Nacho Molina

Mammalian Genes Are Transcribed with Widely Different Bursting Kinetics

Real-time monitoring of gene expression reveals transcription kinetics of mammalian genes. In prokaryotes and eukaryotes, most genes appear to be transcribed during short periods called transcriptional bursts, interspersed by silent intervals. We describe how such bursts generate gene-specific temporal patterns of messenger RNA (mRNA) synthesis in mammalian cells. To monitor transcription at high temporal resolution, we established various gene trap cell lines and transgenic cell lines expressing a short-lived luciferase protein from an unstable mRNA, and recorded bioluminescence in real time in single cells. Mathematical modeling identified gene-specific on- and off-switching rates in transcriptional activity and mean numbers of mRNAs produced during the bursts. Transcriptional kinetics were markedly altered by cis-regulatory DNA elements. Our analysis demonstrated that bursting kinetics are highly gene-specific, reflecting refractory periods during which genes stay inactive for a certain time before switching on again.

SwissRegulon: a database of genome-wide annotations of regulatory sites

SwissRegulon () is a database containing genome-wide annotations of regulatory sites in the intergenic regions of genomes. The regulatory site annotations are produced using a number of recently developed algorithms that operate on multiple alignments of orthologous intergenic regions from related genomes in combination with, whenever available, known sites from the literature, and ChIP-on-chip binding data. Currently SwissRegulon contains annotations for yeast and 17 prokaryotic genomes. The database provides information about the sequence, location, orientation, posterior probability and, whenever available, binding factor of each annotated site. To enable easy viewing of the regulatory site annotations in the context of other features annotated on the genomes, the sites are displayed using the GBrowse genome browser interface and can be queried based on any annotated genomic feature. The database can also be queried for regulons, i.e. sites bound by a common factor.

Stimulus-induced modulation of transcriptional bursting in a single mammalian gene

Significance Recent single-cell studies showed that gene transcription in mammals is fundamentally stochastic, occurring in short and intense transcriptional bursts. However, less is known on how transcriptional bursting is modulated upon stimulation. Here, we monitor the transcriptional response of a single allele of the endogenous connective tissue growth factor gene, encoding a secreted protein involved in wound healing and response to shear stress, to two different physiological stimuli in single cells. Analysis using stochastic modeling shows that both stimuli cause acute transcriptional responses characterized by transiently modified gene activities, and increased transcription rates that may last longer depending on the stimulus. These results provide insights on how transcriptional bursting kinetics can be adjusted to increase gene expression upon physiological stimulations. Mammalian genes are often transcribed discontinuously as short bursts of RNA synthesis followed by longer silent periods. However, how these “on” and “off” transitions, together with the burst sizes, are modulated in single cells to increase gene expression upon stimulation is poorly characterized. By combining single-cell time-lapse luminescence imaging with stochastic modeling of the time traces, we quantified the transcriptional responses of the endogenous connective tissue growth factor gene to different physiological stimuli: serum and TGF-β1. Both stimuli caused a rapid and acute increase in burst sizes. Whereas TGF-β1 showed prolonged transcriptional activation mediated by an increase of transcription rate, serum stimulation resulted in a large and temporally tight first transcriptional burst, followed by a refractory period in the range of hours. Our study thus reveals how different physiological stimuli can trigger kinetically distinct transcriptional responses of the same gene.

Scaling laws in functional genome content across prokaryotic clades and lifestyles

For high-level functional categories that are represented in almost all prokaryotic genomes, the numbers of genes in these categories scale as power-laws in the total number of genes. We present a comprehensive analysis of the variation in these scaling laws across prokaryotic clades and lifestyles. For the large majority of functional categories, including transcription regulators, the inferred scaling laws are statistically indistinguishable across clades and lifestyles, supporting the simple hypothesis that these scaling laws are universally shared by all prokaryotes.

MotEvo: integrated Bayesian probabilistic methods for inferring regulatory sites and motifs on multiple alignments of DNA sequences

MOTIVATION Probabilistic approaches for inferring transcription factor binding sites (TFBSs) and regulatory motifs from DNA sequences have been developed for over two decades. Previous work has shown that prediction accuracy can be significantly improved by incorporating features such as the competition of multiple transcription factors (TFs) for binding to nearby sites, the tendency of TFBSs for co-regulated TFs to cluster and form cis-regulatory modules and explicit evolutionary modeling of conservation of TFBSs across orthologous sequences. However, currently available tools only incorporate some of these features, and significant methodological hurdles hampered their synthesis into a single consistent probabilistic framework. RESULTS We present MotEvo, a integrated suite of Bayesian probabilistic methods for the prediction of TFBSs and inference of regulatory motifs from multiple alignments of phylogenetically related DNA sequences, which incorporates all features just mentioned. In addition, MotEvo incorporates a novel model for detecting unknown functional elements that are under evolutionary constraint, and a new robust model for treating gain and loss of TFBSs along a phylogeny. Rigorous benchmarking tests on ChIP-seq datasets show that MotEvos novel features significantly improve the accuracy of TFBS prediction, motif inference and enhancer prediction. AVAILABILITY Source code, a user manual and files with several example applications are available at www.swissregulon.unibas.ch.

Circadian Dbp Transcription Relies on Highly Dynamic BMAL1-CLOCK Interaction with E Boxes and Requires the Proteasome

The transcription factors BMAL1 and CLOCK drive the circadian transcription of clock and clock-controlled genes, such as Dbp. To investigate the kinetics of BMAL1 binding to target genes in real time, we generated a cell line harboring tandem arrays of Dbp repeats and monitored the binding of a fluorescent BMAL1 fusion protein to these arrays by time-lapse microscopy. BMAL1 occupancy at the Dbp locus was highly circadian and strictly dependent on CLOCK. Moreover, BMAL1-CLOCK associations with Dbp were extremely unstable and displayed stochastic, proteasome-dependent fluctuations. Proteasome inhibition prolonged the residence time of BMAL1-CLOCK but resulted in an immediate attenuation of Dbp transcription. In cells harboring a single Dbp-luciferase reporter gene copy, this silencing was shown to be caused by a decrease in both the frequencies and sizes of transcriptional bursts. Thus, BMAL1 and CLOCK may act as Kamikaze activators, in that they are rapidly degraded once bound to Dbp chromatin.

A multiplicity of factors contributes to selective RNA polymerase III occupancy of a subset of RNA polymerase III genes in mouse liver

The genomic loci occupied by RNA polymerase (RNAP) III have been characterized in human culture cells by genome-wide chromatin immunoprecipitations, followed by deep sequencing (ChIP-seq). These studies have shown that only ∼40% of the annotated 622 human tRNA genes and pseudogenes are occupied by RNAP-III, and that these genes are often in open chromatin regions rich in active RNAP-II transcription units. We have used ChIP-seq to characterize RNAP-III-occupied loci in a differentiated tissue, the mouse liver. Our studies define the mouse liver RNAP-III-occupied loci including a conserved mammalian interspersed repeat (MIR) as a potential regulator of an RNAP-III subunit-encoding gene. They reveal that synteny relationships can be established between a number of human and mouse RNAP-III genes, and that the expression levels of these genes are significantly linked. They establish that variations within the A and B promoter boxes, as well as the strength of the terminator sequence, can strongly affect RNAP-III occupancy of tRNA genes. They reveal correlations with various genomic features that explain the observed variation of 81% of tRNA scores. In mouse liver, loci represented in the NCBI37/mm9 genome assembly that are clearly occupied by RNAP-III comprise 50 Rn5s (5S RNA) genes, 14 known non-tRNA RNAP-III genes, nine Rn4.5s (4.5S RNA) genes, and 29 SINEs. Moreover, out of the 433 annotated tRNA genes, half are occupied by RNAP-III. Transfer RNA gene expression levels reflect both an underlying genomic organization conserved in dividing human culture cells and resting mouse liver cells, and the particular promoter and terminator strengths of individual genes.

Origins and consequences of transcriptional discontinuity.

In both prokaryotes and eukaryotes, transcription has been described as being temporally discontinuous, most genes being active mainly during short activity windows interspersed by silent periods. In mammalian cells, recent studies performed at the single cell level have revealed that transcriptional kinetics are highly gene-specific and constrained by the presence of refractory periods of inactivity before a gene can be turned on again. While the underlying mechanisms generating gene-specific kinetic characteristics remain unclear, various biological consequences of transcriptional discontinuity have been unravelled during the past few years. Here we review recent advances on understanding transcriptional kinetics of individual genes at the single cell level and discuss its possible origins and consequences.

Structure of silent transcription intervals and noise characteristics of mammalian genes

Mammalian transcription occurs stochastically in short bursts interspersed by silent intervals showing a refractory period. However, the underlying processes and consequences on fluctuations in gene products are poorly understood. Here, we use single allele time‐lapse recordings in mouse cells to identify minimal models of promoter cycles, which inform on the number and durations of rate‐limiting steps responsible for refractory periods. The structure of promoter cycles is gene specific and independent of genomic location. Typically, five rate‐limiting steps underlie the silent periods of endogenous promoters, while minimal synthetic promoters exhibit only one. Strikingly, endogenous or synthetic promoters with TATA boxes show simplified two‐state promoter cycles. Since transcriptional bursting constrains intrinsic noise depending on the number of promoter steps, this explains why TATA box genes display increased intrinsic noise genome‐wide in mammals, as revealed by single‐cell RNA‐seq. These findings have implications for basic transcription biology and shed light on interpreting single‐cell RNA‐counting experiments.

Circadian clock-dependent and -independent posttranscriptional regulation underlies temporal mRNA accumulation in mouse liver

Significance Rhythms in gene expression propelled by the circadian clock and environmental signals are ubiquitous across cells and tissues. In particular, in mouse tissues, thousands of transcripts show oscillations with a period of 24 hours. Keys question are how such rhythms propagate and eventually exert functions, but also how these are generated. Here, we developed a mathematical model based on total RNA-seq to classify genes according to the respective contributions of transcriptional and posttranscriptional regulation toward mRNA expression profiles. We found that about one-third of rhythmically accumulating mRNA are under posttranscriptional regulation. Such regulation is only partially dependent on the circadian clock, showing that systemic pathways and feeding patterns contribute important posttranscriptional control of gene expression in liver. The mammalian circadian clock coordinates physiology with environmental cycles through the regulation of daily oscillations of gene expression. Thousands of transcripts exhibit rhythmic accumulations across mouse tissues, as determined by the balance of their synthesis and degradation. While diurnally rhythmic transcription regulation is well studied and often thought to be the main factor generating rhythmic mRNA accumulation, the extent of rhythmic posttranscriptional regulation is debated, and the kinetic parameters (e.g., half-lives), as well as the underlying regulators (e.g., mRNA-binding proteins) are relatively unexplored. Here, we developed a quantitative model for cyclic accumulations of pre-mRNA and mRNA from total RNA-seq data, and applied it to mouse liver. This allowed us to identify that about 20% of mRNA rhythms were driven by rhythmic mRNA degradation, and another 15% of mRNAs regulated by both rhythmic transcription and mRNA degradation. The method could also estimate mRNA half-lives and processing times in intact mouse liver. We then showed that, depending on mRNA half-life, rhythmic mRNA degradation can either amplify or tune phases of mRNA rhythms. By comparing mRNA rhythms in wild-type and Bmal1−/− animals, we found that the rhythmic degradation of many transcripts did not depend on a functional BMAL1. Interestingly clock-dependent and -independent degradation rhythms peaked at distinct times of day. We further predicted mRNA-binding proteins (mRBPs) that were implicated in the posttranscriptional regulation of mRNAs, either through stabilizing or destabilizing activities. Together, our results demonstrate how posttranscriptional regulation temporally shapes rhythmic mRNA accumulation in mouse liver.