Non-coding RNAs associated with Prader-Willi syndrome regulate transcription of neurodevelopmental genes in human induced pluripotent stem cells.

Mutations and aberrant gene expression during cellular differentiation lead to neurodevelopmental disorders, such as Prader-Willi syndrome (PWS), which results from the deletion of an imprinted locus on paternally inherited chromosome 15. We analyzed chromatin-associated RNA in human induced pluripotent cells (iPSCs) upon depletion of hybrid small nucleolar long non-coding RNAs (sno-lncRNAs) and 5' snoRNA capped and polyadenylated long non-coding RNAs (SPA-lncRNAs) transcribed from the locus deleted in PWS. We found that rapid ablation of these lncRNAs affects transcription of specific gene classes. Downregulated genes contribute to neurodevelopment and neuronal maintenance, while upregulated genes are predominantly involved in the negative regulation of cellular metabolism and apoptotic processes. Our data reveal the importance of SPA-lncRNAs and sno-lncRNAs in controlling gene expression in iPSCs and provide a platform for synthetic experimental approaches in PWS studies. We conclude that ncRNAs transcribed from the PWS locus are critical regulators of a transcriptional signature, which is important for neuronal differentiation and development.

Genome-wide chromosomal association of Upf1 is linked to Pol II transcription in Schizosaccharomyces pombe.

Although the RNA helicase Upf1 has hitherto been examined mostly in relation to its cytoplasmic role in nonsense mediated mRNA decay (NMD), here we report high-throughput ChIP data indicating genome-wide association of Upf1 with active genes in Schizosaccharomyces pombe. This association is RNase sensitive, correlates with Pol II transcription and mRNA expression levels. Changes in Pol II occupancy were detected in a Upf1 deficient (upf1Δ) strain, prevalently at genes showing a high Upf1 relative to Pol II association in wild-type. Additionally, an increased Ser2 Pol II signal was detected at all highly transcribed genes examined by ChIP-qPCR. Furthermore, upf1Δ cells are hypersensitive to the transcription elongation inhibitor 6-azauracil. A significant proportion of the genes associated with Upf1 in wild-type conditions are also mis-regulated in upf1Δ. These data envisage that by operating on the nascent transcript, Upf1 might influence Pol II phosphorylation and transcription.

Anti-bias training for (sc)RNA-seq: experimental and computational approaches to improve precision.

RNA-seq, including single cell RNA-seq (scRNA-seq), is plagued by insufficient sensitivity and lack of precision. As a result, the full potential of (sc)RNA-seq is limited. Major factors in this respect are the presence of global bias in most datasets, which affects detection and quantitation of RNA in a length-dependent fashion. In particular, scRNA-seq is affected by technical noise and a high rate of dropouts, where the vast majority of original transcripts is not converted into sequencing reads. We discuss these biases origins and implications, bioinformatics approaches to correct for them, and how biases can be exploited to infer characteristics of the sample preparation process, which in turn can be used to improve library preparation.

Experience Recruits MSK1 to Expand the Dynamic Range of Synapses and Enhance Cognition.

Experience powerfully influences neuronal function and cognitive performance, but the cellular and molecular events underlying the experience-dependent enhancement of mental ability have remained elusive. In particular, the mechanisms that couple the external environment to the genomic changes underpinning this improvement are unknown. To address this, we have used male mice harboring an inactivating mutation of mitogen- and stress-activated protein kinase 1 (MSK1), a brain-derived neurotrophic factor (BDNF)-activated enzyme downstream of the mitogen-activated protein kinase (MAPK) pathway. We show that MSK1 is required for the full extent of experience-induced improvement of spatial memory, for the expansion of the dynamic range of synapses, exemplified by the enhancement of hippocampal long-term potentiation (LTP) and long-term depression (LTD), and for the regulation of the majority of genes influenced by enrichment. In addition, and unexpectedly, we show that experience is associated with an MSK1-dependent downregulation of key MAPK and plasticity-related genes, notably of EGR1/Zif268 and Arc/Arg3.1, suggesting the establishment of a novel genomic landscape adapted to experience. By coupling experience to homeostatic changes in gene expression MSK1, represents a prime mechanism through which the external environment has an enduring influence on gene expression, synaptic function, and cognition.SIGNIFICANCE STATEMENT Our everyday experiences strongly influence the structure and function of the brain. Positive experiences encourage the growth and development of the brain and support enhanced learning and memory and resistance to mood disorders such as anxiety. While this has been known for many years, how this occurs is not clear. Here, we show that many of the positive aspects of experience depend on an enzyme called mitogen- and stress-activated protein kinase 1 (MSK1). Using male mice with a mutation in MSK1, we show that MSK1 is necessary for the majority of gene expression changes associated with experience, extending the range over which the communication between neurons occurs, and for both the persistence of memory and the ability to learn new task rules.

Bayesian inference on stochastic gene transcription from flow cytometry data.

Motivation: Transcription in single cells is an inherently stochastic process as mRNA levels vary greatly between cells, even for genetically identical cells under the same experimental and environmental conditions. We present a stochastic two-state switch model for the population of mRNA molecules in single cells where genes stochastically alternate between a more active ON state and a less active OFF state. We prove that the stationary solution of such a model can be written as a mixture of a Poisson and a Poisson-beta probability distribution. This finding facilitates inference for single cell expression data, observed at a single time point, from flow cytometry experiments such as FACS or fluorescence in situ hybridization (FISH) as it allows one to sample directly from the equilibrium distribution of the mRNA population. We hence propose a Bayesian inferential methodology using a pseudo-marginal approach and a recent approximation to integrate over unobserved states associated with measurement error. Results: We provide a general inferential framework which can be widely used to study transcription in single cells from the kind of data arising in flow cytometry experiments. The approach allows us to separate between the intrinsic stochasticity of the molecular dynamics and the measurement noise. The methodology is tested in simulation studies and results are obtained for experimental multiple single cell expression data from FISH flow cytometry experiments. Availability and implementation: All analyses were implemented in R. Source code and the experimental data are available at https://github.com/SimoneTiberi/Bayesian-inference-on-stochastic-gene-transcription-from-flow-cytometry-data. Supplementary information: Supplementary data are available at Bioinformatics online.

The Regulatory T Cell Lineage Factor Foxp3 Regulates Gene Expression through Several Distinct Mechanisms Mostly Independent of Direct DNA Binding.

The lineage factor Foxp3 is essential for the development and maintenance of regulatory T cells, but little is known about the mechanisms involved. Here, we demonstrate that an N-terminal proline-rich interaction region is crucial for Foxp3's function. Subdomains within this key region link Foxp3 to several independent mechanisms of transcriptional regulation. Our study suggests that Foxp3, even in the absence of its DNA-binding forkhead domain, acts as a bridge between DNA-binding interaction partners and proteins with effector function permitting it to regulate a large number of genes. We show that, in one such mechanism, Foxp3 recruits class I histone deacetylases to the promoters of target genes, counteracting activation-induced histone acetylation and thereby suppressing their expression.

Are gene loops the cause of transcriptional noise?

Expression levels of the same mRNA or protein vary significantly among the cells of an otherwise identical population. Such biological noise has great functional implications and is largely due to transcriptional bursting, the episodic production of mRNAs in short, intense bursts, interspersed by periods of transcriptional inactivity. Bursting has been demonstrated in a wide range of pro- and eukaryotic species, attesting to its universal importance. However, the mechanistic origins of bursting remain elusive. A different type of phenomenon, which has also been suggested to be widespread, is the physical interaction between the promoter and 3' end of a gene. Several functional roles have been proposed for such gene loops, including the facilitation of transcriptional reinitiation. Here, I discuss the most recent findings related to these subjects and argue that gene loops are a likely cause of transcriptional bursting and, thus, biological noise.

AID induces intraclonal diversity and genomic damage in CD86(+) chronic lymphocytic leukemia cells.

The activation-induced cytidine deaminase (AID) mediates somatic hypermutation and class switch recombination of the Ig genes by directly deaminating cytosines to uracils. As AID causes a substantial amount of off-target mutations, its activity has been associated with lymphomagenesis and clonal evolution of B-cell malignancies. Although it has been shown that AID is expressed in B-cell chronic lymphocytic leukemia (CLL), a clear analysis of in vivo AID activity in this B-cell malignancy remained elusive. In this study performed on primary human CLL samples, we report that, despite the presence of a dominant VDJ heavy chain region, a substantial intraclonal diversity was observed at VDJ as well as at IgM switch regions (Sµ), showing ongoing AID activity in vivo during disease progression. This AID-mediated heterogeneity was higher in CLL subclones expressing CD86, which we identified as the proliferative CLL fraction. Finally, CD86 expression correlated with shortened time to first treatment and increased γ-H2AX focus formation. Our data demonstrate that AID is active in CLL in vivo and thus, AID likely contributes to clonal evolution of CLL.

N-terminal tagging of RNA Polymerase II shapes transcriptomes more than C-terminal alterations.

RNA polymerase II (Pol II) has a C-terminal domain (CTD) that is unstructured, consisting of a large number of heptad repeats, and whose precise function remains unclear. Here, we investigate how altering the CTD's length and fusing it with protein tags affects transcriptional output on a genome-wide scale in mammalian cells at single-cell resolution. While transcription generally appears to occur in burst-like fashion, where RNA is predominantly made during short bursts of activity that are interspersed with periods of transcriptional silence, the CTD's role in shaping these dynamics seems gene-dependent; global patterns of bursting appear mostly robust to CTD alterations. Introducing protein tags with defined structures to the N terminus cause transcriptome-wide effects, however. We find the type of tag to dominate characteristics of the resulting transcriptomes. This is possibly due to Pol II-interacting factors, including non-coding RNAs, whose expression correlates with the tags. Proteins involved in liquid-liquid phase separation appear prominently.

EpiChIP: gene-by-gene quantification of epigenetic modification levels.

The combination of chromatin immunoprecipitation with next-generation sequencing technology (ChIP-seq) is a powerful and increasingly popular method for mapping protein-DNA interactions in a genome-wide fashion. The conventional way of analyzing this data is to identify sequencing peaks along the chromosomes that are significantly higher than the read background. For histone modifications and other epigenetic marks, it is often preferable to find a characteristic region of enrichment in sequencing reads relative to gene annotations. For instance, many histone modifications are typically enriched around transcription start sites. Calculating the optimal window that describes this enrichment allows one to quantify modification levels for each individual gene. Using data sets for the H3K9/14ac histone modification in Th cells and an accompanying IgG control, we present an analysis strategy that alternates between single gene and global data distribution levels and allows a clear distinction between experimental background and signal. Curve fitting permits false discovery rate-based classification of genes as modified versus unmodified. We have developed a software package called EpiChIP that carries out this type of analysis, including integration with and visualization of gene expression data.

Bayesian inference of polymerase dynamics over the exclusion process.

Transcription is a complex phenomenon that permits the conversion of genetic information into phenotype by means of an enzyme called RNA polymerase, which erratically moves along and scans the DNA template. We perform Bayesian inference over a paradigmatic mechanistic model of non-equilibrium statistical physics, i.e. the asymmetric exclusion processes in the hydrodynamic limit, assuming a Gaussian process prior for the polymerase progression rate as a latent variable. Our framework allows us to infer the speed of polymerases during transcription given their spatial distribution, while avoiding the explicit inversion of the system's dynamics. The results, which show processing rates strongly varying with genomic position and minor role of traffic-like congestion, may have strong implications for the understanding of gene expression.

Synergising single-cell resolution and 4sU labelling boosts inference of transcriptional bursting.

Despite the recent rise of RNA-seq datasets combining single-cell (sc) resolution with 4-thiouridine (4sU) labelling, analytical methods exploiting their power to dissect transcriptional bursting are lacking. Here, we present a mathematical model and Bayesian inference implementation to facilitate genome-wide joint parameter estimation and confidence quantification (R package: burstMCMC). We demonstrate that, unlike conventional scRNA-seq, 4sU scRNA-seq resolves temporal parameters and furthermore boosts inference of dimensionless parameters via a synergy between single-cell resolution and 4sU labelling. We apply our method to published 4sU scRNA-seq data and linked with ChIP-seq data, we uncover previously obscured associations between different parameters and histone modifications.

Ceg1 depletion reveals mechanisms governing degradation of non-capped RNAs in Saccharomyces cerevisiae.

Most functional eukaryotic mRNAs contain a 5' 7-methylguanosine (m7G) cap. Although capping is essential for many biological processes including mRNA processing, export and translation, the fate of uncapped transcripts has not been studied extensively. Here, we employed fast nuclear depletion of the capping enzymes in Saccharomyces cerevisiae to uncover the turnover of the transcripts that failed to be capped. We show that although the degradation of cap-deficient mRNA is dominant, the levels of hundreds of non-capped mRNAs increase upon depletion of the capping enzymes. Overall, the abundance of non-capped mRNAs is inversely correlated to the expression levels, altogether resembling the effects observed in cells lacking the cytoplasmic 5'-3' exonuclease Xrn1 and indicating differential degradation fates of non-capped mRNAs. The inactivation of the nuclear 5'-3' exonuclease Rat1 does not rescue the non-capped mRNA levels indicating that Rat1 is not involved in their degradation and consequently, the lack of the capping does not affect the distribution of RNA Polymerase II on the chromatin. Our data indicate that the cap presence is essential to initiate the Xrn1-dependent degradation of mRNAs underpinning the role of 5' cap in the Xrn1-dependent buffering of the cellular mRNA levels.

Inhibition of suppressive T cell factor 1 (TCF-1) isoforms in naive CD4+ T cells is mediated by IL-4/STAT6 signaling.

The Wnt pathway transcription factor T cell factor 1 (TCF-1) plays essential roles in the control of several developmental processes, including T cell development in the thymus. Although previously regarded as being required only during early T cell development, recent studies demonstrate an important role for TCF-1 in T helper 2 (Th2) cell polarization. TCF-1 was shown to activate expression of the Th2 transcription factor GATA-binding protein 3 (GATA3) and thus to promote the development of IL-4-producing Th2 cells independent of STAT6 signaling. In this study, we show that TCF-1 is down-regulated in human naive CD4(+) T cells cultured under Th2-polarizing conditions. The down-regulation is largely due to the polarizing cytokine IL-4 because IL-4 alone is sufficient to substantially inhibit TCF-1 expression. The IL-4-induced suppression of TCF-1 is mediated by STAT6, as shown by electrophoretic mobility shift assays, chromatin immunoprecipitation, and STAT6 knockdown experiments. Moreover, we found that IL-4/STAT6 predominantly inhibits the shorter, dominant-negative TCF-1 isoforms, which were reported to inhibit IL-4 transcription. Thus, this study provides a model for an IL-4/STAT6-dependent fine tuning mechanism of TCF-1-driven T helper cell polarization.

RNA sequencing reveals two major classes of gene expression levels in metazoan cells.

The expression level of a gene is often used as a proxy for determining whether the protein or RNA product is functional in a cell or tissue. Therefore, it is of fundamental importance to understand the global distribution of gene expression levels, and to be able to interpret it mechanistically and functionally. Here we use RNA sequencing (RNA-seq) of mouse Th2 cells, coupled with a range of other techniques, to show that all genes can be separated, based on their expression abundance, into two distinct groups: one group comprised of lowly expressed and putatively non-functional mRNAs, and the other of highly expressed mRNAs with active chromatin marks at their promoters. These observations are confirmed in many other microarray and RNA-seq data sets of metazoan cell types.

CMTr cap-adjacent 2'-O-ribose mRNA methyltransferases are required for reward learning and mRNA localization to synapses.

Cap-adjacent nucleotides of animal, protist and viral mRNAs can be O-methylated at the 2' position of the ribose (cOMe). The functions of cOMe in animals, however, remain largely unknown. Here we show that the two cap methyltransferases (CMTr1 and CMTr2) of Drosophila can methylate the ribose of the first nucleotide in mRNA. Double-mutant flies lack cOMe but are viable. Consistent with prominent neuronal expression, they have a reward learning defect that can be rescued by conditional expression in mushroom body neurons before training. Among CMTr targets are cell adhesion and signaling molecules. Many are relevant for learning, and are also targets of Fragile X Mental Retardation Protein (FMRP). Like FMRP, cOMe is required for localization of untranslated mRNAs to synapses and enhances binding of the cap binding complex in the nucleus. Hence, our study reveals a mechanism to co-transcriptionally prime mRNAs by cOMe for localized protein synthesis at synapses.

Analysis and simulation of gene expression profiles in pure and mixed cell populations.

For analysis and interpretation of data obtained from experimental readouts of gene expression, such as microarrays and RNA-sequencing, log transformation is routinely applied. This is because expression data, like many biological parameters, are strongly skewed. We show here that gene expression levels in multicellular organisms often deviate from simple (log) normal distributions and instead exhibit shouldered or bimodal distributions. Based on a mathematical model and numerical simulations, we demonstrate that many observed distributions can be explained as mixtures of bimodal two-component lognormal models. This is due to the fact that after log-transformation, the resulting distributions display reductions in the first peak rather than increasing overlaps over a wide range of parameter values. By comparing the theoretical results with biological datasets, our findings suggest that the distributions are generally bimodal for single cell types and get obscured by the different cell types that are present in tissue samples. Our analysis thus provides an initial explanation for the various types of expression level distributions that are found for different datasets. This will be important for the interpretation of next-generation sequencing data such as transcriptomics by mRNA-sequencing and ChIP-sequencing of epigenetic marks.

Timing RNA polymerase pausing with TV-PRO-seq.

Transcription of many genes in metazoans is subject to polymerase pausing, which is the transient stop of transcriptionally engaged polymerases. This is known to mainly occur in promoter-proximal regions but it is not well understood. In particular, a genome-wide measurement of pausing times at high resolution has been lacking. We present here the time-variant precision nuclear run-on and sequencing (TV-PRO-seq) assay, an extension of the standard PRO-seq that allows us to estimate genome-wide pausing times at single-base resolution. Its application to human cells demonstrates that, proximal to promoters, polymerases pause more frequently but for shorter times than in other genomic regions. Comparison with single-cell gene expression data reveals that the polymerase pausing times are longer in highly expressed genes, while transcriptionally noisier genes have higher pausing frequencies and slightly longer pausing times. Analyses of histone modifications suggest that the marker H3K36me3 is related to the polymerase pausing.