Periodic epi-organization of the yeast genome revealed by the distribution of promoter sites

Composition of Transcription Machinery and Its Crosstalk with Nucleoid-Associated Proteins and Global Transcription Factors

The coordination of bacterial genomic transcription involves an intricate network of interdependent genes encoding nucleoid-associated proteins (NAPs), DNA topoisomerases, RNA polymerase subunits and modulators of transcription machinery. The central element of this homeostatic regulatory system, integrating the information on cellular physiological state and producing a corresponding transcriptional response, is the multi-subunit RNA polymerase (RNAP) holoenzyme. In this review article, we argue that recent observations revealing DNA topoisomerases and metabolic enzymes associated with RNAP supramolecular complex support the notion of structural coupling between transcription machinery, DNA topology and cellular metabolism as a fundamental device coordinating the spatiotemporal genomic transcription. We analyse the impacts of various combinations of RNAP holoenzymes and global transcriptional regulators such as abundant NAPs, on genomic transcription from this viewpoint, monitoring the spatiotemporal patterns of couplons—overlapping subsets of the regulons of NAPs and RNAP sigma factors. We show that the temporal expression of regulons is by and large, correlated with that of cognate regulatory genes, whereas both the spatial organization and temporal expression of couplons is distinctly impacted by the regulons of NAPs and sigma factors. We propose that the coordination of the growth phase-dependent concentration gradients of global regulators with chromosome configurational dynamics determines the spatiotemporal patterns of genomic expression.

Intrachromosomal colocalization strengthens co-expression, co-modification and evolutionary conservation of neighboring genes

Background

Gene order and location in chromosomes of species are non-random. Neighboring gene pairs tend to display some similarities, such as co-expression and co-modification. However, the contribution of linear proximity, spatial proximity, and evolutionary proximity to these similarities remain unclear, together with whether the presence of several types of proximity can strengthens the similarities.

Results

In this study, we investigated the properties of three kinds of colocalized gene pairs: intrachromosomal colocalized gene pairs, always-neighboring gene pairs, and evolutionary neighboring gene pairs. Our analysis showed that (1) Different types of colocalized genes differentially contribute to co-expression, co-modifications and conservation across species; (2) Intrachromosomal colocalization can strengthen co-expression and co-modification of neighboring gene pairs and their conservation across species; (3) The combination of the three kinds of colocalization can lead to the strongest co-modification and is most strongly conserved across species. (4) Colocalized gene pairs are indicative of phylogenetic relationships and whole genome duplications (WGDs).

Conclusions

These results provide valuable clues for future efforts to understand the characteristics of colocalized gene pairs and how the neighborhood affects their interactions.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4844-1) contains supplementary material, which is available to authorized users.

From multiple pathogenicity islands to a unique organized pathogenicity archipelago

Pathogenicity islands are sets of successive genes in a genome that determine the virulence of a bacterium. In a growing number of studies, bacterial virulence appears to be determined by multiple islands scattered along the genome. This is the case in a family of seven plant pathogens and a human pathogen that, under KdgR regulation, massively secrete enzymes such as pectinases that degrade plant cell wall. Here we show that their multiple pathogenicity islands form together a coherently organized, single “archipelago” at the genome scale. Furthermore, in half of the species, most genes encoding secreted pectinases are expressed from the same DNA strand (transcriptional co-orientation). This genome architecture favors DNA conformations that are conducive to genes spatial co-localization, sometimes complemented by co-orientation. As proteins tend to be synthetized close to their encoding genes in bacteria, we propose that this architecture would favor the efficient funneling of pectinases at convergent points within the cell. The underlying functional hypothesis is that this convergent funneling of the full blend of pectinases constitutes a crucial strategy for successful degradation of the plant cell wall. Altogether, our work provides a new approach to describe and predict, at the genome scale, the full virulence complement.

Analysis tools for the interplay between genome layout and regulation

BACKGROUND

Genome layout and gene regulation appear to be interdependent. Understanding this interdependence is key to exploring the dynamic nature of chromosome conformation and to engineering functional genomes. Evidence for non-random genome layout, defined as the relative positioning of either co-functional or co-regulated genes, stems from two main approaches. Firstly, the analysis of contiguous genome segments across species, has highlighted the conservation of gene arrangement (synteny) along chromosomal regions. Secondly, the study of long-range interactions along a chromosome has emphasised regularities in the positioning of microbial genes that are co-regulated, co-expressed or evolutionarily correlated. While one-dimensional pattern analysis is a mature field, it is often powerless on biological datasets which tend to be incomplete, and partly incorrect. Moreover, there is a lack of comprehensive, user-friendly tools to systematically analyse, visualise, integrate and exploit regularities along genomes.

RESULTS

Here we present the Genome REgulatory and Architecture Tools SCAN (GREAT:SCAN) software for the systematic study of the interplay between genome layout and gene expression regulation.

GREAT

SCAN is a collection of related and interconnected applications currently able to perform systematic analyses of genome regularities as well as to improve transcription factor binding sites (TFBS) and gene regulatory network predictions based on gene positional information.

CONCLUSIONS

We demonstrate the capabilities of these tools by studying on one hand the regular patterns of genome layout in the major regulons of the bacterium Escherichia coli. On the other hand, we demonstrate the capabilities to improve TFBS prediction in microbes. Finally, we highlight, by visualisation of multivariate techniques, the interplay between position and sequence information for effective transcription regulation.

GREAT: a web portal for Genome Regulatory Architecture Tools

GREAT (Genome REgulatory Architecture Tools) is a novel web portal for tools designed to generate user-friendly and biologically useful analysis of genome architecture and regulation. The online tools of GREAT are freely accessible and compatible with essentially any operating system which runs a modern browser. GREAT is based on the analysis of genome layout -defined as the respective positioning of co-functional genes- and its relation with chromosome architecture and gene expression. GREAT tools allow users to systematically detect regular patterns along co-functional genomic features in an automatic way consisting of three individual steps and respective interactive visualizations. In addition to the complete analysis of regularities, GREAT tools enable the use of periodicity and position information for improving the prediction of transcription factor binding sites using a multi-view machine learning approach. The outcome of this integrative approach features a multivariate analysis of the interplay between the location of a gene and its regulatory sequence. GREAT results are plotted in web interactive graphs and are available for download either as individual plots, self-contained interactive pages or as machine readable tables for downstream analysis. The GREAT portal can be reached at the following URL https://absynth.issb.genopole.fr/GREAT and each individual GREAT tool is available for downloading.

Neighboring Genes Show Correlated Evolution in Gene Expression

When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking.

An integrated model of transcription factor diffusion shows the importance of intersegmental transfer and quaternary protein structure for target site finding

We present a computational model of transcription factor motion that explains both the observed rapid target finding of transcription factors, and how this motion influences protein and genome structure. Using the Smoldyn software, we modelled transcription factor motion arising from a combination of unrestricted 3D diffusion in the nucleoplasm, sliding along the DNA filament, and transferring directly between filament sections by intersegmental transfer. This presents a fine-grain picture of the way in which transcription factors find their targets two orders of magnitude faster than 3D diffusion alone allows. Eukaryotic genomes contain sections of nucleosome free regions (NFRs) around the promoters; our model shows that the presence and size of these NFRs can be explained as their acting as antennas on which transcription factors slide to reach their targets. Additionally, our model shows that intersegmental transfer may have shaped the quaternary structure of transcription factors: sequence specific DNA binding proteins are unusually enriched in dimers and tetramers, perhaps because these allow intersegmental transfer, which accelerates target site finding. Finally, our model shows that a ‘hopping’ motion can emerge from 3D diffusion on small scales. This explains the apparently long sliding lengths that have been observed for some DNA binding proteins observed in vitro. Together, these results suggest that transcription factor diffusion dynamics help drive the evolution of protein and genome structure.

PreCisIon: PREdiction of CIS-regulatory elements improved by gene's positION

Conventional approaches to predict transcriptional regulatory interactions usually rely on the definition of a shared motif sequence on the target genes of a transcription factor (TF). These efforts have been frustrated by the limited availability and accuracy of TF binding site motifs, usually represented as position-specific scoring matrices, which may match large numbers of sites and produce an unreliable list of target genes. To improve the prediction of binding sites, we propose to additionally use the unrelated knowledge of the genome layout. Indeed, it has been shown that co-regulated genes tend to be either neighbors or periodically spaced along the whole chromosome. This study demonstrates that respective gene positioning carries significant information. This novel type of information is combined with traditional sequence information by a machine learning algorithm called PreCisIon. To optimize this combination, PreCisIon builds a strong gene target classifier by adaptively combining weak classifiers based on either local binding sequence or global gene position. This strategy generically paves the way to the optimized incorporation of any future advances in gene target prediction based on local sequence, genome layout or on novel criteria. With the current state of the art, PreCisIon consistently improves methods based on sequence information only. This is shown by implementing a cross-validation analysis of the 20 major TFs from two phylogenetically remote model organisms. For Bacillus subtilis and Escherichia coli, respectively, PreCisIon achieves on average an area under the receiver operating characteristic curve of 70 and 60%, a sensitivity of 80 and 70% and a specificity of 60 and 56%. The newly predicted gene targets are demonstrated to be functionally consistent with previously known targets, as assessed by analysis of Gene Ontology enrichment or of the relevant literature and databases.

Chromosome positioning and the clustering of functionally related loci in yeast is driven by chromosomal interactions

In recent years there has been considerable and growing interest in the 3-dimensional organization of genomes. In this manuscript we present an integrated computational-molecular study that produces an ensemble of high-resolution 3-dimensional conformations of the budding yeast genome. The compaction, folding and spatial organization of the chromosomes was based on empirical data determined using proximity-based ligation. Our models incorporate external constraints that allow the separation of gross organizational effects from those due to local interactions. Our models show that yeast chromosomes have preferred yet non-exclusive positions. They also identify interaction dependent clustering of tRNAs, early firing origins of replication, and Gal4 protein binding sites, yet the cluster composition is dynamic. Our results support a link between structure and transcription that occurs within the context of a flexible genome organization.

A dynamical model reveals gene co-localizations in nucleus

Co-localization of networks of genes in the nucleus is thought to play an important role in determining gene expression patterns. Based upon experimental data, we built a dynamical model to test whether pure diffusion could account for the observed co-localization of genes within a defined subnuclear region. A simple standard Brownian motion model in two and three dimensions shows that preferential co-localization is possible for co-regulated genes without any direct interaction, and suggests the occurrence may be due to a limitation in the number of available transcription factors. Experimental data of chromatin movements demonstrates that fractional rather than standard Brownian motion is more appropriate to model gene mobilizations, and we tested our dynamical model against recent static experimental data, using a sub-diffusion process by which the genes tend to colocalize more easily. Moreover, in order to compare our model with recently obtained experimental data, we studied the association level between genes and factors, and presented data supporting the validation of this dynamic model. As further applications of our model, we applied it to test against more biological observations. We found that increasing transcription factor number, rather than factory number and nucleus size, might be the reason for decreasing gene co-localization. In the scenario of frequency- or amplitude-modulation of transcription factors, our model predicted that frequency-modulation may increase the co-localization between its targeted genes.

Periodic pattern detection in sparse boolean sequences

Background

The specific position of functionally related genes along the DNA has been shown to reflect the interplay between chromosome structure and genetic regulation. By investigating the statistical properties of the distances separating such genes, several studies have highlighted various periodic trends. In many cases, however, groups built up from co-functional or co-regulated genes are small and contain wrong information (data contamination) so that the statistics is poorly exploitable. In addition, gene positions are not expected to satisfy a perfectly ordered pattern along the DNA. Within this scope, we present an algorithm that aims to highlight periodic patterns in sparse boolean sequences, i.e. sequences of the type 010011011010... where the ratio of the number of 1's (denoting here the transcription start of a gene) to 0's is small.

Results

The algorithm is particularly robust with respect to strong signal distortions such as the addition of 1's at arbitrary positions (contaminated data), the deletion of existing 1's in the sequence (missing data) and the presence of disorder in the position of the 1's (noise). This robustness property stems from an appropriate exploitation of the remarkable alignment properties of periodic points in solenoidal coordinates.

Conclusions

The efficiency of the algorithm is demonstrated in situations where standard Fourier-based spectral methods are poorly adapted. We also show how the proposed framework allows to identify the 1's that participate in the periodic trends, i.e. how the framework allows to allocate a positional score to genes, in the same spirit of the sequence score. The software is available for public use at http://www.issb.genopole.fr/MEGA/Softwares/iSSB_SolenoidalApplication.zip.

Spatial and topological organization of DNA chains induced by gene co-localization

Transcriptional activity has been shown to relate to the organization of chromosomes in the eukaryotic nucleus and in the bacterial nucleoid. In particular, highly transcribed genes, RNA polymerases and transcription factors gather into discrete spatial foci called transcription factories. However, the mechanisms underlying the formation of these foci and the resulting topological order of the chromosome remain to be elucidated. Here we consider a thermodynamic framework based on a worm-like chain model of chromosomes where sparse designated sites along the DNA are able to interact whenever they are spatially close by. This is motivated by recurrent evidence that there exist physical interactions between genes that operate together. Three important results come out of this simple framework. First, the resulting formation of transcription foci can be viewed as a micro-phase separation of the interacting sites from the rest of the DNA. In this respect, a thermodynamic analysis suggests transcription factors to be appropriate candidates for mediating the physical interactions between genes. Next, numerical simulations of the polymer reveal a rich variety of phases that are associated with different topological orderings, each providing a way to increase the local concentrations of the interacting sites. Finally, the numerical results show that both one-dimensional clustering and periodic location of the binding sites along the DNA, which have been observed in several organisms, make the spatial co-localization of multiple families of genes particularly efficient.

The good operation of cells relies on a coordination between chromosome structure and genetic regulation which is yet to be understood. This can be seen in particular from the transcription machinery: in some eukaryotes and bacteria, transcription of highly active genes occurs within discrete foci called transcription factories, where RNA polymerases, transcription factors and their target genes co-localize. The mechanisms underlying the formation of these foci and the resulting topological structure of the chromosome remain to be elucidated. Here, we propose a thermodynamic framework based on a polymer description of DNA in which genes effectively interact through attractive forces in physical space. The formation of transcription foci then corresponds to a self-organizing process whereby the interacting genes and the non-interacting DNA form two phases that tend to separate. Numerical simulations of the model unveil a rich zoology of the topological ordering of DNA around the foci and show that regularities in the positions of the interacting genes make the spatial co-localization of multiple families of genes particularly efficient. Experimental testing of the predictions of our model should shed new light on the relation between transcriptional regulation and cellular conformations of chromosomes.

The determinants of gene order conservation in yeasts

BACKGROUND

Why do some groups of physically linked genes stay linked over long evolutionary periods? Although several factors are associated with the formation of gene clusters in eukaryotic genomes, the particular contribution of each feature to clustering maintenance remains unclear.

RESULTS

We quantify the strength of the proposed factors in a yeast lineage. First we identify the magnitude of each variable to determine linkage conservation by using several comparator species at different distances to Saccharomyces cerevisiae. For adjacent gene pairs, in line with null simulations, intergenic distance acts as the strongest covariate. Which of the other covariates appear important depends on the comparator, although high co-expression is related to synteny conservation commonly, especially in the more distant comparisons, these being expected to reveal strong but relatively rare selection. We also analyze those pairs that are immediate neighbors through all the lineages considered. Current intergene distance is again the best predictor, followed by the local density of essential genes and co-regulation, with co-expression and recombination rate being the weakest predictors. The genome duplication seen in yeast leaves some mark on linkage conservation, as adjacent pairs resolved as single copy in all post-whole genome duplication species are more often found as adjacent in pre-duplication species.

CONCLUSION

Current intergene distance is consistently the strongest predictor of synteny conservation as expected under a simple null model. Other variables are of lesser importance and their relevance depends both on the species comparison in question and the fate of the duplicates following genome duplication.

Gene and genon concept: coding versus regulation. A conceptual and information-theoretic analysis of genetic storage and expression in the light of modern molecular biology

We analyse here the definition of the gene in order to distinguish, on the basis of modern insight in molecular biology, what the gene is coding for, namely a specific polypeptide, and how its expression is realized and controlled. Before the coding role of the DNA was discovered, a gene was identified with a specific phenotypic trait, from Mendel through Morgan up to Benzer. Subsequently, however, molecular biologists ventured to define a gene at the level of the DNA sequence in terms of coding. As is becoming ever more evident, the relations between information stored at DNA level and functional products are very intricate, and the regulatory aspects are as important and essential as the information coding for products. This approach led, thus, to a conceptual hybrid that confused coding, regulation and functional aspects. In this essay, we develop a definition of the gene that once again starts from the functional aspect. A cellular function can be represented by a polypeptide or an RNA. In the case of the polypeptide, its biochemical identity is determined by the mRNA prior to translation, and that is where we locate the gene. The steps from specific, but possibly separated sequence fragments at DNA level to that final mRNA then can be analysed in terms of regulation. For that purpose, we coin the new term "genon". In that manner, we can clearly separate product and regulative information while keeping the fundamental relation between coding and function without the need to introduce a conceptual hybrid. In mRNA, the program regulating the expression of a gene is superimposed onto and added to the coding sequence in cis - we call it the genon. The complementary external control of a given mRNA by trans-acting factors is incorporated in its transgenon. A consequence of this definition is that, in eukaryotes, the gene is, in most cases, not yet present at DNA level. Rather, it is assembled by RNA processing, including differential splicing, from various pieces, as steered by the genon. It emerges finally as an uninterrupted nucleic acid sequence at mRNA level just prior to translation, in faithful correspondence with the amino acid sequence to be produced as a polypeptide. After translation, the genon has fulfilled its role and expires. The distinction between the protein coding information as materialised in the final polypeptide and the processing information represented by the genon allows us to set up a new information theoretic scheme. The standard sequence information determined by the genetic code expresses the relation between coding sequence and product. Backward analysis asks from which coding region in the DNA a given polypeptide originates. The (more interesting) forward analysis asks in how many polypeptides of how many different types a given DNA segment is expressed. This concerns the control of the expression process for which we have introduced the genon concept. Thus, the information theoretic analysis can capture the complementary aspects of coding and regulation, of gene and genon.

Genomic organization of transcriptomes in mammals: Coregulation and cofunctionality

In studies of their transcriptional activity, genomes have shown a high order of organization. We assessed the question of how genomically neighboring genes are transcriptionally coupled across tissues and what could be the driving force behind their coupling. We focused our analysis on the transcriptome information for 13 tissues of Mus musculus and 79 tissues of Homo sapiens. The analysis of coexpression patterns of genomically adjacent genes across tissues revealed 2619 and 1275 clusters of highly coexpressed genes, respectively. Most of these clusters consist of pairs and triplets of genes. They span a limited genomic length and are phylogenetically conserved between human and mouse. These clusters consist mainly of nonparalogous genes and show a decreased functional and similar regulatory relationship to one another compared to general genomic neighbors. We hypothesize that these clusters trace back to large-scale, qualitative, persistent reorganizations of the transcriptome, while transcription factor regulation is likely to handle fine-tuning of transcription on shorter time scales. Our data point to so far uncharacterized cis-acting units and reject cofunctionality as a driving force.

Growth-rate regulated genes have profound impact on interpretation of transcriptome profiling in Saccharomyces cerevisiae

BACKGROUND

Growth rate is central to the development of cells in all organisms. However, little is known about the impact of changing growth rates. We used continuous cultures to control growth rate and studied the transcriptional program of the model eukaryote Saccharomyces cerevisiae, with generation times varying between 2 and 35 hours.

RESULTS

A total of 5930 transcripts were identified at the different growth rates studied. Consensus clustering of these revealed that half of all yeast genes are affected by the specific growth rate, and that the changes are similar to those found when cells are exposed to different types of stress (>80% overlap). Genes with decreased transcript levels in response to faster growth are largely of unknown function (>50%) whereas genes with increased transcript levels are involved in macromolecular biosynthesis such as those that encode ribosomal proteins. This group also covers most targets of the transcriptional activator RAP1, which is also known to be involved in replication. A positive correlation between the location of replication origins and the location of growth-regulated genes suggests a role for replication in growth rate regulation.

CONCLUSION

Our data show that the cellular growth rate has great influence on transcriptional regulation. This, in turn, implies that one should be cautious when comparing mutants with different growth rates. Our findings also indicate that much of the regulation is coordinated via the chromosomal location of the affected genes, which may be valuable information for the control of heterologous gene expression in metabolic engineering.

Conserved distances between vertebrate highly conserved elements

High numbers of sequence element with very high (>95%) sequence conservation between the human and other vertebrate genomes have been reported and ascribed putative cis-regulatory functions. We have investigated the structural relationships between such elements in mammalian genomes and find that not only their sequences, but also the distances between them are significantly (P<2.2x10(-16)) more conserved than corresponding distances between orthologous protein-coding genes or between exons within these genes. Regions of largely conserved distance between consecutive highly conserved elements (HCE) generally overlap previously identified HCE clusters, but may be far longer (up to 20 Mb) and possibly cover close to 25% of the human genome sequence. Similar conservation of distance is found between bird (chicken) and mammalian genomes and is also discernible in comparisons between fish and mammals. The data suggest either that a substantial amount of essential (functionally active) elements with lower sequence conservation occupy the space between the HCEs or that distance itself is an important factor in transcriptional regulation or chromatin modelling.

Co-expressed Yeast Genes Cluster Over a Long Range but are not Regularly Spaced

Analysis in yeast of the relationship between a gene's genomic position and its expression profile, derived from chip array data, suggests that both closely linked genes and genes spaced at regular intervals show correlated expression profiles. Unfortunately, yeast arrays are often printed in genomic order. The above results may hence reflect little more than known spatial biases within arrays. To circumvent this problem, we analyse spatially unbiased expression data derived from a large Northern blot study. We find that local domains of co-expressed genes range up to 30 genes (100 kb), and are thus much larger than previously considered. There is, by contrast, no evidence for periodicity of co-expression in yeast. We likewise find no convincing evidence for periodicity in the human or mouse genome. Further, analysis of yeast transcription factor binding data sets suggests that there is currently no statistical evidence for chromosomal periodicity of co-regulation.

A haploid-specific transcriptional response to irradiation in Saccharomyces cerevisiae

Eukaryotic cells respond to DNA damage by arresting the cell cycle and modulating gene expression to ensure efficient DNA repair. We used global transcriptome analysis to investigate the role of ploidy and mating-type in inducing the response to damage in various Saccharomyces cerevisiae strains. We observed a response to DNA damage specific to haploid strains that seemed to be controlled by chromatin regulatory proteins. Consistent with these microarray data, we found that mating-type factors controlled the chromatin-dependent silencing of a reporter gene. Both these analyses demonstrate the existence of an irradiation-specific response in strains (haploid or diploid) with only one mating-type factor. This response depends on the activities of Hdf1 and Sir2. Overall, our results suggest the existence of a new regulation pathway dependent on mating-type factors, chromatin structure remodeling, Sir2 and Hdf1 and independent of Mec1 kinase.

L’épigénétique comme aspect de la postgénomique

A cell transmits to its progeny the activity level of many of its genes, not just their sequence. Just like the sequence may vary through a mutation, the gene activity level may change through an "epimutation" (an epigenetic modification) which is heritable and does not entail any concomitant genetic alteration. An epimutation can have important phenotypic consequences, that eventually survive to the loss of the environmental conditions that triggered it. For instance, epimutations are responsible for the divergence between a neuron and an epithelial cell that both come from the same egg and contain the same genome complement. This phenotypic difference is much larger than the one between the neurons from two animal species with dissimilar genotypes, thereby underlining the importance of epimutations. Tradition opposes the genetic and epigenetic visions, the latter being often adequated to the DNA methylation phenomenon. However, epimutations display a rich spectrum of modes that can all fit in a unique reference system based on correlated chemical, spatial and temporal scales. This reference system allows the integration of purely genetic mutations at one of its ends, thus paving the way to a new, gradual vision that encompasses the genome and the epigenome. At the other end can be found two types of epimutations that are both wide-ranging in space and rapid in producing phenotypic alterations. Firstly, long-range rearrangements of the three-dimensional structure of the chromosome may influence gene expression in an heritable fashion. Such rearrangements seem to result from the collective dynamics of DNA-related activities, particularly transcription. Lastly, heritable regulatory states, e.g. a differentiated state that results from tipping a regulatory "toggle switch", involve components that are distributed throughout the nucleus or the cytoplasm, and possibly all the way to cell confines.

Genes encoding subunits of stable complexes are clustered on the yeast chromosomes: an interpretation from a dosage balance perspective

Genomic evidence for colocalization of functionally related genes on eukaryote chromosomes is mounting. Here we show that a statistically significant fraction of yeast genes coding for subunits of stable complexes are located within 10-30 kb of each other. Clustering of genes encoding subunits of complexes may ensure better coregulation and maintain the right stoichiometry of complexes upon duplication of chromosomal segments.

Periodic Transcriptional Organization of the E.coli Genome

The organization of transcription within the prokaryotic nucleoid may be expected to both depend on and determine the structure of the chromosome. Indeed, immunofluorescence localization of transcriptional regulators has revealed foci in actively transcribing Escherichia coli cells. Furthermore, structural and biochemical approaches suggest that there are approximately 50 independent loop domains per genome. Here I show that in four E.coli strains, genes that are controlled by a sequence-specific transcriptional regulator tend to locate next to the gene encoding this regulator, or at regular distances that are multiples of 1/50th of the chromosome length. This periodicity is consistent with a solenoidal epi-organization of the chromosome, which would gather into foci the interacting partners; the regulator molecules and their DNA binding sites. Binding at genuine regulatory sites on DNA would thus be optimized by co-transcriptionally translating regulators in their vicinity.