaux vaisseaux à partir de vaisseaux préexistants, soit l’angiogenèse. Le facteur de croissance de l’endothélium vasculaire (VEGF) peut activer la synthase endothéliale du monoxyde d’azote (eNOS) et induire la production de monoxyde d’azote (NO) nécessaire pour la régulation de la perméabilité vasculaire et l’angiogenèse. β- caténine est une composante essentielle du complexe des jonctions d’ancrage ainsi qu’un régulateur majeur de la voie de signalisation de Wnt/β-caténine dans laquelle elle se joint au facteur de transcription TCF/LEF et module l’expression de nombreux gènes, dont certains sont impliqués dans l’angiogenèse. La S-nitrosylation (SNO) est un mécanisme de régulation posttraductionnel des protéines par l’ajout d’un groupement nitroso au niveau de résidus cystéines. Le NO produit par eNOS peut induire la S-nitrosylation de la β−caténine au niveau des jonctions intercellulaires et moduler la perméabilité de l’endothélium. Il a d’ailleurs été montré que le NO peut contrôler l’expression génique par la transcription. Le but de cette thèse est d’établir le rôle du NO au sein de la transcription des cellules endothéliales, spécifiquement au niveau de l’activité de β-caténine. Le premier objectif était de déterminer si la SNO de la β-caténine affecte son activité transcriptionnelle. Nous avons montré que le NO inhibe l’activité transcriptionnelle de β- caténine ainsi que la prolifération des cellules endothéliales induites par l’activation de la voie Wnt/β-caténine. Il est intéressant de constater que le VEGF, qui induit la production de NO via eNOS, réprime l’expression de AXIN2 qui est un gène cible de Wnt s’exprimant suite à la i i stimulation par Wnt3a et ce, dépendamment de eNOS. Nous avons identifié que la cystéine 466 de la β-caténine est un résidu essentiel à la modulation répressive de son activité transcriptionnelle par le NO. Lorsqu’il est nitrosylé, ce résidu est responsable de la perturbation du complexe de transcription formé de β-caténine et TCF-4 ce qui inhibe la prolifération des cellules endothéliales induite par la stimulation par Wnt3a. Puisque le NO affecte la transcription, nous avons réalisé l’analyse du transcriptome afin d’obtenir une vue d’ensemble du rôle du NO dans l’activité transcriptionnelle des cellules endothéliales. L’analyse différentielle de l’expression des gènes de cellules endothéliales montre que la répression de eNOS par siRNA augmente l’expression de gènes impliqués au niveau de la polarisation tels que : PARD3A, PARD3B, PKCZ, CRB1 et TJ3. Cette analyse suggère que le NO peut réguler la polarisation des cellules et a permis d’identifier des gènes responsables de l’intégrité des cellules endothéliales et de la réponse immunitaire. De plus, l’analyse de voies de signalisation par KEGG montre que certains gènes modulés par l’ablation de eNOS sont enrichis dans de nombreuses voies de signalisation, notamment Ras et Notch qui sont importantes lors de la migration cellulaire et la différenciation des cellules de têtes et de tronc (tip/stalk). Le regroupement des gènes exprimés chez les cellules traitées au VEGF (déplétées de eNOS ou non) révèle que le NO peut affecter l’expression de gènes contribuant au processus angiogénique, dont l’attraction chimiotactique. Notre étude montre que le NO module la transcription des cellules endothéliales et régule l’expression des gènes impliqués dans l’angiogenèse et la fonction endothéliale.

Conditional mutual inclusive information enables accurate quantification of associations in gene regulatory networks

International audience

Evolution of developmental gene regulatory networks in echinoids

Developmental gene regulatory networks (dGRNs) are assemblages of regulatory genes that direct embryonic development of animal body plans and their morpho-logical structures. dGRNs exhibit recursively-wired circuitry that is encoded in the genome and executed during development. Alteration to the regulatory architecture of dGRNs causes variation in developmental programs both during the development of an individual organism and during the evolution of an individual lineage. The ex-planatory power of these networks is best exemplified by the global dGRN directing early development of the euechinoid sea urchin Strongylocentrotus purpuratus. This network consists of numerous regulatory genes engaging in hundreds of genomic regulatory transactions that collectively direct the delineation of early embryonic domains and the specification of cell lineages. Research on closely-related euechi-noid sea urchins, e.g. Lytechinus variegatus and Paracentrotus lividus, has revealed marked conservation of dGRN architecture in echinoid development, suggesting little appreciable alteration has occurred since their divergence in evolution at least 90 million years ago (mya).

We sought to test whether this observation extends to all sea urchins (echinoids) and undertook a systematic analysis of over 50 regulatory genes in the cidaroid sea urchin Eucidaris tribuloides, surveing their regulatory activity and function in a sea urchin that diverged from euechinoid sea urchins at least 268 mya. Our results revealed extensive alterations have occurred to all levels of echinoid dGRN archi-tecture since the cidaroid-euechinoid divergence. Alterations to mesodermal sub-circuits were particularly striking, including functional di˙erences in specification of non-skeletogenic mesenchyme (NSM), skeletogenic mesenchyme (SM), and en-domesodermal segregation. Specification of endomesodermal embryonic domains revealed that, while their underlying network circuitry had clearly diverged, regu-latory states established in pregastrular embryos of these two groups are strikingly similar. Analyses of E. tribuloides specification leading to the estab-lishment of dorsal-ventral (aboral-oral) larval polarity indicated that regulation of regulatory genes expressed in mesodermal embryonic domains had incurred significantly more alterations than those expressed in endodermal and ectodermal domains. Taken together, this study highlights the ability of dGRN architecture to buffer extensive alterations in the evolution and early development of echinoids and adds further support to the notion that alterations can occur at all levels of dGRN architecture and all stages of embryonic development.

Network analysis and machine learning assist drug repurposing and safety assessment in neurological diseases

In recent decades, two prominent trends have influenced the data modeling field, namely network analysis and machine learning. This thesis explores the practical applications of these techniques within the domain of drug research, unveiling their multifaceted potential for advancing our comprehension of complex biological systems. The research undertaken during this PhD program is situated at the intersection of network theory, computational methods, and drug research. Across six projects presented herein, there is a gradual increase in model complexity. These projects traverse a diverse range of topics, with a specific emphasis on drug repurposing and safety in the context of neurological diseases. The aim of these projects is to leverage existing biomedical knowledge to develop innovative approaches that bolster drug research. The investigations have produced practical solutions, not only providing insights into the intricacies of biological systems, but also allowing the creation of valuable tools for their analysis. In short, the achievements are: • A novel computational algorithm to identify adverse events specific to fixed-dose drug combinations. • A web application that tracks the clinical drug research response to SARS-CoV-2. • A Python package for differential gene expression analysis and the identification of key regulatory "switch genes". • The identification of pivotal events causing drug-induced impulse control disorders linked to specific medications. • An automated pipeline for discovering potential drug repurposing opportunities. • The creation of a comprehensive knowledge graph and development of a graph machine learning model for predictions. Collectively, these projects illustrate diverse applications of data science and network-based methodologies, highlighting the profound impact they can have in supporting drug research activities.

Characterization Of A Protein-protein Interaction Network Of The Cbl-interacting Protein Kinase 8 From Sugarcane.

Plants are sessile organisms and have evolved to tolerate a constantly changing environment. After the onset of different stress conditions, calcineurin B-like (CBL) proteins can sense calcium signals and activate CBL-interacting protein kinase (CIPK) proteins, which can phosphorylate downstream proteins to reestablish plant homeostasis. Previous studies in the bioenergy crop sugarcane showed that the ScCIPK8 gene is induced by drought stress and is also related to sucrose content. Here, we have characterized the protein-protein interactions of ScCIPK8 with six CBL proteins (ScCBL1, ScCBL2, ScCBL3, ScCBL6, ScCBL9, and ScCBL10). Yeast two-hybrid assays showed that ScCIPK8 interacts with ScCBL1, ScCBL3, and ScCBL6. Bimolecular fluorescence complementation assays confirmed in planta the interactions that were observed in yeast cells. These findings give insights on the regulatory networks related to sugar accumulation and drought stress responses in sugarcane.

Essential regulatory elements for NHE3 gene transcription in renal proximal tubule cells

The objectives of the present study were to identify the cis-elements of the promoter absolutely required for the efficient rat NHE3 gene transcription and to locate positive and negative regulatory elements in the 5’-flanking sequence (5’FS), which might modulate the gene expression in proximal tubules, and to compare this result to those reported for intestinal cell lines. We analyzed the promoter activity of different 5’FS segments of the rat NHE3 gene, in the OKP renal proximal tubule cell line by measuring the activity of the reporter gene luciferase. Because the segment spanning the first 157 bp of 5’FS was the most active it was studied in more detail by sequential deletions, point mutations, and gel shift assays. The essential elements for gene transcription are in the region -85 to -33, where we can identify consensual binding sites for Sp1 and EGR-1, which are relevant to NHE3 gene basal transcription. Although a low level of transcription is still possible when the first 25 bp of the 5’FS are used as promoter, efficient transcription only occurs with 44 bp of 5’FS. There are negative regulatory elements in the segments spanning -1196 to -889 and -467 to -152, and positive enhancers between -889 and -479 bp of 5’FS. Transcription factors in the OKP cell nuclear extract efficiently bound to DNA elements of rat NHE3 promoter as demonstrated by gel shift assays, suggesting a high level of similarity between transcription factors of both species, including Sp1 and EGR-1.

Exact time-dependent solutions for a self-regulating gene

The exact time-dependent solution for the stochastic equations governing the behavior of a binary self-regulating gene is presented. Using the generating function technique to rephrase the master equations in terms of partial differential equations, we show that the model is totally integrable and the analytical solutions are the celebrated confluent Heun functions. Self-regulation plays a major role in the control of gene expression, and it is remarkable that such a microscopic model is completely integrable in terms of well-known complex functions.