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.

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.

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.

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.

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.

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.

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.

Systemic and adipocyte transcriptional and metabolic dysregulation in idiopathic intracranial hypertension.

BACKGROUNDIdiopathic intracranial hypertension (IIH) is a condition predominantly affecting obese women of reproductive age. Recent evidence suggests that IIH is a disease of metabolic dysregulation, androgen excess, and an increased risk of cardiovascular morbidity. Here we evaluate systemic and adipose specific metabolic determinants of the IIH phenotype.METHODSIn fasted, matched IIH (n = 97) and control (n = 43) patients, we assessed glucose and insulin homeostasis and leptin levels. Body composition was assessed along with an interrogation of adipose tissue function via nuclear magnetic resonance metabolomics and RNA sequencing in paired omental and subcutaneous biopsies in a case-control study.RESULTSWe demonstrate an insulin- and leptin-resistant phenotype in IIH in excess of that driven by obesity. Adiposity in IIH is preferentially centripetal and is associated with increased disease activity and insulin resistance. IIH adipocytes appear transcriptionally and metabolically primed toward depot-specific lipogenesis.CONCLUSIONThese data show that IIH is a metabolic disorder in which adipose tissue dysfunction is a feature of the disease. Managing IIH as a metabolic disease could reduce disease morbidity and improve cardiovascular outcomes.FUNDINGThis study was supported by the UK NIHR (NIHR-CS-011-028), the UK Medical Research Council (MR/K015184/1), Diabetes UK, Wellcome Trust (104612/Z/14/Z), the Sir Jules Thorn Award, and the Midlands Neuroscience Teaching and Research Fund.

3 '-5 ' crosstalk contributes to transcriptional bursting.

BACKGROUND: Transcription in mammalian cells is a complex stochastic process involving shuttling of polymerase between genes and phase-separated liquid condensates. It occurs in bursts, which results in vastly different numbers of an mRNA species in isogenic cell populations. Several factors contributing to transcriptional bursting have been identified, usually classified as intrinsic, in other words local to single genes, or extrinsic, relating to the macroscopic state of the cell. However, some possible contributors have not been explored yet. Here, we focus on processes at the 3 ' and 5 ' ends of a gene that enable reinitiation of transcription upon termination. RESULTS: Using Bayesian methodology, we measure the transcriptional bursting in inducible transgenes, showing that perturbation of polymerase shuttling typically reduces burst size, increases burst frequency, and thus limits transcriptional noise. Analysis based on paired-end tag sequencing (PolII ChIA-PET) suggests that this effect is genome wide. The observed noise patterns are also reproduced by a generative model that captures major characteristics of the polymerase flux between the ends of a gene and a phase-separated compartment. CONCLUSIONS: Interactions between the 3 ' and 5 ' ends of a gene, which facilitate polymerase recycling, are major contributors to transcriptional noise.

RNA editing contributes to epitranscriptome diversity in chronic lymphocytic leukemia.

RNA editing-primarily conversion of adenosine to inosine (A > I)-is a widespread posttranscriptional mechanism, mediated by Adenosine Deaminases acting on RNA (ADAR) enzymes to alter the RNA sequence of primary transcripts. Hence, in addition to somatic mutations and alternative RNA splicing, RNA editing can be a further source for recoding events. Although RNA editing has been detected in many solid cancers and normal tissue, RNA editing in chronic lymphocytic leukemia (CLL) has not been addressed so far. We determined global RNA editing and recurrent, recoding RNA editing events from matched RNA-sequencing and whole exome sequencing data in CLL samples from 45 untreated patients. RNA editing was verified in a validation cohort of 98 CLL patients and revealed substantially altered RNA editing profiles in CLL compared with normal B cells. We further found that RNA editing patterns were prognostically relevant. Finally, we showed that ADAR knockout decreased steady state viability of MEC1 cells and made them more susceptible to treatment with fludarabine and ibrutinib in vitro. We propose that RNA editing contributes to the pathophysiology of CLL and targeting the RNA editing machinery could be a future strategy to maximize treatment efficacy.

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.

The RNA helicase UPF1 associates with mRNAs co-transcriptionally and is required for the release of mRNAs from gene loci.

UPF1 is an RNA helicase that is required for nonsense-mediated mRNA decay (NMD) in eukaryotes, and the predominant view is that UPF1 mainly operates on the 3'UTRs of mRNAs that are directed for NMD in the cytoplasm. Here we offer evidence, obtained from Drosophila, that UPF1 constantly moves between the nucleus and cytoplasm by a mechanism that requires its RNA helicase activity. UPF1 is associated, genome-wide, with nascent RNAs at most of the active Pol II transcription sites and at some Pol III-transcribed genes, as demonstrated microscopically on the polytene chromosomes of salivary glands and by ChIP-seq analysis in S2 cells. Intron recognition seems to interfere with association and translocation of UPF1 on nascent pre-mRNAs, and cells depleted of UPF1 show defects in the release of mRNAs from transcription sites and their export from the nucleus.

LiBiNorm: an htseq-count analogue with improved normalisation of Smart-seq2 data and library preparation diagnostics.

Protocols for preparing RNA sequencing (RNA-seq) libraries, most prominently "Smart-seq" variations, introduce global biases that can have a significant impact on the quantification of gene expression levels. This global bias can lead to drastic over- or under-representation of RNA in non-linear length-dependent fashion due to enzymatic reactions during cDNA production. It is currently not corrected by any RNA-seq software, which mostly focus on local bias in coverage along RNAs. This paper describes LiBiNorm, a simple command line program that mimics the popular htseq-count software and allows diagnostics, quantification, and global bias removal. LiBiNorm outputs gene expression data that has been normalized to correct for global bias introduced by the Smart-seq2 protocol. In addition, it produces data and several plots that allow insights into the experimental history underlying library preparation. The LiBiNorm package includes an R script that allows visualization of the main results. LiBiNorm is the first software application to correct for the global bias that is introduced by the Smart-seq2 protocol. It is freely downloadable at http://www2.warwick.ac.uk/fac/sci/lifesci/research/libinorm.

Exome sequencing of the TCL1 mouse model for CLL reveals genetic heterogeneity and dynamics during disease development.

The TCL1 mouse model is widely used to study pathophysiology, clonal evolution, and drug sensitivity or resistance of chronic lymphocytic leukemia (CLL). By performing whole exome sequencing, we present the genetic landscape of primary tumors from TCL1 mice and of TCL1 tumors serially transplanted into wild-type recipients to mimic clonal evolution. We show that similar to CLL patients, mutations in mice are frequently subclonal and heterogenous among different primary TCL1 mice. We further describe that this molecular heterogeneity mirrors heterogenous disease characteristics such as organ infiltration or CLL dependent T cell skewing. Similar to human CLL, we further observed the occurrence of novel mutations and structural variations during clonal evolution and found plasticity in the expansion of B cell receptor specific subclones. Thus, our results uncover that the genetic complexity, pathway dependence and clonal dynamics in mouse CLL are in relevant agreement to human CLL, and they are important to consider in future research using the TCL1 mouse for studying CLL.

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.

Nicotinamide Nucleotide Transhydrogenase as a Novel Treatment Target in Adrenocortical Carcinoma.

Adrenocortical carcinoma (ACC) is an aggressive malignancy with poor response to chemotherapy. In this study, we evaluated a potential new treatment target for ACC, focusing on the mitochondrial reduced form of NAD phosphate (NADPH) generator nicotinamide nucleotide transhydrogenase (NNT). NNT has a central role within mitochondrial antioxidant pathways, protecting cells from oxidative stress. Inactivating human NNT mutations result in congenital adrenal insufficiency. We hypothesized that NNT silencing in ACC cells will induce toxic levels of oxidative stress. To explore this, we transiently knocked down NNT in NCI-H295R ACC cells. As predicted, this manipulation increased intracellular levels of oxidative stress; this resulted in a pronounced suppression of cell proliferation and higher apoptotic rates, as well as sensitization of cells to chemically induced oxidative stress. Steroidogenesis was paradoxically stimulated by NNT loss, as demonstrated by mass spectrometry-based steroid profiling. Next, we generated a stable NNT knockdown model in the same cell line to investigate the longer lasting effects of NNT silencing. After long-term culture, cells adapted metabolically to chronic NNT knockdown, restoring their redox balance and resilience to oxidative stress, although their proliferation remained suppressed. This was associated with higher rates of oxygen consumption. The molecular pathways underpinning these responses were explored in detail by RNA sequencing and nontargeted metabolome analysis, revealing major alterations in nucleotide synthesis, protein folding, and polyamine metabolism. This study provides preclinical evidence of the therapeutic merit of antioxidant targeting in ACC as well as illuminating the long-term adaptive response of cells to oxidative stress.

Imprecision and DNA Break Repair Biased towards Incompatible End Joining in Leukemia.

Cancer is a genetic disease caused by mutations and chromosomal abnormalities that contribute to uncontrolled cell growth. In addition, cancer cells can rapidly respond to conventional and targeted therapies by accumulating novel and often specific genetic lesions leading to acquired drug resistance and relapsing disease. In chronic lymphocytic leukemia (CLL), however, diverse chromosomal aberrations often occur. In many cases, improper repair of DNA double-strand breaks (DSB) is a major source for genomic abnormalities. Therefore, this study examined the repair of DNA DSBs by nonhomologous end joining (NHEJ) in CLL by performing plasmid-based repair assays in primary CLL cells and normal B cells, isolated from patients, as well as TALEN/Cas9-induced chromosomal deletions in the CLL cell line Mec1. It is demonstrated that DNA repair is aberrant in CLL cells, featuring perturbed DNA break structure preference with efficient joining of noncohesive ends and more deletions at repair junctions. In addition, increased microhomology-mediated end joining (MMEJ) of DNA substrates was observed in CLL together with increased expression of MMEJ-specific repair factors. In summary, these data identify major differences in DNA repair efficiency between CLL cells and normal B cells isolated from patients.Implications: This study suggests inherently aberrant DNA DSB repair in the acquisition of subclonal genomic structural variations important for clonal evolution and treatment resistance in CLL. Mol Cancer Res; 16(3); 428-38. ©2017 AACR.

AKR1C3-Mediated Adipose Androgen Generation Drives Lipotoxicity in Women With Polycystic Ovary Syndrome.

Context: Polycystic ovary syndrome (PCOS) is a prevalent metabolic disorder occurring in up to 10% of women of reproductive age. PCOS is associated with insulin resistance and cardiovascular risk. Androgen excess is a defining feature of PCOS and has been suggested as causally associated with insulin resistance; however, mechanistic evidence linking both is lacking. We hypothesized that adipose tissue is an important site linking androgen activation and metabolic dysfunction in PCOS. Methods: We performed a human deep metabolic in vivo phenotyping study examining the systemic and intra-adipose effects of acute and chronic androgen exposure in 10 PCOS women, in comparison with 10 body mass index-matched healthy controls, complemented by in vitro experiments. Results: PCOS women had increased intra-adipose concentrations of testosterone (P = 0.0006) and dihydrotestosterone (P = 0.01), with increased expression of the androgen-activating enzyme aldo-ketoreductase type 1 C3 (AKR1C3) (P = 0.04) in subcutaneous adipose tissue. Adipose glycerol levels in subcutaneous adipose tissue microdialysate supported in vivo suppression of lipolysis after acute androgen exposure in PCOS (P = 0.04). Mirroring this, nontargeted serum metabolomics revealed prolipogenic effects of androgens in PCOS women only. In vitro studies showed that insulin increased adipose AKR1C3 expression and activity, whereas androgen exposure increased adipocyte de novo lipid synthesis. Pharmacologic AKR1C3 inhibition in vitro decreased de novo lipogenesis. Conclusions: These findings define an intra-adipose mechanism of androgen activation that contributes to adipose remodeling and a systemic lipotoxic metabolome, with intra-adipose androgens driving lipid accumulation and insulin resistance in PCOS. AKR1C3 represents a promising therapeutic target in PCOS.